Prognostic gene signatures for non-small-cell lung cancer

By Paul C. Boutros, S. K. Lau, M. Pintilie, Ni Liu, F. Shepherd, S. Der, Ming-Sound Tsao, Linda Z. Penn, Igor Jurisica. 2009

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EgoNet: identification of human disease ego-network modules (2014, background): “In the past decade, extensive work has been done to identify differentially expressed genes across different phenotypes, which can be used as diagnostic markers for classifying different disease states or predicting clinical outcomes [4-7].”
Differential methylation analysis for BS-seq data under general experimental design (2016, background): “Among those 44 genes reported from DSS-general, many of them have been previously reported to be related to lung cancer, for example, KLF6 (Spinola et al., 2007), KLF2 (Xie et al., 2011), KLC1 (Togashi et al., 2012), PCSK6 (Hawes et al., 2010), MAFK (Boutros et al., 2009).”
SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis (2013, background): “The first NSCLC biomarker was proposed by Boutros et al. [17] and contains the following genes: STX1A , HIF1A , CCT3 , HLA-DPB1 , RNF5 , and MAFK .”
Gene Expression-Based Classification of Non-Small Cell Lung Carcinomas and Survival Prediction (2010, methodology): “Nonetheless, our signatures performed well compared to those previously reported [20,21,22,24,25,26] when tested using the Erasmus MC and Duke University cohorts.”
Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes (2012, background): “lung cancer [6–8], lymphomas [9–13], leukemia [14,15], and”