Evolutionary cognition | Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Glycobiology is an important field of study with medical applications because it is known that tumor cells alter their glycosylation pattern, which may contribute to their metastatic potential as well as potential immune evasion. [iStock/© vjanez] http://www.genengnews.com/media/images/AnalysisAndInsight/Apr12_2016_iStock_41612310_PlasmaMembraneOfACell1211657142.jpg

There is growing interest in the field of glycobiology given the fact that epitopes with physiological and pathological relevance have glyco moieties. We believe that another “omics” revolution is on the horizon—the study of the glyco modifications on the surface of cells and their potential as biomarkers and therapeutic targets in many disease classes. Not much industry tracking of this field has taken place. Thus, we sought to map this landscape by examining the entire ensemble of academic publications in this space and teasing apart the trends operative in this field from a qualitative and quantitative perspective. We believe that this methodology of en masse capture and publication and annotation provides an effective approach to evaluate this early-stage field.

Identifiation and Growth of Glycobiology Publications

http://www.genengnews.com/Media/images/AnalysisAndInsight/thumb_April12_2016_SelectBiosciences_Figure11935315421.jpg

For this article, we identified 7000 publications in the broader glycobiology space and analyzed them in detail. It is important to frame glycobiology in the context of genomics and proteomics as a means to assess the scale of the field. Figure 1 presents the relative sizes of these fields as assessed by publications in from 1975 to 2015.

Note that the relative scale of genomics versus proteomics and glycobiology/glycomics in this graph strongly suggests that glycobiology is a nascent space, and thus a driver for us to map its landscape today and as it evolves over the coming years.

Figure 2. (A) Segmentation of the glycobiology landscape. (B) Glycobiology versus glycomics publication growth.

http://www.genengnews.com/Media/images/AnalysisAndInsight/thumb_April12_2016_SelectBiosciences_Figure2ab1917013624.jpg

To examine closely the various components of the glycobiology space, we segmented the publications database, presented in Figure 2A. Note the relative sizes and growth rates (slopes) of the various segments.

Clearly, glycoconjugates currently are the majority of this space and account for the bulk of the publications. Glycobiology and glycomics are small but expanding and therefore can be characterized as “nascent market segments.” These two spaces are characterized in more detail in Figure 2B, which presents their publication growth rates.

Note the very recent increased attention directed at these spaces and hence our drive to initiate industry coverage of these spaces. Figure 2B presents the overall growth and timeline of expansion of these fields—especially glycobiology—but it provides no information about the qualitative nature of these fields.

Focus of Glycobiology Publications

http://www.genengnews.com/Media/images/AnalysisAndInsight/April12_2016_SelectBiosciences_Figure2c1827601892.jpg

Figure 2C. Word cloud based on titles of publications in the glycobiology and glycomics spaces.

To understand the focus of publications in this field, and indeed the nature of this field, we constructed a word cloud based on titles of the publications that comprise this space presented in Figure 2C.

There is a marked emphasis on terms such as oligosaccharides and an emphasis on cells (this is after all glycosylation on the surface of cells). Overall, a pictorial representation of the types and classes of modifications that comprise this field emerge in this word cloud, demonstrating the expansion of the glycobiology and to a lesser extent the glycomics spaces as well as the character of these nascent but expanding spaces.

Characterization of the Glycobiology Space in Journals

Figure 3A. Breakout of publications in the glycobiology/glycomics fields. http://www.genengnews.com/Media/images/AnalysisAndInsight/April12_2016_SelectBiosciences_Figure3a_5002432117316.jpg
Having framed the overall growth of the glycobiology field, we wanted to understand its structure and the classes of researchers as well as publications that comprise this field. To do this, we segmented the publications that constitute this field into the various journals in which glycobiology research is published. Figure 3A presents the breakout of publications by journal to illustrate the “scope” of this field.

The distribution of glycobiology publications across the various journals suggests a very concentrated marketplace that is very technically focused. The majority of the publications segregate into specialized journals on this topic, a pattern very indicative of a field in the very early stages of development—a truly nascent marketplace.

http://www.genengnews.com/Media/images/AnalysisAndInsight/thumb_April12_2016_SelectBiosciences_Figure3b1012091061.jpg

Figure 3B. Origin of publications in the glycobiology/glycomics fields.
We also sought to understand the “origin” of these publications—the breakout between academic- versus industry-derived journals. Figure 3B presents this breakout and shows that these publications are overwhelmingly (92.3%) derived from the academic sector. This is again a testimonial to the early nascent nature of this marketplace without significant engagement by the commercial sector and therefore is an important field to characterize and track from the ground up.

Select Biosciences, Inc. further analyzed the growth trajectory of the glycobiology papers in Figure 3C as a means to examine closely the publications trajectory. Although there appears to be some wobble along the way, overall the trajectory is upward, and of late it is expanding significantly.

In Summary

Figure 3C. Trajectory of the glycobiology space. http://www.genengnews.com/Media/images/AnalysisAndInsight/April12_2016_SelectBiosciences_Figure3c1236921793.jpg
Glycobiology is the study of what coats living cells—glycans, or carbohydrates, and glycoconjugates. This is an important field of study with medical applications because it is known that tumor cells alter their glycosylation pattern, which may contribute to their metastatic potential as well as potential immune evasion.

At this point, glycobiology is largely basic research and thus it pales in comparison with the field of genomics. But in 10 years, we predict the study of glycobiology and glycomics will be ubiquitous and in the mainstream.

We started our analysis of this space because we’ve been focusing on many other classes of analytes, such as microRNAs, long-coding RNAs, oncogenes, tumor suppressor genes, etc., whose potential as biomarkers is becoming established. Glycobiology, on the other hand, represents an entire new space—a whole new category of modifications that could be analyzed for diagnostic potential and perhaps also for therapeutic targeting.

Today, glycobiology and glycomics are where genomics was at the start of the Human Genome Project. They respresent a nascent space and with full headroom for growth. Select Biosciences will continue to track this exciting field for research developments as well as development of biomarkers based on glyco-epitopes.

Enal Razvi, Ph.D., conducted his doctoral work on viral immunology and subsequent to receiving his Ph.D. went on to the Rockefeller University in New York to serve as Aaron Diamond Post-doctoral fellow under Professor Ralph Steinman [Nobel Prize Winner in 2011 for his discovery of dendritic cells in the early-70s with Zanvil Cohn]. Subsequently, Dr. Razvi completed his research fellowship at Harvard Medical School. For the last two decades Dr. Razvi has worked with small and large companies and consulted for more than 100 clients worldwide. He currently serves as Biotechnology Analyst and Managing Director of SelectBio U.S. He can be reached at enal@selectbio.us. Gary M. Oosta holds a Ph.D. in Biophysics from Massachusetts Institute of Technology and a B.A. in Chemistry from E. Mich. Univ. He has 25 years of industrial research experience in various technology areas including medical diagnostics, thin-layer coating, bio-effects of electromagnetic radiation, and blood coagulation. Dr. Oosta has authored 20 technical publications and is an inventor on 77 patents worldwide. In addition, he has managed research groups that were responsible for many other patented innovations. Dr. Oosta has a long-standing interest in using patents and publications as strategic technology indicators for future technology selection and new product development. To enjoy more articles like this from GEN, click here to subscribe now!

