Skip to main content

Germline genomes have a dominant-heritable contribution to cancer immune evasion and immunotherapy response



Immune evasion is a fundamental hallmark for cancer. At the early stages of tumor development, immune evasion strategies must be implemented by tumors to prevent attacks from the host immune systems. Blocking tumors’ immune evasion will re-activate the host immune systems to eliminate tumors. Immune-checkpoint therapy (ICT) which applies anti-PD-1/PD-L1 or anti-CTLA4 treatment has been a remarkable success in the past few years. However, ~70% of patients cannot gain any clinical benefits from ICT treatment due to the tumor-immunity system’s complexity. In the past, germline pathogenic variants have been thought to have only minor-heritable contributions to cancer.


Emerging evidence has shown that germline genomes play a dominant-heritable contribution to cancer via encoding the host immune system. The functional components of the immune system are encoded by the host genome, thus the germline genome might have a profound impact on cancer immune evasion and immunotherapy response. Indeed, recent studies showed that germline pathogenic variants can influence immune capacity in cancer patients at a population level by (i) shaping tumor somatic mutations, altering methylation patterns and antigen-presentation capacity or (ii) influencing NK cell’s function to modulate lymphocyte infiltration in the tumor microenvironment. In addition, the HLA (types A, B or C) genotypes also shape the landscape of tumor somatic mutations.


These results highlight the indispensable roles of germline genome in immunity and cancer development and suggest that germline genomics should be integrated into the research field of cancer biology and cancer immunotherapy.


  1. 1.

    Hanahan, D. and Weinberg, R. A. (2011) Hallmarks of cancer: the next generation. Cell, 144, 646–674

    CAS  PubMed  Google Scholar 

  2. 2.

    Kriegsman, B. A., Vangala, P., Chen, B. J., Meraner, P., Brass, A. L., Garber, M. and Rock, K. L. (2019) Frequent loss of IRF2 in cancers leads to immune evasion through decreased MHC class I antigen presentation and increased PD-L1 expression. J. Immunol., 203, 1999–2010

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Zhang, S., Kohli, K., Black, R. G., Yao, L., Spadinger, S. M., He, Q., Pillarisetty, V. G., Cranmer, L. D., Van Tine, B. A., Yee, C., et al. (2019) Systemic interferon-y increases MHC class I expression and T-cell infiltration in cold tumors: results of a phase 0 clinical trial. Cancer Immunol. Res., 7, 1237–1243

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Lu, Y., Zhang, M., Wang, S., Hong, B., Wang, Z., Li, H., Zheng, Y., Yang, J., Davis, R. E., Qian, J., et al. (2014) p38 MAPK-inhibited dendritic cells induce superior antitumour immune responses and overcome regulatory T-cell-mediated immunosuppression. Nat. Commun., 5, 4229

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Loi, S., Dushyanthen, S., Beavis, P. A., Salgado, R., Denkert, C., Savas, P., Combs, S., Rimm, D. L., Giltnane, J. M., Estrada, M. V., et al. (2016) RAS/MAPK activation is associated with reduced tumor-infiltrating lymphocytes in triple-negative breast cancer: Therapeutic cooperation between MEK and PD-1/PD-L1 immune checkpoint inhibitors. Clin. Cancer Res., 22, 1499–1509

    CAS  PubMed  Google Scholar 

  6. 6.

    Luke, J. J., Bao, R., Sweis, R. F., Spranger, S. and Gajewski, T. F. (2019) WNT/β-catenin pathway activation correlates with immune exclusion across human cancers. Clin. Cancer Res., 25, 3074–3083

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Wang, B., Tian, T., Kalland, K.-H., Ke, X. and Qu, Y. (2018) Targeting Wnt/β-catenin signaling for cancer immunotherapy. Trends Pharmacol. Sci., 39, 648–658

    CAS  PubMed  Google Scholar 

  8. 8.

