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Biomarker May Predict Prostate Cancers Requiring Treatment

Not all early-stage prostate cancer diagnoses are alike. While some patients have aggressive tumors, others have slow-growing, low Gleason score tumors that may not require treatment, but instead can be monitored with regular clinical evaluations. But distinguishing between prostate cancers that require treatment and those that do not is still a major challenge.

Researchers at Columbia University in New York City have now identified a 3-gene signature that could indicate whether a particular early-stage prostate cancer is indolent. The test relies on a tissue sample, and along with a prostate-specific antigen (PSA) test and a histology assessment, could help clinicians make an accurate diagnosis. The early results, including a blinded retrospective analysis of 43 patients, show that the signature can accurately predict which patients with low-risk disease would develop metastatic prostate cancer and which patients would not progress. The study is published in Science Translational Medicine.

“These types of markers will, for the first time, give us the opportunity to measure biological features of cancer in the same patient, with multiple biopsies spread out over many years,” said Eric Klein, MD, chairman, Glickman Urological and Kidney Institute at the Cleveland Clinic in Ohio.
Cory Abate-Shen, PhD, professor of urological oncology at Columbia University; Andrea Califano, PhD, professor of systems biology at Columbia University; and colleagues used a computational approach that identified three genes—FGFR1, PMP22, and CDKN1A—all associated with aging, that could accurately predict outcomes of low-risk, low Gleason score prostate tumors. Protein and mRNA levels of all three genes were high in those patients who had non-aggressive, indolent disease and low in those who had aggressive tumors.

Clinicians still rely on the Gleason score, a histology and pathology evaluation that does not incorporate any molecular assessment. Those patients with a Gleason score of 8 or higher are candidates for immediate treatment, but whether men with a score of 6 or 7 require treatment is difficult to assess—no test exists to identify the small percentage of patients who have early-stage prostate cancer that is more likely to metastasize.

The 3-gene signature was validated using an independent prostate cancer cohort. According to the study authors, the signature was prognostic and improved prognosis compared with the use of PSA and clinical assessment.

“We would predict that the test would be beneficial for patients with low Gleason score prostate tumors,” said Abate-Shen. “These patients are now typically monitored on active surveillance protocols, and the patients get a biopsy periodically. The test would be conducted on the biopsy.”

Rather than focusing on the entire genome, the researchers focused on 377 genes involved in aging, predicting that genes involved in aging and senescence are critical for tumor suppression. Cellular senescence is known to play a role in tumor suppression and is associated with benign prostate tumors both in the clinic and in mouse models, according to the researchers. Using a computational analysis called gene set enrichment analysis (GSEA), they narrowed the long gene list to 19 genes, and then to a set of 3 genes that could identify indolent tumors.

“To focus on senescence genes is intellectually interesting,” said Klein. “There is already a body of work supporting the role of these genes in prostate cancer, but to my knowledge no one has looked at them in early-stage disease before.”

Forty-three patients, who had been under active surveillance for 10 years at Columbia University Medical School, were used for the blinded retrospective analysis to assess the predictive value of the gene signature. Each patient had been diagnosed with low-risk prostate cancer, with a Gleason score of 6 or less. The test was correctly able to identify all 14 patients who eventually developed advanced prostate cancer.

CDKN1A has been shown to be linked to senescence and to regulate the cell cycle. Previous studies have shown that downregulation of the gene is linked to cancer progression. The correlation of FGFR1 (fibroblast growth factor receptor 1) with indolent tumors was surprising, as fibroblast growth factors have been shown to play a role in prostate cancer development. But, as the authors highlight in their discussion, FGFR1 signaling in prostate cancer is likely complex. The third gene in the signature, PMP22, encodes a glycoprotein expressed in neurons and has not been previously associated with prostate cancer.

This 3-gene signature is different from previously identified biomarkers, which have largely focused on advanced tumors. The potential biomarker test could complement other approaches in development, such as urine or blood tests, according to the authors.

A trial to validate the genetic signature is underway at Columbia University, and a national trial is being planned.

“It is really important to find novel ways to help to define early-stage tumors that may or may not progress to aggressive disease,” said Abate-Shen. “This will ultimately really help to minimize overtreatment, while capitalizing on the benefits of cancer screening.”

