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Abstract Advanced 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. Reports to date have not fully established the heterogeneity of the tumor microenvironment (TME) in ovarian cancer and its association with clinical outcomes. The TME, which is composed primarily of fibroblasts, endothelial cells, lymphocytic infiltrates, and extracellular matrix proteins, can directly affect cancer cell growth, migration, and differentiation, and thus presents a unique opportunity for cancer diagnosis and treatment. To investigate the stromal heterogeneity of the 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. Our spatial transcriptomics analysis demonstrated the presence of different tumor clusters represented by different transcriptome signatures within a tumor tissue, suggesting high levels of heterogeneity not only among different HGSC samples but also within single HGSC samples. Moreover, our spatial transcriptomics analysis of treatment-naïve STS and LTS samples demonstrated high levels of both intra- and inter-stromal heterogeneity among HGSCs. Annotated stroma clusters, which were identified predominantly in STS samples, had high levels of both periostin and CD36 expression as well as high levels of COL1A1 expression. Furthermore, a specific subtype of CAFs expressing αSMA, VIM and PDGFRβ and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlated with long-term survival in advanced HGSC patients. We also characterized region-specific ligand-receptor interactions by analyzing crosstalk signaling in neighboring spots at the stroma-tumor interface. Using this method and subsequent validation studies by multiplex immunohistochemistry we found that increased APOE-LRP5 crosstalk occurred at the stroma-tumor interface in tumor tissues from STS compared to LTS. These findings suggest that a strong crosstalk signaling network between tumor-derived LRP5 and CAF-derived APOE may confer a more aggressive phenotype of the HGSC, which contribute to poorer patient survival rates. 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. Citation Format: Sammy Ferri-Borgogno, Ying Zhu, Jianting Sheng, Jared K. Burks, Javier A. Gomez, Kwong Kwok Wong, Stephen TC Wong, Samuel C. Mok. Long-term ovarian cancer survivors: spatial transcriptomics depict ligand-receptor crosstalk heterogeneity at the tumor-stroma interface abstract. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84 (5 Suppl₂): Abstract nr A095.
Ferri‐Borgogno et al. (Mon,) studied this question.