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Prognostic and predictive biomarkers for immunotherapy in advanced renal cell carcinoma

Abstract

The therapeutic algorithm of renal cell carcinoma has been revolutionized by the approval of immunotherapy agents by regulatory agencies. However, objective and durable responses are still not observed in a large number of patients, and prognostic and predictive biomarkers for immunotherapy response are urgently needed. Prognostic models used in clinical practice are based on clinical and laboratory factors (such as hypercalcaemia, neutrophil count or Karnofsky Performance Status), but, with progress in molecular biology and genome sequencing techniques, new renal cell carcinoma molecular features that might improve disease course and outcomes prediction have been highlighted. An implementation of current models is needed to improve the accuracy of prognosis in the immuno-oncology era. Moreover, several potential biomarkers are currently under evaluation, but effective markers to select patients who might benefit from immunotherapy and to guide therapeutic strategies are still far from validation.

Key points

  • No prognostic and predictive biomarkers of response to immune checkpoint inhibitors (ICIs) are available in clinical practice.

  • Current prognostic models for renal cell carcinoma (RCC) should be improved by integrating novel markers.

  • Programmed cell death 1 ligand 1 (PDL1) expression level is a negative prognostic factor with an unclear predictive role for ICI response in patients with RCC.

  • Tumour mutational burden and gene expression profile are promising predictive factors of response to ICIs that deserve to be further explored.

  • Research is in progress to identify additional biomarkers, which, however, are still far from validation and approval.

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Fig. 1: Evolution of prognostic markers in metastatic renal cell carcinoma — towards integrated prognostic models.
Fig. 2: Tumour microenvironment features to predict response to immunotherapy in patients with mRCC.
Fig. 3: Most promising predictive biomarkers of response to immunotherapy in mRCC.

References

  1. Siegel, R. L., Miller, K. D., Fuchs, H. E. & Jemal, A. Cancer Statistics, 2021. CA Cancer J. Clin. 71, 7–33 (2021).

    Article  PubMed  Google Scholar 

  2. Saad, A. M. et al. Trends in renal-cell carcinoma incidence and mortality in the United States in the last 2 decades: a SEER-based study. Clin. Genitourin. Cancer 17, 46–57.e5 (2019).

    Article  PubMed  Google Scholar 

  3. Moch, H., Cubilla, A. L., Humphrey, P. A., Reuter, V. E. & Ulbright, T. M. The 2016 WHO classification of tumours of the urinary system and male genital organs — part A: renal, penile, and testicular tumours. Eur. Urol. 70, 93–105 (2016).

    Article  PubMed  Google Scholar 

  4. Hsieh, J. J. et al. Renal cell carcinoma. Nat. Rev. Dis. Primers 3, 17009 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Marchetti, A. et al. The molecular characteristics of non-clear cell renal cell carcinoma: what’s the story morning glory? Int. J. Mol. Sci. 22, 6237 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Cimadamore, A. et al. Molecular characterization and diagnostic criteria of renal cell carcinoma with emphasis on liquid biopsies. Expert. Rev. Mol. Diagn. 20, 141–150 (2020).

    Article  PubMed  CAS  Google Scholar 

  7. Choueiri, T. K. & Motzer, R. J. Systemic therapy for metastatic renal-cell carcinoma. N. Engl. J. Med. 376, 354–366 (2017).

    Article  PubMed  CAS  Google Scholar 

  8. Bianchi, M. et al. Distribution of metastatic sites in renal cell carcinoma: a population-based analysis. Ann. Oncol. 23, 973–980 (2012).

    Article  PubMed  CAS  Google Scholar 

  9. Motzer, R. J. et al. Kidney cancer, version 3.2022, NCCN clinical practice guidelines in oncology. J. Natl Compr. Cancer Netw. 20, 71–90 (2022).

    Article  Google Scholar 

  10. Rizzo, A., Rosellini, M., Marchetti, A., Mollica, V. & Massari, F. Determinants of treatment for first-line immune-based combinations in metastatic renal cell carcinoma: a critical overview of recent evidence. Immunotherapy 13, 685–692 (2021).

    Article  PubMed  CAS  Google Scholar 

  11. Motzer, R. J. et al. Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell carcinoma. N. Engl. J. Med. 378, 1277–1290 (2018). Pivotal and practice-changing trial in mRCC testing nivolumab + ipilimumab in the first-line setting.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Rini, B. I. et al. Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N. Engl. J. Med. 380, 1116–1127 (2019). Pivotal and practice-changing trial in mRCC testing pembrolizumab + axitinib in the first-line setting.

    Article  PubMed  CAS  Google Scholar 

  13. Motzer, R. J. et al. Avelumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N. Engl. J. Med. 380, 1103–1115 (2019). Pivotal and practice-changing trial in mRCC testing avelumab + axitinib in the first-line setting.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Choueiri, T. K. et al. Nivolumab plus cabozantinib versus sunitinib for advanced renal-cell carcinoma. N. Engl. J. Med. 384, 829–841 (2021). Pivotal and practice-changing trial in mRCC testing nivolumab + cabozantinib in the first-line setting.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Motzer, R. et al. Lenvatinib plus pembrolizumab or everolimus for advanced renal cell carcinoma. N. Engl. J. Med. 384, 1289–1300 (2021). Pivotal and practice-changing trial in mRCC testing pembrolizumab + lenvatinib in the first-line setting.

    Article  PubMed  CAS  Google Scholar 

  16. Navani, V. & Heng, D. Y. C. Treatment selection in first-line metastatic renal cell carcinoma — the contemporary treatment paradigm in the age of combination therapy. JAMA Oncol. 8, 292 (2022).

    Article  PubMed  Google Scholar 

  17. Massari, F. et al. Immune-based combinations for the treatment of metastatic renal cell carcinoma: a meta-analysis of randomised clinical trials. Eur. J. Cancer 154, 120–127 (2021).

    Article  PubMed  CAS  Google Scholar 

  18. Ko, J. J. et al. The International Metastatic Renal Cell Carcinoma Database Consortium model as a prognostic tool in patients with metastatic renal cell carcinoma previously treated with first-line targeted therapy: a population-based study. Lancet Oncol. 16, 293–300 (2015).

    Article  PubMed  Google Scholar 

  19. Dudani, S., Savard, M.-F. & Heng, D. Y. C. An update on predictive biomarkers in metastatic renal cell carcinoma. Eur. Urol. Focus. 6, 34–36 (2020).

    Article  PubMed  Google Scholar 

  20. Ghatalia, P. & Rathmell, W. K. Systematic review: ClearCode 34 — a validated prognostic signature in clear cell renal cell carcinoma (ccRCC). Kidney Cancer 2, 23–29 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kapur, P. et al. Effects on survival of BAP1 and PBRM1 mutations in sporadic clear-cell renal-cell carcinoma: a retrospective analysis with independent validation. Lancet Oncol. 14, 159–167 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Ljungberg, B. et al. European Association of Urology guidelines on renal cell carcinoma: the 2022 update. Eur. Urol. https://doi.org/10.1016/j.eururo.2022.03.006 (2022).

