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Posts Tagged ‘NCI’


 

Reporter: Aviva Lev-Ari, PhD, RN

 

Systems Pharmacology: Pathways to Patient Response @ BioIT World, Boston, MA World Trade Center, April 9-11, 2013

Conference Tracks:

IT Infrastructure – Hardware

Software Development

Cloud Computing

Bioinformatics

Next-Gen Sequencing Informatics

Systems Pharmacology

eClinical Trials Solutions

Data Visualization NEW!

Drug Discovery Informatics

Clinical Omics NEW!

Collaborations and Open

Access Innovations

Cancer Informatics

 

Track 6 focuses on how compounds (drugs) work in the body. How are they influenced by various ‘omics’? How do they vary by tissue? The practical implications of such a compound-centric approach are exciting: new targets, new screens, new markers, new understanding of drug failure mechanisms. The systems computational tool sets including multi-scale modeling, simulation, web-based platforms, etc. will be emphasized.

Final Agenda

 

Download Brochure | Pre-Conference Workshops

 

TUESDAY, APRIL 9

7:00 am Workshop Registration and Morning Coffee

8:00 Pre-Conference Workshops*

 

*Separate Registration Required

2:00 – 7:00 pm Main Conference Registration

4:00 Event Chairperson’s Opening Remarks

Cindy Crowninshield, RD, LDN, Conference Director, Cambridge Healthtech Institute

4:05 Keynote Introduction

Speaker to be Announced, Hitachi Data Systems

 

» 4:15 PLENARY KEYNOTE

Do Network Pharmacologists Need Robot Chemists?

Andrew HopkinsAndrew L. Hopkins, DPhil, FRSC, FSB, Division of Biological Chemistry and Drug Design, College of Life Sciences, University of Dundee

 

5:00 Welcome Reception in the Exhibit Hall with Poster Viewing

Drop off a business card at the CHI Sales booth for a chance to win 1 of 2 iPads® or 1 of 2 Kindle Fires®!*

*Apple ® and Amazon are not sponsors or participants in this program

 

WEDNESDAY, APRIL 10

7:00 am Registration and Morning Coffee

8:00 Chairperson’s Opening Remarks

Phillips Kuhl, Co-Founder and President, Cambridge Healthtech Institute

8:05 Keynote Introduction

Sanjay Joshi, CTO, Life Sciences, EMC Isilon

 

» 8:15 PLENARY KEYNOTE

Atul ButteAtul Butte, M.D., Ph.D., Division Chief and Associate Professor, Stanford University School of Medicine; Director, Center for Pediatric Bioinformatics, Lucile Packard Children’s Hospital; Co-founder, Personalis and Numedii

 

8:55 Benjamin Franklin Award & Laureate Presentation

9:15 Best Practices Award Program

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

 

PHARMACODYNAMIC MODELS

10:50 Chairperson’s Remarks

» Featured Speaker

11:00 Systems Pharmacology in a Post-Genomic Era

Peter Sorger, Ph.D., Professor, Systems Biology, Harvard Medical School; Co-Chair, Harvard Initiative in Systems Pharmacology

I will describe the emergence of “systems pharmacology” as a means to guide the creation of new molecular matter, study cellular networks and their perturbation by drugs, understand pharmaco-kinetics and pharmaco-dynamics in mouse and man and design and analyze clinical trial data. The approach combines mathematical modeling with empirical measurement as a means to tackle basic and clinical problems in pharmacology. Ultimately we aim for models that describe drug responses at multiple temporal and physical scales from molecular mechanism to whole-organism physiology.

11:30 Using Quantitative Systems Pharmacology for De-Risking Projects in CNS R&D

Hugo Geerts, Ph.D., CSO, Computational Neuropharmacology, In Silico Biosciences

Quantitative Systems Pharmacology is a computer based mechanistic modeling approach combining physiology, the functional imaging of genetics with the pharmacology of drug-receptor interaction and parameterized with clinical data and is a possible powerful tool for improving the success rate of CNS R&D projects. The presentation will include failure analyses of unsuccessful clinical trials, correct prospective identification of clinical problems that halted clinical development and estimation of genotype effects on the pharmacodynamics of candidate drugs.

Thomson Reuters logo12:00 pm Systems Pharmacology Approaches to Drug Repositioning

Svetlana Bureeva, Ph.D., Director, Professional Services, Thomson Reuters, IP & Science

Drug repositioning requires advanced computational approaches and comprehensive knowledgebase information to reach success. Thomson Reuters will present on recent advances in drug repositioning approaches, their validation and performance, best practices in using systems biology content, and successful case studies.

12:30 Luncheon Presentation (Sponsorship Opportunity Available) or Lunch on Your Own

 

HIGH CONTENT ANALYSIS: CANCER CELL LINES

1:40 Chairperson’s Remarks

1:45 Systems Pharmacology Using CellMiner and the NCI-60 Cancerous Cell Lines

William Reinhold, Manager, Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology (LMP), National Cancer Institute (NCI)

CellMiner is a web-based application that allows rapid access to and comparison between 20,503 compound activities and the expression levels of 26,065 genes and 360 microRNAs. Included are 102 FDA-approved drugs as well as 53 in clinical trials. The tool is designed for the non-informatisist, and allows the user wide latitude in defining the question of interest. This opens the door to systems pharmacological studies for physicians, molecular biologists and others without bioinformatics expertise.

2:15 Oncology Drug Combinations at Novartis

Joseph Lehár, Ph.D., Associate Director, Bioinformatics, Oncology Translational Research, Novartis; Adjunct Assistant Professor, Bioinformatics, Boston University

Novartis is undertaking a large-scale effort to comprehensively describe cancer through the lens of cell cultures and tissue samples.  In collaboration with academic and industrial partners, we have generated mutation status, gene copy number, and gene expression data for a library of 1,000 cancer cell lines, representing most cancer lineages and common genetic backgrounds.  Most of these cell lines have been tested for chemosensitivity against ~1,200 cancer-relevant compounds, and we are systematically exploring drug combinations for synergy against ~100 prioritized CCLE lines.  We expect this large-scale campaign to enable efficient patient selection for clinical trials on existing cancer drugs, reveal many therapeutically promising drug synergies or anti-resistance combinations, and provide unprecedented detail on functional interactions between cancer signaling pathways.   I will discuss early highlights of this work and describe our plans to make use of this resource.

