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Live Conference Coverage @Medcitynews Converge 2018 Philadelphia: Early Diagnosis Through Predictive Biomarkers, NonInvasive Testing

Posted in Alzheimer's Disease, Big Data, Big Data & Analytics, BioBanking, Biomarkers & Medical Diagnostics, Cancer and Current Therapeutics, Cancer Informatics, Cancer Screening, Diagnostics and Lab Tests, Meta-analysis of transcriptome data, Pharmaceutical Industry Competitive Intelligence, Pharmacotherapy and Cell Activity, Scientific & Biotech Conferences: Press Coverage, Transcriptomics, Uncategorized, tagged AD biomarkers, cancer biomarkers, clinical trial 2.0, innovations in cancer detection, multiple schlerosis, oncoproteomics, Predictive Cancer Biomarkers, Proteomics, Transcriptomics on July 11, 2018| Leave a Comment »

5:00 – 5:45 PM Early Diagnosis Through Predictive Biomarkers, NonInvasive Testing

Reporter: Stephen J. Williams, Ph.D.

 

Diagnosing cancer early is often the difference between survival and death. Hear from experts regarding the new and emerging technologies that form the next generation of cancer diagnostics.

Moderator: Heather Rose, Director of Licensing, Thomas Jefferson University
Speakers:
Bonnie Anderson, Chairman and CEO, Veracyte @BonnieAndDx
Kevin Hrusovsky, Founder and Chairman, Powering Precision Health @KevinHrusovsky

Bonnie Anderson and Veracyte produces genomic tests for thyroid and other cancer diagnosis.  Kevin Hrusovksy and Precision Health uses peer reviewed evidence based medicine to affect precision medicine decision.

Bonnie: aim to get a truth of diagnosis.  Getting tumor tissue is paramount as well as properly preserved tissue.  They use deep RNA sequencing  and machine learning  in their clinically approved tests.

Kevin: Serial biospace entrepreneur.  Two diseases, cancer and neurologic, have been diseases which have been hardest to get reproducible and validated biomarkers of early disease.  He concentrates on protein biomarkers.

Heather:  FDA has recently approved drugs for early disease intervention.  However the use of biomarkers can go beyond patient stratification in clinical trials.

Kevin: 15 approved drugs for MS but the markers are scans looking for brain atrophy which is too late of an endpoint.  So we need biomarkers of early disease progression.  We can use those early biomarkers of disease progression so pharma can target those early biomarkers and or use those early biomarkers of disease progression  for endpoint

Bonnie: exciting time in the early diagnostics field. She prefers transcriptomics to DNA based methods such as WES or WGS (whole exome or whole genome sequencing).  It was critical to show data on the cost savings imparted by their transcriptomic based thryoid cancer diagnostic test for payers to consider this test eligible for reimbursement.

Kevin: There has been 20 million  CAT scans for  cancer but it is estimated 90% of these scans led to misdiagnosis. Biomarker  development  has revolutionized diagnostics in this disease area.  They have developed a breakthrough panel of ten protein biomarkers in serum which he estimates may replace 5 million mammograms.

All panelists agreed on the importance of regulatory compliance and the focus of new research should be on early detection.  In addition they believe that Dr. Gotlieb’s appointment to the FDA is a positive for the biomarker development field, as Dr. Gotlieb understands the potential and importance of early detection and prevention of disease.  Kevin also felt Dr. Gotlieb understands the importance of incorporating biomarkers as endpoints in clinical trials.  Over 750 phase 1,2, and 3 clinical trials use biomarker endpoints but the pharma companies still need to prove the biomarkers clinical relevance to the FDA.They also agreed it would be helpful to involve advocacy groups in putting more pressure on the healthcare providers and policy makers on this importance of diagnostics as a preventative measure.

In addition, the discovery and use of biomarkers as disease endpoints has led to a resurgence of Alzheimer’s disease drug development by companies which have previously given up on these type of neurodegenerative diseases.

Kevin feels proteomics offers great advantages over DNA-based diagnostics, especially in cancer such as ovarian cancer, where a high degree of specificity for a diagnostic test is required to ascertain if a woman should undergo prophylactic oophorectomy.  He suggests that a new blood-based protein biomarker panel is being developed for early detection of some forms of ovarian cancer.

