Summary By analyzing gene expression data in gliobastoma in combination with matched microRNA profiles, we have uncovered a post-transcriptional regulation layer of surprising magnitude, comprising over 248,000 microRNA (miR)-mediated interactions. These include ~7,000 genes whose transcripts act as miR ‘sponges’ and 148 genes that act through alternative, non-sponge interactions. Biochemical analyses in cell lines confirmed that this network regulates established drivers of tumor initiation and subtype, including PTEN, PDGFRA, RB1, VEGFA, STAT3, and RUNX1, suggesting that these interactions mediate crosstalk between canonical oncogenic pathways. RNA silencing of 13 microRNA-mediated PTEN regulators, whose locus deletions are predictive of PTEN expression variability, was sufficient to downregulate PTEN in a 3′ UTR-dependent manner and to increase tumor-cell growth rates. Thus, this miR-mediated network provides a mechanistic, experimentally validated rationale for the loss of PTEN expression in a large number of glioma samples with an intact PTEN locus.

We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.

SUMMARY This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smoking and/or human papillomavirus (HPV). SCCs harbor 3q, 5p, and other recurrent chromosomal copy-number alterations (CNAs), DNA mutations, and/or aberrant methylation of genes and microRNAs, which are correlated with the expression of multi-gene programs linked to squamous cell stemness, epithelial-to-mesenchymal differentiation, growth, genomic integrity, oxidative damage, death, and inflammation. Low-CNA SCCs tended to be HPV(+) and display hypermethylation with repression of TET1 demethylase and FANCF, previously linked to predisposition to SCC, or harbor mutations affecting CASP8, RAS-MAPK pathways, chromatin modifiers, and immunoregulatory molecules. We uncovered hypomethylation of the alternative promoter that drives expression of the ΔNp63 oncogene and embedded miR944. Co-expression of immune checkpoint, T-regulatory, and Myeloid suppressor cells signatures may explain reduced efficacy of immune therapy. These findings support possibilities for molecular classification and therapeutic approaches.

We introduce a method for simultaneous prediction of microRNA–target interactions and their mediated competitive endogenous RNA (ceRNA) interactions. Using high-throughput validation assays in breast cancer cell lines, we show that our integrative approach significantly improves on microRNA–target prediction accuracy as assessed by both mRNA and protein level measurements. Our biochemical assays support nearly 500 microRNA–target interactions with evidence for regulation in breast cancer tumors. Moreover, these assays constitute the most extensive validation platform for computationally inferred networks of microRNA–target interactions in breast cancer tumors, providing a useful benchmark to ascertain future improvements.