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Archive for the ‘Molecular Genetics & Pharmaceutical’ Category

The structure of our visual and auditory system

Larry H. Bernstein, MD, FCAP, Curator

Leaders in Pharmaceutical Intelligence

Series E. 2; 5.8

Revised 9/30/2015

Torsten N. Wiesel (1921— )
President Emeritus
Vincent and Brooke Astor Professor Emeritus – Rockefeller Univerity
1981 Nobel Prize in Physiology or Medicine

Torsten N. Wiesel

The structure of our visual system, beginning at the eyes and ending at the primary visual cortex at the back of the brain, is a little like a maze, intricately constructed to send visual signals through myriad portals and passageways to reach just the right neurons at the end of the path. In the 1950s, H. Keffer Hartline, a member of The Rockefeller Institute for Medical Research, charted the first avenues of that maze when he revealed how the visual stimulus received by the retina is divided, altered and sharpened by the optic nerve network in order to send a more useful picture to the brain. Former Rockefeller president Torsten N. Wiesel, along with his colleague David H. Hubel, continued Dr. Hartline’s exploration at their Harvard Medical School laboratory by delving further back, into the brain, and described for the first time how the system develops innately, how experience shapes it further and how it analyzes visual signals. For this work, Drs. Wiesel and Hubel shared the 1981 Nobel Prize in Physiology or Medicine.

The complex array of stimuli in our visual field passes first through several distinct layers of cells known collectively as the retina. Next they are analyzed by the optic nerve and make their way to the lateral geniculate nucleus (LGN), the first visual processing center in the brain, located in the thalamus of each brain hemisphere. From the LGN, the signals are sent to the primary visual cortex, also known as the striate cortex. Working with cats and rhesus macaque monkeys, Drs. Wiesel and Hubel recorded the electrical impulses of cortical cells in response to various patterns flashed before the eyes. They coined the terms “simple” and “complex” for cells that respond to only one type of stimulus and those that respond to multiple and opposite stimuli.

To understand the differentiation, the scientists conducted a series of experiments to observe the brain’s response when one eye is kept closed for different periods of time. They discovered that animals with one eye closed for the first three months of life become blind in that eye. Examinations revealed no change in the eye itself or in the retina; the LGN cells devoted to that eye had shrunken but still responded to stimulation of the deprived eye as efficiently as those for the normal eye. The difference, they concluded, must therefore be in the striate cortex.

Awards: Nobel Prize in Physiology or Medicine, Louisa Gross Horwitz Prize, National Medal of Science for Biological Sciences

Swedish-born American neurobiologist Torsten N. Wiesel was raised at Beckomberga Hospital, the mental institute where his father was chief psychiatrist. He described himself as a lazy student until his late teens, before embarking on a career of research into the physiology of vision. Wiesel was awarded the Nobel Prize for Medicine in 1981, along with his long-time collaborator David H. Hubel, for mapping the visual or striate cortex, the posterior section of the cerebral cortex. Roger W. Sperry shared that year’s Nobel honors, for work conducted at CalTech. Wiesel also demonstrated the importance of early diagnosis of childhood visual problems.

When a reporter informed him he had won the Nobel Prize, Wiesel’s first response was, “Oh, no, I was afraid of that”, explaining that he feared the hubbub might prove a distraction from his work. In the 1990s he was President of Rockefeller University, and since 2000, he has been Secretary-General of the Human Frontier Science Program, a group which supports collaboration across different scientific fields. He also served more than a decade as Chair of the Human Rights Committee for the National Academy of Sciences.

In 2001, he was named to a high-level post at the National Institutes of Health, but his nomination was scuttled by then-Secretary of Health and Human Services Tommy Thompson, with the official explanation that he had “signed too many full-page letters in the New York Times critical of President Bush.” Wiesel responded, “I have not signed a statement against Bush, but nonetheless for some reason I am on the administration’s blacklist. Perhaps [it is because of] my human rights activities and being contrary in general.”

Structure and evolution of hearing

9.2015 The Scientist

Inner Ear Cartography

Scientists map the position of cells within the organ of Corti.  by Ruth Williams

Age-related hearing loss caused by damage to the sensory hair cells within the cochlea is extremely common, but studying the inner ear is tough. “It’s in the densest bone in the body, so you don’t have access,” says John Brigande of Oregon Health and Science University in Portland. Even if you can extract cells, he says, “there are so darn few of them.” Despite these technical difficulties, researchers have gleaned gene-expression information about different cell types within the organ of Corti—home to the sensory cells within the cochlea. But “it’s not only important to know what a cell expresses,” says Robert Durruthy-Durruthy, a postdoc in the Stanford University lab of Stefan Heller. “It’s also important to know where it can be found within a tissue.” To this end, Durruthy-Durruthy, Heller, and postdoc Jörg Waldhaus have derived a 2-D map of organ of Corti cells from neonatal mice. First, the team sorted all cell types across the medial-to-lateral axis (or width) of the organ based on marker gene expression. The approximately 900 sorted cells, representing nine cell types, were then each quantitatively analyzed for the expression of 192 selected genes. Computational analysis of these expression data then enabled reconstruction of the cells’ positions along the organ’s apical-to-basal (length) and medial-to-lateral axes. In principle, the technique, which harnesses gene-expression information to determine cells’ spatial organization, could be applied to generate 2-D maps of any complex tissue, says Durruthy-Durruthy. Within the mammalian cochlea, apical cells retain regenerative capacity for a few weeks after birth, but basal cells do not. “Spatial mapping allows us to get at the differences [between these cells],” says Brigande, and that could ultimately highlight possible ways to reinstate regeneration in the adult ear. (Cell Reports, 11:1385-99, 2015) To build a map of cells within the organ of Corti—where sound is translated to neural activity— scientists divide the cochlea in two. Each half of the organ of Corti is then broken up into its constituent cells, which comprise nine cell types (represented by the nine colors) spanning the organ’s medial-to-lateral axis.

FROM CELLS TO GENE-EXPRESSION: Each cell is analyzed for the expression of 192 selected genes. Based on the pattern of expression, a cell is given a position within the organ of Corti along both the basal-apical and the medial-lateral axes. Each column represents one of the nine cell types.

Human Hearing: A Primer

Semicircular canals of the vestibular system OSSICLES Ear canal Tympanic membrane (eardrum) When sound enters the ear canal, it vibrates the tympanic membrane, or eardrum. These vibrations are passed through the inner ear via three small bones called ossicles: the malleus, the incus, and the stapes. Finally, vibrations of the stapes stimulate the movement of a fluid called perilymph within the bony labyrinth of the inner ear.

Cochlea – How the human ear translates sound waves into nervous impulses.

Perilymph fills the both the vestibular and tympanic ducts of the cochlea. Between these two channels lies the cochlear duct, which is home to the organ of Corti. There, the soundinduced movement of perilymph in the cochlea is translated to an electrical signal that is sent to the brain for processing.

The organ of Corti sits on the basilar membrane, which separates the cochlear duct from the tympanic duct. As the basilar membrane vibrates in response to fluid movement, it pushes the organ along the tectorial membrane, which shifts laterally over the hair cells. This shift bends projections at the tips of the cells, called stereocilia, resulting in the generation of electrical signals.

The bending of the stereocilia results in the depolarization of the inner hair cell and initiates a nerve impulse through the spinal ganglion neuron at the base of the cell. A series of outer hair cells serves to mechanically amplify the vibrations that trigger the inner hair cells to fire. High-frequency sounds stimulate hair cells at the base of the cochlea, while low-frequency sounds stimulate hair cells at the apex.

Aural History -The form and function of the ears of modern land vertebrates cannot be understood without knowing how they evolved.

by Geoffrey A. Manley

Unlike eyes, which are generally instantly recognizable, ears differ greatly in their appearance throughout the animal kingdom. Some hearing structures may not be visible at all. For example, camouflaged in the barn owl’s facial ruff—a rim of short, brown feathers surrounding the bird’s white face—are clusters of stiff feathers that act as external ears on either side of its head. These feather structures funnel sound collected by two concave facial disks to the ear canal openings, increasing the bird’s hearing sensitivity by 20 decibels—approximately the difference between normal conversation and shouting.

Similar increases in sensitivity result from the large and often mobile external structures, or pinnae, of many mammals, such as cats and bats. Internally, the differences among hearing organs are even more dramatic.

Although fish can hear, only amphibians and true land vertebrates—including the aquatic species that descended from them, such as whales and pinnipeds—have dedicated hearing organs. In land vertebrates belonging to the group Amniota, including lizards, birds, and mammals, sound usually enters through an external canal and impinges on an eardrum that is connected through middle-ear bones to the inner ear. There, hundreds or thousands of sensory hair cells are spread along an elongated membrane that acts as a spectral analyzer, with the result that each local group of hair cells responds best to a certain range of pitches, or sound frequencies. The hair cells then feed this information into afferent nerve fibers that carry the information to the brain. (See “Hearing Primer” on page 34.)

Together, these hair cells and nerve fibers encode a wide range of sounds that enter the ear on that side of the head. Two ears complete the picture, allowing animals’ brains to localize the source of the sounds they hear by comparing the two inputs. Although it seems obvious that the ability to process nearby sounds would be enormously useful, modern amniote ears in fact arose quite late in evolutionary history, and to a large extent independently in different lineages. As a result, external, middle, and inner ears of various amniotes are characteristically different.1

Moreover, the early evolution of these dedicated auditoryorgans in land vertebrates led to the loss of the heavy otolithic membrane that overlies the hair-cell bundles of vestibular organs and is responsible for their slow responses. What remains is the watery macromolecular gel known as the tectorial membrane, which assures that local groups of hair cells move synchronously, resulting in greater sensitivity.

Good high-frequency hearing did not exist from the start, however. For a period of at least 50 million years after amniotes arose, the three main lineages were most likely quite hard of hearing. They had not yet evolved any mechanism for absorbing sound energy from air; they lacked the middle ear and eardrum that are vital for the function of modern hearing organs. As such, ancestral amniotes most likely perceived only sounds of relatively low frequency and high amplitude that reached the inner ear via the limbs or, if the skull were rested on the ground, through the tissues of the head. It is unclear what kind of stimuli could have existed that would have led to the retention of such hearing organs for such a long time.

The magnificent middle ear

During the Triassic period, some 250 to 200 million years ago, a truly remarkable thing happened. Independently, but within just 20 million to 30 million years of one another, all three amniote lineages evolved a tympanic middle ear from parts of the skull and the jaws.2 The tympanic middle ear is the assemblage of tiny bones that connects at one end to an eardrum and at the other end to the oval window, an aperture in the bone of the inner ear. Despite the temporal coincidence in the evolution of these structures in the three amniote lineages and the functional similarities of the adaptations, the groups were by this time so far separated that the middle ears evolved from different structures into two different configurations. The single middle-ear bone, the columella, of archosaurs and lepidosaurs derived from the hyomandibular, a bone that earlier had formed a large strut connecting the braincase to the outer skull.

Research on hearing organs have revealed the remarkable history of this unexpected diversity of ears. Divergence from a common origin Amniote vertebrates comprise three lineages of extant groups that diverged roughly 300 million years ago: the lepidosaurs, which include lizards and snakes; the archosaurs, which include crocodilians and birds; and mammals, which include egg-laying, pouched, and placental mammals. By comparing the skulls of the extinct common ancestors of these three lineages, as well as the ears of the most basal modern amniotes, researchers have concluded that ancestral amniotes had a small (perhaps less than 1 millimeter in length) but dedicated hearing organ: a sensory epithelium called a basilar papilla, with perhaps a few hundred sensory hair cells supported by a thin basilar membrane that is freely suspended in fluid. These rudimentary structures evolved from the hair cells of vestibular organs, which help organisms maintain their balance by responding to physical input, such as head rotation or gravity. Initially, the hearing organ only responded to low-frequency sounds. On their apical surface, all hair cells have tight tufts or bundles of large, hairlike villi known as stereovilli (or, more commonly stereocilia, even though they are not true cilia), which give hair cells their name. Between these stereovilli are proteinaceous links, most of which are closely coupled to sensory transduction channels that respond to a tilting of the stereovilli bundles caused by sound waves.

The amniote hearing organ evolved as a separate group of hair cells that lay between two existing vestibular epithelia. Low-frequency vestibular hair cells became specialized to transduce higher frequencies, requiring much faster response rates. This change is attributable in part to modifications in the ion channels of the cell membrane, such that each cell is “electrically tuned” to a particular frequency, a phenomenon still observed in some modern amniote ears.

MODERN INNER EARS

Arose starting about 200 million years ago In all three lineages, hair cells are arranged along the auditory papilla from low- to high-frequency sensitivity, called a tonotopic organization. In both archosaurs and mammals, one type of hair cell serves to amplify the sound signal received by the other type. In lepidosaurs, the auditory papilla ranges from a few hundred micrometers to 2 millimeters in length and contains two types of hair cells: one with taller bundles and fewer stereovilli that responds to sounds below 1 kHz and another with shorter, thicker bundles that responds to higher-frequency pitches.

The archosaur papilla, which reaches lengths of up to 10 millimeters in some owls, contains many thousands of hair cells of types: tall hair cells, which serve to detect sound, and short hair cells, which amplify the signal. In most mammals, the auditory papilla, called the organ of Corti, evolved to be so long that it began to coil on top of itself. The papilla ranges from 1.5 to 4 coils and 7 millimeters (mouse) to 75 millimeters (blue whale) in length. Mammals have two types of hair cells: covering the oval window, which detect sound, and outer hair cells, which inner hair cells amplify it.

Tectorial membrane

Tall hair cell

Short hair cell

Basilar membrane

Inner

hair cell

Outer

hair cell

In modern representatives, the columella is long and thin, with several, usually cartilaginous extensions known as the extracolumella. One of these, the “inferior process,” connects the inner surface of the eardrum and the columella, which then connects to the footplate that covers the oval window of the inner ear. This two-part system forms a lever that, together with the pressure increase incurred by transmitting from the much larger eardrum to the footplate, greatly magnifies sound entering the inner ear.

In the mammals of the Triassic, the equivalent events were more complex, but the functional result was remarkably similar. Mammal ancestors reduced the number of bones in the lower jaw from seven to one and, in the process, formed a new jaw joint. Initially, the old and new jaw structures existed in parallel, but over time the old joint moved towards the rear of the head. This event, which at any other time would likely have led to the complete loss of the old joint bones, occurred simultaneously with the origin of the mammalian tympanic middle ear. Older paleontological and newer developmental evidence from Shigeru Kuratani’s lab at RIKEN in Japan indicate that the mammalian eardrum evolved at a lower position on the skull relative to that of the other amniotes, a position outside the old jaw joint.3 In time, the bones of this old joint, together with the hyomandibula, became the three bony ossicles (malleus, incus, and stapes) of the new middle ear. Like the middle ear of archosaurs and lepidosaurs, these ossicles form a lever system that, along with the large area difference between eardrum and footplate, greatly magnifies sound input. Thus, remarkably, these complex events led independently to all modern amniotes possessing a middle ear that, at frequencies below 10 kHz, works equally effectively despite the diverse structures and origins. There is also evidence that the three-ossicle mammalian middle ear itself evolved at least twice—in egg-laying mammals such as the platypus, and in therians, which include marsupials and placentals—with similar outcomes.

More…

Aural History

The form and function of the ears of modern land vertebrates cannot be understood without knowing how they evolved.

http://www.the-scientist.com//?articles.view/articleNo/43806/title/Aural-History/

By Geoffrey A. Manley | September 1, 2015

PHOTO CREDITS SEE END OF ARTICLE
http://www.the-scientist.com/Sept2015/feature1.jpg

Unlike eyes, which are generally instantly recognizable, ears differ greatly in their appearance throughout the animal kingdom. Some hearing structures may not be visible at all. For example, camouflaged in the barn owl’s facial ruff—a rim of short, brown feathers surrounding the bird’s white face—are clusters of stiff feathers that act as external ears on either side of its head. These feather structures funnel sound collected by two concave facial disks to the ear canal openings, increasing the bird’s hearing sensitivity by 20 decibels—approximately the difference between normal conversation and shouting. Similar increases in sensitivity result from the large and often mobile external structures, or pinnae, of many mammals, such as cats and bats. Internally, the differences among hearing organs are even more dramatic.

Although fish can hear, only amphibians and true land vertebrates—including the aquatic species that descended from them, such as whales and pinnipeds—have dedicated hearing organs. In land vertebrates belonging to the group Amniota, including lizards, birds, and mammals, sound usually enters through an external canal and impinges on an eardrum that is connected through middle-ear bones to the inner ear. There, hundreds or thousands of sensory hair cells are spread along an elongated membrane that acts as a spectral analyzer, with the result that each local group of hair cells responds best to a certain range of pitches, or sound frequencies. The hair cells then feed this information into afferent nerve fibers that carry the information to the brain. (See “Human Hearing: A Primer.”)

For a period of at least 50 million years after amniotes arose, the three main lineages were most likely quite hard of hearing.

Together, these hair cells and nerve fibers encode a wide range of sounds that enter the ear on that side of the head. Two ears complete the picture, allowing animals’ brains to localize the source of the sounds they hear by comparing the two inputs. Although it seems obvious that the ability to process nearby sounds would be enormously useful, modern amniote ears in fact arose quite late in evolutionary history, and to a large extent independently in different lineages. As a result, external, middle, and inner ears of various amniotes are characteristically different.1 New paleontological studies and comparative research on hearing organs have revealed the remarkable history of this unexpected diversity of ears.

Divergence from a common origin

Amniote vertebrates comprise three lineages of extant groups that diverged roughly 300 million years ago: the lepidosaurs, which include lizards and snakes; the archosaurs, which include crocodilians and birds; and mammals, which include egg-laying, pouched, and placental mammals. By comparing the skulls of the extinct common ancestors of these three lineages, as well as the ears of the most basal modern amniotes, researchers have concluded that ancestral amniotes had a small (perhaps less than 1 millimeter in length) but dedicated hearing organ: a sensory epithelium called a basilar papilla, with perhaps a few hundred sensory hair cells supported by a thin basilar membrane that is freely suspended in fluid. These rudimentary structures evolved from the hair cells of vestibular organs, which help organisms maintain their balance by responding to physical input, such as head rotation or gravity. Initially, the hearing organ only responded to low-frequency sounds. On their apical surface, all hair cells have tight tufts or bundles of large, hairlike villi known as stereovilli (or, more commonly stereocilia, even though they are not true cilia), which give hair cells their name. Between these stereovilli are proteinaceous links, most of which are closely coupled to sensory transduction channels that respond to a tilting of the stereovilli bundles caused by sound waves.

The amniote hearing organ evolved as a separate group of hair cells that lay between two existing vestibular epithelia. Low-frequency vestibular hair cells became specialized to transduce higher frequencies, requiring much faster response rates. This change is attributable in part to modifications in the ion channels of the cell membrane, such that each cell is “electrically tuned” to a particular frequency, a phenomenon still observed in some modern amniote ears. Moreover, the early evolution of these dedicated auditory organs in land vertebrates led to the loss of the heavy otolithic membrane that overlies the hair-cell bundles of vestibular organs and is responsible for their slow responses. What remains is the watery macromolecular gel known as the tectorial membrane, which assures that local groups of hair cells move synchronously, resulting in greater sensitivity.

Good high-frequency hearing did not exist from the start, however. For a period of at least 50 million years after amniotes arose, the three main lineages were most likely quite hard of hearing. They had not yet evolved any mechanism for absorbing sound energy from air; they lacked the middle ear and eardrum that are vital for the function of modern hearing organs. As such, ancestral amniotes most likely perceived only sounds of relatively low frequency and high amplitude that reached the inner ear via the limbs or, if the skull were rested on the ground, through the tissues of the head. It is unclear what kind of stimuli could have existed that would have led to the retention of such hearing organs for such a long time.

The magnificent middle ear

http://www.the-scientist.com/Sept2015/Manleyonline.jpg

CONVERGING ON THE EAR: Starting around 250 million years ago, the three amniote lineages—lepidosaurs (lizards and snakes), archosaurs (crocodilians and birds), and mammals—separately evolved a tympanic middle ear, followed by evolution of the inner ear, both of which served to increase hearing sensitivity. Despite the independent origin of hearing structures in the three lineages, the outcomes were functionally quite similar, serving as a remarkable example of convergent evolution.
See full infographic: JPG

ILLUSTRATIONS: PHEBE LI FOR THE SCIENTIST. ICONS: ISTOCK.COMDuring the Triassic period, some 250 to 200 million years ago, a truly remarkable thing happened. Independently, but within just 20 million to 30 million years of one another, all three amniote lineages evolved a tympanic middle ear from parts of the skull and the jaws.2

The tympanic middle ear is the assemblage of tiny bones that connects at one end to an eardrum and at the other end to the oval window, an aperture in the bone of the inner ear. Despite the temporal coincidence in the evolution of these structures in the three amniote lineages and the functional similarities of the adaptations, the groups were by this time so far separated that the middle ears evolved from different structures into two different configurations. The single middle-ear bone, the columella, of archosaurs and lepidosaurs derived from the hyomandibular, a bone that earlier had formed a large strut connecting the braincase to the outer skull. In modern representatives, the columella is long and thin, with several, usually cartilaginous extensions known as the extracolumella. One of these, the “inferior process,” connects the inner surface of the eardrum and the columella, which then connects to the footplate that covers the oval window of the inner ear. This two-part system forms a lever that, together with the pressure increase incurred by transmitting from the much larger eardrum to the footplate, greatly magnifies sound entering the inner ear.

In the mammals of the Triassic, the equivalent events were more complex, but the functional result was remarkably similar. Mammal ancestors reduced the number of bones in the lower jaw from seven to one and, in the process, formed a new jaw joint. Initially, the old and new jaw structures existed in parallel, but over time the old joint moved towards the rear of the head. This event, which at any other time would likely have led to the complete loss of the old joint bones, occurred simultaneously with the origin of the mammalian tympanic middle ear. Older paleontological and newer developmental evidence from Shigeru Kuratani’s lab at RIKEN in Japan indicate that the mammalian eardrum evolved at a lower position on the skull relative to that of the other amniotes, a position outside the old jaw joint.3 In time, the bones of this old joint, together with the hyomandibula, became the three bony ossicles (malleus, incus, and stapes) of the new middle ear. Like the middle ear of archosaurs and lepidosaurs, these ossicles form a lever system that, along with the large area difference between eardrum and footplate, greatly magnifies sound input.

Thus, remarkably, these complex events led independently to all modern amniotes possessing a middle ear that, at frequencies below 10 kHz, works equally effectively despite the diverse structures and origins. There is also evidence that the three-ossicle mammalian middle ear itself evolved at least twice—in egg-laying mammals such as the platypus, and in therians, which include marsupials and placentals—with similar outcomes.

Inner-ear evolution

http://www.the-scientist.com/Sept2015/piano_med.jpg

PITCH PERFECT: The hearing organs of amniotes are organized tonotopically, with hair cells sensitive to high frequencies at the basal end of the papilla, grading into low-frequency hair cells at the apical end.BASED ON MED-EL WWW.MEDEL.COMThe evolution of tympanic middle ears kick-started the evolution of modern inner ears, where sound waves are converted into the electrical signals that are sent to the brain. The inner ear is least developed in the lepidosaurs, most of which retained a relatively small auditory papilla, in some just a few hundred micrometers long. Many lepidosaurs, predominantly diurnal species, also lost their eardrum. Snakes reduced their middle ear, limiting their hearing to frequencies less than 1 kHz, about two octaves above middle C. (For comparison, humans can hear sounds up to about 15 or 16 kHz.) Clearly, hearing was not under strong selective pressure in this group. There are a few exceptions, however. In geckos, for example, which are largely nocturnal, the papillar structure shows unique specializations, accompanied by high sensitivity and strong frequency selectivity. Indeed, the frequency selectivity of gecko auditory nerve fibers exceeds that of many mammals.

One part of the inner ear that did improve in lizards (but not in snakes) is the hair cells, with the papillae developing different areas occupied by two structural types of these sound-responsive cells. One of these hair cell groups responds to sounds below 1 kHz and perhaps corresponds to the ancestral version. The higher-frequency hair cells have a more specialized structure, particularly with regard to the size and height of the stereovilli, with bundle heights and stereovillus numbers varying consistently along the papilla’s length. Taller bundles with fewer stereovilli, which are much less stiff and therefore respond best to low frequencies, are found at one end of the membrane, while shorter, thicker bundles with more stereovilli that respond best to higher frequencies are found at the other end—a frequency distribution known as a tonotopic organization. Still, with the exception of one group of geckos, lizard hearing is limited to below 5 to 8 kHz.

In contrast to the relatively rudimentary lepidosaur inner ear, the auditory papilla of archosaurs (birds, crocodiles, and their relatives) evolved much greater length. Owls, highly proficient nocturnal hunters, boast the longest archosaur papilla, measuring more than 10 millimeters and containing many thousands of hair cells. As in lizards, archosaur hair cells show strong tonotopic organization, with a gradual change in the diameter and height of the stereovillar bundles contributing to the gradually changing frequency sensitivity along the papilla. In addition, the hair cells are divided along and across the basilar membrane, with tall hair cells (THCs) resting on the inner side and the apical end, most distant from the middle ear, grading into short hair cells (SHCs) on the outer side and at the basal end. Interestingly, many SHCs completely lack afferent innervation, which is the only known case of sensory cells lacking a connection to the brain. Instead of transmitting sensory information to the brain, these hair cells likely amplify the signal received by the inner ear. Despite the more complex anatomy, however, bird hearing is also generally limited to between 5 and 8 kHz, with the exception of some owls, which can hear up to 12 kHz.

The mammalian papilla, called the organ of Corti, also evolved to be larger—generally, but not always, longer than those of birds—but the extension in length varies in different lineages.4 Mammalian papillae also have a unique cellular arrangement. The papillae of modern egg-laying monotremes, which likely resemble those of the earliest mammals, include two groups of hair cells separated by numerous supporting pillar cells that form the tunnel of Corti. In any given cross section, there are approximately five inner hair cells (IHCs) on the inner side of the pillar cells, closer to the auditory nerve, and eight outer hair cells (OHCs) on the outer side. In therian mammals (marsupials and placentals), the numbers of each cell group have been much reduced, with only two pillar cells forming the tunnel in any given cross-section, and generally just a single IHC and three or four OHCs, though the functional consequences of this reduction remain unclear. About 90 percent of afferent fibers innervate IHCs, while only 10 percent or fewer innervate OHCs, despite the fact that OHCs account for some 80 percent of all hair cells. As with bird SHCs that lack afferent innervation, there are indications that the main function of OHCs is to amplify the physical sound signal at very low sound-pressure levels.

Therian mammals also evolved another key hearing adaptation: the cochlea. Shortly before marsupial and placental lineages diverged, the elongating hearing organ, which had always been curved, reached full circle. The only way to further increase its length was to form more than one full coil, a state that was reached roughly 120 million years ago. The result is hearing organs with 1.5 to 4 coils and lengths from 7 millimeters (mouse) to 75 millimeters (blue whale). Hearing ranges also diverged, partly depending on the size of the animal (larger mammals tend to have lower upper-frequency limits), but with a number of remarkable specializations, as expected in a lineage that radiated greatly during several evolutionary episodes.

As a result of these adaptations, most mammals have an upper frequency-response limit that well exceeds those of lepidosaurs and archosaurs. Human hearing extends to frequencies of about 15 kHz; a guinea pig can hear sounds up to about 45 kHz; and in the extreme cases of many bats and toothed whales, hearing extends into ultrasonic frequencies, sometimes as high as 180 kHz, allowing these animals to echolocate in air and water. This impressive increase in frequency limits is due to an extremely stiff middle ear, as well as a stiff cochlea. During early therian evolution, the bone of the canal surrounding the soft tissues invaded the supporting ridges of the basilar membrane, creating stiff laminae. Such bony ridges were retained in species perceiving ultrasonic frequencies, but tended to be reduced and replaced by softer connective-tissue supports in those with lower-frequency limits, such as humans.

