Quantcast

Industry news that matters to you.  Learn more

Kantar Health Launches CancerMPact Biomarker Analysis

Kantar Health, a leading global healthcare consulting firm, today announced the availability of CancerMPact® Biomarker Analysis, a global offer that examines biomarker segmentation in the current and evolving oncology landscape. The analysis is based on a thorough review of literature and recently published data covering the following biomarkers:

  • BRAF (melanoma)
  • EGFR (non-small lung cancer)
  • EML4-ALK (non-small cell lung cancer)
  • KRAS (colorectal cancer)
  • TNBC (breast cancer)

CancerMPact Biomarker Analysis helps clients identify the percentage of cancer patients with a specific biomarker; ascertain variations in biomarker prevalence by race, ethnicity or geography; determine which information to use to inform forecasting and market sizing; and pinpoint which patient segments are available for targeted therapies and clinical trials. Through this new offer, pharma companies are able to better understand which patient subpopulations are candidates for unique treatment options in this complex therapeutic area.

“The era of ‘personalized’ medicine has arrived, and while physicians and patients are ready to embrace it, many factors need to be considered by a manufacturer to accurately evaluate their market opportunities,” Kantar Health Vice President David Robinson said. “We estimate that 17 to 20 percent of oncology patients are currently eligible for personalized care due to either biomarkers or histology-based treatments. This number will grow in the near future as more biomarkers are validated and new patient subpopulations are identified as being appropriate for novel targeted therapeutics.”

CancerMPact Biomarker Analysis is produced by the same oncology experts as CancerMPact®, which has become an invaluable oncology decision support tool for market analysis, strategic planning and identification of commercial opportunities in the U.S., Western Europe, Japan and China. This tool, composed of web-based integrated modules, includes Treatment Practices and Evolution (Treatment Architecture and Future Trends and Insights), Patient Metrics, and Monthly Drugs and Regimens.

Team Finds Markers Related to Ovarian Cancer Survival and Recurrence

Researchers at the University of Illinois have identified biomarkers that can be used to determine ovarian cancer survival and recurrence, and have shown how these biomarkers interact with each other to affect these outcomes. Their findings appear in the journal PLOS ONE.

Researchers try to find molecules called biomarkers that help determine a person’s likelihood of getting a disease or, if they have already been diagnosed, how far the disease has advanced. Genes, transcription factors and microRNAs are often used as biomarkers because these molecules can be heralds of disease or portents of susceptibility.

Genes are segments of DNA that code for proteins or other molecules that perform the functions of the cell. Transcription factors regulate these genes by binding to specific DNA sequences, preventing or inducing the genes to be “expressed” at higher or lower levels. MicroRNAs, as their name suggests, are small RNA molecules that regulate an intermediate stage of gene expression. Transcription factors and microRNAs also can regulate each other.

The relationships among transcription factors, microRNAs and target genes can be visualized as interconnected networks. These intricate webs are often used to determine how diseases such as cancer proceed. Analyzing how these networks function in cancer can offer insight into how tumor cells proliferate and differentiate, undergo (or resist) programmed cell death, and how likely they are to become invasive.

According to the American Cancer Society, an estimated 22,240 women will be diagnosed with ovarian cancer in 2013, and 14,230 will die of the disease; this makes ovarian cancer the fifth most common cause of cancer death in women.

The high prevalence of ovarian cancer and ovarian cancer deaths in the U.S. prompted U. of I. animal sciences professor Sandra Rodriguez-Zas and doctoral researcher Kristin Delfino to search for biomarkers associated with ovarian cancer survival and recurrence.

“We knew that there are specific biomarkers that have been associated with ovarian cancer, but we were looking at whether we could more accurately predict survival or age at cancer recurrence considering hundreds of interacting biomarkers simultaneously,” Rodriguez-Zas said.

The team used data from the Cancer Genome Atlas, which contains information about ovarian cancer patients’ age, survival, cancer recurrence, treatment, tumor stage, tumor grade and genomic expression. The researchers then performed statistical tests to tie these factors to patients’ survival time, measured in months from diagnosis to death, and their recurrence time, measured in months from diagnosis to recurrence.

“The networks change for people who have different rates of survival, so we looked at what’s being expressed in high-survival patients compared to what’s being expressed in low-survival patients,” Delfino said.

The team was able to confirm the association of 21 microRNAs with ovarian cancer. They also found 838 target genes and 12 transcription factors associated with ovarian cancer survival and 734 target genes and eight transcription factors associated with ovarian cancer recurrence.

“We were able to find many biomarkers that held the same relationship with survival no matter the cancer treatment, as well as some that were unique in their relationship with survival depending on the treatment the patient had received,” Rodriguez-Zas said.

Delfino said that a network-based approach is more predictive of ovarian cancer survival and recurrence than a single-molecule-based perspective.

