Stephen T.C. Wong

Spatial Transcriptomics Depict Ligand–Receptor Cross-talk Heterogeneity at the Tumor-Stroma Interface in Long-Term Ovarian Cancer Survivors

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. 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 patients with advanced HGSC. Also, increased APOE-LRP5 cross-talk occurred at the stroma-tumor interface in tumor tissues from STS compared with LTS. These findings were validated using multiplex IHC. Overall, this spatial transcriptomics analysis revealed spatially resolved CAF-tumor cross-talk signaling networks in the ovarian TME that are associated with long-term survival of patients with HGSC. Further studies to confirm whether such cross-talk plays a role in modulating the malignant phenotype of HGSC and could serve as a predictive biomarker of patient survival are warranted. Significance: Generation of spatially resolved gene expression patterns in tumors from patients with ovarian cancer surviving more than 10 years allows the identification of novel predictive biomarkers and therapeutic targets for better patient management. See related commentary by Kelliher and Lengyel, p. 1383

The effect of platelet G proteins on platelet extravasation and tumor growth in the murine model of ovarian cancer

Abstract We and other investigators have shown that platelets promote metastasis and the growth of tumors. Our rationale for conducting this study is that platelets’ prometastatic and progrowth effects depend on a close encounter between platelets and cancer cells. This interaction occurs inside blood vessels with circulating tumor cells and outside blood vessels with cancer cells residing in the tumor parenchyma. Our hypothesis was that platelet extravasation is required for the effect of platelets on tumor growth. Platelets respond to environmental stimuli by activation of G protein–coupled receptors on their surface. We investigated the impact of various platelet G proteins on the growth of ovarian cancer tumors and platelet extravasation. We used mice with platelet-specific deficiency of Gαi2 (Gi), Gα13 (G13), or Gαq (Gq) in a syngeneic ovarian cancer model. We measured the total weight of tumor nodules resected from tumor-bearing mice. We developed methods for automated whole-slide image acquisition and unbiased computerized image analysis to quantify extravasated platelets. We compared the number of platelets inside tumor nodules of platelet G protein–deficient tumor-bearing mice. We found that deficiency of Gi and G13, but not Gq, in platelets resulted in smaller tumors compared with those in corresponding littermates. Deficiency of Gi and G13 in platelets reduced the number of extravasated platelets by >90%, but deficiency of Gq did not reduce the number of extravasated platelets significantly. The lack of Gi or G13 in platelets reduced platelet extravasation into the tumor and tumor growth.