Biopathology
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Biopathology
The study of tissular and tumoral biomarkers
Curated by René Laennec
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Germline EGFR T790M mutation results in a rare and unique lung cancer hereditary syndrome associated with a 31% risk

Germline EGFR T790M mutation results in a rare and unique lung cancer hereditary syndrome associated with a 31% risk | Biopathology | Scoop.it

Two studies found that germline EGFR T790M mutation results in a rare and unique lung cancer hereditary syndrome associated with an estimated 31% risk for the disease in never-smokers. Lead author Adi Gazdar, MD, of the Department of Pathology, UT Southwestern Medical Center, Dallas, TX, and colleagues studied a family with germline EGFR T790M mutations over five generations (14 individuals) and combined their observations with data obtained from a literature search (15 individuals). They found that the mutation occurred in approximately 1% of NSCLCs and in less than one in 7,500 subjects without lung cancer.


Female never-smokers were overrepresented in the family cohort. Among 13 patients for whom gender and smoking status were known, nine were female never-smokers, two were male never-smokers, and two were ever-smokers (one male and one female).

 

“The risk of lung cancer development in never-smoking carriers is greater than the risk of heavy smokers with or without the mutation,” says Dr. Gazdar, who is an IASLC member. “Unaffected carriers with this mutation are at increased risk for the development of lung cancer irrespective of their smoking status and should be followed by increased surveillance, including low-dose computed tomography,” he adds.

 

The cancers associated with germline EGFR T790M mutations share several similar features with lung cancers containing sporadic EGFR mutations, such as a predominance for adenocarcinoma histology, female gender, and never-smoking status. However, a difference with lung cancers having sporadic EGFR mutations is a predominance for white ethnicity (compared with East Asian). 

 

“Germline EGFR T790M mutations are present in approximately 50% of all patients with baseline EGFR T790M identified in their tumor specimens before treatment,” says Dr. Yu, also an IASLC member. “In our practice, we recommend that all patients with baseline  EGFR T790M identified in their lung tumor tissue be referred to clinical genetics to discuss EGFR T790M germline testing. Carriers of this mutation need to be prospectively studied to better understand the clinical implications of this germline mutation.

 

The presence of a germline EGFR T790M mutation also predicts for resistance to standard tyrosine kinase inhibitors (TKIs), which adds complexity to treatment. Until newer third- and fourth-generation TKIs designed to overcome T790M-mediated resistance become available, standard chemotherapy may be the preferred first-line therapy option in the absence of another known or suspected molecular target.


Via Dr. Stefan Gruenwald
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Visualization techniques for categorical analysis of social networks with multiple edge sets

Visualization techniques for categorical analysis of social networks with multiple edge sets | Biopathology | Scoop.it
Publication date: Source:Social Networks, Volume 37 Author(s): Tarik Crnovrsanin , Chris W. Muel...

Via João Greno Brogueira
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DNA Project Aims to Make Public a Company’s Data on Cancer Genes

DNA Project Aims to Make Public a Company’s Data on Cancer Genes | Biopathology | Scoop.it
Researchers are asking cancer clinics to hand over Myriad Genetics’ test results so they can more easily interpret the risk posed by mutations of two breast cancer genes.
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ICGC to sequence 25 000 cancer genomes

ICGC to sequence 25 000 cancer genomes | Biopathology | Scoop.it
The International Cancer Genome Consortium (ICGC) is to decode the genomes from 25 000 cancer samples and create a resource of freely available data that will help cancer researchers around the world.

 

"The International Cancer Genome Consortium initiative will profoundly alter our understanding of the development of human cancer, across the spectrum of tumour types," said Sir Paul Nurse, cancer scientist and 2001 Nobel Laureate for Physiology or Medicine.


Via Dr. Stefan Gruenwald
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Not an easy task: Finding cancer-specific genomics fingerprints

Not an easy task: Finding cancer-specific genomics fingerprints | Biopathology | Scoop.it

Researchers from the Wellcome Trust Sanger Institute's cancer genome project have developed a computer model to identify the fingerprints of DNA-damaging processes that drive cancer development. Armed with these signatures, scientists will be able to search for the chemicals, biological pathways and environmental agents responsible.