    Article  PubMed  Google Scholar 

  23. Tan, M.-H. et al. Comparison of the UCLA integrated staging system and the Leibovich Score in survival prediction for patients with nonmetastatic clear cell renal cell carcinoma. Urology 75, 1365–1370.e3 (2010).

    Article  PubMed  Google Scholar 

  24. Blackmur, J. P. et al. Leibovich score is the optimal clinico-pathological system associated with recurrence of non-metastatic clear cell renal cell carcinoma. Urol. Oncol. Semin. Orig. Investig. 39, 438.e11–438.e21 (2021).

    Google Scholar 

  25. Erdem, S. et al. External validation of the VENUSS prognostic model to predict recurrence after surgery in non-metastatic papillary renal cell carcinoma: a multi-institutional analysis. Urol. Oncol. Semin. Orig. Investig. https://doi.org/10.1016/j.urolonc.2022.01.006 (2022).

    Article  Google Scholar 

  26. Cortellini, A. et al. Predictive ability for disease-free survival of the grade, age, nodes, and tumor (GRANT) score in patients with resected renal cell carcinoma. Curr. Urol. 14, 98–104 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Clark, G. M. Prognostic factors versus predictive factors: examples from a clinical trial of erlotinib. Mol. Oncol. 1, 406–412 (2008).

    Article  PubMed  Google Scholar 

  28. Chen, J., Jiang, C. C., Jin, L. & Zhang, X. D. Regulation of PD-L1: a novel role of pro-survival signalling in cancer. Ann. Oncol. 27, 409–416 (2016).

    Article  PubMed  CAS  Google Scholar 

  29. Dong, H., Zhu, G., Tamada, K. & Chen, L. B7-H1, a third member of the B7 family, co-stimulates T-cell proliferation and interleukin-10 secretion. Nat. Med. 5, 1365–1369 (1999).

    Article  PubMed  CAS  Google Scholar 

  30. Ai, L., Xu, A. & Xu, J. Roles of PD-1/PD-L1 pathway: signaling, cancer, and beyond. Adv. Exp. Med. Biol. 1248, 33–59 (2020).

    Article  PubMed  CAS  Google Scholar 

  31. Cha, J.-H., Chan, L.-C., Li, C.-W., Hsu, J. L. & Hung, M.-C. Mechanisms controlling PD-L1 expression in cancer. Mol. Cell 76, 359–370 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Zou, W. & Chen, L. Inhibitory B7-family molecules in the tumour microenvironment. Nat. Rev. Immunol. 8, 467–477 (2008).

    Article  PubMed  CAS  Google Scholar 

  33. Thompson, R. H. et al. Costimulatory B7-H1 in renal cell carcinoma patients: Indicator of tumor aggressiveness and potential therapeutic target. Proc. Natl Acad. Sci. USA 101, 17174–17179 (2004).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Leite, K. R. et al. PD-L1 expression in renal cell carcinoma clear cell type is related to unfavorable prognosis. Diagn. Pathol. 10, 189 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Motzer, R. J. et al. Nivolumab versus everolimus in advanced renal-cell carcinoma. N. Engl. J. Med. 373, 1803–1813 (2015). Landmark and practice-changing phase III trial assessing the clinical activity and safety of nivolumab in pretreated patients with mRCC.

    Article  PubMed  CAS  Google Scholar 

  36. Topalian, S. L. et al. Safety, activity, and immune correlates of anti–PD-1 antibody in cancer. N. Engl. J. Med. 366, 2443–2454 (2012).

    Article  PubMed  CAS  Google Scholar 

  37. Paver, E. C. et al. Programmed death ligand-1 (PD-L1) as a predictive marker for immunotherapy in solid tumours: a guide to immunohistochemistry implementation and interpretation. Pathology 53, 141–156 (2021).

    Article  PubMed  CAS  Google Scholar 

  38. Khunger, M. et al. Programmed cell death 1 (PD-1) ligand (PD-L1) expression in solid tumors as a predictive biomarker of benefit from PD-1/PD-L1 axis inhibitors: a systematic review and meta-analysis. JCO Precis. Oncol. 1, 1–15 (2017).

    PubMed  Google Scholar 

  39. Carretero-González, A. et al. The value of PD-L1 expression as predictive biomarker in metastatic renal cell carcinoma patients: a meta-analysis of randomized clinical trials. Cancers 12, 1945 (2020).

    Article  PubMed Central  Google Scholar 

  40. Motzer, R. J. et al. Nivolumab plus ipilimumab versus sunitinib in first-line treatment for advanced renal cell carcinoma: extended follow-up of efficacy and safety results from a randomised, controlled, phase 3 trial. Lancet Oncol. 20, 1370–1385 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Motzer, R. J. et al. Avelumab plus axitinib versus sunitinib in advanced renal cell carcinoma: biomarker analysis of the phase 3 JAVELIN renal 101 trial. Nat. Med. 26, 1733–1741 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Rini, B. I. et al. Atezolizumab plus bevacizumab versus sunitinib in patients with previously untreated metastatic renal cell carcinoma (IMmotion151): a multicentre, open-label, phase 3, randomised controlled trial. Lancet 393, 2404–2415 (2019).

    Article  PubMed  Google Scholar 

  43. Tucker, M. D. & Rini, B. I. Predicting response to immunotherapy in metastatic renal cell carcinoma. Cancers 12, 2662 (2020).

    Article  PubMed Central  CAS  Google Scholar 

  44. Guida, A. et al. Finding predictive factors for immunotherapy in metastatic renal-cell carcinoma: what are we looking for? Cancer Treat. Rev. 94, 102157 (2021).

    Article  PubMed  CAS  Google Scholar 

  45. Meléndez, B. et al. Methods of measurement for tumor mutational burden in tumor tissue. Transl. Lung Cancer Res. 7, 661–667 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Schumacher, T. N. & Schreiber, R. D. Neoantigens in cancer immunotherapy. Science 348, 69–74 (2015).

    Article  PubMed  CAS  Google Scholar 

  47. Marabelle, A. et al. Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol. 21, 1353–1365 (2020).

    Article  PubMed  CAS  Google Scholar 

  48. Marabelle, A. et al. Efficacy of pembrolizumab in patients with noncolorectal high microsatellite instability/mismatch repair–deficient cancer: results from the phase II KEYNOTE-158 study. J. Clin. Oncol. 38, 1–10 (2020).

    Article  PubMed  CAS  Google Scholar 

  49. Yarchoan, M., Hopkins, A. & Jaffee, E. M. Tumor mutational burden and response rate to PD-1 inhibition. N. Engl. J. Med. 377, 2500–2501 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Yakirevich, E. & Patel, N. R. Tumor mutational burden and immune signatures interplay in renal cell carcinoma. Ann. Transl. Med. 8, 269–269 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Turajlic, S. et al. Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis. Lancet Oncol. 18, 1009–1021 (2017).

