Skip to main content
Top
Published in: Journal of Translational Medicine 1/2021

Open Access 01-12-2021 | Melanoma | Research

Tumor immunogenomic signatures improve a prognostic model of melanoma survival

Authors: Leah Morales, Danny Simpson, Robert Ferguson, John Cadley, Eduardo Esteva, Kelsey Monson, Vylyny Chat, Carlos Martinez, Jeffrey Weber, Iman Osman, Tomas Kirchhoff

Published in: Journal of Translational Medicine | Issue 1/2021

Login to get access

Abstract

Background

Tumor mutation burden (TMB) has been associated with melanoma immunotherapy (IT) outcomes, including survival. We explored whether combining TMB with immunogenomic signatures recently identified by The Cancer Genome Atlas (TCGA) can refine melanoma prognostic models of overall survival (OS) in patients not treated by IT.

Methods

Cox proportional-hazards (Cox PH) analysis was performed on 278 metastatic melanomas from TCGA not treated by IT. In a discovery and two validation cohorts Cox PH models assessed the interaction between TMB and 53 melanoma immunogenomic features to refine prediction of melanoma OS.

Results

Interferon-γ response (IFNγRes) and macrophage regulation gene signatures (MacReg) combined with TMB significantly associated with OS (p = 8.80E−14). We observed that patients with high TMB, high IFNγRes and high MacReg had significantly better OS compared to high TMB, low IFNγRes and low MacReg (HR = 2.8, p = 3.55E−08). This association was not observed in low TMB patients.