 

"For a long time we have known that mutational signatures exist in cancer," says Dr Peter Campbell, Head of the cancer genome project and co-senior author of the paper. "For example UV light and tobacco smoke both produce very specific signatures in a person's genome. Using our computational framework, we expect to uncover and identify further mutational signatures that are diagnostic for specific DNA-damaging processes, shedding greater light on how cancer develops."

 

The computer model will help to overcome a fundamental problem in studying cancer genomes: that the DNA contains not only the mutations that have contributed to cancer development, but also an entire lifetime's worth of other mutations that have also been acquired. These mutations are layered on top of each other and trying to unpick the individual mutations, when they appeared, and the processes that caused them is a daunting task.

 

"The problem we have solved can be compared to the well-known cocktail party problem," explains Ludmil Alexandrov, first author of the paper from Sanger Institute. "At a party there are lots of people talking simultaneously and, if you place microphones all over the room, each one will record a mixture of all the conversations. To understand what is going on you need to be able to separate out the individual discussions. The same is true in cancer genomics. We have catalogues of mutations from cancer genomes and each catalogue contains the signatures of all the mutational processes that have acted on that patient's genome since birth. Our model allows us to identify the signatures produced by different mutation-causing processes within these catalogues."

 

To identify individual sets of mutations produced by a particular DNA-damaging agent, the cancer genome project at the Sanger Institute simulated cancer genomes and developed a technique to search for these mutational signatures. This approach proved to be very successful. The research team then explored the genomes of 21 breast cancer patients and identified five mutational signatures of cancer-causing processes in the real world.


Via Dr. Stefan Gruenwald
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Large-scale genotyping identifies 41 new loci associated with breast cancer risk : Nature Genetics : Nature Publishing Group

Large-scale genotyping identifies 41 new loci associated with breast cancer risk : Nature Genetics : Nature Publishing Group | Biopathology | Scoop.it
Douglas Easton, Per Hall and colleagues report meta-analyses of genome-wide association studies for breast cancer, including 10,052 cases and 12,575 controls, followed by genotyping using the iCOGS array in an additional 52,675 cases and 49,436...

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Susan Zager's curator insight, May 6, 2013 7:03 AM

It's always important in research to do this type of analysis to help discover ways for breast cancer prevention. According to this study, "Incorporating these loci into risk models should substantially improve disease prediction, even if not all loci can be identified individually. Moreover, fine-scale mapping of the identified regions may uncover more of the missing heritability, either through identifying a more strongly associated variant (as found for the CCND1 locus; see French et al.61) or by identifying additional signals (exemplified for the TERT region in Bojesen et al.62). Genetic profiling using these common susceptibility loci in combination with rarer high-risk loci and other risk factors may provide a rational basis for targeted breast cancer prevention."

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Proteins mark metastasizing breast cancer cells - Oncology Nurse Advisor

Proteins mark metastasizing breast cancer cells Oncology Nurse Advisor But the biomarkers identified by Dario Marchetti, who is a pathologist at Baylor, and colleagues are present in CTCs that are EpCAM-negative, and as such, would not be detected...
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MEK inhibitors as a chemotherapeutic intervention in multiple myeloma - Nature.com

MEK inhibitors as a chemotherapeutic intervention in multiple myeloma - Nature.com | Biopathology | Scoop.it
MEK inhibitors as a chemotherapeutic intervention in multiple myeloma Nature.com Correspondence: Dr A Spencer, Myeloma Research Group, Australian Centre for Blood Diseases and Division of Blood Cancers, Level 1 AMREP, The Alfred Hospital, 55...
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bioTheranostics' Prostate Cancer Index Predicts Risk for Prostate Cancer ... - EON: Enhanced Online News (press release)

bioTheranostics' Prostate Cancer Index Predicts Risk for Prostate Cancer ... - EON: Enhanced Online News (press release) | Biopathology | Scoop.it
bioTheranostics' Prostate Cancer Index Predicts Risk for Prostate Cancer ...
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Wikipedia and Cancer Research UK to take cancer information to the next level

Cancer Research UK is working with Wikipedia to recruit its very own ‘Wikipedian in Residence'.