2:45 Sponsored Presentations (Opportunities Available)

3:15 Refreshment Break in the Exhibit Hall with Poster Viewing

 

PHARMACODYNAMIC MODELS FOR ONCOLOGY

3:45 Systems Biology in Cancer Immunotherapy: Applications in the Understanding of Mechanism of Action and Therapeutic Response

Debraj Guha Thakurta, Ph.D., Senior Scientist II & Group Leader, Systems Biology, Dendreon Corporation

We are using high-content platforms (DNA and protein microarrays, RNA-seq) in various stages of the development of cellular immunotherapies for cancer. We will provide examples of genomic applications that can aid in the mechanistic understanding and the discovery of molecular markers associated with the efficacy of a cancer immunotherapy..

4:15 Use of Systems Pharmacology to Aid Cancer Clinical Development

Anna Georgieva Kondic, Ph.D., MBA, Senior Principal Scientist, Modeling and Simulation, Merck Research Labs

The last few years have seen an increased use of physiologically-based pharmacokinetics and pharmacodynamics models in Oncology drug development. This is partially due to an improved mechanistic understanding of disease drivers and the collection of better patient-level quantitative data that lends itself to modeling. In this talk, a suite of studies where systems modeling was successfully used to inform either preclinical to clinical transition or clinical study design will be presented. The talk will complete with a potential systems pharmacology framework that can be used systematically in drug development.

4:45 Sponsored Presentations (Opportunities Available)

5:15 Best of Show Awards Reception in the Exhibit Hall

6:15 Exhibit Hall Closes

 

Thursday, April 11

7:00 am Breakfast Presentation (Sponsorship Opportunity Available) or Morning Coffee

 

MODELING AND MINING TARGETS

8:45 Chairperson’s Opening Remarks

8:50 Systems Biology Approach for Identification of New Targets and Biomarkers

I-Ming Wang, Ph.D., Associate Scientific Director, Research Solutions and Bioinformatics, Informatics and Analysis, Merck Research Laboratory

A representative gene signature was identified by an integrated analysis of expression data in twelve rodent inflammatory models/tissues. This “inflammatome” signature is highly enriched in known drug target genes and is significantly overlapped with macrophage-enriched metabolic networks (MEMN) reported previously. A large proportion of genes in this signature are tightly connected in several tissue-specific Bayesian networks built from multiple mouse F2 crosses and human tissue cohorts; furthermore, these tissue networks are very significantly overlapped. This indicates that variable expression in this set of co-regulated genes is the main driver of many disease states. Disease-specific gene sets with the potential of being utilized as biomarkers were also identified with the approach we applied. The identification of this “inflammatome” gene signature extends the coverage of MEMN beyond adipose and liver in the metabolic disease to multiple diseases involving various affected tissues.

9:20 Optimizing Therapeutic Index (TI) by Exploring Co-Dependencies of Target and Therapeutic Properties

Madhu Natarajan, Ph.D., Associate Director, Computational Biology, Discovery Research, Shire HGT

Conventional drug-discovery informatics workflows employ combinations of mechanistic/probabilistic in-silico methods to rank lists of targets; therapeutics are then developed for “optimal” targets. I describe a systems pharmacology approach that instead integrates systematic in-silico therapeutic perturbation with models of target/disease biology to identify conditions for optimal TI; non-intuitively optimal TI is sometimes achieved by pairing sub-optimal targets with therapeutics having appropriate properties.

9:50 Sponsored Presentations (Opportunities Available)

10:20 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

10:45 Plenary Keynote Panel Chairperson’s Remarks

Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

10:50 Plenary Keynote Panel Introduction

Yury Rozenman, Head of BT for Life Sciences, BT Global Services

 

» PLENARY KEYNOTE PANEL

11:05 The Life Sciences CIO Panel

Panelists:
Remy Evard, CIO, Novartis Institutes for BioMedical Research
Martin Leach, Ph.D., Vice President, R&D IT, Biogen Idec
Andrea T. Norris, Director, Center for Information Technology (CIT) and Chief Information Officer, NIH
Gunaretnam Rajagopal, Ph.D., Vice President and CIO, Bioinformatics & External Innovation at Janssen Pharmaceutical Companies of Johnson & Johnson
Cris Ross, Chief Information Officer, Mayo Clinic

 

12:15 pm Luncheon in the Exhibit Hall with Poster Viewing

 

MODELING MOLECULAR AND PATHOPHYSIOLOGICAL DATA

1:55 Chairperson’s Remarks

2:00 Predicting Adverse Side Effects of Drugs Using Systems Pharmacology

Jake Chen, Ph.D., Associate Professor, Indiana University School of Informatics & Purdue University Department of Computer Science; Director, Indiana Center for Systems Biology and Personalized Medicine

A new way of studying drug toxicity is to incorporate biomolecular annotation and network data with clinical observations of drug targets upon drug perturbations. I will describe the development of a novel computational modeling framework, with which we demonstrated the highest drug toxicity prediction accuracies ever reported by far. Adoption of this framework may have profound practical drug discovery implications.

2:30 Holistic Integration of Molecular and Physiological Data and Its Application in Personalized Healthcare

David de Graaf, Ph.D. President and CEO, Selventa

There are multiple industry-wide challenges in aggregating molecular and pathophysiological data for systems pharmacology to transform the process of drug discovery and development. One of the ways to address these challenges is to utilize a common computable biological expression language (BEL) that can provide a comprehensive knowledge network for new discoveries. An application of BEL and its use in identifying clinically relevant predictive biomarkers for patient stratification will be presented.

3:00 The Role of Informatics in ADME Pharmacogenetics

Boyd SteereBoyd Steere, Ph.D., Senior Research Scientist, Lilly Research Laboraories, IT Research Informatics, Eli Lilly

The leveraging of pharmacogenetics to support decisions in early-phase clinical trial design requires informatics methods to integrate, visualize, and analyze heterogeneous data sets from many different discovery platforms.  This presentation describes challenges and solutions in making sense of diverse sets of genetic, protein, and metabolic data in support of ADME pharmacology projects.

