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Posts Tagged ‘Brain tumor’


Author: Tilda Barliya PhD

Photoacoustic Tomography (PAT), also called the optoacoustic or thermoacoustic (TA), is a materials analysis technique based on the reconstruction of an internal photoacoustic source distribution from measurements acquired by scanning ultrasound detectors over a surface that encloses the source under study. Moreover, it is non-ionizing and non-invasive, and is the fastest growing new biomedical method, with clinical applications on the way.

Dr. Lihong Wang, a Distinguished Professor of Biomedical Engineering in the School of Engineering and Applied Science at Washington University in St. Louis, summarizes the state of the art in photoacoustic imaging (1).

The photoacoustic (PA) effect:

The fundamental principle of the PA effect can be simply described: an object absorbs EM radiation energy, the absorbed energy converts into heat and the temperature of the object increases. As soon as the temperature increases, thermal expansion takes place, generating acoustic pressure in the medium. However, a steady thermal expansion (time invariant heating) does not generate acoustic waves; thus, the heating source is required to be time variant.

Dr. Wang explains that “the trick of photoacoustic tomography is to convert light absorbed at depth to sound waves, which scatter a thousand times less than light, for transmission back to the surface. The tissue to be imaged is irradiated by a nanosecond-pulsed laser at an optical wavelength”.

Absorption by light by molecules beneath the surface creates a thermally induced pressure jump that launches sound waves that are measured by ultrasound receivers at the surface and reassembled to create what is, in effect, a photograph.

When comparing to other modalities, PAT has several great advantages:

Table 1 Comparison of imaging modalities.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Dr. Wang is already working with physicians at the Washington University School of Medicine to move four applications of photoacoustic tomography into clinical trials (2).

  • One is to visualize the sentinel lymph nodes that are important in breast cancer staging;
  • A second to monitor early response to chemotherapy;
  • A third to image melanomas;
  • The fourth to image the gastrointestinal tract.

Sentinel node biopsy provides a good example of the improvement photoacoustic imaging promises over current imaging practice. Sentinel nodes are the nodes nearest a tumor, such as a breast tumor, to which cancerous cells would first migrate.

Currently, sentinel node biopsy, includes injection of  a radioactive substance, a dye or both near a tumor. The body treats both substances as foreign, so they flow to the first draining node to be filtered and flushed from the body. A gamma probe or a Geiger counter is used to locate the radioactive particles and the surgeon must cut open the area and follow the dye visually to the sentinel lymph node.

Dr. Wang however, offers a simpler method: injecting an optical dye that shows up so clearly in photoacoustic images that a hollow needle can be guided directly to the sentinel lymph node and a sample of tissue taken through the needle.

Contrast agents:

Most photoacoustic (PA) contrast agents are designed for absorbing laser, especially in the NIR spectral range. However, RF contrast agents are also desirable due to the superior penetration depth of RF in the body (1).  A typical example is indocyanine green (ICG), a dye approved by FDA. ICG has high absorption in the NIR spectral region, and it has already been proved to increase the PA signal when it is injected in blood vessels. Most recently, methyline blue was used as the contrast agent to detect the sentinel lymph node (SLN) (4).

Compared with dyes, nanoparticles possess a high and tunable absorption spectrum, and longer circulation time (1). The absorption peak is tunable by changing the shape and size of the particle. In addition, nanoparticles can be used to target certain diseases by bio-conjugating them with proteins, such as antibodies.  Among different nanoparticles, gold nanoparticles are favored in optical imaging due to their exceptional optical properties in the visible and NIR spectral ranges, including scattering, absorption and photoluminescence. So far, none of the gold nanoparticles have been approved by FDA (1).

One exciting aspect of photoacoustic tomography is that images contain functional as well as structural information because color reflects the chemical composition and chemistry determines function. Photoacoustic tomography, for example, can detect the oxygen saturation of hemoglobin, which is bright red when it is carrying oxygen and turns darker red when it releases it (3), that is important, since almost all diseases, especially cancer and diabetes, cause abnormal oxygen metabolism.  For example see image 1.

Image courtesy of Junjie Yao/Lihong Wang

Image 1: melanoma tumor (MT) cells were injected into a mouse ear on day 1. By day 7, there were noticeable changes in the blood flow rate (top graph, right) and the metabolic rate of oxygen usage (bottom graph, right). Counterintuitively, the tumor did not increase the oxygen extraction fraction (middle graph). The colors correspond to depth, with blue being superficial and red deep (3).

Wang’s team demonstrated that oxygen metabolism betrayed the presence of a melanoma within few days of injections in animal models, where as Oxygen use doubled in a week.

In this aspect: photoacoustic images,  can offer several parameters such as;

  • Vessel cross-section,
  • Concentration of hemoglobin and blood flow speed,
  • and The gradient of oxygen saturation can be used to calculate the oxygen use by a region of tissue.

Analysis of oxygen use is not necessarily new and is frequently measured by positron emission tomography (PET), which requires the injection or inhalation of a radioactively labeled tracer and undesirable radiation exposure.

Photoacoustic Tomography is currently being investigated for (5):

  1. Breast cancer (microvascular).  Additionally, for further information on photoacoustic tomography please read the article by Dr. Venkat Karra (I).
  2. Skin cancer (melanin)
  3. Brain tumors
  4. Cardiac disease – myocardial infraction (6)
  5. Ophthalmology – retinal disease (7)
  6. Ostheoarthrities (8)

Summary

photoacoustic tomography perfectly complements other biomedical imaging modalities by providing unique optical absorption contrast with highly scalable spatial resolution, penetration depth, and imaging speed. In light of its capabilities and flexibilities, PAT is expected to play a more essential role in biomedical studies and clinical practice.

Reference:

1.  Changhui Li and Lihong V Wang. Photoacoustic tomography and sensing in biomedicine. Phys. Med. Biol. 2009 54 R59 doi:10.1088/0031-9155/54/19/R01  http://iopscience.iop.org/0031-9155/54/19/R01 http://iopscience.iop.org/0031-9155/54/19/R01/pdf/0031-9155_54_19_R01.pdf

2. Jiecheny Yin. Photoacoustic tomography in cancer detection. http://bme240.eng.uci.edu/students/08s/jiecheny/index.htm

3. Jim Goodwin. NEW IMAGING TECHNIQUE COULD SPEED CANCER DETECTION. http://www.siteman.wustl.edu/ContentPage.aspx?id=5788

4.  Song K H, Stein E W, Margenthaler J A and Wang L V. Noninvasive photoacoustic identification of sentinel lymph nodes containing methylene blue in vivo in a rat model J. Biomed. Opt. 2008: 13 054033–6.  http://oilab.seas.wustl.edu/epub/SongK_2008_J_Biomed_Opt_13_054033.pdf

5. Junjie Yao and Lihong V Wang.  Photoacoustic tomography: fundamentals, advances and prospects. Contrast Media Mol Imaging. 2011 September; 6(5): 332–345. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3205414/