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Problem of Science Doctorate Programs

Posted in Curation, Disease Biology, Evolutionary cognition, Explanatory, Federal Budget Appropriations, Health Economics and Outcomes Research, HealthCare IT, Healthcare Reform, Historical relevance, Intellectual Property, Innovations, Commercialization, Investment in technological breakthrough, Interviews with Scientific Leaders, Investment in Technological Breakthrough, Materials Science & Engineering, Medical Devices R&D Investment, Medical Imaging Technology, Image Processing/Computing, MRI, CT, Nuclear Medicine, Ultra Sound, Pharmaceutical R&D Investment, Population Health Management, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Scientist: Career considerations, Technology Advance Assessment of, Technology Capital Expenses, tagged doctorate and postdoctoral reseach on April 12, 2016| Leave a Comment »

Problem of Science Doctorate Programs

Larry H. Bernstein, MD, FCAP, Curator

LPBI

Article ID #203: Problem of Science Doctorate Programs. Published on 4/12/2016

WordCloud Image Produced by Adam Tubman

The Problem in Biomedical Education

Henry Bourne (UCSF)

Dr. Henry Bourne has trained graduate students and postdocs at UCSF for over 40 years. In his iBiology talk, he discusses the imminent need for change in graduate education. With time to degrees getting longer, the biomedical community needs to create experimental graduate programs to find more effective and low cost ways to train future scientists and run successful laboratories. If we don’t start looking for solutions, the future of the biomedical enterprise will grow increasingly unstable.

Watch Henry Bourne’s iBioMagazine: The Problem in Biomedical Education

Henry Bourne is Professor Emeritus and former chair of the Department of Pharmacology at the University of California – San Francisco. His research focused on trimeric G-proteins, G-protein coupled receptors, and the cellular signals responsible for polarity and direction-finding of human leukocytes. He is the author of several books including a memoir, Ambition and Delight, and has written extensively about graduate training and biomedical workforce issues. Now Dr. Bourne’s research focuses on the organization and founding of US biomedical research in the early 20th century.

Related Talks

Shirley Tilghman: The Malthusian Dilemma in Biomedical Research
Bruce Alberts, Marc Kirschner, Shirley Tilghman, Harold Varmus iBioMagazine: Rescuing US Biomedical Research
Kristin Krukenberg, Sarah Mazzilli, Gary McDowell, Jessica Polka iBioMagazine: Shaping the Future of Research
Jon Lorsch iBioMagazine: Lab Size: Is Bigger Better?
Gregory Petsko iBioMagazine: The Post-doctoral Situation

Watch his archived Q&A on postdocs and the biomedical workforce

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Behavior

Posted in Academic Publishing, Behavioral Genetics, Curation, Evolutionary cognition, Gene Regulation and Evolution, tagged behavior, Cognition, Evolutionary Biology on September 10, 2015| Leave a Comment »

Behavior

Curator: Larry H Bernstein, MD, FCAP

Behavior Brief

The Scientist

http://www.the-scientist.com//?articles.view/articleNo/43904/title/Behavior-Brief/

Wasp-directed webs make better cocoons?

Scientists have uncovered more detail about the unique relationship between the parasitic ichneumon wasp (Reclinervellus nielseni) and its arachnid host, the orb-weaving spider (Cyclosa argenteoalba). While the spider carries the wasp’s egg—and later, hatched larva—within its abdomen, the arachnid spins an atypical web, according to a study published last month (August 5) in The Journal of Experimental Biology. When the larva emerges, killing the spider host, the wasp uses the modified webbing to build a cocoon.

“This discovery—of enhanced behavior as opposed to merely switched behavior—is completely new, impressively demonstrated, and rather unexpected I think,” Mark Shaw an entomologist at the National Museum of Scotland, who was not involved in the study, told Newsweek.

According to The Verge, scientists from Kobe University in Japan along with their collaborators determined that the modified web is similar to the orb-weaving spider’s resting web that it uses when it molts—only it is 40 times stronger. This may help the wasp larva build a more durable cocoon. Ecologist Sophie Labaude of the University of Burgundy in France, who was not involved in the work told The Verge that the altered web composition may be a coincidental side effect of chemicals thought to be introduced into the spider during the course of the parasitic infection.

Catharus ustulatus with a tracker on its back J. CRAVES

Some songbirds don’t set cruising altitude

A study published last month (August 12) in The Auk: Ornithological Advances reported the first complete flight-altitude data for a songbird, revealing that one species, the Swainson’s thrush (Catharus ustulatus), changes its altitude intermittently throughout its migration.

“I really thought that the birds would mostly behave like commercial aircraft, ascending to a particular altitude, leveling off and cruising near that altitude, and then coming down just before they landed,” study coauthor Melissa Bowlin of the University of Michigan-Dearborn said in a statement. “I was shocked when I made the first graph for the first bird, and thought it was an anomaly. The more data we obtained, however, the more often we saw the up-and-down pattern to the birds’ flight.”

Bowlin and her colleagues attached radio transmitters to nine Swainson’s thrushes captured from a forest in Illinois during the birds’ spring migration seasons between 2011 and 2013. Once the birds took off, the researchers followed them in a car, keeping track of the birds’ altitudes as they flew through different landscapes. The researchers found that the birds often altered their altitudes by more than 100 meters during their migration. While the authors noted that the precise locations at which the birds ascended and descended cannot be determined until more data are analyzed, they speculated that the birds’ decisions to change altitude may be related to atmospheric changes.

“Dr. Bowlin and her colleagues’ unique yet perplexing records of migrant altitudes raise a number of thought-provoking questions that have implications for species conservation,” Robert Diehl of the US Geological Survey’s Northern Rocky Mountain Science Center said in a statement.

FLICKR, LAGGEDONUSER

Bonobos reuse “peeps”

Humans may not be the only species that can disassociate their communication from their environment. Bonobos (Pan paniscus) also seem to produce the same high-pitched “peep” noises to express psychological states regardless of their context or circumstances, according to study published last month (August 4) in PeerJ. This ability, called functional flexibility, is analogous to the cries or laughter of a human infant, the study’s authors wrote.

“When I studied the bonobos in their native setting in the Congo, I was struck by how frequent their peeps were, and how many different contexts they produce them in,” study coauthor Zanna Clay, a psychologist at the University of Birmingham, told The Guardian. “It became apparent we couldn’t always differentiate between peeps. We needed to understand the context to get to the root of their communication.”

Clay and her colleagues recorded bonobo peeps made during a range of situations, including feeding, sleeping, and traveling. The researchers found that peeps produced during positive situations, such as feeding were indistinguishable from those made within neutral contexts such as resting. However, in negative circumstances such as a state of alarm, the bonobos’ peeps were acoustically different.

“We interpret this evidence as an example of an evolutionary early transition away from fixed vocal signaling towards functional flexibility,” Clay told The Guardian.

An ant (Pristomyrmex punctatus) stands guard over a Japanese oakblue caterpillar (Narathura japonica).WIKIMEDIA, L. SHYAMAL

Manipulation or mutalism?

A new study suggests that a species of Japanese ant (Pristomyrmex punctatus) that imbibes the sweet nectar secreted by Japanese oakblue butterfly (Narathura japonica) caterpillars must pay a price. According to a study published this summer (July 28) in Current Biology, chemicals in the nectar can effectively brainwash the ants, turning them into loyal bodyguards for the caterpillars.

An international group of researchers led by investigators at Kobe University found that ants who fed upon N. japonica’s sweet secretion displayed more aggressive behavior and had lower levels of dopamine in their brains than ants found near caterpillars that didn’t consume the nectar, according toScience.

The results suggest that the relationship between the ants and caterpillar may not be mutualistic, as previously thought, but may have an aspect of parasitism.

“It’s possible that these common food-for-defense interactions, which are typically assumed to be mutualistic, may in fact be maintained primarily through parasitic manipulation of ant behavior,” the authors wrote in their report.

NATURE COMMUNICATIONS, J. COSTELLO ET AL.

