Turquoise module genes.

Next-generation sequencing technology enables uniform and impartial assessment of cancer diagnoses and prognosis. However, such studies are mostly type-specific, and capturing shared genomic abnormalities responsible for neoplastic transformation and progression is a challenging task. Pan-cancer analysis offers insights into the shared and unique molecular mechanisms driving cancer. We conducted an integrated gene-expression analysis using 10,629 samples from 30 distinct cancer types characterized by The Cancer Genome Atlas (TCGA). A gene co-expression network was constructed and genes overlapping between the selected modules and Differentially Expressed Genes (DEGs) were designated as genes of interest. Following a comprehensive literature review, ATP binding cassette subfamily A member 10 (ABCA10) and ATP binding cassette subfamily B member 5 (ABCB5) were selected as key candidates for downstream analysis due to the absence of systematic pan-cancer analysis of these genes. This study presents a unique contribution as the first comprehensive pan-cancer analysis of ABCA10 and ABCB5, highlighting their roles in tumor biology and clinical outcomes. We employed a variety of bioinformatics tools to explore the role of these genes across different tumors. Our research demonstrated that ABCA10 shows reduced expression, while ABCB5 displays variable expression patterns across tumors, indicating their opposing roles and flexible functions in pan-cancer. In many cancer patients, these expression patterns are correlated with worse survival outcomes. Furthermore, immunotherapy responses and immune infiltration across a variety of tumor types are associated with the expression levels of both ABCA10 and ABCB5. These results imply that ABCA10 and ABCB5 could serve as valuable predictive markers and potential therapeutic targets across various cancers.

下一代测序技术（Next-generation sequencing technology）可实现对癌症诊断与预后的均一、客观评估。然而，此类研究大多为癌型特异性研究，而捕获驱动肿瘤转化与进展的共有基因组异常仍是一项颇具挑战性的任务。泛癌分析（pan-cancer analysis）可揭示驱动癌症发生发展的共有与特有分子机制。本研究依托癌症基因组图谱（The Cancer Genome Atlas, TCGA）收录的30种不同癌症类型的10629份样本，开展了整合基因表达分析。研究构建了基因共表达网络，并将筛选得到的模块与差异表达基因（Differentially Expressed Genes, DEGs）的交集基因定为目标基因。经全面文献调研后，鉴于目前尚无针对这两个基因的系统性泛癌分析，本研究选取ATP结合盒亚家族A成员10（ABCA10）与ATP结合盒亚家族B成员5（ABCB5）作为下游分析的关键候选基因。本研究作为首个针对ABCA10与ABCB5的系统性泛癌分析，具有独特的学术价值，阐明了二者在肿瘤生物学与临床转归中的作用。本研究借助多种生物信息学工具，探究了这两个基因在不同肿瘤中的功能。研究结果显示，ABCA10在各类肿瘤中均呈低表达，而ABCB5的表达模式在不同肿瘤中存在差异，提示二者在泛癌场景中发挥着相反的作用与灵活的功能。在多数癌症患者中，这两个基因的表达模式与较差的生存预后相关。此外，多种肿瘤类型的免疫治疗应答与免疫浸润水平，均与ABCA10和ABCB5的表达水平相关。上述结果表明，ABCA10与ABCB5可作为多种癌症中具有应用价值的预测标志物与潜在治疗靶点。