Supported Projects and Meetings

  • “Genomics meets mathematics: inferring the evolutionary dynamics of breast cancer” Seed Grant (2017) PIs are Marc Ryser, Shelley Hwang, and Rick Durrett, Duke University. Each year, over 60,000 US women are diagnosed with ductal carcinoma in situ (DCIS) of the breast. In as many as 60%-80% of these women, DCIS would never progress to invasive and harmful breast cancer during their lifetime. However, because it is difficult to predict which DCIS will eventually progress to cancer, virtually all patients undergo invasive surgery after diagnosis. In other words, each year as many as 45,000 women will undergo radical overtreatment for a lesion that would not cause any harm in their remaining lifetime. To identify these women, and offer them the option of active surveillance in lieu of radical surgery – as is common in early stage prostate cancer – we need to better understand the evolutionary process that governs the initiation and growth of DCIS. The goal of this study is to combine genomic data with mathematical modeling to improve our understanding of the clonal evolution in DCIS, and to derive risk markers that can be used in the process of clinical decision making. In particular, we hypothesize that the degree of subclone mixing in DCIS can predict the risk of progression to invasive disease, and could be used to avoid overtreatment.

  • “A cross-species analysis of the mutational landscape of cancer” Seed Grant (2017) PIs are Jeff Thorne, Jason Somarelli, Seth Faith, and Matthew Breen, North Carolina State University and Duke University. Cancer cells harbor cancer-causing mutations that are absent in normal cells. Knowing which mutations are responsible for a patient’s cancer provides insight about proper treatment. Although modern technology facilitates identification of mutations harbored by cancer cells, it is difficult to determine exactly which set of mutations actually caused the cancer. The problem is that many mutations experienced by cancer cells have little or no effect. We are hoping to develop an approach for understanding which mutations cause cancer and which do not. Evolutionary information is employed because many mutations observed in cancer have not been directly proven to induce cancer. The evolutionary information comes from comparing DNA sequences of different species. The data from non-human species are valuable because DNA differences between species represent mutations that survived; surviving mutations are unlikely to cause cancer. However, careful attention needs to given to the fact that sometimes a mutation causes cancer in one species but not in another. To properly account for this, we propose to collect new data on cancer-causing mutations from non-human species and combine these with existing human cancer data.

  • “Applying  evolutionary principles to the study of cancer progression and therapy resistance” Seed Grant (2016) PIs are Jason Somarelli and Will Eward, Duke. Cancer represents a breakdown of normal tissue maintenance in which cells acquire the ability to grow uncontrolled. This uncontrolled growth is often treated with surgery, followed by chemotherapy and/or radiation. In many cases, these treatments significantly prolong life and can even lead to cures in some cancer types. However, some cancer cells that are treated with chemotherapy/radiation acquire additional alterations that enable them to become resistant. The emergence of drug/radiation-resistant cells is governed by evolutionary forces of natural selection and survival of the fittest. In the presence of the therapy, resistant cells have a fitness advantage over sensitive cells. As the sensitive cells die off in response to treatment, the resistant cells emerge and begin to take over the population. Interestingly, however, the resistant cells are often less fit than the treatment-sensitive cells when the treatment is removed. We hypothesize that these differences in fitness can be exploited to control the relative populations of treatment-sensitive and treatment-resistant cells during cancer growth. To test this hypothesis, we will use experimental data and phylogenetic analyses of publically-available data to determine whether we can take advantage of the differences in fitness between these cell types to better control tumor growth and further prolong survival.

  • “Screening for Novel Kinase Inhibitors to Combat Drug Resistance in Pancreatic Cancer” Seed Grant (2016) PIs are Antonio Baines and Lee Graves, North Carolina Central University and UNC-Chapel Hill. Drug resistance is a major barrier when it comes to successfully treating cancers, such as pancreatic cancer, demonstrating the need for better and more improved drugs. Unfortunately, treatment with cancer drugs (ex. kinase inhibitors) can potentially lead to the acquiring of DNA mutations in the cell which can help to promote drug resistance. Also, compensatory cell signaling pathways can become activated after treatment resulting in drug resistance. In order to address these concerns, we are proposing to develop a high throughput screening method for identifying novel kinase inhibitors that can impede cancer cell growth as well as enhance existing therapies for pancreatic cancer through better combination strategies.

  • “Comparative Oncology In Animal and Human Health” Symposium (April 7th 2015): A symposium to connect medical students at Duke and UNC with veterinary students at NC State. The event at the North Carolina Biotechnology Center featured speakers Dr. William Eward, MD, DVM, Duke Medicine,  Dr. Matthew Breen, PhD C.Biol FSB, NCSU College of Veterinary Medicine, and Dr. Kristy Richards, MD, Ph.D., Cornell College of Veterinary Medicine. The event was co-sponsored with NC State* and NC One Health Collaborative.

  • PhyloOncology: the phylogenetics of cancer evolution (June 5-7th 2015) Organizers: Rui Diogo, Howard University, Nicolaas Fourie, NIH, and Jason Somarelli, Duke University. The past decade has seen the generation of enormous amounts of ‘omics data from a wide variety of cancer samples. Yet, despite these tremendous research efforts, our understanding of the evolution of cancer is still in its infancy. Part of the problem is not in the acquisition of the data, per se, but in the way we have been analyzing these data. Current methods of disease subtyping view diseases as discrete, identifiable entities. At a gross level this may be accurate, but it belies the complexity of natural systems. The limitations in current subtyping approaches are, in part, due to the nature of statistical interrogation, which requires discrete groups to be identified and then compared and repeated in subsequent independent populations. Phylogenetics, on the other hand, views diseases/cancers as lying on a continuum of accumulating changes. Our group is applying phylogenetics analyses to the vast array of ‘omics data to understand the position of individual patients on this continuum from early disease through metastatic progression. We postulate that phylogenetics can be applied to early detection of cancer and the identification of novel cancer subtypes.

  • Beyond Peto’s paradox with the geriatric Peromyscus (2016) Organizers: Corbin Jones, UNC-Chapel Hill, Peter Waddell, Ronin Institute, Matt Kanke, UNC-Chapel Hill, Jeremy Wang, UNC-Chapel Hill, Kim Creek, USC, Lucia Perisi, USC. Cancer is a heterogeneous or widely divergent collection of diseases with a similarly wide variety of outcomes, natural histories and responses to therapy. While new medical and genomic data have shed light on the molecular mechanisms causing cancer, why cancer should occur is the first place remains unclear. Equally perplexing is why some organisms or individuals seem more or less likely to get cancer. This project uses the unique biology of deer mice (Peromyscus) species to identify the genes contributing to longevity and cancer resistance in P. leucopus, the white-foot dear mouse. Since the 1950s its been known that P. leucopus is very long lived for such a small rodent and has a similarly low rate of cancer compared to common or laboratory mice. Our project will use comparative genomic comparisons between P. leucopus and its close relatives to discover the extraordinary ways these animals have “invented” to reduce cancer.