3:30 A Systems Pharmacology Approach to Understand and Optimize Functional Selectivity for Non-Selective Drugs

Joshua Apgar, Principal Scientist, Systems Biology, Dept. of Immunology & Inflammation, Boehringer Ingelheim Pharmaceuticals, Inc.

Most commonly the selectivity of a compound is defined in an in vitro or cellular assay, and it is thought of as principally a function of the binding energy of the drug to its on-target and off-target proteins; however, in vivo functional selectivity is much more complicated, and is affected by systems level effects such as multiple feedback processes within and between the various on- and off-target pathways. These systems level processes are often impossible to reconstruct in vitro as they involve many cell types, tissues, and organs systems throughout the body. We show here that through mathematical modeling we were able to identify, in silico, molecular properties that are critical to driving functional selectivity. The models, although simple, capture the key systems pharmacology needed to understand the on- an off- target effects. Surprisingly, in this case, the key driver of functional selectivity is not the affinity of the drugs but rather the pharmacokinetics, with drugs having a short half-life predicted to be the most functionally selective.

 SOURCE:
Final Agenda

 

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State of the art in oncologic imaging of lungs.

Author-Writer: Dror Nir, PhD

 This is the second post in a series in which I will address the state of the art in oncologic imaging based on a review paper; Advances in oncologic imaging that provides updates on the latest approaches to imaging of 5 common cancers: breast, lung, prostate, colorectal cancers, and lymphoma. This paper is published at CA Cancer J Clin 2012. © 2012 American Cancer Society.

The paper gives a fair description of the use of imaging in interventional oncology based on literature review of more than 200 peer-reviewed publications.

In this post I summaries the chapter on lung cancer imaging.

Lung Cancer Imaging

“Lung cancer remains the most common cause of death from cancer worldwide, having resulted in 1.38 million deaths (18.2% of all cancer deaths) in 2008.48 It also represents the leading cause of death in smokers and the leading cause of cancer mortality in men and women in the United States. In 2012, it was estimated that 226,160 new cases of lung cancer would be diagnosed (accounting for about 14% of cancer diagnoses) and that lung cancer would cause 160,340 deaths (about 29% of cancer deaths in men and 26% of cancer deaths in women) in the United States.1 The 1-year relative survival rate for the disease increased from 35% to 43% from 1975 through 1979 to 2003 through 2006.49 The 5-year survival rate is 53% for disease that is localized when first detected, but only 15% of lung cancers are diagnosed at this early stage.”

For cancer with such poor survival rates removal of the primary lesion by surgery at an early-stage disease is the best option. The current perception in regards to lung cancr is that patients may have subclinical disease for years before presentation. It is also known that early lung cancer lesions; adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) are slow-growing, doubling time which can exceed 2 years.52 But, since at present, no lung cancer early-detection biomarker is clinically available, the diagnosis of this disease is primarily based on symptoms, and detection often occurs after curative intervention and when it’s already too late – see: Update on biomarkers for the detection of lung cancer and also Diagnosing lung cancer in exhaled breath using gold nanoparticles. Until biomarker is found, the burden of screening for this disease is on imaging.

“AIS and MIA generally appear as a single peripheral ground-glass nodule on CT. A small solid component may be present if areas of alveolar collapse or fibroblastic proliferation are present,5051 but any solid component should raise concern for a more invasive lesion (Fig. 8). Growth over time on imaging can often be difficult to assess due to the long doubling time of these AIS and MIA, which can exceed 2 years.52 However, indicators other than growth, such as air bronchograms, increasing density, and pleural retraction within a ground-glass nodule are suggestive of AIS or MIA.

CT image shows a ground glass nodule, which is the typical appearance of AIS, in the right upper lobe.

CT image shows a ground glass nodule, which is the typical appearance of AIS, in the right upper lobe.

 

CT (A) demonstrated extensive consolidation with air bronchograms in the left upper lobe, which at surgical resection were found to represent adenocarcinoma of mixed subtype with predominate (70%) mucinous bronchioloalveolar subtype. PET imaging in the same patient (B) demonstrated uptake in the lingula higher than expected for bronchioloalveolar carcinoma and probably due to secondary inflammation/infection. CT (C) obtained 3 years after images (A) and (B) demonstrated biopsy-proven recurrent soft-tissue mass near surgical site. Fused FDG/PET images (D) demonstrate no uptake in the area. This finding is consistent with the decreased uptake usually seen in tumors of bronchioloalveolar histology (new terminology of MIA).

CT (A) demonstrated extensive consolidation with air bronchograms in the left upper lobe, which at surgical resection were found to represent adenocarcinoma of mixed subtype with predominate (70%) mucinous bronchioloalveolar subtype. PET imaging in the same patient (B) demonstrated uptake in the lingula higher than expected for bronchioloalveolar carcinoma and probably due to secondary inflammation/infection. CT (C) obtained 3 years after images (A) and (B) demonstrated biopsy-proven recurrent soft-tissue mass near surgical site. Fused FDG/PET images (D) demonstrate no uptake in the area. This finding is consistent with the decreased uptake usually seen in tumors of bronchioloalveolar histology (new terminology of MIA).

In August 2011 the results of the “National Lung Screening Trial “ which was funded by the National Cancer Institute (NCI) were published in NEJM; Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening. This randomized study results showed that with low-dose CT screening of high-risk persons, there was a significant reduction of 20% in the mortality rate from lung cancer as compared to chest radiographs screening.

Based on these results one can find the following information regarding Lung Cancer Screening on the NCI web-site:

Three screening tests have been studied to see if they decrease the risk of dying from lung cancer.

The following screening tests have been studied to see if they decrease the risk of dying from lung cancer:

  • Chest x-ray: An x-ray of the organs and bones inside the chest. An x-ray is a type of energy beam that can go through the body and onto film, making a picture of areas inside the body.
  • Sputum cytology: Sputum cytology is a procedure in which a sample of sputum (mucus that is coughed up from the lungs) is viewed under a microscope to check for cancer cells.
  • Low-dose spiral CT scan (LDCT scan): A procedure that uses low-dose radiation to make a series of very detailed pictures of areas inside the body. It uses an x-ray machine that scans the body in a spiral path. The pictures are made by a computer linked to the x-ray machine. This procedure is also called a low-dose helical CT scan.