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Knowing the genetic vulnerability of bladder cancer for therapeutic intervention

Posted in Anticancer Resistance, Apoptosis, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Biological Networks, Biological Networks, Gene Regulation and Evolution, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Informatics, cancer metabolism, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell death pathways, Cell Processing System in Cell Therapy Process Development, Childhood cancer, Clinical Diagnostics, Clinical Genomics, Gene Regulation, Gene Therapy & Gene Editing Development, Genome Biology, Genomic Endocrinology, interventional oncology, Metabolic Immuno-Oncology, Metastasis Process, Microbiome and Responses to Cancer Therapy, mRNA Therapeutics, Mutagenesis, Personalized and Precision Medicine & Genomic Research, Population genetics, Population Health Management, Population Health Management, Genetics & Pharmaceutical, RNA Biology, RNA Biology, Cancer and Therapeutics, Signaling, tagged bladder, Cancer, classification, invasive, Ral, Ras, therapeutic on November 21, 2017| Leave a Comment »

Knowing the genetic vulnerability of bladder cancer for therapeutic intervention

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

A mutated gene called RAS gives rise to a signalling protein Ral which is involved in tumour growth in the bladder. Many researchers tried and failed to target and stop this wayward gene. Signalling proteins such as Ral usually shift between active and inactive states.

 

So, researchers next tried to stop Ral to get into active state. In inacvtive state Ral exposes a pocket which gets closed when active. After five years, the researchers found a small molecule dubbed BQU57 that can wedge itself into the pocket to prevent Ral from closing and becoming active. Now, BQU57 has been licensed for further development.

 

Researchers have a growing genetic data on bladder cancer, some of which threaten to overturn the supposed causes of bladder cancer. Genetics has also allowed bladder cancer to be reclassified from two categories into five distinct subtypes, each with different characteristics and weak spots. All these advances bode well for drug development and for improved diagnosis and prognosis.

 

Among the groups studying the genetics of bladder cancer are two large international teams: Uromol (named for urology and molecular biology), which is based at Aarhus University Hospital in Denmark, and The Cancer Genome Atlas (TCGA), based at institutions in Texas and Boston. Each team tackled a different type of cancer, based on the traditional classification of whether or not a tumour has grown into the muscle wall of the bladder. Uromol worked on the more common, earlier form, non-muscle-invasive bladder cancer, whereas TCGA is looking at muscle-invasive bladder cancer, which has a lower survival rate.

 

The Uromol team sought to identify people whose non-invasive tumours might return after treatment, becoming invasive or even metastatic. Bladder cancer has a high risk of recurrence, so people whose non-invasive cancer has been treated need to be monitored for many years, undergoing cystoscopy every few months. They looked for predictive genetic footprints in the transcriptome of the cancer, which contains all of a cell’s RNA and can tell researchers which genes are turned on or off.

 

They found three subgroups with distinct basal and luminal features, as proposed by other groups, each with different clinical outcomes in early-stage bladder cancer. These features sort bladder cancer into genetic categories that can help predict whether the cancer will return. The researchers also identified mutations that are linked to tumour progression. Mutations in the so-called APOBEC genes, which code for enzymes that modify RNA or DNA molecules. This effect could lead to cancer and cause it to be aggressive.

 

The second major research group, TCGA, led by the National Cancer Institute and the National Human Genome Research Institute, that involves thousands of researchers across USA. The project has already mapped genomic changes in 33 cancer types, including breast, skin and lung cancers. The TCGA researchers, who study muscle-invasive bladder cancer, have looked at tumours that were already identified as fast-growing and invasive.

 

The work by Uromol, TCGA and other labs has provided a clearer view of the genetic landscape of early- and late-stage bladder cancer. There are five subtypes for the muscle-invasive form: luminal, luminal–papillary, luminal–infiltrated, basal–squamous, and neuronal, each of which is genetically distinct and might require different therapeutic approaches.

 

Bladder cancer has the third-highest mutation rate of any cancer, behind only lung cancer and melanoma. The TCGA team has confirmed Uromol research showing that most bladder-cancer mutations occur in the APOBEC genes. It is not yet clear why APOBEC mutations are so common in bladder cancer, but studies of the mutations have yielded one startling implication. The APOBEC enzyme causes mutations early during the development of bladder cancer, and independent of cigarette smoke or other known exposures.