Via Ricard Robledo, Lionel Reichardt / le Pharmageek
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Prostate Cancer Test From Genomic Health Assesses Risks

Prostate Cancer Test From Genomic Health Assesses Risks | Biopathology | Scoop.it
The test, developed by Genomic Health, can help distinguish aggressive prostate cancer from less threatening ones, potentially saving many men from unneeded operations.
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New Computational Pipeline Analyzes Tumor Images, May Help Predict Response to Cancer Therapy

New Computational Pipeline Analyzes Tumor Images, May Help Predict Response to Cancer Therapy | Biopathology | Scoop.it

How’s this for big data: A whole-slide image of a tumor section can be ten billion pixels. There can be thousands of such images in the tumor cohorts maintained by The Cancer Genome Atlas project, which are collected from a large pool of patients.

 

The images are a potential treasure trove for the emerging field of precision medicine. Hidden in those billions of pixels is a story of how tumor cells organize themselves, the molecular networks that influence these structural traits, and what it all means for patients. Unfortunately, culling this information from numerous images is difficult. That’s because no two tumors are alike, and there are myriad technical variations in how samples are prepared.

 

This analysis could soon get much easier. Berkeley Lab scientists have developed an algorithm and a computational pipeline that combs through large sets of images and identifies tumor subtypes. It also identifies heterogeneity, or the extent to which a tumor comprises different organizational structures. The pipeline then uses clinical data to rank cellular signatures that are predictive of patient outcome. It also uses large-scale genomic data to identify molecular correlates of each subtype.

 

The resulting information will help scientists learn more about the genetic and molecular mechanisms that control tumor signatures. It will also shed light on whether tumor subtype can predict the effectiveness of therapies.

 

“Our goals are to identify morphometric and architectural traits that can be predictive of a therapy. We’d also like to learn about the molecular signatures that lead to architectural aberrations,” says Bahram Parvin of Berkeley Lab’s Life Sciences Division. The development of the core computational module and the pipeline were led by Hang Chang and Gerald Fontenay, respectively, in Parvin’s Lab in the Life Sciences Division.

 

The core computational module works by extracting each cell from an image, and then profiling properties of each cell such as size, shape, and organization. In this way, the telltale characteristics of a specific tumor subtype are gleaned from a large cohort of images.

 

As recently reported, the scientists validated their pipeline by applying it to 377 whole-slide images from 146 patients who have an aggressive brain cancer called Glioblastoma Multiforme. The pipeline identified several tumor subtypes based on a range of cellular profiles. It also determined whether each subtype is predictive of a patient’s response to alternative therapy. Although the pipeline was developed in a high-performance computer language, it is compute intensive and required extensive use of the Lawrencium cluster operated by Berkeley Lab’s IT Division.


Via Dr. Stefan Gruenwald
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World’s largest release of comprehensive human cancer genome data helps researchers to speed discoveries

World’s largest release of comprehensive human cancer genome data helps researchers to speed discoveries | Biopathology | Scoop.it

Whole genome data from hundreds of St. Jude Children's Research Hospital patients exceeds volume of all other sources combined.

 

To speed progress against cancer and other diseases, the St. Jude Children's Research Hospital – Washington University Pediatric Cancer Genome Project today announced the largest-ever release of comprehensive human cancer genome data for free access by the global scientific community. The amount of information released more than doubles the volume of high-coverage, whole genome data currently available from all human genome sources combined. This information is valuable not just to cancer researchers, but also to scientists studying almost any disease.

