Independent Component Analysis Uncovers the Landscape of the Bladder Tumor Transcriptome and Reveals Insights into Luminal and Basal Subtypes

Abstract

Extracting relevant information from large-scale data offers unprecedented opportunities in cancerology. We applied independent component analysis (ICA) to bladder cancer transcriptome data sets and interpreted the components using gene enrichment analysis and tumor-associated molecular, clinicopathological, and processing information. We identified components associated with biological processes of tumor cells or the tumor microenvironment, and other components revealed technical biases. Applying ICA to nine cancer types identified cancer-shared and bladder-cancer-specific components. We characterized the luminal and basal-like subtypes of muscle-invasive bladder cancers according to the components identified. The study of the urothelial differentiation component, specific to the luminal subtypes, showed that a molecular urothelial differentiation program was maintained even in those luminal tumors that had lost morphological differentiation. Study of the genomic alterations associated with this component coupled with functional studies revealed a protumorigenic role for PPARG in luminal tumors. Our results support the inclusion of ICA in the exploitation of multiscale data sets.

CRISPR-Cas9 screen reveals a MYCN-amplified neuroblastoma dependency on EZH2

“…In addition, a singlesample enrichment analysis for rank-normalized CERES gene effects across the mammalian protein complexes in the CORUM database (38) demonstrated that neuroblastoma is the cancer type most dependent on the EED/EZH2 complex compared with all other cancer types screened ( Figure 1C and Supplemental Figure 1A). The EZH2, SUZ12, and EED dependency scores demonstrate individual dependency across subused for the analysis of biological data that involve higherorder associations, such as identifying tumor-related pathways in transcriptional data sets, classifying disease lineages, characterizing transcriptional regulators, and identifying disease-specific biomarkers (31)(32)(33)(34)(35)(36)(37). Thus, we applied ICA to rank-normalized CRISPR-Cas9 screening data and identified the top 3 independent components (IC1, IC2, and IC3) that were significantly depleted in neuroblastoma compared with other cancer cell lines screened ( Figure 1A).…”

Trends and disparities in the use of neoadjuvant chemotherapy for muscle-invasive urothelial carcinoma

“…Genomic 'subtypes' and genetic alterations with distinct molecular profiles and varied response to NAC have been described [19][20][21][22][23] . As our understanding of MIBC biology continues to evolve, more 'personalized' treatment decisions will allow us to better select chemo sensitive tumors.…”

Identification of hub genes and pathways associated with bladder cancer based on co-expression network analysis

“…Dyrskjøt et al (11) detected carcinoma in situ gene expression that is reflected in carcinoma in situ biopsies and superficial transitional cell carcinoma. Biton et al (12) demonstrated that a molecular urothelial differentiation program was maintained by applying independent component analysis to bladder cancer transcriptome data and exploiting additional molecular and clinic pathological data.…”