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. 2021 Aug 11:11:704038.
doi: 10.3389/fonc.2021.704038. eCollection 2021.

Fatty Acid Metabolism-Related lncRNAs Are Potential Biomarkers for Predicting the Overall Survival of Patients With Colorectal Cancer

Yurui Peng  1 , Chenxin Xu  1 , Jun Wen  1 , Yuanchuan Zhang  1 , Meng Wang  1 , Xiaoxiao Liu  1 , Kang Zhao  1 , Zheng Wang  2 , Yanjun Liu  1 , Tongtong Zhang  1   3
Affiliations

Fatty Acid Metabolism-Related lncRNAs Are Potential Biomarkers for Predicting the Overall Survival of Patients With Colorectal Cancer

Yurui Peng et al. Front Oncol. .

Erratum in

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.

Keywords: ceRNA network; colorectal cancer; fatty acid metabolism; long noncoding RNA; nomogram; signature.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The entire analysis process of this study.
Figure 2
Figure 2
Clinical correlation of fatty acid metabolism pathway in patients with CRC. (A) The heatmap showing the associations between the GSVA enrichment score of fatty metabolism pathway and CRC-related clinical characteristics in the dataset from TCGA. **p < 0.01; ***p < 0.001. (B) Kaplan–Meier curves of OS in TCGA-CRC patients based on the GSVA enrichment score. (C–E) boxplots comparing the GSVA enrichment scores in different tumor stages, M stages, and N stages of TCGA-CRC patients.
Figure 3
Figure 3
Construction of the fatty acid metabolism-related ceRNA network. (A–C) Volcano plots of differential expression of lncRNAs, miRNAs, and fatty acid metabolism related-DEmRNAs. Red indicates upregulated RNAs, and green indicates downregulated RNAs; (D) the intersection of predicted miRNAs and DEmiRNAs; (E) the intersection of predicted lncRNA and DElncRNAs; (F) Fatty acid metabolism-related ceRNA network. Red nodes represent the 11 intersected DEmRNAs. Yellow nodes represent the 19 intersected DEmiRNAs. Green nodes represent the 213 intersected DElncRNAs.
Figure 4
Figure 4
Construction of the fatty acid metabolism-related lncRNAs prognostic signature in the training cohort. (A) Univariate Cox regression analysis selected 21 fatty acid metabolism-related lncRNAs correlated with survival; (B) LASSO coefficient profiling of the 21 fatty acid metabolism-related lncRNAs; (C) A coefficient profile plot was generated against the log (lambda) sequence; (D) multivariate Cox regression analysis selected 8 fatty acid metabolism-related lncRNAs correlated with survival; (E) Kaplan–Meier curves of patients with CRC based on the prognostic signature; (F) ROC curves of 1-, 3-, and 5-year OS predicted by the prognostic signature; (G) The distribution of the risk score, OS, and lncRNA expression pattern; (H) The heatmap showing the associations between the risk score and CRC-related clinical variables. *p < 0.05; ***p < 0.001.
Figure 5
Figure 5
Construction of a nomogram in the training cohort. (A, B) Univariate and multivariate Cox regression analysis of OS-related variables; (C) The nomogram consists of age, tumor stage, and risk score; (D) Kaplan–Meier curves of patients with CRC based on the nomogram; (E–G) ROC curves of 1-, 3-, and 5-year OS predicted by the nomogram; (H–J) Calibration curves of 1-, 3-, and 5-year OS predicted by the nomogram.
Figure 6
Figure 6
Validation of the signature and nomogram in the TCGA internal validation cohort. (A) Kaplan–Meier curves of patients with CRC based on the prognostic signature; (B) ROC curves of 1-, 3-, and 5-year OS predicted by the prognostic signature; (C) The distribution of the OS, risk score, and lncRNA expression pattern; (D, E) Univariate and multivariate Cox regression analysis of OS-related variables; (F) Kaplan–Meier curves of patients with CRC based on the nomogram; (G–I) ROC curves of 1-, 3-, and 5-year OS predicted by the nomogram; (J–L) Calibration curves of 1-, 3-, and 5-year OS predicted by the nomogram.
Figure 7
Figure 7
Validation of the signature and nomogram in the qRT-PCR external validation cohort. (A) Kaplan–Meier curves of patients with CRC based on the prognostic signature; (B) ROC curves of 1-, 3-, and 5-year OS predicted by the prognostic signature; (C) The distribution of the OS, risk score and lncRNA expression pattern; (D, E) Univariate and multivariate Cox regression analysis of OS-related variables; (F) Kaplan–Meier curves of patients with CRC based on the nomogram; (G–I) ROC curves of 1-, 3-, and 5-year OS predicted by the nomogram; (J–L) Calibration curves of 1-, 3-, and 5-year OS predicted by the nomogram.
Figure 8
Figure 8
Effects of lncRNA TSPEAR-AS2 on fatty acid metabolism in CRC cells. (A) SW480 and SW460 cell lines were transfected with si-TSPEAR-AS2 (lncRNA-KD), and the knockdown efficiency was confirmed by qRT-PCR; (B) The effect of knockdown of lncRNA TSPEAR-AS2 on the triglyceride content in CRC cells; (C) FASN and ACC1 protein expression in CRC cells were examined by western blots. (D) Chromogenic in situ hybridization (CISH) was performed on clinical samples; (E) The lipid content (% of control) in lncRNA TSPEAR-AS2 high expression group and lncRNA TSPEAR-AS2 low expression group. **p < 0.01.
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