{"title":"早发性和晚发性卵巢癌的分子特征:来自多维证据的见解。","authors":"Yanting Shen, Jie Cheng, Qing Ding, Zhihui Tao","doi":"10.1186/s13048-025-01664-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Ovarian cancer (OC) is among the most lethal gynecologic malignancies, characterized by poor prognosis. While aging is a well-established risk factor, the underlying mechanisms distinguishing early- and late-onset ovarian cancer remain poorly understood.</p><p><strong>Methods: </strong>This study analyzed the global burden and age-related trends of ovarian cancer using the GBD database. A cut-off age of 55 years was used to differentiate between early and late onset ovarian cancer, and a Mendelian randomization method was also used to investigate the causal relationship between aging and ovarian cancer. Machine learning was applied to identify tumor-specific age-associated genes, followed by bioinformatics analyses and single-cell sequencing to explore the roles of these genes and immune profile alterations in ovarian cancer. Additionally, models were constructed, and drug sensitivity analyses performed to evaluate their potential as diagnostic markers or therapeutic targets.</p><p><strong>Results: </strong>Ovarian cancer incidence and mortality exhibit age-related trends, with telomere length positively associated with increased risk (OR = 1.27, 95% CI: 1.01-1.60, P = 3.90 × 10⁻<sup>2</sup>). Older patients with OC have a worse prognosis. PRKCD and UCP2 were significantly upregulated in ovarian cancer. PRKCD facilitates epithelial-mesenchymal transition (EMT), contributing to ovarian cancer progression, while UCP2 modulates ROS dynamics, influencing chemoresistance. Immune microenvironment analysis revealed differences between high- and low-expression groups, particularly in T cells, macrophages, and other immune cells. Both genes are sensitive to a varity of drugs, including dasatinib, fluvastatin, highlighting their potential as therapeutic targets.</p><p><strong>Conclusion: </strong>Aging is a significant risk factor for ovarian cancer, with PRKCD and UCP2 closely linked to its onset and progression. These genes show promise as novel biomarkers and therapeutic targets for ovarian cancer.</p>","PeriodicalId":16610,"journal":{"name":"Journal of Ovarian Research","volume":"18 1","pages":"83"},"PeriodicalIF":4.2000,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12016143/pdf/","citationCount":"0","resultStr":"{\"title\":\"Molecular characteristics of early- and late-onset ovarian cancer: insights from multidimensional evidence.\",\"authors\":\"Yanting Shen, Jie Cheng, Qing Ding, Zhihui Tao\",\"doi\":\"10.1186/s13048-025-01664-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Ovarian cancer (OC) is among the most lethal gynecologic malignancies, characterized by poor prognosis. While aging is a well-established risk factor, the underlying mechanisms distinguishing early- and late-onset ovarian cancer remain poorly understood.</p><p><strong>Methods: </strong>This study analyzed the global burden and age-related trends of ovarian cancer using the GBD database. A cut-off age of 55 years was used to differentiate between early and late onset ovarian cancer, and a Mendelian randomization method was also used to investigate the causal relationship between aging and ovarian cancer. Machine learning was applied to identify tumor-specific age-associated genes, followed by bioinformatics analyses and single-cell sequencing to explore the roles of these genes and immune profile alterations in ovarian cancer. Additionally, models were constructed, and drug sensitivity analyses performed to evaluate their potential as diagnostic markers or therapeutic targets.</p><p><strong>Results: </strong>Ovarian cancer incidence and mortality exhibit age-related trends, with telomere length positively associated with increased risk (OR = 1.27, 95% CI: 1.01-1.60, P = 3.90 × 10⁻<sup>2</sup>). Older patients with OC have a worse prognosis. PRKCD and UCP2 were significantly upregulated in ovarian cancer. PRKCD facilitates epithelial-mesenchymal transition (EMT), contributing to ovarian cancer progression, while UCP2 modulates ROS dynamics, influencing chemoresistance. Immune microenvironment analysis revealed differences between high- and low-expression groups, particularly in T cells, macrophages, and other immune cells. Both genes are sensitive to a varity of drugs, including dasatinib, fluvastatin, highlighting their potential as therapeutic targets.</p><p><strong>Conclusion: </strong>Aging is a significant risk factor for ovarian cancer, with PRKCD and UCP2 closely linked to its onset and progression. These genes show promise as novel biomarkers and therapeutic targets for ovarian cancer.</p>\",\"PeriodicalId\":16610,\"journal\":{\"name\":\"Journal of Ovarian Research\",\"volume\":\"18 1\",\"pages\":\"83\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2025-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12016143/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Ovarian Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s13048-025-01664-9\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"REPRODUCTIVE BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ovarian Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13048-025-01664-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REPRODUCTIVE BIOLOGY","Score":null,"Total":0}
Molecular characteristics of early- and late-onset ovarian cancer: insights from multidimensional evidence.
Background: Ovarian cancer (OC) is among the most lethal gynecologic malignancies, characterized by poor prognosis. While aging is a well-established risk factor, the underlying mechanisms distinguishing early- and late-onset ovarian cancer remain poorly understood.
Methods: This study analyzed the global burden and age-related trends of ovarian cancer using the GBD database. A cut-off age of 55 years was used to differentiate between early and late onset ovarian cancer, and a Mendelian randomization method was also used to investigate the causal relationship between aging and ovarian cancer. Machine learning was applied to identify tumor-specific age-associated genes, followed by bioinformatics analyses and single-cell sequencing to explore the roles of these genes and immune profile alterations in ovarian cancer. Additionally, models were constructed, and drug sensitivity analyses performed to evaluate their potential as diagnostic markers or therapeutic targets.
Results: Ovarian cancer incidence and mortality exhibit age-related trends, with telomere length positively associated with increased risk (OR = 1.27, 95% CI: 1.01-1.60, P = 3.90 × 10⁻2). Older patients with OC have a worse prognosis. PRKCD and UCP2 were significantly upregulated in ovarian cancer. PRKCD facilitates epithelial-mesenchymal transition (EMT), contributing to ovarian cancer progression, while UCP2 modulates ROS dynamics, influencing chemoresistance. Immune microenvironment analysis revealed differences between high- and low-expression groups, particularly in T cells, macrophages, and other immune cells. Both genes are sensitive to a varity of drugs, including dasatinib, fluvastatin, highlighting their potential as therapeutic targets.
Conclusion: Aging is a significant risk factor for ovarian cancer, with PRKCD and UCP2 closely linked to its onset and progression. These genes show promise as novel biomarkers and therapeutic targets for ovarian cancer.
期刊介绍:
Journal of Ovarian Research is an open access, peer reviewed, online journal that aims to provide a forum for high-quality basic and clinical research on ovarian function, abnormalities, and cancer. The journal focuses on research that provides new insights into ovarian functions as well as prevention and treatment of diseases afflicting the organ.
Topical areas include, but are not restricted to:
Ovary development, hormone secretion and regulation
Follicle growth and ovulation
Infertility and Polycystic ovarian syndrome
Regulation of pituitary and other biological functions by ovarian hormones
Ovarian cancer, its prevention, diagnosis and treatment
Drug development and screening
Role of stem cells in ovary development and function.