 

The 520 genome sequences released today are matched sets of normal and tumor tissue samples from 260 pediatric cancer patients. The Pediatric Cancer Genome Project is expected to sequence more than 1,200 genomes by year’s end. Each sample is sequenced at a quality control level known as 30-fold coverage, ensuring maximum accuracy. St. Jude researchers are analyzing the genomic sequences to determine the differences between each child’s normal and cancerous cells to pinpoint the causes of more than a half-dozen of the most deadly childhood cancers, an effort which has already produced a number of key discoveries reported in top scientific journals.


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Cancer Clues: Ready for More 10,000 Cancer Genomes Projects?

Cancer Clues: Ready for More 10,000 Cancer Genomes Projects? | Biopathology | Scoop.it

Cancer researchers who have spent the last 7 years compiling a catalog of mutations in patients' tumors are now talking about what they should do next. This week, researchers at the National Cancer Institute (NCI) unveiled a project on their wish list: a much broader survey of 10,000 tumors per cancer type that would aim to pin down very rare cancer genes.

 

Next year, NCI will wind up The Cancer Genome Atlas (TCGA), a huge project piloted in 2006 that is systematically searching tumors for genetic changes involved in cancer. More than 150 cancer researchers have divvied up the work of sequencing about 500 tumor samples for each of some 20 cancer types (10,000 samples in total) at a cost of more than $375 million. TCGA has verified known cancer genes and found new genetic changes driving some cancers; although the project has been criticized as too costly, many researchers think it has been worthwhile.

 

So what next? On Monday at a meeting of NCI's Board of Scientific Advisors (BSA), NCI cancer geneticists Louis Staudt and Stephen Chanock sketched out one idea that emerged from a recent TCGA workshop (starts at 116:00 on video). Staudt explained that because tumors are often riddled with mutations that aren't involved in cancer, it is difficult to pick out those that matter. Even some known cancer genes for lung adenocarcinoma, one of the most intensively studied cancers, haven't popped out in cancer genome surveys. To find rare cancer genes, researchers need to sequence many more samples, he said.


Via Dr. Stefan Gruenwald
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Prognostic RNA Markers Identified In A Common Form Of Breast Cancer

Prognostic RNA Markers Identified In A Common Form Of Breast Cancer | Biopathology | Scoop.it

"A Big-Data analysis that integrates three large sets of genomic data available through The Cancer Genome Atlas has identified 37 RNA molecules that might predict survival in patients with the most common form of breast cancer.

The study by researchers at the Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J. Solove Research Institute (OSUCCC - James) initially analyzed messenger RNA (mRNA) and microRNA expression, DNA methylation data and clinical findings for 466 patients with invasive ductal carcinoma, the most common type of breast cancer."


Via Susan Zager
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Susan Zager's curator insight, May 1, 2013 4:08 PM

These genes can be candidates for early blood detection.


"Key points related to the study's findings include:

  • The identified RNA signature might predict response to treatment, as well as being prognostic;
  • DNA methylation was used to confirm the association between mRNA expression and overall survival;
  • The signature includes mutations in PIK3CA and its pathway, indicating that the PIK3CA/AKT2/PTEN axis is an important and independent cofactor in prognosis;
  • The prognostic value of the integrated signature was highest in early stage I and II breast cancers, making this a potentially valuable biomarker signature in clinical practice."


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(ngTMA) increases the quality of biomarker studies - Journal of ...

Next-generation tissue microarrays (ngTMA) combine histological expertise with digital pathology and automated tissue microarraying. The aim of this study was to test the feasibility of ngTMA for the investigation of biomarkers within the tumor ...
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Study Results Show Prosigna(TM) Breast Cancer Prognostic Gene Signature ... - Wall Street Journal (press release)

Study Results Show Prosigna(TM) Breast Cancer Prognostic Gene Signature ... - Wall Street Journal (press release) | Biopathology | Scoop.it
Study Results Show Prosigna(TM) Breast Cancer Prognostic Gene Signature ...
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Study confirms everolimus can overcome trastuzumab resistance in HER-2 ... - Medical Xpress

Study confirms everolimus can overcome trastuzumab resistance in HER-2 ... - Medical Xpress | Biopathology | Scoop.it
Study confirms everolimus can overcome trastuzumab resistance in HER-2 ...
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