Methods S1 - Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and Prognosis

This file contains: Figure S1 Distributions of stemness bipartition diagonal linear discriminant (DLD) scores in each dataset. In the ovarian cancer datasets, the DLD scores were all bimodal, and Gaussian mixture modeling [39] of the score was used to classify the lower scoring group as differentiated and the higher scoring group as stem-like. In the breast cancer datasets, mixture modeling was still used to discover approximate stem-like and differentiated classes, despite lack of clear bimodality. The range of scores is inconsistent in different datasets, because genes were often lost when crossing microarray platforms and potentially because of batch effects across datasets. Table S1 Proliferation genes (see Supplementary Methods) that were removed from the set of 83 GeneSigDB [35] gene signatures that were used for class discovery with ISIS [33]. After removing these genes, 2,632 genes were still used for class discovery.Table S2 Genes used to generate the stemness bipartition and their corresponding weights when predicting the bipartition in other datasets, as well as pooled t-statistics for differential expression between the stem-like and differentiated subtypes. Negative weights correspond to the differentiated subtype and positive weights correspond to the stem-like subtype. Table S3. A list of the 83 gene signatures from GeneSigDB [35] that are reported to be associated with stem cells. Table S4 The 13 gene sets used by Ben-Porath et al. to characterize classes of cancer as stem cell-like or differentiated. Genes in these gene sets were limited to those that were in the DNA microarray platform (Affy U133 Plus 2.0 platform) of the AOCS data [10]. Table S5 Gene-Set-Enrichment p-values for enrichment in stem-like and differentiated subtypes for all of the curated gene sets on MSigDB v 3.0. No multiple testing correction was used. Table S6 Gene-Set-Enrichment p-values for enrichment in stem-like and differentiated subtypes for all of the Gene Ontology gene sets on MSigDB v 3.0. No multiple testing correction was used. Table S7 Genes over-expressed in breast cancer cells containing wild type and mutant p53 from Figure 5 of Troester et al. [47] and Table 1 of Takahashi et al. [48] and whether they are over-expressed in the stem-like or differentiated subtype. P-value is for over-expression in either the stem-like or differentiated class and was calculated with the likelihood ratio test for logistic regression. Only genes in the AOCS dataset were considered. No multiple testing correction was performed. In the Troester et al., the Gene-Set-Enrichment p-value for enrichment of mutant p53 genes in stem-like subtype was 0.00004 and p-value for enrichment of WT p53 genes in differentiated subtype was 0.00005. These p-values were 0.00008 and 0.05144, respectively, in the Takahashi et al. signature. (DOCX)