6. Holotta M, Grossauer HKremser CTorbica PVölkl JDegenhart GEsterhammer RNuster RPaltauf GJaschke W. Photoacoustic tomography of ex vivo mouse hearts with myocardial infarction. J. Biomed Opt. 2011 Mar;16(3):036007. doi: 10.1117/1.3556720. http://www.ncbi.nlm.nih.gov/pubmed/21456870

7. Hao F. ZhangCarmen A. Puliafito, and Shuliang Jiao, Photoacoustic Ophthalmoscopy for In Vivo Retinal Imaging: Current Status and Prospects.  Ophthalmic Surg Lasers Imaging. 2011 July; 42(0): S106–S115.  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3291958/

8. Yao Sun, Eric S. Sobel, and Huabei Jiang. First assessment of three-dimensional quantitative photoacoustic tomography for in vivo detection of osteoarthritis in the finger joints.  Med. Phys. 38, 4009 (2011); http://dx.doi.org/10.1118/1.3598113 . http://online.medphys.org/resource/1/mphya6/v38/i7/p4009_s1?isAuthorized=no

Other articles from our Open Access Journal:

I. By : Venkat Karra. Visualizing breast cancer without X-rays. https://pharmaceuticalintelligence.com/2012/05/08/visualizing-breast-cancer-without-x-rays/

II. By: Dr. Dror Nir. Ultrasound in Radiology – Results of a European Survey. https://pharmaceuticalintelligence.com/2013/07/21/ultrasound-in-radiology-results-of-a-european-survey/

III.  By: Dr. Dror Nir. Causes and imaging features of false positives and false negatives on 18F-PET/CT in oncologic imaging. https://pharmaceuticalintelligence.com/2013/05/18/causes-and-imaging-features-of-false-positives-and-false-negatives-on-18f-petct-in-oncologic-imaging/

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Imaging of Non-tumorous and Tumorous Human Brain Tissues

Reporter and Curator: Dror Nir, PhD

The point of interest in the article I feature below is that it represents a potential building block in a future system that will use full-field optical coherence tomography during brain surgery to improve the accuracy of cancer lesions resection. The article is featuring promising results for differentiating tumor from normal brain tissue in large samples (order of 1–3 cm2) by offering images with spatial resolution comparable to histological analysis, sufficient to distinguish microstructures of the human brain parenchyma.  Easy to say, and hard to make…:) –> Intraoperative apparatus to guide the surgeon in real time during resection of brain tumors.

 

Imaging of non-tumorous and tumorous human brain tissues with full-field optical coherence tomography 

Open Access Article

Osnath Assayaga1Kate Grievea1Bertrand DevauxbcFabrice HarmsaJohan Palludbc,Fabrice ChretienbcClaude BoccaraaPascale Varletbc;  a Inserm U979 “Wave Physics For Medicine” ESPCI -ParisTech – Institut Langevin, 1 rue Jussieu, 75005, b France, Centre Hospitalier Sainte-Anne, 1 rue Cabanis 75014 Paris, France

c University Paris Descartes, France.

Abstract

A prospective study was performed on neurosurgical samples from 18 patients to evaluate the use of full-field optical coherence tomography (FF-OCT) in brain tumor diagnosis.

FF-OCT captures en face slices of tissue samples at 1 μm resolution in 3D to a penetration depth of around 200 μm. A 1 cm2 specimen is scanned at a single depth and processed in about 5 min. This rapid imaging process is non-invasive and requires neither contrast agent injection nor tissue preparation, which makes it particularly well suited to medical imaging applications.

Temporal chronic epileptic parenchyma and brain tumors such as meningiomas, low-grade and high-grade gliomas, and choroid plexus papilloma were imaged. A subpopulation of neurons, myelin fibers and CNS vasculature were clearly identified. Cortex could be discriminated from white matter, but individual glial cells such as astrocytes (normal or reactive) or oligodendrocytes were not observable.

This study reports for the first time on the feasibility of using FF-OCT in a real-time manner as a label-free non-invasive imaging technique in an intraoperative neurosurgical clinical setting to assess tumorous glial and epileptic margins.

Abbreviations

  • FF-OCT, full field optical coherence tomography;
  • OCT, optical coherence tomography

Keywords

Optical imaging; Digital pathology; Brain imaging; Brain tumor; Glioma

1. Introduction

1.1. Primary CNS tumors

Primary central nervous system (CNS) tumors represent a heterogeneous group of tumors with benign, malignant and slow-growing evolution. In France, 5000 new cases of primary CNS tumors are detected annually (Rigau et al., 2011). Despite considerable progress in diagnosis and treatment, the survival rate following a malignant brain tumor remains low and 3000 deaths are reported annually from CNS tumors in France (INCa, 2011). Overall survival from brain tumors depends on the complete resection of the tumor mass, as identified through postoperative imaging, associated with updated adjuvant radiation therapy and chemotherapy regimen for malignant tumors (Soffietti et al., 2010). Therefore, there is a need to evaluate the completeness of the tumor resection at the end of the surgical procedure, as well as to identify the different components of the tumor interoperatively, i.e. tumor tissue, necrosis, infiltrated parenchyma (Kelly et al., 1987). In particular, the persistence of non-visible tumorous tissue or isolated tumor cells infiltrating brain parenchyma may lead to additional resection.

For low-grade tumors located close to eloquent brain areas, a maximally safe resection that spares functional tissue warrants the current use of intraoperative techniques that guide a more complete tumor resection. During awake surgery, speech or fine motor skills are monitored, while cortical and subcortical stimulations are performed to identify functional areas (Sanai et al., 2008). Intraoperative MRI provides images of the surgical site as well as tomographic images of the whole brain that are sufficient for an approximate evaluation of the abnormal excised tissue, but offers low resolution (typically 1 to 1.5 mm) and produces artifacts at the air-tissue boundary of the surgical site.

Histological and immunohistochemical analyses of neurosurgical samples remain the current gold standard method used to analyze tumorous tissue due to advantages of sub-cellular level resolution and high contrast. However, these methods require lengthy (12 to 72 h), complex multiple steps, and use of carcinogenic chemical products that would not be technically possible intra-operatively. In addition, the number of histological slides that can be reviewed and analyzed by a pathologist is limited, and it defines the number and size of sampled locations on the tumor, or the surrounding tissue.

To obtain histology-like information in a short time period, intraoperative cytological smear tests are performed. However tissue architecture information is thereby lost and the analysis is carried out on only a limited area of the sample (1 mm × 1 mm).

Intraoperative optical imaging techniques are recently developed high resolution imaging modalities that may help the surgeon to identify the persistence of tumor tissue at the resection boundaries. Using a conventional operating microscope with Xenon lamp illumination gives an overall view of the surgical site, but performance is limited by the poor discriminative capacity of the white light illumination at the surgical site interface. Better discrimination between normal and tumorous tissues has been obtained using fluorescence properties of tumor cells labeled with preoperatively administered 5-ALA. Tumor tissue shows a strong ALA-induced PPIX fluorescence at 635 nm and 704 nm when the operative field is illuminated with a 440 nm-filtered lamp. More complete resections of high-grade gliomas have been demonstrated using 5-ALA fluorescence guidance (Stummer et al., 2000), however brain parenchyma infiltrated by isolated tumor cells is not fluorescent, reducing the interest of this technique when resecting low-grade gliomas.