Young siphonophores take the lead

For physonect siphonophores (Nanomia bijuga), jellyfish-like marine creatures that travel together as a single unit, the youngest colony members alwaysride shotgun, according to a study published yesterday (September 1) in Nature Communications.

To cover distances of up to 200 meters a day to find food, N. bijuga colony members have to work together. “The younger swimming bells at the tip of the colony are responsible for turning. They generate a lot of torque,” study coauthor Kelly Sutherland, an oceanographer at the University of Oregon, said in a statement. “The older swimming bells toward the base of the colony are responsible for thrust.”

Sutherland and her colleagues recorded swimming colonies from Friday Harbor, Washington, and tracked how the organism displaced particles around it to discern the contribution each unit makes to the movement. They found that even small amounts of water displacement exerted by the youngest members at the tip of the colony had big impacts on which direction the unit travelled.

“They are like the handle of a door,” study coauthor John Costello, a biologist at the Marine Biological Laboratory in Woods Hole, Massachusetts, said in a statement. “If you push on a door near its hinges—its axis of rotation—the door is hard to open. But if you push on the door handle, which is far from the axis of rotation, the door opens easily. A little force placed with a big lever arm has a big effect on turning.”

The authors suggested that the siphonophore’s strategy involving multiple propulsion “engines” and efficient directional control could inspire improved designs for underwater vehicles.

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

Posted in Academic Publishing, Biochemical pathways, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Informatics, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Surgery of the Heart, Cell Biology, Clinical & Translational, Clinical Diagnostics, Clinical Genomics, Curation, Curation methodology, De novo synthesis, Discovery process, Disease Biology, Drug Delivery Platform Technology, Enzymes and isoenzymes, Evolutionary cognition, Experimental validation, Explanatory, FDA, FDA Regulatory Affairs, Health Economics and Outcomes Research, HealthCare IT, Historical relevance, International Global Work in Pharmaceutical, Interventional Oncology: Radiofrequency Ablation, Transarterial Chemoembolization, Microwave Ablation and Irreversible Electroporation (IRE), Interviews with Scientific Leaders, Metabolism, Metabolomics, Molecular Genetics & Pharmaceutical, Open Access Journals, Personal Health Applications: Tech Innovations serves HealhCare, Pharmaceutical R&D Informatics, Pharmaceutical R&D Investment, Proteomics, REAL TIME Conference Coverage Twitter's Hashtags and Handles per Presentation/session, Scientific & Biotech Conferences: Press Coverage, Signaling & Cell Circuits, Small Molecules in Development of Therapeutic Drugs, Technology Advance Assessment of, Theoretic convergence, tagged Amazon Kindle, anti-cancer drugs, Aviva Lev-Ari, breast cancer, breast cancer genes, Cancer - General, cancer patient management, cancer risk, Cell Biology, Chemotherapy, Clinical trial, Conditions and Diseases, Content Curation, Curation, Curation methodology, DNA, DNA Sequencing, Food and Drug Administration, genetics, genome, genomics, Harvard Medical School, health outcomes research, Larry H. Bernstein, Medical imaging, Metabolomics, National Institutes of Health, personalised medicine, Personalized medicine, Prostate cancer, research, RNA, science, Stem cell on August 14, 2015| Leave a Comment »

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

which 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 of Lymphomas [2.4.4C]

Posted in Academic Publishing, Automated Cell Processing, Best evidence, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Informatics, Cancer Screening, Cell Biology, Circulating Progenitor Cells, Clinical & Translational, Clinical Diagnostics, Clinical Genomics, Curation, Discovery process, Disease Biology, Evolutionary cognition, Experimental validation, Explanatory, Gene Regulation, Genetics & Pharmaceutical, Genome Biology, Genomic Expression, Hematology, Hematopoiesis, Historical relevance, Lymphoma, Pharmaceutical Analytics, Pharmaceutical Drug Discovery, Pharmacogenomics, Technology Advance Assessment of, Translational Science, tagged choice of treatment, hematological cancers, lymphomas, treatment of lymphomas on August 11, 2015| Leave a Comment »

Treatment of Lymphomas [2.4.4C]

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

http://pharmaceuticalinnovation.com/2015/8/11/larryhbern/Treatment-of-Lymphomas-[2.4.4C]

Lymphoma treatment

Overview

http://www.emedicinehealth.com/lymphoma/page8_em.htm#lymphoma_treatment

The most widely used therapies are combinations of chemotherapyand radiation therapy.

Biological therapy, which targets key features of the lymphoma cells, is used in many cases nowadays.

The goal of medical therapy in lymphoma is complete remission. This means that all signs of the disease have disappeared after treatment. Remission is not the same as cure. In remission, one may still have lymphoma cells in the body, but they are undetectable and cause no symptoms.

When in remission, the lymphoma may come back. This is called recurrence.
The duration of remission depends on the type, stage, and grade of the lymphoma. A remission may last a few months, a few years, or may continue throughout one’s life.
Remission that lasts a long time is called durable remission, and this is the goal of therapy.
The duration of remission is a good indicator of the aggressiveness of the lymphoma and of the prognosis. A longer remission generally indicates a better prognosis.

Remission can also be partial. This means that the tumor shrinks after treatment to less than half its size before treatment.

The following terms are used to describe the lymphoma’s response to treatment:

Improvement: The lymphoma shrinks but is still greater than half its original size.
Stable disease: The lymphoma stays the same.
Progression: The lymphoma worsens during treatment.
Refractory disease: The lymphoma is resistant to treatment.

The following terms to refer to therapy:

Induction therapy is designed to induce a remission.
If this treatment does not induce a complete remission, new or different therapy will be initiated. This is usually referred to as salvage therapy.
Once in remission, one may be given yet another treatment to prevent recurrence. This is called maintenance therapy.

Chemotherapy

Many different types of chemotherapy may be used for Hodgkin lymphoma. The most commonly used combination of drugs in the United States is called ABVD. Another combination of drugs, known as BEACOPP, is now widely used in Europe and is being used more often in the United States. There are other combinations that are less commonly used and not listed here. The drugs that make up these two more common combinations of chemotherapy are listed below.

ABVD: Doxorubicin (Adriamycin), bleomycin (Blenoxane), vinblastine (Velban, Velsar), and dacarbazine (DTIC-Dome). ABVD chemotherapy is usually given every two weeks for two to eight months.

BEACOPP: Bleomycin, etoposide (Toposar, VePesid), doxorubicin, cyclophosphamide (Cytoxan, Neosar), vincristine (Vincasar PFS, Oncovin), procarbazine (Matulane), and prednisone (multiple brand names). There are several different treatment schedules, but different drugs are usually given every two weeks.

The type of chemotherapy, number of cycles of chemotherapy, and the additional use of radiation therapy are based on the stage of the Hodgkin lymphoma and the type and number of prognostic factors.

Adult Non-Hodgkin Lymphoma Treatment (PDQ®)

http://www.cancer.gov/cancertopics/pdq/treatment/adult-non-hodgkins/Patient/page1

Key Points for This Section

Adult non-Hodgkin lymphoma is a disease in which malignant (cancer) cells form in the lymph system.

Because lymph tissue is found throughout the body, adult non-Hodgkin lymphoma can begin in almost any part of the body. Cancer can spread to the liver and many other organs and tissues.

Non-Hodgkin lymphoma in pregnant women is the same as the disease in nonpregnant women of childbearing age. However, treatment is different for pregnant women. This summary includes information on the treatment of non-Hodgkin lymphoma during pregnancy

Non-Hodgkin lymphoma can occur in both adults and children. Treatment for children, however, is different than treatment for adults. (See the PDQ summary on Childhood Non-Hodgkin Lymphoma Treatment for more information.)

There are many different types of lymphoma.

