Our goal is to identify genomic changes in breast cancer that are relevant to patient care. We use sequencing assays to characterize DNA methylation and messenger RNA from breast cancer cell lines, primary tumors, and metastatic tumors. We use Reduced Representation Bisulfite Sequencing (RRBS) to quantify DNA methylation at millions of loci across the genome, and we use RNA-seq to characterize the whole transcriptome. We analyze RNA-seq data to quantify gene expression, characterize novel isoforms of known genes, identify novel transcribed regions in the genome, and detect expressed mutations and gene fusions. We analyze these data in different patient cohorts to look for biomarkers that predict long-term prognosis. We also analyze samples collected from patients enrolled in clinical trials to identify biomarkers that predict response to specific therapies. In addition to identifying biomarkers, we also integrate these data to identify molecular pathways associated clinical outcome or resistance to treatment. We hope to identify pathways driving breast cancer progression that can be targeted by therapeutics used to treat other malignancies, in addition to identifying pathways that are candidates for the development of novel targeted therapies.
Kidney cancer is one of the ten most prevalent cancers in men and woman, affecting nearly 60,000 new people annually in the United States alone. When the patient is diagnosed and the tumor is resected while still localized to the kidney, prognosis is relative good; however, survival rates drop dramatically with local and distant metastasis. While treatment for these advanced cases has improved in recent years, the best drugs only increase disease free progression after resection by months. We are using high-throughput sequencing and array technologies to investigate the role of copy number variation and DNA methylation in kidney tumors and adjacent normal tissues. We hope to identify global molecular signatures distinguishing clinically significant classes of patients, as well as diagnostic and prognostic biomarkers, novel pathways associated with kidney cancer etiology and progress, and potential therapeutic targets.
The American Cancer Soceity reports that in 2012, ~43,920 individuals will be diagnosed with pancreatic cancer, and ~37,390 patients will succumb to the disease. The high mortality rate associated with pancreatic cancer is due to the late diagnosis of most patients; once the cancer has metastasized away from the pancreas, surgical resection is no longer a viable treatment option, and these patients are treated with palliative chemotherapeutics. The currently used chemotherapuetics only provide a modest improvement in patient survival time, as pancreatic tumors exhibit a high degree of chemotherapeutic resistance. We are utilizing high-throughput next-generation sequencing technologies such as RRBS, RNA-seq and microRNA sequencing to investigate molecular differences between pancreatic tumor tissue and patient-matched benign-adjacent pancreatic tissue. We hope to identify novel cellular pathways for therapeutic intervention and discover molecular signatures that can be useful for early detection of pancreatic cancer.
Prostate tumors frequently exhibit altered DNA methylation and gene expression patterns when compared to adjacent normal tissue. These disease-specific changes are promising candidate biomarkers due to their specificity. There is a clear need to identify novel, noninvasive biomarkers for the diagnosis and prognosis of prostate cancer. Current diagnostic tools for prostate cancer lack the sensitivity and specificity required for the detection of very early prostate lesions and diagnosis ultimately relies on an invasive biopsy. Once prostate cancer is diagnosed, there are no available prognostic markers for prostate cancer that provide information on how aggressively the tumor will grow. Therefore, more intrusive therapeutic routes are often chosen that result in a drastic reduction in the quality of life for the patient, even though the majority of prostate tumors are slow growing and non-aggressive. To identify candidate diagnostic and prognostic biomarkers that can be used to molecularly distinguish patients with less aggressive tumors, we are studying DNA methylation patterns in human prostate tumor tissues and patient-matched benign adjacent tissues using Reduced Representation Bisulfite Sequencing (RRBS) and the Illumina Methyl450 array. In addition, we are measuring mRNA and microRNA expression patterns using RNA-seq and microRNA sequencing in these prostate tissues. By integrating the datasets from each of these methods, we hope to discover pathways involved in prostate cancer that can be targeted by therapeutics, and identify diagnostic and prognostic biomarkers on a genome-wide scale.