Refinement of this induced fluorescence technique has been achieved using a confocal microscope and intraoperative injection of sodium fluorescein. A 488 nm laser illuminates the operative field and tissue contact analysis is performed using a handheld surgical probe (field of view less than 0.5 × 0.5 mm) which scans the fluorescence of the surgical interface at the 505–585 nm band. Fluorescent isolated tumor cells are clearly identified at depths from 0 to 500 μm from the resection border (Sanai et al., 2011), demonstrating the potential of this technique in low-grade glioma resection.

Reviewing the state-of-the-art, a need is identified for a quick and reliable method of providing the neurosurgeon with architectural and cellular information without the need for injection or oral intake of exogenous markers in order to guide the neurosurgeon and optimize surgical resections.

1.2. Full-field optical coherence tomography

Introduced in the early 1990s (Huang et al., 1991), optical coherence tomography (OCT) uses interference to precisely locate light deep inside tissue. The photons coming from the small volume of interest are distinguished from light scattered by the other parts of the sample by the use of an interferometer and a light source with short coherence length. Only the portion of light with the same path length as the reference arm of the interferometer, to within the coherence length of the source (typically a few μm), will produce interference. A two-dimensional B-scan image is captured by scanning. Recently, the technique has been improved, mainly in terms of speed and sensitivity, through spectral encoding (De Boer et al., 2003Leitgeb et al., 2003 and Wojtkowski et al., 2002).

A recent OCT technique called full-field optical coherence tomography (FF-OCT) enables both a large field of view and high resolution over the full field of observation (Dubois et al., 2002 and Dubois et al., 2004). This allows navigation across the wide field image to follow the morphology at different scales and different positions. FF-OCT uses a simple halogen or light-emitting diode (LED) light source for full field illumination, rather than lasers and point-by-point scanning components required for conventional OCT. The illumination level is low enough to maintain the sample integrity: the power incident on the sample is less than 1 mW/mm2 using deep red and near infrared light. FF-OCT provides the highest OCT 3D resolution of 1.5 × 1.5 × 1 μm3 (X × Y × Z) on unprepared label-free tissue samples down to depths of approximately 200 μm–300 μm (tissue-dependent) over a wide field of view that allows digital zooming down to the cellular level. Interestingly, it produces en face images in the native field view (rather than the cross-sectional images of conventional OCT), which mimic the histology process, thereby facilitating the reading of images by pathologists. Moreover, as for conventional OCT, it does not require tissue slicing or modification of any kind (i.e. no tissue fixation, coloration, freezing or paraffin embedding). FF-OCT image acquisition and processing time is less than 5 min for a typical 1 cm2 sample (Assayag et al., in press) and the imaging performance has been shown to be equivalent in fresh or fixed tissue (Assayag et al., in press and Dalimier and Salomon, 2012). In addition, FF-OCT intrinsically provides digital images suitable for telemedicine.

Numerous studies have been published over the past two decades demonstrating the suitability of OCT for in vivo or ex vivo diagnosis. OCT imaging has been previously applied in a variety of tissues such as the eye (Grieve et al., 2004 and Swanson et al., 1993), upper aerodigestive tract (Betz et al., 2008Chen et al., 2007 and Ozawa et al., 2009), gastrointestinal tract (Tearney et al., 1998), and breast tissue and lymph nodes (Adie and Boppart, 2009Boppart et al., 2004Hsiung et al., 2007Luo et al., 2005Nguyen et al., 2009Zhou et al., 2010 and Zysk and Boppart, 2006).

In the CNS, published studies that evaluate OCT (Bizheva et al., 2005Böhringer et al., 2006Böhringer et al., 2009Boppart, 2003 and Boppart et al., 1998) using time-domain (TD) or spectral domain (SD) OCT systems had insufficient resolution (10 to 15 μm axial) for visualization of fine morphological details. A study of 9 patients with gliomas carried out using a TD-OCT system led to classification of the samples as malignant versus benign (Böhringer et al., 2009). However, the differentiation of tissues was achieved by considering the relative attenuation of the signal returning from the tumorous zones in relation to that returning from healthy zones. The classification was not possible by real recognition of CNS microscopic structures. Another study showed images of brain microstructures obtained with an OCT system equipped with an ultra-fast laser that offered axial and lateral resolution of 1.3 μm and 3 μm respectively (Bizheva et al., 2005). In this way, it was possible to differentiate malignant from healthy tissue by the presence of blood vessels, microcalcifications and cysts in the tumorous tissue. However the images obtained were small (2 mm × 1 mm), captured on fixed tissue only and required use of an expensive large laser thereby limiting the possibility for clinical implementation.

Other studies have focused on animal brain. In rat brain in vivo, it has been shown that optical coherence microscopy (OCM) can reveal neuronal cell bodies and myelin fibers (Srinivasan et al., 2012), while FF-OCT can also reveal myelin fibers (Ben Arous et al., 2011), and movement of red blood cells in vessels (Binding et al., 2011).

En face images captured with confocal reflectance microscopy can closely resemble FF-OCT images. For example, a prototype system used by Wirth et al. (2012) achieves lateral and axial resolution of 0.9 μm and 3 μm respectively. However small field size prevents viewing of wide-field architecture and slow acquisition speed prohibits the implementation of mosaicking. In addition, the poorer axial resolution and lower penetration depth of confocal imaging in comparison to FF-OCT limit the ability to reconstruct cross-sections from the confocal image stack.

This study is the first to analyze non-tumorous and tumorous human brain tissue samples using FF-OCT.

2. Materials and methods

2.1. Instrument

The experimental arrangement of FF-OCT (Fig. 1A) is based on a configuration that is referred to as a Linnik interferometer (Dubois et al., 2002). A halogen lamp is used as a spatially incoherent source to illuminate the full field of an immersion microscope objective at a central wavelength of 700 nm, with spectral width of 125 nm. The signal is extracted from the background of incoherent backscattered light using a phase-shifting method implemented in custom-designed software. This study was performed on a commercial FF-OCT system (LightCT, LLTech, France).

 

Fig 1

Capturing “en face” images allows easy comparison with histological sections. The resolution, pixel number and sampling requirements result in a native field of view that is limited to about 1 mm2. The sample is moved on a high precision mechanical platform and a number of fields are stitched together (Beck et al., 2000) to display a significant field of view. The FF-OCT microscope is housed in a compact setup (Fig. 1B) that is about the size of a standard optical microscope (310 × 310 × 800 mm L × W × H).

