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Numerous studies have revealed a tight connection between tumor development and the coagulation system. However, the effects of coagulation on the prognosis and tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) remain poorly understood.
We employed the consensus clustering method to characterize distinct molecular subtypes associated with coagulation patterns. Subsequently, we examined variations in the overall survival (OS), genomic profiles, and TME characteristics between these subtypes. To develop a prognostic coagulation‐related risk score (CRRS) model, we utilized the least absolute shrinkage and selection operator Cox regression and stepwise multivariate Cox regression analyses. We also created a nomogram to aid in the clinical application of the risk score, evaluating the relationships between the CRRS and the immune microenvironment, responsiveness to immunotherapy, and targeted treatment. The clinical significance of PLAUR and its biological function in ccRCC were also further analyzed.
There were significant differences in clinical features, prognostic stratification, genomic variation, and TME characteristics between the two coagulation‐related subtypes. We established and validated a CRRS using six coagulation‐related genes that can be employed as an effective indicator of risk stratification and prognosis estimation for ccRCC patients. Significant variations in survival outcomes were observed between the high‐ and low‐risk groups. The nomogram was proficient in predicting the 1‐, 3‐, and 5‐year OS. Additionally, the CRRS emerged as a novel tool for evaluating the clinical effectiveness of immunotherapy and targeted treatments in ccRCC. Moreover, we confirmed upregulated PLAUR expression in ccRCC samples that was significantly correlated with poor patient prognosis. PLAUR knockdown notably inhibited ccRCC cell proliferation and migration.
Our data suggested that CRRS may be employed as a reliable predictive biomarker that can provide therapeutic benefits for immunotherapy and targeted therapy in ccRCC.
Moch H, Cubilla AL, Humphrey PA, Reuter VE, Ulbright TM. The 2016 WHO classification of tumours of the urinary system and male genital organs‐part A: renal, penile, and testicular tumours. Eur Urol. 2016;70(1):93–105. https://doi.org/10.1016/j.eururo.2016.02.029
Rini BI, Campbell SC, Escudier B. Renal cell carcinoma. Lancet. 2009;373(9669):1119–32. https://doi.org/10.1016/S0140-6736(09)60229-4
Kotecha RR, Motzer RJ, Voss MH. Towards individualized therapy for metastatic renal cell carcinoma. Nat Rev Clin Oncol. 2019;16(10):621–33. https://doi.org/10.1038/s41571-019-0209-1
Kraft C, Schuettfort G, Weil Y, Tirneci V, Kasper A, Haberichter B, et al. Thrombosis of the inferior vena cava and malignant disease. Thromb Res. 2014;134(3):668–73. https://doi.org/10.1016/j.thromres.2014.07.012
Warsow G, Hübschmann D, Kleinheinz K, Nientiedt C, Heller M, van Coile L, et al. Genomic features of renal cell carcinoma with venous tumor thrombus. Sci Rep. 2018;8(1):7477. https://doi.org/10.1038/s41598-018-25544-z
Psutka SP, Leibovich BC. Management of inferior vena cava tumor thrombus in locally advanced renal cell carcinoma. Ther Adv Urol. 2015;7(4):216–29. https://doi.org/10.1177/1756287215576443
Xiao B, Ma LL, Zhang SD, Xiao CL, Lu J, Hong K, et al. Correlation between coagulation function, tumor stage and metastasis in patients with renal cell carcinoma: a retrospective study. Chin Med J. 2011;124(8):1205–8.
