Predictive Gene Signature in MAGE-A3 Antigen-Specific Cancer Immunotherapy
Open accessAbstract
PURPOSE: To detect a pretreatment gene expression signature (GS) predictive of response to MAGE-A3 immunotherapeutic in patients with metastatic melanoma and to investigate its applicability in a different cancer setting (adjuvant therapy of resected early-stage non-small-cell lung cancer [NSCLC]). PATIENTS AND METHODS: Patients were participants in two phase II studies of the recombinant MAGE-A3 antigen combined with an immunostimulant (AS15 or AS02B). mRNA from melanoma biopsies was analyzed by microarray analysis and quantitative polymerase chain reaction. These results were used to identify and cross-validate the GS, which was then applied to the NSCLC data. RESULTS: In the patients with melanoma, 84 genes were identified whose expression was potentially associated with clinical benefit. This effect was strongest when the immunostimulant AS15 was included in the immunotherapy (hazard ratio [HR] for overall survival, 0.37; 95% CI, 0.13 to 1.05; P = .06) and was less strong with the other immunostimulant AS02B (HR, 0.84; 95% CI, 0.36 to 1.97; P = .70). The same GS was then used to predict the outcome for patients with resected NSCLC treated with MAGE-A3 plus AS02B; actively treated GS-positive patients showed a favorable disease-free interval compared with placebo-treated GS-positive patients (HR, 0.42; 95% CI, 0.17 to 1.03; P = .06), whereas among GS-negative patients, no such difference was found (HR, 1.17; 95% CI, 0.59 to 2.31; P = .65). The genes identified were mainly immune related, involving interferon gamma pathways and specific chemokines, suggesting that their pretreatment expression influences the tumor's immune microenvironment and the patient's clinical response. CONCLUSION: An 84-gene GS associated with clinical response for MAGE-A3 immunotherapeutic was identified in metastatic melanoma and confirmed in resected NSCLC.
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Intratumoral presence of CD8+ T cells is linked to a type-I interferon transcriptional signature.
“multiple clinical observations have linked intratumoral presence of CD8+ T cells to a type-I interferon (IFN) transcriptional signature14–16.”
From Epigenetic state determines the in vivo efficacy of STING agonist therapy (2023) · cites this paper as [15]
The Discussion links tumor CD8 markers with IFNG-regulated genes and downstream targets of STAT1 and IRF1. That supports an association between a CD8-related tumor signature and interferon signaling, but the paper identifies IFNG rather than a type-I interferon signature; it does not establish the claimed type-I specificity. (LLM, conf=0.85)
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Cites
REporting recommendations for tumour MARKer prognostic studies (REMARK).
for the Statistics Subcommittee of the NCI-EORTC Working Group on Cancer Diagnostics, McShane, L. M., Altman, D. G., Sauerbrei, W., Taube, S. E., Gion, M., & Clark, G. M. (2005) · British Journal of Cancer · doi:10.1038/sj.bjc.6602678 · Cited by 1,394 · see citing works
Chemokine expression in melanoma metastases associated with CD8+ T-cell recruitment
Harlin, H., Meng, Y., Peterson, A. C., Zha, Y., Tretiakova, M., Slingluff, C., McKee, M., & Gajewski, T. F. (2009) · Cancer Research · doi:10.1158/0008-5472.can-08-2281 · Cited by 1,121 · see citing works
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Research works printed but not linked: 1
- Therasse P, Eisenhauer EA, Verweij J: RECIST revisited: A review of validation studies on tumour assessment. Eur J Cancer 42:1031-1039, 2006
Cited by
Sorted by citations
CXCL9, CXCL10, CXCL11/CXCR3 axis for immune activation - a target for novel cancer therapy
Tokunaga, R., Zhang, W., Naseem, M., Puccini, A., Berger, M. D., Soni, S., McSkane, M., Baba, H., & Lenz, H.-J. (2018) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2017.11.007 · Cited by 1,627 · see citing works
Saxena, M., van der Burg, S. H., Melief, C. J. M., & Bhardwaj, N. (2021) · Nature reviews. Cancer · doi:10.1038/s41568-021-00346-0 · Cited by 1,581 · see citing works
Mittal, D., Gubin, M. M., Schreiber, R. D., & Smyth, M. J. (2014) · Current Opinion in Immunology · doi:10.1016/j.coi.2014.01.004 · Cited by 1,471 · see citing works
Conserved pan-cancer microenvironment subtypes predict response to immunotherapy
Bagaev, A., Kotlov, N., Nomie, K., Svekolkin, V., Gafurov, A., Isaeva, O., Osokin, N., Kozlov, I., Frenkel, F., Gancharova, O., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.04.014 · Cited by 1,302 · see citing works
