Failed immune responses across multiple pathologies share pan-tumor and circulating lymphocytic targets
Anne Monette, … , Igor Jurisica, Réjean Lapointe
Anne Monette, … , Igor Jurisica, Réjean Lapointe
Published March 26, 2019
Citation Information: J Clin Invest. 2019;129(6):2463-2479. https://doi.org/10.1172/JCI125301.
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Research Article Immunology Oncology

Failed immune responses across multiple pathologies share pan-tumor and circulating lymphocytic targets

Abstract

Tumor-infiltrating lymphocytes (TILs) are widely associated with positive outcomes, yet carry key indicators of a systemic failed immune response against unresolved cancer. Cancer immunotherapies can reverse their tolerance phenotypes while preserving tumor reactivity and neoantigen specificity shared with circulating immune cells. We performed comprehensive transcriptomic analyses to identify gene signatures common to circulating and TILs in the context of clear cell renal cell carcinoma. Modulated genes also associated with disease outcome were validated in other cancer types. Through comprehensive bioinformatics analyses, we identified practical diagnostic markers and actionable targets of the failed immune response. On circulating lymphocytes, 3 genes (LEF1, FASLG, and MMP9) could efficiently stratify patients from healthy control donors. From their associations with resistance to cancer immunotherapies and microbial infections, we uncovered not only pan-cancer, but pan-pathology, failed immune response profiles. A prominent lymphocytic matrix metallopeptidase cell migration pathway is central to a panoply of diseases and tumor immunogenicity, correlates with multi-cancer recurrence, and identifies a feasible noninvasive approach to pan-pathology diagnoses. The differentially expressed genes we have identified warrant future investigation into the development of their potential in noninvasive precision diagnostics and precision pan-disease immunotherapeutics.

Authors

Anne Monette, Antigoni Morou, Nadia A. Al-Banna, Louise Rousseau, Jean-Baptiste Lattouf, Sara Rahmati, Tomas Tokar, Jean-Pierre Routy, Jean-François Cailhier, Daniel E. Kaufmann, Igor Jurisica, Réjean Lapointe

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Figure 1

Distinct comprehensive transcriptomics from paired CD8+ and CD19+ profiles from ccRCC blood, tumors and tissues, and control donor blood isolates.

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Distinct comprehensive transcriptomics from paired CD8+ and CD19+ profil...
(A and B) PCA demonstrating distinct DEG profiles from comprehensive HTA 2.0 microarray analyses of (A) CD8+ (n = 15) and (B) CD19+ (n = 15) immune cell subsets from TILs and TIL-Bs, TIICs, and circulating ptPBLs, and cdPBLs (n = 10). (C) Four-way Venn diagram demonstrating percentage overlaps of DEGs identified by microarrays across different source biospecimens analyzed. (D) Venn diagram showing that ptPBLs have greater numbers of differentially represented exon-exon PSR junctions compared with TILs, relative to TIICs from paired CD8+ samples (P < 0.05; ANOVA, Transcriptome Analysis Console v.3, Affymetrix). Thirteen percent of shared PSR junctions exist between ptPBLs and TILs, representing 33% of total genes common to ptPBLs and TILs having shared isoform identity. (E) GO PM proteins identified by Partek and unsupervised hierarchical clustering algorithm-generated heatmaps demonstrating that the 4 different CD8+ isolates are stratified according to PM, using log2 expression values applying the Euclidean distance metric and complete linkage clustering method (R programming language; R-studio). Heatmaps demonstrate the unsupervised clustering of PBL isolates as most closely related, with TILs and TIICs at their boundaries, suggesting that their profiles may be influenced by the cancer microenvironment. (F) Feasibility of using PM-associated proteins toward identifying pan-cancer DEGs that can stratify patients is demonstrated by PCA biplots of PM DEGs from CD8+ cdPBL and ptPBL isolates created on log2 values using the biplot function (R; R-studio). diff., differential; id., identity; PSR, probe-selected region.