    Article  PubMed  CAS  Google Scholar 

  52. Samstein, R. M. et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat. Genet. 51, 202–206 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Wang, X. & Li, M. Correlate tumor mutation burden with immune signatures in human cancers. BMC Immunol. 20, 4 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Braun, D. A. et al. Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma. Nat. Med. 26, 909–918 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Motzer, R. J. et al. Biomarker analysis from CheckMate 214: nivolumab plus ipilimumab versus sunitinib in renal cell carcinoma. J. Immunother. Cancer 10, e004316 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  56. McDermott, D. F. et al. Clinical activity and molecular correlates of response to atezolizumab alone or in combination with bevacizumab versus sunitinib in renal cell carcinoma. Nat. Med. 24, 749–757 (2018). Exploratory biomarker analysis that identified four molecular subgroups that might correlate with response to anti-VEGF and immunotherapy.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Choueiri, T. K. et al. Biomarker analyses from JAVELIN Renal 101: Avelumab + axitinib (A+Ax) versus sunitinib (S) in advanced renal cell carcinoma (aRCC). J. Clin. Oncol. 37, 101–101 (2019).

    Article  Google Scholar 

  58. Maia, M. C., Almeida, L., Bergerot, P. G., Dizman, N. & Pal, S. K. Relationship of tumor mutational burden (TMB) to immunotherapy response in metastatic renal cell carcinoma (mRCC). J. Clin. Oncol. 36, 662–662 (2018).

    Article  Google Scholar 

  59. Labriola, M. K. et al. Characterization of tumor mutation burden, PD-L1 and DNA repair genes to assess relationship to immune checkpoint inhibitors response in metastatic renal cell carcinoma. J. Immunother. Cancer 8, e000319 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Dizman, N. et al. Correlates of clinical benefit from immunotherapy and targeted therapy in metastatic renal cell carcinoma: comprehensive genomic and transcriptomic analysis. J. Immunother. Cancer 8, e000953 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Wood, M. A., Weeder, B. R., David, J. K., Nellore, A. & Thompson, R. F. Burden of tumor mutations, neoepitopes, and other variants are weak predictors of cancer immunotherapy response and overall survival. Genome Med. 12, 33 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Lee, C.-H. et al. Lenvatinib plus pembrolizumab in patients with either treatment-naive or previously treated metastatic renal cell carcinoma (Study 111/KEYNOTE-146): a phase 1b/2 study. Lancet Oncol. 22, 946–958 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03469713 (2022).

  64. Yarchoan, M. et al. PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers. JCI Insight 4, e126908 (2019).

    Article  PubMed Central  Google Scholar 

  65. Massari, F. et al. Toward a genome-based treatment landscape for renal cell carcinoma. Crit. Rev. Oncol. Hematol. 142, 141–152 (2019).

    Article  PubMed  Google Scholar 

  66. Piva, F. et al. Computational analysis of the mutations in BAP1, PBRM1 and SETD2 genes reveals the impaired molecular processes in renal cell carcinoma. Oncotarget 6, 32161–32168 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Gossage, L., Eisen, T. & Maher, E. R. VHL, the story of a tumour suppressor gene. Nat. Rev. Cancer 15, 55–64 (2015).

    Article  PubMed  CAS  Google Scholar 

  68. Ashley, D. J. The two “hit” and multiple “hit” theories of carcinogenesis. Br. J. Cancer 23, 313–328 (1969).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Jonasch, E., Walker, C. L. & Rathmell, W. K. Clear cell renal cell carcinoma ontogeny and mechanisms of lethality. Nat. Rev. Nephrol. 17, 245–261 (2021).

    Article  PubMed  CAS  Google Scholar 

  70. Choueiri, T. K. & Kaelin, W. G. Targeting the HIF2–VEGF axis in renal cell carcinoma. Nat. Med. 26, 1519–1530 (2020).

    Article  PubMed  CAS  Google Scholar 

  71. Cowey, C. L. & Rathmell, W. K. VHL gene mutations in renal cell carcinoma: role as a biomarker of disease outcome and drug efficacy. Curr. Oncol. Rep. 11, 94–101 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Büscheck, F. et al. Prevalence and clinical significance of VHL mutations and 3p25 deletions in renal tumor subtypes. Oncotarget 11, 237–249 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  73. Stenehjem, D. D. et al. Predictive genomic markers of response to VEGF targeted therapy in metastatic renal cell carcinoma. PLoS ONE 14, e0210415 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  74. Abou Alaiwi, S. et al. Mammalian SWI/SNF complex genomic alterations and immune checkpoint blockade in solid tumors. Cancer Immunol. Res. 8, 1075–1084 (2020).

    Article  PubMed  Google Scholar 

  75. Joseph, R. W. et al. Clear cell renal cell carcinoma subtypes identified by BAP1 and PBRM1 expression. J. Urol. 195, 180–187 (2016).

    Article  PubMed  CAS  Google Scholar 

  76. Gulati, S. & Vogelzang, N. J. Biomarkers in renal cell carcinoma: are we there yet? Asian J. Urol. 8, 362–375 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Varela, I. et al. Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma. Nature 469, 539–542 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Gad, S. et al. Involvement of PBRM1 in VHL disease-associated clear cell renal cell carcinoma and its putative relationship with the HIF pathway. Oncol. Lett. 22, 835 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  79. Carril-Ajuria, L., Santos, M., Roldán-Romero, J. M., Rodriguez-Antona, C. & de Velasco, G. Prognostic and predictive value of PBRM1 in clear cell renal cell carcinoma. Cancers 12, 16 (2019).

    Article  PubMed Central  Google Scholar 

  80. Voss, M. H. et al. Genomically annotated risk model for advanced renal-cell carcinoma: a retrospective cohort study. Lancet Oncol. 19, 1688–1698 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Miao, D. et al. Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma. Science 359, 801–806 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  82. Braun, D. A. et al. Clinical validation of PBRM1 alterations as a marker of immune checkpoint inhibitor response in renal cell carcinoma. JAMA Oncol. 5, 1631 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  83. Hakimi, A. A. et al. The impact of PBRM1 mutations on overall survival in greater than 2100 patients treated with immune checkpoint blockade (ICB). J. Clin. Oncol. 37, 666–666 (2019).

    Article  Google Scholar 

  84. Ricketts, C. J. et al. The Cancer Genome Atlas comprehensive molecular characterization of renal cell carcinoma. Cell Rep. 23, 313–326.e5 (2018). Comprehensive genomic and phenotypic analysis of 843 RCCs from The Cancer Genome Atlas database.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  85. Ho, T. H. et al. Correlation between molecular subclassifications of clear cell renal cell carcinoma and targeted therapy response. Eur. Urol. Focus. 2, 204–209 (2016).

