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Scientists Identify Biomarker to Predict Immune Response Risk After Stem Cell Transplants

Researchers from Indiana University, the University of Michigan, the Fred Hutchinson Cancer Research Center and the Dana-Farber Cancer Institute have identified and validated a biomarker accessible in blood tests that could be used to predict which stem cell transplant patients are at highest risk for a potentially fatal immune response called graft-versus-host disease.

Although transplant specialists have been able to reduce its impact, graft-versus-host disease remains a leading cause of death among patients who receive a stem cell transplant from another person, known as an allogeneic transplant. Such transplants are used to treat blood and bone marrow cancers such as leukemia and multiple myeloma, often as a last resort. Graft-versus-host disease occurs when immune cells from the transplant see the patient’s body as foreign and attack it.

Approximately 20,000 allogeneic stem cell transplants were performed worldwide in 2012. Thirty to 40 percent of stem cell transplant recipients whose donor is related will experience graft-versus-host disease. The percentage could rise to 60 to 80 percent if the patient and donor are not related.

The researchers found that patients with a high level of a protein named ST2 were more than twice as likely to have graft-versus-host disease that resisted standard treatment with steroids; and nearly four times as likely to die within six months of the transplant. Their findings were reported in the Aug. 8 edition of the New England Journal of Medicine.

“What we found particularly significant was that this marker was a better predictor than the clinical severity of the disease when it was diagnosed,” said Sophie Paczesny, M.D., Ph.D., associate professor of medicine at the IU School of Medicine and senior author of the study.

Thus, patients with low ST2 levels were more likely to respond to treatment regardless of how serious their graft-versus-host disease was graded, while patients with high ST2 levels were less likely to respond to treatment, whether their disease was graded less serious or more serious.

“This blood test, which is currently available to clinicians, will make informed treatment possible as the clinicians will now be able to adjust therapy to the degree of risk rather than treating every patient the same way,” Dr. Paczesny said.

In addition, while the disease most commonly appears about 30 days after the transplant, higher ST2 levels in blood samples taken as early as 14 days after transplant — far before the clinical signs of graft-versus-host disease are apparent — were associated with an increased risk of death from the toxicity of the transplant.

Therefore, the authors noted, early identification of patients who likely won’t respond to standard treatments is important and would allow physicians to consider additional therapies and early intervention. On the other hand, patients with low risk will not need to have additional medicine further suppressing their immune system. But, they cautioned, additional large prospective studies are needed to better define the levels of risk predicted by the ST2 marker.

Study: ST2 as a marker for risk of therapy-resistant graft-versus-host disease and death. [New England Journal of Medicine]

Source: Indiana University School of Medicine

Early Indicators of Lung Cancer Probed in New Study

Many of the critical processes underlying cancer formation and eventual metastasis to other organs remain mysterious. In the quest for earlier diagnoses and more effective treatment, intensive research efforts have been applied to the search for biomarkers—presymptomatic signs of disease detectable in blood, saliva, or other biofluids.

Chad Borges, an analytical biochemist working at Arizona State University’s Biodesign Institute has been studying a particularly promising class of potential biomarkers known as glycans. His new study, appearing in the journal Analytical Chemistry, investigates the formation of aberrant glycan molecules, which have been clinically implicated in a range of deadly cancers including ovarian, prostate, pancreatic, liver, multiple myeloma, breast, lung, gastric, thyroid and colorectal.

Indeed, as the authors note, nearly every known type of tumor cell displays abnormal glycans, making them a particularly attractive candidate for biomarker discovery and validation. Until now, however, detecting the source of aberrant glycans has been frustratingly difficult.

Borges is a member of Biodesign’s Molecular Biomarkers Unit, where proteins and protein modifications are examined for their potential as markers of human disease. “Our primary work has to do with extracting proteins from blood samples or other biofluids, purifying them and examining them in an intact state through mass spectrometry,” Borges says. “We look for variants in these proteins, which in many cases include glycosylation—the focus of this paper—except in this case we looked at global changes across all blood serum proteins.”

Glycans are biological sugar polymers, made up of several different types of sugar units—glucose, mannose, galactose and others. Glycans typically adorn the surfaces of cells and can act to modify proteins. Unlike other biological polymers like DNA and proteins, however, glycans are made “on-the-go,” without a preset template. This makes their formation and behavior trickier to predict.

As Borges explains, “glycans are assembled by enzymes through a first come, first build process. In cancer, the protein enzymes that form glycans—known as glycotranserases—get overexpressed. When that happens, you get these weird glycan structures that aren’t normal.” The study found, for the first time, at least two glycotransferases displaying aberrant activity in lung cancer samples, with other abnormal glycotransferase activity strongly implied as well.

The assembly of glycans is schematically similar to a tinker toy set in which glycotransferase enzymes act to connect various wheel-like sugar units via spoke-like branching elements. Overexpression of glycotransferases produces aberrant glycans, which tend to display bushier, more profuse branching patterns when compared with their normal counterparts. (see Figure 1).

