Predictors of therapy efficacy of immune response checkpoint inhibitors in clear cell renal cell carcinoma

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Abstract

Immunotherapy in oncologic diseases involves the use of drugs which stimulate the immune system and indirectly suppress tumor cells growth. These agents have expanded the treatment options for cancer patients. Despite the impressive success achieved in the development of immune checkpoint inhibitors (ICIs) and subsequent approval in a broader spectrum of malignant tumors, most patients are not responded the therapy. Currently available predictive markers of efficacy are nonspecific. However, microRNAs are of particular interest, which regulate gene expression and are involved in the carcinogenesis and therapy resistance. Therefore, it is clear that for the most efficient and cost-effective use of ICIs, it is important to have validated biomarkers that will accurately predict the therapeutic response. The published results on molecular genetic changes in patients with renal cell carcinoma (RCC) were analyzed and summarized in order to determine possible prognostic biomarkers when prescribing ICI therapy.

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About the authors

I. R. Gilyazova

Institute of Biochemistry and Genetics, Ufa Scientific Center, RAS; Bashkir State Medical University

Author for correspondence.
Email: gilyasova_irina@mail.ru
ORCID iD: 0000-0001-9499-5632

Ph.D. in Biology, Associate Professor, Senior Research Fellow, the Head of the Laboratory of Molecular Genetics

Russian Federation, Ufa; Ufa

А. А. Izmailov

Republican Clinical Oncology Dispensary

Email: izmailov75@mail.ru
ORCID iD: 0000-0002-8461-9243

Ph.D., MD, Associate Professor, Head Physician, Professor at the Department of Urology

Russian Federation, Ufa

D. D. Asadullina

Institute of Biochemistry and Genetics, Ufa Scientific Center, RAS; Bashkir State Medical University

Email: dilara.asadullina@yandex.ru
ORCID iD: 0000-0003-4911-8037

Ph.D. student, Junior Researcher at the Laboratory of Molecular Genetics

Russian Federation, Ufa; Ufa

E. A. Ivanova

Institute of Biochemistry and Genetics, Ufa Scientific Center, RAS

Email: lissa987@yandex.ru
ORCID iD: 0000-0002-7853-8658

Ph.D. in Biology, Research Fellow

Russian Federation, Ufa

V. N. Pavlov

Bashkir State Medical University

Email: vpavlov3@yandex.ru
ORCID iD: 0000-0003-2125-4897

Ph.D., MD, Professor, Rector, Head of the Department of Urology with the course of postgraduate education

Russian Federation, Ufa

E. K. Khusnutdinova

Institute of Biochemistry and Genetics, Ufa Scientific Center, RAS

Email: elzakh@mail.ru
ORCID iD: 0000-0003-2987-3334

Doctor of Biological Science, Professor, Director, Head of the Department of Medical Genetics and Fundamental Medicine