    Haslam, A. and Prasad, V. (2019) Estimation of the percentage of US patients with cancer who are eligible for and respond to checkpoint inhibitor immunotherapy drugs. JAMA Netw. Open, 2, e192535

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    Khair, D. O., Bax, H. J., Mele, S., Crescioli, S., Pellizzari, G., Khiabany, A., Nakamura, M., Harris, R. J., French, E., Hoffmann, R. M., et al. (2019) Combining immune checkpoint inhibitors: established and emerging targets and strategies to improve outcomes in melanoma. Front. Immunol., 10, 453

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Chen, D. S. and Mellman, I. (2013) Oncology meets immunology: the cancer-immunity cycle. Immunity, 39, 1–10

    PubMed  Google Scholar 

  11. 11.

    Binnewies, M., Roberts, E. W., Kersten, K., Chan, V., Fearon, D. F., Merad, M., Coussens, L. M., Gabrilovich, D. I., Ostrand-Rosenberg, S., Hedrick, C. C., et al. (2018) Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat. Med., 24, 541–550

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Gonzalez, H., Hagerling, C. and Werb, Z. (2018) Roles of the immune system in cancer: from tumor initiation to metastatic progression. Genes Dev., 32, 1267–1284

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Darvin, P., Toor, S. M., Sasidharan Nair, V. and Elkord, E. (2018) Immune checkpoint inhibitors: recent progress and potential biomarkers. Exp. Mol. Med., 50, 1–11

    PubMed  Google Scholar 

  14. 14.

    Szabo, C. I. and King, M. C. (1997) Population genetics of BRCA1 and BRCA2. Am. J. Hum. Genet., 60, 1013–1020

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Malone, K. E., Daling, J. R., Doody, D. R., Hsu, L., Bernstein, L., Coates, R. J., Marchbanks, P. A., Simon, M. S., McDonald, J. A., Norman, S. A., et al. (2006) Prevalence and predictors of BRCA1 and BRCA2 mutations in a population-based study of breast cancer in white and black American women ages 35 to 64 years. Cancer Res., 66, 8297–8308

    CAS  PubMed  Google Scholar 

  16. 16.

    Bodmer, W. and Tomlinson, I. (2010) Rare genetic variants and the risk of cancer. Curr. Opin. Genet. Dev., 20, 262–267

    CAS  PubMed  Google Scholar 

  17. 17.

    Knudson, Jr., A. G. (1971) Mutation and cancer: statistical study of retinoblastoma. Proc. Natl. Acad. Sci. USA, 68, 820–823

    PubMed  Google Scholar 

  18. 18.

    Knudson, A. G. (2001) Two genetic hits (more or less) to cancer. Nat. Rev. Cancer, 1, 157–162

    CAS  PubMed  Google Scholar 

  19. 19.

    Donovan, S. L., Schweers, B., Martins, R., Johnson, D. and Dyer, M. A. (2006) Compensation by tumor suppressor genes during retinal development in mice and humans. BMC Biol., 4, 14

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Ajioka, I., Martins, R. A. P., Bayazitov, I. T., Donovan, S., Johnson, D. A., Frase, S., Cicero, S. A., Boyd, K., Zakharenko, S. S. and Dyer, M. A. (2007) Differentiated horizontal interneurons clonally expand to form metastatic retinoblastoma in mice. Cell, 131, 378–390

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Malkin, D., Li, F. P., Strong, L. C., Fraumeni, J. F. Jr, Nelson, C. E., Kim, D. H., Kassel, J., Gryka, M. A., Bischoff, F. Z., Tainsky, M. A., et al. (1990) Germ linep53 mutations in a familial syndrome of breast cancer, sarcomas, and other neoplasms. Science, 250, 1233–1238

    CAS  PubMed  Google Scholar 

  22. 22.

    Kemp, C. J., Wheldon, T. and Balmain, A. (1994) p53-deficient mice are extremely susceptible to radiation-induced tumorigenesis. Nat. Genet., 8, 66–69

    CAS  PubMed  Google Scholar 

  23. 23.

    Lee, J. M., Abrahamson, J. L. A., Kandel, R., Donehower, L. A. and Bernstein, A. (1994) Susceptibility to radiation-carcinogenesis and accumulation of chromosomal breakage in p53 deficient mice. Oncogene, 9, 3731–3736

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Levine, A. J., Hu, W. and Feng, Z. (2006) The P53 pathway: what questions remain to be explored? Cell Death Differ., 13, 1027–1036

    CAS  PubMed  Google Scholar 

  25. 25.

