Decoding the impact of fibroblast heterogeneity on prognosis and drug resistance in high-grade serous ovarian cancer through tumor evolution analysis

BackgroundTumor heterogeneity is associated with poor prognosis and drug resistance, leading to therapeutic failure. Here, we aim to utilize tumor evolution analysis to decode the intra- and inter-tumoral heterogeneity of high-grade serous ovarian cancer (HGSOC), unraveling the correlation between tumor heterogeneity and prognosis as well as chemotherapy response through single-cell and spatial transcriptomic analysis. MethodsWe collected and curated 28 HGSOC patients single-cell transcriptomic data from five datasets. Then, we developed a novel text mining-based machine learning approach to deconstruct the evolutionary patterns of tumor cell functions. This allowed us to identify key tumor-related genes within different evolutionary branches, elucidate the microenvironmental cell compositions that various functional tumor cells depend on, and analyze the intra- and inter-heterogeneity of tumors and their microenvironments in relation to prognosis and chemotherapy response in HGSOC patients. We further validated our findings in two spatial and seven bulk transcriptomic datasets, totally 1,030 patients. ResultsBy employing transcriptomic clusters as proxies for functional clonality, we identified a significant increase in tumor cell state heterogeneity, which was strongly correlated with patient prognosis and treatment response. Furthermore, increased intra- and inter-tumoral functional clonality was associated with the characteristics of cancer-associated fibroblast (CAF). We also found that the spatial proximity between CXCL12-positive CAF and tumor cells, mediated through the CXCL12/CXCR4 interaction, is highly positively correlated with poor prognosis and chemotherapy resistance in HGSOC. Finally, we constructed a panel of 24 genes through statistical modeling, that are highly correlated with CXCL12-positive fibroblasts and can predict both prognosis and chemotherapy response in HGSOC. ConclusionsOur study offers insights into the collective behavior of tumor cell communities in HGSOC, as well as potential drivers of tumor evolution in response to therapy. Functional analyses and experiments revealed a strong association between CXCL12-positive fibroblasts and tumor progression as well as treatment outcomes. Our findings provide an important theoretical basis for clinical HGSOC treatment.