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用于预测结直肠癌预后的代谢相关长链非编码RNA风险指数的构建与验证

Construction and validation of a metabolic-associated lncRNA risk index for predicting colorectal cancer prognosis.

作者信息

Lin Quanjun, Wang Zhiqiang, Wang Jue, Xu Ming, Yuan Yihang

机构信息

Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

出版信息

Front Oncol. 2023 Mar 31;13:1163283. doi: 10.3389/fonc.2023.1163283. eCollection 2023.

DOI:10.3389/fonc.2023.1163283
PMID:37064091
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10102509/
Abstract

BACKGROUND

Metabolic reprogramming is one of the most important events in the development of tumors. Similarly, long non-coding RNAs are closely related to the occurrence and development of colorectal cancer (CRC). However, there is still a lack of systematic research on metabolism-related lncRNA in CRC.

METHODS

Expression data of metabolism-related genes and lncRNA were obtained from The Cancer Genome Atlas (TCGA). Hub metabolism-related genes (HMRG) were screened out by differential analysis and univariate Cox analysis; a metabolism-related lncRNA risk index (MRLncRI) was constructed by co-expression analysis, univariate Cox regression analysis, LASSO, and multivariate Cox regression analysis. Survival curves were drawn by the Kaplan-Meier method. The ssGSEA method assessed the tumor microenvironment of the sample, and the IPS assessed the patient's response to immunotherapy. "Oncopredict" assessed patient sensitivity to six common drugs.

RESULTS

MRLncRI has excellent predictive ability for CRC prognosis. Based on this, we also constructed a nomogram that is more suitable for clinical applications. Most immune cells and immune-related terms were higher in the high-risk group. IPS scores were higher in the high-risk group. In addition, the high-risk and low-risk groups were sensitive to different drugs.

CONCLUSION

MRLncRI can accurately predict the prognosis of CRC patients, is a promising biomarker, and has guiding significance for the clinical treatment of CRC.

摘要

背景

代谢重编程是肿瘤发生发展过程中最重要的事件之一。同样，长链非编码RNA与结直肠癌（CRC）的发生发展密切相关。然而，目前对于CRC中与代谢相关的lncRNA仍缺乏系统研究。

方法

从癌症基因组图谱（TCGA）获取与代谢相关的基因和lncRNA的表达数据。通过差异分析和单因素Cox分析筛选出核心代谢相关基因（HMRG）；通过共表达分析、单因素Cox回归分析、LASSO和多因素Cox回归分析构建与代谢相关的lncRNA风险指数（MRLncRI）。采用Kaplan-Meier法绘制生存曲线。用ssGSEA方法评估样本的肿瘤微环境，用IPS评估患者对免疫治疗的反应。“Oncopredict”评估患者对六种常用药物的敏感性。

结果

MRLncRI对CRC预后具有良好的预测能力。基于此，我们还构建了更适合临床应用的列线图。大多数免疫细胞和免疫相关指标在高危组中更高。高危组的IPS评分更高。此外，高危组和低危组对不同药物敏感。

结论

MRLncRI可准确预测CRC患者的预后，是一种有前景的生物标志物，对CRC的临床治疗具有指导意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/4d049900fec3/fonc-13-1163283-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/773974998c36/fonc-13-1163283-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/70c494719447/fonc-13-1163283-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/4d049900fec3/fonc-13-1163283-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/773974998c36/fonc-13-1163283-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/4519bf7e96c3/fonc-13-1163283-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/ab9f163db963/fonc-13-1163283-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/a1658c6f304b/fonc-13-1163283-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/e1ce5d4aaa06/fonc-13-1163283-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/70c494719447/fonc-13-1163283-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/3518eb58b680/fonc-13-1163283-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ce/10102509/4d049900fec3/fonc-13-1163283-g009.jpg

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