2015
DOI: 10.1186/s12864-015-1687-x
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Tumor characterization and stratification by integrated molecular profiles reveals essential pan-cancer features

Abstract: BackgroundIdentification of tumor heterogeneity and genomic similarities across different cancer types is essential to the design of effective stratified treatments and for the discovery of treatments that can be extended to different types of tumors. However, systematic investigations on comprehensive molecular profiles have not been fully explored to achieve this goal.ResultsHere, we performed a network-based integrative pan-cancer genomic analysis on >3000 samples from 12 cancer types to uncover novel strat… Show more

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Cited by 34 publications
(31 citation statements)
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“…It is generally understood that HNSC and LUSC are molecular similar, as these cancer types tend to cluster together in pan-cancer unsupervised clustering analyses (21,67,68). Our analysis revealed a particularly striking correlation of the NSD1 subtypes between these two tumor types, revealing NSD1 inactivation as a driver of this novel molecular pan-cancer group.…”
Section: !mentioning
confidence: 63%
“…It is generally understood that HNSC and LUSC are molecular similar, as these cancer types tend to cluster together in pan-cancer unsupervised clustering analyses (21,67,68). Our analysis revealed a particularly striking correlation of the NSD1 subtypes between these two tumor types, revealing NSD1 inactivation as a driver of this novel molecular pan-cancer group.…”
Section: !mentioning
confidence: 63%
“…While this study aims at exploring the association of breast cancer histologic grade and those driver genetic changes and their interactions, it will be also important to further correlate or integrate our findings with other novel genome based molecular classifiers434445464748. Such an effort may significantly improve our approach towards more precise or personalized breast cancer therapy.…”
Section: Discussionmentioning
confidence: 95%
“…Since then, the method has become a cornerstone of cancer genome analysis. Hofree et al [6] used a network propagation method (Network-Based Stratification, or NBS) to cluster cancer patient data, Paull et al [7] identified causal paths linking mutations to expression regulators, and Liu et al and Zhong et al [8,9] applied the NBS method across a wide variety of cancer types.…”
Section: Introductionmentioning
confidence: 99%