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Combined Assessment of the Tumor-Stroma Ratio and Tumor Immune Cell Infiltrate for Immune Checkpoint Inhibitor Therapy Response Prediction in Colon Cancer.

ABSTRACT: The best current biomarker strategies for predicting response to immune checkpoint inhibitor (ICI) therapy fail to account for interpatient variability in response rates. The histologic tumor-stroma ratio (TSR) quantifies intratumoral stromal content and was recently found to be predictive of response to neoadjuvant therapy in multiple cancer types. In the current work, we predicted the likelihood of ICI therapy responsivity of 335 therapy-naive colon adenocarcinoma tumors from The Cancer Genome Atlas, using bioinformatics approaches. The TSR was scored on diagnostic tissue slides, and tumor-infiltrating immune cells (TIICs) were inferred from transcriptomic data. Tumors with high stromal content demonstrated increased T regulatory cell infiltration (p = 0.014) but failed to predict ICI therapy response. Consequently, we devised a hybrid tumor microenvironment classification of four stromal categories, based on histological stromal content and transcriptomic-deconvoluted immune cell infiltration, which was associated with previously established transcriptomic and genomic biomarkers for ICI therapy response. By integrating these biomarkers, stroma-low/immune-high tumors were predicted to be most responsive to ICI therapy. The framework described here provides evidence for expansion of current histological TIIC quantification to include the TSR as a novel, easy-to-use biomarker for the prediction of ICI therapy response.

SUBMITTER: Ravensbergen CJ

PROVIDER: S-EPMC8616493 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Immune checkpoint inhibitors (ICIs) have shown clinical benefit in solid tumors, with modest rates of clinical response. Hence, improved therapeutic approaches need to be investigated. Herein, we assessed a combination of chidamide plus celecoxib (called CC-01) combined with programmed cell death protein 1 (PD-1) blockade in a CT26 model as potent tumor microenvironment (TME) regulator. The antitumor activity was assessed by measuring tumor size, overall response rate, and survival rate. Immune profiling of tumor-infiltrating lymphocytes was performed by flow cytometry. Tumor tissues were assessed by chip assay to predict the possible pathway. Tumor size was significantly reduced in mice treated with CC-01 combined with or without anti-PD-1 antibody, however the triple combination therapy consistently demonstrated that it significantly increased both the ORR and survival rate in term of clinical applications. In the combination group, immune landscape profiling revealed decreased populations of immunosuppressive regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages. Analysis of the mouse tumor chip data using Gene Ontology enrichment analysis of biological processes revealed that the triple combination upregulated genes associated with responses to interferon-gamma. Our results demonstrated that CC-01 possessed potent TME regulatory properties, augmenting the antitumor effect when combined with ICIs. This antitumor effect was achieved by altering the immune landscape in TILs (tumor-infiltrating lymphocytes) and was associated with immune cell activation in the TME. Furthermore, CC-01 demonstrated potent anticancer immune response activity, mainly reducing the number and function of several immunosuppressive cells. The combination of CC-01 with an ICI will further enhance the anticancer effect and boost the immune response rate. Collectively, our results support the clinical evaluation of CC-01 in combination with ICIs in several advanced cancers.

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Combined Assessment of the Tumor-Stroma Ratio and Tumor Immune Cell Infiltrate for Immune Checkpoint Inhibitor Therapy Response Prediction in Colon Cancer.

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