ABSTRACT
PURPOSE: We aim to improve the prediction of response or resistance to immunotherapies in patients with melanoma. This goal is based on the hypothesis that current gene signatures predicting immunotherapy outcomes show only modest accuracy due to the lack of spatial information about cellular functions and molecular processes within tumors and their microenvironment. EXPERIMENTAL DESIGN: We collected gene expression data spatially from three cellular compartments defined by CD68+ macrophages, CD45+ leukocytes, and S100B+ tumor cells in 55 immunotherapy-treated melanoma specimens using Digital Spatial Profiling-Whole Transcriptome Atlas. We developed a computational pipeline to discover compartment-specific gene signatures and determine if adding spatial information can improve patient stratification. RESULTS: We achieved robust performance of compartment-specific signatures in predicting the outcome of immune checkpoint inhibitors in the discovery cohort. Of the three signatures, the S100B signature showed the best performance in the validation cohort (N = 45). We also compared our compartment-specific signatures with published bulk signatures and found the S100B tumor spatial signature outperformed previous signatures. Within the eight-gene S100B signature, five genes (PSMB8, TAX1BP3, NOTCH3, LCP2, and NQO1) with positive coefficients predict the response, and three genes (KMT2C, OVCA2, and MGRN1) with negative coefficients predict the resistance to treatment. CONCLUSIONS: We conclude that the spatially defined compartment signatures utilize tumor and tumor microenvironment-specific information, leading to more accurate prediction of treatment outcome, and thus merit prospective clinical assessment.
Subject(s)
Biomarkers, Tumor , Immunotherapy , Melanoma , Transcriptome , Tumor Microenvironment , Humans , Melanoma/genetics , Melanoma/therapy , Melanoma/immunology , Melanoma/pathology , Immunotherapy/methods , Tumor Microenvironment/immunology , Tumor Microenvironment/genetics , Biomarkers, Tumor/genetics , Gene Expression Profiling , Immune Checkpoint Inhibitors/therapeutic use , Immune Checkpoint Inhibitors/pharmacology , Gene Expression Regulation, Neoplastic , S100 Calcium Binding Protein beta Subunit/genetics , Antigens, Differentiation, Myelomonocytic/genetics , Antigens, CD/genetics , Female , Male , Prognosis , Macrophages/immunology , Macrophages/metabolism , CD68 MoleculeABSTRACT
KRAS inhibitors have demonstrated exciting preclinical and clinical responses, although resistance occurs rapidly. Here, we investigate the effects of KRAS-targeting therapies on the tumor microenvironment using a library of KrasG12D, p53-mutant, murine pancreatic ductal adenocarcinoma-derived cell lines (KPCY) to leverage immune-oncology combination strategies for long-term tumor efficacy. Our findings show that SOS1 and MEK inhibitors (SOS1i+MEKi) suppressed tumor growth in syngeneic models and increased intratumoral CD8+ T cells without durable responses. Single-cell RNA sequencing revealed an increase in inflammatory cancer-associated fibroblasts (iCAF), M2 macrophages, and a decreased dendritic cell (DC) quality that ultimately resulted in a highly immunosuppressive microenvironment driven by IL6+ iCAFs. Agonist CD40 treatment was effective to revert macrophage polarization and overcome the lack of mature antigen-presenting DCs after SOS1i+MEKi therapy. Treatment increased the overall survival of KPCY tumor-bearing mice. The addition of checkpoint blockade to SOS1i+MEKi combination resulted in tumor-free mice with established immune memory. Our data suggest that KRAS inhibition affects myeloid cell maturation and highlights the need for combining KRAS cancer-targeted therapy with myeloid activation to enhance and prolong antitumor effects. SIGNIFICANCE: Combination of SOS1 and MEK inhibitors increase T cell infiltration while blunting pro-immune myeloid cell maturation and highlights the need for combining KRAS cancer-targeted therapy with myeloid activation to enhance and prolong anti-tumor effects.