2.2. Imaging protocol

All images presented in this study were captured on fresh brain tissue samples from patients operated on at the Neurosurgery Department of Sainte-Anne Hospital, Paris. Informed and written consent was obtained in all cases following the standard procedure at Sainte-Anne Hospital from patients who were undergoing surgical intervention. Fresh samples were collected from the operating theater immediately after resection and sent to the pathology department. A pathologist dissected each sample to obtain a 1–2 cm2 piece and made a macroscopic observation to orientate the specimen in order to decide which side to image. The sample was immersed in physiological serum, placed in a cassette, numbered, and brought to the FF-OCT imaging facility in a nearby laboratory (15 min distant) where the FF-OCT images were captured. The sample was placed in a custom holder with a coverslip on top (Fig. 1C, D). The sample was raised on a piston to rest gently against the coverslip in order to flatten the surface and so optimize the image capture. The sample is automatically scanned under a 10 × 0.3 numerical aperture (NA) immersion microscope objective. The immersion medium is a silicone oil of refractive index close to that of water, chosen to optimize index matching and slow evaporation. The entire area of each sample was imaged at a depth of 20 μm beneath the sample surface. This depth has been reported to be optimal for comparison of FF-OCT images to histology images in a previous study on breast tissue (Assayag et al., in press). There are several reasons for the choice of imaging depth: firstly, histology was also performed at approximately 20 μm from the edge of the block, i.e. the depth at which typically the whole tissue surface begins to be revealed. Secondly, FF-OCT signal is attenuated with depth due to multiple scattering in the tissue, and resolution is degraded with depth due to aberrations. The best FF-OCT images are therefore captured close to the surface, and the best matching is achieved by attempting to image at a similar depth as the slice in the paraffin block. It was also possible to capture image stacks down to several hundred μm in depth (where penetration depth is dependent on tissue type), for the purpose of reconstructing a 3D volume and imaging layers of neurons and myelin fibers. An example of such a stack in the cerebellum is shown as a video (Video 2) in supplementary material. Once FF-OCT imaging was done, each sample was immediately fixed in formaldehyde and returned to the pathology department where it underwent standard processing in order to compare the FF-OCT images to histology slides.

2.3. Matching FF-OCT to histology

The intention in all cases was to match as closely as possible to histology. FF-OCT images were captured 20 μm below the surface. Histology slices were captured 20 μm from the edge of the block. However the angle of the inclusion is hard to control and so some difference in the angle of the plane always exists when attempting matching. Various other factors that can cause differences stem from the histology process — fixing, dehydrating, paraffin inclusion etc. all alter the tissue and so precise correspondence can be challenging. Such difficulties are common in attempting to match histology to other imaging modalities (e.g. FF-OCT Assayag et al., in press; OCT Bizheva et al., 2005; confocal microscopy Wirth et al., 2012).

An additional parameter in the matching process is the slice thickness. Histology slides were 4 μm in thickness while FF-OCT optical slices have a 1 μm thickness. The finer slice of the FF-OCT image meant that lower cell densities were perceived on the FF-OCT images (in those cases where individual cells were seen, e.g. neurons in the cortex). This difference in slice thickness affects the accuracy of the FF-OCT to histology match. In order to improve matching, it would have been possible to capture four FF-OCT slices in 1 μm steps and sum the images to mimic the histology thickness. However, this would effectively degrade the resolution, which was deemed undesirable in evaluating the capacities of the FF-OCT method.

3. Results

18 samples from 18 adult patients (4 males, 14 females) of age range 19–81 years have been included in the study: 1 mesial temporal lobe epilepsy and 1 cerebellum adjacent to a pulmonary adenocarcinoma metastasis (serving as the non-tumor brain samples), 7 diffuse supratentorial gliomas (4 WHO grade II, 3 WHO grade III), 5 meningiomas, 1 hemangiopericytoma, and 1 choroid plexus papilloma. Patient characteristics are detailed in Table 1.

 

Table 1

3.1. FF-OCT imaging identifies myelinated axon fibers, neuronal cell bodies and vasculature in the human epileptic brain and cerebellum

The cortex and the white matter are clearly distinguished from one another (Fig. 2). Indeed, a subpopulation of neuronal cell bodies (Fig. 2B, C) as well as myelinated axon bundles leading to the white matter could be recognized (Fig. 2D, E). Neuronal cell bodies appear as dark triangles (Fig. 2C) in relation to the bright surrounding myelinated environment. The FF-OCT signal is produced by backscattered photons from tissues of differing refractive indices. The number of photons backscattered from the nuclei in neurons appears to be too few to produce a signal that allows their differentiation from the cytoplasm, and therefore the whole of the cell body (nucleus plus cytoplasm) appears dark.

Fig 2

 

Myelinated axons are numerous, well discernible as small fascicles and appear as bright white lines (Fig. 2E). As the cortex does not contain many myelinated axons, it appears dark gray. Brain vasculature is visible (Fig. 2F and G), and small vessels are distinguished by a thin collagen membrane that appears light gray. Video 1 in supplementary material shows a movie composed of a series of en face 1 μm thick optical slices captured over 100 μm into the depth of the cortex tissue. The myelin fibers and neuronal cell bodies are seen in successive layers.

The different regions of the human hippocampal formation are easily recognizable (Fig. 3). Indeed, CA1 field and its stratum radiatum, CA4 field, the hippocampal fissure, the dentate gyrus, and the alveus are easily distinguishable. Other structures become visible by zooming in digitally on the FF-OCT image. The large pyramidal neurons of the CA4 field (Fig. 3B) and the granule cells that constitute the stratum granulosum of the dentate gyrus are visible, as black triangles and as small round dots, respectively (Fig. 3D).

 

Fig 3

In the normal cerebellum, the lamellar or foliar pattern of alternating cortex and central white matter is easily observed (Fig. 4A). By digital zooming, Purkinje and granular neurons also appear as black triangles or dots, respectively (Fig. 4C), and myelinated axons are visible as bright white lines (Fig. 4E). Video 2 in supplementary material shows a fly-through movie in the reconstructed axial slice orientation of a cortex region in cerebellum. The Purkinje and granular neurons are visible down to depths of 200 μm in the tissue.

 

Fig 4

3.2. FF-OCT images distinguish meningiomas from hemangiopericytoma in meningeal tumors

The classic morphological features of a meningioma are visible on the FF-OCT image: large lobules of tumorous cells appear in light gray (Fig. 5A), demarcated by collagen-rich bundles (Fig. 5B) which are highly scattering and appear a brilliant white in the FF-OCT images. The classic concentric tumorous cell clusters (whorls) are very clearly distinguished on the FF-OCT image (Fig. 5D). In addition the presence of numerous cell whorls with central calcifications (psammoma bodies) is revealed (Fig. 5F). Collagen balls appear bright white on the FF-OCT image (Fig. 5H). As the collagen balls progressively calcify, they are consumed by the black of the calcified area, generating a target-like image (Fig. 5H). Calcifications appear black in FF-OCT as they are crystalline and so allow no penetration of photons to their interior.

Fig 5

Mesenchymal non-meningothelial tumors such as hemangiopericytomas represent a classic differential diagnosis of meningiomas. In FF-OCT, the hemangiopericytoma is more monotonous in appearance than the meningiomas, with a highly vascular branching component with staghorn-type vessels (Fig. 6A, C).

Fig 6

3.3. FF-OCT images identify choroid plexus papilloma

The choroid plexus papilloma appears as an irregular coalescence of multiple papillas composed of elongated fibrovascular axes covered by a single layer of choroid glial cells (Fig. 7). By zooming in on an edematous papilla, the axis appears as a black structure covered by a regular light gray line (Fig. 7B). If the papilla central axis is hemorrhagic, the fine regular single layer is not distinguishable (Fig. 7C). Additional digital zooming in on the image reveals cellular level information, and some nuclei of plexus choroid cells can be recognized. However, cellular atypia and mitosis are not visible. These represent key diagnosis criteria used to differentiate choroid plexus papilloma (grade I) from atypical plexus papilloma (grade II).

