Identification of an immune gene expression signature associated with favorable clinical features in Treg-enriched patient tumor samples

Abstract

Immune heterogeneity within the tumor microenvironment undoubtedly adds several layers of complexity to our understanding of drug sensitivity and patient prognosis across various cancer types. Within the tumor microenvironment, immunogenicity is a favorable clinical feature in part driven by the antitumor activity of CD8+ T cells. However, tumors often inhibit this antitumor activity by exploiting the suppressive function of regulatory T cells (Tregs), thus suppressing the adaptive immune response. Despite the seemingly intuitive immunosuppressive biology of Tregs, prognostic studies have produced contradictory results regarding the relationship between Treg enrichment and survival. We therefore analyzed RNA-seq data of Treg-enriched tumor samples to derive a pan-cancer gene signature able to help reconcile the inconsistent results of Treg studies, by better understanding the variable clinical association of Tregs across alternative tumor contexts. We show that increased expression of a 32-gene signature in Treg-enriched tumor samples (n = 135) is able to distinguish a cohort of patients associated with chemosensitivity and overall survival. This cohort is also enriched for CD8+ T cell abundance, as well as the antitumor M1 macrophage subtype. With a subsequent validation in a larger TCGA pool of Treg-enriched patients (n = 626), our results reveal a gene signature able to produce unsupervised clusters of Treg-enriched patients, with one cluster of patients uniquely representative of an immunogenic tumor microenvironment. Ultimately, these results support the proposed gene signature as a putative biomarker to identify certain Treg-enriched patients with immunogenic tumors that are more likely to be associated with features of favorable clinical outcome.

An immunogenic NSCLC microenvironment is associated with favorable survival in lung adenocarcinoma

“…In LUAD, 402 genes were significantly upregulated in the cold versus hot TMEs ( Figure 4A). These genes were enriched for ribosomal and metabolic pathways, RNA transport, as well as nucleotide metabolism, which is in line with previous studies ( Figure 4B; Supplementary Table 1) [21,[29][30][31][32]. In LUAD, 2022 genes were upregulated in hot versus cold tumors.…”

“…One cluster (cluster2) was significantly enriched for LUAD tumor samples (P < 0.0001, x 2 = 113.9; Figure 2A). In order to determine whether the clusters produced were indeed indicative of immunogenic TMEs, we examined gene expression levels of several immunogenic activation markers between cluster1 and cluster2, namely CD8A, PRF1, HLA-A, and GZMA, which are shown to be favorably expressed in immunogenic tumors [4,5,[17][18][19][20][21]. Expressions of these 4 genes were significantly elevated in cluster2 (P = 4.15e-7, P = 2.0e-6, 3.93e-12, 4.90e-5; Figure 2B-2E), which was enriched for LUAD.…”

“…Unsupervised clusters were produced for both LUAD and LUSC independently. In LUAD, cluster1 possessed higher levels of immune cells known to help drive a favorable anti-tumor phenotype across various cancer types (e.g., CD8+ T-cells, M1-macrophages), indicative of a clinically favorable TME ( Figure 3A) [20,21,25,26]. This TME profile was also confirmed to possess higher levels of the cytolytic activation biomarkers CD8A, PRF1, HLA-A, and GZMA (P = 1.76e-10, P = 2.89e-10, P = 1.13e-5, and P = 1.01e-9; Supplementary Figure 1B-1E, respectively).…”

Increased Expression Together with the Gene Regulation Network of NEIL3 Predicts Poor Prognosis and Correlates with Immune Infiltrates in Hepatocellular Carcinoma

“…Tregs, and exhausted T cells. These gene markers had been reported in previous studies [22][23][24][25][26].…”

An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples

“…Single-cell analysis has become increasingly popular in the field of cancer immunology [1] and autoimmune disorders [2, 3], with the aim to potentially identify patient-specific signatures and apply a more targeted therapy [4–6]. There is also enhanced focus on T and B lymphocyte profiling in infections [7], or in patients treated with vaccines [8] or antibody-based immunotherapies [9].…”