Zeng, D., Li, M., Zhou, R., Zhang, J., Sun, H., Shi, M., Bin, J., Liao, Y., Rao, J., & Liao, W. (2019) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0436 · Cited by 986 · see citing works
“Genomic and clinical data sets with immune-checkpoint blockade Five genomic and transcriptomic data sets from patients with metastatic urothelial cancer (13) treatedwith ananti–PD-L1 agent (atezolizumab), patients with metastatic melanoma (43) treated with anti–PD-1 (pembrolizumab), patients with advanced melanoma tre…”
MethodPrat, A., Navarro, A., Paré, L., Reguart, N., Galván, P., Pascual, T., Martínez, A., Nuciforo, P., Comerma, L., Alos, L., et al. (2017) · Cancer Research · doi:10.1158/0008-5472.can-16-3556 · Cited by 455 · see citing works
Mechanisms regulating T-cell infiltration and activity in solid tumors
Lanitis, E., Dangaj, D., Irving, M., & Coukos, G. (2017) · Annals of Oncology · doi:10.1093/annonc/mdx238 · Cited by 369 · see citing works
The immune system and cancer evasion strategies: therapeutic concepts
Muenst, S., Läubli, H., Soysal, S. D., Zippelius, A., Tzankov, A., & Hoeller, S. (2016) · Journal of Internal Medicine · doi:10.1111/joim.12470 · Cited by 304 · see citing works
WNT/β-Catenin Signaling Pathway Regulating T Cell-Inflammation in the Tumor Microenvironment
Li, X., Xiang, Y., Li, F., Yin, C., Li, B., & Ke, X. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02293 · Cited by 291 · see citing works
Molecular pathways and therapeutic targets in lung cancer
Shtivelman, E., Hensing, T., Simon, G. R., Dennis, P. A., Otterson, G. A., Bueno, R., & Salgia, R. (2014) · Oncotarget · doi:10.18632/oncotarget.1891 · Cited by 220 · see citing works
“This suggests that the tumor’s immune microenvironment plays a major role in the patient’s clinical response [251].”
BackgroundCAMOIP: a web server for comprehensive analysis on multi-omics of immunotherapy in pan-cancer
Lin, A., Qi, C., Wei, T., Li, M., Cheng, Q., Liu, Z., Luo, P., & Zhang, J. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac129 · Cited by 152 · see citing works
Interferons and the immunogenic effects of cancer therapy
Minn, A. J. (2015) · Trends in Immunology · doi:10.1016/j.it.2015.09.007 · Cited by 130 · see citing works
Epigenetic state determines the in vivo efficacy of STING agonist therapy
Falahat, R., Berglund, A., Perez-Villarroel, P., Putney, R. M., Hamaidi, I., Kim, S., Pilon-Thomas, S., Barber, G. N., & Mulé, J. J. (2023) · Nature Communications · doi:10.1038/s41467-023-37217-1 · Cited by 94 · see citing works
- Authors
- Ulloa-Montoya, F., Louahed, J., Dizier, B., Gruselle, O., Spiessens, B., Lehmann, F. F., Suciu, S., Kruit, W. H. J., Eggermont, A. M. M., Vansteenkiste, J., & Brichard, V. G.
- Affiliations
- Fernando Ulloa-Montoya, Jamila Louahed, Benjamin Dizier, Olivier Gruselle, Bart Spiessens, Frédéric F. Lehmann, and Vincent G. Brichard, GlaxoSmithKline Vaccines, Rixensart; Stefan Suciu, European Organisation for Research and Treatment of Cancer Headquarters, Brussels; Johan Vansteenkiste, University Hospital Leuven/KU Leuven, Leuven, Belgium; Wim H.J. Kruit, Erasmus Medical Center, Rotterdam, the Netherlands; and Alexander M.M. Eggermont, Institut Gustave Roussy, Villejuif, France.
- European Organisation for Research and Treatment of Cancer (NL)
- Venue
- Journal of Clinical Oncology
- Published
- 2013-07-01
- Volume
- 31
- Issue
- 19
- Pages
- 2388-2395
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2156769579
- Cited by
- 436
- References
- 2
- Citations by year
- 2026: 13 · 2025: 22 · 2024: 41 · 2023: 36 · 2022: 40 · 2021: 46 · 2020: 19 · 2019: 17 · 2018: 24 · 2017: 35 · 2016: 32 · 2015: 43 · 2014: 47 · 2013: 19 · 2012: 2
- FWCI
- 25.91
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Clinical Oncology (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- Funders
- GlaxoSmithKline
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Keywords
- MAGE-A3, cancer immunotherapy, predictive gene signature, metastatic melanoma, non-small cell lung cancer, adjuvant therapy, immunostimulants, gene expression signatures, interferon-gamma pathway, chemokines, tumor immune microenvironment, treatment response prediction, overall survival
- MeSH terms
- Adjuvants, Immunologic, Adult, Aged, Aged, 80 and over, Antigens, Neoplasm, Carcinoma, Non-Small-Cell Lung, Female, Humans, Immunotherapy, Lung Neoplasms, Male, Melanoma, Middle Aged, Neoplasm Proteins, Predictive Value of Tests, Recombinant Proteins, Skin Neoplasms, Biomarkers, Tumor, Gene Expression Regulation, Neoplastic, Odds Ratio, Treatment Outcome, Cancer Vaccines, Reverse Transcriptase Polymerase Chain Reaction, Gene Expression Profiling, Protein Array Analysis, Molecular Targeted Therapy, Transcriptome
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