Fig 7

3.4. FF-OCT images detect the brain tissue architecture modifications generated by diffusely infiltrative gliomas

Contrary to the choroid plexus papillomas which have a very distinctive architecture in histology (cauliflower-like aspect), very easily recognized in the FF-OCT images (Fig. 7A to G), diffusely infiltrating glioma does not present a specific tumor architecture (Fig. 8) as they diffusely permeate the normal brain architecture. Hence, the tumorous glial cells are largely dispersed through a nearly normal brain parenchyma (Fig. 8E). The presence of infiltrating tumorous glial cells attested by high magnification histological observation (irregular atypical cell nuclei compared to normal oligodendrocytes) is not detectable with the current generation of FF-OCT devices, as FF-OCT cannot reliably distinguish the individual cell nuclei due to lack of contrast (as opposed to lack of resolution). In our experience, diffuse low-grade gliomas (less than 20% of tumor cell density) are mistaken for normal brain tissue on FF-OCT images. However, in high-grade gliomas (Fig. 8G–K), the infiltration of the tumor has occurred to such an extent that the normal parenchyma architecture is lost. This architectural change is easily observed in FF-OCT and is successfully identified as high-grade glioma, even though the individual glial cell nuclei are not distinguished.

Fig 8

4. Discussion

We present here the first large size images (i.e. on the order of 1–3 cm2) acquired using an OCT system that offer spatial resolution comparable to histological analysis, sufficient to distinguish microstructures of the human brain parenchyma.

Firstly, the FF-OCT technique and the images presented here combine several practical advantages. The imaging system is compact, it can be placed in the operating room, the tissue sample does not require preparation and image acquisition is rapid. This technique thus appears promising as an intraoperative tool to help neurosurgeons and pathologists.

Secondly, resolution is sufficient (on the order of 1 μm axial and lateral) to distinguish brain tissue microstructures. Indeed, it was possible to distinguish neuron cell bodies in the cortex and axon bundles going towards white matter. Individual myelin fibers of 1 μm in diameter are visible on the FF-OCT images. Thus FF-OCT may serve as a real-time anatomical locator.

Histological architectural characteristics of meningothelial, fibrous, transitional and psammomatous meningiomas were easily recognizable on the FF-OCT images (lobules and whorl formation, collagenous-septae, calcified psammoma bodies, thick vessels). Psammomatous and transitional meningiomas presented distinct architectural characteristics in FF-OCT images in comparison to those observed in hemangiopericytoma. Thus, FF-OCT may serve as an intraoperative tool, in addition to extemporaneous examination, to refine differential diagnosis between pathological entities with different prognoses and surgical managements.

Diffuse glioma was essentially recognized by the loss of normal parenchyma architecture. However, glioma could be detected on FF-OCT images only if the glial cell density is greater than around 20% (i.e. the point at which the effect on the architecture becomes noticeable). The FF-OCT technique is therefore not currently suitable for the evaluation of low tumorous infiltration or tumorous margins. Evaluation at the individual tumor cell level is only possible by IDH1R132 immunostaining in IDH1 mutated gliomas in adults (Preusser et al., 2011). One of the current limitations of the FF-OCT technique for use in diagnosis is the difficulty in estimating the nuclear/cytoplasmic boundaries and the size and form of nuclei as well as the nuclear-cytoplasmic ratio of cells. This prevents precise classification into tumor subtypes and grades.

To increase the accuracy of diagnosis of tumors where cell density measurement is necessary for grading, perspectives for the technique include development of a multimodal system (Harms et al., 2012) to allow simultaneous co-localized acquisition of FF-OCT and fluorescence images. The fluorescence channel images in this multimodal system show cell nuclei, which increase the possibility of diagnosis and tumor grading direct from optical images. However, the use of contrast agents for the fluorescence channel means that the multimodal imaging technique is no longer non-invasive, and this may be undesirable if the tissue is to progress to histology following optical imaging. This is a similar concern in confocal microscopy where use of dyes is necessary for fluorescence detection (Wirth et al., 2012).

In its current form therefore, FF-OCT is not intended to serve as a diagnostic tool, but should rather be considered as an additional intraoperative aid in order to determine in a short time whether or not there is suspicious tissue present in a sample. It does not aim to replace histological analyses but rather to complement them, by offering a tool at the intermediary stage of intraoperative tissue selection. In a few minutes, an image is produced that allows the surgeon or the pathologist to assess the content of the tissue sample. The selected tissue, once imaged with FF-OCT, may then proceed to conventional histology processing in order to obtain the full diagnosis (Assayag et al., in press and Dalimier and Salomon, 2012).

Development of FF-OCT to allow in vivo imaging is underway, and first steps include increasing camera acquisition speed. First results of in vivo rat brain imaging have been achieved with an FF-OCT prototype setup, and show real-time visualization of myelin fibers (Ben Arous et al., 2011) and movement of red blood cells in vessels (Binding et al., 2011). To respond more precisely to surgical needs, it would be preferable to integrate the FF-OCT system into a surgical probe. Work in this direction is currently underway and preliminary images of skin and breast tissue have been captured with a rigid probe FF-OCT prototype (Latrive and Boccara, 2011).

In conclusion, we have demonstrated the capacity of FF-OCT for imaging of human brain samples. This technique has potential as an intraoperative tool for determining tissue architecture and content in a few minutes. The 1 μm3 resolution and wide-field down to cellular-level views offered by the technique allowed identification of features of non-tumorous and tumorous tissues such as myelin fibers, neurons, microcalcifications, tumor cells, microcysts, and blood vessels. Correspondence with histological slides was good, indicating suitability of the technique for use in clinical practice for tissue selection for biobanking for example. Future work to extend the technique to in vivo imaging by rigid probe endoscopy is underway.

The following are the supplementary data related to this article.

Video 1.  Shows a movie composed of a series of en face 1 μm thick optical slices captured over 100 μm into the depth of the cortex tissue. The myelin fibers and neuronal cell bodies are seen in successive layers. Field size is 800 μm × 800 μm.

Video 2.  Shows a fly-through movie in the reconstructed cross-sectional orientation showing 1 μm steps through a 3D stack down to 200 μm depth in cerebellum cortical tissue. Purkinje and granular neurons are visible as dark spaces. Field size is 800 μm × 200 μm.

Acknowledgments

The authors wish to thank LLTech SAS for use of the LightCT Scanner.

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Long Noncoding RNA Network regulates PTEN Transcription

Author: Larry H Bernstein, MD, FCAP

Scientists Find Surprising New Influence On Cancer Genes

A pseudogene long noncoding RNA networkregulates PTEN transcription and translation in human cells
Per Johnsson, A Ackley, L Vidarsdottir, Weng-Onn Lui, M Corcoran, D Grandér, and KV Morris
a new study led by scientists at The Scripps Research Institute (TSRI) shows how
  • pseudogenes can regulate the activity of a cancer-related gene called PTEN.
The study also shows that pseudogenes can be targeted to control PTEN’s activity.