 

The TCGA researchers found a subset of bladder-cancer patients, those with the greatest number of APOBEC mutations, had an extremely high five-year survival rate of about 75%. Other patients with fewer APOBEC mutations fared less well which is pretty surprising.

 

This detailed knowledge of bladder-cancer genetics may help to pinpoint the specific vulnerabilities of cancer cells in different people. Over the past decade, Broad Institute researchers have identified more than 760 genes that cancer needs to grow and survive. Their genetic map might take another ten years to finish, but it will list every genetic vulnerability that can be exploited. The goal of cancer precision medicine is to take the patient’s tumour and decode the genetics, so the clinician can make a decision based on that information.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/29117162

 

https://www.ncbi.nlm.nih.gov/pubmed/27321955

 

https://www.ncbi.nlm.nih.gov/pubmed/28583312

 

https://www.ncbi.nlm.nih.gov/pubmed/24476821

 

https://www.ncbi.nlm.nih.gov/pubmed/28988769

 

https://www.ncbi.nlm.nih.gov/pubmed/28753430

 

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A novel 5-gene pancreatic adenocarcinoma classifier: Meta-analysis of transcriptome data – Clinical Genomics Research @BIDMC

Posted in CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Screening, Genomic Expression, Meta-analysis of transcriptome data, Pancreatic adenocarcinoma classifier on December 28, 2016| Leave a Comment »

A novel 5-gene pancreatic adenocarcinoma classifier: Meta-analysis of transcriptome data – Clinical Genomics Research @BIDMC

Curator: Tilda Barliya, PhD

Analysis of  Bhasin et al paper and Literature search

Table 1: 5-genes classifiers as biomarkers for PDAC:

Gene symbol	Gene name	Subcellular localization
ECT2	Epithelial cell transforming sequence 2 oncogene	Nucleus, cytoplasm
AHNAK2	AHNAKE nucleoprotein 2	Plasma membrane, cytoplasm
POSTN	Periostin, osteoblast specific factor	Extracellular space
TMPRSS4	Transmembrane protease, serine 4	Plasma membrane
SERPINB5	Serpin peptidase inhibitor, clade B (ovalbumin) member 5	Extracellular space

Introduction:

• Bhasin et al, conducted a beautiful study using a powerful meta-analysis from different sources to identify the “important/classifier” genes associated with Pancreatic Cancer (PDAC).
• The authors identified 5 genes that were considered as good classifiers (table 1).
• It is important to note that the meta-analysis was performed on tissue and microdissection samples.
• In their summary, the authors aim to validate these genes in blood/urine samples.
• While these genes might be over expressed in tissue samples it may not be true to their existence in blood and careful examination and validation is required.
• Liquid biopsies are emerging as the go-to use tools for disease detection, mostly aimed for early diagnosis.
• Liquid biopsies are non-invasive biopsies of blood, urine (potentially saliva) and their “exotic” components, i.e miRNA, exosomes etc.
• Since Liquid biopsies are non-invasive, they are painless and patients are more complied.
• It is important to note that there is a gap between the expression of a gene or a protein in tissue section and their expression in the blood and may not necessarily correlate.
• It will be very interesting to follow their research and future outcomes.

Additional References:

• TMPRSS4: an emerging potential therapeutic target in cancer.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4453593/

• The tumour trail left in blood

http://www.nature.com/nature/journal/v532/n7598/full/532269a.html

Aashir Awan, PhD, wrote on 12/28/2016

I was wondering if these same 5 genes were upregulated in the pancreatic ductal adenocarcinoma cell lines that are available out there.  In doing cell biology work, there is always a dilemma whether cancer cell lines correctly re-capitulate in vivo tumors or not.  Personally, I prefer primary cell lines to do analysis but this finding can be used to test primary vs cell line.  In addition, I’ve attached the gene network for Ect2.  If you look carefully, the two big proteins that jump out are RACGAP1 and KIF23.  I think in designing therapies, combinatorial targets can yield the best outcomes.  Drugs directed towards two or more targets would seem ideal in my opinion.

