Prognostic and predictive immune gene signatures in breast cancer

Current Opinion in Oncology

Volumn 27, Issue 6, 2015, Pages 433-444

  Bedognetti, Davide ^a   Hendrickx, Wouter ^a   Marincola, Francesco M ^a   Miller, Lance D ^b  

^a SIDRA MEDICAL AND RESEARCH CENTER   (Qatar)

^b WAKE FOREST SCHOOL OF MEDICINE   (United States)

Author keywords

Breast cancer; Immune gene signatures; Immune score; Immunotherapy; Transcriptomic studies

Indexed keywords

ANTINEOPLASTIC AGENT; IMMUNOMODULATING AGENT; CANCER VACCINE; GENETIC MARKER; MONOCLONAL ANTIBODY; TRANSCRIPTOME;

BREAST CANCER; CANCER ADJUVANT THERAPY; CANCER GENETICS; CANCER IMMUNOLOGY; CANCER IMMUNOTHERAPY; CANCER PATIENT; CANCER PROGNOSIS; HUMAN; IMMUNOGENICITY; LUNG CANCER; MELANOMA; META ANALYSIS (TOPIC); OUTCOME ASSESSMENT; PRIORITY JOURNAL; RANDOMIZED CONTROLLED TRIAL (TOPIC); REVIEW; SOLID TUMOR; TRANSCRIPTOMICS; BREAST NEOPLASMS; FEMALE; GENE EXPRESSION PROFILING; GENETIC MARKER; GENETICS; IMMUNOLOGY; IMMUNOTHERAPY; PROCEDURES; PROGNOSIS; TUMOR MICROENVIRONMENT;

ANTIBODIES, MONOCLONAL; BREAST NEOPLASMS; CANCER VACCINES; FEMALE; GENE EXPRESSION PROFILING; GENETIC MARKERS; HUMANS; IMMUNOTHERAPY; MELANOMA; PROGNOSIS; TRANSCRIPTOME; TUMOR MICROENVIRONMENT;

EID: 84944058907     PISSN: 10408746     EISSN: 1531703X     Source Type: Journal    
DOI: 10.1097/CCO.0000000000000234     Document Type: Review

References (79)