Lymphomas are divided into two general types: Hodgkin lymphoma and non-Hodgkin lymphoma. This summary is about the treatment of adult non-Hodgkin lymphoma. For information about other types of lymphoma, see the following PDQ summaries:

Age, gender, and a weakened immune system can affect the risk of adult non-Hodgkin lymphoma.

If cancer is found, the following tests may be done to study the cancer cells:

Immunohistochemistry : A test that uses antibodies to check for certain antigens in a sample of tissue. The antibody is usually linked to a radioactive substance or a dye that causes the tissue to light up under a microscope. This type of test may be used to tell the difference between different types of cancer.
Cytogenetic analysis : A laboratory test in which cells in a sample of tissue are viewed under a microscope to look for certain changes in the chromosomes.
Immunophenotyping : A process used to identify cells, based on the types of antigens ormarkers on the surface of the cell. This process is used to diagnose specific types of leukemia and lymphoma by comparing the cancer cells to normal cells of the immune system.

Certain factors affect prognosis (chance of recovery) and treatment options.

The prognosis (chance of recovery) and treatment options depend on the following:

The stage of the cancer.
The type of non-Hodgkin lymphoma.
The amount of lactate dehydrogenase (LDH) in the blood.
The amount of beta-2-microglobulin in the blood (for Waldenström macroglobulinemia).
The patient’s age and general health.
Whether the lymphoma has just been diagnosed or has recurred (come back).

Stages of adult non-Hodgkin lymphoma may include E and S.

Adult non-Hodgkin lymphoma may be described as follows:

E: “E” stands for extranodal and means the cancer is found in an area or organ other than the lymph nodes or has spread to tissues beyond, but near, the major lymphatic areas.

S: “S” stands for spleen and means the cancer is found in the spleen.

Stage I adult non-Hodgkin lymphoma is divided into stage I and stage IE.

Stage I: Cancer is found in one lymphatic area (lymph node group, tonsils and nearby tissue, thymus, or spleen).
Stage IE: Cancer is found in one organ or area outside the lymph nodes.

Stage II adult non-Hodgkin lymphoma is divided into stage II and stage IIE.

Stage II: Cancer is found in two or more lymph node groups either above or below the diaphragm (the thin muscle below the lungs that helps breathing and separates the chest from the abdomen).
Stage IIE: Cancer is found in one or more lymph node groups either above or below the diaphragm. Cancer is also found outside the lymph nodes in one organ or area on the same side of the diaphragm as the affected lymph nodes.

Stage III adult non-Hodgkin lymphoma is divided into stage III, stage IIIE, stage IIIS, and stage IIIE+S.

Stage III: Cancer is found in lymph node groups above and below the diaphragm (the thin muscle below the lungs that helps breathing and separates the chest from the abdomen).
Stage IIIE: Cancer is found in lymph node groups above and below the diaphragm and outside the lymph nodes in a nearby organ or area.
Stage IIIS: Cancer is found in lymph node groups above and below the diaphragm, and in the spleen.
Stage IIIE+S: Cancer is found in lymph node groups above and below the diaphragm, outside the lymph nodes in a nearby organ or area, and in the spleen.

In stage IV adult non-Hodgkin lymphoma, the cancer:

is found throughout one or more organs that are not part of a lymphatic area (lymph node group, tonsils and nearby tissue, thymus, or spleen), and may be in lymph nodes near those organs; or
is found in one organ that is not part of a lymphatic area and has spread to organs or lymph nodes far away from that organ; or
is found in the liver, bone marrow, cerebrospinal fluid (CSF), or lungs (other than cancer that has spread to the lungs from nearby areas).

Adult non-Hodgkin lymphomas are also described based on how fast they grow and where the affected lymph nodes are in the body. Indolent & aggressive.

The treatment plan depends mainly on the following:

The type of non-Hodgkin’s lymphoma
Its stage (where the lymphoma is found)
How quickly the cancer is growing
The patient’s age
Whether the patient has other health problems
If there are symptoms present such as fever and night sweats (see above)

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Hematological Malignancies, Table of Contents

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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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Hematological Cancer Classification

Posted in Academic Publishing, Acute lymphocytic leukemia, Acute myelocytic leukemia, Automated Cell Processing, BioIT: BioInformatics, Biological Networks, Biomedical Measurement Science, Bone marrow derived cells, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Screening, Cell Biology, Circulating Progenitor Cells, Clinical & Translational, Clinical Diagnostics, Clinical Genomics, Curation, Curation methodology, Cytoskeleton, Discovery process, Disease Biology, Evolutionary cognition, Experimental validation, Explanatory, Gene Regulation, Genomic Expression, Hematology, Hematopoiesis, Lymphoma, tagged acute and chronic leukemias, Cancer Genomics, childhood leukemia, classification, hematological malignancies, leukemias, lymphomas, phenotypes on August 11, 2015| Leave a Comment »

Hematological Cancer Classification

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

Introduction to leukemias and lymphomas

2.4.1 Ontogenesis of the blood elements: hematopoiesis

http://www.britannica.com/EBchecked/topic/69747/blood-cell-formation

Blood cells are divided into three groups: the red blood cells (erythrocytes), the white blood cells (leukocytes), and the blood platelets (thrombocytes). The white blood cells are subdivided into three broad groups: granulocytes, lymphocytes, and monocytes.

Blood cells do not originate in the bloodstream itself but in specific blood-forming organs, notably the marrow of certain bones. In the human adult, the bone marrow produces all of the red blood cells, 60–70 percent of the white cells (i.e., the granulocytes), and all of the platelets. The lymphatic tissues, particularly the thymus, the spleen, and the lymph nodes, produce the lymphocytes (comprising 20–30 percent of the white cells). The reticuloendothelial tissues of the spleen, liver, lymph nodes, and other organs produce the monocytes (4–8 percent of the white cells). The platelets, which are small cellular fragments rather than complete cells, are formed from bits of the cytoplasm of the giant cells (megakaryocytes) of the bone marrow.

In the human embryo, the first site of blood formation is the yolk sac. Later in embryonic life, the liver becomes the most important red blood cell-forming organ, but it is soon succeeded by the bone marrow, which in adult life is the only source of both red blood cells and the granulocytes. Both the red and white blood cells arise through a series of complex, gradual, and successive transformations from primitive stem cells, which have the ability to form any of the precursors of a blood cell. Precursor cells are stem cells that have developed to the stage where they are committed to forming a particular kind of new blood cell.

In a normal adult the red cells of about half a liter (almost one pint) of blood are produced by the bone marrow every week. Almost 1 percent of the body’s red cells are generated each day, and the balance between red cell production and the removal of aging red cells from the circulation is precisely maintained.

http://interactive-biology.com/wp-content/uploads/2012/07/Cells-in-the-Bone-Marrow-1024×747.png

Erythropoiesis

http://www.interactive-biology.com/3969/erythropoiesis-formation-of-red-blood-cells/

Erythropoiesis – Formation of Red Blood Cells

Because of the inability of erythrocytes (red blood cells) to divide to replenish their own numbers, the old ruptured cells must be replaced by totally new cells. They meet their demise because they don’t have the usual specialized intracellular machinery, which controls cell growth and repair, leading to a short life span of 120 days.

This short life span necessitates the process erythropoiesis, which is the formation of red blood cells. All blood cells are formed in the bone marrow. This is the erythrocyte factory, which is soft, highly cellar tissue that fills the internal cavities of bones.

