Background: The proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify candidate protein markers and therapeutic targets for colorectal cancer (CRC). Methods: Protein quantitative trait loci (pQTLs) were derived from seven published genome-wide association studies (GWASs) on plasma proteome, and summary-level data were extracted for 4853 circulating protein markers. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (16,871 cases and 26,328 controls), the FinnGen cohort (4957 cases and 304,197 controls), and the UK Biobank (9276 cases and 477,069 controls). Colocalization and summary-data-based MR (SMR) analyses were performed sequentially to verify the causal role of candidate proteins. Single cell-type expression analysis, protein-protein interaction (PPI), and druggability evaluation were further conducted to detect the specific cell type with enrichment expression and prioritize potential therapeutic targets. Results: Collectively, genetically predicted levels of 13 proteins were associated with CRC risk. Elevated levels of two proteins (GREM1, CHRDL2) and decreased levels of 11 proteins were associated with an increased risk of CRC, among which four (GREM1, CLSTN3, CSF2RA, CD86) were prioritized with the most convincing evidence. These protein-coding genes are mainly expressed in tissue stem cells, epithelial cells, and monocytes in colon tumor tissue. Two interactive pairs of proteins (GREM1 and CHRDL2; MMP2 and TIMP2) were identified to be involved in osteoclast differentiation and tumorigenesis pathways; four proteins (POLR2F, CSF2RA, CD86, MMP2) have been targeted for drug development on autoimmune diseases and other cancers, with the potentials of being repurposed as therapeutic targets for CRC. Conclusions: This study identified several protein biomarkers to be associated with CRC risk and provided new insights into the etiology and promising targets for the development of screening biomarkers and therapeutic drugs for CRC.

GDF15 promotes EMT and metastasis in colorectal cancer GDF15 promotes EMT and metastasis in colorectal cancer

Long non-coding RNAs (lncRNAs) function as key molecules in cancer progression. The lncRNA CYTOR plays oncogenic roles in multiple types of cancer, yet the detailed molecular mechanisms of those roles remain unknown. The aim of this study was to investigate the clinical significance, biological function and interacting partners of CYTOR in colorectal cancer (CRC). A systematic and comprehensive analysis of CYTOR expression was performed in 138 CRC samples and in the TCGA and GEO databases. Biological function was investigated through knockdown and overexpression of CYTOR in vitro and in vivo. In addition, its protein binding partner was identified and validated using ChIRP-MS and RNA immunoprecipitation assays. Their key interaction sites on CYTOR were verified by CRISPR/Cas9 and a series of mutant constructs. Furthermore, the downstream targets of CYTOR were confirmed via immunoblotting and luciferase reporter assays. CYTOR was significantly up-regulated in CRC samples and associated with poor prognosis, promoting proliferation and metastasis in vitro and in vivo. NCL and Sam68 could recognize their specific motifs and directly bind to EXON1 of CYTOR. Moreover, EXON1 was the key functional site mediating the interaction of CYTOR with NCL and Sam68. NCL and Sam68 functioned as oncogenes to promote CRC progression. Furthermore, we confirmed that the heterotrimeric complex of CYTOR, NCL and Sam68 activated the NF-κB pathway and EMT to contribute to CRC progression. CYTOR plays important roles in CRC progression by interacting with NCL and Sam68 and may serve as a prognostic biomarker and/or an effective target for CRC therapies.

Collaborative projects such as The Cancer Genome Atlas (TCGA) have generated various -omics and clinical data on cancer. Many computational tools have been developed to facilitate the study of the molecular characterization of tumors using data from the TCGA. Alternative splicing of a gene produces splicing variants, and accumulating evidence has revealed its essential role in cancer-related processes, implying the urgent need to discover tumor-specific isoforms and uncover their potential functions in tumorigenesis. We developed TSVdb, a web-based tool, to explore alternative splicing based on TCGA samples with 30 clinical variables from 33 tumors. TSVdb has an integrated and well-proportioned interface for visualization of the clinical data, gene expression, usage of exons/junctions and splicing patterns. Researchers can interpret the isoform expression variations between or across clinical subgroups and estimate the relationships between isoforms and patient prognosis. TSVdb is available at http://www.tsvdb.com , and the source code is available at https://github.com/wenjie1991/TSVdb . TSVdb will inspire oncologists and accelerate isoform-level advances in cancer research.