Single-Cell Transcriptomic Atlas of Chicken Ovarian Aging and Cancer Drives Prognostic Model Development

<b>Background</b>: 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. <b>Methods</b>: 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. <b>Results</b>: 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. <b>Conclusions</b>: 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.