Erythrocyte differentiation takes place in 8 stages. It is the pathway through which an erythrocyte matures from a hemocytoblast into a full-blown erythrocyte. The first seven all take place within the bone marrow. After stage 7 the cell is then released into the bloodstream as a reticulocyte, where it then matures 1-2 days later into an erythrocyte. The stages are as follows:

Hemocytoblast, which is a pluripotent hematopoietic stem cell
Common myeloid progenitor, a multipotent stem cell
Unipotent stem cell
Pronormoblast
Basophilic normoblast also called an erythroblast.
Polychromatophilic normoblast
Orthochromatic normoblast
Reticulocyte

These characteristics can be seen during the course of erythrocyte maturation:

The size of the cell decreases
The cytoplasm volume increases
Initially there is a nucleus and as the cell matures the size of the nucleus decreases until it vanishes with the condensation of the chromatin material.

Low oxygen tension stimulates the kidneys to secrete the hormone erythropoietin into the blood, and this hormone stimulates the bone marrow to produce erythrocytes.

Rarely, a malignancy or cancer of erythropoiesis occurs. It is referred to as erythroleukemia. This most likely arises from a common myeloid precursor, and it may occur associated with a myelodysplastic syndrome.

Summary of erythrocyte maturation

White blood cell series: myelopoiesis

http://www.nlm.nih.gov/medlineplus/ency/presentations/100151_3.htm

http://www.nlm.nih.gov/medlineplus/ency/images/ency/fullsize/15220.jpg

There are various types of white blood cells (WBCs) that normally appear in the blood: neutrophils (polymorphonuclear leukocytes; PMNs), band cells (slightly immature neutrophils), T-type lymphocytes (T cells), B-type lymphocytes (B cells), monocytes, eosinophils, and basophils. T and B-type lymphocytes are indistinguishable from each other in a normal slide preparation. Any infection or acute stress will result in an increased production of WBCs. This usually entails increased numbers of cells and an increase in the percentage of immature cells (mainly band cells) in the blood. This change is referred to as a “shift to the left” People who have had a splenectomy have a persistent mild elevation of WBCs. Drugs that may increase WBC counts include epinephrine, allopurinol, aspirin, chloroform, heparin, quinine, corticosteroids, and triamterene. Drugs that may decrease WBC counts include antibiotics, anticonvulsants, antihistamine, antithyroid drugs, arsenicals, barbiturates, chemotherapeutic agents, diuretics and sulfonamides. (Updated by: David C. Dugdale, III, MD)

https://www.med-ed.virginia.edu/courses/path/innes/nh/wcbmaturation.cfm

Note that the mature forms of the myeloid series (neutrophils, eosinophils, basophils), all have lobed (segmented) nuclei. The degree of lobation increases as the cells mature.

The earliest recognizable myeloid cell is the myeloblast (10-20m dia) with a large round to oval nucleus. There is fine diffuse immature chromatin (without clumping) and a prominant nucleolus.

The cytoplasm is basophilic without granules. Although one may see a small golgi area adjacent to the nucleus, granules are not usually visible by light microscopy. One should not see blast cells in the peripheral blood.

https://www.med-ed.virginia.edu/courses/path/innes/images/nhjpeg/nh%20myeloblast%20x100b.jpeg

The promyelocyte (10-20m) is slightly larger than a blast. Its nucleus, although similar to a myeloblast shows slight chromatin condensation and less prominent nucleoli. The cytoplasm contains striking azurophilic granules or primary granules. These granules contain myeloperoxidase, acid phosphatase, and esterase enzymes. Normally no promyelocytes are seen in the peripheral blood.

At the point in development when secondary granules can be recognized, the cell becomes a myelocyte.

https://www.med-ed.virginia.edu/courses/path/innes/images/nhjpeg/nh%20promyelocyte%20×100%20a.jpeg

Myelocytes (10-18m) are not normally found in the peripheral blood. Nucleoli may not be seen in the late myelocyte. Primary azurophilic granules are still present, but secondary granules predominate. Secondary granules (neut, eos, or baso) first appear adjacent to the nucleus. In neutrophils this is the “dawn” of neutrophilia.

Metamyelocytes (10-18m) have kidney shaped indented nuclei and dense chromatin along the nuclear membrane. The cytoplasm is faintly pink, and they have secondary granules (neutro, eos, or baso). Zero to one percent of the peripheral blood white cells may be metamyelocytes (juveniles).

https://www.med-ed.virginia.edu/courses/path/innes/images/nhjpeg/nh%20metamyelocyte%20×100.jpeg

Bands, slightly smaller than juveniles, are marked by a U-shaped or deeply indented nucleus.

https://www.med-ed.virginia.edu/courses/path/innes/images/nhjpeg/nh%20band%20x100a.jpeg

Segmented (segs) or polymorphonuclear (PMN) leukocytes (average 14 m dia) are distinguished by definite lobation with thin thread-like filaments of chromatin joining the 2-5 lobes. 45-75% of the peripheral blood white cells are segmented neutrophils.

https://www.med-ed.virginia.edu/courses/path/innes/images/nhjpeg/nh%20neutrophil%20×100%20d.jpeg

Thrombocytogenesis

The incredible journey: From megakaryocyte development to platelet formation

Kellie R. Machlus ¹^,² and Joseph E. Italiano Jr
JCB 2013; 201(6): 785-796
http://dx.doi.org:/10.1083/jcb.201304054

Large progenitor cells in the bone marrow called megakaryocytes (MKs) are the source of platelets. MKs release platelets through a series of fascinating cell biological events. During maturation, they become polyploid and accumulate massive amounts of protein and membrane. Then, in a cytoskeletal-driven process, they extend long branching processes, designated proplatelets, into sinusoidal blood vessels where they undergo fission to release platelets.

http://dm5migu4zj3pb.cloudfront.net/manuscripts/26000/26891/medium/JCI0526891.f4.jpg

http://www.nature.com/nri/journal/v11/n4/images/nri2956-f3.jpg

2.4.2 Classification of hematological malignancies
Practical Diagnosis of Hematologic Disoreders. 4^th edition. Vol 2.
Kjeldsberg CR, Ed. ASCP Press. 2006. Chicago, IL.

2.4.2.1 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

2.4.2.2 Secondary Classification

2.4.2.3 Nuance – PathologyOutlines
Nat Pernick, Ed.

Leukemia – Acute

Primary references acute leukemia-general AML general AML classification transient abnormal myelopoiesis

Recurrent genetic abnormalities: AML with t(6;9) AML with t(8;21) AML with 11q23 abnormalities AML with inv(16) or t(16;16) AML with Down syndrome AML with FLT3 mutations AML with myelodysplastic related changes AML therapy related APL microgranular variant APL with t(15;17) APL with t(V;17) APL therapy related

AML not otherwise categorized: minimally differentiated (M0) without maturation (M1) with maturation (M2) M3 myelomonocytic monoblastic and monocytic erythroid megakaryoblastic CD13/CD33 negative basophilic myeloid sarcoma acute panmyelosis with myelofibrosis with Philadelphia chromosome with pseudo Chediak-Higashi anomaly hypocellular

ALL: general WHO classification with eosinophilia

PreB ALL: general t(9;22) t(v;11q23) t(1;19) t(5;14) t(12;21) hyperdiploidy hypodiploidy mature B ALL/Burkitt

Other ALL: T ALL ambiguous lineage mixed phenotype

AML and related malignancies

Acute myeloid leukemias with recurrent genetic abnormalities:

AML with t(8;21)(q22;q22); RUNX1-RUNX1T1
AML with inv(16)(p13.1;q22) or t(16;16)(p13.1;q22); CBF&beta-MYH11
Acute promyelocytic leukemia with t(15;17)(q22;q12); PML/RAR&alpha and variants
AML with t(9;11)(p22;q23); MLLT3-MLL
AML with t(6;9)(p23;q34); DEK-NUP214
AML with inv(3)(q21q26.2) or t(3;3)(q21;q26.2); RPN1-EVI1
AML (megakaryoblastic) with t(1;22)(p13;q13); RBM15-MKL1
AML with mutated NPM1*
AML with mutated CEBPA*