Mol Cancer. 2011; 10: 38.   Published online 2011 April 13. doi:  10.1186/1476-4598-10-38    PMCID: PMC3098824

New Type of Gene That Regulates Tumour Suppressor PTEN Identified

Feb. 24, 2013 — Researchers at Karolinska Institutet in Sweden have identified a new so-called pseudogene that regulates the tumour-suppressing PTEN gene.
They hope that this pseudogene will be able to control PTEN to

  1. reverse the tumour process,
  2. make the cancer tumour more sensitive to chemotherapy and
  3. prevent the development of resistance.

The findings, which are published in the scientific journal Nature Structural and Molecular Biology, can be of significance in

    • the future development of cancer drugs.

The development of tumours coincides with the activation of several cancer genes as well as the inactivation of other tumour-suppressing genes owing to

  1. damage to the DNA and
  2. to the fact that
    • the cancer cells manage to switch off the transcription of tumour-suppressor genes.

To identify what might be regulating this silencing, the researchers studied PTEN,

    • one of the most commonly inactivated tumour-suppressor genes.

It has long been believed that the switching-off process is irreversible, but the team has now shown that

  • silenced PTEN genes in tumour cells can be ‘rescued’ and
  • re-activated by a ‘pseudogene’,
    • a type of gene that, unlike normal genes,
    • does not encode an entire protein.

“We identified a new non-protein encoding pseudogene, which

  • determines whether the expression of PTEN
    • is to be switched on or off,”

says research team member Per Johnsson, at Karolinska Institutet’s Department of Oncology-Pathology. “What makes this case spectacular is that the gene

  • only produces RNA,
  • the protein’s template.

It is this RNA that, through a sequence of mechanisms,

    • regulates PTEN.

Pseudogenes have been known about for many years, but

  • it was thought that they were only junk material.”

No less than 98 per cent of human DNA consists of non-protein encoding genes (i.e. pseudogenes), and by studying these formerly neglected genes the researchers

  • have begun to understand that they are very important and
    • can have an effect without encoding proteins.

Using model systems, the team has shown that the new pseudogene can

  • control the expression of PTEN and
    • make tumours more responsive to conventional chemotherapy.

Pre Johnssom suggests “we might one day be able to re-programme cancer cells

  • to proliferate less,
  • become more normal, and that
  • resistance to chemotherapy can hopefully be avoided.

“We also believe that our findings can be very important for the future development of cancer drugs.  The human genome conceals no less than 15,000 or so pseudogenes, and it’s not unreasonable to think

  • that many of them are relevant to diseases such as cancer.”

The study was conducted in collaboration with scientists at The Scripps Research Institute, USA, and the University of New South Wales, Australia, and was made possible with

  • grants from the Swedish Childhood Cancer Foundation, the Swedish Cancer Society, the Cancer Research Funds of Radiumhemmet, Karolinska Institutet’s KID programme for doctoral studies, the Swedish Research Council, the Erik and Edith Fernström Foundation for Medical Research, the National Institute of Allergy and Infectious Diseases, the National Cancer Institute and the National Institutes of Health.

The functional role of long non-coding RNA in human carcinomas
EA Gibb, CJ Brown, and WL Lam
Long non-coding RNAs (lncRNAs) are emerging as new players in the cancer paradigm demonstrating potential roles in both oncogenic and tumor suppressive pathways. These novel genes are frequently

    • aberrantly expressed in a variety of human cancers,

however the biological functions of the vast majority remain unknown. Recently, evidence has begun to accumulate describing the molecular mechanisms by which these RNA species function, providing insight into

    • the functional roles they may play in tumorigenesis.

In this review, we highlight the emerging functional role of lncRNAs in human cancer.

One of modern biology’s great surprises was the discovery that the human genome encodes only ~20,000 protein-coding genes, representing <2% of the total genome sequence [1,2]. However, with the advent of

  • tiling resolution genomic microarrays and
  • whole genome and transcriptome sequencing technologies
    • it was determined that at least 90% of the genome is actively transcribed [3,4].

The human transcriptome was found to be more complex than

  • a collection of protein-coding genes and their splice variants; showing
    • extensive antisense,
    • overlapping and non-coding RNA (ncRNA) expression [5-10].

Although initially argued to be spurious transcriptional noise, recent evidence suggests that the proverbial “dark matter” of the genome

  • may play a major biological role in cellular development and metabolism [11-17].

One such player, the newly discovered long non-coding RNA (lncRNA) genes, demonstrate

  1. developmental and tissue specific expression patterns, and
  2. aberrant regulation in a variety of diseases, including cancer [18-27].

NcRNAs are loosely grouped into two major classes based on transcript size; small ncRNAs and lncRNAs [28-30].

  1. Small ncRNAs are represented by a broad range of known and newly discovered RNA species, with many being associated
    • with 5′ or 3′ regions of genes [4,31,32].

This class includes the well-documented miRNAs, RNAs ~22 nucleotides (nt) long involved in the specific regulation of both

  1. protein-coding, and
  2. putatively non-coding genes,
    • by post-transcriptional silencing or infrequently
    • by activation [33-35].

miRNAs serve as major

  1. regulators of gene expression and as
  2. intricate components of the cellular gene expression network [33-38].

Another newly described subclass are the transcription initiation RNAs (tiRNAs), which are

  • the smallest functional RNAs at only 18 nt in length [39,40].
  1. small ncRNAs classes, including miRNAs, have established roles in tumorigenesis, an intriguing association between
  2. the aberrant expression of ncRNA satellite repeats and cancer has been recently demonstrated [41-46].

Types of human non-coding RNAs

In contrast to miRNAs, lncRNAs, the focus of this article, are

    • mRNA-like transcripts ranging in length from 200 nt to ~100 kilobases (kb) lacking significant open reading frames.

Many identified lncRNAs are transcribed by RNA polymerase II (RNA pol II) and are polyadenylated, but this is not a fast rule [47,48].
There are examples of lncRNAs, such as the

  • antisense asOct4-pg5 or the
  • brain-associated BC200,
    • which are functional, but not polyadenylated [49-51].
  1. lncRNA expression levels appear to be lower than protein-coding genes [52-55], and some
  2. lncRNAs are preferentially expressed in specific tissues [21].

Novel lncRNAs may contribute a significant portion of the aforementioned ‘dark matter’ of the human transcriptome [56,57]. In an exciting report
by Kapranov et.al., it was revealed the bulk of the relative mass of RNA in a human cell, exclusive of the ribosomal and mitochondrial RNA,
is represented by non-coding transcripts with no known function
[57].

Like miRNAs and protein-coding genes, some

  • transcriptionally active lncRNA genes display
  • histone H3K4 trimethylation at their 5′-end and
  • histone H3K36 trimethylation in the body of the gene [8,58,59].

The small number of characterized human lncRNAs have been associated with a spectrum of biological processes, for example,

  • epigenetics,
  • alternative splicing,
  • nuclear import,
    1. as structural components,
    2. as precursors to small RNAs and
    3. even as regulators of mRNA decay [4,60-70].

