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

## TL;DR

This study uses chicken ovarian data to create a 20-gene model that predicts survival and chemotherapy response in human ovarian cancer patients.

## Contribution

The first single-cell RNA sequencing study of chicken ovarian cancer, leading to a novel 20-gene prognostic model for human patients.

## Key findings

- 216 genes were identified as commonly dysregulated in chicken ovarian aging and cancer, linking immune dysfunction to malignant transformation.
- A 20-gene model stratified human ovarian cancer patients into high- and low-risk groups with significant survival differences.
- The model predicted chemotherapy sensitivity and correlated with immune infiltration patterns in the tumor microenvironment.

## Abstract

Ovarian cancer is the deadliest gynecologic malignancy, with its progression closely linked to age-related changes in the ovarian immune microenvironment. The laying hen, as the spontaneous model for human ovarian cancer research, provides a unique opportunity to reveal the relationship between aging and cancer development. This study used single-cell RNA sequencing to analyze ovaries from young healthy hens, elderly healthy hens, and elderly hens with ovarian cancer, aiming to identify genes commonly dysregulated in ovarian aging and carcinogenesis. The findings led to a prognostic model for human ovarian cancer that predicts patient survival and chemotherapy sensitivity, supporting the hen as a preclinical model and providing a tool to guide personalized therapy.

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.