Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma
Christof C. Smith, … , Sara R. Selitsky, Benjamin G. Vincent
Christof C. Smith, … , Sara R. Selitsky, Benjamin G. Vincent
Published August 23, 2018
Citation Information: J Clin Invest. 2018;128(11):4804-4820. https://doi.org/10.1172/JCI121476.
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Research Article Immunology Oncology

Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma

Abstract

Human endogenous retroviruses (hERVs) are remnants of exogenous retroviruses that have integrated into the genome throughout evolution. We developed a computational workflow, hervQuant, which identified more than 3,000 transcriptionally active hERVs within The Cancer Genome Atlas (TCGA) pan-cancer RNA-Seq database. hERV expression was associated with clinical prognosis in several tumor types, most significantly clear cell renal cell carcinoma (ccRCC). We explored two mechanisms by which hERV expression may influence the tumor immune microenvironment in ccRCC: (i) RIG-I–like signaling and (ii) retroviral antigen activation of adaptive immunity. We demonstrated the ability of hERV signatures associated with these immune mechanisms to predict patient survival in ccRCC, independent of clinical staging and molecular subtyping. We identified potential tumor-specific hERV epitopes with evidence of translational activity through the use of a ccRCC ribosome profiling (Ribo-Seq) dataset, validated their ability to bind HLA in vitro, and identified the presence of MHC tetramer–positive T cells against predicted epitopes. hERV sequences identified through this screening approach were significantly more highly expressed in ccRCC tumors responsive to treatment with programmed death receptor 1 (PD-1) inhibition. hervQuant provides insights into the role of hERVs within the tumor immune microenvironment, as well as evidence that hERV expression could serve as a biomarker for patient prognosis and response to immunotherapy.

Authors

Christof C. Smith, Kathryn E. Beckermann, Dante S. Bortone, Aguirre A. De Cubas, Lisa M. Bixby, Samuel J. Lee, Anshuman Panda, Shridar Ganesan, Gyan Bhanot, Eric M. Wallen, Matthew I. Milowsky, William Y. Kim, W. Kimryn Rathmell, Ronald Swanstrom, Joel S. Parker, Jonathan S. Serody, Sara R. Selitsky, Benjamin G. Vincent

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Figure 4

Immune-related hERV signatures are prognostic for patient overall survival.

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Immune-related hERV signatures are prognostic for patient overall surviv...
(A) Schematic summary of hERV interactions with the immune system in the context of an anti-tumor immune response. (B) Venn diagram showing the number hERVs significantly associated (GLM, FDR-corrected P < 0.05) with genes corresponding to the upregulation (blue) or downregulation (orange) of the RIG-I–like pathway or positively associated (GLM, FDR corrected P < 0.05) with expression of B cell clones (green). (C) Kaplan-Meier survival curves for TCGA KIRC patients split by the upper (blue) and lower (red) 50th percentile of expression for each of the 3 hERV group signatures represented in A. (D) Change in multivariable CoxPH log-likelihood ratios in TCGA KIRC using clinical stage and/or M1–M4 molecular subtyping and the 3 classes of hERV groups represented in B as predictors for survival. Stacked bars show the change in likelihood ratio for each feature when removed from the full model, as well as the χ2 test P value for each hERV group signature when removed from the full model (*P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001). (E) Univariable CoxPH coefficients for hERV signatures as a predictor for overall survival among each cancer type. FDR-corrected P value represented by red asterisks (*P ≤ 0.05).