Abstract
Abnormal metabolism, including abnormal fatty acid metabolism, is an emerging hallmark of cancer. The current study sought to investigate the potential prognostic value of fatty acid metabolism-related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC). To this end, we obtained the gene expression data and clinical data of patients with CRC from The Cancer Genome Atlas (TCGA) database. Through gene set variation analysis (GSVA), we found that the fatty acid metabolism pathway was related to the clinical stage and prognosis of patients with CRC. After screening differentially expressed RNAs, we constructed a fatty acid metabolism-related competing endogenous RNA (ceRNA) network based on the miRTarBase, miRDB, TargetScan, and StarBase databases. Next, eight fatty acid metabolism-related lncRNAs included in the ceRNA network were identified to build a prognostic signature with Cox and least absolute shrinkage and selection operator (LASSO) regression analyses, and a nomogram was established based on the lncRNA signature and clinical variables. The signature and nomogram were further validated by Kaplan–Meier survival analysis, Cox regression analysis, calibration plots, receiver operating characteristic (ROC) curves, decision curve analysis (DCA). Besides, the TCGA internal and the quantitative real-time polymerase chain reaction (qRT-PCR) external cohorts were applied to successfully validate the robustness of the signature and nomogram. Finally, in vitro assays showed that knockdown of prognostic lncRNA TSPEAR-AS2 decreased the triglyceride (TG) content and the expressions of fatty acid synthase (FASN) and acetyl-CoA carboxylase 1 (ACC1) in CRC cells, which indicated the important role of lncRNA TSPEAR-AS2 in modulating fatty acid metabolism of CRC. The result of Oil Red O staining showed that the lipid content in lncRNA TSPEAR-AS2 high expression group was higher than that in lncRNA TSPEAR-AS2 low expression group. Our study may provide helpful information for fatty acid metabolism targeting therapies in CRC.
Highlights
Worldwide, colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related death [1]
After calculating the gene set variation analysis (GSVA) enrichment score of the fatty acid metabolism pathway of each CRC patient, we found that the score was closely related to the tumor stage (P < 0.001), metastasis status (M) (P < 0.01), and lymph node status (N) (P < 0.001) (Figure 2A)
We constructed a fatty acid metabolism-related competing endogenous RNA (ceRNA) network and identified eight fatty acid metabolism-related long noncoding RNAs (lncRNAs) to build a prognostic signature for CRC
Summary
Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related death [1]. Despite rapid advances in detection and treatment, the mortality of CRC remains high due to the lack of biomarkers for early screening and prognosis prediction, meaning that many cases are not diagnosed until advanced clinical stages [3]. Efficient prognostic biomarkers and a greater understanding of the molecular mechanisms of CRC are essential to improve the prognosis of patients with CRC. Energy metabolism reprogramming, which can promote rapid cell growth and proliferation, is an emerging hallmark of cancer [4, 5]. It has shown that the decipherment of the fatty acid metabolism and molecular mechanism of CRC will lead to identifying novel therapeutic targets, developing effective treatment methods [13, 14].
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