Amplification within the ear

http://www.the-scientist.com/Sept2015/ear_hair.jpg

HAIRS OF THE EAR: Rows of inner-ear hair cells have villous bundles (blue) on their apical surface that convert sound waves to nervous signals sent to the brain.© STEVE GSCHMEISSNER/SCIENCE SOURCEIn addition to the specialized structures of the middle and inner ears of amniotes that served to greatly increase hearing sensitivity, the hair cells themselves can produce active movements that further amplify sound stimuli. The evolutionarily oldest such active mechanism was discovered in the late 1980s by Jim Hudspeth’s group, then at the University of California, San Francisco, School of Medicine, working with frogs,5 and Andrew Crawford and Robert Fettiplace, then at the University of Cambridge, working with turtles.6 The amplification mechanism, called the active bundle mechanism, probably evolved in the ancestors of vertebrates and helped overcome the viscous forces of the surrounding fluids, which resist movement. When sound stimuli move the hair-cell bundle and thus open transduction channels to admit potassium ions, some calcium ions also enter the cell. These calcium ions bind to and influence the open transduction channels, increasing the speed with which these channels close. Such closing forces are exerted in phase with the incoming sound waves, increasing the distance that the hair cells move in response, and thereby increasing their sensitivity. It is likely that this mechanism operates in all vertebrate hair cells.5 In lizards, my group provided evidence that this bundle mechanism really does operate in the living animal.7

In 1986, a second mechanism of hair cell–driven sound amplification was discovered in mammalian OHCs by Bill Brownell’s group, then at the University of Florida School of Medicine. Brownell and his colleagues showed that mammalian OHCs, but not IHCs, changed their length very rapidly in phase with the signal if exposed to an alternating electrical field.8 Such fields occur when hair cells respond to sound. Subsequent experiments showed that the change in cell length is due to changes in the molecular configuration of a protein, later named prestin, which occurs in high density along the lateral cell membrane of OHCs. In mammals, the force produced by the OHCs is so strong that the entire organ of Corti, which includes all cell types that surround the hair cells and the basilar membrane itself, is driven in an up-and-down motion. This movement can amplify sounds by at least 40dB, allowing very quiet noises to be detected. There is evidence for the independent evolution of specific molecular configurations of prestins that allow for the amplification of very high ultrasonic frequencies in bats and whales.9

Bird ears also appear to produce active forces that amplify sound. The SHCs have bundles comprising up to 300 stereovilli (about three times as many as the bundles of mammalian OHCs),10 and the movement of these bundles probably drives the movement of THCs indirectly via the tectorial membrane. Also, very recent data from the lab of Fettiplace, now at the University of Wisconsin–Madison, suggests that in birds, prestin (albeit in a different molecular form) may work in the plane across the hearing organ (i.e., not up and down as in mammals), perhaps reinforcing the influence of the bundle active mechanism on the THCs via the tectorial membrane.11

Three hundred million years of evolution have resulted in a fascinating variety of ear configurations that, despite their struc­tural diversity, show remarkably similar physiological responses.

In addition to amplifying hair-cell activity, these active mechanisms manifest as spontaneous movements of the hearing organ, oscillating even in the absence of sound stimuli. Such spontaneous movements actually produce sound that is emitted through the middle ear to the outside world and can be measured in the ear canal. These spontaneous otoacoustic emissions (SOAEs) enable remote sensing of what is going on within the inner ear and have permitted increasingly important research on inner-ear mechanisms and new clinical diagnostic methods to monitor the health of the ear’s sensory epithelium. We recently showed that spectral patterns of SOAEs in lizards, birds, and mammals are remarkably similar, despite up to 70-fold differences in the size of the hearing organs, suggesting that there are profound commonalities among the inner ears of amniotes that we still do not really understand.12

Remarkable convergence

Three hundred million years of evolution have resulted in a fascinating variety of ear configurations that, despite their structural diversity, show remarkably similar physiological responses. There are hardly any differences in sensitivity between the hearing of endothermal birds and mammals, and the frequency selectivity of responses is essentially the same in most lizards, birds, and mammals. The combined research efforts of paleontologists, anatomists, physiologists, and developmental biologists over several decades have clarified the major evolutionary steps in all lineages that modified the malleable middle and inner ears into their present-day kaleidoscopic variety of form, yet a surprising consensus in their function.

Geoffrey A. Manley is a retired professor from the Institute of Zoology at the Technical University in Munich, Germany. He is currently a guest scientist in the laboratory of his wife, Christine Köppl, at Oldenburg University in Germany.

References

  1. G.A. Manley, C. Köppl, “Phylogenetic development of the cochlea and its innervation,” Curr Opin Neurobiol, 8:468-74, 1998.
  2. J.A. Clack, “Patterns and processes in the early evolution of the tetrapod ear,” J Neurobiol, 53:251-64, 2002.
  3. T. Kitazawa et al., “Developmental genetic bases behind the independent origin of the tympanic membrane in mammals and diapsids,” Nat Commun, 6:6853, 2015.
  4. G.A. Manley, “Evolutionary paths to mammalian cochleae,” JARO, 13:733-43, 2012.
  5. A.J. Hudspeth, “How the ear’s works work: Mechanoelectrical transduction and amplification by hair cells,” C R Biol, 328:155-62, 2005.
  6. A.C. Crawford, R. Fettiplace, “The mechanical properties of ciliary bundles of turtle cochlear hair cells,” J Physiol, 364:359-79, 1985.
  7. G.A. Manley et al., “In vivo evidence for a cochlear amplifier in the hair-cell bundle of lizards,” PNAS, 98:2826-31, 2001.
  8. B. Kachar et al., “Electrokinetic shape changes of cochlear outer hair cells,” Nature, 322:365-68, 1986.
  9. Y. Liu et al., “Convergent sequence evolution between echolocating bats and dolphins,” Curr Biol, 20:R53-R54, 2010.
  10. C. Köppl et al., “Big and powerful: A model of the contribution of bundle motility to mechanical amplification in hair cells of the bird basilar papilla,” in Concepts and Challenges in the Biophysics of Hearing, ed. N.P. Cooper, D.T. Kemp (Singapore: World Scientific, 2009), 444-50.
  11. M. Beurg et al., “A prestin motor in chicken auditory hair cells: Active force generation in a nonmammalian species,” Neuron, 79:69-81, 2013.
  12. C. Bergevin et al., “Salient features of otoacoustic emissions are common across tetrapod groups and suggest shared properties of generation mechanisms,” PNAS, 112:3362-67, 2015.

Sea Lion: © iStock/LFStewart; Squirrel: © Erik Mandre/Shutterstock; Frog: ©Frank B. Yuwono/Shutterstock; Owl: ©XNature.Photography/Shutterstock; Lizard: ©Andrew Wijesuriya/Shutterstock; Bat: © iStock/GlobalP; Ostrich: © Jamen Percy/Shutterstock; Dog: ©Annette Shaff/Shutterstock; Lynx: © Dmitri Gomon/Shutterstock

Correction (September 15, 2015): Citation #8 of this story has been updated to accurately reflect the research referenced in the text. The Scientist regrets the error.

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vertebratessensory biologyhearingevolutionary biologyevolution and amniotes

Early Hominin Hearing

http://www.the-scientist.com//?articles.view/articleNo/44119/title/Early-Hominin-Hearing/

Based on the structure of fossilized skulls and ear bones, researchers learn that early hominins heard sounds best between the frequencies that humans and chimpanzees do.

By Karen Zusi | September 29, 2015

africanus skullWIKIMEDIA, JOSÉ BRAGA

http://www.the-scientist.com/images/Nutshell/Sept2015/hominin310.jpg

Early hominin species Australopithecus africanus andParanthropus robustus, which lived around 2 million years ago, possessed hearing capabilities largely similar to modern-day chimpanzees but with a few differences that made their sense more akin to that of humans, according to a recent study. The results were reported last week (September 25) in Science Advances.

“We know that the hearing patterns, or audiograms, in chimpanzees and humans are distinct because their hearing abilities have been measured in the laboratory in living subjects,” study coauthor Rolf Quam of Binghamton University in New York said in a press release. “So we were interested in finding out when this human-like hearing pattern first emerged during our evolutionary history.”

Quam and an international team of researchers studied the anatomy of the ear in three complete fossilized specimens, as well as several partial specimens, from South Africa. The team reconstructed the size and relative proportions of up to six different structures—such as the stapes, a middle ear bone—using 3-D CT scans. The researchers then used a published model to predict how the early hominins may have heard, based on these measurements.

Both species of early hominin evolved an anatomy that allowed them to hear sounds at slightly higher frequencies than chimpanzees, best in the 1.0 kHz to 3.5 kHz range. In comparison, chimpanzees can hear sounds best between 1.0 kHz and 3.0 kHz. Humans can typically hear sounds best between 1.0 kHz and 4.5 kHz; this range encompasses most sounds formed in spoken language.

“[The early hominins] didn’t hear as well as humans, and they are more like chimps,” Quam told The New York Times. But the researchers speculated that the changes in hearing anatomy over time were driven by a lifestyle spent on the open savanna, where short-range communication would have been favored.

“Hearing abilities are closely tied with verbal communication,” Quam wrote at The Conversation. “By figuring out when certain hearing capacities emerged during our evolutionary history, we might be able to shed some light on when spoken language started to evolve.”

Tags

paleontologyhuman evolutionhomininhearingfossilsCT scan and chimpanzee

Hearing Explained

Observe the ins and outs of how our ears perceive sound.

By The Scientist Staff | September 1, 2015

http://www.the-scientist.com//?articles.view/articleNo/43884/title/Hearing-Explained/

Human Hearing: A Primer

How the human ear translates sound waves into nervous impulses

By The Scientist Staff | September 1, 2015

https://youtu.be/46aNGGNPm7s

When sound enters the ear canal, it vibrates the tympanic membrane, or eardrum. These vibrations are passed through the inner ear via three small bones called ossicles: the malleus, the incus, and the stapes. Finally, vibrations of the stapes stimulate the movement of a fluid called perilymph within the bony labyrinth of the inner ear.

See labeled infographic: JPG© CATHERINE DELPHIA

hearing

http://www.the-scientist.com/images/August2015/Primer_2.jpg

Perilymph fills the both the vestibular and tympanic ducts of the cochlea. Between these two channels lies the cochlear duct, which is home to the organ of Corti. There, the sound induced movement of perilymph in the cochlea is translated to an electrical signal that is sent to the brain for processing.

An electrical signal is generated by inner hair cells that sit above the basilar membrane, which separates the cochlear duct from the tympanic duct. As the basilar membrane vibrates in response to fluid movement, it pushes the hair cells along another membrane, known as the tectorial membrane, which shifts laterally to bend projections at the tips of the cells, called stereocilia.

The bending of the stereocilia results in the depolarization of the inner hair cell and initiates a nerve impulse through the spiral ganglion neuron at the base of the cell. A series of outer hair cells serves to mechanically amplify the vibrations that trigger the inner hair cells to fire. High-frequency sounds stimulate hair cells at the base of the cochlea, while low-frequency sounds stimulate hair cells at the apex.

See labeled infographic: JPG© CATHERINE DELPHIA

HAIRS OF THE EAR ear_hair

http://www.the-scientist.com/images/August2015/Primer_1.jpg

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spiral ganglion neuronssensory biologyneuroscienceneuronsmechanotransductionmechanoreception and hearing

Author of books:
Brain Mechanisms of Vision (1991, with David H. Hubel)
Colloquium on Vision: From Photon to Perception (200, with John Dowling and Lubert Stryer)
Brain and Visual Perception: The Story of a 25-Year Collaboration (2005, with David H. Hubel)

Professor: Physiology, Harvard University (1964-74)
Professor: Neurobiology, Harvard University (1974-84)
Professor: Neurobiology, Rockefeller University (1984-98)
Administrator: President, Rockefeller University (1991-98)

The interplay of light and life

Lubert Stryer (born March 2, 1938, in Tianjin, China) is the Mrs. George A. Winzer Professor of Cell Biology, Emeritus, at the Stanford University School of Medicine.[1][2] His research over more than four decades has been centered on the interplay of light and life. In 2007 he received the National Medal of Science for elucidating the biochemical basis of signal amplification in vision, pioneering the development of high density micro-arrays for genetic analysis, and authoring the biochemistry textbook.[3]

Stryer received his B.S. degree from the University of Chicago in 1957 and his M.D. degree from Harvard Medical School. He was a Helen Hay Whitney Research Fellow[4] in the Department of Physics at Harvard and then at the MRC Laboratory of Molecular Biology[5] in Cambridge, England, before joining the faculty of the Department of Biochemistry at Stanford in 1963. In 1969 he moved to Yale to become Professor of Molecular Biophysics and Biochemistry, and in 1976, he returned to Stanford to head a new Department of Structural Biology.[6]

Stryer and coworkers pioneered the use of fluorescence spectroscopy, particularly Förster resonance energy transfer (FRET), to monitor the structure and dynamics of biological macromolecules.[7][8] In 1967, Stryer and Haugland showed that the efficiency of energy transfer depends on the inverse sixth power of the distance between the donor and acceptor,[9][10] as predicted by Förster’s theory. They proposed that energy transfer can serve as a spectroscopic ruler to reveal proximity relationships in biological macromolecules.

A second contribution was Stryer’s discovery of the primary stage of amplification in visual excitation.[11][12] Stryer, together with Fung and Hurley, showed that a single photoexcited rhodopsin molecule activates many molecules of transducin, which in turn activate many molecules of a cyclic GMP phosphodiesterase. Stryer’s laboratory has also contributed to our understanding of the role of calcium in visual recovery and adaptation.[13][14][15]

Stryer participated in developing light-directed, spatially addressable parallel chemical synthesis for the synthesis of peptides and polynucleotides.[16][17][18] Light-directed combinatorial synthesis has been used by Stephen Fodor and coworkers at Affymetrix to make DNA arrays containing millions of different sequences for genetic analyses.

Download Biochemistry Jeremy M Berg John L Tymoczko …

Dec 13, 2014 – Uploaded by Marquita Iraely

Download Biochemistry Jeremy M Berg John L Tymoczko Lubert Stryer PDF. Marquita Iraely …

Macmillan Higher Education: Biochemistry Seventh Edition …

http://www.macmillanhighered.com/Catalog/…/biochemistry-seventhedition-be…

Jeremy M. Berg , John L. Tymoczko (Carleton College) , Lubert Stryer (Stanford … this extraordinary textbook has helped shape the way biochemistry is taught, …

Loose-leaf Version for Biochemistry Seventh Edition Edition

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Proteins that control neurotransmitter release

Author & Curator: Larry H. Bernstein, MD, FCAP

Richard H. Scheller, PhD

The sec6/8 Complex Is Located at Neurite Outgrowth and Axonal Synapse-Assembly Domains

Christopher D. Hazuka, Davide L. Foletti, Shu-Chan Hsu, Yun Kee, F. Woodward Hopf, and Richard H. Scheller
Department of Molecular and Cellular Physiology, Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California 94305-5428

The Journal of Neuroscience, February 15, 1999, 19(4):1324–1334   http://www.jneurosci.org/content/19/4/1324.full.pdf

The molecules that specify domains on the neuronal plasma membrane for the delivery and accumulation of vesicles during neurite outgrowth and synapse formation are unknown. We investigated the role of the sec6/8 complex, a set of proteins that specifies vesicle targeting sites in yeast and epithelial cells, in neuronal membrane trafficking. This complex was found in layers of developing rat brain undergoing synaptogenesis. In cultured hippocampal neurons, the sec6/8 complex was present in regions of ongoing membrane addition: the tips of growing neurites, filopodia, and growth cones. In young axons, the sec6/8 complex was also confined to periodic domains of the plasma membrane. The distribution of synaptotagmin, synapsin1, sec6, and FM1–43 labeling in cultured neurons suggested that the plasma membrane localization of the sec6/8 complex preceded the arrival of synaptic markers and was downregulated in mature synapses. We propose that the sec6/8 complex specifies sites for targeting vesicles at domains of neurite outgrowth and potential active zones during synaptogenesis. Key words: synaptogenesis; neurotransmission; secretion; exocytosis; synaptic vesicle; vesicle targeting

Targeting of vesicles to synaptic sites during development may use similar mechanisms as those involved in vesicle fusion underlying membrane outgrowth. Before contact with a postsynaptic target, axons possess mobile vesicle clusters bearing synaptotagmin, which fuse with the plasma membrane after stimulation (Matteoli et al., 1992; Kraszewski et al., 1995; Dai and Peng, 1996). Thus, growing axons must contain the molecular machinery required for constitutive exocytosis, endocytosis, and activitydependent vesicle release. However, it is unclear how vesicles become clustered at synapses. Although vesicle fusion in axons might occur anywhere along the plasma membrane, there must be membrane targets that signal the clustering of vesicles for synapse formation. Furthermore, it is unclear how sites of vesicle exocytosis are modified as the neuron forms stable contacts with postsynaptic partners.

Identification of a Novel Rab11/25 Binding Domain Present in Eferin and Rip Proteins

Rytis Prekeris*, Jason M. Davies*, and Richard H. Scheller#
JBC Papers in Press. Published on July 31, 2001 as Manuscript M106133200
http://www.jbc.org/content/early/2001/07/31/jbc.M106133200.full.pdf

Rab11, a low molecular weight GTP binding protein, has been shown to play a key role in a variety of cellular processes, including endosomal recycling, phagocytosis, and transport of secretory proteins from the TGN. In this study we describe a novel Rab11 effector, EF hands containing Rab11 interacting protein (eferin). In addition, we identify a 20 amino acid domain that is present at the C-terminus of eferin and other Rab11/25 interacting proteins, such as Rip11 and nRip11. Using biochemical techniques we demonstrate that this domain is necessary and sufficient for Rab11 binding in vitro and that it is required for localization of Rab11 effector proteins in vivo. The data suggest that various Rab effectors compete with each other for the binding to Rab11/25 possibly accounting for the diversity of Rab11 functions.

Members of the Rab/Ypt GTPase family have emerged as important regulators of vesicular trafficking (1). Rab proteins have been proposed to mediate a variety of functions, including vesicle translocation and docking at a specific fusion sites. Like all small GTPases, Rabs cycle between active (GTP bound) and inactive (GDP bound) conformations (2). In the GTP bound state, Rab proteins can bind a variety of downstream effector proteins, while GTP hydrolysis leads to a conformational change in the “switch” region that renders the Rab GTPase unrecognizable to its effector proteins (3,4). A key question in understanding the interactions between Rabs and their effectors concerns the mechanisms by which Rab GTPases specifically bind a diverse spectrum of effectors and how this is regulated by the common structural motif used as a GTP switch. Biochemical and genetic studies have identified several hypervariable regions that might be involved in determining Rab specificity, including N- and C-termini, as well as α3/β5 by guest on September 6, 2015 http://www.jbc.org/ Downloaded from loop (5,6). Indeed, the recently reported structure of Rab3a bound to a putative effector, rabphillin-3a, revealed that Rab3a/rabphillin-3a complex interacts through two main regions (7). The first consists of conformationally sensitive “switch” regions of Rab3a bound to the a1 helix and the C-terminal part of rabphillin-3a. The second involves the SGAWFF domain of rabphillin-3a which fits into a pocket formed by the three hypervariable complementary determining regions (CDRs) of Rab3a, corresponding to the N- and C-termini and α3/β5 loop. Thus, it appears that the hypervariable RabCDR are involved in determining the specificity of effector binding, while the conserved “switch” regions impart GTP dependency and binding. It remains to be determined, however, whether this paradigm also applies to other Rab/effector complexes. Rab11a, -11b, and -25 are closely related members of Rab GTPase family that have been implicated in regulating a variety of different post-Golgi trafficking pathways, such as protein recycling (8), phagocytosis (9), insulin-stimulated Glut4 insertion in the plasma membrane (10), and membrane trafficking from early endosomes to the transGolgi network (11). During the last few years several Rab11/25 interacting proteins have been identified, including Rab11BP/Rabphilin-11, Rip11, nRip11, and myosin Vb (12- 15). However, the mechanisms of their function, as well as molecular aspects of their interactions with Rab11, remain to be fully understood. In the present study, we report the identification of EF-hands containing Rab11/25 interacting protein (eferin). Furthermore, we characterized a Rab binding domain (RBD11) which is present at the Cterminus of eferin as well as other Rab11/25 binding proteins, such as Rip11 and nRip11. Using biochemical techniques we demonstrated that RBD11 is the region which encodes the specificity for Rab11/25, but is distinct from the region interacting with Rab “switch” domain, since its interactions with the Rab11/25 are not GTP-dependent.

The functional significance of the differences in Rip and eferin interactions with Rab11/25 remains to be determined. One possibility is that additional cellular factors can regulate the affinity of Rab11/25 binding to its effectors. Indeed, the recombinant full length Rip11 binds poorly to Rab11a in pull down and yeast-two hybrid assays as compared to full length endogenous Rip11 from cellular TX-100 extracts (data not shown). Furthermore, it has been previously shown that Rip11 can also interact with γSNAP and cytoskeleton (13,24). Thus, the interactions of Rips and eferin with different factors could be used as a means of differentially regulating Rab11/25 binding. Alternatively, the Rab11/25 binding motif in eferin and Rip11 might be conformationlly hidden and require activation before binding to Rab11/25. We have previously demonstrated that phosphorylation of Rip11 plays an important role in its trafficking (13). Thus, differential phosphorylation on Rab11/25 binding motifs could also play a role in regulating the binding of Rip11 and eferin to Rab GTPases. Despite to recent progress in understanding the roles of Rabs and their effectors in regulating membrane trafficking, we are only beginning to unravel the structural determinants of their function. Identification and characterization of the Rab11/25 binding regions in Rip and Eferin proteins will be of a crucial importance in understanding the molecular mechanisms involved in differential regulation of the variety of Rab11-dependent trafficking pathways.

J. Immunol. Methods
J Immunol Methods 2008 Mar 14;332(1-2):41-52. Epub 2008 Jan 14.
Genentech Inc., 1DNA Way, South San Francisco, California, 94080, United States. jagath@gene.com
Cysteines with reactive thiol groups are attractive tools for site-specific labeling of proteins. Engineering a reactive cysteine residue into proteins with multiple disulfide bonds is often a challenging task as it may interfere with structural and functional properties of the protein. Here we developed a phage display-based biochemical assay, PHESELECTOR (Phage ELISA for Selection of Reactive Thiols) to rapidly screen reactive thiol groups on antibody fragments without interfering with their antigen binding, using trastuzumab-Fab (hu4D5Fab) as a model system

Antibody-drug conjugates enhance the antitumor effects of antibodies and reduce adverse systemic effects of potent cytotoxic drugs. However, conventional drug conjugation strategies yield heterogenous conjugates with relatively narrow therapeutic index (maximum tolerated dose/curative dose). Using leads from our previously described phage display-based method to predict suitable conjugation sites, we engineered cysteine substitutions at positions on light and heavy chains that provide reactive thiol groups and do not perturb immunoglobulin folding and assembly, or alter antigen binding.

Neuron
Neuron 2008 Nov;60(3):400-1

Antibody drug conjugates (ADCs) combine the ideal properties of both antibodies and cytotoxic drugs by targeting potent drugs to the antigen-expressing tumor cells, thereby enhancing their antitumor activity. Successful ADC development for a given target antigen depends on optimization of antibody selection, linker stability, cytotoxic drug potency, and mode of linker-drug conjugation to the antibody. Here, we systematically examined the in vitro potency as well as in vivo preclinical efficacy and safety profiles of a heterogeneous preparation of conventional trastuzumab-mcc-DM1 (TMAb-mcc-DM1) ADC with that of a homogeneous engineered thio-trastuzumab-mpeo-DM1 (thioTMAb-mpeo-DM1) conjugate.

Sensory and signaling pathways are exquisitely organized in primary cilia. Bardet-Biedl syndrome (BBS) patients have compromised cilia and signaling. BBS proteins form the BBSome, which binds Rabin8, a guanine nucleotide exchange factor (GEF) activating the Rab8 GTPase, required for ciliary assembly.

The reactive thiol in cysteine is used for coupling maleimide linkers in the generation of antibody conjugates. To assess the impact of the conjugation site, we engineered cysteines into a therapeutic HER2/neu antibody at three sites differing in solvent accessibility and local charge. The highly solvent-accessible site rapidly lost conjugated thiol-reactive linkers in plasma owing to maleimide exchange with reactive thiols in albumin, free cysteine or glutathione.

The intracellular pathogenic bacterium Salmonella enterica serovar typhimurium (Salmonella) relies on acidification of the Salmonella-containing vacuole (SCV) for survival inside host cells. The transport and fusion of membrane-bound compartments in a cell is regulated by small GTPases, including Rac and members of the Rab GTPase family, and their effector proteins. However, the role of these components in survival of intracellular pathogens is not completely understood.

Nat. Med.
Nat Med 2013 Oct;19(10):1232-5
Genentech Research and Early Development, 1 DNA Way, San Francisco, California, USA.
MAbs
MAbs 2014 Jan-Feb;6(1):95-107
Multi-transmembrane proteins are especially difficult targets for antibody generation largely due to the challenge of producing a protein that maintains its native conformation in the absence of a stabilizing membrane. Here, we describe an immunization strategy that successfully resulted in the identification of monoclonal antibodies that bind specifically to extracellular epitopes of a 12 transmembrane protein, multi-drug resistant protein 4 (MRP4). These monoclonal antibodies were developed following hydrodynamic tail vein immunization with a cytomegalovirus (CMV) promoter-based plasmid expressing MRP4 cDNA and were characterized by flow cytometry.

Antibody-drug conjugates (ADCs) have a significant impact toward the treatment of cancer, as evidenced by the clinical activity of the recently approved ADCs, brentuximab vedotin for Hodgkin lymphoma and ado-trastuzumab emtansine (trastuzumab-MCC-DM1) for metastatic HER2+ breast cancer. DM1 is an analog of the natural product maytansine, a microtubule inhibitor that by itself has limited clinical activity and high systemic toxicity. However, by conjugation of DM1 to trastuzumab, the safety was improved and clinical activity was demonstrated.

Richard H Scheller, PhD

Published on 16 Sep 2014

The Keck School of Medicine of USC is the first medical school in the nation to host the Lasker Lectures, featuring recipients of the prestigious 2013 Albert Lasker Basic Medical Research Award. In this installment, Richard H. Scheller, PhD, executive vice president of Genentech research and early development, discusses breakthoughs in drug development that are turning the tide in the war against cancer.

https://www.youtube.com/watch?v=Fx54EVJMcxM

Kavli Prize 2015

Xenon Pharmaceuticals Appoints Dr. Richard H. Scheller to Its Board of Directors

Biopharmaceutical company Xenon Pharmaceuticals (NasdaqGM:XENE) reported on Monday the addition of Richard H. Scheller, PhD to its board of directors.

Most recently, Dr Scheller has served as chief science officer and head of Therapeutics at 23andMe.

Previously Dr Scheller was the executive vice president at Genentech Research and Early Development & a member of the Roche Corporate Executive Committee; chief scientific officer, executive vice president of Research and senior vice president of Research at Genentech; as well as a professor of Molecular and Cellular Physiology and of Biological Sciences at Stanford University Medical Center and an investigator of the Howard Hughes Medical Institute.

Dr Scheller is currently an adjunct professor in the Department of Biochemistry and Biophysics, School of Medicine at the University of California, San Francisco.

He has been a Director at Xenon Pharmaceuticals Inc. since March 16, 2015 and Medrio, Inc. since November 2012. He serves as a Member of the Medical and Scientific Review Board of Evotec (US), Inc. (Renovis Inc.). In 2014, he was named a trustee of Caltech. He served as a Member of Scientific Advisory Board of Intra-Cellular Therapies, Inc. and Rinat Neuroscience Corporation.

He served on numerous advisory boards including the National Advisory Mental Health Council of the National Institutes of Health. Dr. Scheller served as chairman of the Genentech Foundation’s board of directors. He is a globally recognized leader in biomedical research.

He has published over 200 papers in scientific journals, and worked in cell biology. He has received several additional awards for his work elucidating the molecular mechanisms governing neurotransmitter release, including the 2013 Albert Lasker Basic Medical Research Award, the 2014 California Institute of Technology’s Caltech Distinguished Alumni Award, the 2010 Kavli Prize in Neuroscience, and the 1997 U.S. National Academy of Sciences Award in Molecular Biology. He is a Fellow of the American Academy of Arts and Sciences. Dr. Scheller holds a Doctorate in Chemistry from the California Institute of Technology in 1980, where he was also a Postdoctoral Fellow, Division of Biology. He was also a Postdoctoral Fellow at Columbia University, College of Physicians & Surgeons. He has Bachelor’s Degree in Biochemistry in 1975 at the University of Wisconsin, Madison.

