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=Volume 13 - 2022

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, ZEB1-AS1 in CRC cell lines were further confirmed by vitro experiments.
Results: An 8-lncRNA (LINC00261, RP1-170O19.17, CAPN10-AS1, SNHG7, ZEB1-AS1, U47924.27, NIFK-AS1, 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 AUC of 1,3, 5-year survival were 0.678, 0.669; 0.72 in TCGA; 0.58, 0.55, 0.56 in GSE39582; and 0.75, 0.54, 0.56 in GSE29621 respectively. In addition, we found that the risk score was an independent risk factor for CRC patients. Nomograms were constructed, and the predictive accuracy of the nomogram model was assessed by ROC curve analysis. And this signature could effectively predict the chemotherapy response in CRC patients. Moreover, SNHG7, ZEB1-AS1 depletion could significantly suppress the colony formation, migration, and invasion of CRC cells in vitro. 
Conclusions: We constructed a signature and nomogram that could predict the metastasis of CRC and provide certain theoretical guidance for novel therapeutic approaches for CRC.