Other genomic approaches to distinguish indolent and aggressive disease are also underway. The first-generation expression-based tests, including Oncotype DX prostate and Prolaris, can facilitate clinical decisions based on the molecular characteristics of a prostate tumor. Both the available tests and the new ones “promise to reduce overtreatment and help men make the right decisions based on biology rather than uncertainty,” said Klein. 

Study: A Molecular Signature Predictive of Indolent Prostate Cancer [Science Translational Medicine]

Source: CancerNetwork

BIDMC Cardiovascular Institute Researchers Will Lead $4 Million NIH Grant to Study MicroRNAs

A cardiovascular research team from Beth Israel Deaconess Medical Center (BIDMC) and Brigham and Women’s Hospital (BWH), led by BIDMC Principal Investigator Saumya Das, MD, PhD, has been awarded a $4 million Common Fund grant from the National Institutes of Health (NIH) as part of a newly formed program on Extracellular RNA Communication. The five-year grant will focus on identifying microRNA biomarkers in heart disease.

Each year, complications from heart attacks (myocardial infarctions) contribute to more than half a million cases of heart failure and 300,000 cases of sudden cardiac arrest, when the heart suddenly stops. Both of these conditions are closely related to a process known as remodeling, in which the structure and function of the heart changes – or remodels — following a heart attack.

“Our goal is to explore the role that microRNAs play in predicting which heart-attack patients will go on to experience complications,” explains Das, an electrophysiologist in BIDMC’s Cardiovascular Institute and co-director of the cardiovascular genetics program within the Outpatient Cardiovascular Clinic.

“Current strategies used to identify the highest risk patients have often been inaccurate,” he adds. “We think that a blood test that makes use of microRNA biomarkers could replace existing strategies and more accurately predict which patients might experience poor outcomes and thereby identify who would most benefit from frequent monitoring and medical care.” Other investigators who are part of the NIH grant, “Plasma miRNA Predictors of Adverse Mechanical and Electrical Remodeling After Myocardial Infarction,” include BIDMC Director of Cardiovascular Research Anthony Rosenzweig, MD, and BWH investigators Raymond Y. Kwong, MD, MPH, and Mark Sabatine, MD, MPH.

microRNAs are one type of extracellular RNA. Once considered nothing more than genomic “junk,” microRNAs have more recently been recognized as playing a key role in cellular functions. Several years ago, scientists began to recognize that these small, noncoding RNAs were not only found inside cells, but could also be found in blood and other tissue fluids.

Using patient plasma samples from extensively characterized patients who have suffered heart attacks, the scientific team will first identify which specific microRNAs are related to poor heart remodeling. They will then use cell culture and animal models of heart disease to further prioritize which microRNAs play a functional role in disease progression. Finally, the investigators will validate these prioritized microRNAs as prognostic markers for poor health outcomes after heart attacks in a large prospective clinical trial.

“Ultimately, we think that miRNA-based tests could replace current tests to predict which patients might be at risk of complications and, therefore, be good candidates to receive an implanted defibrillator,” says Das. “At the same time, we hope to be able to better predict which individuals are at less risk of complications – and thereby spare them unnecessary and costly procedures.”

Beth Israel Deaconess Medical Center is a patient care, teaching and research affiliate of Harvard Medical School, and currently ranks third in National Institutes of Health funding among independent hospitals nationwide.

BIDMC has a network of community partners that includes Beth Israel Deaconess Hospital-Milton, Beth Israel Deaconess Hospital-Needham, Anna Jaques Hospital, Cambridge Health Alliance, Lawrence General Hospital, Signature Health Care, Commonwealth Hematology-Oncology, Beth Israel Deaconess HealthCare, Community Care Alliance, and Atrius Health. BIDMC is also clinically affiliated with the Joslin Diabetes Center and Hebrew Senior Life and is a research partner of Dana-Farber/Harvard Cancer Center. BIDMC is the official hospital of the Boston Red Sox. For more information, visit www.bidmc.org.

Source: Beth Israel Deaconess Medical Center

Exosome Diagnostics Enters Collaboration Agreement with Lilly for Exosome Blood-Based Biomarker Discovery

Exosome Diagnostics recently announced it has entered into a collaboration agreement with Eli Lilly and Company (NYSE: LLY) for biomarker discovery and validation using Exosome Diagnostics proprietary EXO50 nucleic acid extraction kit. Under the agreement, Lilly will gain early access to Exosome Diagnostics technology to help identify key gene mutations and expression levels in blood that may be correlated with drug response and disease recurrence. Financial terms were not disclosed.

