PDF(Pubmed)
Abstract：
Recent studies have shown that ovarian aging is strongly associated with the risk of breast cancer, however, its prognostic impact on breast cancer is not yet fully understood. In this study, we performed a multicohort genetic analysis to explore its prognostic value and biological features in breast cancer.
The gene expression and clinicopathological data of 3366 patients from the The Cancer Genome Atlas (TCGA) cohort, the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort and the GSE86166 cohort were analyzed. A total of 290 ovarian aging-related genes (OARGs) were included in the establishment of the prognostic model. Furthermore, functional mechanisms analysis, drug sensitivity, and immune cell infiltration were investigated using bioinformatic methods.
An eight OARG-based signature was established and validated using independent cohorts. Two risk subgroups of patients with distinct survival outcomes were identified by the OARG-based signature. A nomogram with good predictive performance was developed by integrating the OARG risk score with clinicopathological factors. Moreover, the OARG-based signature was correlated with DNA damage repair, immune cell signaling pathways, and immunomodulatory functions. The patients in the low-risk subgroup were found to be sensitive to traditional chemotherapeutic, endocrine, and targeted agents (doxorubicin, tamoxifen, lapatinib, etc.) and some novel targeted drugs (sunitinib, pazopanib, etc.). Moreover, patients in the low-risk subgroup may be more susceptible to immune escape and therefore respond less effectively to immunotherapy.
In this study, we proposed a comprehensive analytical method for breast cancer assessment based on OARG expression patterns, which could precisely predict clinical outcomes and drug sensitivity of breast cancer patients.
The gene expression and clinicopathological data of 3366 patients from the The Cancer Genome Atlas (TCGA) cohort, the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort and the GSE86166 cohort were analyzed. A total of 290 ovarian aging-related genes (OARGs) were included in the establishment of the prognostic model. Furthermore, functional mechanisms analysis, drug sensitivity, and immune cell infiltration were investigated using bioinformatic methods.
An eight OARG-based signature was established and validated using independent cohorts. Two risk subgroups of patients with distinct survival outcomes were identified by the OARG-based signature. A nomogram with good predictive performance was developed by integrating the OARG risk score with clinicopathological factors. Moreover, the OARG-based signature was correlated with DNA damage repair, immune cell signaling pathways, and immunomodulatory functions. The patients in the low-risk subgroup were found to be sensitive to traditional chemotherapeutic, endocrine, and targeted agents (doxorubicin, tamoxifen, lapatinib, etc.) and some novel targeted drugs (sunitinib, pazopanib, etc.). Moreover, patients in the low-risk subgroup may be more susceptible to immune escape and therefore respond less effectively to immunotherapy.
In this study, we proposed a comprehensive analytical method for breast cancer assessment based on OARG expression patterns, which could precisely predict clinical outcomes and drug sensitivity of breast cancer patients.
摘要：
■最近的研究表明，卵巢老化与乳腺癌的风险密切相关，然而,其对乳腺癌预后的影响尚不完全清楚.在这项研究中,我们进行了多队列遗传分析,以探讨其在乳腺癌中的预后价值和生物学特征.
■来自癌症基因组图谱（TCGA）队列的3366例患者的基因表达和临床病理数据，对乳腺癌国际联合会(METABRIC)队列和GSE86166队列的分子分类学进行了分析.共有290个卵巢衰老相关基因(OARGs)被纳入预后模型的建立。此外，功能机制分析，药物敏感性,使用生物信息学方法研究免疫细胞浸润。
■建立了八个基于OARG的签名，并使用独立的队列进行了验证。通过基于OARG的签名鉴定了具有不同生存结果的患者的两个风险亚组。通过将OARG风险评分与临床病理因素相结合，开发了具有良好预测性能的列线图。此外，基于OARG的签名与DNA损伤修复相关，免疫细胞信号通路，和免疫调节功能。低危亚组患者对传统化疗敏感,内分泌，和靶向药物（阿霉素，他莫昔芬,拉帕替尼,等。)和一些新型靶向药物(舒尼替尼，帕唑帕尼,等。).此外，低危亚组患者可能更容易受到免疫逃逸的影响,因此对免疫疗法的反应效率较低.
■在这项研究中，我们提出了一种基于OARG表达模式的乳腺癌评估综合分析方法，可以准确预测乳腺癌患者的临床结局和药物敏感性。
■来自癌症基因组图谱（TCGA）队列的3366例患者的基因表达和临床病理数据，对乳腺癌国际联合会(METABRIC)队列和GSE86166队列的分子分类学进行了分析.共有290个卵巢衰老相关基因(OARGs)被纳入预后模型的建立。此外，功能机制分析，药物敏感性,使用生物信息学方法研究免疫细胞浸润。
■建立了八个基于OARG的签名，并使用独立的队列进行了验证。通过基于OARG的签名鉴定了具有不同生存结果的患者的两个风险亚组。通过将OARG风险评分与临床病理因素相结合，开发了具有良好预测性能的列线图。此外，基于OARG的签名与DNA损伤修复相关，免疫细胞信号通路，和免疫调节功能。低危亚组患者对传统化疗敏感,内分泌，和靶向药物（阿霉素，他莫昔芬,拉帕替尼,等。)和一些新型靶向药物(舒尼替尼，帕唑帕尼,等。).此外，低危亚组患者可能更容易受到免疫逃逸的影响,因此对免疫疗法的反应效率较低.
■在这项研究中，我们提出了一种基于OARG表达模式的乳腺癌评估综合分析方法，可以准确预测乳腺癌患者的临床结局和药物敏感性。