These abnormal glycans can help facilitate metastasis of cancerous cells, because their presence on cell surfaces is differentially recognized by the immune system. Instead of destroying diseased cells, the immune system leaves them alone. The abnormal glycans can also help cancer cells traverse non-native tissues, i.e. metastasize.

In the current proof-of-concept study, archived plasma samples from 30 lung cancer patients were examined, along with 29 non-cancerous control samples matched by age, gender and smoking status. The study attempted to track the immediate upstream cause of aberrant glycans, namely the glycotransferase enzymes that build them—a process that takes place in the endoplasmic reticulum and Golgi apparatus of the cell.

“Most glycomics efforts look at intact glycans, but often this is not a good molecular surrogate for the activity of glycotranferases because glycotranferases work on hundreds of growing glycan polymers,” Borges notes. “Our new, bottom-up approach looks at glycans in a different way.” To evaluate glycotranferase activity, the study pooled together the glycan polymer branching points or nodes for all of the aberrant glycan structures observed. Specific sugar subunits and linkage types characterize these glycan nodes.

A technique known as gas chromatography/mass spectrometry was used to detect glycan node levels, which were then combined to infer glycotransferase activity. The study demonstrated that a number of glycan nodes exhibited a 1:1 molecular correspondence with particular glycotranferases. The technique was used to accurately pinpoint lung cancer in blood samples with 76-88 percent reliability.

While a number of hurdles must be addressed in future research, the new technique holds the promise of a simple test capable of analyzing multiple glycotransferases simultaneously and linking abnormal activity with the aberrant glycans formed by these enzymes. The test can be carried out without the need for enzyme or antibody reagents and provides a potential means of finally harnessing aberrant glycans as useful disease biomarkers.

The method’s effectiveness is expected to further improve once information from large data sets of known patient outcome are applied and analyzed. This will hopefully permit the development of disease-specific biomarkers for a range of ailments including cancers and other inflammation-related diseases.

Applying the glycan-node strategy directly to cancerous fluids or tissues, rather than plasma/serum (where normal glycans tend to dilute the desired signal) may further enhance the test’s sensitivity. “The interesting thing is that we see widely different glycan profiles for different biofluids and different tissues, suggesting that they will be able to provide information above and beyond what blood serum alone can provide,” Borges says.

The method, once refined, may offer clinicians an extra piece of evidence on which to base decisions concerning invasive procedures (like lung biopsy or pancreatectomy) for confirming cancer diagnosis and charting appropriate treatment.

Source: Multiplexed surrogate analysis of glycotransferase activity in whole biospecimens.

Source: Arizona State University Biodesign Institute

Quintiles Releases Perspectives on Early Phase Oncology and Hematology Biomarkers

In advance of the American Society of Clinical Oncology (ASCO) Annual Meeting, Quintiles recently announced the release of its perspective on two areas of focus for clinical oncologists – the impact of patient selection in early-phase studies and the use of biomarkers in the treatment of hematologic malignancies.

The first of these reports, Tomorrow’s Path to Improved Early-Phase Oncology Drug Development, explores the importance of key elements to maximize quality and efficiency of go/no-go decisions in early-phase studies. As the understanding of the biology of cancer becomes more sophisticated and generates more opportunities, fundamental challenges caused by the complexities of this group of diseases are becoming more evident. Molecular profiling and leveraging molecular selection of patients has the potential to significantly improve the quality of early decisions in oncology drug development.

“By identifying a well defined group of patients with a particular molecular biological profile, we have the potential to make more efficient decisions on product candidates at the earliest possible stage,” said Philip Breitfeld, M.D., vice president and therapeutic strategy head, Quintiles. “As the cost of oncology drug development rises, the use of targeted therapies represents a path toward more precise treatment approaches that would drive down costs, timelines and failure rates.”

The second report, Biomarkers: Recent Advances in their Application to the Treatment of Hematologic Malignancies, presents a point of view on the value of biomarkers in the early detection and stratification of groups at risk for aggressive disease to improve the overall survival rates associated with late stage diagnosis.

Hematopoietic malignancies, which include a heterogeneous group of diseases such as multiple myeloma, lymphomas and leukemias, are characterized based on the appearance of the cells as well as demonstrating the presence or absence of certain cell surface proteins (Cluster of Differentiation or CD markers), characteristic chromosomal abnormalities, and by the identification of particular genetic mutations.

“While the use of biomarkers is widely supported and the hope of early detection is promising, few biomarkers have been identified or clinically validated for the early detection, progression or risk assessment for such malignancies,” said Harish Dave, M.D., MBA, vice president, global medical strategy head, hematology and oncology, oncology therapeutic area, Quintiles. “Recent advances in understanding of these malignancies and the advent of high-throughput technologies have the potential to facilitate rigorous translational research toward the discovery, development and clinical validation of novel biomarkers.”

Source: Quintiles

Firm Hopes Big Data Can Personalize Health Care

When Colin Hill’s father was diagnosed with later-stage prostate cancer last summer, he was treated the same as every other patient with the illness.

This standardized approach bothered Hill, who believes medicine should approach each patient’s illness as unique, with medication tailored to the person’s history and biology.

