Links between the tumor mutational signature, myeloid and tumor-infiltrating lymphocytes (TIL) phenotype and functional states are lacking in malignant pleural mesothelioma (MPM). We performed multi-omic profiling of the tumor immune microenvironment (TIME) of epithelioid MPM cases to provide insights that could drive novel therapeutic avenues in future studies. MPM tumor tissue from patients who underwent surgical resection was confirmed by a pathologist as epithelioid histological type. Flow cytometry, cytokine profiing and TIL expansion was performed ex vivo. Twenty-two tumor samples were processed for bulk RNA-seq with 15 matched cases profiled for WES. Single cell(sc) RNA-seq with matched scTCR-seq was performed on 9 tumor cases. Analysis was performed using in-house set open-source pipelines with downstream analysis in R. Statistical significance was determined using BH adjusted p-value and +/-1 log2FC with Wilcoxon Sum Ranking test for differentially expressed genes (adjusted p-value significance: 0 ≤ *** < 0.001 ≤ ** < 0.01). BAP1 was the dominant mutation identified in the analyzed cohort (SNV (6/22, 27.3%), CNV (3/15, 20%)). Median tumor mutation burden was low (0.80) and no HLA loss of heterozygosity was identified. scRNA-seq profiling identified clusters of highly proliferative, effector memory CD8+ TIL that contained hyper and highly expanded clones. TIL expressed a high degree of checkpoint receptors (PD-1***, LAG3***, TIM3***) which was confirmed by flow cytometry, and the transcription factor, TOX***. Treg clusters and suppressive myeloid cell types were identified which could limit immune responses against the tumor. CCL22, IP-10 and sCD25 were detected in the tumor tissue. Expanded TIL showed a loss of polyfunctional cytokine secretion but retained production of IFNγ. Hyper and highly expanded TCRs were identified suggesting potential anti-tumor response despite having a dysfunctional, highly proliferative phenotype and a highly suppressive TIME. Our ongoing efforts are focused on receptor-ligand interaction predictions as well as identifying predicted neo-antigens.
LAG3 is an inhibitory receptor expressed by T cells related to inhibition of IFNg production and mitochondrial biogenesis in naive CD4 T cells. Combined expression with other immune checkpoints (ICs) like TIM3 and PD1 is associated with exhausted T cells. It is unknown if tumor-infiltrating lymphocytes (TIL) metabolism reprogramming is related to the presence of ICs impacting their anti-tumoral ability. TIL expansion was performed using the TIL 3.0 methodology from 62 surgically resected liposarcoma (LPS) tumors. Flow cytometry phenotypic analysis included CD73, PD1, Tim3, CTLA4, LAG3, OX40, ICOS and 41BB. Cytotoxicity by IFNγ secretion and CD107a degranulation, reactive oxygen species (ROS) and mitochondrial membrane potential (ΔΨm) was measured on the expanded TIL. TIL expansion success was 54.8% (n=34/62 expanded). The median proportion of T cell populations post expansion was 2.68% CD4+, 80.7% CD8+ and 11.45% CD4-CD8- (DN) comprised mainly of γδ T cells. LAG3 was the highest expressed checkpoint receptor across the TIL subtypes (median 5.28% of CD4+, 3.37% of CD8+ and 15.7% of DN). Likewise, TIM3, OX40, and PD-1 were differentially expressed (median TIM3 1.23% CD4+, 2.73% CD8+, 7.3% DN; OX40 9.4% CD4+, 0.43% CD8+, 0.3% DN; PD-1 9.2% CD4+, 2.8% CD8+, 2.28% DN). Higher metabolic fitness by ROS and ΔΨm correlated with increased IFNγ and CD107a degranulation. We identified three distinctive clusters driven by LAG3 expression and metabolic signature. 1) High LAG3, cytotoxicity, and metabolic fitness, 2) Low cytotoxic-metabolic fitness and low LAG3 and 3) absence of LAG3 and high cytotoxic-metabolic fitness. The data suggest clusters 1 and 2 describe two different patterns; one more activated that might be associated with the presence of LAG3, and the other is dysfunctional by the lack of cytotoxic and metabolic response. Meanwhile, the third cluster suggests a naive bystander T-cell population with a high degranulation and metabolic profile. We describe a potential relationship between metabolic profiles and LAG3 expression. This data underscores the importance of metabolic fitness driving cytotoxic function and deepens our understanding of potentially important biomarkers in adoptive T cell therapy.
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