Gene Network for Ect2

Original Research

Oncotarget. 2016 Apr 26;7(17):23263-81. doi: 10.18632/oncotarget.8139.

Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier.

Bhasin MK¹, Ndebele K², Bucur O^2,3, Yee EU², Otu HH⁴, Plati J², Bullock A⁵, Gu X¹, Castan E¹, Zhang P¹, Najarian R², Muraru MS², Miksad R⁵, Khosravi-Far R², Libermann TA¹.

Author information

Abstract

PURPOSE:

Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis. Superior early detection biomarkers are critical to improving PDAC survival and risk stratification.

EXPERIMENTAL DESIGN:

Optimized meta-analysis of PDAC transcriptome datasets identified and validated key PDAC biomarkers. PDAC-specific expression of a 5-gene biomarker panel was measured by qRT-PCR in microdissected patient-derived FFPE tissues. Cell-based assays assessed impact of two of these biomarkers, TMPRSS4 and ECT2, on PDAC cells.

RESULTS:

A 5-gene PDAC classifier (TMPRSS4, AHNAK2, POSTN, ECT2, SERPINB5) achieved on average 95% sensitivity and 89% specificity in discriminating PDAC from non-tumor samples in four training sets and similar performance (sensitivity = 94%, specificity = 89.6%) in five independent validation datasets. This classifier accurately discriminated PDAC from chronic pancreatitis (AUC = 0.83), other cancers (AUC = 0.89), and non-tumor from PDAC precursors (AUC = 0.92) in three independent datasets. Importantly, the classifier distinguished PanIN from healthy pancreas in the PDX1-Cre;LSL-KrasG12D PDAC mouse model. Discriminatory expression of the PDAC classifier genes was confirmed in microdissected FFPE samples of PDAC and matched surrounding non-tumor pancreas or pancreatitis. Notably, knock-down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability and TMPRSS4 knockdown also blocked PDAC migration and invasion.

CONCLUSIONS:

This study identified and validated a highly accurate 5-gene PDAC classifier for discriminating PDAC and early precursor lesions from non-malignant tissue that may facilitate early diagnosis and risk stratification upon validation in prospective clinical trials. Cell-based experiments of two overexpressed proteins encoded by the panel, TMPRSS4 and ECT2, suggest a causal link to PDAC development and progression, confirming them as potential therapeutic targets.

KEYWORDS:

bioinformatics; biomarkers; meta-analysis; pancreatic cancer; transcriptome

PMID:

26993610

PMCID:

PMC5029625

DOI:

10.18632/oncotarget.8139

SOURCE

https://www.ncbi.nlm.nih.gov/pubmed/26993610 

Oncotarget, Vol. 7, No. 17 – Referred as PDF, above

 

BIDMC Researchers Discover Early Indicators of Pancreatic Cancer

Markers may help doctors detect pancreatic cancer before it becomes deadly

• Date: 3/28/2016
• BIDMC Contact: Jennifer Kritz
• Phone: 617-667-7301
• Email: jkritz@bidmc.harvard.edu

In photo: First author Manoj Bhasin, PhD, and co-senior author Towia Libermann, PhD, Co-Director and Director of BIDMC’s Genomics, Proteomics, Bioinformatics and Systems Biology Center.

SOURCE

http://www.bidmc.org/News/PRLandingPage/2016/March/Libermann-Pancreatic-Cancer-Research-2016.aspx

BOSTON – Pancreatic cancer, the fourth leading cause of cancer death in the United States, is often diagnosed at a late stage, when curative treatment is no longer possible. A team led by investigators at Beth Israel Deaconess Medical Center (BIDMC) has now identified and validated an accurate 5-gene classifier for discriminating early pancreatic cancer from non-malignant tissue. Described online in the journal Oncotarget, the finding is a promising advance in the fight against this typically fatal disease.

“Pancreatic cancer is a devastating disease with a death rate close to the incidence rate,” said co-senior author Towia Libermann, PhD, Director of the Genomics, Proteomics, Bioinformatics and Systems Biology Center at BIDMC and Associate Professor of Medicine at Harvard Medical School (HMS). “Because more than 90 percent of pancreatic cancer cases are diagnosed at the metastatic stage, when there are only limited therapeutic options, earlier diagnosis is anticipated to have a major impact on extending life expectancy for patients. There has been a lack of reliable markers, early indicators and risk factors associated with pancreatic cancer, but this new way of differentiating between healthy and malignant tissue offers hope for earlier diagnosis and treatment.”

