COMPUTATIONAL IDENTIFICATION OF INFILTRATING T LYMPHOCYTES INTO SOLID TUMOR

T cells play a central role in cancer immunity. Successful anti-tumor immunotherapy relies on the effective infiltration of cytotoxic T cells. However, the tumor microenvironment presents physical and immunosuppressive barriers to prevent T cell entry. Here, we developed two novel computational tools, ReMITT and SIBERT, to search for migrating T cells and T cell entry regions (TERs) into the tumor core. SIBERT combines a novel change point detection method and a spatial imputation model to detect regions with signatures of recent T cell entry using the spatial transcriptomics data. Applying SIBERT to multiple human cancer samples revealed several TERs for each sample, which were dominantly distributed near the tumor margins rich in blood vessels. Unbiased gene expression analysis revealed key pathways and cytokine/receptors involved in T cell transmigration. Under the rationale of immunoediting, we also predicted potentially novel tumor antigens excluded from the TERs. This work provided insights in T cell exclusion for future immunotherapy development

Publication Details

Journal
SMU Scholar (Southern Methodist University)
Published
2025-05-17
Primary Topic
Cancer Immunotherapy and Biomarkers
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article
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article

COMPUTATIONAL IDENTIFICATION OF INFILTRATING T LYMPHOCYTES INTO SOLID TUMOR

SMU Scholar (Southern Methodist University)
Cancer Immunotherapy and Biomarkers
article

COMPUTATIONAL IDENTIFICATION OF INFILTRATING T LYMPHOCYTES INTO SOLID TUMOR

article en

Abstract

T cells play a central role in cancer immunity. Successful anti-tumor immunotherapy relies on the effective infiltration of cytotoxic T cells. However, the tumor microenvironment presents physical and immunosuppressive barriers to prevent T cell entry. Here, we developed two novel computational tools, ReMITT and SIBERT, to search for migrating T cells and T cell entry regions (TERs) into the tumor core. SIBERT combines a novel change point detection method and a spatial imputation model to detect regions with signatures of recent T cell entry using the spatial transcriptomics data. Applying SIBERT to multiple human cancer samples revealed several TERs for each sample, which were dominantly distributed near the tumor margins rich in blood vessels. Unbiased gene expression analysis revealed key pathways and cytokine/receptors involved in T cell transmigration. Under the rationale of immunoediting, we also predicted potentially novel tumor antigens excluded from the TERs. This work provided insights in T cell exclusion for future immunotherapy development

SMU Scholar (Southern Methodist University)
Reduced inequalities
Openalex Percentile: Top 38%
Cancer Immunotherapy and Biomarkers
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