Russian Federation, Ufa

References

  1. Ross K., Jones R.J. Immune checkpoint inhibitors in renal cell carcinoma. Clin Sci (Lond). 2017;131:2627–2642. https://doi.org/10.1042/CS20160894
  2. World Cancer Research Fund International.[Internet] [cited 2023 Jan 17]. Available from:https://www.wcrf.org/cancer-trends/kidney-cancer-statistics/. Kidney. 2020
  3. Kaprin А.D., Starinskogo V.V., Shahzadova А.О. The state of cancer care for the population of Russia in 2021. М: МNIOI P.А. Gerzena. 2022; 239 p.Russian. (Каприн А.Д., Старинский В.В., Шахзадова А.О. Состояние онкологической помощи населению России в 2021 году. М: МНИОИ П.А. Герцена.2022; 239 с.).
  4. Shek D., Read S.A., Akhuba L., Qiao L., Gao B., Nagrial A., et al. Non-coding RNA and immune-checkpoint inhibitors: friends or foes? Immunotherapy. 2020;12:513–529. https://doi.org/10.2217/imt-2019-0204
  5. Smolle M.A., Prinz F., Calin G.A., Pichler M. Current concepts of non-coding RNA regulation of immune checkpoints in cancer. Mol Aspects Med. 2019;70:117–26. https://doi.org/10.1016/j.mam.2019.09.007
  6. Stühler V., Maas J.M., Rausch S., Stenzl A., Bedke J. Immune checkpoint inhibition for the treatment of renal cell carcinoma. Expert Opin Biol Ther. 2020;20:83–94. https://doi.org/10.1080/14712598.2020.1677601
  7. Roviello G., Corona S.P., Nesi G., Mini E. Results from a meta-analysis of immune checkpoint inhibitors in first-line renal cancer patients: does PD-L1 matter? Ther Adv Med Oncol. 2019;11:175883591986190. https://doi.org/10.1177/1758835919861905
  8. Schmidt A.L., Siefker-Radtke A., McConkey D., McGregor B. Renal Cell and Urothelial Carcinoma: Biomarkers for New Treatments. American Society of Clinical Oncology Educational Book. 2020:e197–206. https://doi.org/10.1200/EDBK_279905
  9. Labriola M.K., Zhu J., Gupta R., McCall S., Jackson J., Kong E.F., 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. 2020;8:e000319. https://doi.org/10.1136/jitc-2019-000319
  10. Lai Y., Zeng T., Liang X., Wu W., Zhong F., Wu W. Cell death-related molecules and biomarkers for renal cell carcinoma targeted therapy. Cancer Cell Int. 2019;19:221. https://doi.org/10.1186/s12935-019-0939-2
  11. Hsieh J.J., Le V.H., Oyama T., Ricketts C.J., Ho T.H., Cheng E.H. Chromosome 3p Loss–Orchestrated VHL, HIF, and Epigenetic Deregulation in Clear Cell Renal Cell Carcinoma. Journal of Clinical Oncology. 2018;36:3533–3539. https://doi.org/10.1200/JCO.2018.79.2549
  12. Hakimi A.A., Reznik E., Lee C-H., Creighton C.J., Brannon A.R., Luna A., et al. An Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma. Cancer Cell. 2016;29:104–116. https://doi.org/10.1016/j.ccell.2015.12.004
  13. Messai Y., Gad S., Noman M.Z., Le Teuff G., Couve S., Janji B., et al. Renal Cell Carcinoma Programmed Death-ligand 1, a New Direct Target of Hypoxia-inducible Factor-2 Alpha, is Regulated by von Hippel–Lindau Gene Mutation Status. Eur Urol. 2016;70:623–632. https://doi.org/10.1016/j.eururo.2015.11.029
  14. Liu X-D., Kong W., Peterson C.B., McGrail D.J., Hoang A., Zhang X., et al. PBRM1 loss defines a nonimmunogenic tumor phenotype associated with checkpoint inhibitor resistance in renal carcinoma. Nat Commun. 2020;11:2135. https://doi.org/10.1038/s41467-020-15959-6
  15. Abou Alaiwi S., Nassar A., El Bakouny Z., Berchuck J.E., Nuzzo P., Flippot R., et al. Association of polybromo-associated BAF (PBAF) complex mutations with overall survival (OS) in cancer patients (pts) treated with checkpoint inhibitors (ICIs). Journal of Clinical Oncology. 2019;37:103–103. https://doi.org/10.1200/JCO.2019.37.15_suppl.103
  16. Havel J.J., Chowell D., Chan T.A. The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy. Nat Rev Cancer. 2019;19:133–150. https://doi.org/10.1038/s41568-019-0116-x
  17. Büttner R., Longshore J.W., López-Ríos F., Merkelbach-Bruse S., Normanno N., Rouleau E., et al. Implementing TMB measurement in clinical practice: considerations on assay requirements. ESMO Open. 2019;4:e000442. https://doi.org/10.1136/esmoopen-2018-000442
  18. Samstein R.M., Lee C-H., Shoushtari A.N., Hellmann M.D., Shen R., Janjigian Y.Y., et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51:202–206. https://doi.org/10.1038/s41588-018-0312-8.