    Article  PubMed  Google Scholar 

  86. Hagiwara, M., Fushimi, A., Matsumoto, K. & Oya, M. The significance of PARP1 as a biomarker for predicting the response to PD-L1 blockade in patients with PBRM1-mutated clear cell renal cell carcinoma. Eur. Urol. 81, 145–148 (2022).

    Article  PubMed  CAS  Google Scholar 

  87. Gibson, B. A. & Kraus, W. L. New insights into the molecular and cellular functions of poly(ADP-ribose) and PARPs. Nat. Rev. Mol. Cell Biol. 13, 411–424 (2012).

    Article  PubMed  CAS  Google Scholar 

  88. Demidova, E. V., Ghatalia, P. & Arora, S. Combination strategies for immune checkpoint inhibitors in PBRM1-mutant renal cell carcinoma: to PARP or not to PARP? Eur. Urol. 81, 149–150 (2022).

    Article  PubMed  CAS  Google Scholar 

  89. Cancer Genome Atlas Research Network. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499, 43–49 (2013).

    Article  Google Scholar 

  90. Chen, R., Zhao, W., Fang, C., Yang, X. & Ji, M. Histone methyltransferase SETD2: a potential tumor suppressor in solid cancers. J. Cancer 11, 3349–3356 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  91. Hakimi, A. A. et al. Adverse outcomes in clear cell renal cell carcinoma with mutations of 3p21 epigenetic regulators BAP1 and SETD2: a report by MSKCC and the KIRC TCGA research network. Clin. Cancer Res. 19, 3259–3267 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  92. Chen, Y. et al. 79P SETD2 a potential tissue-agnostic predictive biomarker for ICIs in solid tumors. Ann. Oncol. 32, S390 (2021).

    Article  Google Scholar 

  93. González-Rodríguez, P. et al. SETD2 mutation in renal clear cell carcinoma suppress autophagy via regulation of ATG12. Cell Death Dis. 11, 69 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Di Nunno, V. et al. BAP1 in solid tumors. Futur. Oncol. 15, 2151–2162 (2019).

    Article  Google Scholar 

  95. Scheuermann, J. C. et al. Histone H2A deubiquitinase activity of the Polycomb repressive complex PR-DUB. Nature 465, 243–247 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  96. Joseph, R. W. et al. Loss of BAP1 protein expression is an independent marker of poor prognosis in patients with low-risk clear cell renal cell carcinoma. Cancer 120, 1059–1067 (2014).

    Article  PubMed  CAS  Google Scholar 

  97. Bossé, D. et al. Alterations in key clear cell renal cell carcinoma (RCC) genes to refine patient prognosis. J. Clin. Oncol. 36, 4516–4516 (2018).

    Article  Google Scholar 

  98. Mano, R. et al. Somatic mutations as preoperative predictors of metastases in patients with localized clear cell renal cell carcinoma — an exploratory analysis. Urol. Oncol. 39, 791.e17–791.e24 (2021).

    Article  CAS  Google Scholar 

  99. Wang, T. et al. An empirical approach leveraging tumorgrafts to dissect the tumor microenvironment in renal cell carcinoma identifies missing link to prognostic inflammatory factors. Cancer Discov. 8, 1142–1155 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  100. Zhou, Q. et al. CCR5 blockade inflames antitumor immunity in BAP1-mutant clear cell renal cell carcinoma. J. Immunother. Cancer 8, e000228 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  101. Qu, G., Wang, H., Yan, H., Liu, G. & Wu, M. Identification of CXCL10 as a prognostic biomarker for clear cell renal cell carcinoma. Front. Oncol. 12, 1–9 (2022).

    Article  CAS  Google Scholar 

  102. Aldinucci, D., Borghese, C. & Casagrande, N. The CCL5/CCR5 axis in cancer progression. Cancers 12, 1765 (2020).

    Article  PubMed Central  CAS  Google Scholar 

  103. Huang, C.-Y. et al. CCL5 increases lung cancer migration via PI3K, Akt and NF-κB pathways. Biochem. Pharmacol. 77, 794–803 (2009).

    Article  PubMed  CAS  Google Scholar 

  104. Long, H. et al. Autocrine CCL5 signaling promotes invasion and migration of CD133+ ovarian cancer stem‐like cells via NF‐κB‐mediated MMP‐9 upregulation. Stem Cell 30, 2309–2319 (2012).

    Article  CAS  Google Scholar 

  105. Kato, T. et al. CCR1/CCL5 interaction promotes invasion of taxane-resistant PC3 prostate cancer cells by increasing secretion of MMPs 2/9 and by activating ERK and Rac signaling. Cytokine 64, 251–257 (2013).

    Article  PubMed  CAS  Google Scholar 

  106. Yang, L. et al. Blockade of CCR5-mediated myeloid derived suppressor cell accumulation enhances anti-PD1 efficacy in gastric cancer. Immunopharmacol. Immunotoxicol. 40, 91–97 (2018).

    Article  PubMed  CAS  Google Scholar 

  107. Pan, Y. et al. Establishment of a novel gene panel as a biomarker of immune checkpoint inhibitor response. Clin. Transl. Immunol. 9, e1145 (2020).

    Article  CAS  Google Scholar 

  108. Ricciuti, B. et al. Impact of DNA damage response and repair (DDR) gene mutations on efficacy of PD-(L)1 immune checkpoint inhibition in non-small cell lung cancer. Clin. Cancer Res. 26, 4135–4142 (2020).

    Article  PubMed  CAS  Google Scholar 

  109. Ged, Y. et al. DNA damage repair pathway alterations in metastatic clear cell renal cell carcinoma and implications on systemic therapy. J. Immunother. Cancer 8, e000230 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  110. Nandi, B. et al. The roles of homologous recombination and the immune system in the genomic evolution of cancer. J. Transl. Sci. https://doi.org/10.15761/JTS.1000282 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  111. Pascal, J. M. The comings and goings of PARP-1 in response to DNA damage. DNA Repair. 71, 177–182 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  112. Hopkins, J. L., Lan, L. & Zou, L. DNA repair defects in cancer and therapeutic opportunities. Genes Dev. 36, 278–293 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  113. Underhill, C., Toulmonde, M. & Bonnefoi, H. A review of PARP inhibitors: from bench to bedside. Ann. Oncol. 22, 268–279 (2011).

    Article  PubMed  CAS  Google Scholar 

  114. Telli, M. L. PARP inhibitors in cancer: moving beyond BRCA. Lancet Oncol. 12, 827–828 (2011).

    Article  PubMed  Google Scholar 

  115. Pletcher, J. P. et al. The emerging role of poly (ADP-Ribose) polymerase inhibitors as effective therapeutic agents in renal cell carcinoma. Front. Oncol. 11, 681441 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  116. US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03786796 (2022).

  117. Ged, Y., Rifkind, I., Michalik, A., Carducci, M. A. & Markowski, M. C. ORCHID: a phase II study of olaparib in metastatic renal cell carcinoma patients harboring a BAP1 or other DNA repair gene mutations. J. Clin. Oncol. 40, TPS400 (2022).