1. Bedognetti D, Wang E, Sertoli MR, Marincola FM. Gene-expression profiling in vaccine therapy and immunotherapy for cancer. Expert Rev Vaccines 2010; 9:555-565.
2. Wang E, Bedognetti D, Marincola FM. Prediction of response to anticancer immunotherapy using gene signatures. J Clin Oncol 2013; 31:2369-2371.
3. Wang E, Miller LD, Ohnmacht GA, et al. Prospective molecular profiling of melanoma metastases suggests classifiers of immune responsiveness. Cancer research 2002; 62:3581-3586.
4. Panelli MC, Stashower ME, Slade HB, et al. Sequential gene profiling of basal cell carcinomas treated with imiquimod in a placebo-controlled study defines the requirements for tissue rejection. Genome Biol 2007; 8:R8.
5. Weiss GR, Grosh WW, Chianese-Bullock KA, et al. Molecular insights on the peripheral and intratumoral effects of systemic high-dose rIL-2 (aldesleukin) administration for the treatment of metastatic melanoma. Clin Cancer Res 2011; 17:7440-7450.
6. Ji RR, Chasalow SD, Wang L, et al. An immune-active tumor microenvironment favors clinical response to ipilimumab. Cancer Immunol Immunother 2012; 61:1019-1031.
7. Bedognetti D, Spivey TL, Zhao Y, et al. CXCR3/CCR5 pathways in metastatic melanoma patients treated with adoptive therapy and interleukin-2. Br J Cancer 2013; 109:2412-2423.
8. Ulloa-Montoya F, Louahed J, Dizier B, et al. Predictive gene signature in MAGE-A3 antigen-specific cancer immunotherapy. J Clin Oncol 2013; 31:2388-2395.
9. Gajewski T, Meng Y, Harlin H. Chemokines expressed in melanoma metastases associated with T cell infiltration. J Clin Oncol 2007. (abstract); 25; 18S: 8501.
10. Herbst RS, Soria JC, Kowanetz M, et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 2014; 515:563-567.
11. Wang E, Bedognetti D, Tomei S, Marincola FM. Common pathways to tumor rejection. Ann N Y Acad Sci 2013; 1284:75-79.
12. Spivey TL, Uccellini L, Ascierto ML, et al. Gene expression profiling in acute allograft rejection: challenging the immunologic constant of rejection hypothesis. J Transl Med 2011; 9:174.
13. Imanguli MM, Swaim WD, League SC, et al. Increased T-bet+ cytotoxic effectors and type I interferon-mediated processes in chronic graft-versushost disease of the oral mucosa. Blood 2009; 113:3620-3630.
14. Galon J, Angell HK, Bedognetti D, Marincola FM. The continuum of cancer immunosurveillance: prognostic, predictive, and mechanistic signatures. Immunity 2013; 39:11-26.
15. Uccellini L, DeGiorgi V, Zhao Y, et al. IRF5 gene polymorphisms in melanoma. J Transl Med 2012; 10:170.
16. Wang E, Worschech A,Marincola FM. The immunologic constant of rejection. Trends Immunol 2008; 29:256-262.
17. Spivey TL, De Giorgi V, Zhao YD, et al. The stable traits of melanoma genetics: an alternate approach to target discovery. BMC Genomics 2012; 13:156.
18. Murtas D, Maric D, De Giorgi V, et al. IRF-1 responsiveness to IFN-gamma predicts different cancer immune phenotypes. Br J Cancer 2013; 109:76-82.
19. Gentles AJ, Newman AM, Liu CL, et al. The prognostic landscape of genes and infiltrating immune cells across human cancers. Nature Med 2015; 21:938-945.
20. Salgado R, Denkert C, Demaria S, et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group. Ann Oncol 2015; 26:259-271.
21. Loi S, Michiels S, Salgado R, et al. Tumor infiltrating lymphocytes are prognostic in triple negative breast cancer and predictive for trastuzumab benefit in early breast cancer: results from the FinHER trial. Ann Oncol 2014; 25:1544-1550.
22. Ali HR, Provenzano E, Dawson SJ, et al. Association between CD8+ T-cell infiltration and breast cancer survival in 12,439 patients. Ann Oncol 2014; 25:1536-1543.
23. Teschendorff AE, Miremadi A, Pinder SE, et al. An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol 2007; 8:R157.
24. Desmedt C, Haibe-Kains B, Wirapati P, et al. Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 2008; 14:5158-5165.
25. Rody A, Holtrich U, Pusztai L, et al. T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers. Breast Cancer Res 2009; 11:R15.
26. Staaf J, Ringner M, Vallon-Christersson J, et al. Identification of subtypes in human epidermal growth factor receptor 2: positive breast cancer reveals a gene signature prognostic of outcome. J Clin Oncol 2010; 28:1813-1820.
27. Bianchini G, Iwamoto T, Qi Y, et al. Prognostic and therapeutic implications of distinct kinase expression patterns in different subtypes of breast cancer. Cancer Res 2010; 70:8852-8862.
28. Sabatier R, Finetti P, Cervera N, et al. A gene expression signature identifies two prognostic subgroups of basal breast cancer. Breast Cancer Res Treatment 2011; 126:407-420.
29. Karn T, Pusztai L, Holtrich U, et al. Homogeneous datasets of triple negative breast cancers enable the identification of novel prognostic and predictive signatures. PloS One 2011; 6:e28403.
