Long-term ovarian cancer survivors: spatial transcriptomics depict ligand-receptor crosstalk heterogeneity at the tumor-stroma interface

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 identification of predictive markers associated with tumors developed from these long-term survivors (LTS) is crucial to identifying therapeutic targets for the disease, and thus improving patient survival rates. Reports to date have not fully established the stromal heterogeneity of the tumor microenvironment (TME) in ovarian cancer and its association with clinical outcomes. We used a spatial transcriptomics platform to generate spatially resolved transcript profiles in treatment naive advanced HGSC from LTS and short-term survivors (STS), and determined whether cancer-associated fibroblasts (CAFs) heterogeneity is associated with survival in patients with advanced HGSC. We integrated spatial transcriptomics with single-cell RNA sequencing data to distinguish tumor and stroma regions, and developed a method to investigate spatially resolved ligand-receptor interactions between various tumor and CAF subtypes in the TME. In addition, we used multiplex immunohistochemistry techniques to validate our findings. We found that a specific subtype of CAFs and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlate with long-term survival in advanced HGSC patients. We also demonstrated that significant APOE- LRP5 crosstalk occurred at the stroma-tumor interface in tumor tissues from STS compared to LTS, suggesting that such crosstalk plays a crucial role in modulating the malignant phenotype of HGSC, and could serve as a predictive biomarker of patient survival.

Translational strategies and systems biology insights for blood-brain barrier opening and delivery in brain tumors and Alzheimer’s disease

“…Spatial transcriptomic and proteomics platforms can provide molecular profiling of the BBB in primary and metastatic brain tumors [ 60 ] and neurodegenerative diseases [ 61 ]. Further computational modeling for region-specific cell-cell-communication and signaling pathway prediction [ 62 ] would facilitate the identification of potential targetable strategies for opening or stabilizing the BBB for drug delivery. Zhang et al applied the Nanostring GeoMX to study brain metastasis-associated astrocytes in non-small cell lung cancer patients [ 60 ].…”