    Maistro, S., Teixeira, N., Encinas, G., Katayama, M. L. H., Niewiadonski, V. D. T., Cabral, L. G., Ribeiro, R. M., Gaburo Junior, N., de Gouvêa, A. C., Carraro, D. M., et al. (2016) Germline mutations in BRCA1 and BRCA2 in epithelial ovarian cancer patients in Brazil. BMC Cancer, 16, 934

    PubMed  PubMed Central  Google Scholar 

  26. 26.

    Chan, S. H., Lim, W. K., Ishak, N. D. B., Li, S.-T., Goh, W. L., Tan, G. S., Lim, K. H., Teo, M., Young, C. N. C., Malik, S., et al. (2017) Germline mutations in cancer predisposition genes are frequent in sporadic sarcomas. Sci. Rep., 7, 10660

    PubMed  PubMed Central  Google Scholar 

  27. 27.

    Kuchenbaecker, K. B., Hopper, J. L., Barnes, D. R., Phillips, K.-A., Mooij, T. M., Roos-Blom, M.-J., Jervis, S., van Leeuwen, F. E., Milne, R. L., Andrieu, N., et al. (2017) Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA, 317, 2402–2416

    CAS  PubMed  Google Scholar 

  28. 28.

    Liaw, D., Marsh, D. J., Li, J., Dahia, P. L. M., Wang, S. I., Zheng, Z., Bose, S., Call, K. M., Tsou, H. C., Peacoke, M., et al. (1997) Germline mutations of the PTEN gene in Cowden disease, an inherited breast and thyroid cancer syndrome. Nat. Genet., 16, 64–67

    CAS  PubMed  Google Scholar 

  29. 29.

    De Queiroz Rossanese, L. B., De Lima Marson, F. A., Ribeiro, J. D., Coy, C. S. and Bertuzzo, C. S. (2013) APC germline mutations in families with familial adenomatous polyposis. Oncol. Rep., 30, 2081–2088

    PubMed  Google Scholar 

  30. 30.

    Washington, K. and Zemper, A. E. D. (2019) Apc-related models of intestinal neoplasia: a brief review for pathologists. Surg. Exp. Pathol., 2, 11

    Google Scholar 

  31. 31.

    Zeineldin, M. and Neufeld, K. L. (2013) More than two decades of Apc modeling in rodents. Biochim. Biophys. Acta, 1836, 80–89

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Moore, L. E., Nickerson, M. L., Brennan, P., Toro, J. R., Jaeger, E., Rinsky, J., Han, S. S., Zaridze, D., Matveev, V., Janout, V., et al. (2011) Von hippel-lindau (VHL) inactivation in sporadic clear cell renal cancer: associations with germline VHL polymorphisms and etiologic risk factors. PLoS Genet., 7, e1002312

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Gray, P. N., Tsai, P., Chen, D., Wu, S., Hoo, J., Mu, W., Li, B., Vuong, H., Lu, H. M., Batth, N., et al. (2018) TumorNext-Lynch-MMR: a comprehensive next generation sequencing assay for the detection of germline and somatic mutations in genes associated with mismatch repair deficiency and Lynch syndrome. Oncotarget, 9, 20304–20322

    PubMed  PubMed Central  Google Scholar 

  34. 34.

    Mou, H., Kennedy, Z., Anderson, D. G., Yin, H. and Xue, W. (2015) Precision cancer mouse models through genome editing with CRISPR-Cas9. Genome Med., 7, 53

    PubMed  PubMed Central  Google Scholar 

  35. 35.

    Guernet, A. and Grumolato, L. (2017) CRISPR/Cas9 editing of the genome for cancer modeling. Methods, 121–122, 130–137

    PubMed  Google Scholar 

  36. 36.

    Park, S., Supek, F. and Lehner, B. (2018) Systematic discovery of germline cancer predisposition genes through the identification of somatic second hits. Nat. Commun., 9, 2601

    PubMed  PubMed Central  Google Scholar 

  37. 37.