Screening with low-dose spiral CT scans has been shown to decrease the risk of dying from lung cancer in heavy smokers.

A lung cancer screening trial studied people aged 55 years to 74 years who had smoked at least 1 pack of cigarettes per day for 30 years or more. Heavy smokers who had quit smoking within the past 15 years were also studied. The trial used chest x-rays or low-dose spiral CT scans (LDCT) scans to check for signs of lung cancer.

LDCT scans were better than chest x-rays at finding early-stage lung cancer. Screening with LDCT also decreased the risk of dying from lung cancer in current and former heavy smokers.

Guide is available for patients and doctors to learn more about the benefits and harms of low-dose helical CT screening for lung cancer.

Screening with chest x-rays or sputum cytology does not decrease the risk of dying from lung cancer.

Chest x-ray and sputum cytology are two screening tests that have been used to check for signs of lung cancer. Screening with chest x-ray, sputum cytology, or both of these tests does not decrease the risk of dying from lung cancer.

The authors of Advances in oncologic imaging found out that for pre-treatment staging and post treatment follow-up of lung cancer patients mainly involves CT (preferably contrast enhanced, FDG PET and PET/CT. “Integrated PET/CT has been found to be more accurate than PET alone, CT alone, or visual correlation of PET and CT for staging NSCLC (Non-small-cell lung carcinoma).59 “

The standard treatment of choice for localized disease remains surgical resection with or without chemo-radiation therapy (stage dependant). “The current recommendations for routine follow-up after complete resection of NSCLC are as follows: for 2 years following surgery a contrast-enhanced chest CT scan every 4 to 6 months and then yearly non-contrast chest CT scans.62 Detection of recurrence on CT is the primary goal in the initial years, and therefore, optimally, a contrast-enhanced scan should be obtained to evaluate the mediastinum. In subsequent years, when identifying an early second primary lung cancer becomes of more clinical importance, a non-contrast CT chest scan suffices to evaluate the lung parenchyma.

CT (A) of 78-year-old male who was status post–left lobe lobectomy and left upper lobe wedge resection shows recurrent nodule at the surgical resection site. Fused PET/CT (B) demonstrates increased [18F]FDG uptake in the corresponding nodule at the surgical resection site consistent with recurrent tumor.

CT (A) of 78-year-old male who was status post–left lobe lobectomy and left upper lobe wedge resection shows recurrent nodule at the surgical resection site. Fused PET/CT (B) demonstrates increased [18F]FDG uptake in the corresponding nodule at the surgical resection site consistent with recurrent tumor.

In patients undergoing chemotherapies: “ [18F]FDG PET response correlates with histologic response.63 [18F]FDG PET scan data can provide an early readout of response to chemotherapy in patients with advanced-stage lung cancer.64

In patients treated by recently developed “Targeted Therapies” such as Radiofrequency ablation (RFA) the authors found out that PET/CT is the preferred imaging modality for post treatment follow-up.

“ Most patients treated with pulmonary ablation will have had a pre-procedure CT or a fusion PET/CT scan, which allows more precise anatomic localization of abnormalities seen on PET. Generally, either CT or PET/CT is performed within a few weeks of the procedure to provide a new baseline to which future images can be compared to assess for changes in size, degree of enhancement or [18F]FDG avidity.67

CT (A) demonstrates new left upper lobe mass representing new primary NSCLC in a patient who had a status post–right pneumonectomy for a prior NSCLC. CT (B) obtained in the same patient 2 weeks after radiofrequency ablation (RFA) demonstrates the postablation density in the left upper lobe. Fused PET/CT (C) obtained 4 months after RFA demonstrates mild [18F]FDG uptake at RFA site in the left upper lobe consistent with posttreatment inflammation. Fused PET/CT (D) obtained 7 months after RFA demonstrates new focal [18F]FDG uptake at post-RFA-opacity consistent with recurrent tumor.

CT (A) demonstrates new left upper lobe mass representing new primary NSCLC in a patient who had a status post–right pneumonectomy for a prior NSCLC. CT (B) obtained in the same patient 2 weeks after radiofrequency ablation (RFA) demonstrates the postablation density in the left upper lobe. Fused PET/CT (C) obtained 4 months after RFA demonstrates mild [18F]FDG uptake at RFA site in the left upper lobe consistent with posttreatment inflammation. Fused PET/CT (D) obtained 7 months after RFA demonstrates new focal [18F]FDG uptake at post-RFA-opacity consistent with recurrent tumor.

Prostate Cancer Imaging

To be followed…

Other research papers related to the management of Lung cancer were published on this Scientific Web site:

Diagnosing lung cancer in exhaled breath using gold nanoparticles

Lung Cancer (NSCLC), drug administration and nanotechnology

Non-small Cell Lung Cancer drugs – where does the Future lie?

Comprehensive Genomic Characterization of Squamous Cell Lung Cancers

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Author and curator: Ritu Saxena, Ph.D.

This post attempts to integrate three posts and to embed all comments made to all three papers, allowing the reader a critically thought compilation of evidence-based medicine and scientific discourse.

Dr. Dror Nir authored a post on October 16th titled “Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?” The article attracted over 20 comments from readers including researchers and oncologists debating the following issues:

  • imaging technologies in cancer
  • tumor size, and
  • tumor response to treatment.

The debate lead to several new posts authored by:

This post is a compilation of the views of authors representing different specialties including research and medicine. In medicine: Pathology, Oncology Surgery and Medical Imaging, are represented.

Dr. Nir’s post talked about an advanced technique developed by the researchers at Sunnybrook Health Sciences Centre, University of Toronto, Canada for cancer lesions’ detection and image-guided cancer treatment in the specific Region of Interest (ROI). The group was successfully able to show the feasibility and safety of magnetic resonance imaging (MRI) – controlled transurethral ultrasound therapy for prostate cancer in eight patients.

