Significance of Tumor Mutation Burden in Immune Infiltration and Prognosis in Cutaneous Melanoma

被引:87
作者
Kang, Kai [1 ]
Xie, Fucun [1 ]
Mao, Jinzhu [1 ]
Bai, Yi [2 ,3 ]
Wang, Xiang [1 ]
机构
[1] Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Med Oncol, Beijing, Peoples R China
[2] Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Liver Surg, Beijing, Peoples R China
[3] First Cent Hosp, Dept Hepatobiliary Surg, Tianjin, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2020年 / 10卷
关键词
cutaneous melanoma; tumor mutation burden; immune infiltration; gene expression profile; functional enrichment analysis; prognosis; bioinformatics analysis; TO-LYMPHOCYTE RATIO; MALIGNANT-MELANOMA; BONE METASTASIS; RISK-FACTORS; IFN-GAMMA; CANCER; SURVIVIN; EXPRESSION; CELLS; EPIDEMIOLOGY;
D O I
10.3389/fonc.2020.573141
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background:Melanoma is highly immunogenic and therefore suitable for immunotherapy, but the efficacy is limited by response rate. In several types of tumor, tumor mutation burden (TMB) and immune infiltration have been reported to predict the response to immunotherapy, although each has its limitations. In the current study, we aimed to explore the association of TMB with immune infiltration and prognosis in cutaneous melanoma. Methods:The data of cutaneous melanoma used for analyses was downloaded from The Cancer Genome Atlas (TCGA) database. The mutation data was sorted using "maftools" R package. TMB was estimated and then patients were divided into two groups based on TMB. The association of TMB with prognosis and clinical characteristics was explored. Differential analysis between two TMB groups was performed using "DESeq2" R package to identify differentially expressed genes (DEGs). The function enrichment analyses of DEGs were conducted to screen critical pathways. Besides, DEGs were further filtered to identify two hub genes, based on which a risk score model and nomogram for predicting prognosis were conducted, and the validation was performed using three datasets from Gene Expression Omnibus (GEO) database. Finally, CIBERSORT algorithm and TIMER database were used to assess the effect of TMB and hub genes on immune infiltration. Results:The most common mutation was C > T, and the top three frequently mutated genes wereTTN, MUC16, andBRAF. Higher TMB indicated better survival outcomes and lower pathological stages. 735 DEGs were identified and mainly involved in immune-related and adhesion-related pathways. The risk score model and nomogram were validated using receiver operating characteristic (ROC) curves and calibration curves, and exhibited relatively high predictive capability. Decision curve analysis (DCA) was used to assess clinical benefit. As for immune infiltration, the proportion was higher for macrophages M1 and M2 in the high-TMB group, while lower for memory B cells and regulatory T cells. Conclusions:In cutaneous melanoma, TMB was positively correlated with prognosis. The risk score model and nomogram can be conveniently used to predict prognosis. The association of TMB with immune infiltration can help improve the predicting methods for the response to immunotherapy.
引用
收藏
页数:18
相关论文
共 98 条
[11]   Immune and Molecular Correlates in Melanoma Treated With Immune Checkpoint Blockade [J].
Byrne, Elizabeth H. ;
Fisher, David E. .
CANCER, 2017, 123 :2143-2153
[12]   First-Line Nivolumab in Stage IV or Recurrent Non-Small-Cell Lung Cancer [J].
Carbone, D. P. ;
Reck, M. ;
Paz-Ares, L. ;
Creelan, B. ;
Horn, L. ;
Steins, M. ;
Felip, E. ;
van den Heuvel, M. M. ;
Ciuleanu, T. -E. ;
Badin, F. ;
Ready, N. ;
Hiltermann, T. J. N. ;
Nair, S. ;
Juergens, R. ;
Peters, S. ;
Minenza, E. ;
Wrangle, J. M. ;
Rodriguez-Abreu, D. ;
Borghaei, H. ;
Blumenschein, G. R. ;
Villaruz, L. C. ;
Havel, L. ;
Krejci, J. ;
Corral Jaime, J. ;
Chang, H. ;
Geese, W. J. ;
Bhagavatheeswaran, P. ;
Chen, A. C. ;
Socinski, M. A. .
NEW ENGLAND JOURNAL OF MEDICINE, 2017, 376 (25) :2415-2426
[13]   Macrophage targeting: opening new possibilities for cancer immunotherapy [J].
Cassetta, Luca ;
Kitamura, Takanori .
IMMUNOLOGY, 2018, 155 (03) :285-293
[14]   Cell adhesion in tumor invasion and metastasis: loss of the glue is not enough [J].
Cavallaro, U ;
Christofori, G .
BIOCHIMICA ET BIOPHYSICA ACTA-REVIEWS ON CANCER, 2001, 1552 (01) :39-45
[15]   Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden [J].
Chalmers, Zachary R. ;
Connelly, Caitlin F. ;
Fabrizio, David ;
Gay, Laurie ;
Ali, Siraj M. ;
Ennis, Riley ;
Schrock, Alexa ;
Campbell, Brittany ;
Shlien, Adam ;
Chmielecki, Juliann ;
Huang, Franklin ;
He, Yuting ;
Sun, James ;
Tabori, Uri ;
Kennedy, Mark ;
Lieber, Daniel S. ;
Roels, Steven ;
White, Jared ;
Otto, Geoffrey A. ;
Ross, Jeffrey S. ;
Garraway, Levi ;
Miller, Vincent A. ;
Stephens, Phillip J. ;
Frampton, Garrett M. .
GENOME MEDICINE, 2017, 9
[16]   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
[17]  
Chen BB, 2018, METHODS MOL BIOL, V1711, P243, DOI 10.1007/978-1-4939-7493-1_12
[18]   Survivin and Tumorigenesis: Molecular Mechanisms and Therapeutic Strategies [J].
Chen, Xun ;
Duan, Ning ;
Zhang, Caiguo ;
Zhang, Wentao .
JOURNAL OF CANCER, 2016, 7 (03) :314-323
[19]   Molecular testing for BRAF mutations to inform melanoma treatment decisions: a move toward precision medicine [J].
Cheng, Liang ;
Lopez-Beltran, Antonio ;
Massari, Francesco ;
MacLennan, Gregory T. ;
Montironi, Rodolfo .
MODERN PATHOLOGY, 2018, 31 (01) :24-38
[20]   cytoHubba: identifying hub objects and sub-networks from complex interactome [J].
Chin, Chia-Hao ;
Chen, Shu-Hwa ;
Wu, Hsin-Hung ;
Ho, Chin-Wen ;
Ko, Ming-Tat ;
Lin, Chung-Yen .
BMC SYSTEMS BIOLOGY, 2014, 8