“We took a step back and looked at everything from a network point of view instead of just individually to see how the components interacted with each other and how the biomarkers were associated with ovarian cancer survival and recurrence,” Delfino said.

“This demonstrated that the consideration of networks of microRNAs, transcription factors, and target genes allows us to identify reliable indicators of cancer survival and recurrence and serves as the basis for effective prognostic tools,” Rodriguez-Zas said.

Delfino believes this study opens the door to the creation of less invasive diagnostic tests and more specialized treatment options for women with ovarian cancer.

“In the future we’d like to be able to just take a little sample of your DNA and be able to tell you what’s going to happen, what we can do to prevent it, and how to cut cancer off before it ever reaches that point,” Delfino said. “Everyone is different, and hopefully, we will be able to specify the treatment that will best treat the individual patient.”

Study: Transcription Factor-MicroRNA-Target Gene Networks Associated with Ovarian Cancer Survival and Recurrence

Source: University of Illinois at Urbana-Champaign

Molecular Response Launches TargetXTM Platform for Rapid Discovery & Validation of New Oncology Targets

Molecular Response recently announced the launch of its TargetX platform for rapid discovery and validation of new oncology targets. The program provides partners with access to the world’s largest bank of living tumor specimens, matched genomic database, and in vivo/ex vivo patient derived tumor models for validation. The integrated platform enables investigators to do in days what used to take months.

Target discovery and validation in oncology has largely relied on molecular and functional studies performed in cell lines. Recent advances in genomics have now created large databases based on well-characterized tumor tissue, which has enabled direct investigation of patient tumors for novel targets. Following these discoveries, it is routine to perform functional studies in cell line-based systems; however, it is often challenging to find a relevant cell line model and if found, there are often numerous factors which confound biology when using historical cell lines for functional studies. The result can be a process which takes considerable time and does not readily translate to clinical relevance.

“TargetX is the largest scale genomic database matched to living patient-derived tumor models,” said Dr. Mohit Trikha, CSO of Triphase Accelerator and founder of Drug Design Corp. “We plan to access it for our drug pipeline development and biomarker identification; having everything in one place allows us to do in days what used to take months. Additionally, we can now work with living patient derived tumor samples rather than cultured cell lines.”

The platform relies on Molecular Response’s proprietary bank of more than 144,000 patient derived tumor cells, of which nearly 400 tumors have been genomically characterized and databased for target discovery studies. The database is growing, but currently features the following cancer indications: colon carcinoma, NSCLC, melanoma, ovarian carcinoma, prostate cancer and Non-Hodgkins Lymphoma. Upon discovery of a novel target, tumors of interest are immediately implanted into mice to perform functional studies in direct patient derived models–either in vivo or ex vivo. Molecular Response currently has more than 60 such patient derived xenograft models established for in vivo studies.

“We continue to focus on the use of patient derived models, both in vivo and ex vivo, for advancing oncology drug development,” said Thomas Broudy, CSO of Molecular Response. “Everybody would like to perform studies in the patient derived tumor setting starting as early as possible, but without the resource to do so, it’s nearly impossible. TargetX now enables you to do that.”

Molecular Response presented results from the TargetX platform at the AACR meeting; the company has identified a novel kinase target for potential therapeutic development. They investigated prevalence of target overexpression across 7 cancer indications, and identified melanoma as a clinical indication of high interest. Growth characteristics from patient tumors featuring high kinase gene expression vs. low expression were examined to help characterize the role of this target in oncology disease progression. Functional studies in these patient derived models to further validate the novel kinase are ongoing, as is a small molecule and antibody-based therapeutic development program.

Source: Business Wire

Alzheimer’s Disease and Dementia Early-Diagnostic Clinic Launched in Iceland

MentisCura Diagnostics (www.mentiscura.com) recently announced the launch of its first clinical center for the early detection of Alzheimer’s disease and other dementias. The operational launch brings sophisticated biomarkers capable of assisting early, differential diagnosis into a clinical setting and provides for the first time cutting edge electrophysiological analysis developed by MentisCura to the general public through community physicians.

Both the high prevalence and rapidly increasing incidence of CNS disorders are raising alarm on account of the growing burden of care associated with these diseases. According to data published by the Alzheimer’s Association, Alzheimer’s disease is the sixth-leading cause of death in the United States, with as many as one in eight older Americans having Alzheimer’s disease in 2012. A recent World Alzheimer’s Report estimated the 2010 worldwide cost of dementia to be more than $600bn.

“Our new service fulfills an important role addressing the key issues of earlier and more accurate diagnosis. Current diagnostic tools such as fMRI and PET are in a price range that precludes their use as screening tools for dementias. The low cost, high-throughput and non-invasive nature of our test makes it uniquely useful in a real world clinical setting, where physicians need to assess patients and make diagnostic decisions before these diseases have reached a late and untreatable stage. From a five-minute EEG recording using the international standard 10-20 testing protocol, our powerful analytical systems are able to provide same-day results back to physicians,” said Kristinn Gretarsson, CEO of MentisCura.

