Author Interviews, Breast Cancer, Genetic Research / 10.01.2015
Tumor Marker E2F4 Linked to Breast Cancer Survival
MedicalResearch.com Interview with:
Dr. Chao Cheng PhD
Department of Genetics
Geisel School of Medicine at Dartmouth
Hanover 03755, NH
MedicalResearch: What is the background for this study? What are the main findings?
Dr. Chao Cheng: Cancer survival prognosis—“How long do I have, Dr.?” is a topic of great importance to cancer patients and their families. While clinical and pathological variables, such as cancer type, stage, grade, and patient demographics, have long been used to predict survival outcomes, only recently have molecular signatures become incorporated into survival prediction. A molecular approach holds great promise for improving prediction accuracy and additionally elucidating mechanisms of disease, however it is fraught with difficulty due to assay “noise” and “big data” statistical issues, such as the multiple comparisons problem
In this study, we began by analyzing transcription factor binding profiles across available cell lines. By restricting our analysis to transcription factors, DNA expression regulators known to be involved in tumor genesis, we reasoned that we could avoid many of the “big data” issues and achieve results that would make mechanistic and biological sense. We first employed a statistical method we described previously to calculate which genes were the major downstream targets of our transcription factors. With these targets identified, we then analyzed gene expression data using a bioinformatics method to infer the relative activity of each transcription factor based upon the overall expression levels of their gene targets. From here, we incorporated cancer survival data and examined how each transcription factor’s regulatory activity did, or did not, correlate with survival.
The most prognostic transcription factor was E2F4, a member of the E2F family and a known regulator of the cell cycle. We therefore restricted our analysis to E2F4 and examined how its activity level impacted survival in breast cancer patients.
We found that tumors with high E2F4 regulatory activity as compared to low E2F4 regulatory activity had much worse survival outcomes. These results were stable even after controlling for tumor stage, grade, patient age, and treatment, and were based on data from over 1900 patients across eight independent datasets. These results demonstrate that E2F4 is an independent and enhancing predictor of survival above the currently examined variables.
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