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Open Access to Large Scale Datasets Is Needed to Translate Knowledge of Cancer Heterogeneity into Better Patient Outcomes
The February Issue of PLOS Medicine includes two studies that relate intratumoral heterogeneity to clinical cancer outcomes. James Rocco and colleagues analyzed data from The Cancer Genome Atlas (TCGA) to show that tumor heterogeneity can serve as a prognostic indicator in head and neck squamous cell carcinoma (HNSCC), and James Brenton and colleagues found higher levels of tumor heterogeneity to be associated with decreased survival in serous ovarian cancer.
In a Guest Editorial, Andrew Beck of Harvard Medical School discusses how these two studies support the idea that molecular characterization of large sets of cancer samples can lead to improved personalized therapies for cancer.
Image Credit: Christian Schnettelker, Flickr
Citation: (2015) PLoS Medicine Issue Image | Vol. 12(2) February 2015. PLoS Med 12(2): ev12.i02. https://doi.org/10.1371/image.pmed.v12.i02
Published: February 27, 2015
Copyright: © 2015 Schnettelker. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The February Issue of PLOS Medicine includes two studies that relate intratumoral heterogeneity to clinical cancer outcomes. James Rocco and colleagues analyzed data from The Cancer Genome Atlas (TCGA) to show that tumor heterogeneity can serve as a prognostic indicator in head and neck squamous cell carcinoma (HNSCC), and James Brenton and colleagues found higher levels of tumor heterogeneity to be associated with decreased survival in serous ovarian cancer.
In a Guest Editorial, Andrew Beck of Harvard Medical School discusses how these two studies support the idea that molecular characterization of large sets of cancer samples can lead to improved personalized therapies for cancer.
Image Credit: Christian Schnettelker, Flickr