Education: 1971-1975 University of Wisconsin-Madison B.S. – Biochemistry with Honors 1975-1980 California Institute of Technology Ph.D. – Chemistry – Advisor: Eric H. Davidson 1980-1981 California Institute of Technology Postdoctoral Fellow-Division of Biology Advisor: Eric H. Davidson 1981-1982 Columbia University-College of Physicians & Surgeons Postdoctoral Fellow-Molecular Neurobiology Advisors: Richard Axel and Eric R. Kandel Industry Positions: 2001-2003 Senior Vice President – Research Genentech, Inc. 2003-2009 Executive Vice President – Research Genentech, Inc. 2008-2009 Chief Scientific Officer and Executive Vice President – Research Genentech, Inc. 2009- Executive Vice President – Genentech Research and Early Development (gRED) and Member of the Enlarged Roche Corporate Executive Committee Academic Appointments: 1982-1987 Assistant Professor, Department of Biological Sciences, Stanford University 1987-1990 Associate Professor, Department of Biological Sciences, Stanford University 1990-1993 Associate Professor, Department of Molecular and Cellular Physiology, Stanford University Associate Professor (by courtesy), Department of Biological Sciences, Stanford University

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Heroes in Basic Medical Research – Leroy Hood

Larry H Bernstein, MD, FCAP, Curator

Leaders in Pharmaceutical Intelligence

Series E. 2; 4.5

Leroy Hood, MD, PhD

Dr. Hood created the technological foundation for the sciences of genomics (study of genes) and proteomics (study of proteins) through the invention of five groundbreaking instruments and by explicating the potentialities of genome and proteome research into the future through his pioneering of the fields of systems biology and systems medicine. Hood’s instruments not only pioneered the deciphering of biological information, but also introduced the concept of high throughput data accumulation through automation and parallelization of the protein and DNA chemistries.

The first four instruments were commercialized by Applied Biosystems, Inc., a company founded by Dr. Hood in 1981, and the ink-jet technology was commercialized by Agilent Technologies, thus making these instruments immediately available to the world-community of scientists.

The first two instruments transformed the field of proteomics. The protein sequencer allowed scientists to read and analyze proteins that had not previously been accessible, resulting in the characterization of a series of new proteins whose genes could then be cloned and analyzed. These discoveries led to significant ramifications for biology, medicine, and pharmacology. The second instrument, the protein synthesizer, synthesized proteins and peptides in sufficient quantities to begin characterizing their functions. The DNA synthesizer, the first of three instruments for genomic analyses, was used to synthesize DNA fragments for DNA mapping and gene cloning. The most notable of Hood’s inventions, the automated DNA sequencer developed in 1986, made possible high-speed sequencing of human genomes and was the key technology enabling the Human Genome Project.

In the early 1990s Hood and his colleagues developed the ink-jet DNA synthesis technology for creating DNA arrays with tens of thousands of gene fragments, one of the first of the so-called DNA chips, which enabled measuring the levels of 10,000s of expressed genes. This instrument has also transformed genomics, biology, and medicine.

In 1992, Hood created the first cross-disciplinary biology department, Molecular Biotechnology, at the University of Washington. In 2000, he left the UW to co-found Institute for Systems Biology, the first of its kind. He has pioneered systems medicine the years since ISB’s founding.

In 2000, Hood and two colleagues founded the Institute for Systems Biology (ISB), a nonprofit research institute integrating biology, technology, computation and medicine to take a systems (holistic) approach to studying the complexity of biology and medicine by analyzing all elements in a biological system rather than studying them one gene or protein at a time (an atomistic approach).

Hood has made many seminal discoveries in the fields of immunology, neurobiology and biotechnology and, most recently, has been a leader in the development of systems biology, its applications to cancer, neurodegenerative disease, and the linkage of systems biology to personalized medicine.

Hood’s efforts in a systems approach to disease have led him to pioneer a new approach to medicine that he coined P4 Medicine in 2003. His view is that P4 medicine will transform the practice of medicine over the next decade, moving it from a largely reactive discipline to a proactive one.

Dr. Hood’s outstanding contributions have had a resounding effect on the advancement of science since the 1960s. Throughout his career, he has adhered to the advice of his mentor, Dr. William J. Dreyer: “If you want to practice biology, do it on the leading edge, and if you want to be on the leading edge, invent new tools for deciphering biological information.”

 

Hood is now pioneering new approaches to P4 medicine

Co-founder and Chairman P4 Medicine institute

—predictive, preventive, personalized and participatory, and most recently, has embarked on creating a P4 pilot project on 100,000 well individuals, that is transforming healthcare.

In addition to his ground-breaking research, Hood has published 750 papers, received 36 patents, 17 honorary degrees and more than 100 awards and honors. He is one of only 15 individuals elected to all three National Academies—the National Academy of Science, the National Academy of Engineering, and the Institute of Medicine. Hood has founded or co-founded 15 different biotechnology companies.

 

http://www.youtube.com/watch%3Fv%3D5aE8tgbsl9U Feb 18, 2015 Dr. Leroy Hood, President and Co-founder, Institute for Systems Biology, gives a talk entitled “Systems Medicine and a Longitudinal, …

http://www.youtube.com/watch%3Fv%3DaYGTLj02sx0  Nov 19, 2014 … of Healthcare? A Personal View of Biological Complexity, Paradigm Changes, Systems Biology and Systems Medicine .Speaker: Leroy Hood.

http://www.youtube.com/watch%3Fv%3DnT1MvnH6j8Q Sep 26, 2014 Dr. Leroy Hood discusses how P4 (Predictive, Preventive, … EMBC 2014 Theme Keynote Lecture with Dr. Emery Brown – Duration: 58:49. by …

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CRISPR/Cas9 Finds Its Way As an Important Tool For Drug Discovery & Development

  UPDATED 6/11/2021

CRISPR Diagnostics: CRISPR-dx Comes of Age: Tool in Drug Development

The past five years has seen a rapid expansion of the ability of CRISPR based tools toward diagnostic testing. Recently, CRISPR has been used to detect SARS-CoV-2 in patients. An article in the journal Science describes the different classes of CRISPR diagnostics in use today .

Update near end of post

UPDATED 8/08/2020

Association to Causation: Using GWAS to Identify Druggable Targets

A Gen Webinar Thursday, August 6, 2020; 11:00am – 12:30pm EST

See at end of post

Curator: Stephen J. Williams, Ph.D.

 

2.1.2.1

CRISPR/Cas9 Finds Its Way As an Important Tool For Drug Discovery & Development, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

The RNA-guided Cas9 nuclease from the microbial clustered regularly interspaced short palindromic repeats (CRISPR) adaptive immune system can be used to facilitate efficient genome engineering in eukaryotic cells by simply specifying a 20-nt targeting sequence within its guide RNA.

CRISPR/Cas systems are part of the adaptive immune system of bacteria and archaea, protecting them against invading nucleic acids such as viruses by cleaving the foreign DNA in a sequence-dependent manner. Although CRISPR arrays were first identified in the Escherichia coli genome in 1987 (Ishino et al., 1987), their biological function was not understood until 2005, when it was shown that the spacers were homologous to viral and plasmid sequences suggesting a role in adaptive immunity (Bolotin et al., 2005; Mojica et al., 2005; Pourcel et al., 2005). Two years later, CRISPR arrays were confirmed to provide protection against invading viruses when combined with Cas genes (Barrangou et al., 2007). The mechanism of this immune system based on RNA-mediated DNA targeting was demonstrated shortly thereafter (Brouns et al., 2008; Deltcheva et al., 2011; Garneau et al., 2010; Marraffini and Sontheimer, 2008).

Jennifer Doudna, PhD Professor of Molecular and Cell Biology and Chemistry, University of California, Berkeley Investigator, Howard Hughes Medical Institute has recently received numerous awards and accolades for the discovery of CRISPR/Cas9 as a tool for mammalian genetic manipulation as well as her primary intended research target to understand bacterial resistance to viral infection.

A good post on the matter and Dr. Doudna can be seen below:

http://pharmaceuticalintelligence.com/2014/06/13/215-245-6132014-jennifer-doudna-the-biology-of-crisprs-from-genome-defense-to-genetic-engineering/

In Delineating a Role for CRISPR-Cas9 in Pharmaceutical Targeting inheritable metabolic disorders in which may benefit from a CRISPR-Cas9 mediated therapy is discussed. However this curation is meant to focus on CRISPR/CAS9 AS A TOOL IN PRECLINICAL DRUG DEVELOPMENT.

 

Three Areas of Importance of CRISPR/Cas9 as a TOOL in Preclinical Drug Discovery Include:

  1. Gene-Function Studies: CRISPR/CAS9 ability to DEFINE GENETIC LESION and INSERTION SITE
  2. CRISPR/CAS9 Use in Developing Models of Disease
  3. CRISPR/CAS9 Use as a Diagnostic Tool
  • Using CRISPR/Cas9 in PRECLINICAL TOXICOLOGY STUDIES

I.     Gene-Function Studies: CRISPR/CAS9 ability to DEFINE GENETIC LESION and INSERTION SITE

The advent of the first tools for manipulating genetic material (cloning, PCR, transgenic technology, and before microarray and other’omic methods) allowed scientists to probe novel, individual gene functions as well as their variants and mutants in a “one-gene-at-a time” process. In essence, a gene (or mutant gene) was sequenced, cloned into expression vectors and transfected into recipient cells where function was evaluated.

However, some of the experimental issues with this methodology involved

  • Most transfections experiments result in NON ISOGENIC cell lines – by definition the insertion of a transgene alters the genetic makeup of a cell line. Simple transfection experiments with one transgene compared to a “null” transfectant compares non-isogenic lines, possibly confusing the interpretation of gene-function studies. Therefore a common technique is to develop cell lines with inducible gene expression, thereby allowing the investigator to compare a gene’s effect in ISOGENIC cell lines.
  1. Use of CRSPR in Highthrough-put Screening of Genetic Function

A very nice presentation and summary of CRSPR’s use in determining gene function in a high-throughput manner can be found below

www.rna.uzh.ch/events/journalclub/20140429JCCaihong.pdf

  1. Determining Off-target Effects of Gene Therapy Simplified with CRSPR

In GUIDE-seq: First genome-wide method of detecting off-target DNA breaks induced by CRISPR-Cas nucleases (from This Journal’s series on Live Meeting Coverage) at a 2014 Koch lecture

Shengdar Q Tsai and J Keith Joung describe

an approach for global detection of DNA double-stranded breaks (DSBs) introduced by RGNs and potentially other nucleases. This method, called genome-wide, unbiased identification of DSBs enabled by sequencing (GUIDE-seq), relies on capture of double-stranded oligodeoxynucleotides into DSBs. Application of GUIDE-seq to 13 RGNs in two human cell lines revealed wide variability in RGN off-target activities and unappreciated characteristics of off-target sequences. The majority of identified sites were not detected by existing computational methods or chromatin immunoprecipitation sequencing (ChIP-seq). GUIDE-seq also identified RGN-independent genomic breakpoint ‘hotspots’.

SOURCE http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3117.html

II. CRISPR/Cas9 Use in Developing Models of Disease

 

  1. Developing Animal Tumor Models

In a post this year I discussed a talk at the recent 2015 AACR National Meeting on a laboratories ability to use CRISPR gene editing in-vivo to produce a hepatocarcinoma using viral delivery. The post can be seen here: Notes from Opening Plenary Session – The Genome and Beyond from the 2015 AACR Meeting in Philadelphia PA; Sunday April 19, 2015

1) In this talk Dr. Tyler Jacks discussed his use of CRSPR to generate a mouse model of liver tumor in an immunocompetent mouse. Some notes from this talk are given below

  1. B) Engineering Cancer Genomes: Tyler Jacks, Ph.D.; Director, Koch Institute for Integrative Cancer Research
  • Cancer GEM’s (genetically engineered mouse models of cancer) had moved from transgenics to defined oncogenes
  • Observation that p53 -/- mice develop spontaneous tumors (lymphomas)
  • then GEMs moved to Cre/Lox systems to generate mice with deletions however these tumor models require lots of animals, much time to create, expensive to keep;
  • figured can use CRSPR/Cas9 as rapid, inexpensive way to generate engineered mice and tumor models
  • he used CRSPR/Cas9 vectors targeting PTEN to introduce PTEN mutations in-vivo to hepatocytes; when they also introduced p53 mutations produced hemangiosarcomas; took ONLY THREE months to produce detectable tumors
  • also produced liver tumors by using CRSPR/Cas9 to introduce gain of function mutation in β-catenin

See an article describing this study by MIT News “A New Way To Model Cancer: New gene-editing technique allows scientists to more rapidly study the role of mutations in tumor development.”

The original research article can be found in the August 6, 2014 issue of Nature[1]

And see also on the Jacks Lab site under Research

2)     In the Upcoming Meeting New Frontiers in Gene Editing multiple uses of CRISPR technology is discussed in relation to gene knockout/function studies, tumor model development and

New Frontiers in Gene Editing

Session Spotlight:
BUILDING IN VIVO MODELS FOR DRUG DISCOVERY

Genome Editing Animal Models in Drug Discovery
Myung Shin, Ph.D., Senior Principal Scientist, Biology-Discovery, Genetics and Pharmacogenomics, Merck Research Laboratories

Recent advances in genome editing have greatly accelerated and expanded the ability to generate animal models. These tools allow generating mouse models in condensed timeline compared to that of conventional gene-targeting knock-out/knock-in strategies. Moreover, the genome editing methods have expanded the ability to generate animal models beyond mice. In this talk, we will discuss the application of ZFN and CRISPR to generate various animal models for drug discovery programs.

In vivo Cancer Modeling and Genetic Screening Using CRISPR/Cas9
Sidi Chen, Ph.D., Postdoctoral Fellow, Laboratories of Dr. Phillip A. Sharp and Dr. Feng Zhang, Koch Institute for Integrative Cancer Research at MIT and Broad Institute of Harvard and MIT

Here we describe a genome-wide CRISPR-Cas9-mediated loss-of-function screen in tumor growth and metastasis. We mutagenized a non-metastatic mouse cancer cell line using a genome-scale library. The mutant cell pool rapidly generates metastases when transplanted into immunocompromised mice. Enriched sgRNAs in lung metastases and late stage primary tumors were found to target a small set of genes, suggesting specific loss-of-function mutations drive tumor growth and metastasis.

FEATURED PRESENTATION: In vivo Chromosome Engineering Using CRISPR-Cas9
Andrea Ventura, M.D., Ph.D., Assistant Member, Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center

We will discuss our experience using somatic genome editing to engineer oncogenic chromosomal rearrangements in vivo. More specifically, we will present the results of our ongoing efforts aimed at modeling cancers driven by chromosomal rearrangements using viral mediated delivery of Crispr-Cas9 to adult animals.

RNAi and CRISPR/Cas9-Based in vivo Models for Drug Discovery
Christof Fellmann, Ph.D., Postdoctoral Fellow, Laboratory of Dr. Jennifer Doudna, Department of Molecular and Cell Biology, The University of California, Berkeley

Genetically engineered mouse models (GEMMs) are a powerful tool to study disease initiation, treatment response and relapse. By combining CRISPR/Cas9 and “Sensor” validated, tetracycline-regulated “miR-E” shRNA technology, we have developed a fast and scalable platform to generate RNAi GEMMs with reversible gene silencing capability. The synergy of CRISPR/Cas9 and RNAi enabled us to not only model disease pathogenesis, but also mimic drug therapy in mice, providing us capability to perform preclinical studies in vivo.

In vivo Genome Editing Using Staphylococcus aureus Cas9
Fei Ann Ran, Ph.D., Post-doctoral Fellow, Laboratory of Dr. Feng Zhang, Broad Institute and Junior Fellow, Harvard Society of Fellows

The RNA-guided Cas9 nuclease from the bacterial CRISPR/Cas system has been adapted as a powerful tool for facilitating targeted genome editing in eukaryotes. Recently, we have identified an additional small Cas9 nuclease from Staphylococcus aureus that can be packaged with its guide RNA into a single adeno-associated virus (AAV) vector for in vivo applications. We demonstrate the use of this system for effective gene modification in adult animals and further expand the Cas9 toolbox for in vivo genome editing.

OriGene, Making the Right Tools for CRISPR Research
Xuan Liu, Ph.D., Senior Director, Marketing, OriGene

CRISPR technology has quickly revolutionized the scientific community. Its simplicity has democratized the genome editing technology and enabled every lab to consider its utility in gene function research. As the largest tool box for gene functional research, OriGene created a large collection of CRISPR-related tools, including various all-in-one vectors for gRNA cloning, donor vector backbones, genome-wide knockout kits, AAVS1 insertion vectors, etc. OriGene’s high quality products will accelerate CRISPR research.

  1. Transgenic Animals : Custom Mouse and Rat Model Generation Service Using CRISPR/Cas9 by AppliedStem Cell Inc. (http://www.appliedstemcell.com/)

A critical component of producing transgenic animals is the ability of each successive generations to pass on the transgene. In her post on this site, A NEW ERA OF GENETIC MANIPULATION  Dr. Demet Sag discusses the molecular biology of Cas9 systems and their efficiency to cause point mutations which can be passed on to subsequent generations

This group developed a new technology for editing genes that can be transferable change to the next generation by combining microbial immune defense mechanism, CRISPR/Cas9 that is the latest ground breaking technology for translational genomics with gene therapy-like approach.

  • In short, this so-called “mutagenic chain reaction” (MCR) introduces a recessive mutation defined by CRISPR/Cas9 that lead into a high rate of transferable information to the next generation. They reported that when they crossed the female MCR offspring to wild type flies, the yellow phenotype observed more than 95 percent efficiency.

The advantage of CRISPR/Cas9 over ZFNs or TALENs is its scalability and multiplexibility in that multiple sites within the mammalian genome can be simultaneously modified, providing a robust, high-throughput approach for gene editing in mammalian cells.

Applied StemCell, Inc. offers various services related to animal models including conventional transgenic rats, and phenotype analysis using knock-in, knock-out strategies.

Further explanation of their use of CRSPR can be found at the site below:

http://pharmaceuticalintelligence.com/2014/10/29/gene-editing-at-crispr-speed-services-and-tools/

In addition, ReproCELL Inc., a Tokyo based stem cell company, uses CRSPR to develop

· Tailored disease model cells (hiPSC-Disease Model Cells)

  • 2 types of services
  • ReproUNUS™-g:human iPS cell derived functional cells involving gene editing by CRISPR/Cas9 system
  • eproUNUS™-p:patient derived iPS cell derived functional cells

III. Using CRISPR/Cas9 in PRECLINICAL TOXICOLOGY STUDIES

As of now it is unclear as to the strategy of pharma in how to use this technology for toxicology testing however a few companies have licensed the technology to use across their R&D platforms including

A recent paper used a sister technique TALEN to generate knock-in pigs which suggest that it would be possible to generate pigs with human transgenes, especially in human liver isozymes in orer to study hepatotoxicity of drugs.

Efficient bi-allelic gene knockout and site-specific knock-in mediated by TALENs in pigs

Jing Yao, Jiaojiao Huang, Tang Hai, Xianlong Wang, Guosong Qin, Hongyong Zhang, Rong Wu, Chunwei Cao, Jianzhong Jeff Xi, Zengqiang Yuan, Jianguo Zhao

Sci Rep. 2014; 4: 6926. Published online 2014 November 5. doi: 10.1038/srep06926

UPDATED 8/08/2020

Association to Causation: Using GWAS to Identify Druggable Targets

A Gen Webinar Thursday, August 611:00am – 12:30pm

This webinar is available at https://www.genengnews.com/resources/webinars/association-to-causation-using-gwas-to-identify-druggable-target/

Speakers:

Martin Kampmann, PhD

matinkampmann ucsf

Associate Professor
UCSF
Investigator
Chan Zuckerberg Biohub

Kevin Holden, PhD

kevinholdn sythego

Head of Science
Synthego

Abhi Saharia, PhD

abhisharia sythego

VP, Commercial Development
Synthego

Human genetics provides perhaps the single best opportunity to innovate and improve clinical success rates, through the identification of novel drug targets for complex disease. Even as correlation identifies multiple genetic variants associated with disease, it is challenging to conduct requisite functional studies to identify the causal variants, especially since most association signals map to non-coding regions of the genome.

Genetic editing technologies, such as CRISPR, have enabled the modeling of associated variants at their native loci, including non-coding loci, empowering the identification of underlying biological mechanisms of disease with potential causal genes. However, genome editing is largely manual today severely limiting scale, and forcing the use of rational filters to prioritize which variants to investigate functionally.

In this GEN webinar, we will discuss several strategies enabling large-scale functional investigation of disease-associated variants in a cost- and time-effective manner, including different types of pooled CRISPR-based screens and the development of a fully automated genome engineering platform. We will also review how optimization of genome engineering on this platform enables the engineering of disease-associated variants at scale in pluripotent cells.

  • They will be presenting on use of wide scale CRSPR screens to validate druggable targets
  • The presenters will also discuss new platforms for these wide scale screens

Martin Kampmann, PhD UCSF

  • Multiple genetic variants associated with disease
  • Big gap between accumulation of genetic variant information and functions of these variants
  • CRSPRi or CRSPa (siRNA coupled or enhancer coupled CRSPR guides)
  • Arrayed screens: multiplate guide RNAs and phenotype measured (phenotype can be morphology, complex biological systems like organoids or non autonomous functions
  • Using pooled screens and use of suitable cell model critical for this strategy
  • For example in iPSC vs. neurons has different expression patterns upon same CRSPR of UBA1
  • Advantage is using CRSPR to take iPSC from diseased variant patient to make a corrected isogenic control then introduce gRNAs and use modifier screens to determine phenotypes
  • Generated a platform called CRISPRbrain.org to do bioinformatics on various experiments with different guide RNAs (CRSPRs)

Abhi Saharia, PhD Syntheco

  • Target identification with CSRSPR at Scale
  • Nature medicine paper did GWAS and found 27 SNV associated with high risk disease and a rational filter focused on 1 SNV in noncoding region but why study a single variant and if studied all 27 would they have been able to identify a more representative druggable set?
  • Goal is to reduce or eliminate these rational filters
  • HALO (scalable RNA guide), ECLIPSE platform (automated generation of modified cell lines, BIOINFORMATIC platform (integrated informatics)
  • Syntheco uses an electroporation with ribonucleic proteins (RNP) to give highest efficiency and minimizes off target as complex is only in cells for a short period of time
  • They confirm they are doing single cell cloning by using automated microscopy to confirm single cell growth in each cloning well

Kevin Holden, Head of Science at Syntheco

  • Engineering iPSc genetically modified cells at scale
  • The closer you get to your target site the more efficient your CRSPR so a big factor when making guides, especially for knock-in CRSPR
  • Adding a small molecule non homologous end joining inhibitor increases efficiency to 95%
  • Cold shocking the cells also assists in homologous repair
  • Use cleavage resistant templates

III. CRISPR/CAS9 AS A DIAGNOSTIC TOOL

     In the journal Science, Omar Abudayyeh and Jonathan Gootenberg discuss how CRISPR-based diagnostic (CRISPR-dx) tools offer a solution, and multiple CRISPR-dx products for detection of the SARS-CoV-2 RNA genome have been authorized by the US Food and Drug Administration (FDA).  In addition they discuss the work by Jiao et al. in combining this technique to develop a rapid and sensitive SARS-CoV2 diagnostic test.

Omar O. AbudayyehJonathan S. Gootenberg. Science  28 May 2021: CRISPR Diagnostics
Vol. 372, Issue 6545, pp. 914-915; DOI: 10.1126/science.abi9335

Summary

Although clinical diagnostics take many forms, nucleic acid–based testing has become the gold standard for sensitive detection of many diseases, including pathogenic infections. Quantitative polymerase chain reaction (qPCR) has been widely adopted for its ability to detect only a few DNA or RNA molecules that can unambiguously specify a particular disease. However, the complexity of this technique restricts application to laboratory settings. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has underscored the need for the development and deployment of nucleic acid tests that are economical, easily scaled, and capable of being run in low-resource settings, without sacrifices in speed, sensitivity or specificity. CRISPR-based diagnostic (CRISPR-dx) tools offer a solution, and multiple CRISPR-dx products for detection of the SARS-CoV-2 RNA genome have been authorized by the US Food and Drug Administration (FDA). On page 941 of this issue, Jiao et al. (1) describe a new CRISPR-based tool to distinguish several SARS-CoV-2 variants in a single reaction.

Although clinical diagnostics take many forms, nucleic acid–based testing has become the gold standard for sensitive detection of many diseases, including pathogenic infections. Quantitative polymerase chain reaction (qPCR) has been widely adopted for its ability to detect only a few DNA or RNA molecules that can unambiguously specify a particular disease. However, the complexity of this technique restricts application to laboratory settings. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has underscored the need for the development and deployment of nucleic acid tests that are economical, easily scaled, and capable of being run in low-resource settings, without sacrifices in speed, sensitivity or specificity. CRISPR-based diagnostic (CRISPR-dx) tools offer a solution, and multiple CRISPR-dx products for detection of the SARS-CoV-2 RNA genome have been authorized by the US Food and Drug Administration (FDA). On page 941 of this issue, Jiao et al. (1) describe a new CRISPR-based tool to distinguish several SARS-CoV-2 variants in a single reaction.

There are multiple types of CRISPR systems comprising basic components of a single protein or protein complex, which cuts a specific DNA or RNA target programmed by a complementary guide sequence in a CRISPR-associated RNA (crRNA). The type V and VI systems and the CRISPR-associated endonucleases Cas12 (23) and Cas13 (45) bind and cut DNA or RNA, respectively. Furthermore, upon recognizing a target DNA or RNA sequence, Cas12 and Cas13 proteins exhibit “collateral activity” whereby any DNA or RNA, respectively, in the sample is cleaved regardless of its nucleic acid sequence (46). Thus, reporter DNAs or RNAs, which allow for visual or fluorescent detection upon cleavage, can be added to a sample to infer the presence or absence of specific DNA or RNA species (48).

Initial versions of CRISPR-dx utilizing Cas13 alone were sensitive to the low picomolar range, corresponding to a limit of detection of millions of molecules in a microliter sample. To improve sensitivity, preamplification methods, such as recombinase polymerase amplification (RPA), PCR, loop-mediated isothermal amplification (LAMP), or nucleic acid sequence–based amplification (NASBA), can be used with Cas12 or Cas13 to enable a limit of detection down to a single molecule (8). This preamplification approach, applicable to both Cas12 and Cas13 (67), enabled a suite of detection methods and multiplexing up to four orthogonal targets (7). Additional developments expanded CRISPR-dx readouts beyond fluorescence, including lateral flow (7), colorimetric (9), and electronic or material responsive readouts (10), allowing for instrument-free approaches. In addition, post–collateral-cleavage amplification methods, such as the use of the CRISPR-associated enzyme Csm6, have been combined with Cas13 to further increase the speed of CRISPR-dx tests (7). As an alternative to collateral-cleavage–based detection, type III CRISPR systems, which involve large multiprotein complexes capable of targeting both DNA and RNA, have been used for SARS-CoV-2 detection through production of colorimetric or fluorometric readouts (11).

FDA-authorized CRISPR-dx tests are currently only for use in centralized labs, because the most common CRISPR detection protocols require fluid handling steps and two different incubations, precluding their immediate use at the point of care. Single-step formulations have been developed to overcome this limitation, and these “one-pot” versions of CRISPR-dx are simple to run, operate at a single temperature, and run without complex equipment, producing either fluorescence or lateral flow readouts. The programmability of CRISPR makes new diagnostic tests easier to develop, and within months of the release of the SARS-CoV-2 genome, many COVID-19–specific CRISPR tests were reported and distributed around the world.

The broader capability for Cas enzyme–enhanced nucleic acid binding or cleavage has led to several other detection modalities. Cas9-based methods for cleaving nucleic acids in solution for diagnostic purposes have been combined with other detection platforms, such as destruction of undesired amplicons for preparation of next-generation sequencing libraries (12), or selective removal of alleles for nucleotide-specific detection (13). Alternatively, the programmable cleavage event from the Cas nuclease can be used to initiate an amplification reaction (14). Cas9-based DNA targeting has also been used for nucleotide detection in combination with solid-state electronics, promising an amplification-free platform for detection. In this platform, called CRISPR-Chip, the Cas9 protein binds nucleotide targets of interest (often in the context of the native genome) to graphene transistors, where the presence of these targets alters either current or voltage (15). By utilizing additional Cas9 orthologs and specific guide designs, CRISPR-Chip approaches have been tuned for single–base-pair sensitivity (15). Because they are integrated with electronic readers, CRISPR-Chip platforms may allow facile point-of-care detection with handheld devices.

