Kubat Oktem Elif
Istanbul Medeniyet University Faculty of Engineering and Natural Sciences, Department of Molecular Biology and Genetics, Istanbul, Türkiye.
Medeni Med J. 2025 Mar 28;40(1):1-11. doi: 10.4274/MMJ.galenos.2025.34783.
Cancer is a disease characterized by an unregulated division of abnormal cells in the body. The discovery of oncogenes and tumor suppressor genes has paved the way for the targeted use of individual biomarkers and proteins in cancer therapy. The signaling pathways in cells are closely linked, and research into these connections would lead to more precise personalized treatments for cancer. An imbalance in the complement system is associated with the development and progression of cancer. Comparable variations in gene expression and common complement biomarkers in different cancer types are poorly understood. This study aims to gain insights into biomarkers linking the complement system to carcinogenesis.
Clinical and transcriptome data from the cancer genome atlas were used to analyze differentially expressed genes involved in the complement system in different cancer types. Various bioinformatics and machine learning techniques were used to suggest complement pathway-related carcinogenesis biomarkers.
This study provides a comprehensive elucidation of component 7 (C7), complement factor-D (CFD), interleukin-11 (IL11), apolipoprotein C1 (APOC1), and integrin binding sialic acid protein (IBSP) proteins as common biomarkers associated with the complement system in cancer and highlights the diagnostic and prognostic potential of these biomarkers.
These biomarkers would pave the way for targeted cancer treatments in the context of precision medicine.
癌症是一种以体内异常细胞无节制分裂为特征的疾病。癌基因和肿瘤抑制基因的发现为在癌症治疗中靶向使用个体生物标志物和蛋白质铺平了道路。细胞中的信号通路紧密相连,对这些联系的研究将带来更精确的癌症个性化治疗。补体系统失衡与癌症的发生和发展有关。不同癌症类型中基因表达的可比变化和常见补体生物标志物目前了解甚少。本研究旨在深入了解将补体系统与致癌作用联系起来的生物标志物。
利用来自癌症基因组图谱的临床和转录组数据,分析不同癌症类型中参与补体系统的差异表达基因。运用各种生物信息学和机器学习技术来确定与补体途径相关的致癌生物标志物。
本研究全面阐明了成分7(C7)、补体因子D(CFD)、白细胞介素-11(IL11)、载脂蛋白C1(APOC1)和整合素结合唾液酸蛋白(IBSP)作为与癌症补体系统相关的常见生物标志物,并突出了这些生物标志物的诊断和预后潜力。
这些生物标志物将为精准医学背景下的靶向癌症治疗铺平道路。