    Huang, K. L., Mashl, R. J., Wu, Y., Ritter, D. I., Wang, J., Oh, C., Paczkowska, M., Reynolds, S., Wyczalkowski, M. A., Oak, N., et al. (2018) Pathogenic germline variants in 10,389 adult cancers. Cell, 173, 355–370.e14

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Kilpivaara, O. and Aaltonen, L. A. (2013) Diagnostic cancer genome sequencing and the contribution of germline variants. Science, 339, 1559–1562

    CAS  PubMed  Google Scholar 

  39. 39.

    Wang, E., Zaman, N., Mcgee, S., Milanese, J.-S., Masoudi-Nejad, A. and O’Connor-McCourt, M. (2015) Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data. Semin. Cancer Biol., 30, 4–12

    PubMed  Google Scholar 

  40. 40.

    Sever, R. and Brugge, J. S. (2015) Signal transduction in cancer. Cold Spring Harb. Perspect. Med., 5, a006098–a006098

    PubMed  PubMed Central  Google Scholar 

  41. 41.

    Wellenstein, M. D. and de Visser, K. E. (2018) Cancer-cell-intrinsic mechanisms shaping the tumor immune landscape. Immunity, 48, 399–416

    CAS  PubMed  Google Scholar 

  42. 42.

    Nguyen, K. B. and Spranger, S. (2020) Modulation of the immune microenvironment by tumor-intrinsic oncogenic signaling. J. Cell Biol., 219, e201908224

    PubMed  Google Scholar 

  43. 43.

    Lim, Y. W., Chen-Harris, H., Mayba, O., Lianoglou, S., Wuster, A., Bhangale, T., Khan, Z., Mariathasan, S., Daemen, A., Reeder, J., et al. (2018) Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration. Proc. Natl. Acad. Sci. USA, 115, E11701–E11710

    CAS  PubMed  Google Scholar 

  44. 44.

    Robinson, J., Halliwell, J. A., Hayhurst, J. D., Flicek, P., Parham, P. and Marsh, S. G. E. (2015) The IPD and IMGT/HLA database: allele variant databases. Nucleic Acids Res., 43, D423–D431

    CAS  PubMed  Google Scholar 

  45. 45.

    Marty, R., Kaabinejadian, S., Rossell, D., Slifker, M. J., van de Haar, J., Engin, H. B., de Prisco, N., Ideker, T., Hildebrand, W. H., Font-Burgada, J., et al. (2017) MHC-I genotype restricts the oncogenic mutational landscape. Cell, 171, 1272–1283.e15

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Wang, E., Zou, J., Zaman, N., Beitel, L. K., Trifiro, M. and Paliouras, M. (2013) Cancer systems biology in the genome sequencing era: part 2, evolutionary dynamics of tumor clonal networks and drug resistance. Semin. Cancer Biol., 23, 286–292

    CAS  PubMed  Google Scholar 

  47. 47.

    Wang, E., Zou, J., Zaman, N., Beitel, L. K., Trifiro, M. and Paliouras, M. (2013) Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks. Semin. Cancer Biol., 23, 279–285

    CAS  PubMed  Google Scholar 

  48. 48.

    Milanese J.-S., Tibiche C., Zou J., Meng Z., Nantel A., Drouin S., Marcotte R., and Wang E. (2019) Germline variants associated with leukocyte genes predict tumor recurrence in breast cancer patients. NPJ Precis. Oncol., 3, 28

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Parsons, B. L. (2008) Many different tumor types have polyclonal tumor origin: evidence and implications. Mutat. Res., 659, 232–247

    CAS  PubMed  Google Scholar 

  50. 50.

    Parsons, B. L. (2018) Multiclonal tumor origin: evidence and implications. Mutat. Res., 777, 1–18

    CAS  PubMed  Google Scholar 

  51. 51.

    Knudson, A. G. Jr. (1973) Mutation and human cancer. Adv. Cancer Res., 17, 317–352

    Google Scholar 

  52. 52.

