Transposon-activated POU5F1B promotes colorectal cancer growth and metastasis.

The treatment of colorectal cancer (CRC) is an unmet medical need in absence of early diagnosis. Here, upon characterizing cancer-specific transposable element-driven transpochimeric gene transcripts (TcGTs) produced by this tumor in the SYSCOL cohort, we find that expression of the hominid-restricted retrogene POU5F1B through aberrant activation of a primate-specific endogenous retroviral promoter is a strong negative prognostic biomarker. Correlating this observation, we demonstrate that POU5F1B fosters the proliferation and metastatic potential of CRC cells. We further determine that POU5F1B, in spite of its phylogenetic relationship with the POU5F1/OCT4 transcription factor, is a membrane-enriched protein that associates with protein kinases and known targets or interactors as well as with cytoskeleton-related molecules, and induces intracellular signaling events and the release of trans-acting factors involved in cell growth and cell adhesion. As POU5F1B is an apparently non-essential gene only lowly expressed in normal tissues, and as POU5F1B-containing TcGTs are detected in other tumors besides CRC, our data provide interesting leads for the development of cancer therapies.

Endogenous retroviruses drive KRAB zinc-finger protein family expression for tumor suppression.

Gene expression aberration is a hallmark of cancers, but the mechanisms underlying such aberrations remain unclear. Human endogenous retroviruses (HERVs) are genomic repetitive elements that potentially function as enhancers. Since numerous HERVs are epigenetically activated in tumors, their activation could cause global gene expression aberrations in tumors. Here, we show that HERV activation in tumors leads to the up-regulation of hundreds of transcriptional suppressors, namely, Krüppel-associated box domain-containing zinc-finger family proteins (KZFPs). KZFP genes are preferentially encoded nearby the activated HERVs in tumors and transcriptionally regulated by these adjacent HERVs. Increased HERV and KZFP expression in tumors was associated with better disease conditions. Increased KZFP expression in cancer cells altered the expression of genes related to the cell cycle and cell-matrix adhesion and suppressed cellular growth, migration, and invasion abilities. Our data suggest that HERV activation in tumors drives the synchronized elevation of KZFP expression, presumably leading to tumor suppression.

Detection and benchmarking of somatic mutations in cancer genomes using RNA-seq data.

To detect functional somatic mutations in tumor samples, whole-exome sequencing (WES) is often used for its reliability and relative low cost. RNA-seq, while generally used to measure gene expression, can potentially also be used for identification of somatic mutations. However there has been little systematic evaluation of the utility of RNA-seq for identifying somatic mutations. Here, we develop and evaluate a pipeline for processing RNA-seq data from glioblastoma multiforme (GBM) tumors in order to identify somatic mutations. The pipeline entails the use of the STAR aligner 2-pass procedure jointly with MuTect2 from genome analysis toolkit (GATK) to detect somatic variants. Variants identified from RNA-seq data were evaluated by comparison against the COSMIC and dbSNP databases, and also compared to somatic variants identified by exome sequencing. We also estimated the putative functional impact of coding variants in the most frequently mutated genes in GBM. Interestingly, variants identified by RNA-seq alone showed better representation of GBM-related mutations cataloged by COSMIC. RNA-seq-only data substantially outperformed the ability of WES to reveal potentially new somatic mutations in known GBM-related pathways, and allowed us to build a high-quality set of somatic mutations common to exome and RNA-seq calls. Using RNA-seq data in parallel with WES data to detect somatic mutations in cancer genomes can thus broaden the scope of discoveries and lend additional support to somatic variants identified by exome sequencing alone.