AUTHOR=Tang Qiang , Hu Xin , Guo Qiong , Shi Yueyue , Liu Liming , Ying Guoguang TITLE=Discovery and Validation of a Novel Metastasis-Related lncRNA Prognostic Signature for Colorectal Cancer JOURNAL=Frontiers in Genetics VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.704988 DOI=10.3389/fgene.2022.704988 ISSN=1664-8021 ABSTRACT=

Background: Cancer metastasis-related chemoresistance and tumour progression are the leading causes of death among CRC patients. Therefore, it is urgent to identify reliable novel biomarkers for predicting the metastasis of CRC.

Methods: The gene expression and corresponding clinical data of CRC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate and multivariate analyses were performed to identify prognostic metastasis-related lncRNAs. Nomograms were constructed, and the predictive accuracy of the nomogram model was assessed by ROC curve analysis. Then, the R package “pRRophetic” was used to predict chemotherapeutic response in CRC patients. In addition, the CIBERSORT database was introduced to evaluate tumour infiltrating immune cells between the high—and low-risk groups. The potential roles of SNHG7 and ZEB1-AS1 in CRC cell lines were further confirmed by in vitro experiments.

Results: An 8-lncRNA (LINC00261, RP1-170O19.17, CAPN10-AS1, SNHG7, ZEB1-AS1, U47924.27, NIFK-AS1, and LINC00925) signature was constructed for CRC prognosis prediction, which stratified patients into two risk groups. Kaplan-Meier analysis revealed that patients in the higher-risk group had a lower survival probability than those in the lower-risk group [p < 0.001 (TCGA); P = 0.044 (GSE39582); and P = 0.0078 (GSE29621)] The AUCs of 1-, 3-, and 5-year survival were 0.678, 0.669, and 0.72 in TCGA; 0.58, 0.55, and 0.56 in GSE39582; and 0.75, 0.54, and 0.56 in GSE29621, respectively. In addition, the risk score was an independent risk factor for CRC patients. Nomograms were constructed, and the predictive accuracy was assessed by ROC curve analysis. This signature could effectively predict the immune status and chemotherapy response in CRC patients. Moreover, SNHG7 and ZEB1-AS1 depletion significantly suppressed the colony formation, migration, and invasion of CRC cells in vitro.

Conclusion: We constructed a signature that could predict the metastasis of CRC and provide certain theoretical guidance for novel therapeutic approaches for CRC.