    Article  Google Scholar 

  118. US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03741426 (2021).

  119. US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT04068831 (2022).

  120. Seyedin, S. N. et al. Combination therapy with radiation and PARP inhibition enhances responsiveness to anti-PD-1 therapy in colorectal tumor models. Int. J. Radiat. Oncol. 108, 81–92 (2020).

    Article  Google Scholar 

  121. Sen, T. et al. Targeting DNA damage response promotes antitumor immunity through STING-mediated T-cell activation in small cell lung cancer. Cancer Discov. 9, 646–661 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  122. Färkkilä, A. et al. Immunogenomic profiling determines responses to combined PARP and PD-1 inhibition in ovarian cancer. Nat. Commun. 11, 1459 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  123. Heidegger, I., Pircher, A. & Pichler, R. Targeting the tumor microenvironment in renal cell cancer biology and therapy. Front. Oncol. 9, 490 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  124. Lai, Y. et al. The tumour microenvironment and metabolism in renal cell carcinoma targeted or immune therapy. J. Cell Physiol. 236, 1616–1627 (2021).

    Article  PubMed  CAS  Google Scholar 

  125. Simonaggio, A. et al. Tumor microenvironment features as predictive biomarkers of response to immune checkpoint inhibitors (ICI) in metastatic clear cell renal cell carcinoma (mccRCC). Cancers 13, 231 (2021).

    Article  PubMed Central  CAS  Google Scholar 

  126. D’Costa, N. M. et al. Identification of gene signature for treatment response to guide precision oncology in clear-cell renal cell carcinoma. Sci. Rep. 10, 2026 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  127. Hakimi, A. A. et al. Transcriptomic profiling of the tumor microenvironment reveals distinct subgroups of clear cell renal cell cancer: data from a randomized phase III trial. Cancer Discov. 9, 510–525 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  128. Motzer, R. J. et al. Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade. Cancer Cell 38, 803–817.e4 (2020). The largest integrated multi-omics characterization of mRCC in a phase III trial in which seven molecular subgroups associated with differential clinical outcomes were identified in response to sunitinib, atezolizumab or atezolizumab plus bevacizumab.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  129. Motzer, R. J. et al. Final overall survival and molecular analysis in IMmotion151, a phase 3 trial comparing atezolizumab plus bevacizumab vs sunitinib in patients with previously untreated metastatic renal cell carcinoma. JAMA Oncol. 8, 275 (2022).

    Article  PubMed  Google Scholar 

  130. Kinget, L. et al. 689P Human leukocyte antigen (HLA) class I/II expression as a predictive biomarker for response to immune oncology (IO) therapy in metastatic clear-cell renal cell carcinoma (m-ccRCC). Ann. Oncol. 32, S706 (2021).

    Article  Google Scholar 

  131. Epaillard, N. et al. BIONIKK: a phase 2 biomarker driven trial with nivolumab and ipilimumab or VEGFR tyrosine kinase inhibitor (TKI) in naïve metastatic kidney cancer. Bull. Cancer 107, eS22–eS27 (2020).

    Article  PubMed  Google Scholar 

  132. Vano, Y. A. et al. Nivolumab, nivolumab-ipilimumab, and VEGFR-tyrosine kinase inhibitors as first-line treatment for metastatic clear-cell renal cell carcinoma (BIONIKK): a biomarker-driven, open-label, non-comparative, randomised, phase 2 trial. Lancet Oncol. 23, 612–624 (2022). The first prospective trial to evaluate the efficacy of ICIs and TKIs in patients with mRCC stratified according to tumour molecular features.

    Article  PubMed  CAS  Google Scholar 

  133. Braun, D. A. et al. Progressive immune dysfunction with advancing disease stage in renal cell carcinoma. Cancer Cell 39, 632–648.e8 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  134. Chen, D. S. & Mellman, I. Elements of cancer immunity and the cancer-immune set point. Nature 541, 321–330 (2017). Three tumour immune profiles were identified based on the characteristics of the TME, two of which are associated with resistance to immunotherapy.

    Article  PubMed  CAS  Google Scholar 

  135. Binnewies, M. et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat. Med. 24, 541–550 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  136. Koh, M. Y., Sayegh, N. & Agarwal, N. Seeing the forest for the trees — single-cell atlases link CD8+ T cells and macrophages to disease progression and treatment response in kidney cancer. Cancer Cell 39, 594–596 (2021).

    Article  PubMed  CAS  Google Scholar 

  137. Clark, D. J. et al. Integrated proteogenomic characterization of clear cell renal cell carcinoma. Cell 179, 964–983.e31 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  138. Turajlic, S. et al. Tracking cancer evolution reveals constrained routes to metastases: TRACERx renal. Cell 173, 581–594.e12 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  139. Raimondi, A. et al. Predictive biomarkers of response to immunotherapy in metastatic renal cell cancer. Front. Oncol. 10, 1644 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  140. Zhang, S. et al. Immune infiltration in renal cell carcinoma. Cancer Sci. 110, 1564–1572 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  141. Şenbabaoğlu, Y. et al. Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures. Genome Biol. 17, 231 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  142. Nakano, O. et al. Proliferative activity of intratumoral CD81 T-lymphocytes as a prognostic factor in human renal cell carcinoma: clinicopathologic demonstration of antitumor immunity. Cancer Res. 61, 5132–5136 (2021).

    Google Scholar 

  143. Zhu, Q. et al. PD-L1 expression patterns in tumour cells and their association with CD8+ tumour infiltrating lymphocytes in clear cell renal cell carcinoma. J. Cancer 10, 1154–1161 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  144. Chevrier, S. et al. An immune atlas of clear cell renal cell carcinoma. Cell 169, 736–749.e18 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  145. Beuselinck, B. et al. Molecular subtypes of clear cell renal cell carcinoma are associated with sunitinib response in the metastatic setting. Clin. Cancer Res. 21, 1329–1339 (2015).

    Article  PubMed  CAS  Google Scholar 

  146. Verbiest, A. et al. Clear-cell renal cell carcinoma: molecular characterization of IMDC risk groups and sarcomatoid tumors. Clin. Genitourin. Cancer 17, e981–e994 (2019).

    Article  PubMed  Google Scholar 

  147. Beuselinck, B. et al. Tumor molecular characteristics in patients (pts) with international metastatic renal cell carcinoma database consortium (IMDC) good (G) and intermediate/poor (I/P) risk. Ann. Oncol. 29, viii306–viii307 (2018).

    Article  Google Scholar 

  148. Albiges, L. et al. Nivolumab plus ipilimumab versus sunitinib for first-line treatment of advanced renal cell carcinoma: extended 4-year follow-up of the phase III CheckMate 214 trial. ESMO Open 5, e001079 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  149. Au, L. et al. Determinants of anti-PD-1 response and resistance in clear cell renal cell carcinoma. Cancer Cell 39, 1497–1518.e11 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  150. Choueiri, T. K. et al. Adjuvant pembrolizumab after nephrectomy in renal-cell carcinoma. N. Engl. J. Med. 385, 683–694 (2021).

