HLA-A*26 is correlated with response to nivolumab in Japanese melanoma patients
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Patients with HLA-A*26 were more than twice as likely to respond to anti-PD-1 treatment than patients negative for the allele.
“Antigen presentation by the host may also play a role during anti-PD-1 treatment, as patients with the HLA-A*26 were more than twice as likely to respond than patients negative for the allele (111).”
From Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations (2018) · cites this paper as [111]
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Safety, activity, and immune correlates of anti–PD-1 antibody in cancer
Topalian, S. L., Hodi, F. S., Brahmer, J. R., Gettinger, S. N., Smith, D. C., McDermott, D. F., Powderly, J. D., Carvajal, R. D., Sosman, J. A., Atkins, M. B., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200690 · Cited by 12,628 · see citing works
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802 · see citing works
Tumeh, P. C., Hellmann, M. D., Hamid, O., Tsai, K. K., Loo, K. L., Gubens, M. A., Rosenblum, M. D., Harview, C. L., Taube, J. M., Handley, N. R., et al. (2017) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-16-0325 · Cited by 572 · see citing works
Self-citationGragert, L. A., Madbouly, A. S., Freeman, J., & Maiers, M. J. (2013) · Human Immunology · doi:10.1016/j.humimm.2013.06.025 · Cited by 412 · see citing works
Ikeda, N., Kojima, H., Nishikawa, M., Hayashi, K., Futagami, T., Tsujino, T., Kusunoki, Y., Fujii, N., Suegami, S., Miyazaki, Y., et al. (2015) · Tissue Antigens · doi:10.1111/tan.12536 · Cited by 179 · see citing works
Self-citationgap : Genetic Analysis Package
Zhao, J. H. (2007) · Journal of Statistical Software · doi:10.18637/jss.v023.i08 · Cited by 117 · see citing works
Zhao, J. H. (2004) · doi:10.32614/cran.package.gap · Cited by 28 · see citing works
Flagged first, then by citations
Research works printed but not linked: 20
- Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, et al. Characterization of microRNAs in serum: A novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 2008;18:997e1006.
- Chew AL, Bashir SJ, Wain EM, Fenton DA, Stefanato CM. Expanding the spectrum of frontal fibrosing alopecia: a unifying concept. J Am Acad Dermatol 2010;63:653e60.
- Galasso M, Elena Sana M, Volinia S. Non-coding RNAs: a key to future personalized molecular therapy? Genome Med 2010;2:12.
- Gilad S, Meiri E, Yogev Y, Benjamin S, Lebanony D, Yerushalmi Y, et al. Serum microRNAs are promising novel biomarkers. PLoS One 2008;3:e3148.
- Guo L, Xu K, Yan H, Feng H, Wang T, Chai L, et al. MicroRNA expression signature and the thera- peutic effect of the microRNA-21 antagomir in hypertrophic scarring. Mol Med Rep 2017;15: 1211e21.
- Hwang HW, Mendell JT. MicroRNAs in cell pro- liferation, cell death, and tumorigenesis. Br J Cancer 2006;94:776e80.
- Kossard S. Postmenopausal frontal fibrosing alo- pecia. Scarring alopecia in a pattern distribu- tion. Arch Dermatol 1994;130:770e4.
- Kossard S, Lee MS, Wilkinson B. Postmenopausal frontal fibrosing alopecia: a frontal variant of lichen planopilaris. J Am Acad Dermatol 1997;36:59e66.
- Lau NC, Lim LP, Weinstein EG, Bartel DP. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 2001;294:858e62.
- Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, et al. Circulating microRNAs as stable blood- based markers for cancer detection. Proc Natl Acad Sci USA 2008;105:10513e8.
- Patel V, Noureddine L. MicroRNAs and fibrosis. Curr Opin Nephrol Hypertens 2012;21:410e6.
- Pauley KM, Cha S, Chan EK. MicroRNA in auto- immunity and autoimmune diseases. J Autoimmun 2009;32:189e94.
- Piro RM, Ala U, Molineris I, Grassi E, Bracco C, Perego GP, et al. An atlas of tissue-specific conserved coexpression for functional annota- tion and disease gene prediction. Eur J Hum Genet 2011;19:1173e80.
- Stuart JM, Segal E, Koller D, Kim SK. A gene- coexpression network for global discovery of conserved genetic modules. Science 2003;302: 249e55.
- Su Z, Xia J, Zhao Z. Functional complementation be- tween transcriptional methylation regulation and post-transcriptional microRNA regulation in the human genome. BMC Genomics 2011;12:S5e15.
- Tsang JS, Ebert MS, van Oudenaarden A. Genome-wide dissection of microRNA func- tions and co-targeting networks using gene set signatures. Mol Cell 2010;38:140e53.
- Tziotzios C, Stefanato CM, Fenton DA, Simpson MA, McGrath JA. Frontal fibrosing alopecia: re- flections and hypotheses on aetiology and path- ogenesis. Exp Dermatol 2016;25:847e52.
