Background: Ovarian cancer remains the deadliest gynecologic malignancy, with its progression closely tied to age-associated remodeling of the tumor immune microenvironment. The laying hen serves as a valuable spontaneous model for human ovarian cancer. Its single-cell analyses may provide valuable insights into the immune-related axis linking ovarian aging to carcinogenesis.Methods: This study applied single-cell RNA sequencing to profile ovaries from three laying hen groups, including 35-week-old normal ovaries (A35w), 110-week-old normal ovaries (B110w), and 110-week-old ovarian cancer tissues (C110w). Key analyses had UCell-based scoring of senescence-related pathways and cancer hallmarks, differential expression analysis for overlapping dysregulated genes, LASSO regression-based prognostic model construction, and assessment of chemotherapy sensitivity and immune infiltration.Results: A comprehensive cellular landscape of chicken ovaries was established, identifying major immune populations including B cells, CD4+ T cells, CD8+ T cells, macrophages, and plasma cells. Senescence-related pathways and cancer hallmarks showed progressive activation in immune cells from A35w to B110w to C110w. A total of 216 genes commonly dysregulated in aging and carcinogenesis, reveal core links between immune dysfunction and malignant transformation. The 20-gene prognostic model derived from these genes stratified human ovarian cancer patients into high-risk and low-risk groups with significant overall survival differences, exhibited robust predictive performance across TCGA, GSE32063, and GSE140082. The model also predicted the differential chemotherapy sensitivity in high-risk and low-risk patients and correlated with specific immune infiltration patterns in the tumor microenvironment.Conclusions: Notably, this is the first single-cell RNA sequencing study of chicken ovarian cancer, and we constructed the 20-gene prognostic model for human ovarian cancer using 216 genes that change significantly in immune cells during both ovarian aging and carcinogenesis. This work provides support to establish the hen as a potential preclinical animal model and a translational tool to guide personalized therapy.
背景：卵巢癌仍是最致命的妇科恶性肿瘤，其进展与肿瘤免疫微环境中与年龄相关的重塑密切相关。蛋鸡可作为人类卵巢癌有价值的自发模型。其单细胞分析可能为连接卵巢衰老与癌变的免疫相关轴提供重要见解。
方法：本研究应用单细胞RNA测序技术对三组蛋鸡卵巢进行解析，包括35周龄正常卵巢（A35w）、110周龄正常卵巢（B110w）和110周龄卵巢癌组织（C110w）。关键分析包括：基于UCell的衰老相关通路和癌症标志评分、重叠失调基因的差异表达分析、基于LASSO回归的预后模型构建，以及化疗敏感性和免疫浸润评估。
结果：建立了鸡卵巢的综合细胞图谱，识别出包括B细胞、CD4+ T细胞、CD8+ T细胞、巨噬细胞和浆细胞在内的主要免疫群体。衰老相关通路和癌症标志在从A35w到B110w再到C110w的免疫细胞中呈现渐进性激活。共发现216个在衰老和癌变过程中共同失调的基因，揭示了免疫功能障碍与恶性转化之间的核心联系。基于这些基因构建的20基因预后模型，可将人类卵巢癌患者分为高风险组和低风险组，两组间总生存期存在显著差异，并在TCGA、GSE32063和GSE140082数据集中均表现出稳健的预测性能。该模型还能预测高风险和低风险患者的差异化化疗敏感性，并与肿瘤微环境中的特定免疫浸润模式相关。
结论：值得注意的是，这是首个针对鸡卵巢癌的单细胞RNA测序研究，我们利用在卵巢衰老和癌变过程中免疫细胞均发生显著变化的216个基因，构建了用于人类卵巢癌的20基因预后模型。这项工作为确立蛋鸡作为潜在临床前动物模型及指导个性化治疗的转化工具提供了支持。
肿瘤(癌症)患者之家