“Exosome Diagnostics technology may provide a unique opportunity to gain insight into the biology of complex conditions such as cancer and immune disorders,” said Andrew Schade, senior medical director, diagnostic and experimental pathology at Lilly. “Exosome technology enables biofluid molecular sampling and the ability to monitor disease progression in real time. As Lilly explores new ways to pursue patient tailoring, we’ll continue to work with partners to expand our capabilities.”

“Accessing high quality messenger and microRNA directly from frozen patient fluid samples offers a rapid, cost-effective route to identify and validate biomarkers, which may be correlated with drug response and disease recurrence,” said James McCullough, chief executive officer of Exosome Diagnostics. “Lilly has accumulated an extensive and well annotated clinical blood sample biobank that provides a unique opportunity to track target biomarkers through the clinical trial process and help overcome the limitations of stored biopsy tissue.”

Exosomes and other microvesicles are secreted by all cells into all biofluids, and provide a natural biological packaging and distribution mechanism for RNA and DNA. Exosome Diagnostics’ rapid exosome isolation and extraction technology produces high-quality RNA and DNA, including full length mRNA and microRNA, from small volumes of patient biofluids, such as blood (serum and plasma), urine and cerebrospinal fluid, for analysis by standard PCR, array and sequencing instruments. Analysis can be performed on fresh or frozen fluid samples, allowing for broad, flexible and convenient analyses of clinical trial samples, both in real-time and retrospectively, with no special preservation methods required. Exosomes and their protected nucleic acid contents are being investigated in a broad range of diseases including cancer, CNS disorders such as Alzheimer’s and Parkinson’s disease, cardiovascular disease, maternal/fetal medicine, and chronic kidney disease, among others. In July, QIAGEN and Exosome Diagnostics signed an agreement for the creation of High-Performance Biofluid Sample Preparation Kits for Personalized Healthcare Research which covers the exclusive supply of these products upon availability in 2014.

Source: Exosome Diagnostics

NanoString Technologies Receives FDA 510(k) Clearance for Prosigna Breast Cancer Prognostic Gene Signature Assay

NanoString Technologies, Inc., (NASDAQ: NSTG) a provider of life science tools for translational research and molecular diagnostic products, recently announced that it has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its Prosigna™ Breast Cancer Prognostic Gene Signature Assay. Based on the PAM50 gene signature, Prosigna is the company’s first FDA-cleared in vitro diagnostic assay and uses the gene expression profile of cells found in breast cancer tissue to assess a patient’s risk of distant recurrence of disease. The Prosigna Assay is performed using the nCounter® Dx Analysis System, which can be placed in qualified laboratories throughout the United States, empowering oncologists and pathologists to quickly and easily meet the testing needs of their breast cancer patients.

“Receipt of FDA 510(k) clearance for Prosigna marks a key milestone for NanoString and is an important step forward in the treatment of breast cancer. This achievement is a testament to the ongoing dedication and professionalism of our team, and the commitment of our collaborators,” said Brad Gray, President and Chief Executive Officer of NanoString Technologies. “Prosigna illustrates our approach of using nCounter technology to translate genomic discoveries into powerful in vitro diagnostic products, and it represents a significant growth opportunity beyond our robust life sciences research business.”

The Prosigna Assay is intended for use as a prognostic indicator for distant recurrence-free survival at 10 years, and is indicated for postmenopausal women with Stage I/II lymph node-negative or Stage II lymph node-positive (one to three positive nodes) hormone receptor-positive breast cancer who have undergone surgery in conjunction with locoregional treatment consistent with standard of care. For each patient, the Prosigna Assay reports the Prosigna Score (referred to as Risk of Recurrence Score, or ROR Score, in the scientific literature, including the TransATAC study recently published in the Journal of Clinical Oncology ) and a risk category based on both the Prosigna Score and nodal status. Node-negative patients are classified as low, intermediate or high risk, while node-positive patients are classified as low or high risk.