  19. Sharma P., Hu-Lieskovan S., Wargo J.A., Ribas A. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell.2017;168:707–723. https://doi.org/10.1016/j.cell.2017.01.017
  20. Shin D.S., Zaretsky J.M., Escuin-Ordinas H., Garcia-Diaz A., Hu-Lieskovan S., Kalbasi A., et al. Primary Resistance to PD-1 Blockade Mediated by JAK1/2 Mutations. Cancer Discov. 2017;7:188–201. https://doi.org/10.1158/2159-8290.CD-16-1223
  21. Marschner D., Falk M., Javorniczky N.R., Hanke-Müller K., Rawluk J., Schmitt-Graeff A., et al. MicroRNA-146a regulates immune-related adverse events caused by immune checkpoint inhibitors. JCI Insight. 2020;5. https://doi.org/10.1172/jci.insight.132334
  22. Ivanova E., Asadullina D., Rakhimov R., Izmailov A., Izmailov Al., Gilyazova G., et al. Exosomal miRNA-146a is downregulated in clear cell renal cell carcinoma patients with severe immune-related adverse events. Noncoding RNA Res. 2022;7:159–163. https://doi.org/10.1016/j.ncrna.2022.06.004
  23. Kamal Y., Cheng C., Frost H.R., Amos C.I. Predictors of disease aggressiveness influence outcome from immunotherapy treatment in renal clear cell carcinoma. Oncoimmunology. 2019;8:e1500106. https://doi.org/10.1080/2162402X.2018.1500106
  24. Motzer R.J., Penkov K., Haanen J., Rini B., Albiges L., Campbell M.T., et al. Avelumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. New England Journal of Medicine. 2019;380:1103–1115. https://doi.org/10.1056/NEJMoa1816047
  25. Basu A. Phone A., Bice T., Sweeney P., Acharya L., Suri Y., et al. Change in neutrophil to lymphocyte ratio (NLR) as a predictor of treatment failure in renal cell carcinoma patients: Analysis of the IROC (Investigating RCC Outcomes) cohort. Journal of Clinical Oncology. 2021;39:344–344. https://doi.org/10.1200/JCO.2021.39.6_suppl.344
  26. Lalani A-K.A., Xie W., Martini D.J., Steinharter J.A., Norton C.K., Krajewski K.M., et al. Change in neutrophil-to-lymphocyte ratio (NLR) in response to immune checkpoint blockade for metastatic renal cell carcinoma. J Immunother Cancer. 2018;6:5. https://doi.org/10.1186/s40425-018-0315-0
  27. Cerezo M., Rocchi S. Cancer cell metabolic reprogramming: a keystone for the response to immunotherapy. Cell Death Dis. 2020;11:964. https://doi.org/10.1038/s41419-020-03175-5.
  28. Cong J., Wang X., Zheng X., Wang D., Fu B., Sun R., et al. Dysfunction of Natural Killer Cells by FBP1-Induced Inhibition of Glycolysis during Lung Cancer Progression. Cell Metab. 2018;28:243-255.e5. https://doi.org/10.1016/j.cmet.2018.06.021
  29. Guerra L., Bonetti L., Brenner D. Metabolic Modulation of Immunity: A New Concept in Cancer Immunotherapy. Cell Rep. 2020;32:107848. https://doi.org/10.1016/j.celrep.2020.107848
  30. Wang H., Franco F., Tsui Y-C., Xie X., Trefny M.P., Zappasodi R., et al. CD36-mediated metabolic adaptation supports regulatory T cell survival and function in tumors. Nat Immunol. 2020;21:298–308. https://doi.org/10.1038/s41590-019-0589-5
  31. Leone R.D., Sun I-M., Oh M-H., Sun I-H., Wen J., Englert J., et al. Inhibition of the adenosine A2a receptor modulates expression of T cell coinhibitory receptors and improves effector function for enhanced checkpoint blockade and ACT in murine cancer models. Cancer Immunology, Immunotherapy. 2018;67:1271–1284. https://doi.org/10.1007/s00262-018-2186-0
  32. Omar H.A., El‐Serafi A.T., Hersi F., Arafa E.A., Zaher D.M., Madkour M., et al. Immunomodulatory MicroRNAs in cancer: targeting immune checkpoints and the tumor microenvironment. FEBS J. 2019;286:3540–3557. https://doi.org/10.1111/febs.15000
  33. Cortez M.A., Anfossi S., Ramapriyan R., Menon H.,.Atalar S.C., Aliru M., et al. Role of miRNAs in immune responses and immunotherapy in cancer. Genes Chromosomes Cancer. 2019;58:244–2453. https://doi.org/10.1002/gcc.22725
  34. Miao S., Mao X., Zhao S., Song K., Xiang C., Lv Y., et al. miR-217 inhibits laryngeal cancer metastasis by repressing AEG-1 and PD-L1 expression. Oncotarget. 2017;8:62143–62153. https://doi.org/10.18632/oncotarget.19121