    Article  PubMed  CAS  Google Scholar 

  151. Farha, M. et al. 692P Characterization of the tumor immune microenvironment in early-stage clear cell renal cell carcinoma (ccRCC): prognostic value of an M0-macrophage enriched subtype. Ann. Oncol. 32, S707 (2021).

    Article  Google Scholar 

  152. Bi, M. et al. Genomic characterization of sarcomatoid transformation in clear cell renal cell carcinoma. Proc. Natl Acad. Sci. USA 113, 2170–2175 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  153. Wang, Z. et al. Sarcomatoid renal cell carcinoma has a distinct molecular pathogenesis, driver mutation profile, and transcriptional landscape. Clin. Cancer Res. 23, 6686–6696 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  154. Bakouny, Z. et al. Integrative molecular characterization of sarcomatoid and rhabdoid renal cell carcinoma. Nat. Commun. 12, 808 (2021). A comprehensive characterization of sarcomatoid and rhabdoid renal cell carcinoma, focused on molecular, immunological and clinical features.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  155. Tannir, N. M. et al. Efficacy and safety of nivolumab plus ipilimumab versus sunitinib in first-line treatment of patients with advanced sarcomatoid renal cell carcinoma. Clin. Cancer Res. 27, 78–86 (2021).

    Article  PubMed  CAS  Google Scholar 

  156. Choueiri, T. K. et al. Efficacy and biomarker analysis of patients (pts) with advanced renal cell carcinoma (aRCC) with sarcomatoid histology (sRCC): subgroup analysis from the phase III JAVELIN renal 101 trial of first-line avelumab plus axitinib (A + Ax) vs sunitinib (S). Ann. Oncol. 30, v361 (2019).

    Article  Google Scholar 

  157. Rini, B. I. et al. Atezolizumab (atezo) + bevacizumab (bev) versus sunitinib (sun) in pts with untreated metastatic renal cell carcinoma (mRCC) and sarcomatoid (sarc) histology: IMmotion151 subgroup analysis. J. Clin. Oncol. 37, 4512–4512 (2019).

    Article  Google Scholar 

  158. Rini, B. I. et al. Pembrolizumab (pembro) plus axitinib (axi) versus sunitinib as first-line therapy for metastatic renal cell carcinoma (mRCC): outcomes in the combined IMDC intermediate/poor risk and sarcomatoid subgroups of the phase 3 KEYNOTE-426 study. J. Clin. Oncol. 37, 4500–4500 (2019).

    Article  Google Scholar 

  159. Rini, B. I. et al. Atezolizumab plus bevacizumab versus sunitinib for patients with untreated metastatic renal cell carcinoma and sarcomatoid features: a prespecified subgroup analysis of the IMmotion151 clinical trial. Eur. Urol. 79, 659–662 (2021).

    Article  PubMed  CAS  Google Scholar 

  160. Choueiri, T. K. et al. Efficacy and correlative analyses of avelumab plus axitinib versus sunitinib in sarcomatoid renal cell carcinoma: post hoc analysis of a randomized clinical trial. ESMO Open 6, 100101 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  161. Motzer, R. J. et al. Nivolumab + cabozantinib (NIVO+CABO) versus sunitinib (SUN) for advanced renal cell carcinoma (aRCC): outcomes by sarcomatoid histology and updated trial results with extended follow-up of CheckMate 9ER. J. Clin. Oncol. 39, 308–308 (2021).

    Article  Google Scholar 

  162. Choueiri, T. K. et al. 660P Phase III CLEAR trial in advanced renal cell carcinoma (aRCC): outcomes in subgroups and toxicity update. Ann. Oncol. 32, S683–S685 (2021).

    Article  Google Scholar 

  163. Iacovelli, R. et al. Patients with sarcomatoid renal cell carcinoma — re-defining the first-line of treatment: a meta-analysis of randomised clinical trials with immune checkpoint inhibitors. Eur. J. Cancer 136, 195–203 (2020).

    Article  PubMed  CAS  Google Scholar 

  164. Coelho Barata, P. M. et al. 688P Gene expression profiling (GEP) signatures associated with markers of sensitivity to immune and angiogenic therapy in clear-cell renal cell carcinoma (ccRCC) with sarcomatoid/rhabdoid features. Ann. Oncol. 32, S705 (2021).

    Article  Google Scholar 

  165. Cimadamore, A. et al. Emerging molecular technologies in renal cell carcinoma: liquid biopsy. Cancers 11, 196 (2019).

    Article  PubMed Central  CAS  Google Scholar 

  166. Nuzzo, P. V. et al. Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes. Nat. Med. 26, 1041–1043 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  167. Wan, J., Zhu, L., Jiang, Z. & Cheng, K. Monitoring of plasma cell-free DNA in predicting postoperative recurrence of clear cell renal cell carcinoma. Urol. Int. 91, 273–278 (2013).

    Article  PubMed  CAS  Google Scholar 

  168. Yamamoto, Y. et al. Clinical significance of the mutational landscape and fragmentation of circulating tumor DNA in renal cell carcinoma. Cancer Sci. 110, 617–628 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  169. Wang, Z. et al. Assessment of blood tumor mutational burden as a potential biomarker for immunotherapy in patients with non-small cell lung cancer with use of a next-generation sequencing cancer gene panel. JAMA Oncol. 5, 696–702 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  170. Lee, J. H. et al. Circulating tumour DNA predicts response to anti-PD1 antibodies in metastatic melanoma. Ann. Oncol. 28, 1130–1136 (2017).

    Article  PubMed  CAS  Google Scholar 

  171. Kim, Y. J. et al. Potential of circulating tumor DNA as a predictor of therapeutic responses to immune checkpoint blockades in metastatic renal cell carcinoma. Sci. Rep. 11, 5600 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  172. Del Re, M. et al. The amount of DNA combined with TP53 mutations in liquid biopsy is associated with clinical outcome of renal cancer patients treated with immunotherapy and VEGFR-TKIs. J. Transl. Med. 20, 371 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  173. Bergerot, P. G., Hahn, A. W., Bergerot, C. D., Jones, J. & Pal, S. K. The role of circulating tumor DNA in renal cell carcinoma. Curr. Treat. Options Oncol. 19, 10 (2018).

    Article  PubMed  Google Scholar 

  174. Kubiliute, R. & Jarmalaite, S. Epigenetic biomarkers of renal cell carcinoma for liquid biopsy tests. Int. J. Mol. Sci. 22, 8846 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  175. Morad, G., Helmink, B. A., Sharma, P. & Wargo, J. A. Hallmarks of response, resistance, and toxicity to immune checkpoint blockade. Cell 184, 5309–5337 (2021). A global review of the mechanisms of response, resistance and toxicity to immunotherapy in human cancers.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  176. Gan, C. L., Dudani, S. & Heng, D. Y. C. Prognostic and predictive factors in metastatic renal cell carcinoma. Cancer J. 26, 365–375 (2020).

