A major challenge facing cancer researchers is the identification and treatment of drug resistant cancers. In a new guest editorial published in PLOS Medicine Andrew Beck, from Harvard Medical School, Boston, argues for enabling the sharing of Omics and clinical data among a large community of cancer researchers and data scientists in order to maximize the translation of research into better individual patient outcomes.
Cancer is a heterogeneous disease across patients as well as a heterogeneous disease within individual patients. Different regions of a tumor often have different molecular features at the genetic and protein levels, and this intra-tumoral molecular heterogeneity is thought to cause drug resistance and treatment failure in cancer. The editorial reflects on two research articles recently published in PLOS Medicine focused on cancer heterogeneity. One study by James Brenton and colleagues demonstrated that treatment resistance in high-grade, serous ovarian cancer can be predicted using a newly developed algorithm that measures intra-tumoral genetic heterogeneity. In a separate paper, James Rocco and colleagues analyzed publicly available, whole-exome sequencing data from The Cancer Genome Atlas to show that a simple quantitative measure of intra-tumoral heterogeneity (mutant-allele tumor heterogeneity) is associated with prognosis in Head and Neck Cancer.
Both of these new methods for measuring intra-tumoral heterogeneity require further testing and validation before they can be utilized in the clinic. However, Dr Beck notes, “[t]he continuing generation of high-quality, open-access Omics data sets from large populations of cancer patients will be critically important to enable the development of computational methods to translate knowledge of cancer heterogeneity into new diagnostics and improved clinical outcomes….”
Dr Beck concludes, “[e]nsuring open access to high quality datasets will ensure that the largest possible community of researchers is able to address the most important problems in cancer medicine today.”
Open Access to Large Scale Datasets Is Needed to Translate Knowledge of Cancer Heterogeneity into Better Patient Outcomes, Beck AH, PLoS Med, doi:10.1371/journal. pmed.1001794, published 24 February 2015.
AHB was supported by funding from the Susan G. Komen for the Cure Foundation under Award Number CCR14302670 and the National Library Of Medicine of the National Institutes of Health under Award Number K22LM011931. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
AHB has read the journal’s policy and has the following conflicts: AHB is on the Medical Advisory Board for Definiens and the Editorial Board of PLOS Medicine.