Conclusions

We report a model combining TMB and tumor immune features that significantly improves prediction of melanoma OS, independent of IT. Our analysis revealed that patients with high TMB, high levels of IFNγRes and MacReg had significantly more favorable OS compared to high TMB patients with low IFNγRes and low MacReg. These findings may substantially improve current melanoma prognostic models.
Appendix
Available only for authorised users
Literature
1.
go back to reference Schadendorf D, Hodi FS, Robert C, Weber JS, Margolin K, Hamid O, et al. Pooled analysis of long-term survival data from phase II and phase III trials of ipilimumab in unresectable or metastatic melanoma. J Clin Oncol. 2015;33(17):1889–94.CrossRefPubMedPubMedCentral Schadendorf D, Hodi FS, Robert C, Weber JS, Margolin K, Hamid O, et al. Pooled analysis of long-term survival data from phase II and phase III trials of ipilimumab in unresectable or metastatic melanoma. J Clin Oncol. 2015;33(17):1889–94.CrossRefPubMedPubMedCentral
2.
go back to reference Hodi FS, O'day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;2010(363):711–23. Hodi FS, O'day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;2010(363):711–23.
3.
go back to reference Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348(6230):124–8.CrossRefPubMedPubMedCentral Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348(6230):124–8.CrossRefPubMedPubMedCentral
4.
go back to reference Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371(23):2189–99.CrossRefPubMedPubMedCentral Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371(23):2189–99.CrossRefPubMedPubMedCentral
5.
6.
go back to reference Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499(7457):214–8.CrossRefPubMedPubMedCentral Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499(7457):214–8.CrossRefPubMedPubMedCentral
7.
go back to reference McGranahan N, Furness AJ, Rosenthal R, Ramskov S, Lyngaa R, Saini SK, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351(6280):1463–9.CrossRefPubMedPubMedCentral McGranahan N, Furness AJ, Rosenthal R, Ramskov S, Lyngaa R, Saini SK, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351(6280):1463–9.CrossRefPubMedPubMedCentral
8.
go back to reference Qu K, Zaba LC, Giresi PG, Li R, Longmire M, Kim YH, et al. Individuality and variation of personal regulomes in primary human T cells. Cell Syst. 2015;1(1):51–61.CrossRefPubMedPubMedCentral Qu K, Zaba LC, Giresi PG, Li R, Longmire M, Kim YH, et al. Individuality and variation of personal regulomes in primary human T cells. Cell Syst. 2015;1(1):51–61.CrossRefPubMedPubMedCentral
9.
go back to reference Colli LM, Machiela MJ, Myers TA, Jessop L, Yu K, Chanock SJ. Burden of nonsynonymous mutations among TCGA cancers and candidate immune checkpoint inhibitor responses. Cancer Res. 2016;76(13):3767–72.CrossRefPubMedPubMedCentral Colli LM, Machiela MJ, Myers TA, Jessop L, Yu K, Chanock SJ. Burden of nonsynonymous mutations among TCGA cancers and candidate immune checkpoint inhibitor responses. Cancer Res. 2016;76(13):3767–72.CrossRefPubMedPubMedCentral
10.
11.
go back to reference Thorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, Ou Yang TH, et al. The Immune Landscape of Cancer. Immunity. 2018;48(4):812–30 e14. Thorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, Ou Yang TH, et al. The Immune Landscape of Cancer. Immunity. 2018;48(4):812–30 e14.
12.
go back to reference Zhang J, Caruso FP, Sa JK, Justesen S, Nam DH, Sims P, et al. The combination of neoantigen quality and T lymphocyte infiltrates identifies glioblastomas with the longest survival. Commun Biol. 2019;2:135.CrossRefPubMedPubMedCentral Zhang J, Caruso FP, Sa JK, Justesen S, Nam DH, Sims P, et al. The combination of neoantigen quality and T lymphocyte infiltrates identifies glioblastomas with the longest survival. Commun Biol. 2019;2:135.CrossRefPubMedPubMedCentral
13.
go back to reference Li BL, Wan XP. Prognostic significance of immune landscape in tumour microenvironment of endometrial cancer. J Cell Mol Med. 2020. Li BL, Wan XP. Prognostic significance of immune landscape in tumour microenvironment of endometrial cancer. J Cell Mol Med. 2020.
14.
go back to reference Cancer Genome Atlas Research N, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013;45(10):1113–20. Cancer Genome Atlas Research N, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013;45(10):1113–20.
15.
go back to reference Shukla SA, Rooney MS, Rajasagi M, Tiao G, Dixon PM, Lawrence MS, et al. Comprehensive analysis of cancer-associated somatic mutations in class I HLA genes. Nat Biotechnol. 2015;33(11):1152–8.CrossRefPubMedPubMedCentral Shukla SA, Rooney MS, Rajasagi M, Tiao G, Dixon PM, Lawrence MS, et al. Comprehensive analysis of cancer-associated somatic mutations in class I HLA genes. Nat Biotechnol. 2015;33(11):1152–8.CrossRefPubMedPubMedCentral
16.
17.
go back to reference Jurtz V, Paul S, Andreatta M, Marcatili P, Peters B, Nielsen M. NetMHCpan-4.0: improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data. J Immunol. 2017;199(9):3360–8.CrossRefPubMed Jurtz V, Paul S, Andreatta M, Marcatili P, Peters B, Nielsen M. NetMHCpan-4.0: improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data. J Immunol. 2017;199(9):3360–8.CrossRefPubMed
18.
