The DOI matches its Crossref record; 62 of the 63 references it cites were found in a registry or an index.
Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma
Open accessAbstract
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.
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“increased expression of ERVs, including a full-length HERV4700 element, was significantly associated with improved response to PD-1/PD-L1 blockade in clear cell renal cell carcinoma32,33.”
From Multi-omic analysis of hepatocellular carcinoma reveals aberrant cis-regulatory changes and dysregulated retrotransposons with prognostic potential (2025) · cites this paper as [32]
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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Salmon provides fast and bias-aware quantification of transcript expression
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017) · Nature Methods · doi:10.1038/nmeth.4197 · Cited by 12,700
Molecular signatures database (MSigDB) 3.0
Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdóttir, H., Tamayo, P., & Mesirov, J. P. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr260 · Cited by 7,111
Neoantigens in cancer immunotherapy
Schumacher, T. N., & Schreiber, R. D. (2015) · Science · doi:10.1126/science.aaa4971 · Cited by 4,783
Spatiotemporal Dynamics of Intratumoral Immune Cells Reveal the Immune Landscape in Human Cancer
Bindea, G., Mlecnik, B., Tosolini, M., Kirilovsky, A., Waldner, M. J., Obenauf, A. C., Angell, H. K., Fredriksen, T., Lafontaine, L., Berger, A., et al. (2013) · Immunity · doi:10.1016/j.immuni.2013.10.003 · Cited by 4,455
Molecular and genetic properties of tumors associated with local immune cytolytic activity
Rooney, M. S., Shukla, S. A., Wu, C. J., Getz, G., & Hacohen, N. (2015) · Cell · doi:10.1016/j.cell.2014.12.033 · Cited by 3,825
Liu, J., Lichtenberg, T., Hoadley, K. A., Poisson, L. M., Lazar, A. J., Cherniack, A. D., Kovatich, A. J., Benz, C. C., Levine, D. A., Lee, A. V., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.052 · Cited by 3,725
Phenotypic Analysis of Antigen-Specific T Lymphocytes
Altman, J. D., Moss, P. A. H., Goulder, P. J. R., Barouch, D. H., McHeyzer-Williams, M. G., Bell, J. I., McMichael, A. J., & Davis, M. M. (1996) · Science · doi:10.1126/science.274.5284.94 · Cited by 3,544
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Self-citationPino-González, M., Quintela, M. E. L., de Rueda, G. D. V. O., Porto, M. D., Álvarez, I. A., Fernández, A. F., Miguel-Fraile, P. S., Rey, J. A. O., Gallardo‐Gómez, M., Videira, L. C., et al. (2026) · medRxiv · doi:10.64898/2026.09.01.26361892
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The therapeutic potential of transposable element activity modulation
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Metadata
- Authors
- Smith, C. C., Beckermann, K. E., Bortone, D. S., De Cubas, A. A., Bixby, L. M., Lee, S. J., Panda, A., Ganesan, S., Bhanot, G., Wallen, E. M., Milowsky, M. I., Kim, W. Y., Rathmell, W. K., Swanstrom, R., Parker, J. S., Serody, J. S., Selitsky, S. R., & Vincent, B. G.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Vanderbilt University Medical Center (US)
- Rutgers, The State University of New Jersey (US)
- ORCID
- Venue
- Journal of Clinical Investigation
- Published
- 2018-10-02
- Volume
- 128
- Issue
- 11
- Pages
- 4804-4820
- ISSN
- 0021-9738 (ISSN-L)
- 1558-8238
- PMC
- PMC6205406
- OpenAlex
- W2888593931
- Cited by
- 303
- References
- 63
- Citations by year
- 2026: 16 · 2025: 37 · 2024: 30 · 2023: 48 · 2022: 52 · 2021: 47 · 2020: 53 · 2019: 18 · 2018: 2
- FWCI
- 11.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Journal of Clinical Investigation (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Rutgers University Community Repository (Rutgers University) (submittedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- UNC Oncology Clinical Translational Research Training Program (5K12CA120780)
- National Institute of Health (5-P50-CA058223-22, 2-P30-CA016086-40, 1-U24-CA210988-01, U54-CA198999, 1F30CA225136-01)
- Forbeck Foundation Collaborative Research Award (NA)
- UNC University Cancer Research Fund (NA)
- Merck-Cancer Research Institute Irvington Postdoctoral Fellowship (NA)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Health Sciences › Medicine › Oncology › Renal cell carcinoma treatment
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- human endogenous retroviruses, clear cell renal cell carcinoma, immunotherapy response prediction, anti-PD-1 therapy, tumor immune microenvironment, HLA binding, prognostic factors, ribosome profiling, T cell response
- MeSH terms
- Carcinoma, Renal Cell, Humans, Immunotherapy, Kidney Neoplasms, Prognosis, Endogenous Retroviruses, Tumor Microenvironment
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