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In silico reconstruction of primary and metastatic tumor architecture using GIS-augmented spatial transcriptomics

ABSTRACT: Tumor microenvironment (TME) consists of different cell populations, whose interactions contribute to tumor heterogeneity and therapy response. Spatial transcriptomics (ST) offers valuable insights into spatial complexity and heterogeneity of TME. We established a Python package, Geographic Information System (GIS)-augmented In-Silico Reconstruction of Tumor Architecture (GIS-ROTA), based on application of GIS methods to ST data to examine/explore spatial heterogeneity of co-regulated gene sets, such as pathways and cell types within the TME. In our Visium dataset of primary and metastatic estrogen receptor positive breast tumor samples, GIS-ROTA revealed extensive co-localization of estrogen response with metabolic pathway gene sets and mutual exclusivity with metastasis-related and specific immune-related pathway gene sets. Our findings demonstrate the robustness of GIS-ROTA in quantitating tumor heterogeneity and identifying spatially significant regions while minimizing the subjectivity involved in interpreting the clusters from conventional statistical methods. Thus, GIS-ROTA enables the development of therapeutic strategies that target multiple cell populations.

ORGANISM(S): Homo sapiens

PROVIDER: GSE298286 | GEO | 2026/02/17

REPOSITORIES: GEO

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Project description:Novel immunotherapy combination therapies have improved outcomes for patients with hepatocellular carcinoma (HCC), but responses are limited to a subset of patients. Little is known about the inter- and intra-tumor heterogeneity in cellular signaling networks within the HCC tumor microenvironment (TME) that underlie responses to modern systemic therapy. We applied spatial transcriptomics (ST) profiling to characterize the tumor microenvironment in HCC resection specimens from a prospective clinical trial of neoadjuvant cabozantinib, a multi-tyrosine kinase inhibitor that primarily blocks VEGF, and nivolumab, a PD-1 inhibitor in which 5 out of 15 patients were found to have a pathologic response at the time of resection. ST profiling demonstrated that the TME of responding tumors was enriched for immune cells and cancer associated fibroblasts (CAF) with pro-inflammatory signaling relative to the non-responders. The enriched cancer-immune interactions in responding tumors are characterized by activation of the PAX5 module, a known regulator of B cell maturation, which colocalized with spots with increased B cell markers expression suggesting strong activity of these cells. HCC-CAF interactions were also enriched in the responding tumors and were associated with extracellular matrix (ECM) remodeling as there was high activation of FOS and JUN in CAFs adjacent to tumor. The ECM remodeling is consistent with proliferative fibrosis in association with immune-mediated tumor regression. Among the patients with major pathologic response, a single patient experienced early HCC recurrence. ST analysis of this clinical outlier demonstrated marked tumor heterogeneity, with a distinctive immune-poor tumor region that resembles the non-responding TME across patients and was characterized by HCC-CAF interactions and expression of cancer stem cell markers, potentially mediating early tumor immune escape and recurrence in this patient. These data show that responses to modern systemic therapy in HCC are associated with distinctive molecular and cellular landscapes and provide new targets to enhance and prolong responses to systemic therapy in HCC.

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In silico reconstruction of primary and metastatic tumor architecture using GIS-augmented spatial transcriptomics

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