Cancer is at its heart a genetic disease, a progression from normal cells to abnormal, precancerous, then cancer cells. What drives cells from normal to cancerous cell are the changes to the genes inside those cells. Every type of cancer, from breast cancer to pancreatic cancer, has subtypes. Each subtype has a different cause and requires different treatments. For that reason, some of the most promising advances in cancer research involve finding the genetic markers at the root of the many forms of cancer.
HudsonAlpha researchers are uniquely positioned to take on the work of uncovering the genetic causes of many different forms of cancer. The Institute has the most advanced available genomic technologies and expertise to examine all of the genes in the human genome at once in order to answer key questions about cancer. Our labs are discovering the differences among cancer subtypes and using those discoveries to develop tests for early detection and diagnosis. Because we look at the whole genome, we are also able to identify promising targets for new drugs. Finally, we are finding the genetic differences that distinguish people who respond to a particular cancer treatment from those patients who, unfortunately, do not. That knowledge can help physicians give their patients the right treatment at the right time.
Experts at HudsonAlpha are working to provide physicians with a more targeted approach to treating estrogen receptor positive breast cancer, the most common type of breast cancer. In a clinical trial, our scientists are testing a particular drug combination that has not been used before, and they are looking for the biomarkers, or clues in our DNA, that will help physicians predict who will respond to the new drug therapy.
HudsonAlpha investigators have identified a set of genes in a particular form that is a biomarker for kidney cancer. Biomarkers are measurable characteristics of biological processes that can indicate either normal activity or the presence of something disease-causing in cells. Our scientists are using the genomic biomarker for kidney cancer that we discovered to develop a new screening method. Instead of using an invasive kidney biopsy to test for cancer, the new method could look for that biomarker in blood or urine, alerting a physician to a patient’s increased risk for kidney cancer. Because of its relative simplicity, the test could even become part of standard medical screening.
Our researchers are measuring gene expression patterns in ovarian cancer in order to investigate how ovarian tumors differ among different ethnicities. Gene expression is the process through which an inherited gene becomes a physical trait, whether the trait is a particular feature in a cell or eye color. This work could identify a biomarker for ovarian cancer, which has a high survival rate when it is detected early. In addition, Institute scientists are exploring whether genomic profiling could help predict how patients respond to a specific drug treatment for ovarian cancer. Genomic profiling is a method used to learn about all of the genes in a specific cell type – in this case ovarian cancer cells. The method examines how those genes interact with each other and with the environment. Investigators working on this project are also identifying new drugs that could be used to treat ovarian cancer, and they are looking for genetic clues to help them predict how a patient will respond to standard ovarian cancer treatments.
Using cutting-edge sequencing tools, HudsonAlpha investigators have identified a biomarker that distinguishes between two very different types of pancreatic cancer. One type is very aggressive and the other progresses more slowly. We are working on a clinical trial that will confirm the biomarker can be used to help physicians predict which pancreatic cancer patients should be treated with the most intensive treatments available and which patients could try less intrusive therapies first. This distinction is crucial for pancreatic cancer patients because those intense treatments can be incredibly difficult to endure and are sometimes even toxic themselves.
HudsonAlpha investigators are leveraging our 2012 discovery of a biomarker associated with recurrence in prostate cancer patients. This prostate cancer signature indicates if a cancer is likely to be aggressive, requiring equally aggressive therapies. We are pursuing our biomarker discovery from its current early stages into product development as a prognostic tool. More recently, we identified a set of biomarkers that distinguish cancerous tissue from healthy tissue in prostate cancer. Now, we are developing a predictive test for prostate cancer that would screen for that biomarker in the bloodstream. Because we are screening through the whole genome, we can also identify potential new targets for drug therapies.
Researchers at the Institute have identified another biomarker that could be used to diagnose colon cancer in very early stages using a blood or urine test. The test would be less invasive than other current methods for detecting colon cancer, so individuals would be more likely to receive an earlier diagnosis and a better prognosis.
In addition to research projects in childhood genetic diseases, Institute scientists are working to improve pediatric cancer research and help children who suffer from these terrible diseases. In partnership with St. Jude’s Children’s Research Hospital, HudsonAlpha researchers are leveraging the Institute’s sequencing and analysis expertise to produce high-quality data for the research community that can be used to develop better tools for diagnosing and treating pediatric cancers.
Analyzing Genomic Data on Cancer
Genomic analysis generates massive amounts of data. New discoveries are often buried in the data waiting for the right analytical tool to dig them out. Researchers at HudsonAlpha have recently created such a tool that they used to analyze cell proliferation in 19 different cancers. Proliferation is a hallmark of cancer; it is how cancer cells increase through cell growth and division. This hallmark is also the target of many cancer treatments. The analysis tool developed at HudsonAlpha found a connection between proliferation signatures with survival rates in seven types of cancer. The analysis also identified new genes linked to tumor proliferation. The scientists were also able to identify drugs that effectively target the proliferating genes. These results, uncovered by data analysis and machine learning rather than laboratory experiments, could help physicians provide a more accurate prognosis for their patients. The analytical tool can also be used to improve cancer research and to make more discoveries in large sets of cancer data.