The dilemma of defining the Region of Interest for imaging-based therapy

Dr. Bernstein, one of the authors at Pharmaceuticalintelligence.com, a Fellow of the American College of Pathology, reiterated the objective of the study stating that “Their study’s objective was to prove that using real-time MRI guidance of HIFU treatment is possible and it guarantees that the location of ablated tissue indeed corresponds to the locations planned for treatment.” He expressed his opinion about the study by bringing into focus a very important issue i.e., given the fact that the part surrounding the cancer tissue is in the transition state, challenge in defining a ROI that could be approached by imaging-based therapy. Regarding the study discussed, he states – “This is a method demonstration, but not a proof of concept by any means.  It adds to the cacophany of approaches, and in a much larger study would prove to be beneficial in treatment, but not a cure for serious prostate cancer because it is unlikely that it can get beyond the margin, and also because there is overtreatment at the cutoff of PSA at 4.0. I think that the pathologist has to see the tissue, and the standard in pathology now is for any result that is cancer, two pathologists or a group sitting together should see it. It’s not an easy diagnosis.”

“The crux of the matter in terms of capability is that the cancer tissue, adjacent tissue, and the fibrous matrix are all in transition to the cancerous state. It is taught to resect leaving “free margin”, which is better aesthetically, and has had success in breast surgery. The dilemma is that the patient may return, but how soon?” concludes Dr. Larry.

Dr. Nir responded, “The philosophy behind lumpectomy is preserving quality of life. It was Prof. Veronesi (IEO) who introduced this method 30 years ago noticing that in the majority of cases; the patient will die from something else before presenting recurrence of breast cancer. It is well established that when the resection margins are declared by a pathologist (as good as he/she could be) as “free of cancer”, the probability of recurrence is much lower than otherwise. He explains further, “The worst enemy of finding solutions is doing nothing while using the excuse of looking for the “ultimate solution.” Personally, I believe in combining methods and improving clinical assessment based on information fusion. Being able to predict, and then timely track the response to treatment is a major issue that affects survival and costs!

In this discussion my view is expressed, below.

  • The paper that discusses imaging technique had the objective of finding out whether real-time MRI guidance of treatment was even possible and if yes, whether the treatment could be performed in accurate location of the ROI? The data reveals they were pretty successful in accomplishing their objective and of course that gives hope to the imaging-based targeted therapies.
  • Whether the ROI is defined properly and if it accounts for the real tumor cure, is a different question. Role of pathologists and the histological analysis and what they bring to the table cannot be ruled out, and the absence of a defined line between the tumor and the stromal region in the vicinity is well documented. However, that cannot rule out the value and scope of imaging-based detection and targeted therapy. After all, it is seminal in guiding minimally invasive surgery.
  • As another arm of personalized medicine-based cure for cancer, molecular biologists at MD Anderson have suggested molecular and genetic profiling of the tumor to determine genetic aberrations on the basis of which matched-therapy could be recommended to patients.
  • When phase I trial was conducted, the results were encouraging and the survival rate was better in matched-therapy patients compared to unmatched patients. Therefore, every time there is more to consider when treating a cancer patient and who knows a combination of views of oncologists, pathologists, molecular biologists, geneticists, surgeons would device improvised protocols for diagnosis and treatment. It is always going to be complicated and generalizations would never give an answer. Smart interpretations of therapies – imaging-based or others would always be required!

To read additional comments, including those from Dr. Williams, Dr. Lev-Ari, refers to:

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention? Author and Reporter: Dror Nir, Ph.D.

Dr. Lev-Ari in her paper linked three fields that bear weight in the determination of Tumor Response to Therapy:

  • Personalized Medicine
  • Cancer Cell Biology, and
  • Minimally Invasive Surgery (MIS)

Her objectives were to address research methodology, the heterogeneity innate to Cancer Cell Biology and Treatment choice in the Operating Room — all are related to the topic at hand: How to deliver optimal care with least invasive intervention course.

Any attempt aimed at approaching this desirable result, called Personalized Medicine,  involves engagement in three strategies:

  • prediction of Patient’s reaction to Drug induction
  • design of Clinical Trials to validate drug efficacy on small subset of patients predicted to react favorable to drug regimen, increasing validity and reliability
  • Genetical identification of patients at no need to have a drug administered if non sensitivity to the drug has been predicted

These method are to be applied to a list of 56 leading Cancer types.

While the executive task of the clinician remains to assess the differentiation in Tumor Response to Treatment, pursuit of  individualized histopathology, as well as tumor molecular, genetic and functional characteristics has to take into consideration the “total” individual patients’ characteristics: age, co-morbidities, secondary risks and allergies to drugs.

In Dr. Lev-Ari’s paper Minimally Invasive Treatment (MIT) is compared with Minimally Invasive Surgery (MIS) applied for tumor resection.  In many cases MIS is not the right surgical decision, yet, it is applied for a corollary of patient-centered care considerations. At present, facing the unknown of the future behavior of the tumor as its response to therapeutics bearing uncertainty related to therapy outcomes.

Forget me not – says the ‘Stroma’

Dr. Brücher, the author of review on tumor response criteria, expressed his views on the topic. He remembers that 10 years ago, every cancer researcher stated – “look at the tumor cells only – forget the stroma”. However, the times have changed, “now, everyone knows that it is a system we are looking at, and viewing and analyzing only tumor cells is really not enough.”

He went on to state “if we would be honest, we would have to declare that all data, which had been produced 8-13 years ago, dealing with laser capture microdissection, would need a rescrutinization, because the influence of the stroma was ‘forgotten’.”

He added, “the surgeon looks at the ‘free margin’ in a kind of reductionable model, the pathologist is more the control instance. I personally see the pathologist as ‘the control instance’ of surgical quality. Therefore, not the wish of the surgeon is important, the objective way of looking into problems or challenges. Can a pathologist always state if a R0-resection had been performed?”

What is the real RO-resection?

There have been many surrogate marker analysis, says Dr. Brücher, and that a substantially well thought through structured analysis has never been done: mm by mm and afterwards analyzing that by a ROC analysis. For information on genetic markers on cancer, refer to the following post by Dr. Lev-Ari’s: Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

He also stated that there is no gold standard to compare the statistical ROC analysis to. Often it is just declared and stated but it is still not clear what the real RO-resection is?

He added, “in some organs it is very difficult and we all (surgeons, pathologists, clinicians) that we always get to the limit, if we try interpreting the R-classification within the 3rd dimension.”