The investigators used a number of publicly available gene expression datasets for pancreatic cancer and developed a strategy to reanalyze these datasets together, applying rigorous statistical criteria to compare different datasets from different laboratories and different platforms with each other. The team then selected a subset of data for developing a panel for differentiating between pancreatic cancer and healthy pancreas tissue and thereafter applied this “Pancreatic Cancer Predictor” to the remaining datasets for independent validation to confirm the accuracy of the markers.

After demonstrating and independently validating that a 5-gene pancreatic cancer predictor discriminated between cancerous and healthy tissue, the researchers applied the predictor to datasets that also included benign lesions of the pancreas, including pancreatitis and early stage cancer. The predictor accurately differentiated pancreatic cancer, benign pancreatic lesions, early stage pancreatic cancer and healthy tissue. The predictor achieved on average 95 percent sensitivity and 89 percent specificity in discriminating pancreatic cancer from non-tumor samples in four training sets and similar performance (94 percent sensitivity, 90 percent specificity) in five independent validation datasets.

“Using innovative data normalization and gene selection approaches, we combined the statistical power of multiple genomic studies and masked their variability and batch effects to identify robust early diagnostic biomarkers of pancreatic cancer,” said first author Manoj Bhasin, PhD, Co-Director of BIDMC’s Genomics, Proteomics, Bioinformatics and Systems Biology Center and Assistant Professor of Medicine at HMS.

“The identification and initial validation of a highly accurate 5-gene pancreatic cancer biomarker panel that can discriminate late and early stages of pancreatic cancer from normal pancreas and benign pancreatic lesions could facilitate early diagnosis of pancreatic cancer,” said co-senior author Roya Khosravi-Far, PhD, Associate Professor of Pathology at BIDMC. “Our findings may open a window of opportunity for earlier diagnosis and, consequently, earlier intervention and more effective treatment of this deadly cancer, leading to higher survival rates.”

The first diagnostic application of the panel may be for analyses of fine needle biopsies routinely used for diagnosing pancreatic cancer and for determining the malignant potential of mostly benign pancreatic cysts that can sometimes be precursors of pancreatic cancer. In addition to providing a new tool for diagnoses, the research may also lead to new insights into how pancreatic cancer arises.

“Because these five genes are ‘turned on’ so early in the development of pancreatic cancer, they may play roles as drivers of this disease and may be exciting targets for therapies,” said Libermann. Most of the five genes—named TMPRSS4, AHNAK2, POSTN, ECT2 and SERPINB5—have been linked to migration, invasion, adhesion, and metastasis of pancreatic or other cancers.

The scientists next plan to evaluate the precise roles of the five genes and to validate the accuracy of their diagnostic assay in a prospective clinical study. “Moving forward, we will explore the potential to convert this tissue-based diagnostic into a noninvasive blood or urine test,” Libermann said.

“To further enhance the diagnostic power of this biomarker, we plan to expand it by including non-coding RNAs, proteins, metabolites and mutations associated with pancreatic cancer. This will result in development of the first of its kind biomarker that gauges pancreatic cancer alterations from multiple genomic angles for making highly accurate diagnoses,” added Bhasin. Such an inexpensive and simple test could help transform the landscape of pancreatic cancer and help prevent many of the estimated 330,000 deaths that it causes worldwide each year.

Study coauthors include BIDMC investigators Kenneth Ndebele, Octavian Bucur, Eric Yee, Jessica Plati, Andrea Bullock, Xuesong Gu, Eduardo Castan, Peng Zhang, Robert Najarian, Maria Muraru and Rebecca Miksad, and the University of Nebraska-Lincoln’s Hasan H. Otu. The work was supported by the National Institutes of Health, National Cancer Institute and Ben and Rose Cole Charitable Pria Foundation.

SOURCE

http://www.bidmc.org/News/PRLandingPage/2016/March/Libermann-Pancreatic-Cancer-Research-2016.aspx

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