go back to reference Schoenfeld D. Partial residuals for the proportional hazards regression-model. Biometrika. 1982;69(1):239–41.CrossRef Schoenfeld D. Partial residuals for the proportional hazards regression-model. Biometrika. 1982;69(1):239–41.CrossRef
19.
go back to reference Terry M, Therneau PMG. Modeling Survival Data: Extending the Cox Model. Berlin: Springer; 2000. Terry M, Therneau PMG. Modeling Survival Data: Extending the Cox Model. Berlin: Springer; 2000.
20.
go back to reference Therneau TM. A package for survival analysis in S. v2.42 ed2015. Therneau TM. A package for survival analysis in S. v2.42 ed2015.
21.
go back to reference Alboukadel Kassambara MK. survminer: drawing survival curves using 'ggplot2'. 0.4.2 ed2018. Alboukadel Kassambara MK. survminer: drawing survival curves using 'ggplot2'. 0.4.2 ed2018.
22.
go back to reference Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015;350(6257):207–11.CrossRefPubMedPubMedCentral Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015;350(6257):207–11.CrossRefPubMedPubMedCentral
23.
go back to reference Voss MH, Hellmann MD, Chen YB, Gold TM, Lambert CR, VanAllen E, et al. Mutation burden and tumor neoantigens in RCC patients (pts) treated with nivolumab. Journal of Clinical Oncology. 2016;34(2). Voss MH, Hellmann MD, Chen YB, Gold TM, Lambert CR, VanAllen E, et al. Mutation burden and tumor neoantigens in RCC patients (pts) treated with nivolumab. Journal of Clinical Oncology. 2016;34(2).
24.
go back to reference Haddad RI, Seiwert TY, Chow LQM, Gupta S, Weiss J, Gluck I, et al. Genomic determinants of response to pembrolizumab in head and neck squamous cell carcinoma (HNSCC). Journal of Clinical Oncology. 2017;35. Haddad RI, Seiwert TY, Chow LQM, Gupta S, Weiss J, Gluck I, et al. Genomic determinants of response to pembrolizumab in head and neck squamous cell carcinoma (HNSCC). Journal of Clinical Oncology. 2017;35.
25.
go back to reference Fabrizio DA, George TJ, Dunne RF, Frampton G, Sun J, Gowen K, et al. Beyond microsatellite testing: assessment of tumor mutational burden identifies subsets of colorectal cancer who may respond to immune checkpoint inhibition. J Gastrointest Oncol. 2018;9(4):610.CrossRefPubMedPubMedCentral Fabrizio DA, George TJ, Dunne RF, Frampton G, Sun J, Gowen K, et al. Beyond microsatellite testing: assessment of tumor mutational burden identifies subsets of colorectal cancer who may respond to immune checkpoint inhibition. J Gastrointest Oncol. 2018;9(4):610.CrossRefPubMedPubMedCentral
26.
go back to reference Thomas A, Routh ED, Pullikuth A, Jin GX, Su J, Chou JW, et al. Tumor mutational burden is a determinant of immune-mediated survival in breast cancer. Oncoimmunology. 2018;7(10):e1490854.CrossRefPubMedPubMedCentral Thomas A, Routh ED, Pullikuth A, Jin GX, Su J, Chou JW, et al. Tumor mutational burden is a determinant of immune-mediated survival in breast cancer. Oncoimmunology. 2018;7(10):e1490854.CrossRefPubMedPubMedCentral
27.
go back to reference Danilova L, Wang H, Sunshine J, Kaunitz GJ, Cottrell TR, Xu H, et al. Association of PD-1/PD-L axis expression with cytolytic activity, mutational load, and prognosis in melanoma and other solid tumors. P Natl Acad Sci USA. 2016;113(48):E7769–77.CrossRef Danilova L, Wang H, Sunshine J, Kaunitz GJ, Cottrell TR, Xu H, et al. Association of PD-1/PD-L axis expression with cytolytic activity, mutational load, and prognosis in melanoma and other solid tumors. P Natl Acad Sci USA. 2016;113(48):E7769–77.CrossRef
28.
go back to reference Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJM, Robert L, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515(7528):568.CrossRefPubMedPubMedCentral Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJM, Robert L, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515(7528):568.CrossRefPubMedPubMedCentral
30.
go back to reference Stein M, Keshav S, Harris N, Gordon S. Interleukin 4 potently enhances murine macrophage mannose receptor activity: a marker of alternative immunologic macrophage activation. J Exp Med. 1992;176(1):287–92.CrossRefPubMed Stein M, Keshav S, Harris N, Gordon S. Interleukin 4 potently enhances murine macrophage mannose receptor activity: a marker of alternative immunologic macrophage activation. J Exp Med. 1992;176(1):287–92.CrossRefPubMed
31.
go back to reference Na YR, Gu GJ, Jung D, Kim YW, Na J, Woo JS, et al. GM-CSF Induces Inflammatory Macrophages by Regulating Glycolysis and Lipid Metabolism. J Immunol. 2016;197(10):4101–9.CrossRefPubMed Na YR, Gu GJ, Jung D, Kim YW, Na J, Woo JS, et al. GM-CSF Induces Inflammatory Macrophages by Regulating Glycolysis and Lipid Metabolism. J Immunol. 2016;197(10):4101–9.CrossRefPubMed
Metadata
Title
Tumor immunogenomic signatures improve a prognostic model of melanoma survival
Authors
Leah Morales
Danny Simpson
Robert Ferguson
John Cadley
Eduardo Esteva
Kelsey Monson
Vylyny Chat
Carlos Martinez
Jeffrey Weber
Iman Osman
Tomas Kirchhoff
Publication date
01-12-2021
Publisher
BioMed Central
Keywords
Melanoma
Melanoma
Published in
Journal of Translational Medicine / Issue 1/2021
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-021-02738-0

Other articles of this Issue 1/2021

Journal of Translational Medicine 1/2021 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.