- Valadi H, Ekstrom K, Bossios A, Sjostrand M, Lee JJ, Lotvall JO. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol 2007;9:654e9.
- Yang G, Yang L, Wang W, Wang J, Wang J, Xu Z. Discovery and validation of extracellular/circu- lating microRNAs during idiopathic pulmonary fibrosis disease progression. Gene 2015;562: 138e44.
- Zhang B, Farwell MA. MicroRNAs: a new emerging class of players for disease diagnostics and gene therapy. J Cell Mol Med 2008;12:3e21. REFERENCES
Cited by
Sorted by citations
Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations
Seidel, J. A., Otsuka, A., & Kabashima, K. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00086 · Cited by 1,360 · see citing works
Self-citationBiomarkers for Immune Checkpoint Inhibitor-Mediated Tumor Response and Adverse Events
Nakamura, Y. (2019) · Frontiers in Medicine · doi:10.3389/fmed.2019.00119 · Cited by 184 · see citing works
Biomarkers for Immune Checkpoint Inhibitors in Melanoma
Kitano, S., Nakayama, T., & Yamashita, M. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00270 · Cited by 60 · see citing works
Anderson, R., & Rapoport, B. L. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00080 · Cited by 44 · see citing works
Wölffer, M., Battke, F., Schulze, M., Feldhahn, M., Flatz, L., Martus, P., & Forschner, A. (2022) · Cancers · doi:10.3390/cancers14020302 · Cited by 32 · see citing works
Iga, N., Otsuka, A., Hirata, M., Kataoka, T. R., Irie, H., Nakashima, C., Matsushita, S., Uchi, H., Yamamoto, Y., Funakoshi, T., et al. (2019) · Cancer Science · doi:10.1111/cas.14195 · Cited by 13 · see citing works
Self-citationZervanos, D.-I., Galatou, E., Miliotou, Α. N., Theodoroula, N. F., Grigoriadis, N., & Vizirianakis, I. S. (2025) · Future Pharmacology · doi:10.3390/futurepharmacol5030043 · Cited by 8 · see citing works
Review – The impact of pharmacogenetics on the outcome of immune checkpoint inhibitors
de Joode, K., Heersche, N., Basak, E. A., Bins, S., van der Veldt, A. A. M., van Schaik, R. H. N., & Mathijssen, R. H. J. (2023) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2023.102662 · Cited by 7 · see citing works
Ishida, Y., Nakashima, C., Kojima, H., Tanaka, H., Fujimura, T., Matsushita, S., Yamamoto, Y., Yoshino, K., Fujisawa, Y., Otsuka, A., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-34044-z · Cited by 5 · see citing works
Self-citationKimura, T., Tanaka, N., Maekawa, T., Kiniwa, Y., Okuyama, R., Asai, J., Matsushita, S., Uchi, H., Kato, H., Nagase, K., et al. (2026) · Communications Medicine · doi:10.1038/s43856-025-01341-4 · Cited by 1 · see citing works
Multi-Dimensional Biomarkers for the Personalized Treatment of Melanoma
Levesque, M. P. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-801238-3.11671-x · Cited by 1 · see citing works
Self-citationImmune Checkpoint Inhibitors: A Step forward in Cancer Management
Carratù, M. R., Potenza, M. A., Nacci, C., Rasmo, D. D., & Signorile, A. (2019) · Madridge Journal of Oncogenesis · doi:10.18689/mjo-1000112
Immunotherapy of advanced melanoma－Up to date－
篤司, 大. (2018) · Skin Cancer · doi:10.5227/skincancer.33.107
- Authors
- Ishida, Y., Otsuka, A., Tanaka, H., Levesque, M. P., Dummer, R., & Kabashima, K.
- Affiliations
- Kyoto University (JP)
- HLA Laboratory (JP)
- University Hospital Zurich (CH)
- Agency for Science, Technology and Research (SG)
- Corresponding author
- Otsuka, Atsushi
- Kabashima, Kenji
- ORCID
- Venue
- Journal of Investigative Dermatology
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 137
- Issue
- 11
- Pages
- 2443-2444
- ISSN
- 0022-202X (ISSN-L)
- OpenAlex
- W2737245267
- Cited by
- 13
- References
- 7
- Citations by year
- 2026: 1 · 2025: 1 · 2023: 1 · 2022: 1 · 2020: 1 · 2019: 3 · 2018: 5
- FWCI
- 1.09
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Investigative Dermatology (publishedVersion)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- King's College Hospital NHS Foundation Trust
- National Institute for Health and Care Research
- King's College London
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- HLA-A26, nivolumab, melanoma, immune checkpoint blockade, predictive biomarkers, treatment response, Japanese patients, anti-PD-1 therapy
- MeSH terms
- Antineoplastic Agents, Immunological, Nivolumab, Adult, Aged, Aged, 80 and over, Alleles, Female, Humans, Japan, Male, Melanoma, Middle Aged, Retrospective Studies, Skin Neoplasms, HLA-A Antigens, Cohort Studies, Survival Analysis, Treatment Outcome, Risk Assessment, Molecular Targeted Therapy
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