    Nowell, P. C. (1976) The clonal evolution of tumor cell populations. Science, 194, 23–28

    CAS  PubMed  Google Scholar 

  53. 53.

    Fearon, E. R., Hamilton, S. R. and Vogelstein, B. (1987) Clonal analysis of human colorectal tumors. Science, 238, 193–197

    CAS  PubMed  Google Scholar 

  54. 54.

    Vogelstein, B., Fearon, E. R., Hamilton, S. R. and Feinberg, A. P. (1985) Use of restriction fragment length polymorphisms to determine the clonal origin of human tumors. Science, 227, 642–645

    CAS  PubMed  Google Scholar 

  55. 55.

    Ross, E. M. and Markowetz, F. (2016) OncoNEM: inferring tumor evolution from single-cell sequencing data. Genome Biol., 17, 69

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Hou, Y., Song, L., Zhu, P., Zhang, B., Tao, Y., Xu, X., Li, F., Wu, K., Liang, J., Shao, D., et al. (2012) Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell, 148, 873–885

    CAS  PubMed  Google Scholar 

  57. 57.

    Xu, X., Hou, Y., Yin, X., Bao, L., Tang, A., Song, L., Li, F., Tsang, S., Wu, K., Wu, H., et al. (2012) Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell, 148, 886–895

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Shi, X., Chakraborty, P. and Chaudhuri, A. (2018) Unmasking tumor heterogeneity and clonal evolution by single-cell analysis. J. Cancer Metastasis Treat., 4, 47

    CAS  Google Scholar 

  59. 59.

    Milanese, J., Tibiche, C., Zaman, N., Zou, J., Han, P., Meng, Z., Nantel, A., Droit, A. and Wang, E. (2020) eTumorMetastasis, a network-based algorithm predicts clinical outcomes using whole-exome sequencing data of cancer patients. Genom. Proteom. Bioinfor., (In press)

  60. 60.

    Li, J., Lenferink, A. E. G., Deng, Y., Collins, C., Cui, Q., Purisima, E. O., O’Connor-McCourt, M. D. and Wang, E. (2010) Identification of high-quality cancer prognostic markers and metastasis network modules. Nat. Commun., 1, 34

    PubMed  Google Scholar 

  61. 61.

    Gao, S., Tibiche, C., Zou, J., Zaman, N., Trifiro, M., O’Connor-McCourt, M. and Wang, E. (2016) Identification and construction of combinatory cancer hallmark-based gene signature sets to predict recurrence and chemotherapy benefit in stage II colorectal cancer. JAMA Oncol., 2, 37–45

    PubMed  Google Scholar 

  62. 62.

    Toi, M., Iwata, H., Yamanaka, T., Masuda, N., Ohno, S., Nakamura, S., Nakayama, T., Kashiwaba, M., Kamigaki, S. and Kuroi, K., et al. (2010) Clinical significance of the 21-gene signature (oncotype DX) in hormone receptor-positive early stage primary breast cancer in the Japanese population. Cancer, 116, 3112–3118

    CAS  PubMed  Google Scholar 

  63. 63.

    Feng, X., Xu, X., Li, D., Cui, Q. and Wang, E. (2019) Germline genomic patterns are associated with cancer risk, oncogenic pathways and clinical outcomes. bioRxiv, 616268

  64. 64.

    Xu, X., Li, J., Zou, J., Feng, X., Zhang, C., Zheng, R., Duanmu, W., Saha-Mandal, A., Ming, Z. and Wang, E. (2019) Association of germline variants in natural killer cells with tumor immune microenvironment subtypes, tumor-infiltrating lymphocytes, immunotherapy response, clinical outcomes, and cancer risk. JAMA Netw. Open, 2, e199292

    PubMed  PubMed Central  Google Scholar 

  65. 65.

    Sharma, S., Kelly, T. K. and Jones, P. A. (2010) Epigenetics in cancer. Carcinogenesis, 31, 27–36

    CAS  PubMed  Google Scholar 

  66. 66.