Furthermore, accumulating reports of misregulated lncRNA expression across numerous cancer types suggest that

    • aberrant lncRNA expression may be a major contributor to tumorigenesis [71].

This surge in publications reflects the increasing attention to this subject  and a number of useful lncRNA databases have been created .
In this review we highlight the emerging

    • functional role of aberrant lncRNA expression, including
    • transcribed ultraconserved regions (T-UCRs), within human carcinomas.

Publications describing cancer-associated ncRNAs. Entries are based on a National Library of Medicine Pubmed search using the terms
“ncRNA” or “non-coding RNA” or “noncoding RNA” or non-protein-coding RNA” with cancer and annual (Jan.1-Dec.31) date limitations. …
Publically available long non-coding RNA online databases

The definition ‘non-coding RNA’ is typically used to describe transcripts where

    • sequence analysis has failed to identify an open reading frame.

There are cases where ‘non-coding’ transcripts were found to encode short, functional peptides [72]. Currently, a
universal classification scheme to define lncRNAs does not exist. Terms such as

  • large non-coding RNA,
  • mRNA-like long RNA, and
  • intergenic RNA

all define cellular RNAs, exclusive of rRNAs,

    • greater than 200 nt in length and having no obvious protein-coding capacity [62].

This has led to confusion in the literature as to exactly which transcripts should constitute a lncRNA. One subclass of lncRNAs is called
large or long intergenic ncRNAs (lincRNAs). These lncRNAs are

  1. exclusively intergenic and are
  2. marked by a chromatin signature indicative of transcription [8,58].

RNA species that are bifunctional preclude categorization into either group of

  • protein-coding or
  • ncRNAs as

their transcripts function both at the RNA and protein levels [73].

The term ‘lncRNA‘ is used only to describe transcripts with no protein-coding capacity. In the meantime, and for the purposes of this review,
we will consider lncRNAs as a blanket term to encompass

  1. mRNA-like ncRNAs,
  2. lincRNAs, as well as
  3. antisense and intron-encoded transcripts,
  4. T-UCRs and
  5. transcribed pseudogenes.

Discovery of LncRNAs

The earliest reports describing lncRNA predated the discovery of miRNAs, although the term ‘lncRNA‘ had not been coined at the time .
One of the first lncRNA genes reported was the imprinted H19 gene, which was quickly followed by the discovery of the

  • silencing X-inactive-specific transcript (XIST) lncRNA gene, which
    • plays a critical function in X-chromosome inactivation [74,75].

The discovery of the first miRNA lin-14 dramatically redirected the focus of ncRNA research from long ncRNAs to miRNAs [76], and
the discovery of miRNAs revealed RNA could

  1. regulate gene expression and
  2. entire gene networks could be affected by ncRNA expression and

Within the last decade miRNAs were discovered to be associated with cancer. At the time of this writing there are approximately
1049 human miRNAs described in miRBase V16 [80,81] with the potential of

    • affecting the expression of approximately 60% of protein -coding genes [82,83].

Conversely, the variety and dynamics of lncRNA expression was not to be fully appreciated until the introduction of whole transcriptome sequencing.
With the advent of the FANTOM and ENCODE transcript mapping projects, it was revealed that the mammalian genome is extensively transcribed,
although a large portion of this represented non-coding sequences [3,84]. Coupled with the novel functional annotation of a few lncRNAs, this discovery
promoted research focusing on lncRNA discovery and characterization. Recent reports have described new lncRNA classes such as lincRNAs and T-UCRs [8,58,85].
Current estimates of the lncRNA gene content in the human genome ranges from ~7000 – 23,000 unique lncRNAs, implying this class of ncRNA will
represent an enormous, yet undiscovered, component of normal cellular networks that may be disrupted in cancer biology [62].

Emerging Role of Long Non-Coding RNA in Tumorigenesis

A role for differential lncRNA expression in cancer had been suspected for many years, however, lacked strong supporting evidence [86]. With advancements
in cancer transcriptome profiling and accumulating evidence supporting lncRNA function, a number of differentially expressed lncRNAs have been associated
with cancer. LncRNAs have been implicated to

  • regulate a range of biological functions and
  • the disruption of some of these functions, such as
    • genomic imprinting and transcriptional regulation,
    • plays a critical role in cancer development.

Here we describe some of the better characterized lncRNAs that have been associated with cancer biology.

Human cancer-associated lncRNAs

Imprinted lncRNA genes

Imprinting is a process whereby the copy of a gene inherited from one parent is epigenetically silenced [87,88]. Intriguingly, imprinted regions often
include multiple maternal and paternally expressed genes with a high frequency of ncRNA genes. The imprinted ncRNA genes are implicated in the
imprinting of the region by a variety of mechanisms including

  • enhancer competition and chromatin remodeling [89].

A key feature of cancer is the loss of this imprinting resulting in altered gene expression [90,91]. Two of the best known imprinted genes
are in fact lncRNAs.

H19

The H19 gene encodes a 2.3 kb lncRNA that is expressed exclusively from the maternal allele. H19 and its reciprocally imprinted protein-coding neighbor
the Insulin-Like Growth Factor 2 or IGF2 gene at 11p15.5 were among the first genes, non-coding or otherwise, found to demonstrate genomic imprinting [74,92].

The expression of H19 is high during vertebrate embryo development, but is

  • downregulated in most tissues shortly after birth with the exception of skeletal tissue and cartilage [20,93,94].
  • Loss of imprinting and subsequent strong gene expression has been well-documented in human cancers. Likewise,
  • loss of imprinting at the H19 locus resulted in high H19 expression in cancers of the esophagus, colon, liver, bladder and with hepatic metastases [95-97].

H19 has been implicated as having both oncogenic and tumor suppression properties in cancer. H19 is upregulated in a number of human cancers, including
hepatocellular, bladder and breast carcinomas, suggesting an oncogenic function for this lncRNA [97-99]. In colon cancer H19 was shown to be directly activated
by the oncogenic transcription factor c-Myc, suggesting

  • H19 may be an intermediate functionary between c-Myc and downstream gene expression [98].

Conversely, the tumor suppressor gene and transcriptional activator p53 has been shown to

  • down-regulate H19 expression [100,101].

H19 transcripts also serve as a precursor for miR-675, a miRNA involved in the regulation of developmental genes [102].
miR-675 is processed from the first exon of H19 and functionally

  • downregulates the tumor suppressor gene retinoblastoma (RB1) in human colorectal cancer, further implying an oncogenic role for H19 [103].

There is evidence suggesting H19 may also play a role in tumor suppression [104,105]. Using a mouse model for colorectal cancer, it was shown that
mice lacking H19 manifested an increased polyp count compared to wild-type [106]. Secondly, a mouse teratocarcinoma model demonstrated larger
tumor growth when the embryo lacked H19, and finally in a hepatocarcinoma model, mice developed cancer much earlier when H19 was absent [107].
The discrepancy as to whether H19 has oncogenic or tumor suppressive potential may be due in part to the bifunctional nature of the lncRNA or may
be context dependent. In either case, the precise functional and biological role of H19 remains to be determined.