Tian YJ, Hong M, Jing SS, Liu XC, Wang HZ, Wang XP, et al. Clinical and prognostic effect of plasma fibrinogen in renal cell carcinoma: a meta‐analysis. BioMed Res Int. 2017;2017:1–8. https://doi.org/10.1155/2017/9591506
Galmiche A, Rak J, Roumenina LT, Saidak Z. Coagulome and the tumor microenvironment: an actionable interplay. Trends in Cancer. 2022;8(5):369–83. https://doi.org/10.1016/j.trecan.2021.12.008
Saidak Z, Soudet S, Lottin M, Salle V, Sevestre MA, Clatot F, et al. A pan‐cancer analysis of the human tumor coagulome and its link to the tumor immune microenvironment. Cancer Immunol Immunother. 2021;70(4):923–33. https://doi.org/10.1007/s00262-020-02739-w
Vuong L, Kotecha RR, Voss MH, Hakimi AA. Tumor microenvironment dynamics in clear‐cell renal cell carcinoma. Cancer Discov. 2019;9(10):1349–57. https://doi.org/10.1158/2159-8290.cd-19-0499
Tas F, Kilic L, Bilgin E, Keskin S, Sen F, Ciftci R, et al. Clinical and prognostic significance of coagulation assays in advanced epithelial ovarian cancer. Int J Gynecol Cancer. 2013;23(2):276–81. https://doi.org/10.1097/igc.0b013e31827b8796
Tikhomirova I, Petrochenko E, Malysheva Y, Ryabov M, Kislov N. Interrelation of blood coagulation and hemorheology in cancer. Clin Hemorheol Microcirc. 2017;64(4):635–44. https://doi.org/10.3233/ch-168037
Kawai K, Watanabe T. Colorectal cancer and hypercoagulability. Surg Today. 2014;44(5):797–803. https://doi.org/10.1007/s00595-013-0606-5
Ma MS, Cao R, Wang W, Wang BY, Yang YC, Huang YC, et al. The D‐dimer level predicts the prognosis in patients with lung cancer: a systematic review and meta‐analysis. J Cardiothorac Surg. 2021;16(1):243. https://doi.org/10.1186/s13019-021-01618-4
Tieken C, Versteeg HH. Anticoagulants versus cancer. Thromb Res. 2016;140(Suppl 1):S148–53. https://doi.org/10.1016/S0049-3848(16)30114-1
Haist M, Stege H, Pemler S, Heinz J, Fleischer MI, Graf C, et al. Anticoagulation with factor Xa inhibitors is associated with improved overall response and progression‐free survival in patients with metastatic malignant melanoma receiving immune checkpoint inhibitors—a retrospective, real‐world cohort study. Cancers. 2021;13(20):5103. https://doi.org/10.3390/cancers13205103
Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD. The sva package for removing batch effects and other unwanted variation in high‐throughput experiments. Bioinformatics. 2012;28(6):882–3. https://doi.org/10.1093/bioinformatics/bts034
Mayakonda A, Lin DC, Assenov Y, Plass C, Koeffler HP. Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 2018;28(11):1747–56. https://doi.org/10.1101/gr.239244.118
Wilkerson MD, Hayes DN. ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics. 2010;26(12):1572–3. https://doi.org/10.1093/bioinformatics/btq170
Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453–7. https://doi.org/10.1038/nmeth.3337
Yoshihara K, Shahmoradgoli M, Martínez E, Vegesna R, Kim H, Torres‐Garcia W, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun. 2013;4:2612. https://doi.org/10.1038/ncomms3612
Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA‐seq data. BMC Bioinformatics. 2013;14:7. https://doi.org/10.1186/1471-2105-14-7
Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D, et al. Pan‐cancer immunogenomic analyses reveal genotype‐immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep. 2017;18(1):248–62. https://doi.org/10.1016/j.celrep.2016.12.019
Jiang P, Gu S, Pan D, Fu J, Sahu A, Hu X, et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med. 2018;24(10):1550–8. https://doi.org/10.1038/s41591-018-0136-1
Geeleher P, Cox N, Huang RS. pRRophetic: an R package for prediction of clinical chemotherapeutic response from tumor gene expression levels. PLoS One. 2014;9(9):e107468. https://doi.org/10.1371/journal.pone.0107468
Chen W, Wang H, Lu Y, Huang Y, Xuan Y, Li X, et al. GTSE1 promotes tumor growth and metastasis by attenuating of KLF4 expression in clear cell renal cell carcinoma. Lab Invest. 2022;102(9):1011–22. https://doi.org/10.1038/s41374-022-00797-5
Falanga A, Marchetti M, Vignoli A. Coagulation and cancer: biological and clinical aspects. J Thromb Haemostasis. 2013;11(2):223–33. https://doi.org/10.1111/jth.12075
Falanga A, Russo L, Verzeroli C. Mechanisms of thrombosis in cancer. Thromb Res. 2013;131(Suppl 1):S59–S62. https://doi.org/10.1016/S0049-3848(13)70024-0