* provisional

Acute myeloid leukemia with myelodysplasia related changes

Therapy related acute myeloid leukemia

Alkylating agent related
Topoisomerase II inhibitor related (some maybe lymphoid)

Acute myeloid leukemia not otherwise categorized:

AML minimally differentiated (M0)
AML without maturation (M1)
AML with maturation (M2)
Acute myelomonocytic leukemia (M4)
Acute monoblastic and monocytic leukemia (M5a, M5b)
Acute erythroid leukemia (M6)
Acute megakaryoblastic leukemia (M7)
Acute basophilic leukemia
Acute panmyelosis with myelofibrosis

Myeloid Sarcoma

Myeloid proliferations related to Down syndrome:

Transient abnormal myelopoeisis
Myeloid leukemia associated with Down syndrome

Blastic plasmacytoid dentritic cell neoplasm:

Acute leukemia of ambiguous lineage:

Acute undifferentiated leukemia
Mixed phenotype acute leukemia with t(9;22)(q34;q11.2); BCR-ABL1
Mixed phenotype acute leukemia with t(v;11q23); MLL rearranged
Mixed phenotype acute leukemia, B/myeloid, NOS
Mixed phenotype acute leukemia, T/myeloid, NOS
Mixed phenotype acute leukemia, NOS, rare types
Other acute leukemia of ambiguous lineage
References: WHO Classification of Tumours of Haematopoietic and Lymphoid Tissue (IARC, 2008), Discovery Medicine 2010, eMedicine

Acute lymphocytic leukemia

General
=================================================================

WHO classification system includes former FAB classifications ALL-L1 and L2
● FAB L3 is now considered Burkitt lymphoma

WHO classification of acute lymphoblastic leukemia
=================================================================

Precursor B lymphoblastic leukemia / lymphoblastic lymphoma:
● ALL with t(9;22)(q34;q11.2); BCR-ABL (Philadelphia chromosome)
● ALL with t(v;11q23) (MLL rearranged)
● ALL with t(1;19)(q23;p13.3); TCF3-PBX1 (E2A-PBX1)
● ALL with t(12;21)(p13;q22); ETV6-RUNX1 (TEL-AML1)
● Hyperdiploid > 50
● Hypodiploid
● t(5;14)(q31;q32); IL3-IGH

Precursor T lymphoblastic leukemia / lymphoma

Additional references
=================================================================

Mod Pathol 2000; 13:193

Mixed phenotype acute leukemia (MPAL)

General
=================================================================

De novo acute leukemia containing separate populations of blasts of more than one lineage (bilineal or bilineage), or a single population of blasts co-expressing antigens of more than one lineage (biphenotypic)Excludes:
● Acute myeloid leukemia (AML) with recurrent translocations t(8;21), t(15;17) or inv(16)
● Leukemias with FGFR1 mutations
● Chronic myelogenous leukemia (CML) in blast crisis
● Myelodysplastic syndrome (MDS)-related AML and therapy-related AML, even if they have MPAL immunophenotypeCriteria for biphenotypic leukemia:
● Score of 2 or more for each of two separate lineages:The European Group for the Immunological Classification of Leukemias (EGIL) scoring system2008 WHO classification of acute leukemias of ambiguous lineage

Prognosis
=================================================================

Poor, overall survival of 18 months
● Young age, normal karyotype and ALL induction therapy are associated with favorable survival
● Ph+ is a predictor for poor prognosis
● Bone marrow transplantation should be considered in first remission

Major Categories

MPAL with t(9;22)(q34;q11.2); BCR-ABL1
=================================================================

20% of all MPAL
● Blasts with t(9;22)(q34;q11.2) translocation or BCR-ABL1 rearrangement (Ph+) without history of CML
● Majority in adults
● High WBC counts● Most of the cases B/myeloid phenotype
● Rare T/myeloid, B and T lineage, or trilineage leukemiasMorphology:
● Many cases show a dimorphic blast population, one resembling myeloblasts and the other lymphoblastsCytogenetic abnormalities:
● Conventional karyotyping for t(9;22), FISH or PCR for BCR-ABL1 translocation
● Additional complex karyotypes
● Ph+ is a poor prognostic factor for MPAL, with a reported median survival of 8 months
● Worse than patients of all other types of MPAL

MPAL with t(v;11q23); MLL rearranged
=================================================================

Meeting the diagnostic criteria for MPAL with blasts bearing a translocation involving the 11q23 breakpoint (MLL gene)
● MPAL with MLL rearranged rare
● More often seen in children and relatively common in infancy
● High WBC counts
● Poor prognosis
● Dimorphic blast population, with one resembling monoblasts and the other resembling lymphoblasts
● Lymphoblast population often shows a CD19+, CD10- B precursor immunophenotype, frequently CD15+
● Expression of other B markers usually weak
● Translocations involving MLL gene include t(4;11)(q21;q23), t(11;19)(q23;p13), and t(9;11)(p22;q23)
● Cases with chromosome 11q23 deletion should not be classified in this category

B cell acute lymphoblastic leukemia (ALL) / lymphoblastic lymphoma (LBL)

General

=================================================================

Current 2008 WHO classification: B lymphoblastic leukemia / lymphoma, NOS or B lymphoblastic leukemia / lymphoma with recurrent genetic abnormalities
See also lymphomas: B cell chapter
Also called B cell acute lymphoblastic leukemia / lymphoblastic lymphoma, pre B ALL / LBL
Usually children
B acute lymphoblastic leukemia presents with pancytopenia due to extensive marrow involvement, stormy onset of symptoms, bone pain due to marrow expansion, hepatosplenomegaly due to neoplastic infiltration, CNS symptoms due to meningeal spread and testicular involvement
B acute lymphoblastic lymphoma often presents with cutaneous nodules, bone or nodal involvement, < 25% lymphoblasts in bone marrow and peripheral blood; aleukemic cases are usually asymptomatic
Depending on specific leukemia, arises in either hematopoietic stem cell or B-cell progenitor
Tumors are derived from pre-germinal center naive B cells with unmutated VH region genes
Have multiple immunophenotyping aberrancies relative to normal B cell precursors (hematogones); at relapse, 73% show loss of 1+ aberrance and 60% show new aberrancies (Am J Clin Pathol 2007;127:39)

Prognostic features

=================================================================

Favorable prognosis: age 1-10 years, female, white; preB phenotype, hyperdiploidy>50, t(12,21), WBC count at presentation <50×108/L, non-traumatic tap with no blasts in CNS, rapid response to chemotherapy < 5% blasts on morphology on day 15, remission status after induction <5% blasts on morphology and <0.01% blast on flow or PCR, CD10+
Intermediate prognosis: hyperdiploidy 47-50, diploid, 6q- and rearrangements of 8q24
Unfavorable prognosis: under age 1 (usually have 11q23 translocations) or over age 10; t(9;22) (but not if age 59+ years, Am J Clin Pathol 2002;117:716); male, > 50×108/L WBC at presentation, hypodiploidy, near tetraploidy, 17p- and MLL rearrangements t(v;11q23); CD10-; non-traumatic tap with > 5% blasts or traumatic tap (7%); also increased microvessel staining using CD105 in children (Leuk Res 2007;31:1741), MDR1 expression in children (Oncol Rep 2004;12:1201) and adults (Blood 2002;100:974), 25%+ blasts on morphology on day 15, remission status after induction ≥ 5% blasts on morphology and ≥ 0.1% blasts on flow or PCR

