Masood Madahiah Bint E, Shafique Iqra, Rafique Muhammad Inam, Iman Ayesha, Abbasi Ariba, Rafiq Mehak, Habib Uzma
School of Interdisciplinary Engineering & Sciences (SINES), National University of Sciences & Technology, Islamabad, Pakistan.
Department of Biomedical Engineering and Sciences, School of Mechanical & Manufacturing Engineering, National University of Sciences & Technology, Islamabad, Pakistan.
PLoS One. 2025 May 30;20(5):e0308585. doi: 10.1371/journal.pone.0308585. eCollection 2025.
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.
下一代测序技术能够对癌症诊断和预后进行统一且公正的评估。然而,此类研究大多针对特定类型,而捕获导致肿瘤转化和进展的共同基因组异常是一项具有挑战性的任务。泛癌分析为驱动癌症的共同和独特分子机制提供了见解。我们使用来自癌症基因组图谱(TCGA)所表征的30种不同癌症类型的10629个样本进行了综合基因表达分析。构建了一个基因共表达网络,并将所选模块与差异表达基因(DEG)之间重叠的基因指定为感兴趣的基因。在全面的文献综述之后,由于缺乏对这些基因的系统性泛癌分析,ATP结合盒亚家族A成员10(ABCA10)和ATP结合盒亚家族B成员5(ABCB5)被选为下游分析的关键候选基因。本研究作为对ABCA10和ABCB5的首次全面泛癌分析,具有独特贡献,突出了它们在肿瘤生物学和临床结果中的作用。我们使用了多种生物信息学工具来探索这些基因在不同肿瘤中的作用。我们的研究表明,ABCA10表达降低,而ABCB5在不同肿瘤中表现出可变的表达模式,表明它们在泛癌中具有相反的作用和灵活的功能。在许多癌症患者中,这些表达模式与较差的生存结果相关。此外,多种肿瘤类型的免疫治疗反应和免疫浸润与ABCA10和ABCB5的表达水平相关。这些结果表明,ABCA10和ABCB5可作为各种癌症中有价值的预测标志物和潜在治疗靶点。