  35. Qu F., Ye J., Pan X., Wang J., Gan S., Chu C., et al. MicroRNA-497-5p down-regulation increases PD-L1 expression in clear cell renal cell carcinoma. J Drug Target. 2019;27:67–74. https://doi.org/10.1080/1061186X.2018.1479755
  36. Incorvaia L., Fanale D., Badalamenti G., Brando C., Bono M., De Luca I., et al. A “Lymphocyte MicroRNA Signature” as Predictive Biomarker of Immunotherapy Response and Plasma PD-1/PD-L1 Expression Levels in Patients with Metastatic Renal Cell Carcinoma: Pointing towards Epigenetic Reprogramming. Cancers (Basel). 2020;12:3396. https://doi.org/10.3390/cancers12113396
  37. Dilsiz N. Role of exosomes and exosomal microRNAs in cancer. Future Sci OA. 2020;6:FSO465. https://doi.org/10.2144/fsoa-2019-0116
  38. He J., He J., Min L., He Y., Guan H., Wang J., et al. Extracellular vesicles transmitted miR‐31‐5p promotes sorafenib resistance by targeting MLH1 in renal cell carcinoma. Int J Cancer. 2020;146:1052–63. https://doi.org/10.1002/ijc.32543
  39. Yu D-C., Li Q-G., Ding X-W., Ding Y-T. Circulating MicroRNAs: Potential Biomarkers for Cancer. Int J Mol Sci. 2011;12:2055–2063. https://doi.org/10.3390/ijms12032055
  40. Halvorsen A.R., Sandhu V., Sprauten M., Flote V.G., Kure E.H., Brustugun O.T., et al. Circulating microRNAs associated with prolonged overall survival in lung cancer patients treated with nivolumab. Acta Oncol (Madr). 2018;57:1225–1231. https://doi.org/10.1080/0284186X.2018. 1465585
  41. Costantini A., Julie C., Dumenil C., Hélias-Rodzewicz Z., Tisserand J., Dumoulin J., et al. Predictive role of plasmatic biomarkers in advanced non-small cell lung cancer treated by nivolumab. Oncoimmunology. 2018:e1452581. https://doi.org/10.1080/2162402X.2018. 1452581
  42. Sudo K., Kato K., Matsuzaki J., Takizawa S., Aoki Y., Shoji H., et al. Identification of serum microRNAs predicting the response of esophageal squamous-cell carcinoma to nivolumab. Jpn J Clin Oncol. 2019. https://doi.org/10.1093/jjco/hyz146
  43. Tengda L., Shuping L., Mingli G., Jie G., Yun L., Weiwei Z., et al. Serum exosomal microRNAs as potent circulating biomarkers for melanoma. Melanoma Res. 2018;28:295–303. https://doi.org/10.1097/CMR.0000000000000450
  44. Pantano F., Zalfa F., Iuliani M., Simonetti S., Manca P., Napolitano A., et al. Large-Scale Profiling of Extracellular Vesicles Identified miR-625-5p as a Novel Biomarker of Immunotherapy Response in Advanced Non-Small-Cell Lung Cancer Patients. Cancers (Basel). 2022;14:2435. https://doi.org/10.3390/cancers14102435
  45. Routy B., Le Chatelier E., Derosa L., Duong C.P.M., Alou M.T., Daillère R., et al. Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors. Science (1979). 2018;359:91–97. https://doi.org/10.1126/science.aan3706
  46. Wind T.T., Gacesa R., Vich Vila A., De Haan J.J., Jalving M., Weersma R.K., et al. Gut microbial species and metabolic pathways associated with response to treatment with immune checkpoint inhibitors in metastatic melanoma. Melanoma Res. 2020;30:235–246. https://doi.org/10.1097/CMR.0000000000000656
  47. Tinsley N., Zhou C., Tan G., Rack S., Lorigan P., Blackhall F., et al. Cumulative Antibiotic Use Significantly Decreases Efficacy of Checkpoint Inhibitors in Patients with Advanced Cancer. Oncologist 2020;25:55–63. https://doi.org/10.1634/theoncologist.2019-0160
  48. Richtig G., Hoeller C., Wolf M., Wolf I., Rainer B.M,. Schulter G., et al. Body mass index may predict the response to ipilimumab in metastatic melanoma: An observational multi-centre study. PLoS One. 2018;13:e0204729. https://doi.org/10.1371/journal.pone.0204729
  49. Cortellini A., Bersanelli M., Buti S., Cannita K., Santini D., Perrone F., et al. A multicenter study of body mass index in cancer patients treated with anti-PD-1/PD-L1 immune checkpoint inhibitors: when overweight becomes favorable. J Immunother Cancer. 2019;7:57. https://doi.org/10.1186/s40425-019-0527-y.
  50. McQuade J.L., Daniel C.R., Hess K.R., Mak C., Wang D.Y., Rai R.R., et al. Association of body-mass index and outcomes in patients with metastatic melanoma treated with targeted therapy, immunotherapy, or chemotherapy: a retrospective, multicohort analysis. Lancet Oncol. 2018;19:310–322. https://doi.org/10.1016/S1470-2045(18)30078-0

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