Chengjian Ji1, Yichun Wang1, Yi Wang2, Jiaochen Luan1, Liangyu Yao1, Yamin Wang1, Ninghong Song1,3. 1. Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 2. Department of Urology, Affiliated Hospital of Nantong University, Nantong, China. 3. The Affiliated Kezhou People's Hospital of Nanjing Medical University, Kezhou, China.
Abstract
BACKGROUND: Testicular cancer is a very common malignancy in young men. Although testicular cancer has a high cure rate, patients have a high long-term risk of secondary malignant tumors and cardiovascular disease. In addition, for patients resistant to traditional treatment methods, new treatment methods and methods for predicting prognosis are also urgently needed. METHODS: Gene expression profiles of 165 normal testicular tissues and 156 testicular germ cell tumor (TGCT) tissues from GTEx database and TCGA database were used to obtain differentially expressed genes (DEGs) in TGCT. Through the ImmPort database, we obtained immune-related genes (IRGs). Univariate Cox regression analysis was used to identify prognostic IRGs. A transcription factor regulatory network was constructed to clarify the possible regulatory mechanism for the differential expression of these IRGs. Multivariate Cox regression analysis was used to establish a prognostic model. Gene expression data and related survival data of 108 TCGT patients from GEO database were used for external validation. Survival analysis, receiver operating characteristic curves (ROC) curve analysis, independent prognostic analysis, principal component analysis (PCA) and clinical correlation analysis were performed to evaluate this model. RESULTS: Three hundred and thirty-three IRGs were differentially expressed between TGCT and normal testicular tissues. We established a prognostic model (riskScore) based on 5 risk genes (SEMA6B, SEMA3G, OBP2B, INSL6 and RETN). Whether in the training cohort, the testing cohort or the entire TCGA cohort, this model could accurately stratify patients with different survival outcomes. The prognostic value of riskScore and 5 risk genes was also confirmed in the GEO database. GSEA analysis showed that DEGs in patients with better prognosis were enriched in immune-related pathways, while DEGs in patients with poorer prognosis were enriched in cancer-related pathways and cardiovascular disease-related pathways. Finally, a new Nomogram with higher prognostic value was constructed to better predict the 1-year PFS, 3-year PFS and 5-year PFS of TCGT patients. CONCLUSIONS: We successfully established an immune-related risk model with high prognostic value and created a new Nomogram. We found that different immune status in tumor microenvironment may be responsible for the different survival outcomes among TGCT patients. 2020 Annals of Translational Medicine. All rights reserved.
BACKGROUND: Testicular cancer is a very common malignancy in young men. Although testicular cancer has a high cure rate, patients have a high long-term risk of secondary malignant tumors and cardiovascular disease. In addition, for patients resistant to traditional treatment methods, new treatment methods and methods for predicting prognosis are also urgently needed. METHODS: Gene expression profiles of 165 normal testicular tissues and 156 testicular germ cell tumor (TGCT) tissues from GTEx database and TCGA database were used to obtain differentially expressed genes (DEGs) in TGCT. Through the ImmPort database, we obtained immune-related genes (IRGs). Univariate Cox regression analysis was used to identify prognostic IRGs. A transcription factor regulatory network was constructed to clarify the possible regulatory mechanism for the differential expression of these IRGs. Multivariate Cox regression analysis was used to establish a prognostic model. Gene expression data and related survival data of 108 TCGT patients from GEO database were used for external validation. Survival analysis, receiver operating characteristic curves (ROC) curve analysis, independent prognostic analysis, principal component analysis (PCA) and clinical correlation analysis were performed to evaluate this model. RESULTS: Three hundred and thirty-three IRGs were differentially expressed between TGCT and normal testicular tissues. We established a prognostic model (riskScore) based on 5 risk genes (SEMA6B, SEMA3G, OBP2B, INSL6 and RETN). Whether in the training cohort, the testing cohort or the entire TCGA cohort, this model could accurately stratify patients with different survival outcomes. The prognostic value of riskScore and 5 risk genes was also confirmed in the GEO database. GSEA analysis showed that DEGs in patients with better prognosis were enriched in immune-related pathways, while DEGs in patients with poorer prognosis were enriched in cancer-related pathways and cardiovascular disease-related pathways. Finally, a new Nomogram with higher prognostic value was constructed to better predict the 1-year PFS, 3-year PFS and 5-year PFS of TCGT patients. CONCLUSIONS: We successfully established an immune-related risk model with high prognostic value and created a new Nomogram. We found that different immune status in tumor microenvironment may be responsible for the different survival outcomes among TGCT patients. 2020 Annals of Translational Medicine. All rights reserved.
Authors: Lois B Travis; Sophie D Fosså; Sara J Schonfeld; Mary L McMaster; Charles F Lynch; Hans Storm; Per Hall; Eric Holowaty; Aage Andersen; Eero Pukkala; Michael Andersson; Magnus Kaijser; Mary Gospodarowicz; Timo Joensuu; Randi J Cohen; John D Boice; Graça M Dores; Ethel S Gilbert Journal: J Natl Cancer Inst Date: 2005-09-21 Impact factor: 13.506
Authors: Z Cierna; M Mego; V Miskovska; K Machalekova; M Chovanec; D Svetlovska; K Hainova; K Rejlekova; D Macak; S Spanik; D Ondrus; K Kajo; J Mardiak; P Babal Journal: Ann Oncol Date: 2015-11-23 Impact factor: 32.976
Authors: Joost L Boormans; Javier Mayor de Castro; Lorenzo Marconi; Yuhong Yuan; M Pilar Laguna Pes; Carsten Bokemeyer; Nicola Nicolai; Ferran Algaba; Jan Oldenburg; Peter Albers Journal: Eur Urol Date: 2017-11-20 Impact factor: 20.096
Authors: Christian Daniel Fankhauser; Sophia Sander; Lisa Roth; Oliver Gross; Daniel Eberli; Tullio Sulser; Burkhardt Seifert; Joerg Beyer; Thomas Hermanns Journal: Br J Cancer Date: 2018-02-27 Impact factor: 7.640