Transcriptional regulation of gene networks involved in cancer
University of Colorado Anschutz Medical Campus, Pharmocology Department
There are diverse projects available in the Espinosa lab all centered on understanding gene networks in cancer. Current Projects include:
1) Understanding Hypoxia-inducible gene networks
2) the genes and mechanisms related to p53-cell type specific responses in cancer
3) the molecular mechanisms of p63-driven oncogenesis in squamous cell carcinomas
4) the genomics and molecular networks in trisomy 21 individuals.
The student will work under the guidance of Instructors and Post-docs in the lab to conduct experiments related to their selected research project and experimental aims. Lab work will include work involving culturing cancer cells and associated molecular and biochemical approaches (RNA/DNA/Protein isolation, Immunobloting, RT-PCR, Chromatin Immunoprecipitation, etc.). The student will present their experimental findings to the laboratory and at the Cancer Center poster session.
Our main research goal is to understand how gene networks control cell behavior and how to tame pleiotropic transcription factors for therapeutic purposes. Cancer is our primary motivation, but our discoveries often lead us into other
areas of biology. We define cancer as a disease of gene networks gone awry. Our research focuses on the molecular mechanisms by which cancer-relevant genes regulate the networks in which they are embedded. We believe that this type of basic research is
a requisite step in the development of effective cancer therapeutics. This field is broad with many important questions, which inspires us to constantly expand our repertoire of approaches and technologies to find answers.
Much of our research enterprise focuses on the p53 gene network. p53 is the most commonly mutated gene in human cancer and our research may enable effective cancer therapies. We also study other cancer related genes, such as the oncogenes CDK8, HIF1A and p63.
We employ biochemical, molecular biology and cell biology approaches, as well as various genomics approaches using onsite next-generation DNA sequencing and Functional Genomics facilities administered by our lab. We have developed an in-lab bioinformatics practice that allows us to rapidly transition from the computational analysis of genomics data to hypothesis-driven experiments at the bench.