    Article  PubMed  CAS  Google Scholar 

  177. Klatte, T., Rossi, S. H. & Stewart, G. D. Prognostic factors and prognostic models for renal cell carcinoma: a literature review. World J. Urol. 36, 1943–1952 (2018).

    Article  PubMed  Google Scholar 

  178. Motzer, R. J. et al. Survival and prognostic stratification of 670 patients with advanced renal cell carcinoma. J. Clin. Oncol. 17, 2530–2530 (1999).

    Article  PubMed  CAS  Google Scholar 

  179. Gao, X. & McDermott, D. F. Ipilimumab in combination with nivolumab for the treatment of renal cell carcinoma. Expert. Opin. Biol. Ther. 18, 947–957 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  180. Amin, A. & Hammers, H. The evolving landscape of immunotherapy-based combinations for frontline treatment of advanced renal cell carcinoma. Front. Immunol. 9, 3120 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  181. Rizzo, A. et al. Comparative effectiveness of first-line immune checkpoint inhibitors plus tyrosine kinase inhibitors according to IMDC risk groups in metastatic renal cell carcinoma: a meta-analysis. Immunotherapy 13, 783–793 (2021).

    Article  PubMed  CAS  Google Scholar 

  182. Martini, D. J. et al. Novel risk scoring system for patients with metastatic renal cell carcinoma treated with immune checkpoint inhibitors. Oncologist 25, e484–e491 (2020).

    Article  PubMed  CAS  Google Scholar 

  183. Santoni, M., Cortellini, A. & Buti, S. Unlocking the secret of the obesity paradox in renal tumours. Lancet Oncol. 21, 194–196 (2020).

    Article  PubMed  Google Scholar 

  184. Cortellini, A. et al. Another side of the association between body mass index (BMI) and clinical outcomes of cancer patients receiving programmed cell death protein-1 (PD-1)/Programmed cell death-ligand 1 (PD-L1) checkpoint inhibitors: a multicentre analysis of immune-related adverse events. Eur. J. Cancer 128, 17–26 (2020).

    Article  PubMed  CAS  Google Scholar 

  185. Sanchez, A. et al. Transcriptomic signatures related to the obesity paradox in patients with clear cell renal cell carcinoma: a cohort study. Lancet Oncol. 21, 283–293 (2020).

    Article  PubMed  CAS  Google Scholar 

  186. Wang, Z. et al. Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade. Nat. Med. 25, 141–151 (2019).

    Article  PubMed  CAS  Google Scholar 

  187. Lalani, A. A. et al. Assessment of immune checkpoint inhibitors and genomic alterations by body mass index in advanced renal cell carcinoma. JAMA Oncol. 7, 773–775 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  188. Indini, A. et al. Impact of BMI on survival outcomes of immunotherapy in solid tumors: a systematic review. Int. J. Mol. Sci. 22, 2628 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  189. Routy, B. et al. Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors. Science 359, 91–97 (2018).

    Article  PubMed  CAS  Google Scholar 

  190. Salgia, N. J. et al. Stool microbiome profiling of patients with metastatic renal cell carcinoma receiving anti-PD-1 immune checkpoint inhibitors. Eur. Urol. 78, 498–502 (2020).

    Article  PubMed  CAS  Google Scholar 

  191. Derosa, L. et al. Negative association of antibiotics on clinical activity of immune checkpoint inhibitors in patients with advanced renal cell and non-small-cell lung cancer. Ann. Oncol. 29, 1437–1444 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  192. Derosa, L. et al. Gut bacteria composition drives primary resistance to cancer immunotherapy in renal cell carcinoma patients. Eur. Urol. 78, 195–206 (2020).

    Article  PubMed  CAS  Google Scholar 

  193. Dizman, N. et al. Nivolumab plus ipilimumab with or without live bacterial supplementation in metastatic renal cell carcinoma: a randomized phase 1 trial. Nat. Med. 28, 704–712 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  194. Buder-Bakhaya, K. & Hassel, J. C. Biomarkers for clinical benefit of immune checkpoint inhibitor treatment — a review from the melanoma perspective and beyond. Front. Immunol. 9, 1474 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  195. Voong, K. R., Feliciano, J., Becker, D. & Levy, B. Beyond PD-L1 testing-emerging biomarkers for immunotherapy in non-small cell lung cancer. Ann. Transl. Med. 5, 376–376 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  196. Lalani, A.-K. A. et al. Change in neutrophil-to-lymphocyte ratio (NLR) in response to immune checkpoint blockade for metastatic renal cell carcinoma. J. Immunother. Cancer 6, 5 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  197. Desnoyer, A. et al. 5105 — Fresh blood immune cell monitoring in patients treated with nivolumab in the GETUG-AFU26 NIVOREN study: association with toxicity and treatment outcome. Ann. Oncol. 30 (Suppl. 5), v356–v402 (2019).

    Google Scholar 

  198. De Giorgi, U. et al. Safety and efficacy of nivolumab for metastatic renal cell carcinoma: real-world results from an expanded access programme. BJU Int. 123, 98–105 (2019).

    Article  PubMed  Google Scholar 

  199. Soleimani, M. et al. 693P Plasma exosome microRNA-155-3p expression in patients with metastatic renal cell carcinoma treated with immune checkpoint inhibitors: potential biomarker of response to systemic therapy. Ann. Oncol. 32, S708 (2021).

    Article  Google Scholar 

  200. Montemagno, C. et al. Soluble forms of PD-L1 and PD-1 as prognostic and predictive markers of sunitinib efficacy in patients with metastatic clear cell renal cell carcinoma. Oncoimmunology 9, 1846901 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  201. Shirasu, M. & Touhara, K. The scent of disease: volatile organic compounds of the human body related to disease and disorder. J. Biochem. 150, 257–266 (2011).

    Article  PubMed  CAS  Google Scholar 

  202. Janssens, E., van Meerbeeck, J. P. & Lamote, K. Volatile organic compounds in human matrices as lung cancer biomarkers: a systematic review. Crit. Rev. Oncol. Hematol. 153, 103037 (2020).

    Article  PubMed  Google Scholar 

  203. van de Kant, K. D., van der Sande, L. J., Jöbsis, Q., van Schayck, O. C. & Dompeling, E. Clinical use of exhaled volatile organic compounds in pulmonary diseases: a systematic review. Respir. Res. 13, 117 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  204. Calenic, B. et al. Oxidative stress and volatile organic compounds: interplay in pulmonary, cardio-vascular, digestive tract systems and cancer. Open Chem. 13, 0105 (2015).

