Detecting the Tumor Prognostic Factors From the YTH Domain Family Through Integrative Pan-Cancer Analysis.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Cancer Informatics Pub Date : 2024-11-16 eCollection Date: 2024-01-01 DOI:10.1177/11769351241300030

Chong-Ying Zhu, Qi-Wei Yang, Xin-Yue Mu, Yan-Yu Zhai, Wen-Yan Zhao, Zuo-Jing Yin

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引用次数: 0

Abstract

Objectives: Emerging evidence suggests that N6-methyladenosine (m⁶A) methylation plays a critical role in cancers through various mechanisms. This work aims to reveal the essential role of m⁶A methylation "readers" in regulation of cancer prognosis at the pan-cancer level.

Methods: Herein, we focused on one special protein family of the "readers" of m⁶A methylation, YT521-B homology (YTH) domain family genes, which were observed to be frequently dysregulated in tumor tissues and closely associated with cancer prognosis. Then, a comprehensive analysis of modulation in cancer prognosis was conducted by integrating RNA sequencing (RNAseq) datasets of YTH family genes and clinical information at the pan-cancer level.

Results: YTH family genes were significantly differentially expressed in most of the cancers, particularly increased in Gastrointestinal cancers, and decreased in Endocrine and Urologic cancers. In addition, they were observed to be associated with overall survival (OS) and disease-specific survival (DSS) with various extent, especially in lower grade glioma (LGG), thyroid cancer (THCA), liver hepatocellular carcinoma (LIHC) and kidney clear cell carcinoma (KIRC), so were some "writers" (METLL3, METLL14, WTAP) and "erasers" (FTO, ALKBH5). Further survival analysis illustrated that YTH family genes specifically YTHScore constructed by combining 5 YTH family genes, as well as RWEScore calculated by combining genes from "readers"-"writers"-"erasers" could dramatically distinguish tumor prognosis in 4 representative cancers. As expected, YTHScore presented an equally comparable prognostic classification with RWEScore. Finally, analysis of immune signatures and clinical characteristics implied that, the activity of the innate immune, diagnostic age, clinical stage, Tumor-Node-Metastasis (TNM) stage and immune types, might play specific roles in modulating tumor prognosis.

Conclusions: The study demonstrated that YTH family genes had the potential to predict tumor prognosis, in which the YTHScore illustrated equal ability to predict tumor prognosis compared to RWEScore, thus providing insights into prognostic biomarkers and therapeutic targets at the pan-cancer level.

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通过泛癌综合分析检测 YTH 结构域家族的肿瘤预后因子

目的：新的证据表明，N6-甲基腺苷（m6A）甲基化通过各种机制在癌症中发挥着关键作用。方法：我们重点研究了m6A甲基化 "读者 "中的一个特殊蛋白家族--YT521-B同源（YTH）结构域家族基因，观察到这些基因在肿瘤组织中频繁失调，并与癌症预后密切相关。然后，通过整合YTH家族基因的RNA测序（RNAseq）数据集和泛癌水平的临床信息，对其在癌症预后中的调控进行了综合分析：结果：YTH 家族基因在大多数癌症中都有明显的差异表达，尤其是在胃肠道癌症中增加，而在内分泌和泌尿系统癌症中减少。此外，还观察到它们与总生存期（OS）和疾病特异性生存期（DSS）有不同程度的相关性，尤其是在低级别胶质瘤（LGG）、甲状腺癌（THCA）、肝肝细胞癌（LIHC）和肾透明细胞癌（KIRC）中，一些 "写手"（METLL3、METLL14、WTAP）和 "擦除者"（FTO、ALKBH5）也是如此。进一步的生存分析表明，YTH 家族基因，特别是由 5 个 YTH 家族基因组合而成的 YTHScore，以及由 "阅读者"-"书写者"-"擦除者 "基因组合而成的 RWEScore 可以显著区分 4 种代表性癌症的肿瘤预后。不出所料，YTHScore 与 RWEScore 在预后分类方面具有同等的可比性。最后，对免疫特征和临床特征的分析表明，先天性免疫的活性、诊断年龄、临床分期、肿瘤-结节-转移（TNM）分期和免疫类型可能在调节肿瘤预后方面发挥特殊作用：该研究表明，YTH 家族基因具有预测肿瘤预后的潜力，其中 YTHScore 与 RWEScore 相比，具有相同的预测肿瘤预后的能力，从而为泛癌症层面的预后生物标志物和治疗靶点提供了新的视角。

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 Informatics Medicine-Oncology

CiteScore

3.00

自引率

5.00%

发文量

审稿时长

8 weeks

期刊介绍： The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.