Genomic instability in ovarian cancer: Through the lens of single nucleotide polymorphisms

IF 3.2 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY Clinica Chimica Acta Pub Date : 2024-10-10 DOI:10.1016/j.cca.2024.119992
Harshavardhani Canchi Sistla , Srikanth Talluri , Taruna Rajagopal , Sivaramakrishnan Venkatabalasubramanian , Nageswara Rao Dunna
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Abstract

Ovarian cancer (OC) is the deadliest gynecological malignancy among all female reproductive cancers. It is characterized by high mortality rate and poor prognosis. Genomic instability caused by mutations, single nucleotide polymorphisms (SNPs), copy number variations (CNVs), microsatellite instability (MSI), and chromosomal instability (CIN) are associated with OC predisposition. SNPs, which are highly prevalent in the general population, show a greater relative risk contribution, particularly in sporadic cancers. Understanding OC etiology in terms of genetic basis can increase the use of molecular diagnostics and provide promising approaches for designing novel treatment modalities. This will help deliver personalized medicine to OC patients, which may soon be within reach. Given the pivotal impact of SNPs in cancers, the primary emphasis of this review is to shed light on their prevalence in key caretaker genes that closely monitor genomic integrity, viz., DNA damage response, repair, cell cycle checkpoints, telomerase maintenance, and apoptosis and their clinical implications in OC. We highlight the current challenges faced in different SNP-based studies. Various computational methods and bioinformatic tools employed to predict the functional impact of SNPs have also been comprehensively reviewed concerning OC research. Overall, this review identifies that variants in the DDR and HRR pathways are the most studied, implying their critical role in the disease. Conversely, variants in other pathways, such as NHEJ, MMR, cell cycle, apoptosis, telomere maintenance, and PARP genes, have been explored the least.
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卵巢癌的基因组不稳定性:透过单核苷酸多态性的视角
卵巢癌(OC)是所有女性生殖系统癌症中最致命的妇科恶性肿瘤。其特点是死亡率高、预后差。基因突变、单核苷酸多态性(SNP)、拷贝数变异(CNV)、微卫星不稳定性(MSI)和染色体不稳定性(CIN)导致的基因组不稳定与卵巢癌易感性有关。SNPs 在普通人群中非常普遍,其相对风险更大,尤其是在散发性癌症中。从遗传学的角度了解卵巢癌的病因,可以提高分子诊断的使用率,并为设计新型治疗模式提供有前景的方法。这将有助于为 OC 患者提供个性化医疗,而这可能很快就会实现。鉴于 SNPs 在癌症中的关键影响,本综述的主要重点是阐明它们在密切监控基因组完整性的关键看护基因(即 DNA 损伤反应、修复、细胞周期检查点、端粒酶维持和细胞凋亡)中的流行情况及其在 OC 中的临床意义。我们强调了目前基于 SNP 的不同研究面临的挑战。我们还全面综述了与 OC 研究相关的各种用于预测 SNP 功能影响的计算方法和生物信息学工具。总的来说,这篇综述指出,DDR 和 HRR 通路中的变异是研究最多的,这意味着它们在疾病中起着关键作用。相反,对其他途径中的变异,如 NHEJ、MMR、细胞周期、细胞凋亡、端粒维持和 PARP 基因的研究则最少。
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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