XIST – X-inactive-specific transcript

The 17 kb lncRNA XIST is arguably an archetype for the study of functional lncRNAs in mammalian cells, having been studied for nearly two decades.
In female cells, the XIST transcript plays a critical role in X-chromosome inactivation by

  • physically coating one of the two X-chromosomes, and is necessary for the
  • cis-inactivation of the over one thousand X-linked genes [75,108-110].

Like the lncRNAs HOTAIR and ANRIL, XIST associates with polycomb-repressor proteins, suggesting

    • a common pathway of inducing silencing utilized by diverse lncRNAs.

Discovery of Molecular Mechanisms of Traditional Chinese Medicinal Formula Si-Wu-Tang Using Gene Expression Microarray and Connectivity Map
by Zhining Wen, Zhijun Wang, Steven Wang, Ranadheer Ravula, Lun Yang, …et al.
PLoS ONE (2011); 6:(3), Publisher: PLoS, Pages: 14    http.//dx.doi.org/10.1371/journal.pone.0018278        PubMed: 21464939
http://dx.plos.org/Wen Z, Wang Z, Wang Z, et al./discovery of molecular mechanisms of traditional chinese medicinal formula…/
To pursue a systematic approach to discovery of mechanisms of action of traditional Chinese medicine (TCM), we used

  • microarrays,
  • bioinformatics and the
  • Connectivity Map (CMAP)
    • to examine TCM-induced changes in gene expression.

We demonstrated that this approach can be used to elucidate new molecular targets using a model TCM herbal formula Si-Wu-Tang (SWT) which is

  • widely used for women’s health.

The human breast cancer MCF-7 cells treated with 0.1 µM estradiol or 2.56 mg/ml of SWT

  • showed dramatic gene expression changes, while
  • no significant change was detected for ferulic acid, a known bioactive compound of SWT.

Pathway analysis using

  • differentially expressed genes related to the treatment effect
  • identified that expression of genes in the nuclear factor erythroid 2-related factor 2 (Nrf2) cytoprotective pathway
  • was most significantly affected by SWT,
    • but not by estradiol or ferulic acid.
  • The Nrf2-regulated genes
    • HMOX1,
    • GCLC,
    • GCLM,
    • SLC7A11 and
    • NQO1 were
  • upreguated by SWT in a dose-dependent manner, which was validated by real-time RT-PCR. Consistently,
  • treatment with SWT and its four herbal ingredients resulted in an 
  • increased antioxidant response element (ARE)-luciferase reporter activity in MCF-7 and HEK293 cells.

Furthermore, the gene expression profile of differentially expressed genes related to SWT treatment was used to compare with those of

  • 1,309 compounds in the CMAP database.

The CMAP profiles of estradiol-treated MCF-7 cells showed an excellent match with SWT treatment,

  • consistent with SWT’s widely claimed use for women’s diseases and indicating a phytoestrogenic effect.

Read Full Post »


Reporter: Ritu Saxena, Ph.D.

With the number of cancer cases plummeting every year, there is a dire need for finding a cure to wipe the disease out. A number of therapeutic drugs are currently in use, however, due to heterogeneity of the disease targeted therapy is required. An important criteria that needs to be addressed in this context is the –‘tumor response’ and how it could be predicted, thereby improving the selection of patients for cancer treatment. The issue of tumor response has been addressed in a recent editorial titled “Tumor response criteria: are they appropriate?” published recently in Future Oncology.

The article talks about how the early tumor treatment response methods came into practice and how we need to redefine and reassess the tumor response.

Defining ‘tumor response’ has always been a challenge

WHO defines a response to anticancer therapy as 50% or more reduction in the tumor size measured in two perpendicular diameters. It is based on the results of experiments performed by Moertel and Hanley in 1976 and later published by Miller et al in 1981. Twenty years later, in the year 2000, the US National Cancer Institute, with the European Association for Research and Treatment of Cancer, proposed ‘new response criteria’ for solid tumors; a replacement of 2D measurement with measurement of one dimen­sion was made. Tumor response was defined as a decrease in the largest tumor diameter by 30%, which would translate into a 50% decrease for a spherical lesion. However, response criteria have not been updated after that and there a structured standardization of treatment response is still required especially when several studies have revealed that the response of tumors to a therapy via imaging results from conventional approaches such as endoscopy, CT scan, is not reliable. The reason is that evaluating the size of tumor is just one part of the story and to get the complete picture inves­tigating and evaluating the tissue is essential to differentiate between treatment-related scar, fibrosis or micro­scopic residual tumor.

In clinical practice, treatment response is determined on the basis of well-established parameters obtained from diagnostic imaging, both cross-sectional and functional. In general, the response is classified as:

  • Complete remission: If a tumor disappears after a particular therapy,
  • Partial remission: there is residual tumor after therapy.

For a doctor examining the morphology of the tumor, complete remission might seem like good news, however, mission might not be complete yet! For example, in some cases, with regard to prognosis, patients with 0% residual tumor (complete tumor response) had the same prognosis com­pared with those patients with 1–10% residual tumor (subtotal response).

Another example is that in patients demonstrating complete remission of tumor response as observed with clinical, sonographic, functional (PET) and histopathological analysis experience recur­rence within the first 2 years of resection.

Adding complexity to the situation is the fact that the appropriate, clinically relevant timing of assess­ment of tumor response to treatment remains undefined. An example mentioned in the editorial is – for gastrointestinal (GI) malignancies, the assessment timing varies considerably from 3 to 6 weeks after initia­tion of neoadjuvant external beam radiation. Further, time could vary depending upon the type of radiation administered, i.e., if it is external beam, accelerated hyperfractionation, or brachytherapy.

Abovementioned examples remind us of the intricacy and enigma of tumor biol­ogy and subsequent tumor response.

Conclusion

Owing to the extraordinary het­erogeneity of cancers between patients, and pri­mary and metastatic tumors in the same patients, it is important to consider several factors while determining the response of tumors to different therapie in clinical trials. Authors exclaim, “We must change the tools we use to assess tumor response. The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ charac­teristics.”

Future perspective

Editorial points out that the oncologists, radiotherapists, and immunologists all might have a different opinion and observation as far as tumor response is considered. For example, surgical oncologists might determine a treatment to be effective if the local tumor control is much better after multimodal treatment, and that patients post-therapeutically also reveal an increase of the rate of microscopic and macroscopic R0-resection. Immunologists, on the other hand, might just declare a response if immune-competent cells have been decreased and, possibly, without clinical signs of decrease of tumor size.

What might be the answer to the complexity to reading tumor response is stated in the editorial – “an interdisciplinary initiative with all key stake­holders and disciplines represented is imperative to make predictive and prognostic individualized tumor response assessment a modern-day reality. The integrated multidisciplinary panel of international experts need to define how to leverage existing data, tissue and testing platforms in order to predict individual patient treatment response and prog­nosis.”

Sources:

Editorial : Björn LDM Brücher et al Tumor response criteria: are they appropriate? Future Oncology August 2012, Vol. 8, No. 8, 903-906.

Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer 1981, 47(1),207–214.

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