Prognostic Model for Clear-cell Renal Cell Carcinoma Based on Natural Killer Cell-related Genes.

被引:4
作者
Shi, Xuezhong [1 ]
Yuan, Mengyang [1 ]
Yang, Yongli [1 ]
Wang, Nana [1 ]
Niu, Yali [1 ]
Yang, Chaojun [1 ]
Dong, Ani [1 ]
Zhu, Huili [1 ]
Jia, Xiaocan [1 ,2 ]
机构
[1] Zhengzhou Univ, Coll Publ Hlth, Dept Epidemiol & Biostat, Zhengzhou, Henan, Peoples R China
[2] Zhengzhou Univ, Coll Publ Hlth, Dept Epidemiol & Biostat, St 100 Kexuedadao Rd, Zhengzhou 450001, Henan, Peoples R China
关键词
Immune; Prognosis; Survival; Tumor microenvironment; Therapy; CANCER; THERAPY;
D O I
10.1016/j.clgc.2022.11.009
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Natural killer cells play a fundamental role in immune surveillance of ccRCC. A NKRPS was established by univariate Cox and LASSO-Cox regression based on the TCGA cohort (n = 515). The high-risk group exhibited superior immune infiltration and higher expression of ICI-related genes. This suggests that the NKRPS is valuable in predicting prognosis and providing a therapeutic reference for ccRCC patients. Background: Natural killer (NK) cells are a key factor affecting progression and immune surveillance of clear-cell renal cell carcinoma (ccRCC). This study sought to construct a natural killer cell-related prognostic signature (NKRPS) to predict the outcome of ccRCC patients and to furnish guidance for finding appropriate treatment strategies. Methods: From the TCGA and ArrayExpress databases, transcriptomic profiles and relevant clinical information of ccRCC patients were downloaded for the TCGA cohort (n = 515) and the E-MTAB-1980 cohort (n = 101). With the univariate Cox analysis and LASSO-Cox regression algorithm, a NKRPS was built to evaluate patients' prognosis. Receiver operating characteristic (ROC) cur ves and calibration cur ves were drawn to estimate the predictive power of the prognostic model. Then, tumor microenvironment (TME), tumor mutational burden (TMB), sensitization to immune checkpoint inhibitors (ICIs) therapy and targeted drug treatment were analyzed in ccRCC patients. Results: Nine genes (BID, CCL7, CSF2, IL23A, KNSTRN, RHBDD3, PIK3R3, RNF19B and VAV3) were identified to construct a NKRPS. High-risk group displayed undesirable survival compared to low-risk group ( P < .05). Moreover, the area under the curve (AUC) of ROC at 1-, 3and 5-year were 0.766, 0.755, and 0.757, respectively. High-risk group was characterized by superior immune infiltration, higher TMB, and higher expression of 5 ICI-related genes. Additionally, this model enabled to predict the sensitivity of patients to chemotherapy drugs. Conclusion: NKRPS had a strong predictive power on prognosis of ccRCC patients, which may facilitate individualized treatment and medical decision making.
引用
收藏
页码:E126 / E137
页数:12
相关论文
共 45 条
[1]   Natural killer-like signature observed post therapy in locally advanced rectal cancer is a determinant of pathological response and improved survival [J].
Alderdice, Matthew ;
Dunne, Philip D. ;
Cole, Aidan J. ;
O'Reilly, Paul G. ;
McArt, Darragh G. ;
Bingham, Vicky ;
Fuchs, Marc-Aurel ;
McQuaid, Stephen ;
Loughrey, Maurice B. ;
Murray, Graeme I. ;
Samuel, Leslie M. ;
Lawler, Mark ;
Wilson, Richard H. ;
Salto-Tellez, Manuel ;
Coyle, Vicky M. .
MODERN PATHOLOGY, 2017, 30 (09) :1287-1298
[2]   Mapping the immune environment in clear cell renal carcinoma by single-cell genomics [J].
Borcherding, Nicholas ;
Vishwakarma, Ajaykumar ;
Voigt, Andrew P. ;
Bellizzi, Andrew ;
Kaplan, Jacob ;
Nepple, Kenneth ;
Salem, Aliasger K. ;
Jenkins, Russell W. ;
Zakharia, Yousef ;
Zhang, Weizhou .
COMMUNICATIONS BIOLOGY, 2021, 4 (01)
[3]   Cancer cells educate natural killer cells to a metastasis-promoting cell state [J].
Chan, Isaac S. ;
Knutsdottir, Hildur ;
Ramakrishnan, Gayathri ;
Padmanaban, Veena ;
Warrier, Manisha ;
Ramirez, Juan Carlos ;
Dunworth, Matthew ;
Zhang, Hao ;
Jaffee, Elizabeth M. ;
Bader, Joel S. ;
Ewald, Andrew Josef .
JOURNAL OF CELL BIOLOGY, 2020, 219 (09)
[4]   Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic [J].
Chan, T. A. ;
Yarchoan, M. ;
Jaffee, E. ;
Swanton, C. ;
Quezada, S. A. ;
Stenzinger, A. ;
Peters, S. .
ANNALS OF ONCOLOGY, 2019, 30 (01) :44-56
[5]   Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade [J].
Charoentong, Pornpimol ;
Finotello, Francesca ;
Angelova, Mihaela ;
Mayer, Clemens ;
Efremova, Mirjana ;
Rieder, Dietmar ;
Hackl, Hubert ;
Trajanoski, Zlatko .
CELL REPORTS, 2017, 18 (01) :248-262
[6]   The immunology of renal cell carcinoma [J].
Diaz-Montero, C. Marcela ;
Rini, Brian I. ;
Finke, James H. .
NATURE REVIEWS NEPHROLOGY, 2020, 16 (12) :721-735
[7]   The ILC World Revisited [J].
Diefenbach, Andreas ;
Colonna, Marco ;
Romagnani, Chiara .
IMMUNITY, 2017, 46 (03) :327-332
[8]   Transcript signature predicts tissue NK cell content and defines renal cell carcinoma subgroups independent of TNM staging [J].
Eckl, Judith ;
Buchner, Alexander ;
Prinz, Petra U. ;
Riesenberg, Rainer ;
Siegert, Sabine I. ;
Kammerer, Robert ;
Nelson, Peter J. ;
Noessner, Elfriede .
JOURNAL OF MOLECULAR MEDICINE-JMM, 2012, 90 (01) :55-66
[9]   Immune Checkpoint Inhibitors: Toward New Paradigms in Renal Cell Carcinoma [J].
Flippot, Ronan ;
Escudier, Bernard ;
Albiges, Laurence .
DRUGS, 2018, 78 (14) :1443-1457
[10]  
Gao J, 2021, Front Oncol, V11