Data from Spatial transcriptomics depict ligand-receptor crosstalk heterogeneity at the tumor-stroma interface in long-term ovarian cancer survivors

AbstractAdvanced high-grade serous ovarian cancer (HGSC) is an aggressive disease that accounts for 70% of all ovarian cancer deaths. Nevertheless, 15% of patients diagnosed with advanced HGSC survive more than 10 years. The elucidation of predictive markers of these long-term survivors (LTS) could help identify therapeutic targets for the disease, and thus improve patient survival rates. To investigate the stromal heterogeneity of the tumor microenvironment (TME) in ovarian cancer, we used spatial transcriptomics to generate spatially resolved transcript profiles in treatment naïve advanced HGSC from LTS and short-term survivors (STS) and determined the association between cancer-associated fibroblasts (CAF) heterogeneity and survival in patients with advanced HGSC. Spatial transcriptomics and single-cell RNA sequencing data were integrated to distinguish tumor and stroma regions, and a computational method was developed to investigate spatially resolved ligand-receptor interactions between various tumor and CAF subtypes in the TME. A specific subtype of CAFs and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlated with long-term survival in advanced HGSC patients. Also, increased APOE-LRP5 crosstalk occurred at the stroma-tumor interface in tumor tissues from STS compared to LTS. These findings were validated using multiplex immunohistochemistry. Overall, this spatial transcriptomics analysis revealed spatially resolved CAF-tumor crosstalk signaling networks in the ovarian TME that are associated with long-term survival of HGSC patients. Further studies to confirm whether such crosstalk plays a role in modulating the malignant phenotype of HGSC and could serve as a predictive biomarker of patient survival are warranted.