 

Different classes of CRISPR diagnostics. GRAPHIC: ERIN DANIEL


Jiao et al. use a distinct characteristic of type II CRISPR systems, which involve Cas9, to develop a new type of noncollateral based CRISPR detection. Unlike Cas12s and Cas13, Cas9-crRNA complex formation requires an additional RNA known as the trans-activating CRISPR RNA (tracrRNA). By sequencing RNAs bound to Cas9 from Campylobacter jejuni in its natural host, the authors identified unexpected crRNAs, called noncanonical crRNA (ncrRNA), that corresponded to endogenous transcripts. Upon investigation of this surprising observation, it became clear that the tracrRNA was capable of hybridizing to semi-complementary sequences from a variety of RNA sources, leading to biogenesis of ncrRNAs of various sizes. Recognizing that they could program tracrRNAs to target a transcript of interest, the authors generated a reprogrammed tracrRNA (Rptr) that could bind and cleave a desired transcript, converting a piece of that transcript into a functional guide RNA. By then creating fluorescent DNA sensors that would be cleaved by the Rptr and ncrRNAs, the sensing of RNA by Cas9 could be linked to a detectable readout. This platform, called LEOPARD (leveraging engineered tracrRNAs and on-target DNAs for parallel RNA detection), can be combined with gel-based readouts and enables multiplexed detection of several different sequences in a single reaction (see the figure).

Jiao et al. also combined LEOPARD with PCR in a multistep workflow to detect SARS-CoV-2 genomes from patients with COVID-19. Although more work is needed to integrate this Cas9-based detection modality into a single step with RPA or LAMP to create a portable and sensitive isothermal test, an advantage of this approach is the higher-order multiplexing that can be achieved, allowing multiple pathogens, diseases, or variants to be detected simultaneously. More work is also needed to combine this technology with extraction-free methods for better ease of use; alternative readouts to gel-based readouts, such as lateral flow and colorimetric readouts, would be beneficial for point-of-care detection.

In just 5 years, the CRISPR-dx field has rapidly expanded, growing from a set of peculiar molecular biology discoveries to multiple FDA-authorized COVID-19 tests and spanning four of the six major subtypes of CRISPR systems. Despite the tremendous promise of CRISPR-dx, substantial challenges remain to adapting these technologies for point-of-care and at-home settings. Simplification of the chemistries to operate as a single reaction in a matter of minutes would be revolutionary, especially if the reaction could be run at room temperature without any complex or expensive equipment. These improvements to CRISPR-dx assays can be achieved by identification or engineering of additional Cas enzymes with lower-temperature requirements, higher sensitivity, or faster kinetics, enabling rapid and simple amplification-free detection with single-molecule sensitivity.

Often overlooked is the necessity for a sample DNA or RNA preparation step that is simple enough to be added directly to the CRISPR reaction to maintain a simple workflow for point-of-care testing. In addition, higher-order multiplexing developments would allow for expansive testing menus and approach the possibility of testing for all known diseases. As these advancements are realized, innovative uses of CRISPR-dx will continue in areas such as surveillance, integration with biomaterials, and environmental monitoring. In future years, CRISPR-dx assays may become universal in the clinic and at home, reshaping how diseases are diagnosed.

References and Notes

Other related articles on CRISPR/Cas9 were published in this Open Access Online Scientific Journal, include the following:

Search Results for ‘CRISPR’

Where is the most promising avenue to success in Pharmaceuticals with CRISPR-Cas9?

CRISPR/Cas9 genome editing tool for Staphylococcus aureus Cas9 complex (SaCas9) @ MIT’s Broad Institute

Delineating a Role for CRISPR-Cas9 in Pharmaceutical Targeting

Using CRISPR to investigate pancreatic cancer

Simple technology makes CRISPR gene editing cheaper

RNAi, CRISPR, and Gene Editing: Discussions on How To’s and Best Practices @14th Annual World Preclinical Congress June 10-12, 2015 | Westin Boston Waterfront | Boston, MA

CRISPR/Cas9: Contributions on Endoribonuclease Structure and Function, Role in Immunity and Applications in Genome Engineering

CRISPR-CAS editing brings cloning of woolly mammoth one step closer to reality

GUIDE-seq: First genome-wide method of detecting off-target DNA breaks induced by CRISPR-Cas nucleases

The Patents for CRISPR, the DNA editing technology as the Biggest Biotech Discovery of the Century

CRISPR: Applications for Autoimmune Diseases @UCSF

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Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Reporter: Stephen S Williams, PhD

Article ID #180: Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle. Published on 8/15/2015

WordCloud Image Produced by Adam Tubman

Leaders in Pharmaceutical Business Intelligence would like to announce the First volume of their BioMedical E-Book Series D:

Metabolic Genomics & Pharmaceutics, Vol. I

SACHS FLYER 2014 Metabolomics SeriesDindividualred-page2

which is now available on Amazon Kindle at

http://www.amazon.com/dp/B012BB0ZF0.

This e-Book is a comprehensive review of recent Original Research on  METABOLOMICS and related opportunities for Targeted Therapy written by Experts, Authors, Writers. This is the first volume of the Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases.  It is written for comprehension at the third year medical student level, or as a reference for licensing board exams, but it is also written for the education of a first time baccalaureate degree reader in the biological sciences.  Hopefully, it can be read with great interest by the undergraduate student who is undecided in the choice of a career. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation. The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012.  All new articles on this subject, will continue to be incorporated, as published with periodical updates.

We invite e-Readers to write an Article Reviews on Amazon for this e-Book on Amazon.

All forthcoming BioMed e-Book Titles can be viewed at:

http://pharmaceuticalintelligence.com/biomed-e-books/

Leaders in Pharmaceutical Business Intelligence, launched in April 2012 an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of  life sciences, pharmaceutical, healthcare & medicine industries. The venture operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and for curation and reporting on frontiers in biomedical, biological sciences, healthcare economics, pharmacology, pharmaceuticals & medicine. In addition the venture publishes a Medical E-book Series available on Amazon’s Kindle platform.

Analyzing and sharing the vast and rapidly expanding volume of scientific knowledge has never been so crucial to innovation in the medical field. WE are addressing need of overcoming this scientific information overload by:

  • delivering curation and summary interpretations of latest findings and innovations on an open-access, Web 2.0 platform with future goals of providing primarily concept-driven search in the near future
  • providing a social platform for scientists and clinicians to enter into discussion using social media
  • compiling recent discoveries and issues in yearly-updated Medical E-book Series on Amazon’s mobile Kindle platform

This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Table of Contents for Metabolic Genomics & Pharmaceutics, Vol. I

Chapter 1: Metabolic Pathways

Chapter 2: Lipid Metabolism

Chapter 3: Cell Signaling

Chapter 4: Protein Synthesis and Degradation

Chapter 5: Sub-cellular Structure

Chapter 6: Proteomics

Chapter 7: Metabolomics

Chapter 8:  Impairments in Pathological States: Endocrine Disorders; Stress

                   Hypermetabolism and Cancer

Chapter 9: Genomic Expression in Health and Disease 

 

Summary 

Epilogue

 

 

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Cancer Biology and Genomics for Disease Diagnosis (Vol. I) Now Available for Amazon Kindle

Cancer Biology and Genomics for Disease Diagnosis (Vol. I) Now Available for Amazon Kindle

Reporter: Stephen J Williams, PhD

Article ID #179: Cancer Biology and Genomics for Disease Diagnosis (Vol. I) Now Available for Amazon Kindle. Published on 8/14/2015

WordCloud Image Produced by Adam Tubman

Leaders in Pharmaceutical Business Intelligence would like to announce the First volume of their BioMedical E-Book Series C: e-Books on Cancer & Oncology

Volume One: Cancer Biology and Genomics for Disease Diagnosis

CancerandOncologyseriesCcoverwhich is now available on Amazon Kindle at                          http://www.amazon.com/dp/B013RVYR2K.

This e-Book is a comprehensive review of recent Original Research on Cancer & Genomics including related opportunities for Targeted Therapy written by Experts, Authors, Writers. This ebook highlights some of the recent trends and discoveries in cancer research and cancer treatment, with particular attention how new technological and informatics advancements have ushered in paradigm shifts in how we think about, diagnose, and treat cancer. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation. The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012.  All new articles on this subject, will continue to be incorporated, as published with periodical updates.

We invite e-Readers to write an Article Reviews on Amazon for this e-Book on Amazon. All forthcoming BioMed e-Book Titles can be viewed at:

http://pharmaceuticalintelligence.com/biomed-e-books/

Leaders in Pharmaceutical Business Intelligence, launched in April 2012 an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of  life sciences, pharmaceutical, healthcare & medicine industries. The venture operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and for curation and reporting on frontiers in biomedical, biological sciences, healthcare economics, pharmacology, pharmaceuticals & medicine. In addition the venture publishes a Medical E-book Series available on Amazon’s Kindle platform.

Analyzing and sharing the vast and rapidly expanding volume of scientific knowledge has never been so crucial to innovation in the medical field. WE are addressing need of overcoming this scientific information overload by:

  • delivering curation and summary interpretations of latest findings and innovations
  • on an open-access, Web 2.0 platform with future goals of providing primarily concept-driven search in the near future
  • providing a social platform for scientists and clinicians to enter into discussion using social media
  • compiling recent discoveries and issues in yearly-updated Medical E-book Series on Amazon’s mobile Kindle platform

This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Table of Contents for Cancer Biology and Genomics for Disease Diagnosis

Preface

Introduction  The evolution of cancer therapy and cancer research: How we got here?

Part I. Historical Perspective of Cancer Demographics, Etiology, and Progress in Research

Chapter 1:  The Occurrence of Cancer in World Populations

Chapter 2.  Rapid Scientific Advances Changes Our View on How Cancer Forms

Chapter 3:  A Genetic Basis and Genetic Complexity of Cancer Emerge

Chapter 4: How Epigenetic and Metabolic Factors Affect Tumor Growth

Chapter 5: Advances in Breast and Gastrointestinal Cancer Research Supports Hope for Cure

Part II. Advent of Translational Medicine, “omics”, and Personalized Medicine Ushers in New Paradigms in Cancer Treatment and Advances in Drug Development

Chapter 6:  Treatment Strategies

Chapter 7:  Personalized Medicine and Targeted Therapy

Part III.Translational Medicine, Genomics, and New Technologies Converge to Improve Early Detection

Chapter 8:  Diagnosis                                     

Chapter 9:  Detection

Chapter 10:  Biomarkers

Chapter 11:  Imaging In Cancer

Chapter 12: Nanotechnology Imparts New Advances in Cancer Treatment, Detection, &  Imaging                                 

Epilogue by Larry H. Bernstein, MD, FACP: Envisioning New Insights in Cancer Translational Biology

 

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Treatment for Chronic Leukemias [2.4.4B]

Larry H. Bernstein, MD, FCAP, Author, Curator, Editor

http://pharmaceuticalintelligence.com/2015/8/11/larryhbern/Treatment-for-Chronic-Leukemias-[2.4.4B]

2.4.4B1 Treatment for CML

Chronic Myelogenous Leukemia Treatment (PDQ®)

http://www.cancer.gov/cancertopics/pdq/treatment/CML/Patient/page4

Treatment Option Overview

Key Points for This Section

There are different types of treatment for patients with chronic myelogenous leukemia.

Six types of standard treatment are used:

  1. Targeted therapy
  2. Chemotherapy
  3. Biologic therapy
  4. High-dose chemotherapy with stem cell transplant
  5. Donor lymphocyte infusion (DLI)
  6. Surgery

New types of treatment are being tested in clinical trials.

Patients may want to think about taking part in a clinical trial.

Patients can enter clinical trials before, during, or after starting their cancer treatment.

Follow-up tests may be needed.

There are different types of treatment for patients with chronic myelogenous leukemia.

Different types of treatment are available for patients with chronic myelogenous leukemia (CML). Some treatments are standard (the currently used treatment), and some are being tested in clinical trials. A treatment clinical trial is a research study meant to help improve current treatments or obtain information about new treatments for patients with cancer. When clinical trials show that a new treatment is better than the standard treatment, the new treatment may become the standard treatment. Patients may want to think about taking part in a clinical trial. Some clinical trials are open only to patients who have not started treatment.

Six types of standard treatment are used:

Targeted therapy

Targeted therapy is a type of treatment that uses drugs or other substances to identify and attack specific cancer cells without harming normal cells. Tyrosine kinase inhibitors are targeted therapy drugs used to treat chronic myelogenous leukemia.

Imatinib mesylate, nilotinib, dasatinib, and ponatinib are tyrosine kinase inhibitors that are used to treat CML.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Chemotherapy

Chemotherapy is a cancer treatment that uses drugs to stop the growth of cancer cells, either by killing the cells or by stopping them from dividing. When chemotherapy is taken by mouth or injected into a vein or muscle, the drugs enter the bloodstream and can reach cancer cells throughout the body (systemic chemotherapy). When chemotherapy is placed directly into the cerebrospinal fluid, an organ, or a body cavity such as the abdomen, the drugs mainly affect cancer cells in those areas (regional chemotherapy). The way the chemotherapy is given depends on the type and stage of the cancer being treated.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Biologic therapy

Biologic therapy is a treatment that uses the patient’s immune system to fight cancer. Substances made by the body or made in a laboratory are used to boost, direct, or restore the body’s natural defenses against cancer. This type of cancer treatment is also called biotherapy or immunotherapy.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

High-dose chemotherapy with stem cell transplant

High-dose chemotherapy with stem cell transplant is a method of giving high doses of chemotherapy and replacing blood-forming cells destroyed by the cancer treatment. Stem cells (immature blood cells) are removed from the blood or bone marrow of the patient or a donor and are frozen and stored. After the chemotherapy is completed, the stored stem cells are thawed and given back to the patient through an infusion. These reinfused stem cells grow into (and restore) the body’s blood cells.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Donor lymphocyte infusion (DLI)

Donor lymphocyte infusion (DLI) is a cancer treatment that may be used after stem cell transplant.Lymphocytes (a type of white blood cell) from the stem cell transplant donor are removed from the donor’s blood and may be frozen for storage. The donor’s lymphocytes are thawed if they were frozen and then given to the patient through one or more infusions. The lymphocytes see the patient’s cancer cells as not belonging to the body and attack them.

Surgery

Splenectomy

What`s new in chronic myeloid leukemia research and treatment?

http://www.cancer.org/cancer/leukemia-chronicmyeloidcml/detailedguide/leukemia-chronic-myeloid-myelogenous-new-research

Combining the targeted drugs with other treatments

Imatinib and other drugs that target the BCR-ABL protein have proven to be very effective, but by themselves these drugs don’t help everyone. Studies are now in progress to see if combining these drugs with other treatments, such as chemotherapy, interferon, or cancer vaccines (see below) might be better than either one alone. One study showed that giving interferon with imatinib worked better than giving imatinib alone. The 2 drugs together had more side effects, though. It is also not clear if this combination is better than treatment with other tyrosine kinase inhibitors (TKIs), such as dasatinib and nilotinib. A study going on now is looking at combing interferon with nilotinib.

Other studies are looking at combining other drugs, such as cyclosporine or hydroxychloroquine, with a TKI.

New drugs for CML

Because researchers now know the main cause of CML (the BCR-ABL gene and its protein), they have been able to develop many new drugs that might work against it.

In some cases, CML cells develop a change in the BCR-ABL oncogene known as a T315I mutation, which makes them resistant to many of the current targeted therapies (imatinib, dasatinib, and nilotinib). Ponatinib is the only TKI that can work against T315I mutant cells. More drugs aimed at this mutation are now being tested.

Other drugs called farnesyl transferase inhibitors, such as lonafarnib and tipifarnib, seem to have some activity against CML and patients may respond when these drugs are combined with imatinib. These drugs are being studied further.

Other drugs being studied in CML include the histone deacetylase inhibitor panobinostat and the proteasome inhibitor bortezomib (Velcade).

Several vaccines are now being studied for use against CML.

2.4.4.B2 Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia Treatment (PDQ®)

General Information About Chronic Lymphocytic Leukemia

Key Points for This Section

  1. Chronic lymphocytic leukemia is a type of cancer in which the bone marrow makes too many lymphocytes (a type of white blood cell).
  2. Leukemia may affect red blood cells, white blood cells, and platelets.
  3. Older age can affect the risk of developing chronic lymphocytic leukemia.
  4. Signs and symptoms of chronic lymphocytic leukemia include swollen lymph nodes and tiredness.
  5. Tests that examine the blood, bone marrow, and lymph nodes are used to detect (find) and diagnose chronic lymphocytic leukemia.
  6. Certain factors affect treatment options and prognosis (chance of recovery).
  7. Chronic lymphocytic leukemia is a type of cancer in which the bone marrow makes too many lymphocytes (a type of white blood cell).

Chronic lymphocytic leukemia (also called CLL) is a blood and bone marrow disease that usually gets worse slowly. CLL is one of the most common types of leukemia in adults. It often occurs during or after middle age; it rarely occurs in children.

http://www.cancer.gov/images/cdr/live/CDR755927-750.jpg

Anatomy of the bone; drawing shows spongy bone, red marrow, and yellow marrow. A cross section of the bone shows compact bone and blood vessels in the bone marrow. Also shown are red blood cells, white blood cells, platelets, and a blood stem cell.

Anatomy of the bone. The bone is made up of compact bone, spongy bone, and bone marrow. Compact bone makes up the outer layer of the bone. Spongy bone is found mostly at the ends of bones and contains red marrow. Bone marrow is found in the center of most bones and has many blood vessels. There are two types of bone marrow: red and yellow. Red marrow contains blood stem cells that can become red blood cells, white blood cells, or platelets. Yellow marrow is made mostly of fat.

Leukemia may affect red blood cells, white blood cells, and platelets.

Normally, the body makes blood stem cells (immature cells) that become mature blood cells over time. A blood stem cell may become a myeloid stem cell or a lymphoid stem cell.

A myeloid stem cell becomes one of three types of mature blood cells:

  1. Red blood cells that carry oxygen and other substances to all tissues of the body.
  2. White blood cells that fight infection and disease.
  3. Platelets that form blood clots to stop bleeding.

A lymphoid stem cell becomes a lymphoblast cell and then one of three types of lymphocytes (white blood cells):

  1. B lymphocytes that make antibodies to help fight infection.
  2. T lymphocytes that help B lymphocytes make antibodies to fight infection.
  3. Natural killer cells that attack cancer cells and viruses.

Blood cell development. CDR526538-750

Blood cell development. CDR526538-750

http://www.cancer.gov/images/cdr/live/CDR526538-750.jpg

Blood cell development; drawing shows the steps a blood stem cell goes through to become a red blood cell, platelet, or white blood cell. A myeloid stem cell becomes a red blood cell, a platelet, or a myeloblast, which then becomes a granulocyte (the types of granulocytes are eosinophils, basophils, and neutrophils). A lymphoid stem cell becomes a lymphoblast and then becomes a B-lymphocyte, T-lymphocyte, or natural killer cell.

Blood cell development. A blood stem cell goes through several steps to become a red blood cell, platelet, or white blood cell.

In CLL, too many blood stem cells become abnormal lymphocytes and do not become healthy white blood cells. The abnormal lymphocytes may also be called leukemia cells. The lymphocytes are not able to fight infection very well. Also, as the number of lymphocytes increases in the blood and bone marrow, there is less room for healthy white blood cells, red blood cells, and platelets. This may cause infection, anemia, and easy bleeding.

This summary is about chronic lymphocytic leukemia. See the following PDQ summaries for more information about leukemia:

  • Adult Acute Lymphoblastic Leukemia Treatment.
  • Childhood Acute Lymphoblastic Leukemia Treatment.
  • Adult Acute Myeloid Leukemia Treatment.
  • Childhood Acute Myeloid Leukemia/Other Myeloid Malignancies Treatment.
  • Chronic Myelogenous Leukemia Treatment.
  • Hairy Cell Leukemia Treatment

Older age can affect the risk of developing chronic lymphocytic leukemia.

Anything that increases your risk of getting a disease is called a risk factor. Having a risk factor does not mean that you will get cancer; not having risk factors doesn’t mean that you will not get cancer. Talk with your doctor if you think you may be at risk. Risk factors for CLL include the following:

  • Being middle-aged or older, male, or white.
  • A family history of CLL or cancer of the lymph system.
  • Having relatives who are Russian Jews or Eastern European Jews.

Signs and symptoms of chronic lymphocytic leukemia include swollen lymph nodes and tiredness.

Usually CLL does not cause any signs or symptoms and is found during a routine blood test. Signs and symptoms may be caused by CLL or by other conditions. Check with your doctor if you have any of the following:

  • Painless swelling of the lymph nodes in the neck, underarm, stomach, or groin.
  • Feeling very tired.
  • Pain or fullness below the ribs.
  • Fever and infection.
  • Weight loss for no known reason.

Tests that examine the blood, bone marrow, and lymph nodes are used to detect (find) and diagnose chronic lymphocytic leukemia.

The following tests and procedures may be used:

Physical exam and history : An exam of the body to check general signs of health, including checking for signs of disease, such as lumps or anything else that seems unusual. A history of the patient’s health habits and past illnesses and treatments will also be taken.

Complete blood count (CBC) with differential : A procedure in which a sample of blood is drawn and checked for the following:

The number of red blood cells and platelets.

The number and type of white blood cells.

The amount of hemoglobin (the protein that carries oxygen) in the red blood cells.

The portion of the blood sample made up of red blood cells.

Results from the Phase 3 Resonate™ Trial

Significantly improved progression free survival (PFS) vs ofatumumab in patients with previously treated CLL

  • Patients taking IMBRUVICA® had a 78% statistically significant reduction in the risk of disease progression or death compared with patients who received ofatumumab1
  • In patients with previously treated del 17p CLL, median PFS was not yet reached with IMBRUVICA® vs 5.8 months with ofatumumab (HR 0.25; 95% CI: 0.14, 0.45)1

Significantly prolonged overall survival (OS) with IMBRUVICA® vs ofatumumab in patients with previously treated CLL

  • In patients with previously treated CLL, those taking IMBRUVICA® had a 57% statistically significant reduction in the risk of death compared with those who received ofatumumab (HR 0.43; 95% CI: 0.24, 0.79; P<0.05)1

Typical treatment of chronic lymphocytic leukemia

http://www.cancer.org/cancer/leukemia-chroniclymphocyticcll/detailedguide/leukemia-chronic-lymphocytic-treating-treatment-by-risk-group

Treatment options for chronic lymphocytic leukemia (CLL) vary greatly, depending on the person’s age, the disease risk group, and the reason for treating (for example, which symptoms it is causing). Many people live a long time with CLL, but in general it is very difficult to cure, and early treatment hasn’t been shown to help people live longer. Because of this and because treatment can cause side effects, doctors often advise waiting until the disease is progressing or bothersome symptoms appear, before starting treatment.

If treatment is needed, factors that should be taken into account include the patient’s age, general health, and prognostic factors such as the presence of chromosome 17 or chromosome 11 deletions or high levels of ZAP-70 and CD38.

Initial treatment

Patients who might not be able to tolerate the side effects of strong chemotherapy (chemo), are often treated with chlorambucil alone or with a monoclonal antibody targeting CD20 like rituximab (Rituxan) or obinutuzumab (Gazyva). Other options include rituximab alone or a corticosteroid like prednisione.

In stronger and healthier patients, there are many options for treatment. Commonly used treatments include:

  • FCR: fludarabine (Fludara), cyclophosphamide (Cytoxan), and rituximab
  • Bendamustine (sometimes with rituximab)
  • FR: fludarabine and rituximab
  • CVP: cyclophosphamide, vincristine, and prednisone (sometimes with rituximab)
  • CHOP: cyclophosphamide, doxorubicin, vincristine (Oncovin), and prednisone
  • Chlorambucil combined with prednisone, rituximab, obinutuzumab, or ofatumumab
  • PCR: pentostatin (Nipent), cyclophosphamide, and rituximab
  • Alemtuzumab (Campath)
  • Fludarabine (alone)

Other drugs or combinations of drugs may also be also used.

If the only problem is an enlarged spleen or swollen lymph nodes in one region of the body, localized treatment with low-dose radiation therapy may be used. Splenectomy (surgery to remove the spleen) is another option if the enlarged spleen is causing symptoms.

Sometimes very high numbers of leukemia cells in the blood cause problems with normal circulation. This is calledleukostasis. Chemo may not lower the number of cells until a few days after the first dose, so before the chemo is given, some of the cells may be removed from the blood with a procedure called leukapheresis. This treatment lowers blood counts right away. The effect lasts only for a short time, but it may help until the chemo has a chance to work. Leukapheresis is also sometimes used before chemo if there are very high numbers of leukemia cells (even when they aren’t causing problems) to prevent tumor lysis syndrome (this was discussed in the chemotherapy section).

Some people who have very high-risk disease (based on prognostic factors) may be referred for possible stem cell transplant (SCT) early in treatment.

Second-line treatment of CLL

If the initial treatment is no longer working or the disease comes back, another type of treatment may help. If the initial response to the treatment lasted a long time (usually at least a few years), the same treatment can often be used again. If the initial response wasn’t long-lasting, using the same treatment again isn’t as likely to be helpful. The options will depend on what the first-line treatment was and how well it worked, as well as the person’s health.

Many of the drugs and combinations listed above may be options as second-line treatments. For many people who have already had fludarabine, alemtuzumab seems to be helpful as second-line treatment, but it carries an increased risk of infections. Other purine analog drugs, such as pentostatin or cladribine (2-CdA), may also be tried. Newer drugs such as ofatumumab, ibrutinib (Imbruvica), and idelalisib (Zydelig) may be other options.

If the leukemia responds, stem cell transplant may be an option for some patients.

Some people may have a good response to first-line treatment (such as fludarabine) but may still have some evidence of a small number of leukemia cells in the blood, bone marrow, or lymph nodes. This is known as minimal residual disease. CLL can’t be cured, so doctors aren’t sure if further treatment right away will be helpful. Some small studies have shown that alemtuzumab can sometimes help get rid of these remaining cells, but it’s not yet clear if this improves survival.

Treating complications of CLL

One of the most serious complications of CLL is a change (transformation) of the leukemia to a high-grade or aggressive type of non-Hodgkin lymphoma called diffuse large cell lymphoma. This happens in about 5% of CLL cases, and is known as Richter syndrome. Treatment is often the same as it would be for lymphoma (see our document called Non-Hodgkin Lymphoma for more information), and may include stem cell transplant, as these cases are often hard to treat.

Less often, CLL may transform to prolymphocytic leukemia. As with Richter syndrome, these cases can be hard to treat. Some studies have suggested that certain drugs such as cladribine (2-CdA) and alemtuzumab may be helpful.

In rare cases, patients with CLL may have their leukemia transform into acute lymphocytic leukemia (ALL). If this happens, treatment is likely to be similar to that used for patients with ALL (see our document called Leukemia: Acute Lymphocytic).

Acute myeloid leukemia (AML) is another rare complication in patients who have been treated for CLL. Drugs such as chlorambucil and cyclophosphamide can damage the DNA of blood-forming cells. These damaged cells may go on to become cancerous, leading to AML, which is very aggressive and often hard to treat (see our document calledLeukemia: Acute Myeloid).

CLL can cause problems with low blood counts and infections. Treatment of these problems were discussed in the section “Supportive care in chronic lymphocytic leukemia.”

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Hematologic Malignancies , Table of Contents

Writer and Curator:  Larry H. Bernstein, MD, FCAP

Hematologic Malignancies 

Not excluding lymphomas [solid tumors]

The following series of articles are discussions of current identifications, classification, and treatments of leukemias, myelodysplastic syndromes and myelomas.

2.4 Hematological Malignancies

2.4.1 Ontogenesis of blood elements

Erythropoiesis

White blood cell series: myelopoiesis

Thrombocytogenesis

2.4.2 Classification of hematopoietic cancers

Primary Classification

Acute leukemias

Myelodysplastic syndromes

Acute myeloid leukemia

Acute lymphoblastic leukemia

Myeloproliferative Disorders

Chronic myeloproliferative disorders

Chronic myelogenous leukemia and related disorders

Myelofibrosis, including chronic idiopathic

Polycythemia, including polycythemia rubra vera

Thrombocytosis, including essential thrombocythemia

Chronic lymphoid leukemia and other lymphoid leukemias

Lymphomas

Non-Hodgkin Lymphoma

Hodgkin lymphoma

Lymphoproliferative disorders associated with immunodeficiency

Plasma Cell dyscrasias

Mast cell disease and Histiocytic neoplasms

Secondary Classification

Nuance – PathologyOutlines

2.4.3 Diagnostics

Computer-aided diagnostics

Back-to-Front Design

Realtime Clinical Expert Support

Regression: A richly textured method for comparison and classification of predictor variables

Converting Hematology Based Data into an Inferential Interpretation

A model for Thalassemia Screening using Hematology Measurements

Measurement of granulocyte maturation may improve the early diagnosis of the septic state.