    Witkowski, L., Carrot-Zhang, J., Albrecht, S., Fahiminiya, S., Hamel, N., Tomiak, E., Grynspan, D., Saloustros, E., Nadaf, J., Rivera, B., et al. (2014) Germline and somatic SMARCA4 mutations characterize small cell carcinoma of the ovary, hypercalcemic type. Nat. Genet., 46, 438–443

    CAS  PubMed  Google Scholar 

  67. 67.

    Butler, J. S., Koutelou, E., Schibler, A. C. and Dent, S. Y. R. (2012) Histone-modifying enzymes: regulators of developmental decisions and drivers of human disease. Epigenomics, 4, 163–177

    CAS  PubMed  PubMed Central  Google Scholar 

  68. 68.

    Klutstein, M., Nejman, D., Greenfield, R. and Cedar, H. (2016) DNA methylation in cancer and aging. Cancer Res., 76, 3446–3450

    CAS  PubMed  Google Scholar 

  69. 69.

    Miao, D., Margolis, C. A., Gao, W., Voss, M. H., Li, W., Martini, D. J., Norton, C., Bossé, D., Wankowicz, S. M., Cullen, D., et al. (2018) Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma. Science, 359, 801–806

    CAS  PubMed  PubMed Central  Google Scholar 

  70. 70.

    Pan, D., Kobayashi, A., Jiang, P., Ferrari de Andrade, L., Tay, R. E., Luoma, A. M., Tsoucas, D., Qiu, X., Lim, K., Rao, P., et al. (2018) A major chromatin regulator determines resistance of tumor cells to T cell-mediated killing. Science, 359, 770–775

    CAS  PubMed  PubMed Central  Google Scholar 

  71. 71.

    Kearney, C. J., Vervoort, S. J., Hogg, S. J., Ramsbottom, K. M., Freeman, A. J., Lalaoui, N., Pijpers, L., Michie, J., Brown, K. K., Knight, D. A., et al. (2018) Tumor immune evasion arises through loss of TNF sensitivity. Sci. Immunol., 3, eaar3451

    PubMed  Google Scholar 

  72. 72.

    Beatty, G. L. and Paterson, Y. (2000) IFN-γ can promote tumor evasion of the immune system in vivo by down-regulating cellular levels of an endogenous tumor antigen. J. Immunol., 165, 5502–5508

    CAS  PubMed  Google Scholar 

  73. 73.

    Houlahan, K. E., Shiah, Y.-J., Gusev, A., Yuan, J., Ahmed, M., Shetty, A., Ramanand, S. G., Yao, C. Q., Bell, C., O’Connor, E., et al. (2019) Genome-wide germline correlates of the epigenetic landscape of prostate cancer. Nat. Med., 25, 1615–1626

    CAS  PubMed  PubMed Central  Google Scholar 

  74. 74.

    Foulkes, W. D. (2008) Inherited susceptibility to common cancers. N. Engl. J. Med., 359, 2143–2153

    CAS  PubMed  Google Scholar 

  75. 75.

    Torgovnick, A. and Schumacher, B. (2015) DNA repair mechanisms in cancer development and therapy. Front. Genet., 6, 157

    PubMed  PubMed Central  Google Scholar 

  76. 76.

    Büttner, R., Longshore, J. W., López-Ríos, F., Merkelbach-Bruse, S., Normanno, N., Rouleau, E. and Penault-Llorca, F. (2019) Implementing TMB measurement in clinical practice: considerations on assay requirements. ESMO Open, 4, e000442

    PubMed  PubMed Central  Google Scholar 

  77. 77.

    Caruso, C. (2019) TMB faces validation hurdles. Cancer Discov., 9, 1334–1334

    Google Scholar 

  78. 78.

    Potapova, T. A., Zhu, J. and Li, R. (2013) Aneuploidy and chromosomal instability: a vicious cycle driving cellular evolution and cancer genome chaos. Cancer Metastasis Rev., 32, 377–389

    PubMed  Google Scholar 

  79. 79.

    Pérez de Castro, I. and Malumbres, M. (2012) Mitotic stress and chromosomal instability in cancer: the case for TPX2. Genes Cancer, 3, 721–730

    PubMed  PubMed Central  Google Scholar 

  80. 80.