Dr. Brücher explains regarding resectability classification, “If lymph nodes are negative it does not mean, lymph nodes are really negative. For example, up to 38% upper GI cancers have histological negative lymph nodes, but immunohistochemical positive lymph nodes. And, Stojadinovic et al have also shown similar observations at el in colorectal cancer. So the 4th dimension of cancer – the lymph nodes / the lymphatic vessel invasion are much more important than just a TNM classification, which unfortunately does often not reflect real tumor biology.”

The discussion regarding the transition state of the tumor surrounding tissue and the ‘free margin’ led to a bigger issue, the heterogeneity of tumors.

Dr. Bernstein quoted a few lines from the review article titled “Tumor response criteria: are they appropriate?, authored by Dr Björn LDM Brücher et al published in Future Oncology in 2012.

  • Tumor heterogeneity is a ubiquitous phemomenon. In particular, there are important differences among the various types of gastrointestinal (GI) cancers in terms of tumor biology, treatment response and prognosis.
  • This forms the principal basis for targeted therapy directed by tumor-specific testing at either the gene or protein level. Despite rapid advances in our understanding of targeted therapy for GI cancers, the impact on cancer survival has been marginal.
  • Can tumor response to therapy be predicted, thereby improving the selection of patients for cancer treatment?
  • In 2000, the NCI with the European Association for Research and Treatment of Cancer, proposed a replacement of 2D measurement with a decrease in the largest tumor diameter by 30% in one dimension. Tumor response as defined would translate into a 50% decrease for a spherical lesion
  • We must rethink how we may better determine treatment response in a reliable, reproducible way that is aimed at individualizing the therapy of cancer patients.
  • We must change the tools we use to assess tumor response. The new modality should be based on empirical evidence that translates into relevant and meaningful clinical outcome data.
  • This becomes a conundrum of sorts in an era of ‘minimally invasive treatment’.
  • Integrated multidisciplinary panel of international experts – not sure that that will do it.

Dr. Bernstein followed up by authoring a separate post on tumor response. His views on tumor response criteria have been quoted in the following paragraphs:

Can tumor response to therapy be predicted?

The goal is not just complete response. Histopathological response seems to be related post-treatment histopathological assessment but it is not free from the challenge of accurately determining treatment response, as this method cannot delineate whether or not there are residual cancer cells. Functional imaging to assess metabolic response by 18-fluorodeoxyglucose PET also has its limits, as the results are impacted significantly by several variables:

• tumor type
• sizing
• doubling time
• anaplasia?
• extent of tumor necrosis
• type of antitumor therapy and the time when response was determined.

The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ characteristics, a greater challenge in an era of ‘minimally invasive treatment’.

This listing suggests that for every cancer the following data has to be collected (except doubling time). If there were five variables, the classification based on these alone would calculate to be very sizable based on Eugene Rypka’s feature extraction and classification.

But looking forward, time to remission and disease free survival are additionally important. Treatment for cure is not the endpoint, but the best that can be done is to extend the time of survival to a realistic long term goal and retain a quality of life.

For detailed discussion on the topic of tumor response and comments refer to the following posts:

What can we expect of tumor therapeutic response?

Author: Larry H. Bernstein, MD, FCAP

Judging ‘Tumor response’-there is more food for thought

Reporter: Ritu Saxena, Ph.D.

Additional Sources:

Research articles:

Brücher BLDM  et al. Tumor response criteria: are they appropriate? Future Oncol. August Vol. 8, No. 8, Pages 903-906 (2012).

Brücher BLDM, Piso P, Verwaal V et al. Peritoneal carcinomatosis: overview and basics. Cancer Invest.30(3),209–224 (2012).


Brücher BLDM, Swisher S, Königsrainer A et al. Response to preoperative therapy in upper gastrointestinal cancers. Ann. Surg. Oncol.16(4),878–886 (2009).


Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer47(1),207–214 (1981).


Therasse P, Arbuck SG, Eisenhauer EA et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J. Natl Cancer Inst.92(3),205–216 (2000).


Brücher BLDM, Becker K, Lordick F et al. The clinical impact of histopathological response assessment by residual tumor cell quantification in esophageal squamous cell carcinomas. Cancer106(10),2119–2127 (2006).

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Reporter: Aviva Lev-Ari, PhD, RN

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Former FDA Chief on Modernizing Drug and Device Approvals

Introduction

John C. Reed, MD, PhD: Hello, and welcome to Medscape One-on-One. I’m Dr. John Reed, Professor and CEO of Sanford-Burnham Medical Research Institute. Joining me today at the Celebration of Science Conference at the National Institutes of Health (NIH) is Andrew C. von Eschenbach, President of Samaritan Health Initiatives, former Commissioner of the US Food and Drug Administration (FDA), and former Director of the National Cancer Institute (NCI). Welcome.

Andrew C. von Eschenbach, MD: Great to be with you.

The Collaboration of Government, Industry, and Academia

Dr. Reed: At this conference, you spoke about the interaction of government, industry, and academic centers. The relationship among these 3 entities is often challenging, but also crucial to the advancement of science. Can you give us a couple of examples how these partnerships are working well, and also some ideas of how we can improve collaboration among these groups?

Dr. von Eschenbach: I think we both appreciate that caring for patients, solving their problems, and curing their diseases is a team sport. We all have a part and a role to play in this. Government, academia, industry — we need to come together to figure out how to create these comprehensive systematic solutions to problems.

It starts with discovery. Academic centers and researchers like you are really revealing the mysteries of the underlying mechanisms of these diseases, and are making it possible for industry to start creating and developing solutions and interventions that can target those mechanisms and alter the outcome of those diseases — whether it’s eliminating suffering and death due to cancer or solving the problem of Alzheimer disease.

Government has to play a critical role in catalyzing and fostering that collaboration. A great example of where I saw this occurred was when I was at the NCI. When I looked at the government’s investment following the National Cancer Act in 1971, which enabled the NCI to create cancer centers, I could see 65 cancer centers all over this country. But what I also saw was that around these centers, there were these clusters of state-of-the-art care. There were these clusters of emerging biotechnology and the pharmaceutical industry coming together and creating an ecosystem that would be able to go from discovery and development to delivery.

