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. 2022 Aug 11:28:1610536.
doi: 10.3389/pore.2022.1610536. eCollection 2022.

Identification and Validation of an m6A-Related LncRNA Signature to Predict Progression-Free Survival in Colorectal Cancer

Yong Zhang  1   2 , Lu Li  1 , Feifei Chu  1 , Xingguo Xiao  1 , Li Zhang  1 , Kunkun Li  1 , Huili Wu  1
Affiliations

Identification and Validation of an m6A-Related LncRNA Signature to Predict Progression-Free Survival in Colorectal Cancer

Yong Zhang et al. Pathol Oncol Res. .

Abstract

The RNA methylation of N6 adenosine (m6A) plays a crucial role in various biological processes. Strong evidence reveals that the dysregulation of long non-coding RNAs (lncRNA) brings about the abnormality of downstream signaling in multiple ways, thus influencing tumor initiation and progression. Currently, it is essential to discover effective and succinct molecular biomarkers for predicting colorectal cancer (CRC) prognosis. However, the prognostic value of m6A-related lncRNAs for CRC remains unclear, especially for progression-free survival (PFS). Here, we screened 24 m6A-related lncRNAs in 622 CRC patients and identified five lncRNAs (SLCO4A1-AS1, MELTF-AS1, SH3PXD2A-AS1, H19 and PCAT6) associated with patient PFS. Compared to normal samples, their expression was up-regulated in CRC tumors from TCGA dataset, which was validated in 55 CRC patients from our in-house cohort. We established an m6A-Lnc signature for predicting patient PFS, which was an independent prognostic factor by classification analysis of clinicopathologic features. Moreover, the signature was validated in 1,077 patients from six independent datasets (GSE17538, GSE39582, GSE33113, GSE31595, GSE29621, and GSE17536), and it showed better performance than three known lncRNA signatures for predicting PFS. In summary, our study demonstrates that the m6A-Lnc signature is a promising biomarker for forecasting patient PFS in CRC.

Keywords: colorectal cancer; lncRNA; m6A; progression free survival; 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 gene expression of m6A-related lncRNAs in CRC. (A) The heatmap of 43 m6A-related lncRNAs expression in tumor and normal samples from TCGA dataset. The lncRNAs highlighted in red color in the heatmap are the lncRNAs in (B,C). Complete hierarchical clustering based on euclidean distance was used. (B) The boxplot and beeswarm plot of five prognostic lncRNAs expression in tumor and normal samples from the TCGA dataset. (C) The boxplot of the five lncRNAs expression in 55 pairs of tissues (tumor and matched adjacent normal samples) from 55 CRC patients in our in-house cohort.
FIGURE 2
FIGURE 2
The prognostic value of the m6A-Lnc signature for predicting PFS in CRC. (A) The prognostic value of the five lncRNAs for predicting PFS. (B) Patients at high risk had significantly worse PFS than those at low risk in the TCGA dataset. (C) Patients at high risk had higher expression than those at low risk for the five lncRNAs. (D) The prognostic value of the m6A-Lnc signature for predicting PFS in GSE17538, GSE39582, and GSE33113. (E) The prognostic value of the m6A-Lnc signature for predicting PFS in GSE31595, GSE29621, and GSE17536.
FIGURE 3
FIGURE 3
The accuracy of m6A-LncScore in predicting PFS considering clinicopathological factors. (A) The nomogram plot of m6A-LncScore for predicting PFS. (B) The ROC curve plot of m6A-LncScore for predicting PFS compared to tumor stage. The p value of AUC between the integrated model with m6A-LncScore and tumor stage was labeled, ***p < 0.005; **p < 0.01; *p < 0.05; ns p > 0.05. (C) The calibration plot of the model integrating m6A-LncScore with tumor grade for predicting PFS.
FIGURE 4
FIGURE 4
The correlation of clinicopathologic features with m6A-LncScore. (A) The m6A-LncScore was associated with clinicopathologic features. (B) Stratification analysis shows m6A-LncScore is not dependent on clinicopathologic features for predicting PFS.
FIGURE 5
FIGURE 5
Comparison of predictive power for PFS across the m6A-Lnc signature and three known lncRNA signatures. (A–C) The prognostic value of three known signatures. (D) The predictive power of m6A-LncSig was significantly higher than other three signatures. (E) The predictive power of m6A-LncSig was comparable with or significantly higher than three other signatures when integrated with tumor grade. The p value of AUC between m6A-LncSig and three other lncRNA signatures was labeled, ***p < 0.005; **p < 0.01; *p < 0.05; ns p > 0.05.
FIGURE 6
FIGURE 6
The biological functions associated with the prognostic signature. (A) immune-related pathways in KEGG. (B) immune-related cancer hallmark pathways.
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