30. Bianchini G, Qi Y, Alvarez RH, et al. Molecular anatomy of breast cancer stroma and its prognostic value in estrogen receptor-positive and-negative cancers. J Clin Oncol 2010; 28:4316-4323.
31. Ascierto ML, Kmieciak M, Idowu MO, et al. A signature of immune function genes associated with recurrence-free survival in breast cancer patients. Breast Cancer Res Treatment 2012; 131:871-880.
32. Ascierto ML, Idowu MO, Zhao Y, et al. Molecular signatures mostly associated with NK cells are predictive of relapse free survival in breast cancer patients. J Transl Med 2013; 11:145.
33. Curtis C, Shah SP, Chin SF, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 2012; 486:346-352.
34. Burstein MD, Tsimelzon A, Poage GM, et al. Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer. Clin Cancer Res 2015; 21:1688-1698.
35. Nagalla S, Chou JW, Willingham MC, et al. Interactions between immunity, proliferation and molecular subtype in breast cancer prognosis. Genome Biol 2013; 14:R34.
36. Miller LD, Chou JW, Black MA, et al. Immune gene signatures and tumor intrinsic markers delineate novel immunogenic subtypes of breast cancer. J ImmunoTher Cancer 2014; 2 (Suppl 3):256.
37. Alistar A, Chou JW, Nagalla S, et al. Dual roles for immune metagenes in breast cancer prognosis and therapy prediction. Genome Med 2014; 6:80.
38. Finak G, Bertos N, Pepin F, et al. Stromal gene expression predicts clinical outcome in breast cancer. Nature Med 2008; 14:518-527.
39. Gu-Trantien C, Loi S, Garaud S, et al. CD4(+) follicular helper T cell infiltration predicts breast cancer survival. J Clin Investig 2013; 123:2873-2892.
40. Ignatiadis M, Singhal SK, Desmedt C, et al. Gene modules and response to neoadjuvant chemotherapy in breast cancer subtypes: a pooled analysis. J Clin Oncol 2012; 30:1996-2004.
41. Bonsang-Kitzis H, Sadacca B, Hamy-Petit AS, et al. Biological network-driven gene selection identifies a stromal immune module as a key determinant of triple-negative breast carcinoma prognosis. Oncoimmunology 2015. [Epub ahead of print]
42. Perez EA, Thompson EA, Ballman KV, et al. Genomic analysis reveals that immune function genes are strongly linked to clinical outcome in the North Central Cancer Treatment Group N9831 Adjuvant Trastuzumab Trial. J Clin Oncol 2015; 33:701-708.
43. Denkert C, Loibl S, Noske A, et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 2010; 28:105-113.
44. Schmidt M, Hellwig B, Hammad S, et al. A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin kappa C as a compatible prognostic marker in human solid tumors. Clin Cancer Res 2012; 18:2695-2703.
45. Stoll G, Enot D, Mlecnik B, et al. Immune-related gene signatures predict the outcome of neoadjuvant chemotherapy. Oncoimmunology 2014; 3:e27884.
46. Bedognetti D, Wang E, Marincola FM. Meta-analysis and metagenes: CXCL-13-driven signature as a robust marker of intratumoral immune response and predictor of breast cancer chemotherapeutic outcome. Oncoimmunology 2014; 3:e28727.
47. Denkert C, von Minckwitz G, Brase JC, et al. Tumor-infiltrating lymphocytes and response to neoadjuvant chemotherapy with or without carboplatin in human epidermal growth factor receptor 2-positive and triple-negative primary breast cancers. J Clin Oncol 2015; 33:983-991.
48. Lee HJ, Lee JJ, Song IH, et al. Prognostic and predictive value of NanoStringbased immune-related gene signatures in a neoadjuvant setting of triplenegative breast cancer: relationship to tumor-infiltrating lymphocytes. Breast Cancer Res Treatment 2015; 151:619-627.
49. Bertucci F, Finetti P, Colpaert C, et al. PDL1 expression in inflammatory breast cancer is frequent and predicts for the pathological response to chemotherapy. Oncotarget 2015; 6:13506-13519.
50. Bertucci F, Ueno NT, Finetti P, et al. Gene expression profiles of inflammatory breast cancer: correlation with response to neoadjuvant chemotherapy and metastasis-free survival. Ann Oncol 2014; 25:358-365.
51. Taube JM, Klein A, Brahmer JR, et al. Association of PD-1, PD-1 ligands, and other features of the tumor immune microenvironment with response to anti-PD-1 therapy. Clin Cancer Res 2014; 20:5064-5074.
52. Jacquemier J, Bertucci F, Finetti P, et al. High expression of indoleamine 2,3-dioxygenase in the tumour is associated with medullary features and favourable outcome in basal-like breast carcinoma. International journal of cancer. J Int Cancer 2012; 130:96-104.
53. West NR, Kost SE, Martin SD, et al. Tumour-infiltrating FOXP3(+) lymphocytes are associated with cytotoxic immune responses and good clinical outcome in oestrogen receptor-negative breast cancer. Br J Cancer 2013; 108:155-162.