    Mackenzie, K. J., Carroll, P., Martin, C.-A., Murina, O., Fluteau, A., Simpson, D. J., Olova, N., Sutcliffe, H., Rainger, J. K., Leitch, A., et al. (2017) cGAS surveillance of micronuclei links genome instability to innate immunity. Nature, 548, 461–465

    CAS  PubMed  PubMed Central  Google Scholar 

  81. 81.

    Motwani, M. and Fitzgerald, K. A. (2017) cGAS micro-manages genotoxic stress. Immunity, 47, 616–617

    CAS  PubMed  Google Scholar 

  82. 82.

    Breunis, W. B., Tarazona-Santos, E., Chen, R., Kiley, M., Rosenberg, S. A. and Chanock, S. J. (2008) Influence of cytotoxic T lymphocyte-associated antigen 4 (CTLA4) common polymorphisms on outcome in treatment of melanoma patients with CTLA-4 blockade. J. Immunother., 31, 586–590

    CAS  PubMed  PubMed Central  Google Scholar 

  83. 83.

    Hamid, O., Schmidt, H., Nissan, A., Ridolfi, L., Aamdal, S., Hansson, J., Guida, M., Hyams, D. M., Gómez, H., Bastholt, L., et al. (2011) A prospective phase II trial exploring the association between tumor microenvironment biomarkers and clinical activity of ipilimumab in advanced melanoma. J. Transl. Med., 9, 204

    CAS  PubMed  PubMed Central  Google Scholar 

  84. 84.

    Kuehn H. S., Ouyang W., Lo B., Deenick E. K., Niemela J. E., Avery D. T., Schickel J.-N., Tran D. Q., Stoddard J., Zhang Y., et al. (2014) Immune dysregulation in human subjects with heterozygous germline mutations in CTLA4. Science, 345, 1623–1627

    CAS  PubMed  PubMed Central  Google Scholar 

  85. 85.

    Chat, V., Ferguson, R., Simpson, D., Kazlow, E., Lax, R., Moran, U., Wilson, M., Pavlick, A. C., Sullivan, R. J., Flaherty, K., et al. (2018) Autoimmune genetic variants as germline biomarkers of response in melanoma immunotherapy treatment. J. Clin. Oncol., 36, 3079–3079

    Google Scholar 

  86. 86.

    Ugurel, S., Schrama, D., Keller, G., Schadendorf, D., Bröcker, E.-B., Houben, R., Zapatka, M., Fink, W., Kaufman, H. L. and Becker, J. C. (2008) Impact of the CCR5 gene polymorphism on the survival of metastatic melanoma patients receiving immunotherapy. Cancer Immunol. Immunother., 57, 685–691

    CAS  PubMed  Google Scholar 

  87. 87.

    Uccellini, L., De Giorgi, V., Zhao, Y., Tumaini, B., Erdenebileg, N., Dudley, M. E., Tomei, S., Bedognetti, D., Ascierto, M. L., Liu, Q., et al. (2012) IRF5 gene polymorphisms in melanoma. J. Transl. Med., 10, 170

    CAS  PubMed  PubMed Central  Google Scholar 

  88. 88.

    Arce Vargas, F., Furness, A. J. S., Litchfield, K., Joshi, K., Rosenthal, R., Ghorani, E., Solomon, I., Lesko, M. H., Ruef, N., Roddie, C., et al. (2018) Fc effector function contributes to the activity of human anti-CTLA-4 antibodies. Cancer Cell, 33, 649–663.e4

    CAS  PubMed  PubMed Central  Google Scholar 

  89. 89.

    Van Allen, E. M., Golay, H. G., Liu, Y., Koyama, S., Wong, K., Taylor-Weiner, A., Giannakis, M., Harden, M., Rojas-Rudilla, V., Chevalier, A., et al. (2015) Long-term benefit of PD-L1 blockade in lung cancer associated with JAK3 activation. Cancer Immunol. Res., 3, 855–863

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90.