The automated malnutrition assessment.

Molecular Diagnostics

Genomic Analysis of Hematological Malignancies

Next-generation sequencing in hematologic malignancies: what will be the dividends?

Leveraging cancer genome information in hematologic malignancies.

p53 mutations are associated with resistance to chemotherapy and short survival in hematologic malignancies

Genomic approaches to hematologic malignancies

2.4.4 Treatment of hematopoietic cancers

2.4.4.1 Treatments for leukemia by type

2.4.4..2 Acute lymphocytic leukemias

2.4..4.3 Treatment of Acute Lymphoblastic Leukemia

Acute Lymphoblastic Leukemia

Gene-Expression Patterns in Drug-Resistant Acute Lymphoblastic Leukemia Cells and Response to Treatment

Leukemias Treatment & Management

Treatments and drugs

2.4.5 Acute Myeloid Leukemia

New treatment approaches in acute myeloid leukemia: review of recent clinical studies

Novel approaches to the treatment of acute myeloid leukemia.

Current treatment of acute myeloid leukemia

Adult Acute Myeloid Leukemia Treatment (PDQ®)

2.4.6 Treatment for CML

Chronic Myelogenous Leukemia Treatment (PDQ®)

What`s new in chronic myeloid leukemia research and treatment?

4.2.7 Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia Treatment (PDQ®)

Results from the Phase 3 Resonate™ Trial

Typical treatment of chronic lymphocytic leukemia

4.2.8 Lymphoma treatment

4.2.8.1 Overview

4.2.8.2 Chemotherapy

………………………………..

Chapter 6

Total body irradiation (TBI)

Bone marrow (BM) transplantation

Autologous stem cell transplantation

Hematopoietic stem cell transplantation

Supportive Therapies

Blood transfusions

Erythropoietin

G-CSF (granulocyte-colony stimulating factor)

Plasma exchange (plasmapheresis)

Platelet transfusions

Steroids

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SACHS FLYER 2014 Metabolomics SeriesDindividualred-page2

We welcome Book Reviews on Amazon.com

Metabolic Genomics & Pharmaceutics

Volume Author, Curator, Editor

Larry H Bernstein, MD, FCAP

Leaders in Pharmaceutical Business Intelligence

http://www.amazon.com/dp/B012BB0ZF0

Introduction

Chapter 1: Metabolic Pathways

Chapter 2: Lipid Metabolism

Chapter 3: Cell Signaling

Chapter 4: Protein Synthesis and Degradation

Chapter 5:  Sub-cellular Structure

Chapter 6: Proteomics

Chapter 7: Metabolomics

Chapter 8.  Impairments in Pathological States: Endocrine Disorders; Stress Hypermetabolism and Cancer

Chapter 9: Genomic Expression in Health and Disease 

Summary 

Epilogue

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Nonhematologic Cancer Stem Cells [11.2.3]

Writer and Curator: Larry H. Bernstein, MD, FCAP 

Nonhematologic Stem Cells

11.2.3.1 C8orf4 negatively regulates self-renewal of liver cancer stem cells via suppression of NOTCH2 signalling

Pingping Zhu, Yanying Wang, Ying Du, Lei He, Guanling Huang, et al.
Nature Communications May 2015; 6(7122). http://dx.doi.org:/10.1038/ncomms8122

Liver cancer stem cells (CSCs) harbor self-renewal and differentiation properties, accounting for chemotherapy resistance and recurrence. However, the molecular mechanisms to sustain liver CSCs remain largely unknown. In this study, based on analysis of several hepatocellular carcinoma (HCC) transcriptome datasets and our experimental data, we find that C8orf4 is weakly expressed in HCC tumors and liver CSCs. C8orf4 attenuates the self-renewal capacity of liver CSCs and tumor propagation. We show that NOTCH2 is activated in liver CSCs. C8orf4 is located in the cytoplasm of HCC tumor cells and associates with the NOTCH2 intracellular domain, which impedes the nuclear translocation of N2ICD. C8orf4 deletion causes the nuclear translocation of N2ICD that triggers the NOTCH2 signaling, which sustains the stemness of liver CSCs. Finally, NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Altogether, C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signaling.

Like stem cells, CSCs are characterized by self-renewal and differentiation simultaneously9. Not surprisingly, CSCs share core regulatory genes and developmental pathways with normal tissue stem cells. Accumulating evidence shows that NOTCH, Hedgehog and Wnt signaling pathways are implicated in the regulation of CSC self-renewal4. NOTCH signaling modulates many aspects of metazoan development and tissue stemness1011. NOTCH receptors contain four members (NOTCH1–4) in mammals, which are activated by engagement with various ligands. The aberrant NOTCH signaling was first reported to be involved in the tumorigenesis of human T-cell leukaemia1213. Recently, a number of studies have reported that the NOTCH signaling pathway is implicated in regulating self-renewal of breast stem cells and mammary CSCs1415. However, how the NOTCH signaling regulates the liver CSC self-renewal remains largely unknown.

C8orf4, also called thyroid cancer 1 (TC1), was originally cloned from a papillary thyroid carcinoma and its surrounding normal thyroid tissue16. C8orf4 is ubiquitously expressed across a wide range of vertebrates with the sequence conservation across species. A number of studies have reported that C8orf4 is highly expressed in several tumors and implicated in tumorigenesis171819. In addition, C8orf4 augments Wnt/β-catenin signaling in some cancer cells2021, suggesting it may be involved in the regulation of self-renewal of CSCs. However, the biological function of C8orf4 in the modulation of liver CSC self-renewal is still unknown. Here we show that C8orf4 is weakly expressed in HCC and liver CSCs. NOTCH2 signaling is highly activated in HCC tumors and liver CSCs. C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signaling.

C8orf4 is weakly expressed in HCC tissues and liver CSCs

To search for driver genes in the oncogenesis of HCC, we performed genome-wide analyses using several online-available HCC transcriptome datasets by R language and Bioconductor approaches. After analysing gene expression profiles of HCC tumor and peri-tumor tissues, we identified >360 differentially expressed genes from both Park’s cohort (GSE36376; ref. 22) and Wang’s cohort (GSE14520; refs 2324). Of these changed genes, we focused on C8orf4, which was weakly expressed in HCC tumors derived from both Park’s cohort (GSE36376) and Wang’s cohort (GSE14520) (Fig. 1a). Lower expression of C8orf4 was further confirmed in HCC samples by quantitative reverse transcription–PCR (qRT–PCR) and immunoblotting (Fig. 1b,c). In this study, HCC patient samples we used included all subtypes of HCC. In addition, these observations were further validated by immunohistochemical (IHC) staining (Fig. 1d). These data indicate that C8orf4 is weakly expressed in HCC tumor tissues.

C8orf4 is weakly expressed in HCC tumours and liver CSCs

C8orf4 is weakly expressed in HCC tumours and liver CSCs

Figure 1. C8orf4 is weakly expressed in HCC tumours and liver CSCs

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f1.jpg

(a)C8orf4 is weakly expressed in HCC patients. Using R language and Bioconductor methods, we analyzed C8orf4 expression in HCC tumor and peri-tumor tissues provided by Park’s cohort (GSE36376) and Wang’s cohort (GSE14520) datasets. (b,c) C8orf4 expression levels were verified in HCC patient samples by quantitative RT–PCR (qRT–PCR) (b) and immunoblotting (c). β-actin served as a loading control. 18S: 18S rRNA. (d) HCC samples were assayed by immunohistochemical staining. Scale bar—left: 50 μm; right: 20 μm. (eC8orf4 is weakly expressed in CD13+CD133+ cells sorted from Huh7 cells and primary HCC samples. C8orf4 messenger RNA (mRNA) was measured by qRT–PCR. Six HCC samples got similar results. (fC8orf4 is much more weakly expressed in oncospheres than non-sphere tumor cells. Non-sphere: Huh7 or HCC primary cells that failed to form spheres. (g) HCC sample tissues were co-stained with anti-C8orf4 and anti-CD13 or anti-CD133 antibodies, then counterstained with DAPI for confocal microscopy. White arrows indicate CD13+ or CD133+ cells. Scale bars: 20 μm. For a,b, data are shown as box and whisker plot. Boxes represent interquartile range (IQR); upper and lower edge corresponds to the 75th and 25th percentiles, respectively. Horizontal lines within boxes represent median levels of gene intensity. Whiskers below and above boxes extend to the 5th and 95th percentiles, respectively. For e and f, Student’s t-test was used for statistical analysis, *P<0.05;**P<0.01, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments. P, peri-tumor; T, tumor.

 

Notably, C8orf4 was also weakly expressed in embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) by analysis of its expression profiles derived from online datasets (GSE14897; ref. 25 and GSE25417; ref. 26) (Supplementary Fig. 1a,b). C8orf4 was also lowly expressed in normal liver stem cells (Supplementary Fig. 1c,d), suggesting that C8orf4 may be involved in the regulation of self-renewal of liver stem cells. Thus, we propose that C8orf4 might play a role in the maintenance of liver CSCs. Since CD13 and CD133 were widely used as liver CSC surface markers, we sorted CD13+CD133+ cells from Huh7 and Hep3B HCC cell lines as well as HCC samples, serving as liver CSCs. We observed that C8orf4 was weakly expressed in liver CSCs enriched from both HCC cell lines and patient samples (Fig. 1e). Six HCC samples were analyzed for these experiments. Similar results were obtained in CD13+CD133+ cells from Hep3B cells. Furthermore, we performed sphere formation experiments using Huh7 cells and HCC primary sample cells, and detected expression levels of C8orf4. We observed that C8orf4 was dramatically reduced in the oncospheres generated by both HCC cell lines and patient samples (Fig. 1f). In addition, we noticed that C8orf4 expression was negatively correlated with liver CSC markers such as CD13 and CD133 in HCC samples (Fig. 1g), suggesting lower expression of C8orf4 in liver CSCs. Moreover, C8orf4 was mainly located in the cytoplasm of tumour cells. Altogether, C8orf4 is weakly expressed in HCC tumor tissues and liver CSCs.

C8orf4 negatively regulates self-renewal of liver CSCs

We then wanted to look at whether C8orf4 plays a critical role in the self-renewal maintenance of liver CSCs. C8orf4 was knocked out in Huh7 cells through a CRISPR/Cas9 system (Fig. 2a). TwoC8orf4-knockout (KO) cell strains were established and C8orf4 was completely deleted in these two strains. C8orf4 deletion dramatically enhanced oncosphere formation (Fig. 2b). We co-stained SOX9, a widely used progenitor marker, and Ki67, a well-known proliferation marker, in C8orf4 KO sphere cells. We found that SOX9 was strongly stained in C8orf4 KO sphere cells (Supplementary Fig. 2a). In contrast, Ki67 staining was not significantly altered in C8orf4 KO sphere cells versus WT sphere cells. We also digested sphere cells and examined the SOX9 and Ki67 expression by flow cytometry. Similar results were achieved (Supplementary Fig. 2b). Importantly, through serial passage of CSC sphere cells, similar observations were obtained in the fourth generation oncosphere assay (Supplementary Fig. 2c,d). These data suggest that C8orf4 is involved in the regulation of liver CSC self-renewal.

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Figure 2: C8orf4 knockout enhances self-renewal of liver CSCs.

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  • C8orf4-deficient Huh7 cells were established using a CRISPR/Cas9 system. T7 endonuclease I cleavage confirmed the efficiency of sgRNA (left panel, white arrowheads), and C8orf4-knockout efficiency was confirmed by western blot (right panel). Two knockout cell lines were used.  C8KO#1:C8orf4KO#1;  C8KO#2C8orf4KO#2. (bC8orf4-deficient cells enhanced sphere formation activity. Calculated ratios are shown in the right panel. (cC8orf4-deficient or WT Huh7 cells (1 × 106) were injected into BALB/c nude mice. Tumor sizes were observed every 5 days. (dC8orf4 deficiency enhances tumor-initiating capacity. Diluted cell numbers of Huh7 cells were implanted into BALB/c nude mice for tumor initiation. Percentages of tumor-formation mice were calculated (left panel), and frequency of tumor-initiating cells was calculated using extreme limiting dilution analysis (right panel). Error bars represent the 95% confidence intervals of the estimation. (e) Expression levels of CD13 andCD133 were analyzed in C8orf4-knockout Huh7 cells. (f) C8orf4 was silenced in HCC primary cells and C8orf4 depletion enhanced sphere formation activity. Calculated ratios are shown at the right panel. Three HCC specimens obtained similar results. (g) C8orf4-overexpressing Huh7 cells were established (left panel). C8orf4-overexpressing Huh7 cells and control Huh7 cells were cultured for sphere formation. (h,i) Xenograft tumor growth (h) and frequency of tumor-initiating cells (i) for C8orf4-overexpressing Huh7 cells were analyzed as c,d. (j) C8orf4 overexpression reduces expression of CD133 and CD13 in Huh7 cells. (k) C8orf4 was transfected in HCC primary cells and cultured for sphere formation. Three HCC patient samples obtained similar results. Scale bars: b,f,g,k, 500 μm. Student’s t-test was used for statistical analysis,    *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data represent at least three independent experiments. oeC8orf4, overexpression of C8orf4; oeVec, overexpression vector.

In addition, C8orf4-deficient Huh7 cells overtly increased xenograft tumour growth (Fig. 2c). We then performed sphere formation and digested oncospheres formed by C8orf4-deficient or WT cells into single-cell suspension, then subcutaneously implanted 1 × 104, 1 × 103, 1 × 102 and 10 cells into BALB/c nude mice. Tumour formation was examined for tumour-initiating capacity at the third month. C8orf4 deficiency remarkably enhanced tumour-initiating capacity and liver CSC ratios (Fig. 2d). In addition, C8orf4 deletion significantly enhanced expression levels of the liver CSC markers such as CD13 and CD133 (Fig. 2e). We also silenced C8orf4 in HCC primary cells using a lentivirus infection system and established C8orf4-silenced cells. Two pairs of short hairpin RNA (shRNA) sequences obtained similar knockdown efficiency. C8orf4 knockdown remarkably promoted sphere formation and xenograft tumour growth (Fig. 2f and Supplementary Fig. 2e). These data indicate that C8orf4 deletion potentiates the self-renewal of liver CSCs.
We next overexpressed C8orf4 in Huh7 cells and HCC primary cells using lentivirus infection. We observed that C8orf4 overexpression in Huh7 cells remarkably reduced sphere formation and xenograft tumour growth (Fig. 2g,h). In addition, C8orf4 overexpression remarkably reduced tumour-initiating capacity and expression of liver CSC markers (Fig. 2i,j). Similar results were observed by C8orf4 overexpression in HCC primary cells (Fig. 2k). We tested three HCC samples with similar results. Overall, C8orf4 negatively regulates the maintenance of liver CSC self-renewal and tumour propagation.

C8orf4 suppresses NOTCH2 signaling in liver CSCs

To further determine the underlying mechanism of C8orf4 in the regulation of liver CSCs, we analyzed three major self-renewal signaling pathways, including Wnt/β-catenin, Hedgehog and NOTCH pathways, in C8orf4-deleted Huh7 cells and HCC primary cells. We found that only NOTCH target genes were remarkably upregulated in C8orf4-deficient cells (Fig. 3a), whereasC8orf4 deficiency did not significantly affect the Wnt/β-catenin or the Hedgehog pathway. Given that the NOTCH family receptors have four members, we wanted to determine which NOTCH member was involved in the C8orf4-mediated suppression of liver CSC stemness. We noticed that only NOTCH2 was highly expressed in both Huh7 cells and HCC samples (Fig. 3b). In addition, this result was also confirmed by analysis of NOTCH expression levels derived from Wang’s cohort (GSE14520) and Petel’s cohort (E-TABM-36; ref. 27) (Fig. 3c). Moreover, we analysed expression profiles of C8orf4 and NOTCH target genes using Park’s cohort (GSE36376) and Wurmbach’s cohort (GSE6764; ref. 28). These cohort datasets provided several Notch signaling and its target genes. HEY1NRARP and HES6 genes were highly expressed in HCC tumour tissues (GSE6764; ref. 28), which were further confirmed in HCC samples by real-time PCR (Supplementary Fig. 3a,b). Furthermore, HEY1NRARP and HES6 genes have been reported to be relatively specific NOTCH target genes. We then examined these three genes as the NOTCH2 target genes throughout this study. We found that the C8orf4 expression level was negatively correlated with the expression levels of HEY1 and HES6, suggesting that C8orf4 inhibited NOTCH signaling in HCC patients (Fig. 3d). Finally these results were further confirmed in HCC samples by qRT-PCR (Fig. 3e). To further explore the activation status of NOTCH2 signaling in liver CSCs, we examined the expression levels of NOTCH downstream target genes in oncospheres and CD13+CD133+ cells derived from both Huh7 cells and HCC cells. We observed that NOTCH target genes were highly expressed in liver CSCs (Fig. 3f,g). These observations were verified by immunoblotting (Fig. 3h). In addition, the expression levels of NRARPHES6 and HEY1 were positively related to the expression levels of EpCAM and CD133 derived from Zhang’s cohort (GSE25097; ref. 29) and Wang’s cohort (GSE14520; Supplementary Fig. 3c,d). These data suggest that the NOTCH2 signaling plays a critical role in the maintenance of self-renewal of liver CSCs.

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Figure 3: C8orf4 suppresses NOTCH2 signaling in liver CSCs.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f3.jpg

(aC8orf4 deficiency or depletion activates NOTCH signaling. The indicated major stemness signalling pathways were analysed in C8orf4-knockout Huh7 cells (left panel) and C8orf4-silenced primary cells of HCC samples (right panel). (b) Four receptor members of NOTCH family were examined in both Huh7 cells (left panel) and 29 pairs of HCC samples (right panel). (cNOTCH receptors were analyzed from Wang’s cohort (left panel) and Petel’s cohort (right panel) datasets. (dHEY1 and HES6 were highly expressed in C8orf4low samples by analysis of Park’s cohort (upper panel) and Wurmbach’s cohort (lower panel). (e) Expression levels of HEY1 and HES6 along with C8orf4 were analysed in HCC samples by qRT–PCR. (f,g) Expression levels of NRARPHEY1 and HES6 in spheres generated by Huh7 cells and HCC primary cells (f) and in CD13+CD133+ cells sorted from Huh7 cells and HCC primary cells (g). Non-sphere: Huh7 cells or HCC cells that failed to form spheres. (h) HEY1, HES6 and NRARP expression in sphere and non-sphere cells was detected by immunoblotting. β-actin was used as a loading control. For c,d, data are shown as box and whisker plot. Box: interquartile range (IQR); horizontal line within box: median; whiskers: 5–95 percentile. For a,b,f,g, Student’s t-test was used for statistical analysis, *P<0.05;**P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments.

C8orf4 interacts with NOTCH2 that is critical for liver CSCs

On ligand–receptor binding, the NOTCH receptor experiences a proteolytic cleavage by metalloprotease and γ-secretase, releasing a NOTCH extracellular domain (NECD) and a NOTCH intracellular domain (NICD), respectively30. Then the active NICD undergoes nuclear translocation and activates the expression of NOTCH downstream target genes31.Then we constructed the NOTCH2 extracellular domain (N2ECD) and intracellular domain (N2ICD) and examined the interaction with C8orf4 via a yeast two-hybrid approach. Interestingly, we found that C8orf4 interacted with N2ICD, but not N2ECD (Fig. 4a). The interaction was validated by co-immunoprecipitation (Fig. 4b). Through domain mapping, the ankyrin repeat domain of NOTCH2 was essential and sufficient for its association with C8orf4 (Fig. 4c). Taken together, C8orf4 interacts with the N2ICD domain of NOTCH2.

Figure 4: C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs.

C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs

C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f4.jpg

(a) C8orf4 interacts with N2ICD. Yeast strain AH109 was co-transfected with Gal4 DNA-binding domain (BD) fused C8orf4 and Gal4-activating domain (AD) fused N2ICD. p53 and large T antigen were used as a positive control. (b) Recombinant Flag-N2ICD and GFP–C8orf4 were incubated for co-immunoprecipitation. (c) The ankyrin repeat AR domain is essential and sufficient for the interaction of C8orf4 with N2ICD. Various N2ICD truncation constructs were co-transfected with GFP–C8orf4 for domain mapping. NLS: nuclear location signal. (d) NOTCH2 was knocked down in Huh7 cells and detected by qRT–PCR and immunoblotting. (e) NOTCH2-silenced Huh7 cells were cultured for sphere formation assays. Two pairs of shRNAs against NOTCH2 obtained similar results. (f,g) Xenograft tumor growth (f) and frequency of tumor-initiating cells (g) for NOTCH2-silenced Huh7 cells were analyzed. (h) NOTCH2 was silenced in HCC primary cells and NOTCH2 depletion declined sphere formation activity. Three HCC specimens obtained similar results. (i) Sphere formation capacity was examined in differently treated HCC primary cells. (j) HCC primary cells were treated with indicated lentivirus and implanted into BALB/c nude mice for xenograft tumor growth assays. Scale bars: e,h,i, 500 μm, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments. IB, immunoblotting; IP, immunoprecipitation; NS, not significant.

To further verify the role of NOTCH2 in the maintenance of liver CSC self-renewal, we knocked down NOTCH2 in Huh7 cells and established stably depleted cell lines by two pairs of NOTCH2 shRNAs (Fig. 4d). NOTCH2 knockdown dramatically reduced sphere formation (Fig. 4e), as well as attenuated xenograft tumor growth and tumor-initiating capacity (Fig. 4f,g). Similar observations were achieved in NOTCH2-depleted HCC primary cells (Fig. 4h). In addition, we found that simultaneous knockdown of NOTCH2 and overexpression of C8orf4 failed to reduce sphere formation capacity compared with individual knockdown of NOTCH2 (Fig. 4i), suggesting that NOTCH2 and C8orf4 affected sphere formation through the same pathway. Meanwhile, C8orf4 knockdown failed to rescue the sphere formation ability of NOTCH2-depleted HCC primary cells (Fig. 4i). Similar observations were obtained in Huh7 cells (Supplementary Fig. 4). Finally, NOTCH2 depletion in C8orf4-silenced Huh7 cells or HCC primary cells also abrogated the C8orf4 depletion-mediated enhancement of xenograft tumor growth (Fig. 4j), suggesting that C8orf4 acted as upstream of NOTCH2 signaling. These data suggest that C8orf4 suppresses the liver CSC stemness through inhibiting the NOTCH2 signaling pathway.

C8orf4 blocks nuclear translocation of N2ICD

As shown in Fig. 1g, C8orf4 was mainly localized in the cytoplasm in tumor cells of HCC samples. To confirm these observations, we stained C8orf4 in several HCC cell lines and noticed that C8orf4 also resided in the cytoplasm of Huh7 cells and Hep3B cells (Fig. 5a and Supplementary Fig. 5a). These results were further validated by cellular fractionation (Fig. 5b). Importantly, C8orf4 KO led to nuclear translocation of N2ICD (Fig. 5c). In addition, we also examined the intracellular location of N2ICD in Huh7 spheres. We found that C8orf4 deletion caused complete nuclear translocation of N2ICD in oncosphere cells (Fig. 5d,e), while N2ICD was mainly located in the cytoplasm of WT oncosphere cells. However, we found that C8orf4 KO did not affect subcellular localization of β-catenin (Supplementary Fig. 5b,c). Through luciferase assays, C8orf4 transfection did not significantly influence promoter transcription activity of Wnt target genes such as TCF1, LEF and SOX4 (Supplementary Fig. 5d). These data indicate that C8orf4 resides in the cytoplasm of HCC cells and inhibits nuclear translocation of N2ICD.

C8orf4 deletion causes the nuclear translocation of N2ICD

C8orf4 deletion causes the nuclear translocation of N2ICD

Figure 5: C8orf4 deletion causes the nuclear translocation of N2ICD.

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(a) C8orf4 resides in the cytoplasm of Huh7 cells. Huh7 cells were permeabilized and stained with anti-C8orf4 antibody, then counterstained with PI for confocal microscopy. (b) Cellular fractionation was performed and detected by immunoblotting. (c,d) C8orf4 knockout causes the nuclear translocation of N2ICD. C8orf4-deficient Huh7 cells (c) and sphere cells (d) were permeabilized and stained with anti-C8orf4 and anti-N2ICD antibodies, then counterstained with DAPI followed by confocal microscopy. (e) Cellular fractionation was performed in C8orf4-deficient sphere and WT sphere cells followed by immunoblotting. (f) C8orf4-deficient Huh7 cells were implanted into BALB/c nude mice. Xenograft tumors were analyzed by immunohistochemical staining. Red arrowheads denote nuclear translocation of N2ICD. (g) C8orf4-overexpressing Huh7 cells were permeabilized for immunofluorescence staining. (h) Cellular fractionation was performed in C8orf4-overexpressing Huh7 cells for immunoblotting. (i,j) C8orf4 was overexpressed in N2ICD-overexpressing Huh7 cells followed by immunofluorescence staining (i) and immunoblotting (j). (k) NOTCH target genes were measured in cells treated as in i by real-time PCR. Scale bars: a,c,d,g,i, 10 μm; f, 40 μm. Student’s t-test was used for statistical analysis, **P<0.01;***P<0.001, data are shown as mean±s.d.. Data represent at least three independent experiments.

To further determine whether C8orf4 inhibits the NOTCH2 signaling in the propagation of xenograft tumors, we examined the distribution of N2ICD and NOTCH2 target gene activation inC8orf4-deficient xenograft tumor tissues. We found that C8orf4-deficient tumors displayed much more nuclear translocation of N2ICD compared with WT tumors (Fig. 5f). Expectedly, C8orf4-deficient tumors showed elevated expression levels of NOTCH2 target genes such as HEY1, HES6 and NRARP (Supplementary Fig. 5e). Furthermore, C8orf4 overexpression blocked the nuclear translocation of N2ICD (Fig. 5g,h). Consequently, C8orf4-overexpressing tumors showed much less N2ICD nuclear translocation and reduced expression levels of NOTCH2 target genes compared with control tumors (Supplementary Fig. 5f,g). Of note, C8orf4 overexpression in N2ICD-overexpressing Huh7 cells still blocked nuclear translocation of N2ICD (Fig. 5i,j). Consequently, C8orf4 overexpression abolished the activation of Notch2 signaling (Fig. 5k). These results suggest that C8orf4 deletion causes the nuclear translocation of N2ICD leading to activation of NOTCH2 signaling.

NOTCH2 signalling is required for the stemness of liver CSCs

To further verify the role of NRARP and HEY1 in the maintenance of liver CSC self-renewal, we knocked down these two genes in Huh7 cells and established stably depleted cell lines by two pairs of shRNAs. As expected, NRARP knockdown dramatically reduced sphere formation (Fig. 6a,b). NRARP knockdown also attenuated tumor-initiating capacity and liver CSC ratios (Fig. 6c). Similar results were achieved in NRARP-silenced HCC primary cells (Fig. 6d,e). Similarly, HEY1 silencing remarkably reduced sphere formation derived from Huh7 and HCC primary cells (Fig. 6f–i), as well as declined xenograft tumor growth and tumor-initiating capacity (Supplementary Fig. 6a,b). In sum, NOTCH2 signaling is required for the maintenance of liver CSC self-renewal.

(not shown)

Figure 6: Depletion of NRARP and HEY1 impairs stemness of liver CSCs.

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(a,b) NRARP-silenced Huh7 cells were established (a) and showed reduced sphere formation capacity (b). Two pairs of shRNAs against NRARP obtained similar results. (c) NRARP-silenced Huh7 cells decline tumour-initiating capacity (left panel) and reduce liver CSC frequency (right panel). Error bars represent the 95% confidence intervals of the estimation. (d,e) NRARP was knocked down in HCC primary cells (d) and sphere formation was detected (e). Three HCC samples were tested with similar results. (f,g) HEY1-silenced Huh7 cells were established (f) and sphere formation was assayed (g). Two pairs of shRNAs against HEY1 obtained similar results. (h,i) HEY1 was knocked down in HCC primary cells (h) and HEY1 depletion impaired sphere formation capacity (i). Three HCC samples were tested with similar results. Scale bars: b,e,g,i, 500 μm. For a,b,di, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01;  ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments.

