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In situ tumor arrays reveal early environmental control of cancer immunity [STAMP Pre and Post Implantation Tumor Cells]

ABSTRACT: The immune phenotype of a tumor is a key predictor of its response to immunotherapy1–4. Patients who respond to immune checkpoint blockade generally present with tumors infiltrated by T cells, a phenotype referred to as ‘inflamed’5–7. However, not all inflamed tumors respond to therapy, and even lower response rates occur among patients with tumors that lack T cells (‘desert’) or that spatially exclude T cells to the periphery of the tumor lesion (‘excluded’)8. Despite the importance of these tumor immune phenotypes in patients, little is known about their development, heterogeneity or dynamics due to the technical difficulty of modeling and tracking these features in situ. Here, we introduce STAMP (skin tumor array by microporation), a preclinical approach that combines in vivo high-throughput time-lapse imaging with next generation sequencing of tumor arrays. Using this approach, we follow the early formation of thousands of tumors to show that development of a given immune phenotype is not under strict control of tumor genetics or transcriptional state, but is also influenced by local features of the tumor microenvironment. Only the spatial organization of T cells, specifically early infiltration of T cells recruited by fibroblasts and monocytes into the core of a tumor, was predictive of functional T cell attack and tumor rejection. Evaluating the dynamic immune-history of tumors revealed that early conversion to the immune inflamed phenotype was predictive of therapy-induced or spontaneous tumor regression. Thus, STAMP captures the dynamic and complex relationships of spatial, cellular and molecular components of tumor progression and has the potential to translate therapeutic concepts into successful clinical strategies.

ORGANISM(S): Mus musculus

PROVIDER: GSE222230 | GEO | 2023/02/17

REPOSITORIES: GEO

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Project description:Background:Acral melanoma (AM) has distinct characteristics as compared to cutaneous melanoma and exhibits poor response to immune checkpoint inhibitors (ICI). Tumor-intrinsic mechanisms of immune exclusion have been identified in many cancers but less studied in AM. Methods: We characterized clinically annotated tumors from patients diagnosed with AM at our institution in correlation with ICI response using whole transcriptome RNAseq, whole exome sequencing, CD8 immunohistochemistry, and multispectral immunofluorescence imaging. A defined interferon-γ-associated T cell-inflamed gene signature was used to categorize tumors into non-T cell-inflamed and T cell-inflamed phenotypes. In combination with AM tumors from two published studies, we systematically assessed the immune landscape of AM and detected differential gene expression and pathway activation in a non-T cell-inflamed tumor microenvironment (TME). Two single-cell(sc) RNAseq AM cohorts and 11 bulk RNAseq cohorts of various tumor types were used for independent validation on pathways associated with lack of ICI response. In total, 892 specimens were included in this study. Results: 72.5% of AM tumors showed low expression of the T cell-inflamed gene signature, with 23.9% of total tumors categorized as the non-T cell-inflamed phenotype. Patients of low CD3 + CD8 + PD1 + intratumoral T cell density showed poor prognosis. We identified 11 oncogenic pathways significantly upregulated in non-T cell-inflamed relative to T cell-inflamed TME shared across all three acral cohorts (MYC, HGF, MITF, VEGF, EGFR, SP1, ERBB2, TFEB, SREBF1, SOX2, and CCND1). scRNAseq analysis revealed that tumor cell-expressing pathway scores were significantly higher in low vs high T cell-infiltrated AM tumors. We further demonstrated that the 11 pathways were enriched in ICI non-responders compared to responders across cancers, including acral melanoma, cutaneous melanoma, triple-negative breast cancer, and non-small cell lung cancer. Pathway activation was associated with low expression of interferon stimulated genes, suggesting suppression of antigen presentation. Across the 11 pathways, fatty acid synthase and CXCL8 were unifying downstream target molecules suggesting potential nodes for therapeutic intervention. Conclusions: A unique set of pathways is associated with immune exclusion and ICI resistance in AM. These data may inform immunotherapy combinations for immediate clinical translation.

Project description:Background: The tumor microenvironment can be classified into immunologically active “inflamed” tumors and inactive “non-inflamed” tumors based on the infiltration of cytotoxic immune cells. Previous studies on liver cancer have reported a superior prognosis for inflamed tumors compared to non-inflamed tumors. However, liver cancer is highly heterogeneous immunologically and genetically, and a finer classification of the liver cancer microenvironment may improve our understanding of its immunological diversity and response to immune therapy. Methods: We characterized the immune gene signatures of 234 primary liver cancers, mainly virus-related, from a Japanese population using RNA-Seq of tumors and matched non-tumorous hepatitis livers. We then compared them with the somatic alterations detected using the whole-genome sequencing. Findings: Liver cancers expressed lower levels of immune marker genes than non-tumorous hepatitis livers, indicating immunosuppression in the tumor microenvironment. Several immunosuppression mechanisms functioned actively and mutually exclusively, resulting in four immune subclasses of liver cancer: tumor-associated macrophage (TAM), CTNNB1, cytolytic activity (CYT), and regulatory T cell (Treg). The CYT and Treg subclasses represented inflamed tumors, while the TAM and CTNNB1 subclasses represented non-inflamed tumors. The TAM subclass, which comprised 31% of liver cancers, showed a poor survival, expressed elevated levels of extracellular matrix genes, and was associated with somatic mutations of chromatin regulator ARID2. The results of cell line experiments suggested a functional link between ARID2 and chemokine production by liver cancer cells. Interpretation: Primary liver cancer was classified into four subclasses based on mutually exclusive mechanisms for immunosuppression. This classification indicate the importance of immunosuppression mechanisms, such as TAM and Treg, as therapeutic targets for liver cancer.

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In situ tumor arrays reveal early environmental control of cancer immunity [STAMP Pre and Post Implantation Tumor Cells]

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