Vedovati MC, Giustozzi M, Becattini C. Venous thromboembolism and cancer: current and future role of direct‐acting oral anticoagulants. Thromb Res. 2019;177:33–41. https://doi.org/10.1016/j.thromres.2019.02.031
Lee AYY, Levine MN. Venous thromboembolism and cancer: risks and outcomes. Circulation. 2003;107(23 Suppl 1):I17–21. https://doi.org/10.1161/01.cir.0000078466.72504.ac
García‐Escobar I, Brozos‐Vázquez E, Gutierrez Abad D, Martínez‐Marín V, Pachón V, Muñoz Martín AJ, et al. Direct oral anticoagulants for the treatment and prevention of venous thromboembolism in patients with cancer: current evidence. Clin Transl Oncol. 2021;23(6):1034–46. https://doi.org/10.1007/s12094-020-02506-4
Granito A, Muratori L, Lalanne C, Quarneti C, Ferri S, Guidi M, et al. Hepatocellular carcinoma in viral and autoimmune liver diseases: role of CD4+ CD25+ Foxp3+ regulatory T cells in the immune microenvironment. World J Gastroenterol. 2021;27(22):2994–3009. https://doi.org/10.3748/wjg.v27.i22.2994
Tanaka A, Sakaguchi S. Regulatory T cells in cancer immunotherapy. Cell Res. 2017;27(1):109–18. https://doi.org/10.1038/cr.2016.151
Pan YY, Yu YD, Wang XJ, Zhang T. Tumor‐associated macrophages in tumor immunity. Front Immunol. 2020;11:583084. https://doi.org/10.3389/fimmu.2020.583084
Rizzo A, Mollica V, Santoni M, Ricci AD, Rosellini M, Marchetti A, et al. Impact of clinicopathological features on survival in patients treated with first‐line immune checkpoint inhibitors plus tyrosine kinase inhibitors for renal cell carcinoma: a meta‐analysis of randomized clinical trials. Eur Urol Focus. 2022;8(2):514–21. https://doi.org/10.1016/j.euf.2021.03.001
Massari F, Mollica V, Rizzo A, Cosmai L, Rizzo M, Porta C. Safety evaluation of immune‐based combinations in patients with advanced renal cell carcinoma: a systematic review and meta‐analysis. Expert Opin Drug Saf. 2020;19(10):1329–38. https://doi.org/10.1080/14740338.2020.1811226
Liu M, Chen S, Zhang A, Zheng Q, Fu J. PLAUR as a potential biomarker associated with immune infiltration in bladder urothelial carcinoma. J Inflamm Res. 2021;14:4629–41. https://doi.org/10.2147/jir.s326559
Zeng F, Li GZ, Liu X, Zhang KN, Huang H, Jiang T, et al. Plasminogen activator urokinase receptor implies immunosuppressive features and acts as an unfavorable prognostic biomarker in glioma. Oncologist. 2021;26(8):e1460–69. https://doi.org/10.1002/onco.13750
Ploug M, Rønne E, Behrendt N, Jensen AL, Blasi F, Danø K. Cellular receptor for urokinase plasminogen activator. Carboxyl‐terminal processing and membrane anchoring by glycosyl‐phosphatidylinositol. J Biol Chem. 1991;266(3):1926–33. https://doi.org/10.1016/S0021-9258(18)52382-6
Laurenzana A, Chillà A, Luciani C, Peppicelli S, Biagioni A, Bianchini F, et al. uPA/uPAR system activation drives a glycolytic phenotype in melanoma cells. Int J Cancer. 2017;141(6):1190–200. https://doi.org/10.1002/ijc.30817
Hildenbrand R, Schaaf A. The urokinase‐system in tumor tissue stroma of the breast and breast cancer cell invasion. Int J Oncol. 2009;34(1):15–23. https://doi.org/10.3892/ijo_00000124
Boonstra MC, Verspaget HW, Ganesh S, Kubben FJGM, Vahrmeijer AL, van de Velde CJH, et al. Clinical applications of the urokinase receptor (uPAR) for cancer patients. Curr Pharm Des. 2011;17(19):1890–910. https://doi.org/10.2174/138161211796718233
LeBeau AM, Duriseti S, Murphy ST, Pepin F, Hann B, Gray JW, et al. Targeting uPAR with antagonistic recombinant human antibodies in aggressive breast cancer. Cancer Res. 2013;73(7):2070–81. https://doi.org/10.1158/0008-5472.can-12-3526
Zhang CQ, Zhang GC, Sun N, Zhang Z, Xue LY, Zhang ZH, et al. An individualized immune signature of pretreatment biopsies predicts pathological complete response to neoadjuvant chemoradiotherapy and outcomes in patients with esophageal squamous cell carcinoma. Signal Transduct Target Ther. 2020;5(1):182. https://doi.org/10.1038/s41392-020-00221-8
Lindsten T, Hedbrant A, Ramberg A, Wijkander J, Solterbeck A, Eriksson M, et al. Effect of macrophages on breast cancer cell proliferation, and on expression of hormone receptors, uPAR and HER‐2. Int J Oncol. 2017;51(1):104–14. https://doi.org/10.3892/ijo.2017.3996
Chen HM, Lu SY, Guan JQ, Zhu XQ, Sun FF, Huang JT, et al. Identification of prognostic immune‐related genes in rhabdoid tumor of kidney based on TARGET database analysis. Aging. 2021;13(4):5461–74. https://doi.org/10.18632/aging.202475
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