“MentisCura provides a welcome and reliable tool for diagnosing the causes of cognitive impairment and dementia. It plays a key role in our diagnostic protocol for dementia and is an important part of our follow up on disease progression and treatment efficacy,” commented Jon Snaedal, MD, Chief Physician of the Memory Clinic at the National Hospital of Iceland.

MentisCura’s clinic offers a complete, integrated service to hospitals and general practitioners through sampling, processing and analysis of patient EEG data. The MentisCura Analysis System is a CE marked diagnostic aid, based on advanced, proprietary EEG-biomarker technology platform that accurately maps changes in electrophysiology to specific disease pathologies, through correlation with the world´s most comprehensive proprietary EEG database for dementia and cognitive disorders. The platform supports diagnoses for most common types of dementia, including Alzheimer’s disease and Lewy Body Dementia.

Source: Business Wire

Tenfold Boost in Ability to Pinpoint Proteins in Cancer Cells

Better diagnosis and treatment of cancer could hinge on the ability to better understand a single cell at its molecular level. New research offers a more comprehensive way of analyzing one cell’s unique behavior, using an array of colors to show patterns that could indicate why a cell will or won’t become cancerous.

A University of Washington team has developed a new method for color-coding cells that allows them to illuminate 100 biomarkers, a ten-time increase from the current research standard, to help analyze individual cells from cultures or tissue biopsies. The work is published in the March 19 issue of Nature Communications.

“Discovering this process is an unprecedented breakthrough for the field,” said corresponding author Xiaohu Gao, a UW associate professor of bioengineering. “This technology opens up exciting opportunities for single-cell analysis and clinical diagnosis.”

The research builds on current methods that use a smaller array of colors to point out a cell’s biomarkers – characteristics that indicate a special, and potentially abnormal or diseased, cell. Ideally, scientists would be able to test for a large number of biomarkers, then rely on the patterns that emerge from those tests to understand a cell’s properties.

The UW research team has created a cycle process that allows scientists to test for up to 100 biomarkers in a single cell. Before, researchers could only test for 10 at a time.

The analysis uses quantum dots, which are fluorescent balls of semiconductor material. Quantum dots are the smaller version of the material found in many electronics, including smartphones and radios. These quantum dots are between 2 and 6 nanometers in diameter, and they vary on the color they emit depending on their size.

Cyclical testing hasn’t been done before, though many quantum dot papers have tried to expand the number of biomarkers tested for in a single cell. This method essentially reuses the same tissue sample, testing for biomarkers in groups of 10 in each round.

“Proteins are the building blocks for cell function and cell behavior, but their makeup in a cell is highly complex,” Gao said. “You need to look at a number of indicators (biomarkers) to know what’s going on.”

The new process works like this: Gao and his team purchase antibodies that are known to bind with the specific biomarkers they want to test for in a cell. They pair quantum dots with the antibodies in a fluid solution, injecting it onto a tissue sample. Then, they use a microscope to look for the presence of fluorescent colors in the cell. If they see particular quantum dot colors in the tissue sample, they know the corresponding biomarker is present in the cell.

After completing one cycle, Gao and co-author Pavel Zrazhevskiy, a UW postdoctoral associate in bioengineering, inject a low-pH fluid into the cell tissue that neutralizes the color fluorescence, essentially wiping the sample clean for the next round. Remarkably, the tissue sample doesn’t degrade at all even after 10 such cycles, Gao said.

For cancer research and treatment, in particular, it’s important to be able to look at a single cell at high resolution to examine its details. For example, if 99 percent of cancer cells in a person’s body respond to a treatment drug, but 1 percent doesn’t, it’s important to analyze and understand the molecular makeup of that 1 percent that responds differently.

“When you treat with promising drugs, there are still a few cells that usually don’t respond to treatment,” said Gao. “They look the same, but you don’t have a tool to look at their protein building blocks. This will really help us develop new drugs and treatment approaches.”

The process is relatively low-cost and simple, and Gao hopes the procedure can be automated. He envisions a chamber to hold the tissue sample, and wire-thin pumps to inject and vacuum out fluid between cycles. A microscope underneath the chamber would take photos during each stage. All of the images would be quantified on a computer, where scientists and physicians could look at the intensity and prevalence of colors.

Gao hopes to collaborate with companies and other researchers to move toward an automated process and clinical use.

“The technology is ready,” Gao said. “Now that it’s developed, we’re ready for clinical impacts, particularly in the fields of systems biology, oncology and pathology.”

The research was funded by the National Institutes of Health, the U.S. National Science Foundation, the U.S. Department of Defense, the Wallace H. Coulter Foundation and the UW’s Department of Bioengineering.

Study: Quantum dot imaging platform for single-cell molecular profiling

Source: University of Washington