NOTCH2 signaling is correlated with HCC severity

As shown above, the NOTCH2 signaling was highly activated in liver CSCs and involved in the regulation of liver CSC stemness. We further examined the relationship of NOTCH2 signaling with the progression of HCC. First, we analyzed NOTCH2 activation levels in HCC tumor tissues and peri-tumor tissues derived from Park’s cohort (GSE36376). We observed that HEY1HES6 and NRARP were highly expressed in the tumor tissues of HCC patients (Fig. 7a). Consistently, high expression levels of HEY1HES6 and NRARP in HCC tumors were validated by Zhang’s cohort (GSE25097) (Fig. 7b). Importantly, high expression of these three genes was confirmed in HCC samples through quantitative RT–PCR (Fig. 7c), as well as immunoblotting (Fig. 7d). To confirm a causative link between low C8orf4 expression level and nuclear N2ICD, we examined 93 HCC samples (31 peri-tumor, 37 early stage of HCC patients and 25 advanced stage of HCC patients) with immunohistochemistry staining. We observed that nuclear staining of N2ICD appeared in ~10% tumor cells in the majority of early HCC patients we tested (Fig. 7e,f). In advanced HCC patients, nuclear staining of N2ICD in tumor cells increased to ~30% in almost all the advanced HCC patients we examined. Consequently, HEY1 staining existed in ~10% tumor cells with scattered distribution and increased to 30% tumor cells in the advanced HCC patients (Fig. 7e). Consistently, low expression of C8orf4 was well correlated with activation of NOTCH2 signaling (Fig. 7e,f).

NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients

NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients

Figure 7: NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients.

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(a,b) NOTCH target genes were highly expressed in HCC tumour tissues derived from Park’s cohort (a) and Zhang’s cohort (b). (c) High expression levels of NOTCH target genes in HCC tumor tissues were verified by qRT–PCR. (d) HEY1 expression in HCC tumor tissues was detected by western blot. (e) IHC staining for N2ICD, C8orf4 and HEY1. These images represent 93 HCC samples. Scale bars, 50 μm. (f) IHC images were calculated using Image-Pro Plus 6. (g) Expression levels of NOTCH target genes were elevated in HCC tumors and advanced HCC patients derived from Wang’s cohort. (hHEY1 expression level was positively correlated with prognosis prediction of HCC patients analyzed by Petel’s cohort and Wang’s cohort. HCC samples were divided into two groups according to HEY1 expression levels followed by Kaplan–Meier survival analysis. For ac, data are shown as box and whisker plot, Box: interquartile range (IQR); horizontal line within box: median; whiskers: 5–95 percentile. For f,g, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001; data are shown as mean ± standard deviation. Experiments were repeated at least three times. aHCC, advanced HCC; CL, cirrhosis liver; eHCC, early HCC; IL, inflammatory liver; NL, normal liver; NS, not significant.

Serial passages of colonies or sphere formation in vitro, as well as transplantation of tumor cells, are frequently used to assess the long-term self-renewal capacities of CSCs32. We used HCC primary cells for serial passage growth in vitro and tested the expression levels of C8orf4HEY1 and SOX9. We found that C8orf4 expression was gradually reduced over serial passages in oncosphere cells (Supplementary Fig. 7a). Consequently, the expression of NOTCH2 targets such as HEY1 and SOX9 was gradually increased in oncosphere cells during serial passages (Supplementary Fig. 7b). In addition, N2ICD nuclear translocation appeared in oncosphere cells with high expression of HEY1 plus low expression of C8orf4 (termed as C8orf4/N2ICDnuc/HEY1+cells) (Supplementary Fig. 7c). These data suggest that the C8orf4/N2ICDnuc/HEY1+ fraction cells represent a subset of liver CSCs.

Through analyzing Wang’s cohort (GSE54238), we noticed that the NOTCH2 activation levels were positively correlated with the development and progression of HCC (Fig. 7g). By contrast, the NOTCH2 pathway was not activated in inflammation liver, cirrhosis liver and normal liver (Fig. 7f). Consistently, similar observations were achieved by analysis of Zhang’s cohort (GSE25097) (Supplementary Fig. 7d). In addition, the NOTCH2 activation levels were consistent with clinicopathological stages of HCC patients derived from Wang’s cohort (GSE14520) (Supplementary Fig. 7e). Finally, HCC patients with higher expression of HEY1 displayed worse prognosis derived from Petel’s cohort (E-TABM-36) and Wang’s cohort (GSE14520) (Fig. 7h). These two cohorts (E-TABM-36 and GSE14520) have survival information of HCC patients. Taken together, the NOTCH2 activation levels in tumor tissues are consistent with clinical severity and prognosis of HCC patients.

Discussion

CSC have been identified in many solid tumors, including breast, lung, brain, liver, colon, prostate and bladder cancers4633. CSCs have similar characteristics associated with normal tissue stem cells, including self-renewal, differentiation and the ability to form new tumors. CSCs may be responsible for cancer relapse and metastasis due to their invasive and drug-resistant capacities34. Thus, targeting CSCs may become a promising therapeutic strategy to deadly malignancies3536. However, it remains largely unknown about hepatic CSC biology. In this study, we used CD13 and CD133 to enrich CD13+CD133+
subpopulation cells as liver CSCs. Based on analysis of several online-available HCC transcriptome datasets, we found that C8orf4 is weakly expressed in HCC tumors as well as in CD13+CD133+ liver CSCs. NOTCH2 signaling is required for the maintenance of liver CSC self-renewal. C8orf4 resides in the cytoplasm of tumor cells and interacts with N2ICD, blocking the nuclear translocation of N2ICD. Lower expression of C8orf4 causes nuclear translocation of N2ICD that activates NOTCH2 signaling in liver CSCs. NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Therefore, C8orf4 negatively regulates self-renewal of liver CSCs via suppression of NOTCH2 signaling.

Elucidating signaling pathways that maintains self-renewal of liver CSCs is pivotal for the understanding of hepatic CSC biology and the development of novel therapies against HCC. Several signaling pathways, such as Wnt/β-catenin, transforming growth factor-beta, AKT and STAT3 pathways, have been defined to be implicated in the regulation of liver CSCs37. Not surprisingly, some liver CSC subsets and normal tissue stem cells may share core regulatory genes and common signaling pathways. The NOTCH signaling pathway plays an important role in development via cell-fate determination, proliferation and cell survival3839. The NOTCH family receptors contain four members in mammals (NOTCH1–4), which are activated by binding to their corresponding ligands. A large body of evidence provides that NOTCH signaling is implicated in carcinogenesis40. However, the role of NOTCH signaling in liver cancer is controversial. A previous study reported that NOTCH1 signaling suppresses tumor growth of HCC41. Recently, several reports showed that NOTCH signaling enhances liver tumor initiation424344. Importantly, a recent study showed that various NOTCH receptors have differential functions in the development of liver cancer45. Here we demonstrate that NOTCH2 signaling is activated in HCC tumor tissues and liver CSCs, which is required for the maintenance of liver CSC self-renewal.

C8orf4, also known as TC1, was originally cloned from a papillary thyroid cancer16, 46. The copy number variations of C8orf4 are associated with acute myeloid leukemia and other hematological malignancies19, 47. C8orf4 has been reported to be implicated in various cancers. C8orf4 was highly expressed in thyroid cancer, gastric cancer and breast cancer16, 20, 46. C8orf4 has been reported to enhance Wnt/β-catenin signaling in cancer cells that is associated with poor prognosis20, 21. However, C8orf4 is downregulated in colon cancer48. In this study, we show that C8orf4 is weakly expressed in HCC tumor tissues and liver CSCs. Our observations were confirmed by two HCC cohort datasets. Importantly, C8orf4 negatively regulates the NOTCH2 signaling to suppress the self-renewal of liver CSCs. Therefore, C8orf4 may exert distinct functions in the regulation of various malignancies.

NOTCH receptors consist of noncovalently bound extracellular and transmembrane domains. Once binding with membrane-bound Delta or Jagged ligands, the NOTCH receptors undergoes a proteolytic step by metalloprotease and γ-secretase, generating NECD and NICD fragments11, 31. The NICD, a soluble fragment, is released in the cytoplasm on proteolysis. Then the NICD translocates to the nucleus and binds to the transcription initiation complex, leading to activation of NOTCH-associated target genes49. However, it is largely unclear how the NICD is regulated during NOTCH signaling activation. Here we show that N2ICD binds to C8orf4 in the cytoplasm of liver non-CSC tumor cells, which impedes the nuclear translocation of N2ICD. By contrast, in liver CSCs, lower expression of C8orf4 causes the nuclear translocation of N2ICD, leading to activation of NOTCH signaling.

CSCs or tumour-initiating cells, behave like tissue stem cells in that they are capable of self-renewal and of giving rise to hierarchical organization of heterogeneous cancer cells4. Thus, CSCs harbour the stem cell properties of self-renewal and differentiation. Actually, the CSC model cannot account for tumorigenesis in all tumours. CSCs could undergo genetic evolution, and the non-CSCs might switch to CSC-like cells4. These results highlight the dynamic nature of CSCs, suggesting that the clonal evolution and CSC models can act in concert for tumorigenesis. Furthermore, low C8orf4 expression in tumor cells results in overall Notch2 activation, which then may have more of a progenitor signature and be more aggressive. These cells would likely have a growth advantage in non-adherent conditions and express many of the stemness markers. The dynamic nature of CSCs or persistent NOTCH2 activation may contribute to the high number of C8orf4/N2ICDnuc/HEY1+ cells in advanced HCC tumors and correlation in the patient cohort.

A recent study showed that NOTCH2 and its ligand Jag1 are highly expressed in human HCC tumors, suggesting activation of NOTCH2 signaling in HCC45. In addition, inhibiting NOTCH2 or Jag1 dramatically reduces tumor burden and growth. However, suppression of NOTCH3 has no effect on tumor growth. Dill et al.43 reported that Notch2 is an oncogene in HCC. Notch2-driven HCC are poorly differentiated with a high expression level of the progenitor marker Sox9, indicating a critical role of Notch2 signaling in liver CSCs. Here we found that NOTCH2 and its target genes such as NRARP, HEY1 and HES6 are highly expressed in HCC samples. In addition, depletion of NRARP and HEY1 impairs the stemness maintenance of liver CSCs and tumor propagation. Moreover, the expression levels of NRARP, HEY1 and HES6 in tumors are positively correlated with clinical severity and prognosis of HCC patients. Finally, the NOTCH2 activation status is positively related to the clinicopathological stages of HCC patients. Altogether, C8orf4 and NOTCH2 signaling can be detected for the diagnosis and prognosis prediction of HCC patients, as well as used as targets for eradicating liver CSCs for future therapy.

11.2.3.2 Quantifying the Landscape for Development and Cancer from a Core Cancer Stem Cell Circuit

The authors developed a landscape and path theoretical framework to investigate the global natures and dynamics for a core cancer stem cell gene network. The landscape exhibits four basins of attraction, representing cancer stem cell, stem cell, cancer and normal cell states. They also uncovered certain key genes and regulations responsible for determining the switching between different states. [Cancer Res]

Chunhe Li and Jin Wang
Cancer Res May 13, 2015; 75(10).
http://dx.doi.org:/10.1158/0008-5472.CAN-15-0079

Cancer presents a serious threat to human health. The understanding of the cell fate determination during development and tumor genesis remains challenging in current cancer biology. It was suggested that cancer stem cell (CSC) may arise from normal stem cells, or be transformed from normal differentiated cells. This gives hints on the connection between cancer and development. However, the molecular mechanisms of these cell type transitions and the CSC formation remain elusive. We quantified landscape, dominant paths and switching rates between cell types from a core gene regulatory network for cancer and development. Stem cell, CSC, cancer, and normal cell types emerge as basins of attraction on associated landscape. The dominant paths quantify the transition processes among CSC, stem cell, normal cell and cancer cell attractors. Transition actions of the dominant paths are shown to be closely related to switching rates between cell types, but not always to the barriers in between, due to the presence of the curl flux. During the process of P53 gene activation, landscape topography changes gradually from a CSC attractor to a normal cell attractor. This confirms the roles of P53 of preventing the formation of CSC, through suppressing self-renewal and inducing differentiation. By global sensitivity analysis according to landscape topography and action, we identified key regulations determining cell type switchings and suggested testable predictions. From landscape view, the emergence of the CSCs and the associated switching to other cell types are the results of underlying interactions among cancer and developmental marker genes. This indicates that the cancer and development are intimately connected. This landscape and flux theoretical framework provides a quantitative way to understand the underlying mechanisms of CSC formation and interplay between cancer and development. Major Findings: We developed a landscape and path theoretical framework to investigate the global natures and dynamics for a core cancer stem cell gene network. Landscape exhibits four basins of attraction, representing CSC, stem cell, cancer and normal cell states. We quantified the kinetic rate and paths between different attractor states. We uncovered certain key genes and regulations responsible for determining the switching between different states.

11.2.3.3 IMP3 Promotes Stem-Like Properties in Triple-Negative Breast Cancer by Regulating SLUG

Scientists observed that insulin-like growth factor-2 mRNA binding protein 3 (IMP3) expression is significantly higher in tumor initiating than in non-tumor initiating breast cancer cells and demonstrated that IMP3 contributes to self-renewal and tumor initiation, properties associated with cancer stem cells. [Oncogene]

S Samanta, H Sun, H L Goel, B Pursell, C Chang, A Khan, et al.
Oncogene
 , (18 May 2015) |
http://dx.doi.org:/10.1038/onc.2015.164

IMP3 (insulin-like growth factor-2 mRNA binding protein 3) is an oncofetal protein whose expression is prognostic for poor outcome in several cancers. Although IMP3 is expressed preferentially in triple-negative breast cancer (TNBC), its function is poorly understood. We observed that IMP3 expression is significantly higher in tumor initiating than in non-tumor initiating breast cancer cells and we demonstrate that IMP3 contributes to self-renewal and tumor initiation, properties associated with cancer stem cells (CSCs). The mechanism by which IMP3 contributes to this phenotype involves its ability to induce the stem cell factor SOX2. IMP3 does not interact with SOX2 mRNA significantly or regulate SOX2 expression directly. We discovered that IMP3 binds avidly to SNAI2 (SLUG) mRNA and regulates its expression by binding to the 5′ UTR. This finding is significant because SLUG has been implicated in breast CSCs and TNBC. Moreover, we show that SOX2 is a transcriptional target of SLUG. These data establish a novel mechanism of breast tumor initiation involving IMP3 and they provide a rationale for its association with aggressive disease and poor outcome.

11.2.3.4 Type II Transglutaminase Stimulates Epidermal Cancer Stem Cell Epithelial-Mesenchymal Transition

Researchers investigated the role of type II transglutaminase (TG2) in regulating epithelial mesenchymal transition (EMT) in epidermal cancer stem cells. They showed that TG2 knockdown or treatment with TG2 inhibitor, resulted in a reduced EMT marker expression, and reduced cell migration and invasion. [Oncotarget]

ML Fisher, G Adhikary, W Xu, C Kerr, JW Keillor, RL Ecker
Oncotarget May 08, 2015;

Type II transglutaminase (TG2) is a multifunctional protein that has recently been implicated as having a role in ECS cell survival. In the present study we investigate the role of TG2 in regulating epithelial mesenchymal transition (EMT) in ECS cells. Our studies show that TG2 knockdown or treatment with TG2 inhibitor, results in a reduced EMT marker expression, and reduced cell migration and invasion. TG2 has several activities, but the most prominent are its transamidase and GTP binding activity. Analysis of a series of TG2 mutants reveals that TG2 GTP binding activity, but not the transamidase activity, is required for expression of EMT markers (Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α), and increased ECS cell invasion and migration. This coupled with reduced expression of E-cadherin. Additional studies indicate that NFϰB signaling, which has been implicated as mediating TG2 impact on EMT in breast cancer cells, is not involved in TG2 regulation of EMT in skin cancer. These studies suggest that TG2 is required for maintenance of ECS cell EMT, invasion and migration, and suggests that inhibiting TG2 GTP binding/G-protein related activity may reduce skin cancer tumor survival.

Epidermal squamous cell carcinoma (SCC) is among the most common cancers and the frequency is increasing at a rapid rate [1,2]. SCC is treated by surgical excision, but the rate of recurrence approaches 10% and the recurrent tumors are aggressive and difficult to treat [2]. We propose that human epidermal cancer stem (ECS) cells survive at the site of tumor excision, that these cells give rise to tumor regrowth, and that therapies targeted to kill ECS cells constitute a viable anti-cancer strategy. An important goal in this context is identifying and inhibiting activity of key proteins that are essential for ECS cell survival. Working towards this goal, we have developed systems for propagation of human ECS cells [3]. These cells display properties of cancer stem cells including self-renew and high level expression of stem cell marker proteins [3].

In the present study we demonstrate that ECS cells express proteins characteristic of cells undergoing EMT (epithelial-mesenchymal transition). EMT is a morphogenetic process whereby epithelial cells lose epithelial properties and assume mesenchymal characteristics [4]. The epithelial cells lose cell-cell contact and polarity, and assume a mesenchymal migratory phenotype. There are three types of EMT. This first is an embryonic process, during gastrulation, when the epithelial sheet gives rise to the mesoderm [5]. The second is a growth factor and cytokine-stimulated EMT that occurs at sites of tissue injury to facilitate wound repair [6]. The third is associated with epithelial cancer cell acquisition of a mesenchymal migratory/invasive phenotype. This process mimics normal EMT, but is not as well controlled and coordinated [478]. A number of transcription factors (ZEB1, ZEB2, snail, slug, and twist) that are expressed during EMT suppress expression of epithelial makers, including E-cadherin, desmoplakin and claudins [4]. Snail proteins also activate expression of vimentin, fibronectin and metalloproteinases [4]. Snail factors are not present in normal epithelial cells, but are present in the tumor cells and are prognostic factors for poor survival [4].

An important goal is identifying factors that provide overarching control of EMT in cancer stem cells. In this context, several recent papers implicate type II transglutaminase (TG2) as a regulator of EMT [912]. TG2, the best studied transglutaminase, was isolated in 1957 from guinea pig liver extract as an enzyme involved in the covalent crosslinks proteins via formation of isopeptide bonds [13]. However, subsequent studies reveal that TG2 also serves as a scaffolding protein, regulates cell adhesion, and modulates signal transduction as a GTP binding protein that participates in G protein signaling [14]. TG2 is markedly overexpressed in cancer cells, is involved in cancer development [1518], and has been implicated in maintaining and enhancing EMT in breast and ovarian cancer [10121920]. The G protein function may have an important role in these processes [102123].

In the present manuscript we study the role of TG2 in regulating EMT in human ECS cells. Our studies show that TG2 is highly enriched in ECS cells. We further show that these cells express EMT markers and that TG2 is required to maintain EMT protein expression. TG2 knockdown, or treatment with TG2 inhibitor, reduces EMT marker expression and ECS cell survival, invasion and migration. TG2 GTP binding activity is absolutely required for maintenance of EMT protein expression and EMT-related responses. However, in contrast to breast cancer [910], we show that TG2 regulation of EMT is not mediated via NFκB signaling.

TG2 is required for expression of EMT markers

EMT is a property of tumor stem cells that confers an ability to migrate and invade surrounding tissue [2426]. We first examined whether ECS cells express EMT markers. Non-stem cancer cells and ECS cells, derived from the SCC-13 cancer cell line, were analyzed for expression of EMT markers. Fig. 1A shows that a host of EMT transcriptional regulators, including Twist, Snail and Slug, are increased in ECS cells (spheroid) as compared to non-stem cancer cells (monolayer). This is associated with increased levels of vimentin, fibronectin and N-cadherin, which are mesenchymal proteins, and reduced expression of E-cadherin, an epithelial marker. HIF-1α, an additional marker frequently associated with EMT, is also elevated. We next examined whether TG2 is required to maintain EMT marker expression. SCC-13 cell-derived ECS cells were grown in the presence of control- or TG2-siRNA, to reduce TG2, and the impact on EMT marker level was measured. Fig. 1B shows that loss of TG2 is associated with reduced expression of Twist, Snail, vimentin and HIF-1α. To further assess the role of TG2, we utilized SCC13-Control-shRNA and SCC13-TG2-shRNA2 cell lines. These lines were produced by infection of SCC-13 cells with lentiviruses encoding control- or TG2-specific shRNA. Fig. 1C shows that SCC13-TG2-shRNA2 cells express markedly reduced levels of TG2 and that this is associated with reduced expression of EMT associated transcription factors and target proteins, and increased expression of E-cadherin. To confirm this, we grew SCC13-Control-shRNA and SCC13-TG2-shRNA2 cells as monolayer cultures for immunostain detection of EMT markers. As shown in Fig. 2A, TG2 levels are reduced in TG2-shRNA expressing cells, and this is associated with the anticipated changes in epithelial and mesenchymal marker expression.

Tumor cells that express EMT markers display enhanced migration and invasion ability [2426]. We therefore examined the impact of TG2 reduction on these responses. To measure invasion, control-shRNA and TG2-shRNA cells were monitored for ability to move through matrigel. Fig. 2B shows that loss of TG2 reduces movement through matrigel by 50%. We further show that this is associated with a reduction in cell migration using a monolayer culture wound closure assay. The control cells close the wound completely within 14 h, while TG2 knockdown reduces closure rate (Fig. 2C).

TG2 inhibitor reduces EMT marker expression and EMT functional responses

NC9 is a recently developed TG2-specific inhibitor [2728]. We therefore asked whether pharmacologic inhibition of TG2 suppresses EMT. SCC-13 cells were treated with 0 or 20 μM NC9. Fig. 3A shows that NC9 treatment reduces EMT transcription factor (Twist, Snail, Slug) and EMT marker (vimentin, fibronectin, N-cadherin, HIF-1α) levels. Consistent with these changes, the level of the epithelial marker, E-cadherin, is elevated. Fig. 3B and 3C show that pharmacologic inhibition of TG2 activity also reduces EMT biological response. Invasion (Fig. 3B) and cell migration (Fig. 3C) are also reduced.

Identification of TG2 functional domain required for EMT

We next performed studies to identify the functional domains and activities required for TG2 regulation of EMT. TG2 is a multifunctional enzyme that serves as a scaffolding protein, as a transamidase, as a kinase, and as a GTP binding protein [21]. The two best studied functions are the transamidase and GTP binding/G-protein related activities [21]. Transamidase activity is observed in the presence of elevated intracellular calcium, while GTP binding-related signaling is favored by low calcium conditions (reviewed in [21]). To identify the TG2 activity required for EMT, we measured the ability of wild-type and mutant TG2 to restore EMT in SCC13-TG2-shRNA2 cells, which have reduced TG2 expression (Fig. 4A). SCC13-TG2-shRNA2 cells display reduced expression of EMT markers including Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α, and increased expression of the epithelial maker, E-cadherin, as compared to SCC13-Control-shRNA cells. Expression of wild-type TG2, or the TG2-C277S or TG2-W241A mutants, restores marker expression in SCC13-TG2-shRNA2 cells (Fig. 4A). TG2-C277S and TG2-W241A lack transamidase activity [10,2931]. In contrast, TG2-R580A, which lacks G-protein activity [2931], and TG2-Y516F, which retains only partial G-protein activity [30], do not efficiently restore marker expression. These findings suggest that the TG2 GTP binding function is required for EMT.

We next assayed the ability of the TG2 mutants to restore EMT functional responses-invasion and migration. Fig. 4B4C shows that wild-type TG2, TG2-C277S and TG2-W241A restore the ability of SCC13-TG2-shRNA2 cells to invade matrigel, but TG2-R580A and Y516F are less active. Fig. 4D shows a similar finding for cell migration, in that the TG2-R580A and Y517F mutant are only partially able to restore SCC13-TG2-shRNA2 cell migration. These findings suggest that TG2 GTP binding/G-protein related activity is required for EMT-related migration and invasion by skin cancer cells.

Role of TG2 in regulating EMT in A431 cells

The number of available epidermis-derived squamous cell carcinoma cell lines is limited, and so we compared our findings with A431 cells. A431 cells are squamous cell carcinoma cells established from human vulvar skin. A431 cells were grown as monolayer (non-stem cancer cells) and spheroids (ECS cells) and after 10 d the cells were harvested and assayed for expression of TG2 and EMT makers. Fig. 5A shows that TG2 levels are elevated in ECS cells and that this is associated with increased levels of mesenchymal markers, including Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α. In contrast, E-cadherin levels are reduced. We next examined the impact of TG2 knockdown on EMT marker expression. Fig. 5B shows that mesenchymal markers are globally reduced and E-cadherin level is increased. As a biological endpoint of EMT, we examine the impact of TG2 knockdown on spheroid formation and found that TG2 loss leads to reduced spheroid formation (Fig. 5C). We next examined the impact of NC9 treatment on EMT and found a reduction in EMT markers expression associated with an increase in epithelial (E-cadherin) marker level (Fig. 5D). This loss of EMT marker expression is associated with reduced matrigel invasion (Fig. 5E), reduced spheroid formation (Fig. 5F) and reduced cell migration (Fig. 5G).

Role of NFκB

Previous studies in breast [183236], ovarian cancer [123738], and epidermoid carcinoma [11] indicate that NFκB signaling mediates TG2 impact on EMT. We therefore assessed the role of NFκB in skin cancer cells. As shown in Fig. 6A, the increase in TG2 level observed in ECS cells (spheroids) is associated with reduced NFκB level. In addition, NFκB level is increased in TG2 knockdown cells (Fig. 6B). Thus, increased NFκB is not associated with increased TG2. We next assessed the impact of NFκB knockdown on TG2 control of EMT marker expression. Fig. 6C shows that TG2 is required for increased expression of EMT markers (HIF-1α, snail, twist, N-cadherin, vimentin and fibronectin) and reduced expression of the E-cadherin epithelial marker; however, knockdown of NFκB expression does not interfere with TG2 regulation of these endpoints. We next examined the effect of TG2 knockdown on NFκB and IκBα localization. The fluorescence images in Fig. 6D suggest that TG2 knockdown with TG2-siRNA does not alter the intracellular localization of NFκB or IκBα. This is confirmed by subcellular fractionation assay (Fig. 6E) which compares NFκB level in SCC13-TG2-Control and SCC13-TG2-shRNA2 (TG2 knockdown) cells. We also monitored NFκB subcellular distribution following treatment with NC9, the TG2 inhibitor. Fig. 6F shows that cytoplasmic/nuclear distribution of NFκB is not altered by NC9. Finally, we monitored the impact of TG2 expression on NFκB binding to a canonical NFκB-response element. Increased NFκB binding to the response element is a direct measure of NFκB activity [10]. Fig. 6G shows that overall binding is reduced in nuclear (N) extract prepared from ECS cells (spheroids) as compared to non-stem cancer cells (monolayer), and that NFkB binding, as indicated by gel supershift assay, is also slightly reduced in ECS cell extracts. These findings indicate that NFkB binding is slightly reduced in ECS cells, which are TG2-enriched (Fig. 1A).

We next monitored the role of NFκB on biological endpoints of EMT. Fig. 7A and 7B show that TG2 knockdown reduces migration through matrigel, but NFκB knockdown has no impact. Likewise, TG2 knockdown reduces wound closure, but NFκB knockdown does not. These findings suggest that NFκB does not mediate the pro-EMT actions of TG2 in epidermal squamous cell carcinoma.

The metastatic cascade, from primary tumor to metastasis, is a complex process involving multiple pathways and signaling cascades [3941]. Cells that complete the metastatic cascade migrate away from the primary tumor through the blood to a distant site and there form a secondary tumor. Identifying the mechanisms that allow cells to survive this journey and form secondary tumors is an important goal. The processes involved in epithelial-mesenchymal transition (EMT) are important cancer therapy targets, as EMT is associated with enhanced cancer cell migration and stem cell self-renewal. EMT regulators, including Snail, Twist, Slug, are increased in expression in EMT and control expression of genes associated with the EMT phenotype [42].

TG2 is required for EMT

We have characterized a population of ECS cells derived from epidermal squamous cell carcinoma [3]. The present studies show that these cells, which display enhanced migration and invasion, possess elevated levels of TG2. Moreover, these cells are enriched in expression of transcription factors associated with EMT (Snail, Slug, and Twist, HIF-1α) as well as mesenchymal structural proteins including vimentin, fibronectin and N-cadherin. Consistent with a shift to mesenchymal phenotype, E-cadherin, an epithelial marker, is reduced in level. Additional studies show that TG2 knockdown results in a marked reduction in EMT marker expression and that this is associated with reduced ability of the cells to migrate to close a scratch wound and reduced movement in matrigel invasion assays. We also examined the impact of treatment with a TG2 inhibitor. NC9 is an irreversible active site inhibitor of TG2, that locks the enzyme in an open conformation [284345]. NC9 treatment of ECS cells results in decreased levels of Snail, Slug and Twist. These transcription factors suppress E-cadherin expression [46] and their decline in level is associated with increased levels of E-cadherin. NC9 inhibition of TG2 also reduces expression of vimentin, fibronectin and N-cadherin, and these changes are associated with reduced cell migration and reduced invasion through matrigel.