54. Ladoire S, Martin F, Ghiringhelli F. Prognostic role of FOXP3+ regulatory T cells infiltrating human carcinomas: the paradox of colorectal cancer. Cancer Immunol Immunother 2011; 60:909-918.
55. Kmieciak M, Gowda M, Graham L, et al. Human T cells express CD25 and Foxp3 upon activation and exhibit effector/memory phenotypes without any regulatory/suppressor function. J Transl Med 2009; 7:89.
56. Salgado R, Denkert C, Campbell C, et al. Tumor-infiltrating lymphocytes and associations with pathological complete response and event-free survival in HER2-positive early-stage breast cancer treated with lapatinib and trastuzumab: a secondary analysis of the NeoALTTO trial. J Am Med Assoc Oncol 2015; 1:448-454.
57. Bianchini G, Prat A, Pickl M, et al. Response to neoadjuvant trastuzumab and chemotherapy in ER+ and ER-HER2-positive breast cancers: gene expression analysis. J Clin Oncol 2011; 29(Suppl; abstr 529).
58. Gianni L, Bianchini G, Valagussa P, et al. Adaptive immune system and immune checkpoints are associated with response to pertuzumab (P) and trastuzumab (H) in the NeoSphere study. Cancer Res 2012. 72 (Abstr S6-7).
59. Vacchelli E, Senovilla L, Eggermont A, et al. Trial watch: chemotherapy with immunogenic cell death inducers. Oncoimmunology 2013; 2:e23510.
60. Sistigu A, Yamazaki T, Vacchelli E, et al. Cancer cell-autonomous contribution of type I interferon signaling to the efficacy of chemotherapy. Nature Med 2014; 20:1301-1309.
61. Stagg J, Loi S, Divisekera U, et al. Anti-ErbB-2 mAb therapy requires type I and II interferons and synergizes with anti-PD-1 or anti-CD137 mAb therapy. Proc Natl Acad Sci U S A 2011; 108:7142-7147.
62. Foekens JA, Martens JW, Sleijfer S. Are immune signatures a worthwhile tool for decision making in early-stage human epidermal growth factor receptor 2-positive breast cancer? J Clin Oncol 2015; 33:673-675.
63. Nanda R, Chow LQ, Dees EC, et al. A phase Ib study of pembrolizumab (MK-3475) in patients with advanced triple-negative breast cancer. Cancer Res 2015. 75 (Abstr S1-09).
64. Emens LA, Braiteh FB, Cassier P, et al. Inhibition of PD-L1 by MPDL3280A leads to clinical activity in patients with metastatic triple negative breast cancer. Cancer Res 2015. 75 (Abstr PD1-6).
65. Tomei S, Wang E, Delogu LG, et al. Non-BRAF-targeted therapy, immunotherapy, and combination therapy for melanoma. Exp Opin Biol Ther 2014; 14:663-686.
66. Tomei S, Bedognetti D, De Giorgi V, et al. The immune-related role of BRAF in melanoma. Mol Oncol 2015; 9:93-104.
67. Hoadley KA, Yau C, Wolf DM, et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell 2014; 158:929-944.
68. Spranger S, Bao R, Gajewski TF. Melanoma-intrinsic beta-catenin signalling prevents antitumour immunity. Nature 2015; 523:231-235.
69. Mlecnik B, Bindea G, Angell HK, et al. Functional network pipeline reveals genetic determinants associated with in situ lymphocyte proliferation and survival of cancer patients. Sci Transl Med 2014; 6:228ra237.
70. Rooney MS, Shukla SA, Wu CJ, et al. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell 2015; 160: 48-61.
71. Linsley PS, Speake C, Whalen E, Chaussabel D. Copy number loss of the interferon gene cluster in melanomas is linked to reduced T cell infiltrate and poor patient prognosis. PloS One 2014; 9:e109760.
72. Simeone I, Hendricks W, Miller L, et al. Toward the identification of genetic determinants of breast cancer immune responsiveness. In Breast cancer immunotherapy symposium (BRECIS): Sidra Symposia Series, April 13-14, Doha, Qatar (JITC Suppl in press); 2015.
73. Snyder A, Makarov V, Merghoub T, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med 2014; 371:2189-2199.
74. Rizvi NA, Hellmann MD, Snyder A, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in nonsmall cell lung cancer. Science 2015; 348:124-128.
75. Le DT, Uram JN, Wang H, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med 2015; 372:2509-2520.
76. Quigley D, Silwal-Pandit L, Dannenfelser R, et al. Lymphocyte invasion in IC10/basal-like breast tumors is associated with wild-type TP53. Mol Cancer Res 2015; 13:493-501.
77. Gatalica Z, Snyder C, Maney T, et al. Programmed cell death 1 (PD-1) and its ligand (PD-L1) in common cancers and their correlation with molecular cancer type. Cancer Epidemiol Biomarkers Prevent 2014; 23:2965-2970.
78. Kriegsmann M, Endris V, Wolf T, et al. Mutational profiles in triple-negative breast cancer defined by ultradeep multigene sequencing show high rates of PI3K pathway alterations and clinically relevant entity subgroup specific differences. Oncotarget 2014; 5:9952-9965.
79. Trinchieri G. Cancer and inflammation: an old intuition with rapidly evolving new concepts. Annu Rev Immunol 2012; 30:677-706.