Bioinformatics analysis of markers based on m6A related to prognosis combined with immune invasion of rectal adenocarcinoma.

IF 2.2 4区医学 Q3 ONCOLOGY

Cancer Biomarkers Pub Date : 2024-01-01 DOI:10.3233/CBM-230123

Shunkang Yan, Jiandong Zhang, Lianghe Li, Gang Chen, Zhongsheng Chen, Wei Zhan

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引用次数: 0

Abstract

Background: Colorectal cancer (CRC) is a common form of cancer, with rectal cancer accounting for approximately one-third of all cases. Among rectal cancers, 95% are classified as rectal adenocarcinoma (READ). Emerging evidence suggests that long noncoding RNAs (lncRNAs) play a significant role in the development and progression of various cancers. In our study, we aimed to identify differentially expressed lncRNAs potentially associated with m6A and establish a risk assessment model to predict clinical outcomes for READ patients.

Methods: The READ dataset from the TCGA database was utilized in this study to synergistically and logically integrate m6A and lncRNA, while employing bioinformatics technology for the identification of suitable biomarkers. A risk prediction model comprising m6A-associated lncRNAs was constructed to investigate the prognostic, diagnostic, and biological functional relevance of these m6A-related lncRNAs.

Results: Our research builds a composed of three related to m6A lncRNA rectal gland cancer prognosis model, and the model has been proved in the multi-dimensional can serve as the potential of the prognosis of rectal gland cancer biomarkers. Our study constructed a prognostic model of rectal adenocarcinoma consisting of three related m6A lncRNAs: linc00702, ac106900.1 and al583785.1.

Conclusion: The model has been validated as a potential prognostic biomarker for rectal cancer in multiple dimensions, aiming to provide clinicians with an indicator to assess the duration of straight adenocarcinoma. This enables early detection of rectal cancer and offers a promising target for immunotherapy.

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基于 m6A 的与直肠腺癌预后和免疫侵袭相关的标记物的生物信息学分析

背景：大肠癌（CRC）是一种常见的癌症，直肠癌约占所有病例的三分之一。在直肠癌中，95%被归类为直肠腺癌（READ）。新的证据表明，长非编码 RNA（lncRNA）在各种癌症的发生和发展中起着重要作用。在我们的研究中，我们旨在识别与m6A可能相关的差异表达lncRNA，并建立一个风险评估模型来预测READ患者的临床结局：本研究利用TCGA数据库中的READ数据集，对m6A和lncRNA进行协同和逻辑整合，同时利用生物信息学技术鉴定合适的生物标志物。结果表明：我们的研究建立了一个由三个与m6A相关的lncRNA组成的风险预测模型，以研究这些与m6A相关的lncRNA的预后、诊断和生物学功能相关性：我们的研究建立了一个由三个与m6A lncRNA相关的直肠腺癌预后模型，该模型在多维度上被证明可以作为直肠腺癌预后的潜在生物标志物。我们的研究构建了一个由三个相关的 m6A lncRNA：linc00702、ac106900.1 和 al583785.1 组成的直肠腺癌预后模型：该模型从多个维度验证了直肠癌潜在的预后生物标志物，旨在为临床医生提供评估直腺癌持续时间的指标。这有助于早期发现直肠癌，并为免疫疗法提供了一个很有前景的靶点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancer Biomarkers ONCOLOGY-

CiteScore

5.20

自引率

3.20%

发文量

195

审稿时长

3 months

期刊介绍： Concentrating on molecular biomarkers in cancer research, Cancer Biomarkers publishes original research findings (and reviews solicited by the editor) on the subject of the identification of markers associated with the disease processes whether or not they are an integral part of the pathological lesion. The disease markers may include, but are not limited to, genomic, epigenomic, proteomics, cellular and morphologic, and genetic factors predisposing to the disease or indicating the occurrence of the disease. Manuscripts on these factors or biomarkers, either in altered forms, abnormal concentrations or with abnormal tissue distribution leading to disease causation will be accepted.