(Figures are not shown)

We also examined the role of TG2 in A431 squamous cell carcinoma cells derived from the vulva epithelium. TG2 is elevated in A431-derived ECS cells, as are EMT markers, and knockdown of TG2, with TG2-siRNA, reduces EMT marker expression and spheroid formation. Studies with NC9 indicate that NC9 inhibits A431 spheroid formation, EMT, migration and invasion. These studies indicate that TG2 is also required for EMT and migration and invasion in A431 cells. Based on these findings we conclude that TG2 is essential for EMT, migration and invasion, and is likely to contribute to metastasis in squamous cell carcinoma.

TG2 GTP binding activity is required for EMT

TG2 is a multifunctional enzyme that can act as a transamidase, GTP binding protein, protein disulfide isomerase, protein kinase, protein scaffold, and DNA hydrolase [21294447]. The two most studied functions are the transamidase and GTP binding functions [294447]. To identify the TG2 activity responsible for induction of EMT, we studied the ability of TG2 mutants to restore EMT in SCC13-TG2-shRNA2 cells, which express low levels of TG2 and do not express elevated levels of EMT markers or display EMT-related biological responses. These studies show that wild-type TG2 restores EMT marker expression and the ability of the cells to migrate on plastic and invade matrigel. TG2 mutants that retain GTP binding activity (TG2-C277S and TG2-W241A) also restore EMT. In contrast, TG2-R580A, which lacks GTP binding function, does not restore EMT. This evidence suggests that the GTP binding function is essential for TG2 induction of the EMT phenotype in ECS cells. Recent reports suggest that the TG2 is important for maintenance of stem cell survival in breast [91017] and ovarian [123848] cancer cells. Moreover, our findings are in agreement of those of Mehta and colleagues who reported that the TG2 GTP binding function, but not the crosslinking function, is required for TG2 induction of EMT in breast cancer cells [10].

TG2, NFκB signaling and EMT

To gain further insight into the mechanism of TG2 mediated EMT, we examined the role of NFκB. NFκB has been implicated as mediating EMT in breast, ovarian, and pancreatic cancer; however, NFκB may have a unique role in epidermal squamous cell carcinoma. In keratinocytes, NFκB has been implicated in keratinocyte dysplasia and hyperproliferation [49]. However, inhibition of NFκB function has also been shown to predispose murine epidermis to cancer [50]. Here we show that TG2 levels are elevated and NFκB levels are reduced in ECS cells as compared to non-stem cancer cells, and that TG2 knockdown is associated with increased NFκB level. In addition, TG2 knockdown, or inhibition of TG2 by treatment with NC9, does not altered the nuclear/cytoplasmic distribution of NFκB. We further show that elevated levels of TG2 in spheroid culture results in a slight reduction in NFκB binding to the NFκB response element, as measured by gel mobility supershift assay. These molecular assays strongly suggest that NFκB does not mediate the action of TG2 in epidermal cancer stem cells. Moreover, knockdown of NFκB-p65 in TG2 positive cells does not result in a reduction in Snail, Slug and Twist, or mesenchymal marker proteins expression, and concurrent knockdown of TG2 and NFκB does not reduce EMT marker protein levels beyond that of TG2 knockdown alone. These findings suggest that NFκB is not an intermediary in TG2-stimulated EMT in ECS cells. This is in contrast to the required role of NFκB in mediating TG2 induction of cell survival and EMT in breast cancer cells [183233] and ovarian cancer [123738] and epidermoid carcinoma [11].

11.2.3.5 CD24+ Ovarian Cancer Cells are Enriched for Cancer Initiating Cells and Dependent on JAK2 Signaling for Growth and Metastasis

Investigators showed that CD24+ and CD133+ cells have increased tumorsphere forming capacity. CD133+ cells demonstrated a trend for increased tumor initiation while CD24+ cells vs CD24– cells, had significantly greater tumor initiation and tumor growth capacity. [Mol Cancer Ther]

D Burgos-OjedaR Wu, K McLean, Yu-Chih Chen, M Talpaz, et al.
Molec Cancer Ther May 12, 2015; 14(5)
http://dx.doi.org:/10.1158/1535-7163.MCT-14-0607

Ovarian cancer is known to be composed of distinct populations of cancer cells, some of which demonstrate increased capacity for cancer initiation and/or metastasis. The study of human cancer cell populations is difficult due to long requirements for tumor growth, inter-patient variability and the need for tumor growth in immune-deficient mice. We therefore characterized the cancer initiation capacity of distinct cancer cell populations in a transgenic murine model of ovarian cancer. In this model, conditional deletion of Apc, Pten, and Trp53 in the ovarian surface epithelium (OSE) results in the generation of high grade metastatic ovarian carcinomas. Cell lines derived from these murine tumors express numerous putative stem cell markers including CD24, CD44, CD90, CD117, CD133 and ALDH. We show that CD24+ and CD133+ cells have increased tumor sphere forming capacity. CD133+ cells demonstrated a trend for increased tumor initiation while CD24+ cells vs CD24- cells, had significantly greater tumor initiation and tumor growth capacity. No preferential tumor initiating or growth capacity was observed for CD44+, CD90+, CD117+, or ALDH+ versus their negative counterparts. We have found that CD24+ cells, compared to CD24- cells, have increased phosphorylation of STAT3 and increased expression of STAT3 target Nanog and c-myc. JAK2 inhibition of STAT3 phosphorylation preferentially induced cytotoxicity in CD24+ cells. In vivo JAK2 inhibitor therapy dramatically reduced tumor metastases, and prolonged overall survival. These findings indicate that CD24+ cells play a role in tumor migration and metastasis and support JAK2 as a therapeutic target in ovarian cancer.

11.2.3.6 EpCAM-Antibody-Labeled Noncytotoxic Polymer Vesicles for Cancer Stem Cells-Targeted Delivery of Anticancer Drug and siRNA

Researchers designed and synthesized a novel anti-epithelial cell adhesion molecule (EpCAM)-monoclonal-antibody-labeled cancer stem cells (CSCs)-targeting, noncytotoxic and pH-sensitive block copolymer vesicle as a nano-carrier of anticancer drug and siRNA. [Biomacromolecules]

Jing Chen , Qiuming Liu , Jiangang Xiao , and Jianzhong Du
Biomacromolecules May 19, 2015. (just published)
http://dx.doi.org:/10.1021/acs.biomac.5b00551

Cancer stem cells (CSCs) have the capability to initiate tumor, to sustain tumor growth, to maintain the heterogeneity of tumor, and are closely linked to the failure of chemotherapy due to their self-renewal and multilineage differentiation capability with an innate resistance to cytotoxic agents. Herein, we designed and synthesized a novel anti-EpCAM (epithelial cell adhesion molecule)-monoclonal-antibody-labeled CSCs-targeting, noncytotoxic and pH-sensitive block copolymer vesicle as a nano-carrier of anticancer drug and siRNA (to overcome CSCs drug resistance by silencing the expression of oncogenes). This vesicle shows high delivery efficacy of both anticancer drug doxorubicin hydrochloride (DOX∙HCl) and siRNA to the CSCs because it is labeled by the monoclonal antibodies to the CSCs-surface-specific marker. Compared to non-CSCs-targeting vesicles, the DOX∙HCl or siRNA loaded CSCs-targeting vesicles exhibited much better CSCs killing and tumor growth inhibition capabilities with lower toxicity to normal cells (IC50,DOX decreased by 80%), demonstrating promising potential applications in nanomedicine.

11.2.3.7 Survival of Skin Cancer Stem Cells Requires the Ezh2 Polycomb Group Protein

Investigators showed that Ezh2 is required for epidermal cancer stem (ECS) cell survival, migration, invasion and tumor formation, and that this is associated with increased histone H3 trimethylation on lysine 27, a mark of Ezh2 action. They also showed that Ezh2 knockdown or treatment with Ezh2 inhibitors, GSK126 or EPZ-6438, reduced Ezh2 level and activity, leading to reduced ECS cell spheroid formation, migration, invasion and tumor growth. [Carcinogenesis]

G Adhikary, D Grun, S Balasubramanian, C Kerr, J Huang and RL Eckert
Carcinogenesis (2015)
http://dx.doi.org:/10.1093/carcin/bgv064

Polycomb group (PcG) proteins, including Ezh2, are important candidate stem cell maintenance proteins in epidermal squamous cell carcinoma. We previously showed that epidermal cancer stem cells (ECS cells) represent a minority of cells in tumors, are highly enriched in Ezh2 and drive aggressive tumor formation. We now show that Ezh2 is required for ECS cell survival, migration, invasion and tumor formation, and that this is associated with increased histone H3 trimethylation on lysine 27, a mark of Ezh2 action. We also show that Ezh2 knockdown or treatment with Ezh2 inhibitors, GSK126 or EPZ-6438, reduces Ezh2 level and activity, leading to reduced ECS cell spheroid formation, migration, invasion and tumor growth. These studies indicate that epidermal squamous cell carcinoma cells contain a subpopulation of cancer stem (tumor-initiating) cells that are enriched in Ezh2, that Ezh2 is required for optimal ECS cell survival and tumor formation, and that treatment with Ezh2 inhibitors may be a strategy for reducing epidermal cancer stem cell survival and suppressing tumor formation.

11.2.3.8 Inhibition of STAT3, FAK and Src mediated signaling reduces cancer stem cell load, tumorigenic potential and metastasis in breast cancer

R Thakur, R Trivedi, N Rastogi, M Singh & DP Mishra
Scientific Reports May 14, 2015; 5(10194)
http://dx.doi.org:/10.1038/srep10194

Cancer stem cells (CSCs) are responsible for aggressive tumor growth, metastasis and therapy resistance. In this study, we evaluated the effects of Shikonin (Shk) on breast cancer and found its anti-CSC potential. Shk treatment decreased the expression of various epithelial to mesenchymal transition (EMT) and CSC associated markers. Kinase profiling array and western blot analysis indicated that Shk inhibits STAT3, FAK and Src activation. Inhibition of these signaling proteins using standard inhibitors revealed that STAT3 inhibition affected CSCs properties more significantly than FAK or Src inhibition. We observed a significant decrease in cell migration upon FAK and Src inhibition and decrease in invasion upon inhibition of STAT3, FAK and Src. Combined inhibition of STAT3 with Src or FAK reduced the mammosphere formation, migration and invasion more significantly than the individual inhibitions. These observations indicated that the anti-breast cancer properties of Shk are due to its potential to inhibit multiple signaling proteins. Shk also reduced the activation and expression of STAT3, FAK and Src in vivo and reduced tumorigenicity, growth and metastasis of 4T1 cells. Collectively, this study underscores the translational relevance of using a single inhibitor (Shk) for compromising multiple tumor-associated signaling pathways to check cancer metastasis and stem cell load.

Breast cancer is the most common endocrine cancer and the second leading cause of cancer-related deaths in women. In spite of the diverse therapeutic regimens available for breast cancer treatment, development of chemo-resistance and disease relapse is constantly on the rise. The most common cause of disease relapse and chemo-resistance is attributed to the presence of stem cell like cells (or CSCs) in tumor tissues12. CSCs represent a small population within the tumor mass, capable of inducing independent tumors in vivo and are hard to eradicate2. Multiple signaling pathways including Receptor Tyrosine Kinase (RTKs), Wnt/β-catenin, TGF-β, STAT3, Integrin/FAK, Notch and Hedgehog signaling pathway helps in maintaining the stem cell programs in normal as well as in cancer cells3456. These pathways also support the epithelial-mesenchymal transition (EMT) and expression of various drug transporters in cancer cells. Cells undergoing EMT are known to acquire stem cell and chemo-resistant traits7. Thus, the induction of EMT programs, drug resistance and stem cell like properties are interlinked7. Commonly used anti-cancer drugs eradicate most of the tumor cells, but CSCs due to their robust survival mechanisms remain viable and lead to disease relapse8. Studies carried out on patient derived tumor samples and in vivo mouse models have demonstrated that the CSCs metastasize very efficiently than non-CSCs91011. Therefore, drugs capable of compromising CSCs proliferation and self-renewal are urgently required as the inhibition of CSC will induce the inhibition of tumor growth, chemo-resistance, metastasis and metastatic colonization in breast cancer.

Shikonin, a natural dietary component is a potent anti-cancer compound1213. Previous studies have shown that Shk inhibits the cancer cell growth, migration, invasion and tumorigenic potential12. Shk has good bioavailability, less toxicity and favorable pharmacokinetic and pharmacodynamic profiles in vivo12. In a recent report, it was shown that the prolonged exposure of Shk to cancer cells does not cause chemo-resistance13.Other studies have shown that it inhibits the expression of various key inflammatory cytokines and associated signaling pathways1214. It decreases the expression of TNFα, IL12, IL6, IL1β, IL2, IFNγ, inhibits ERK1/2 and JNK signaling and reduces the expression of NFκB and STAT3 transcription factors1415. It inhibits proteasome and also modulates the cancer cell metabolism by inhibiting tumor specific pyurvate kinase-M214,1516. Skh causes cell cycle arrest and induces necroptosis in various cancer types14. Shk also inhibits the expression of MMP9, integrin β1 and decreases invasive potential of cancer cells1417. Collectively, Shk modulates various signaling pathways and elicits anti-cancer responses in a variety of cancer types.

In breast cancer, Shk has been reported to induce the cell death and inhibit cell migration, but the mechanisms responsible for its effect are not well studied1819. Signaling pathways modulated by Shk in cancerous and non-cancerous models have previously been shown important for breast cancer growth, metastasis and tumorigenicity20. Therefore in the current study, we investigated the effect of Shk on various hallmark associated properties of breast cancer cells, including migration, invasion, clonogenicity, cancer stem cell load and in vivo tumor growth and metastasis.

Shk inhibits cancer hallmarks in breast cancer cell lines and primary cells

We first examined the effect of Shk on various cancer hallmark capabilities (proliferation, invasion, migration, colony and mammosphere forming potential) in breast cancer cells. MTT assay was used to find out effect of Shk on viability of breast cancer cells. Semi-confluent cultures were exposed to various concentrations of Shk for 24 h. Shk showed specific anti-breast cancer activity with IC50 values ranging from 1.38 μM to 8.3 μM in MDA-MB 231, MDA-MB 468, BT-20, MCF7, T47D, SK-BR-3 and 4T1 cells (Fig. 1A). Whereas the IC50 values in non-cancerous HEK-293 and human PBMCs were significantly higher indicating that it is relatively safe for normal cells (Fig. S1A). Shk was found to induce necroptotic cell death consistent with previous reports (Fig. S1B). Treatment of breast cancer cells for 24 h with 1.25 μM, 2.5 μM and 5.0 μM of Shk significantly reduced their colony forming potential (Fig. 1B). To check the effect of Shk on the heterogeneous cancer cell population, we tested it on patient derived primary breast cancer cells. Shk reduced the viability and colony forming potential of primary breast cancer cells in dose dependent manner (Fig. 1C,D). Further we checked its effects on migration and invasion of breast cancer cells. Shk (2.5 μM) significantly inhibited the migration of MDA-MB 231, MDA-MB 468, MCF7 and 4T1 cells (Fig. 1E). It also inhibited the cell invasion in dose dependent manner (Fig. 1F and S1CS1DS1E,S1F). We further examined its effect on mammosphere formation. MDA-MB 231, MDA-MB 468, MCF7 and 4T1 cell mammosphere cultures were grown in presence or absence of 1.25 μM, 2.5 μM and 5.0 μM Shk for 24 h. After 8 days of culture, a dose dependent decrease in the mammosphere forming potential of these cells was observed (Figs. 1G,H). Collectively, these results indicated that Shk effectively inhibits the various hallmarks associated with aggressive breast cancer.

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Figure 1: Shk inhibits multiple cancer hallmarks

Shk reduces cancer stem cell load in breast cancer

As Shk exhibited strong anti-mammosphere forming potential; therefore it was further examined for its anti-cancer stem cell (CSC) properties. Cancer stem cell loads in breast cancer cells were assessed using Aldefluor assay which measures ALDH1 expression. MDA-MB 231 cells with the highest number of ALDH1+ cells were selected for further studies (Fig. S2A). We also checked the correlation between ALDH1 expression and mammosphere formation. Sorted ALDH1+ cells were subjected to mammosphere cultures. ALDH1+ cells formed highest number of mammospheres compared to ALDH1-/low and parent cell population, indicating that ALDH1+ cells are enriched in CSCs (Fig. S2B). Shk reduced the Aldefluor positive cells in MDA-MB 231 cells after 24 h of treatment (Fig. 2A,B). Next, we examined the effect of Shk on the expression of stem cell (Sox2, Oct3/4, Nanog, AldhA1 and c-Myc) and EMT (Snail, Slug, ZEB1, Twist, β-Catenin) markers, associated with the sustenance of breast CSCs. Shk (2.5 μM) treatment for 24 h reduced the expression of these markers (Fig. 2C and S2D). Shk also reduced protein expression of these markers in dose dependent manner (Fig. 2D,E and S2C).

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Figure 2: Shk decreases stem cell load in breast cancer cells and enriched CD44+,CD24−/low breast cancer stem cells.

To further confirm anti-CSC properties of Shk, we checked the effect of shikonin on the load of CD44+ CD24− breast CSCs in MCF7 cells grown on matrigel. Shikonin reduced CD44+ CD24− cell load in dose dependent manner after 24 h of treatment (Fig S2E). We also tested its effects on the enriched CSC population. CD44+ CD24− cells were enriched from MCF7 cells using MagCellect CD24− CD44+ Breast CSC Isolation Kit (Fig. S2F). Enriched CSCs formed highest number of mammosphere in comparison to parent MCF7 cell population or negatively selected CD24+ cells (Fig. S2G). Enriched CSCs were treated with indicated doses of Shk (0.625 μM, 1.25 μM and 2.5 μM) for 24 h and were either analyzed for ALDH1 positivity or subjected to colony or mammosphere formation. 2.5 μM dose of Shk reduced ALDH1+ cells by 50% and inhibited colony and mammosphere formation (Fig. S2H2F2G and 2H). Shk also reduced the mRNA expression of CSC markers in CD44+ CD24− cells and patient derived primary cancer cells (Fig. 2I,J). These results collectively indicated that Shk inhibits CSC load and associated programs in breast cancer.

Shk is a potent inhibitor of STAT3 and poorly inhibits FAK and Src

To identify the molecular mechanism responsible for anti-cancer properties of Shk, we used a human phospho-kinase antibody array to study a subset of phosphorylation events in MDA-MB 231 cells after 6h of treatment with 2.5 μM Shk. Amongst the 46 phospho-antibodies spotted on the array, the relative extent of phosphorylation of three proteins decreased to about ≳ 2 fold (STAT3, 3.3 fold; FAK, 2.5 fold and Src, 1.8 fold) upon Shk treatment (Fig. 3A,B). These proteins (STAT3, FAK and Src) are known to regulate CSC proliferation and self renewal212223. Therefore, we focused on these proteins and the result of kinase-array was confirmed by western blotting. Shk effectively inhibits STAT3 at early time point (1 h) while activation of FAK and Src decreased on or after 3 h (Fig. 3C) confirming Shk as a potent inhibitor of STAT3. Shk also reduced the protein expression of STAT3, FAK and Src at 24 h (Fig. 3C).

(not shown)

Figure 3. Shk inhibits STAT3, FAK and Src signaling pathways.

We also observed that Shk does not inhibit JAK2 at initial time-points (Fig. 3C). This raised a possibility that Shk either regulates STAT3 independent of JAK2 or it binds directly to STAT3. To check the first probability, we activated STAT3 by treating the cells with IL6 (100 ng ml−1) for 1 h followed by treatment with Shk (2.5 μM) for 1 h. Both immunofluorescence and western-blotting results showed that Shk inhibited activated STAT3 without inhibiting JAK2 (Fig. S3AS3B) confirming that Shk inhibits JAK2 mediated activation of STAT3 possibly by binding directly to STAT3. For further confirmation, we performed an in silico molecular docking analysis to examine binding of Shk with the STAT3 SH2 domain. In a major conformational cluster, Shk occupied Lys-707, Lys-709 and Phe-710 binding sites in the STAT3 SH2 domain similar to the STAT3 standard inhibitor S3I-201 (Fig. S3C and S3D). The binding energy of Shk to STAT3 was −4.20 kcal mol−1. Collectively, these results showed that Shk potently inhibits STAT3 activation and also attenuates FAK and Src activation.

STAT3, Src and FAK are differentially expressed and activated in breast CSCs (BCSCs)

STAT3 and FAK are known to play an important role in proliferation and self-renewal of CSCs in various cancer types including breast cancer212224. Src also support CSC phenotype in some cancer types, but there are limited reports of its involvement in breast cancer25. Therefore, we checked the expression and activation of STAT3, FAK and Src in CSCs and non-CSCs. Here we used two methods to enrich the CSCs and non-CSCs. In the first method, the MDA-MB 231 cells were subjected to mammosphere formation for 96 h. After 96 h, mammosphere and non-mammosphere forming cells were clearly visible (Fig. 4A). These mammosphere and non-mammosphere forming cells were separated by using a 70 micron cell strainer. Mammospheres were subjected to two subculture cycles to enrich CSCs. With each passage, the viable single cells (non-mammosphere forming cells) and mammospheres were collected in RIPA lysis buffer and western blotting was done (Fig. 4B). We found that the activation and expression of the STAT3, FAK and Src is higher in enriched mammosphere cultures (Fig. 4C). In the second method, CD44+ CD24− cells were isolated from MCF7 cultures using MagCellect Breast CSC Isolation Kit. STAT3, FAK and Src activation and their mRNA and protein expression were assessed in enriched CSCs and were compared to parent MCF7 cell population. STAT3, FAK and Src all were differentially activated in CSCs (Fig. 4E). High mRNA as well as protein expressions of all the three genes was also observed in CSCs (Fig. 4D,E). Collectively, these results indicate that STAT3, FAK and Src are over expressed and activated in BCSCs.

Figure 4: STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

  • Representative picture indicating mammosphere and single suspended cells. (B) Schematic outline of mammosphere enrichment. (C) Protein expression and activation of STAT3, FAK and Src was determined in single suspended cells (non-mammosphere forming cells) and mammospheres by western blot. The full size blots corresponding to the cropped blot images are given in  S10. (D) Gene expression of STAT3, FAK and Src was determined in MCF7 parent population and CD44+ CD24−/low MCF7 cells using PCR. The full agarose gel images corresponding to the cropped images are given in Fig. S10. (E) Protein expression and activation of STAT3, FAK and Src was in CD44+ 24− cells and parent population.

STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f4.jpg

STAT3 is important for mammosphere formation and CSC programs in breast cancer

As our results indicated that the expression and activation of STAT3, FAK and Src is high in BCSCs and Shk is capable of inhibiting these signaling proteins; therefore to find out functional relevance of each protein and associated effects on their pharmacological inhibition by Shk, we used specific inhibitors against these three. Effect of these inhibitors was first tested on the mammosphere forming potential of MDA-MB 231, MDA-MB 468 and MCF7 cells. A drastic reduction in the mammosphere formation was observed upon STAT3 inhibition. FAK and Src inhibition also reduced the primary and secondary mammosphere formation but STAT3 inhibition showed most potent effect (Fig. 5A and S4). Further, we also checked the effect of these inhibitors on the expression of various CSC and EMT related markers in MDA-MB 231 cells. STAT3 inhibition decreased the expression of most of the CSC and EMT markers (Fig. 5B). These two findings indicated that STAT3 inhibition is more effective in reducing mammosphere forming potential and weakens major CSC programs and the anti-CSC potential of Shk is possibly due to its strong STAT3 inhibitory effect.
(not shown)

STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer

STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer

Figure 5: STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer.

http://www.nature.com/srep/2015/150514/srep10194/carousel/srep10194-f5.jpg

(A) Bar graph represents number of mammospheres formed from 2500 cells in presence and absence of indicated treatments. MDA-MB 231, MDA-MB 468 and MCF7 24 h mammosphere cultures were treated with Shk (2.5 μM), FAK inhibitor (FAK inhibitor 14; 2.5 μM), Src inhibitor (AZM 475271; 10 μM) and STAT3 inhibitor (WP1066; 10 μM). After 24 h, treatments were removed and cells were allowed to grow in fresh mammosphere culture media for 8 days. (B) Expression of various stem cell and EMT related transcription factors and markers were detected using western blotting in MDA-MB 231 cells with or without indicated treatments. The full size blots corresponding to the cropped blot images are given in Fig. S10. (C) MDA-MB 231, MDA-MB 468 and MCF7 cells were pre-treated with either IL6 (100 ng ml−1), Fibronectin (1 μg ml−1) or EGF (25 ng ml−1) for two population doublings and subjected to mammosphere formation. Bar graph represents average of three independent experiments. (D) MCF7 cells were pre-treated with either IL6 (100 ng ml−1), Fibronectin (1 μg ml−1) or EGF (25 ng ml−1) for two population doublings and subjected to mammosphere formation. After 24 h, cells were treated with DMSO (untreated) or Shk (treated) as indicated in the bar graph. Data are shown as the mean ±SD. (*) p < 0.05 and (**) p < 0.01.

To further check the involvement of these pathways in CSCs, we cultured MDA-MB 231, MDA-MB 468 and MCF7 cells in the presence of either IL6 (100ng ml−1), EGF (25 ng ml−1) or Fibronectin (1 μg ml−1) coated surface for two population doublings. Cells were then subjected to mammosphere formation. In IL6 pre-treated cultures, there was a sharp rise in mammosphere formation, indicating that the STAT3 activation shifts CSC and non-CSC dynamics towards CSCs (Fig. 5C). IL6 is previously known to induce the conversion of non-CSC to CSC via STAT3 activation26. In MCF7 cells, mammosphere forming potential after IL6 pre-treatment increased nearly by three fold. Therefore, we further checked the effectiveness of Shk on mammosphere forming potential in pre-treated MCF7 cells. It was found that Shk inhibits mammosphere formation most effectively in IL6 pre-treated cultures (Fig. 5D). However, in EGF and Fibronectin pre-treated cultures, Shk was relatively less effective. This was possibly due to its weak FAK and Src inhibitory potential. Collectively, these results illustrated that STAT3 activation is significantly correlated with the mammosphere forming potential of breast cancer cells and its inhibition by a standard inhibitor or Shk potently reduce the mammosphere formation.

Shk inhibit CSCs load by disrupting the STAT3-Oct3/4 axis

In breast cancer, STAT3 mediated expression of Oct3/4 is a major regulator of CSC self-renewal2627. As we observed that both Shk and STAT3 inhibitors decreased the Oct3/4 expression (Figs. 2C and 5B), we further checked the effect of STAT3 activation on ALDH1+ CSCs and Oct3/4 expression. On IL6 pre-treatment, number of ALDH1+ cells increased in all three (MDA-MB 231, MDA-MB 468 and MCF7) cancer cells (Fig. 6A). MCF7 cells showed highest increase. Therefore, to check the effect of STAT3 inhibition on CSC load, we incubated IL6 pre-treated MCF7 cells with Shk and STAT3 inhibitor for 24 h and analyzed for ALDH1 positivity. It was observed that both Shk and STAT3 inhibitor reduced the IL6 induced ALDH1 positivity from 10% to < 2% (Fig. 6B). These results suggested that Shk induced inhibition of STAT3 and decrease in BCSC load is interlinked. We further checked the effect of STAT3 activation status on Oct3/4 expression in MDA-MB 231, MDA-MB 468 and MCF7 cells. We observed that expression of Oct3/4 increases with the increase in STAT3 activation (Fig. 6C–E).

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Figure 6: STAT3 activation status and its effect on cancer stem cell load

STAT3 transcriptional activity is important in maintaining CSC programs2829. Therefore, we also examined the effect of Shk on STAT3 promoter activity. STAT3 reporter assay was performed in presence of IL6 and Shk; it was found that Shk reduced the promoter activity of STAT3 in a dose dependent manner (Fig. S5). Collectively, these results showed that Shk mediated STAT3 inhibition are responsible for decrease in CSC load and Oct3/4 associated stem cell programs.