Another great example is the state of Georgia, which did not have a cancer center at that time. But the state took money from the tobacco settlement, put it into a private endowment, and went about the business of creating the Winship Cancer Institute at Emory University in Atlanta. That attracted a united effort, including government funding from our cancer nanotechnology initiative. It brought in other academic institutions, such as Georgia Tech, and even private philanthropy from such institutions as Home Depot, for example.

We can make this work. We can bring the parts and pieces together as a team to use the brilliance of the science that you, Dr. Reed, have been doing, and others here at NIH and in academic institutions all around the world have been doing, and recognize that science is the means. The end is that we solve people’s problems, and we do it together.

Translating Life-Science Advancements Into Disease Cures and Prevention

Dr. Reed: That’s a great example of the catalytic role that government funding can play in economic development as well as advancing healthcare. You gave the example of Georgia. We’ve seen the same thing happen in the state of Florida, where tobacco settlement monies were used to create a seed investment. That spawned additional development of hospitals, and a government investment that turned a couple hundred jobs into tens of thousands of jobs for the state.

Let me change subjects. You were previously involved in laboratory and clinical research. Can you talk about how advancements in the field of life sciences are paving the way for possible cures and preventions for such diseases as prostate cancer? You used to be an urologist, and prostate cancer is a disease you worked on a lot. There are also neurodegenerative diseases, such as Alzheimer’s disease, which we’re all worried about. What are you excited about in these areas?

Dr. von Eschenbach: If I get a chance to talk to students and they ask what they should do in life, I tell them this is the most exciting time to go into medicine. And we are in the midst of the most profound transformation to ever occur in history in medicine going all the way back to Hippocrates. Throughout the history of medicine, physicians such as myself have been practicing a model based on our observations of the manifestations of disease.

I feel a lump in a woman’s breast. I see a shadow on a chest x-ray. I’m seeing the manifestations of an underlying disease, but it tells me nothing about what to do about it. All of our therapies and all of the things that we do about those observations have been empiric. Today we’re going from observing manifestations to actually understanding the mechanisms of the disease. We’re beginning to recognize the genes, the molecules, and the cellular processes that are responsible for and driving those disease processes. Once we have that knowledge of an underlying mechanism, it intuitively leads us to what the right solution is, to intervene in that mechanism and alter the outcome of that process.

Cancer, for example, is a disease process. It begins with our susceptibility, and that process ends with unfortunate suffering and death. But there are all these steps in between, and you have contributed personally to understanding some of those fundamental mechanisms.

Now physicians can be strategic. We can intervene in that process in a strategic way. Call it “personalized medicine” if you will. Get the right intervention for the right reason to the right patient at the right time, and you can prevent that process from happening. You can detect disease very early. You can eliminate it, or you can modulate and change its behavior and its outcome. You can alter the slope of the curve and allow patients to live the rest of their life never threatened by it.

This is the new frontier for medicine and for physicians. We will enter into this frontier with tools that we never had before. We can visualize biology with new imaging. We now have new therapies that are becoming available to us that will alter and change disease in radical ways. No longer is it just for cancer, surgery, chemotherapy, and radiation. The future for physicians is the most exciting, and yet it is a future that we have to grasp.

Dr. Reed: As a former director of the NCI, do you see a day where cancer patients will be treated not on the basis of whether their cancer arose in the lung or the colon, or the prostate, but on the basis of the underlying genetics of the cancer? By matching the mutations to the medicine — is that how you think it will look in the future?

Dr. von Eschenbach: Absolutely. We’ve been immersed in categorizing diseases on the basis of what we could observe, what we could see. We call something “breast cancer” because we feel a lump in a woman’s breast, or we call something “lung cancer” because it’s in the lung.

But now, as we’re looking at these underlying mechanisms, guess what? We’re finding out that some subsets of lung cancer look exactly like another kind of cancer. And therefore, from that point of view, they have the same treatment. You can use a drug for chronic myelogenous leukemia and it works exceedingly well in gastrointestinal stroma, tumors of the stomach, as well. Even more important, we understand a mechanism for cancer based on angiogenesis in the abnormal growth of blood vessels. We develop a drug for that to retard or slow down the cancer, and it turns out it’s one of the most effective drugs for macular degeneration of the eye.

For physicians and for those of us who are practicing medicine, we’re going to see disease through a different prism. When we see it through that different prism, we’re going to be able to see new ways of conquering many diseases. Cancer is just the lead here. But we’re going to be seeing the same kinds of dramatic changes and breakthroughs in neurocognitive diseases, diabetes, and cardiovascular disease along the way.

We’re also seeing it disseminate very rapidly. It’s no longer centers and then community practice. We’re seeing the opportunity now with new technologies even outside of medicine. We now have information technologies that will help us see a full continuum for every patient. It will mean absolutely state-of-the-art care by every physician, regardless of where you’re located.

Speeding Drug and Device Approvals

Dr. Reed: For these exciting new therapies to come to reality, they have to be approved by the FDA. You are a former commission of the FDA. Some clinicians are frustrated with the time it takes to get new medical devices and drugs approved by the FDA. You’ve been more sympathetic to the agency and the lack of resources it has to help it through a mighty tough job.

What do you think we should be doing — either the American people or the federal government — to better support the FDA and its efforts to get much needed treatments to patients more quickly?

Dr. von Eschenbach: The importance of the FDA can’t be overemphasized. It’s absolutely critical to this entire process of progress that I’ve been talking about. Let’s go back to our model of discovery, development, and delivery enterprise in medicine. It’s no longer linear — from the bench to the bedside. It’s actually circular.

What we’re seeing in terms of physicians delivering care is that there are tools that are now available to help us better understand the human biology of disease. When we treat disease or intervene in a human being, through functional imaging or whatever, it is actually a discovery platform making this process circular.

The success of the process of discovery, development, and delivery is going to be based on speed. How quickly can we do that? How quickly can we keep cycling that revolution of knowledge and intervention? At the hub of that wheel is the FDA. It can be the brake, or it can be the accelerator. It clearly is critical to how rapidly we’re going to be able to move from your brilliant discovery in the laboratory to the point where we’ve actually made a difference in a patient’s life.