    Zitvogel, L., Kepp, O. and Kroemer, G. (2011) Immune parameters affecting the efficacy of chemotherapeutic regimens. Nat. Rev. Clin. Oncol., 8, 151–160

    CAS  PubMed  Google Scholar 

  91. 91.

    Vacchelli E., Ma Y., Baracco E. E., Sistigu A., Enot D. P., Pietrocola F., Yang H., Adjemian S., Chaba K., Semeraro M., et al. (2015) Chemotherapy-induced antitumor immunity requires formyl peptide receptor 1. Science, 350, 972–978

    CAS  PubMed  Google Scholar 

  92. 92.

    Lamichhane, P., Karyampudi, L., Shreeder, B., Krempski, J., Bahr, D., Daum, J., Kalli, K. R., Goode, E. L., Block, M. S., Cannon, M. J., et al. (2017) IL10 Release upon PD-1 blockade sustains immunosuppression in ovarian cancer. Cancer Res., 77, 6667–6678

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93.

    Zaretsky, J. M., Garcia-Diaz, A., Shin, D. S., Escuin-Ordinas, H., Hugo, W., Hu-Lieskovan, S., Torrejon, D. Y., Abril-Rodriguez, G., Sandoval, S., Barthly, L., et al. (2016) Mutations associated with acquired resistance to PD-1 blockade in melanoma. N. Engl. J. Med., 375, 819–829

    CAS  PubMed  PubMed Central  Google Scholar 

  94. 94.

    Gao, J., Shi, L. Z., Zhao, H., Chen, J., Xiong, L., He, Q., Chen, T., Roszik, J., Bernatchez, C., Woodman, S. E., et al. (2016) Loss of IFN-γ pathway genes in tumor cells as a mechanism of resistance to anti-CTLA-4 therapy. Cell, 167, 397–404.e9

    CAS  PubMed  PubMed Central  Google Scholar 

  95. 95.

    Shan, J., Chouchane, A., Mokrab, Y., Saad, M., Boujassoum, S., Sayaman, R. W., Ziv, E., Bouaouina, N., Remadi, Y., Gabbouj, S., et al. (2019) Genetic variation in CCL5 signaling genes and triple negative breast cancer: susceptibility and prognosis implications. Front. Oncol., 9, 1328

    PubMed  PubMed Central  Google Scholar 

  96. 96.

    Hosseini, E., Schwarer, A. P. and Ghasemzadeh, M. (2015) Do human leukocyte antigen E polymorphisms influence graft-versus-leukemia after allogeneic hematopoietic stem cell transplantation? Exp. Hematol., 43, 149–157

    CAS  PubMed  Google Scholar 

  97. 97.

    Wu, S., Powers, S., Zhu, W. and Hannun, Y. A. (2016) Substantial contribution of extrinsic risk factors to cancer development. Nature, 529, 43–47

    CAS  PubMed  Google Scholar 

  98. 98.

    Tomasetti, C., Li, L. and Vogelstein, B. (2017) Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention. Science, 355, 1330–1334

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information



Corresponding authors

Correspondence to Bo Liao or Edwin Wang.

Ethics declarations

The authors Xue Jiang, Mohammad Asad, Lin Li, Zhanpeng Sun, Jean-Sébastien Milanese, Bo Liao and Edwin Wang declare that they have no conflict of interests.

This article is a review article and does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Author Summary: Traditionally, it has been believed that germline pathogenic variants and family histories explain 5%-10% of cancer patient population, thus, heredity has been suggested to have a small contribution to tumorigenesis and metastasis. However, the host immune system often interacts with cancer cells, therefore, escaping from the host immune system surveillance is one of the critical means for tumorigenesis. In the past a few years, it has been shown that germline pathogenic variants influence immune capacity in cancer patients at a population level. From the cancer-immune system point view, heredity plays a dominant role in tumorigenesis, metastasis and immunotherapy response.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jiang, X., Asad, M., Li, L. et al. Germline genomes have a dominant-heritable contribution to cancer immune evasion and immunotherapy response. Quant Biol 8, 216–227 (2020).

Download citation


  • germline
  • genomics
  • cancer
  • immune evasion
  • immunotherapy response