Shk inhibits mammosphere formation, migration and invasion through inhibition of STAT3, FAK and Src in breast cancer cells

As the earlier results (Fig. 1) showed that Shk inhibits cell migration and invasion in breast cancer cells, we further examined the effect of STAT3, FAK and Src inhibitors on cell migration and invasion in MDA-MB 231 cells. It was found that STAT3 inhibitor poorly inhibits cell migration while both Src and FAK inhibitors were effective in reducing cell migration (Fig. 7A). All the three inhibitors decreased the cell invasion and MMP9 expression significantly (Fig. 7B and S6). It was also observed that effect of all these inhibitors, except STAT3 inhibitor on mammosphere formation and FAK inhibitor on cell migration, were not comparable to that of Shk. Shk inhibited all these properties more effectively than individual inhibition of STAT3, FAK and Src. This made us to assume that the ability of Shk to inhibit multiple signaling molecules simultaneously is the reason behind its potent anti-cancer effect. To check this notion, we combined STAT3, FAK and Src inhibitors with each other and examined the effect of combinations on invasion, migration and mammosphere forming potential in MDA-MB 231 cells. We observed further decrease in cell migration and invasion on combining STAT3 and FAK, STAT3 and Src, or FAK and Src (Figs. 7A,B). Combination of FAK and Src was not very effective in inhibiting mammosphere formation in MDA-MB 231 cells and CD44+ CD24− MCF7 CSCs. However, their combination with STAT3 decreased the mammosphere forming potential equivalent to that of Shk (Fig. 7C,D). We also compared the mammosphere forming potential of Shk with Salinomycin (another anti-CSC agent) and found that at 2.5 μM dose of Shk was almost two times more potent than Salinomycin (Fig. S7). Collectively, these results indicated that Shk inhibits multiple signaling proteins (STAT3, FAK and Src) to compromise various aggressive breast cancer hallmarks.

Figure 7: Combination of FAK, Src and STAT3 inhibitors is more potent than individual inhibition against various cancer hallmarks.

combination-of-fak-src-and-stat3-inhibitors-is-more-potent-than-individual-inhibition-against-various-cancer-hallmarks

combination-of-fak-src-and-stat3-inhibitors-is-more-potent-than-individual-inhibition-against-various-cancer-hallmarks

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f7.jpg

  • Cell migration and (B) cell invasion potential of MDA-MB 231 cells was assessed in the presence of Shk (2.5 μM), FAK inhibitor (FAK inhibitor 14; 2.5 μM), Src inhibitor (AZM 475271; 10 μM) and STAT3 inhibitor (WP1066; 10 μM). Various combinations of these inhibitors were also used STAT3+FAK inhibitor (WP1066; 10 μM + FAK inhibitor 14; 2.5 μM), STAT3 + Src Inhibitor (WP1066; 10 μM + AZM 475271; 10 μM) and FAK+Src Inhibitor (FAK inhibitor 14; 2.5 μM + AZM 475271; 10 μM). Cell migration and cell invasion was assessed through scratch cell migration assay and transwell invasion after 24 h of treatments. (C,D) Mammosphere forming potential of MDA-MB 231 cells and CD44+ CD24−/low enriched MCF7 cells was assessed in presence of similar combination of STAT3+FAK inhibitor (WP1066; 10 μM + FAK inhibitor 14; 2.5 μM), STAT3 + Src Inhibitor (WP1066; 10 μM+ AZM 475271; 10 μM) and FAK + Src Inhibitor (FAK inhibitor 14; 2.5 μM + AZM 475271; 10 μM). Cells were subjected to mammosphere cultures for 24 h and treated with the indicated inhibitors for next 24 h, followed by media change and growth of mammospheres were monitored for next 8 days. Data are shown as the mean ±SD. (**) p < 0.01.

Shk inhibits breast cancer growth, metastasis and decreases tumorigenicity

To explore whether Shk may have therapeutic potential for breast cancer treatment in vivo, we tested Shk against 4T1-induced breast cancer syngenic mouse model. 4T1 cells (mouse breast cancer cells) are capable of growing fast and metastasize efficiently in vivo30. Prior to the in vivo experiments, we checked the effect of Shk on ALDH1 positivity and on activation of STAT3, FAK and Src in 4T1 cells in vitro. Shk effectively decreased the ALDH1+ cells and inhibited STAT3, FAK and Src in 4T1 cells in vitro (Fig. S8A and S8B). For in vivo tumor generation, 1 × 106 cells were injected subcutaneously in the fourth nipple mammary fat pad of BALB/c mice. When the average size of tumors reached around 50 mm3, mice were divided into three groups, vehicle and two Shk treated groups each received either 2.5 mg Kg−1 or 5.0 mg Kg−1 Shk. Shk was administered via the intraperitoneal injection on every alternate day. It significantly suppressed the tumor growth in 4T1 induced syngenic mouse model (Fig. 8A). The average reduction in 4T1 tumor growth was 49.78% and 89.73% in 2.5 mg Kg−1 and 5.0 mg Kg−1 groups respectively compared with the vehicle treated group (Fig. 8A). No considerable change in body weight of the treated group animals was observed (Fig. S9A). We further examined the effect of Shk on the tumor initiating potential of breast cancer cells. 4T1 induced tumors were excised from the control and treatment groups on the second day after 4th dose of Shk was administered. Tumors were dissociated; cells were allowed to adhere and then re-injected into new animals for secondary tumor formation. Growth of secondary tumors was monitored till day 15 post-reinjection. Shk treated groups showed a marked decrease in secondary tumor formation (Fig. 8D). We also observed a drastic reduction in the number of metastatic nodules in the lungs of treatment group animals (Fig. 8F). The reduction in the metastatic load was not proportional to the decrease in tumor sizes; however within the treatment group, some animals with small tumors were carrying higher number of metastatic nodules. As FAK is an important mediator of cancer metastasis and metastatic colonization, we further examined the effects of Shk on metastatic colonization. For this, 1 × 105 4T1 cells were injected to BALB/c mice through tail vein. Animals were divided into three groups, as indicated above. Shk and vehicle were administered through intraperitoneal injections at alternate days starting from the 2nd day post tail vein injections till 33rd day. The average reduction in total number of metastatic nodules was 88.6% – 90.5% in Shk treated mice compared to vehicle control (Fig. 8F). An inset picture (Fig. 8A lower panel) represents lung morphology of vehicle control and treated groups. We further examined the activation and expression status of STAT3, FAK and Src between vehicle control and treated group tumors. There were low expression and activation of STAT3, FAK and Src in treated tumors as compared to the vehicle control (Fig. 8B,C). Similar trend was observed in ALDH1 expressions (Fig. 8B). Further, the mice tumor sections were subjected to immunohistochemistry, immunofluorescence and hematoxylin and eosin (H&E) staining to study histology and expression of key proteins being examined in this study. Fig. 8G shows representative images of H&E staining, proliferating cell nuclear antigen (PCNA), terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), STAT3 and Oct3/4 immunostaining. PCNA expression was low while TUNEL positive cells were high in tumor tissues of Shk treated groups. STAT3 and Oct3/4 expression was low in Shk treated groups. These results collectively demonstrated that Shk modulates the expression and activation of STAT3, FAK and Src in vivo and is effective in suppressing tumorigenic potential and metastasis in syngenic mouse model.

Figure 8: Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo.

Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo

Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f8.jpg

  • Shk inhibited 4T1 tumor growth. Bar graph represents the average tumor volumes in vehicle control and Shk treated tumor bearing mice (n = 6). (*) p < 0.05 and (**) p < 0.01. Inset picture of upper panel represents tumor sizes and lower pane represents lung morphology in vehicle control and Shk treatment groups. (B) Western blot examination of indicated proteins for their expression and activation in vehicle control and treated tumor groups. The full size blots corresponding to the cropped blot images are given in Fig. S10. (C) Gene expression of stem cell and EMT markers in tumor tissues excised from the vehicle control and Shk treated groups (n = 3). (D) Number of secondary tumors formed after injecting indicated cell dilutions from Vehicle treated and Shk treated 4T1 tumors. (E) Number of lung nodules formed in mice injected with 4T1 mouse mammary tumor cells in the mammary fat pad and administered with 2.5 mg Kg−1 Shk or vehicle control on every alternate day for 3 weeks (n = 6). (F) Number of lung nodules in mice injected with 4T1 mouse mammary tumor cells through tail vein and administered with 2.5 mg Kg−1 Shk or vehicle control on every alternate day for 3 weeks. (n = 8) (G) Representative panel of the histological H&E staining, immunofluorescence staining for the STAT3, Oct3/4, cell proliferation marker PCNA and DNA damage indicator-TUNEL staining of tumor sections from vehicle and treatment groups.

Recent studies have shown that aggressiveness, therapy resistance and disease relapse in breast cancer is attributed to a small population of CSCs involved in continuous self-renewal and differentiation through signaling pathways similar to that of the normal stem cells31. Therapeutic targeting of CSCs therefore, has profound clinical implications for cancer treatment31. Recent studies indicated that therapies / agents targeting both differentiated cancer cells and CSCs may possibly have significant therapeutic advantages32. Therefore, it is imperative to look for novel therapeutic agents with lesser side effects urgently for effective targeting of CSCs. In search of novel, nontoxic anti-CSC agents, attention has been focused on natural agents in recent times33,34. In this study, we have used a natural napthoquinone compound, Shk with established antitumorigenic, favorable pharmacokinetic and toxicity profiles and report for the first time its potent anti-CSC properties. Shk significantly inhibits breast cancer cell proliferation in vitroex vivoand in vivo. It decreases the cell migration and invasion of breast cancer cells in vivo, as well as inhibits tumorigenicity, metastasis and metastatic colonization in a syngenic mouse model of breast cancer in vivo. These finding suggest a strong potential of Shk in breast cancer therapy.

We assessed the effect of Shk on the CSC load in breast cancer cells through various functional assays (tumorsphere in vitro and syngenic mouse model of breast cancer in vivo) and quantification of specific stem cell markers. In breast cancer, CD44+ CD24− cells and ALDH1+ cells are considered to be BCSCs2125. Shk significantly decreased the mammosphere formation (Fig. 1HS1G and 2H), ALDH1+ cell and CD44+ CD24− cell loads in vitro (Fig. 2BS2E and S2H). It also reduced the expression of CSC markers (Oct3/4, Sox2, Nanog, c-Myc and Aldh1) in vivo andin vitro (Fig. 2C,DS2C and S2D). These genes are known to regulate stem cell programs and in cancer, they are established promoters and regulators of CSC phenotype353637383940. Decrease in the expression of these genes on Shk treatment indicates its potential to suppress CSC programs. Tumor initiating potential (tumorigenicity) is the bona fide measure of CSCs. Reduction in the tumorigenic potential of cells isolated form Shk treated tumors indicates in vivoanti-CSC effects of Shk.

We further demonstrated that Shk is a potent inhibitor of STAT3 and it also inhibits FAK and Src (Fig. 3A–C). Its STAT3 inhibitory property was found to be responsible for its anti-CSC effects (Figs. 6B and 7B). STAT3 and FAK inhibitors are previously known to compromise CSC growth41,42. Here, we found that pharmacological inhibition of STAT3 was more effective in compromising CSC load than FAK and Src inhibitions (Fig. 5A). STAT3 activation through IL6 increases mammosphere formation more significantly than Src and FAK activation through EGF and Fibronectin (Fig. 5C). This indicates that IL6-STAT3 axis is a key regulator of BCSC dynamics.

11.2.3.9 Ovatodiolide Sensitizes Aggressive Breast Cancer Cells to Doxorubicin Anticancer Activity, Eliminates Their Cancer Stem Cell-Like Phenotype, and Reduces Doxorubicin-Associated Toxicity

Investigators evaluated the usability of ovatodiolide (Ova) in sensitizing triple negative breast cancer (TNBC) cells to doxorubicin (Doxo), cytotoxicity, so as to reduce Doxo effective dose and consequently its adverse effects. Ova-sensitized TNBC cells also lost their cancer stem cell-like phenotype evidenced by significant dissolution and necrosis of formed mammospheres, as well as their terminal differentiation. [Cancer Lett]

11.2.3.10 Glabridin Inhibits Cancer Stem Cell-Like Properties of Human Breast Cancer Cells: An Epigenetic Regulation of miR-148a/SMAd2 Signaling

The authors report that glabridin (GLA) attenuated the cancer stem cell (CSC)-like properties through microRNA-148a (miR-148a)/transforming growth factor beta-SMAD2 signal pathway in vitro and in vivo. In MDA-MB-231 and Hs-578T breast cancer cell lines, GLA enhanced the expression of miR-148a through DNA demethylation. [Mol Carcinog]

11.2.3.11 Ginsenoside Rh2 Inhibits Cancer Stem-Like Cells in Skin Squamous Cell Carcinoma

The effects of ginsenoside Rh2 (GRh2) on Lgr5-positive cancer stem cells (CSCs) were determined by flow cytometry and by tumor sphere formation. Scientists found that GRh2 dose-dependently reduced skin squamous cell carcinoma viability, possibly through reduced the number of Lgr5-positive CSCs. [Cell Physiol Biochem]

Liu S. Chen M. Li P. Wu Y. Chang C. Qiu Y. Cao L. Liu Z. Jia C.
Cell Physiol Biochem 2015;36:499-508
http://dx.doi.org:/10.1159/000430115

Background/Aims: Treatments targeting cancer stem cells (CSCs) are most effective cancer therapy, whereas determination of CSCs is challenging. We have recently reported that Lgr5-positive cells are cancer stem cells (CSCs) in human skin squamous cell carcinoma (SCC). Ginsenoside Rh2 (GRh2) has been shown to significantly inhibit growth of some types of cancers, whereas its effects on the SCC have not been examined. Methods: Here, we transduced human SCC cells with lentivirus carrying GFP reporter under Lgr5 promoter. The transduced SCC cells were treated with different doses of GRh2, and then analyzed cell viability by CCK-8 assay and MTT assay. The effects of GRh2 on Lgr5-positive CSCs were determined by fow cytometry and by tumor sphere formation. Autophagy-associated protein and β-catenin were measured by Western blot. Expression of short hairpin small interfering RNA (shRNA) for Atg7 and β-catenin were used to inhibit autophagy and β-catenin signaling pathway, respectively, as loss-of-function experiments. Results: We found that GRh2 dose-dependently reduced SCC viability, possibly through reduced the number of Lgr5-positive CSCs. GRh2 increased autophagy and reduced β-catenin signaling in SCC cells. Inhibition of autophagy abolished the effects of GRh2 on β-catenin and cell viability, while increasing β-catenin abolished the effects of GRh2 on autophagy and cell viability. Conclusion: Taken together, our data suggest that GRh2 inhibited SCC growth, possibly through reduced the number of Lgr5-positive CSCs. This may be conducted through an interaction Carcinoma account for more than 80% of all types of cancer worldwide, and squamous cell carcinoma (SCC) is the most frequent carcinoma. Skin SCC causes a lot of mortality yearly, which requires a better understanding of the molecular carcinogesis of skin SCC for developing efficient therapy [1,2]. Ginsenoside Rh2 (GRh2) is a characterized component in red ginseng, and has proven therapeutic effects on inflammation [3] and a number of cancers [4,5,6,7,8,9,10,11,12,13,14], whereas its effects on the skin SCC have not been examined.

Cancer stem cells (CSCs) are cancer cells with great similarity to normal stem cells, e.g., the ability to give rise to various cell types in a particular cancer [15,16]. CSCs are highly tumorigenic, compared to other non-CSCs. CSCs appear to persist in tumors as a distinct population and CSCs are believed to be responsible for cancer relapse and metastasis after primary tumor resection [15,16,17,18]. Recently, the appreciation of the critical roles of CSCs in cancer therapy have been continuously increasing, although the identification of CSCs in a particular cancer is still challenging.

To date, different cell surface proteins have been used to isolate CSCs from a variety of cancers by flow cytometry. Among these markers for identification of CSCs, the most popular ones are prominin-1 (CD133), side population (SP) and increased activity of aldehyde dehydrogenase (ALDH). CD133 is originally detected in hematopoietic stem cells, endothelial progenitor cells and neuronal and glial stem cells. Later on, CD133 has been shown to be expressed in the CSCs from some tumors [19,20,21,22,23], but with exceptions [24]. SP is a sub-population of cells that efflux chemotherapy drugs, which accounts for the resistance of cancer to chemotherapy. Hoechst (HO) has been experimentally used for isolation of SP cells, while the enrichment of CSCs by SP appears to be limited [25]. Increased activity of ALDH, a detoxifying enzyme responsible for the oxidation of intracellular aldehydes [26,27], has also been used to identify CSCs, using aldefluor assay [28,29]. However, ALDH has also been detected in other cell types, which creates doubts on the purity of CSCs using ALDH method [30,31]. Moreover, all these methods appear to be lack of cancer specificity.

The Wnt target gene Lgr5 has been recently identified as a stem cell marker of the intestinal epithelium, and of the hair follicle [32,33]. Recently, we reported that Lgr5 may be a potential CSC marker for skin SCC [34]. We detected extremely high Lgr5 levels in the resected skin SCC specimen from the patients. In vitro, Lgr5-positive SCC cells grew significantly faster than Lgr5-negative cells, and the fold increase in growth of Lgr5-positive vs Lgr5-negative cells is significantly higher than SP vs non-SP, or ALDH-high vs ALDH-low, or CD133-positive vs CD133-negative cells. Elimination of Lgr5-positive SCC cells completely inhibited cancer cell growth in vitro.

Here, we transduced human SCC cells with lentivirus carrying GFP reporter under Lgr5 promoter. The transduced SCC cells were treated with different doses of GRh2, and then analyzed cell viability by CCK-8 assay and MTT assay. The effects of GRh2 on Lgr5-positive CSCs were determined by flow cytometry and by tumor sphere formation. Autophagy-associated protein and β-catenin were measured by Western blot. Expression of short hairpin small interfering RNA (shRNA) for autophagy-related protein 7 (Atg7) and β-catenin were used to inhibit autophagy and β-catenin signaling pathway, respectively, as loss-of-function experiments. Atg7 was identified based on homology to Pichia pastoris GSA7 and Saccharomyces cerevisiae APG7. In the yeast, the protein appears to be required for fusion of peroxisomal and vacuolar membranes. The protein shows homology to the ATP-binding and catalytic sites of the E1 ubiquitin activating enzymes. Atg7 is a mediator of autophagosomal biogenesis, and is a putative regulator of autophagic function [35,36,37,38]. We found that GRh2 dose-dependently reduced SCC viability, possibly through reduced the number of Lgr5-positive CSCs. GRh2 increased autophagy and reduced β-catenin signaling in SCC cells. Inhibition of autophagy abolished the effects of GRh2 on β-catenin and cell viability, while increasing β-catenin abolished the effects of GRh2 on autophagy and cell viability.

Transduction of SCC cells with GFP under Lgr5 promoter

We have recently shown that Lgr5 is CSC marker for skin SCC [34]. In order to examine the role of GRh2 on SCC cells, as well as a possible effect on CSCs, we transduced human skin SCC cells A431 [34] with a lentivirus carrying GFP reporter under Lgr5 promoter (Fig. 1A). The Lgr5-positive cells were green fluorescent in culture (Fig. 1B), and could be analyzed or isolated by flow cytometry, based on GFP (Fig. 1C).

(not shown)

Fig. 1. Transduction of SCC cells with GFP under Lgr5 promoter. (A) The structure of lentivirus carrying GFP reporter under Lgr5 promoter. (B) The pLgr5-GFP-transduced A431 cells in culture. Lgr5-positive cells were green fluorescent. Nuclear staining was done by DAPI. (C) Representative flow chart for analyzing pLgr5-GFP-transduced A431 cells by flow cytometry based on GFP. Gated cells were Lgr5-positive cells. Scar bar is 20µm.

GRh2 dose-dependently inhibits SCC cell growth

Then, we examined the effect of GRh2 on the viability of SCC cells. We gave GRh2 at different doses (0.01mg/ml, 0.1mg/ml and 1mg/ml) to the cultured pLgr5-GFP-transduced A431 cells. We found that from 0.01mg/ml to 1mg/ml, GRh2 dose-dependently deceased the cell viability in either a CCK-8 assay (Fig. 2A), or a MTT assay (Fig. 2B). Next, we questioned whether GRh2 may have a specific effect on CSCs in SCC cells. Thus, we analyzed GFP+ cells, which represent Lgr5-positive CSCs in pLgr5-GFP-transduced A431 cells after GRh2 treatment. We found that GRh2 dose-dependently deceased the percentage of GFP+ cells, by representative flow charts (Fig. 2C), and by quantification (Fig. 2D). We also examined the capability of the GRh2-treated cells in the formation of tumor sphere. We found that GRh2 dose-dependently deceased the formation of tumor sphere-like structure, by quantification (Fig. 2E), and by representative images (Fig. 2F). Together, these data suggest that GRh2 dose-dependently inhibited SCC cell growth, possibly through inhibition of CSCs.

Fig. 2. GRh2 dose-dependently inhibits SCC cell growth. We gave GRh2 at different doses (0.01mg/ml, 0.1mg/ml and 1mg/ml) to the cultured pLgr5-GFP-transduced A431 cells. (A-B) GRh2 dose-dependently deceased the cell viability in either a CCK-8 assay (A), or a MTT assay (B). (C-D) GFP+ cells after GRh2 treatment were analyzed by flow cytometry, showing that GRh2 dose-dependently deceased the percentage of GFP+ cells, by representative flow charts (C), and by quantification (D). The capability of the GRh2-treated cells to form tumor sphere-like structures was examined, shown by quantification (E), and by representative images (F). *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f02.JPG

GRh2 treatment decreases β-catenin and increases autophagy in SCC cells

We analyzed the molecular mechanisms underlying the cancer inhibitory effects of GRh2 on SCC cells. We thus examined the growth-regulatory proteins in SCC. From a variety of proteins, we found that GRh2 treatment dose-dependently decreases β-catenin, and dose-dependently upregulated autophagy-related proteins Beclin, Atg7 and increased the ratio of LC3 II to LC3 I, by quantification (Fig. 3A), and by representative Western blots (Fig.3B). Since β-catenin signaling is a strong cell-growth stimulator and autophagy can usually lead to stop of cell-growth and cell death, we feel that the alteration in these pathways may be responsible for the GRh2-mediated suppression of SCC growth.

(not shown)

Figure 3. GRh2 treatment decreases β-catenin and increases autophagy in SCC cells.

http://www.karger.com/Article/ShowPic/430115?image=000430115_f03.JPG

Inhibition of autophagy abolishes the effects of GRh2 on β-catenin

In order to find out the relationship between β-catenin and autophagy in this model, we inhibited autophagy using a shRNA for Atg7, and examined its effect on the changes of β-catenin by GRh2. First, the inhibition of Atg7 in A431 cells by shAtg7 was confirmed by RT-qPCR (Fig. 4A), and by Western blot (Fig. 4B). Inhibition of Atg7 resulted in abolishment of the effects of GRh2 on other autophagy-associated proteins (Fig. 4B), and resulted in abolishment of the inhibitory effect of GRh2 on β-catenin (Fig. 4B). Moreover, the effects of GRh2 on cell viability were completely inhibited (Fig. 4C). Together, inhibition of autophagy abolishes the effects of GRh2 on β-catenin. Thus, the regulation of GRh2 on β-catenin needs autophagy-associated proteins.

Fig. 4. Inhibition of autophagy abolishes the effects of GRh2 on β-catenin.

A431 cells were transfected with shRNA for Atg7, or scrambled sequence (scr) as a control. (A) RT-qPCR for Atg7. (B) Quantification of β-catenin, Beclin, Atg7 and LC3 by Western blot. (C) Cell viability by CCK-8 assay. *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f04.JPG

Overexpression of β-catenin abolishes the effects of GRh2 on autophagy

Next, we inhibited the effects of GRh2 on β-catenin by overexpression of β-catenin in A431 cells. First, the overexpression of β-catenin in A431 cells was confirmed by RT-qPCR (Fig. 5A), and by Western blot (Fig. 5B). Overexpression of β-catenin resulted in abolishment of the effects of GRh2 on autophagy-associated proteins (Fig. 5B). Moreover, the effects of GRh2 on cell viability were completely inhibited (Fig. 5C). Together, inhibition of β-catenin signaling abolishes the effects of GRh2 on autophagy. Thus, the regulation of GRh2 on autophagy needs β-catenin signaling. This model is thus summarized in a schematic (Fig. 6), suggesting that GRh2 may target both β-catenin signaling and autophagy, which interacts with each other in the regulation of SCC cell viability and growth.

http://www.karger.com/Article/ShowPic/430115?image=000430115_f05.JPG

Fig. 5. Overexpression of β-catenin abolishes the effects of GRh2 on autophagy. A431 cells were transfected with β-catenin, or scrambled sequence (scr) as a control. (A) RT-qPCR for β-catenin. (B) Quantification of β-catenin, Beclin, Atg7 and LC3 by Western blot. (C) Cell viability by CCK-8 assay. *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f06.JPG

Fig. 6. Schematic of the model. GRh2 may target both β-catenin signaling and autophagy, which interacts with each other in the regulation of SCC cell viability and growth.

Understanding the cancer molecular biology of skin SCC and identification of an effective treatment are both critical for improving the current therapy [1]. Lgr5 has been recently identified as a novel stem cell marker of the intestinal epithelium and the hair follicle, in which Lgr5 is expressed in actively cycling cells [32,33]. Moreover, we recently showed that Lgr5-positive are CSCs in skin SCC [34]. Thus, specific targeting Lgr5-positive cells may be a promising therapy for skin SCC.

In the current study, we analyzed the effects of GRh2 on the viability of SCC. Importantly, we not only found that GRh2 dose-dependently decreases SCC cell viability, but also dose-dependently decreased the number of Lgr5-positive CSCs in SCC cells. These data suggest that the CSCs in SCC may be more susceptible for the GRh2 treatment, and the decreases in CSCs may result in the decreased viability in total SCC cells. This point was supported by following mechanism studies. Activated β-catenin signaling by WNT/GSK3β prevents degradation of β-catenin and induces its nuclear translocation [39]. Nuclear β-catenin thus activates c-myc, cyclinD1 and c-jun to promote cell proliferation, and activates Bcl-2 to inhibit apoptosis [39]. High β-catenin levels thus are a signature of CSCs. Therefore, it is not surprising that CSCs are more affected than other cells when GRh2 targets β-catenin signaling.

In addition, GRh2 appears to target autophagy. Although altered metabolism may be beneficial to the cancer cells, it can create an increased demand for nutrients to support cell growth and proliferation, which creates metabolic stress and subsequently induces autophagy, a catabolic process leading to degradation of cellular components through the lysosomal system [40]. Cancer cells use autophagy as a survival strategy to provide essential biomolecules that are required for cell viability under metabolic stress [40]. However, autophagy not only results in a staring in cell growth, but also may result in cell death [40]. Increases in autophagy may substantially decrease cancer cell growth. Thus, GRh2 has its inhibitory effect on skin SCC cells through a combined effect on cell proliferation (by decreasing β-catenin) and autophagy [40].

Interestingly, our data suggest an interaction between β-catenin and autophagy. This finding is consistent with previous reports showing that autophagy negatively modulates Wnt/β-catenin signaling by promoting Dvl instability [41,42], and with other studies showing that β-catenin regulates autophagy [38,43,44].

Of note, we have checked other SCC lines and essentially got same results. Together with our previous reports showing that Lgr5-positive cells are CSCs in skin SCC [34], these findings thus highlight a future engagement of Lgr5-directed GRh2 therapy, which could be performed in a sufficiently frequent manner, to substantially improve the current treatment for skin SCC.

Normal vs Cancer Thyroid Stem Cells: The Road to Transformation
The authors discuss new insights into thyroid stem cells as a potential source of cancer formation in light of the available information on the oncogenic role of genetic modifications that occur during thyroid cancer development. Understanding the fine mechanisms that regulate tumor transformation may provide new ground for clinical intervention in terms of prevention, diagnosis and therapy. [Oncogene] Abstract
Cancer Stem Cells: A Potential Target for Cancer Therapy
The identification of cancer stem cells (CSCs) and a better understanding of the complex characteristics of CSCs will provide invaluable diagnostic, therapeutic and prognostic targets for clinical application. The authors introduce the dysregulated properties of CSCs in cancers and discuss the possible challenges in targeting CSCs for cancer treatment. [Cell Mol Life Sci] Abstract
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