Regulation has to be modernized. It’s a matter of making sure that the agency has the capacity and the capability. Funding resources are critically important. But what’s more important is we need a new way of doing business. We can no longer use a regulatory process and framework that served us well in the 20th century, but is woefully inadequate for this new reality in the 21st century.

For physicians, especially physicians out in the community, a simple piece of that equation is that we will play a critically important role in the perspective of clinical trials. The way we approve drugs now in phase 1, phase 2, and phase 3 of clinical trials is not commensurate with the mechanistic view of disease. So we’re going to change the FDA. And in doing so, we’re going to fulfill the promise for people.

Dr. Reed: We’re excited to hear that. At the Celebration of Science Conference, we heard a representative from the FDA, Janet Woodcock, talking about that very issue of having more adaptable clinical trial designs. That is an opportunity for us to increase the speed of learning and turnover with real-time feedback from imaging and biomarkers, which allows us to see whether the medicine is working.

Dr. von Eschenbach: The FDA has to practice regulation in the way that physicians practice medicine. Every patient, first of all, wants personalized medicine. They all want to know what’s right and what’s best for me. Doctor, what should I do? We now have the tools to become much more precise about that.

But every patient, also in a way, becomes their own experiment. We apply a therapy, and a rational physician makes a very sophisticated educated guess but never knows whether it’s actually going to work in that one patient. We monitor, and when we observe outcomes, we change. We alter the treatment until we get to that desired outcome.

Why don’t we approve drugs that way? Why don’t we use adaptive trial designs so that we learn as we go, and do that routinely rather than using this stepwise fashion that we’ve been locked into? We have to be open to change.

Promising New Methods of Treating Disease

Dr. Reed: You were once a practicing urologist, and you went on to become director of the NCI. In recent years, you’ve been active in a number of organizations dedicated to researching and developing new methods of treating a variety of diseases. Tell us one of the things that you’re most looking forward to.

Dr. von Eschenbach: Cancer had the opportunity to be at the forefront and the vanguard of this radical transformation. In 1970, cancer was a disease that was devastating us with regard to the human toll of suffering and death, and the economic consequences. At that time, the science of cancer was just beginning to become apparent in a way that we could begin to understand the cancer cell and the living normal cell at its very fundamental genetic and molecular level. That created this enormous cascade of progress.

What we’re seeing now is that the lessons learned and the progress made in cancer can now be disseminated to all the other diseases. For example, Alzheimer disease and neurocognitive and neurologic disorders are probably today where cancer was in 1970. Those diseases have a huge, devastating impact on human life and will bankrupt us in terms of the overall cost of healthcare and the cost of caring for patients affected by these diseases. But science is now emerging to help us better understand these diseases.

It’s a privilege to have lived the life of a cancer physician and researcher, and now I can transpose that experience to ask how we can do that for all diseases. That’s my passion today; it’s not just about cancer. It’s no longer cancer-centric, but it is cancer-led. Everyone will profit from the tremendous progress that researchers are making in the science that we will translate into cures for people.

Dr. Reed: Dr. von Eschenbach, thank you for joining us today. For Medscape One-on-One, I’m John Reed.

http://www.medscape.com/viewarticle/771952?src=ptalk

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Reporter: Venkat Karra, Ph.D,

Recently studies on structural abnormalities of chromosomes (Mosaicism) were conducted by two consortia, one led by scientists at the National Cancer Institute (NCI), and one by Gene Environment Association Studies (GENEVA). This study was sponsored by the National Human Genome Research Institute (NHGRI).  These studies have found that mosaicism can be detected in a small fraction of people without a prior history of cancer. Mosaicism results from a DNA alteration that is present in some of the body’s cells but not in others. A person with mosaicism has a mixture of normal and mutated cells. “These two studies provide large population-based evidence that genetic mosaicism increases with age and could be a risk factor for cancer” which may mean that detection of genetic mosaicism could be an early marker for detecting cancer, or perhaps other chronic diseases,” said Stephen Chanock, M.D., co-author and chief, Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, NCI.

Scientists began observing an unexpected frequency of structural abnormalities in chromosomes during quality control checks of data from genome-wide association studies (GWAS) conducted in the GENEVA consortium and similar programs at NCI. These studies involve comparing hundreds of thousands of common differences across individual patients’ DNA to see if any of those variants are associated with a known trait, such as cancer. At first, these abnormalities were thought to be errors or outcomes of laboratory procedures. But they were found consistently at a low frequency, so the scientists wondered with what frequency these structural abnormalities occurred in the general population.

The NCI-led study observed that genetic mosaic abnormalities were more frequent in individuals with solid tumors (0.97 percent vs. 0.74 percent in cancer-free individuals). The NCI study also observed mosaic chromosomal abnormalities in slightly less than 1 percent of the study participants, but noted that the frequency of detectable genetic mosaicism increased with age. This was consistent with GENEVA results that found genetic mosaicism increased in those over the age of 50.

In both studies, scientists observed an increase in the detection of genetic mosaicism in patients with hematological cancers (leukemia, lymphoma and myeloma), for which DNA was collected at least one year prior to diagnosis, compared to cancer-free individuals. Results from the NCI study showed that risk of leukemia was also substantially higher among people with these chromosomal alterations while the GENEVA study showed that the risk of acquiring a hematological cancer diagnosis was 10 times higher for people who had mosaic chromosomal abnormalities. The results of both studies suggest that mosaicism, observed in older people, may be an asymptomatic condition — not often causing overt illness — that may predispose them to hematological cancer. However, GENEVA and NCI scientists stress that the event numbers analyzed are small, and additional studies are needed across a broader diversity of populations to establish the clinical significance of these findings.

NIH scientists say these findings will have important implications for the design and analysis of molecular studies of cancer, as well as ongoing studies looking at the characterization of cancer genomes, such as NIH’s The Cancer Genome Atlas and the International Cancer Genome Consortium.

NIH scientists recommended that additional analyses be conducted in groups of currently healthy people so that investigators may follow them over time for health outcomes.

The results of the studies were published online May 6, 2012, in Nature Genetics.

Read more….

Source:

http://www.genome.gov/27548594

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