“You show up to the hospital, and it’s like Groundhog Day,” Hill said, with patients being cared for the same way, over and over again. “It’s this outdated standard of care created for this hypothetical average patient. But no one’s an average patient.”

A genetic analysis of the tumor in his 69-year-old father, Foster Hill, found he had a genetic variant of the cancer that does not usually respond well to the hormone therapy Lupron, the current standard of care. But not knowing what else would work, doctors gave Foster Hill Lupron anyway. Luckily, the treatment seems to be helping, and his father’s outlook is much improved.

Hill hopes a Kendall Square company he founded 13 years ago, GNS Healthcare, will eventually improve medical care for his father — and for countless others — by providing personalized treatment. GNS is among the leaders in using Big Data analytics to learn more about diseases, patients, and treatments.

With data from thousands of cases, GNS uses artificial intelligence to determine what treatment made the crucial difference for each patient.

The company is deploying enormous computing power to produce a more complete understanding of treatments for rheumatoid arthritis, diabetes, cancers, and other illnesses.

For example, it is working with the Dana-Farber Cancer Institute and Mount Sinai Medical School to build a computer model of multiple myeloma, so researchers can better understand what works well for patients today, as well as develop more effective treatments for the blood cancer. It is involved in a similar collaboration with Brigham and Women’s Hospital and several other partners to learn more about multiple sclerosis.

Harvard Medical School recently agreed to use a GNS computing platform to analyze how cells replicate or transform into different types, for insights into­ conditions such as cancer and neurodegenerative diseases, Hill said.

And the company has a partnership with the Centers for Medicare & Medicaid Services and Health Services Advisory Group to assess health care quality measures, as well as other recent deals with pharmaceutical companies, hospitals, and advocacy groups, and the insurance giants Aetna and Blue Cross Blue Shield.

“It’s exciting times for us,” Hill said, after 13 years of developing his approach to analyzing health care. “We are now in the thick of things.”

Hill did not always have such an absorbing interest in science. He went to college at Virginia Tech — mainly to play tennis. “I was more serious than I was good,” he quipped.

But while there, he became fascinated by physics and chaos theory — the idea that complex patterns could result from simple rules.

His imagination was stoked by a summer job in 1996 at Santa Fe Institute, an interdisciplinary research center focused on highly complex issues. Hill then went on to graduate from McGill and then Cornell University.

By then, the Human Genome Project was becoming a reality, capturing the attention of many scientists, including a young Hill.

“That’s when two and two came together,” Hill said. “It was like ‘Oh yeah, the stuff we’re doing, though it’s pretty theoretical, it is going to be the thing that links these pieces together,’ ” including chaos theory, genetics, Big Data, and health care.

Now he’s in the middle of the so-called Big Data revolution in health care. Companies such as GNS have an enormous capacity for crunching troves of information on patients, diseases, and medical outcomes collected by medical providers, insurers, and other big players.

Hill likes to say he wants GNS to capture the “data exhaust thrown off” by every interaction a patient has with the health care system, from the doctor’s office to the hospital to the pharmacy. A bad reaction to medication is a data point worth having; ditto for other side effects, as well as results of all kinds of procedures and interventions — bad or good.

While such data sets are getting easier to find, Hill said, genetic information is still too expensive to be truly useful.

“What we don’t have yet for my dad and for other men with prostate cancer is a large coherent set of data on prostate cancer patients that includes the molecular level,” Hill said.

With information aggregated from thousands of cases, Hill said, GNS uses artificial intelligence algorithms developed out of chaos theory to determine what treatment made the crucial difference for each patient, and with it what is likely to work best for the next patient — rather than simply trying one medication after another, as is often done today.

“What we’re trying to get at is not just patterns and trends, but reverse engineer the mechanisms that gave rise to the data,” he said. “We’re trying to find the cause-effect relationships within the data.”

This ability to predict results is what sets GNS apart, said Dr. Atul Butte of Stanford University, one of the academic leaders of the Big Data movement. That’s the “nifty part of their technology,” Butte said.

Alexis Borisy, a partner at the Boston life sciences venture capital firm Third Rock Ventures, said GNS is in the vanguard of Big Data companies analyzing health care information.

“They’ve had a chance to learn, refine, and they’ve kept with it so they’ve had a lot of experience to build on,” Borisy said.

He and Hill have known each other since they were young business executives more than a decade ago, and he said he has tremendous respect for Hill’s intelligence, persistence, and communication skills.

“He is one of the visionaries in the space,” said Borisy, who also serves as chairman of Foundation Medicine, a molecular information company, and interim chief executive of Warp Drive Bio, both of Cambridge. “I think it’s fair to say he’s kept GNS growing and building by the force of his personality and the force of his efforts.”

Source: The Boston Globe

OGT Expands Commitment to Improved Cancer Profiling with CCMC Deal

Oxford Gene Technology (OGT), provider of innovative genetics research and biomarker solutions to advance molecular medicine, announced today that it has signed a licence agreement with the Cancer Cytogenomics Microarray Consortium (CCMC) to design a whole genome, cancer-specific microarray.