Case reports

=================================================================

12 month old girl and 13 month old boy with mature phenotype but no translocations (Arch Pathol Lab Med 2003;127:1340)
56 year old man with ALL arising from follicular lymphoma (Arch Pathol Lab Med 2002;126:997)
76 year old man with basal cell carcinoma (Diagn Pathol 2007;2:32)
With hemophagocytic lymphohistiocytosis (Pediatr Blood Cancer 2008;50:381)

Treatment

================================================================

Chemotherapy cures more children than adults; adolescents benefit from intensive regimens (Hematology Am Soc Hematol Educ Program 2005:123)

Micro description

=================================================================

Bone marrow smears: small to intermediate blast-like cells with scant, variably basophilic cytoplasm, round / oval or convoluted nuclei, fine chromatin and indistinct nucleoli; frequent mitotic figures; may have “starry sky” appearance similar to Burkitt lymphoma; may have large lymphoblasts with 1-4 prominent nucleoli resembling myeloblasts; usually no sclerosis
Bone marrow biopsy: usually markedly hypercellular with reduction of trilinear maturation; cells have minimal cytoplasm, medium sized nuclei that are often convoluted, moderately dense chromatin and indistinct nucleoli, brisk mitotic activity
Other tissues: may have “starry sky” appearance similar to Burkitt lymphoma; collagen dissection, periadipocyte growth pattern and single cell linear filing

Chronic Leukemia

Chronic Myeloid Neoplasms

Myelodysplastic syndromes (MDS): general, WHO classification, childhood, refractory anemia, refractory anemia with ringed sideroblasts, refractory cytopenia with multilineage dysplasia, refractory anemia with excess blasts, 5q-syndrome, therapy related, unclassified, arsenic toxicity

Myeloproliferative neoplasms (MPN): general, WHO classification, chronic eosinophilic leukemia, chronic myelogenous leukemia, chronic neutrophilic leukemia, essential thrombocythemia, hypereosinophilic syndrome, mast cell disease, polycythemia vera, primary myelofibrosis, unclassifiable

MDS/MPN: general, WHO classification, atypical CML, chronic myelomonocytic leukemia (CMML), chronic myelomonocytic leukemia with eosinophilia, juvenile myelomonocytic leukemia, unclassifiable

Myeloid neoplasms associated with eosinophilia and abnormalities of PDGFRA, PDGFRB, or FGFR1: PDGFRA, PDGFRB, FGFR1

Miscellaneous: transient myeloproliferative disorder of DownÃs syndrome

Lymphoma and plasma cell neoplasms

Lymph nodes: normal development-general B cells T cells NK cells normal histology grossing lymph nodes features to report

Molecular testing: theory FISH northern blot PCR southern blot

Non-Hodgkin lymphoma: general cytogenetics staging staging-pediatric morphologic clues hemophagocytic syndrome chemotherapeutic atypia

B cell disorders: general post-rituximab bone marrow biopsy classification-historical WHO classification

B cell lymphoma subtypes: age-related EBV-associated ALK positive large cell Burkitt unclassifiable-intermediate between Burkitt and diffuse large B cell lymphoma CLL
diffuse large B cell: diffuse-NOS CD5+ T cell / histiocyte rich primary cutaneous-general primary cutaneous-leg primary sites-other
follicular: general childhood cutaneous GI
hairy cell leukemia HCL variant intravascular large B cell lymphomatoid granulomatosis lymphoplasmacytic mantle cell-classic mantle cell-blastoid marginal zone-general marginal zone-MALT MALT-primary sites marginal zone-nodal mediastinal (thymic) plasmablastic pre B lymphoblastic leukemia/lymphoma primary effusion prolymphocytic leukemia pyothorax associated SLL splenic marginal zone splenic lymphoma with villous lymphocytes

Plasma cell neoplasms: general myeloma plasmacytoma heavy chain disease primary amyloidosis MGUS Osteosclerotic myeloma (POEMS) cryoglobulinemia

T/NK cell disorders: general WHO classification adult T cell aggressive NK cell leukemia anaplastic large cell ALK+ ALK- angioimmunoblastic T cell blastic plasmacytoid chronic lymphoproliferative disorders of NK cells cutaneous CD4+ small/medium sized T cell lymphoma cutaneous CD30 positive T cell lymphoproliferative disorders cutaneous gamma delta T cell lymphoma enteropathy epidermotropic CD8+ T cell lymphoma hepatosplenic indolent T cell proliferations mycosis fungoides NK/T cell lymphoma-nasal type nodal CD8+ cytotoxic T cell nonB nonT lymphoblastic peripheral T cell lymphoma, NOS primary effusion lymphoma Sezary syndrome staging subcutaneous panniculitis-like T cell large granular lymphocytic leukemia T cell lymphoblastic leukemia/lymphoma T cell prolymphocytic leukemia

Hodgkin lymphoma: general/staging classic lymphocyte depleted lymphocyte rich classical mixed cellularity nodular lymphocyte predominant nodular sclerosis

Post-transplantation: general WHO classification plasmacytic hyperplasia/IM-like lesions polymorphic B cell lymphoproliferative disorders monomorphic B cell lymphoproliferative disorders other graft versus host disease

Other: AIDS associated-general AIDS associated-examples EBV+ T cell lymphoproliferative disorders of childhood primary immune disorders related

Myeloproliferative neoplasms (MPN)

WHO 2008 – Myeloproliferative neoplasms (MPN)

General
=================================================================

Chronic myelogenous leukemia
● Polycythemia vera
● Essential thrombocythemia
● Primary myelofibrosis
● Chronic neutrophilic leukemia
● Chronic eosinophilic leukemia, not otherwise categorized
● Mast cell disease
● MPNs, unclassifiable

WHO 2001 – Chronic myeloproliferative diseases

Definition
=================================================================

Chronic myelogenous leukemia (Philadelphia chromosome, t(9;22)(q34;q11), BCR-ABL positive)
● Chronic neutrophilic leukemia
● Chronic eosinophilic leukemia (and the hypereosinophilic syndrome)
● Polycythemia vera
● Chronic idiopathic myelofibrosis (with extramedullary hematopoiesis)
● Essential thrombocythemia
● Chronic myeloproliferative disease, unclassifiable

Additional references
=================================================================

Leukemia 2008;22:14 (WHO 2008), Blood 2007;110:1092, Blood 2002;100:2292 (WHO 2001)

The World Health Organization (WHO) classification of the myeloid neoplasms James W. Vardiman, Nancy Lee Harris, and Richard D. Brunning
Blood 2002; 100(7) http://dx.doi.org/10.1182/blood-2002-04-1199

Lymphoma – Non B cell neoplasms

T/NK cell disorders/WHO classification (2008)

Principles of classification
=================================================================

Based on all available information (morphology, immunophenotype, genetics, clinical)
● No one antigenic marker is specific for any neoplasm (except ALK1)
● Immune profiling less helpful in subclassification of T cell lymphomas then B cell lymphomas
● Certain antigens commonly associated with specific disease entities but not entirely disease specific
● CD30: common in anaplastic large cell lymphoma but also classic Hodgkin lymphoma and other B and T cell lymphomas
● CD56: characteristic for nasal NK/T cell lymphoma, but also other T cell neoplasms and plasma cell disorders
● Variation of immunophenotype within a given disease (hepatosplenic T cell lymphoma: usually γδ but some are αβ)
● Recurrent genetic alterations have been identified for many B cell lymphomas but not for most T cell lymphomas
● No attempt to stratify lymphoid malignancies by grade
● Recognize the existence of grey zone lymphomas
● This multiparameter approach has been validated in international studies as highly reproducible

WHO 2008 classification of tumors of hematopoietic and lymphoid tissues (T/NK)
=================================================================