Other key features of the Prosigna Breast Cancer Prognostic Gene Signature Assay include:

  • All-in-one assay consumables, including RNA extraction kits, allowing laboratories to test as little as a single section of formalin-fixed paraffin embedded (FFPE) tumor tissue
  • High-throughput workflow allowing each nCounter Dx Analysis System to process up to 30 patient samples per eight hour work day
  • Automated generation of personalized full-color patient reports that can be quickly and easily shared electronically with ordering oncologists

Bruce Seeley, Senior Vice President & General Manager of Diagnostics of NanoString Technologies commented: “We believe that the compelling clinical data, clear patient reporting, and unique delivery model position Prosigna for success in the U.S. market. By integrating the Prosigna Assay into existing laboratory workflows, we are offering physicians and patients seamless and timely access to clinical insights and a powerful tool that can aid in making more informed treatment decisions.”

Prosigna-enabled nCounter Dx Analysis Systems are expected to be available for placement in high-complexity Clinical Laboratory Improvement Amendments (CLIA) certified laboratories late in the fourth quarter of 2013. Prosigna testing services are expected to be available through qualified U.S. clinical laboratories beginning in the first quarter of 2014.

Source: NanoString Technologies

Nodality, Inc. Reports Promising Rheumatoid Arthritis Study Results to Predict Patient Treatment Response to TNF Inhibitors

Nodality, Inc., an innovative biotechnology company advancing discovery, development and use of transformative therapies by revealing functional systems biology, recently announced results of the Company’s comprehensive research study to identify cell markers (biomarkers) of disease activity and treatment success in rheumatoid arthritis (RA) patients. The study findings demonstrated that Nodality’s SCNP technology, which measures functional pathways at the single cell level, can be used to identify biomarkers of responsiveness to treatment with tumor necrosis factor inhibitors (TNFIs). RA affects an estimated two million Americans, and TNFIs constitute the most commonly prescribed therapy. Approximately half of patients respond to treatments such as TNFIs, leaving a substantial unmet need to identify which patients are more likely to respond to current therapies. Optimizing use of currently available therapies could potentially delay tissue damage and progression of disease.

SCNP provides the core technology foundation for Nodality’s programs dedicated to improving clinical medicine by increasing the efficiency of therapeutic R&D programs, enhancing life cycle management for commercialized drugs, and introducing new predictive diagnostics. The study results were featured in an oral presentation titled, Comparison of functional immune signaling profiles in peripheral blood mononuclear cells (PBMC) from rheumatoid arthritis (RA) patients versus healthy donors (HD) using Single Cell Network Profiling (SCNP) (Abstract W7.02.04), at the 15th International Congress of Immunology (ICI) in Milan, Italy, taking place August 22 to 27, 2013. The findings were presented by S. Louis Bridges, Jr., M.D., Ph.D., Marguerite Jones Harbert-Gene V. Ball, MD Professor of Medicine, Director, Division of Clinical Immunology and Rheumatology, University of Alabama School of Medicine.

“Nodality’s research program demonstrates the great promise and potential in gaining a better understanding of disease biology and applying this to the development of prognostic and predictive biomarkers for autoimmune diseases such as RA,” commented Alessandra Cesano, M.D., Ph.D., Chief Medical Officer of Nodality. “I look forward to the final results of this program, one of the most comprehensive of its kind. Our technology, based on immune-biology, can predict which RA patients will respond to specific therapies and reveal the mechanisms of drug resistance, thus informing alternative therapeutic strategies.”

The Nodality research program compares healthy and diseased peripheral blood cells at the single cell level, studying samples obtained through the national Treatment Efficacy and Toxicity in Rheumatoid Arthritis Database and Repository (TETRAD). Nodality anticipates completing its research program and announcing the key findings later this year.

Laura Brege, Nodality’s President and Chief Executive Officer, stated, “ICI has provided an important opportunity to showcase one of our key programs in immunology, further validating our broadly enabling SCNP platform. This platform has led to major collaborations in immunology addressing significant unmet needs among patients, as well as new predictive diagnostic modalities in blood cancers. Ultimately, Nodality’s goal is to accelerate and make more efficient the development of new therapeutic agents for serious diseases affecting large patient populations within immunology and oncology, two areas of continuing significant unmet clinical need.”

Additional program results were featured in a second oral presentation at the ICI Congress in a presentation titled, Functional proteomic interrogation of immune cell crosstalk and the effects of cytokine-targeted inhibitors using Single Cell Network Profiling (SCNP) (Abstract W7.02.03).

Source: Nodality, Inc