    Article  Google Scholar 

  205. Lagniau, S., Lamote, K., van Meerbeeck, J. P. & Vermaelen, K. Y. Biomarkers for early diagnosis of malignant mesothelioma: do we need another moonshot? Oncotarget 8, 53751–53762 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  206. Hanna, G. B., Boshier, P. R., Markar, S. R. & Romano, A. Accuracy and methodologic challenges of volatile organic compound–based exhaled breath tests for cancer diagnosis. JAMA Oncol. 5, e182815 (2019).

    Article  PubMed  Google Scholar 

  207. Li, M. et al. Breath carbonyl compounds as biomarkers of lung cancer. Lung Cancer 90, 92–97 (2015).

    Article  PubMed  Google Scholar 

  208. de Vries, R. et al. Prediction of response to anti-PD-1 therapy in patients with non-small-cell lung cancer by electronic nose analysis of exhaled breath. Ann. Oncol. 30, 1660–1666 (2019).

    Article  PubMed  Google Scholar 

  209. Buma, A. I. G. et al. eNose analysis for early immunotherapy response monitoring in non-small cell lung cancer. Lung Cancer 160, 36–43 (2021).

    Article  PubMed  CAS  Google Scholar 

  210. US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT04146064 (2022).

  211. Stone, L. Urinary VOCs as bladder cancer biomarkers. Nat. Rev. Urol. 19, 256 (2022).

    PubMed  Google Scholar 

  212. Murdocca, M. et al. Urine LOX-1 and volatilome as promising tools towards the early detection of renal cancer. Cancers 13, 4213 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  213. Das, S. & Johnson, D. B. Immune-related adverse events and anti-tumor efficacy of immune checkpoint inhibitors. J. Immunother. Cancer 7, 306 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  214. Khan, Z. et al. Polygenic risk for skin autoimmunity impacts immune checkpoint blockade in bladder cancer. Proc. Natl Acad. Sci. USA 117, 12288–12294 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  215. Nobashi, T. et al. Predicting response to immunotherapy by evaluating tumors, lymphoid cell-rich organs, and immune-related adverse events using FDG-PET/CT. Clin. Nucl. Med. 44, e272–e279 (2019).

    Article  PubMed  Google Scholar 

  216. Verzoni, E. et al. Real-world efficacy and safety of nivolumab in previously-treated metastatic renal cell carcinoma, and association between immune-related adverse events and survival: the Italian expanded access program. J. Immunother. Cancer 7, 99 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  217. Tannir, N. M. et al. Outcomes in patients (pts) with advanced renal cell carcinoma (aRCC) who discontinued (DC) first-line nivolumab + ipilimumab (N+I) or sunitinib (S) due to treatment-related adverse events (TRAEs) in CheckMate 214. J. Clin. Oncol. 37, 581–581 (2019).

    Article  Google Scholar 

  218. Petrelli, F. et al. Association of steroids use with survival in patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis. Cancers 12, 546 (2020).

    Article  PubMed Central  CAS  Google Scholar 

  219. Aldea, M. et al. How to manage patients with corticosteroids in oncology in the era of immunotherapy? Eur. J. Cancer 141, 239–251 (2020).

    Article  PubMed  CAS  Google Scholar 

  220. Miller, G. W. & Jones, D. P. The nature of nurture: refining the definition of the exposome. Toxicol. Sci. 137, 1–2 (2014).

    Article  PubMed  CAS  Google Scholar 

  221. Fournel, L. et al. Cisplatin increases PD-L1 expression and optimizes immune check-point blockade in non-small cell lung cancer. Cancer Lett. 464, 5–14 (2019).

    Article  PubMed  CAS  Google Scholar 

  222. Nowak, A. K. et al. Induction of tumor cell apoptosis in vivo increases tumor antigen cross-presentation, cross-priming rather than cross-tolerizing host tumor-specific CD8 T cells. J. Immunol. 170, 4905–4913 (2003).

    Article  PubMed  CAS  Google Scholar 

  223. Reits, E. A. et al. Radiation modulates the peptide repertoire, enhances MHC class I expression, and induces successful antitumor immunotherapy. J. Exp. Med. 203, 1259–1271 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  224. Iacovelli, R. et al. Evidence and clinical relevance of tumor flare in patients who discontinue tyrosine kinase inhibitors for treatment of metastatic renal cell carcinoma. Eur. Urol. 68, 154–160 (2015).

    Article  PubMed  Google Scholar 

  225. Fukumura, D., Kloepper, J., Amoozgar, Z., Duda, D. G. & Jain, R. K. Enhancing cancer immunotherapy using antiangiogenics: opportunities and challenges. Nat. Rev. Clin. Oncol. 15, 325–340 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  226. Blank, C. U., Haanen, J. B., Ribas, A. & Schumacher, T. N. The “cancer immunogram”. Science 352, 658–660 (2016).

    Article  PubMed  CAS  Google Scholar 

  227. Mpekris, F. et al. Combining microenvironment normalization strategies to improve cancer immunotherapy. Proc. Natl Acad. Sci. USA 117, 3728–3737 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  228. Seymour, L. et al. iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics. Lancet Oncol. 18, e143–e152 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  229. Borcoman, E., Nandikolla, A., Long, G., Goel, S. & Le Tourneau, C. Patterns of response and progression to immunotherapy. Am. Soc. Clin. Oncol. Educ. Book 38, 169–178 (2018).

    Article  PubMed  Google Scholar 

  230. Inno, A. et al. The evolving landscape of criteria for evaluating tumor response in the era of cancer immunotherapy: from Karnofsky to iRECIST. Tumor. J. 104, 88–95 (2018).

    Article  Google Scholar 

  231. Frelaut, M., du Rusquec, P., de Moura, A., Le Tourneau, C. & Borcoman, E. Pseudoprogression and hyperprogression as new forms of response to immunotherapy. BioDrugs 34, 463–476 (2020).

    Article  PubMed  Google Scholar 

  232. Mollica, V. et al. Tumor growth rate decline despite progressive disease may predict improved nivolumab treatment outcome in mRCC: when RECIST is not enough. Cancers 13, 3492 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  233. Wang, Q., Gao, J. & Wu, X. Pseudoprogression and hyperprogression after checkpoint blockade. Int. Immunopharmacol. 58, 125–135 (2018).

    Article  PubMed  CAS  Google Scholar 

  234. Champiat, S. et al. Hyperprogressive disease is a new pattern of progression in cancer patients treated by anti-PD-1/PD-L1. Clin. Cancer Res. 23, 1920–1928 (2017).

    Article  PubMed  CAS  Google Scholar 

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F.M. researched data for the article. F.M., V.M. and A.R. contributed substantially to discussion of the content. F.M., M.R. and A.M. wrote the article. F.M. and M.S. reviewed and edited the manuscript before submission.

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Correspondence to Francesco Massari.

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Rosellini, M., Marchetti, A., Mollica, V. et al. Prognostic and predictive biomarkers for immunotherapy in advanced renal cell carcinoma. Nat Rev Urol (2022). https://doi.org/10.1038/s41585-022-00676-0

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