Precursor T-lymphoid neoplasms
● T lymphoblastic leukemia/lymphoma, 9837/3

Mature T cell and NK cell neoplasms
● T cell prolymphocytic leukemia, 9834/3
● T cell large granular lymphocytic leukemia, 9831/3
● Chronic lymphoproliferative disorder of NK cells, 9831/3
● Aggressive NK cell leukemia, 9948/3
● Systemic EBV-positive T cell lymphoproliferative disease of childhood, 9724/3
● Hydroa vacciniforme-like lymphoma, 9725/3
● Adult T cell leukemia/lymphoma, 9827/3
● Extranodal NK/T cell lymphoma, nasal type, 9719/3
● Enteropathy-associated T cell lymphoma, 9717/3
● Hepatosplenic T cell lymphoma, 9716/3
● Subcutaneous panniculitis-like T cell lymphoma, 9708/3
● Mycosis fungoides, 9700/3
● Sézary syndrome, 9701/3
● Primary cutaneous CD30-positive T cell lymphoproliferative disorders
● Lymphomatoid papulosis, 9718/1
● Primary cutaneous anaplastic large cell lymphoma, 9718/3
● Primary cutaneous gamma-delta T cell lymphoma, 9726/3
● Primary cutaneous CD8-positive aggressive epidermotropic cytotoxic T cell lymphoma, 9709/3
● Primary cutaneous CD4-positive small/medium T cell lymphoma, 9709/3
● Peripheral T cell lymphoma, NOS, 9702/3
● Angioimmunoblastic T cell lymphoma, 9705/3
● Anaplastic large cell lymphoma, ALK-positive, 9714/3
● Anaplastic large cell lymphoma, ALK-negative, 9702/3

Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia Staging
Author: Sandy D Kotiah, MD; Chief Editor: Jules E Harris, MD
Medscape Sep 6, 2013
http://emedicine.medscape.com/article/2006578-overview

General considerations in the staging of chronic lymphocytic leukemia (CLL) and the revised Rai (United States) and Binet (Europe) staging systems for CLL are provided below.^{[1, 2, 3]}

See Chronic Leukemias: 4 Cancers to Differentiate, a Critical Images slideshow, to help detect chronic leukemias and determine the specific type present.

General considerations

CLL and small lymphocytic lymphoma (SLL) are different manifestations of the same disease; SLL is diagnosed when the disease is mainly nodal, and CLL is diagnosed when the disease is seen in the blood and bone marrow
CLL is diagnosed by > 5000 monoclonal lymphocytes/mm³ for longer than 3mo; the bone marrow usually has more than 30% monoclonal lymphocytes and is either normocellular or hypercellular
Monoclonal B lymphocytosis is a precursor form of CLL that is defined by a monoclonal B cell lymphocytosis < 5000 monoclonal lymphocytes/mm³; all lymph nodes smaller than 1.5 cm; no anemia; and no thrombocytopenia

Revised Rai staging system (United States)

Low risk (formerly stage 0)^[1]:

Lymphocytosis, lymphocytes in blood > 15000/mcL, and > 40% lymphocytes in the bone marrow

Intermediate risk (formerly stages I and II):

Lymphocytosis as in low risk with enlarged node(s) in any site, or splenomegaly or hepatomegaly or both

High risk (formerly stages III and IV):

Lymphocytosis as in low risk and intermediate risk with disease-related anemia (hemoglobin level < 11.0 g/dL or hematocrit < 33%) or platelets < 100,000/mcL

Binet staging system (Europe)

Stage A:

Hemoglobin ≥ 10 g/dL, platelets ≥ 100,000/mm³, and < 3 enlarged areas

Stage B:

Hemoglobin ≥ 10 g/dL, platelets ≥ 100,000/mm³, and ≥ 3 enlarged areas

Stage C:

Hemoglobin < 10 g/dL, platelets < 100,000/mm³, and any number of enlarged areas

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Addendum to LPBI’s Vision

Curators:

Stephen J Williams, PhD,

Adam Sonnenberg, BSc and

Aviva Lev-Ari, PhD, RN

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Our Team

Our Open Access Online Journal

http://www.pharmaceuticalIntelligence.com

is a scientific, medical and business, multi-expert authoring environment for information syndication in several domains of Life Sciences, Medicine, Pharmaceutical and Healthcare Industries, BioMedicine, Medical Technologies & Devices. Scientific critical interpretations and original articles are written by PhDs, MDs, MD/PhDs, PharmDs, Technical MBAs as Experts, Authors, Writers (EAWs) on an Equity Sharing basis.

Journal Content Descriptors on 6/29/2015

3,037 Posts

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For more information about our Team please see our site at http://pharmaceuticalintelligence.com/contributors-biographies/

For more information of LPBI Deals and Partnerships please see our site at http://pharmaceuticalintelligence.com/joint-ventures/

For more information about our BioMed E-Series please see our site at http://pharmaceuticalintelligence.com/biomed-e-books/

E-Book Titles by LPBI

For more information on Real-Time Conference Coverage including a full list of Conferences Covered by LPBI please go to http://pharmaceuticalintelligence.com/press-coverage/

For more information on Real-Time Conference Coverage and a full listing of Conferences Covered by LPBI please go to:

http://pharmaceuticalintelligence.com/press-coverage/

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LPBI Presents at Life Sciences Collaborative

Posted in Academic Publishing, BioTechnology - Venture Creation, Curation, Evolutionary cognition, Explanatory, Pharmaceutical Industry Competitive Intelligence, Pharmaceutical R&D Informatics, Pharmaceutical R&D Investment, Scientific & Biotech Conferences: Press Coverage, Social Development, Venture Capital, tagged Aviva Lev-Ari, Biotechnology, Biotechnology Industry Organization, Business incubator, Business intelligence, Business model, competetive intelligence, Conference Coverage with Social Media, Content Curation, curation communities, health, Larry H. Bernstein, Leaders in Pharmaceutical Intelligence, Life Sciences, pharmaceutical competitive intelligence, philadelphia, small business development, Social media on June 26, 2015| Leave a Comment »

Leaders in Pharmaceutical Intelligence Presentation at The Life Sciences Collaborative

Curator: Stephen J. Williams, Ph.D. Website Analytics: Adam Sonnenberg, BSc Leaders in Pharmaceutical Intelligence presented their ongoing efforts to develop an open-access scientific and medical publishing and curation platform to The Life Science Collaborative, an executive pharmaceutical and biopharma networking group in the Philadelphia/New Jersey area.

Our Team

For more information on the Vision, Funding Deals and Partnerships please see our site at http://pharmaceuticalintelligence.com/vision/

For more information about our Team please see our site at http://pharmaceuticalintelligence.com/contributors-biographies/

For more information of LPBI Deals and Partnerships please see our site at http://pharmaceuticalintelligence.com/joint-ventures/

For more information about our BioMed E-Series please see our site at http://pharmaceuticalintelligence.com/biomed-e-books/

E-Book Titles by LPBI

For more information on Real-Time Conference Coverage including a full list of Conferences Covered by LPBI please go to http://pharmaceuticalintelligence.com/press-coverage/

For more information on Real-Time Conference Coverage and a full listing of Conferences Covered by LPBI please go to:

http://pharmaceuticalintelligence.com/press-coverage/

The Pennsylvania (PA) and New Jersey (NJ) Biotech environment had been hit hard by the recession and loss of anchor big pharma companies however as highlighted by our interviews in “The Vibrant Philly Biotech Scene” and other news outlets, additional issues are preventing the PA/NJ area from achieving its full potential (discussions also with LSC)

Download the PowerPoint slides here: Presentationlsc