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Lu Y, Zhou T, Lu M. A prognostic binary classifier comprised of five critical mRNAs stratified pancreatic cancer patients following resection. Heliyon 2024; 10:e31302. [PMID: 38828350 PMCID: PMC11140619 DOI: 10.1016/j.heliyon.2024.e31302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 05/08/2024] [Accepted: 05/14/2024] [Indexed: 06/05/2024] Open
Abstract
Background Pancreatic cancer is characterized by an extremely poor prognosis, even following potentially curative resection. Classical prognostic markers such as histopathological or clinical parameters have limited predictive power. The present study aimed to establish a prognostic model combining mRNA expression data with histopathological and clinical data to better predict survival and stratify pancreatic cancer patients following resection. We pioneered three models in one study and systematically evaluated the clinical benefits of all three models. Methods To identify differentially expressed genes in pancreatic cancer, mRNA data from normal (GTEx database) and pancreatic cancer (TCGA database) tissues were used. Survival analysis was carried out to identify prognosis-relevant genes from the identified differentially expressed genes and LASSO regression was used to filter out hub genes. The risk score of several hub genes was calculated according to gene expression and coefficients. Validation was carried out using an independent set of GEO microarray data. Multivariate COX regression was used for identifying independent clinical and pathological risk factors related to patient's survival in the TCGA database and a prognostic model combining mRNA expression data with histopathological and clinical data was established. Another prognostic model using clinicopathological factors from the SEER database was conceived based on multivariate COX regression. NRI (net reclassification improvement) and IDI (integrated discrimination index) were used to compare the predictive capabilities of the different models. Results We identified 1589 differentially expressed genes (DEGs) through the comparison of normal and pancreatic cancer tissues, of whom 317 were associated with prognosis(p < 0.05). LASSO regression identified five hub genes, MYEOV, ANXA2P2, MET, CEP55, and KRT7, that were used for the five-mRNA-classifier prognostic model. The classifier could stratify patients into a short and long survival group: 5-year overall survival in the training set (TCGA, 6 % vs 52 %, p < 0.001), test set (TCGA, 18 % vs 55 %,p < 0.01) and external validation set (GEO, 0 % vs 25 %, p < 0.05). Sensitivity analysis showed that the mRNA model (model 1) was better than the clinicopathological no-mRNA model (model 2) in predicting 5-year survival in the TCGA database (AUC: 0.877 vs 0.718, z = 3.165, p < 0.01) and better than the multi-factor prognostic model (model 3) from the SEER database (AUC: 0.754, z = 2.637, p < 0.01). On predictive performance, model 1 improved model 2 (NRI = 0.084, z = 1.288, p = 0.198; IDI = 0.055, z = 1.041,p = 0.298) and model 3 (NRI = 0.167,z = 1.961,p = 0.05; IDI = 0.086, z = 1.427, p = 0.154). Conclusion The five-mRNA-classifier is a reliable and feasible instrument to predict the prognosis of pancreatic cancer patients following resection. It might help in patiens counseling and assist clinicians in providing individualized treatment for patients in different risk groups.
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Affiliation(s)
- Yueqing Lu
- Hepatobiliary and Vascular Surgery, People's Hospital Affiliated to Shandong First Medical University, 271199, Shandong Province, China
| | - Tong Zhou
- Hepatobiliary and Vascular Surgery, People's Hospital Affiliated to Shandong First Medical University, 271199, Shandong Province, China
| | - Mingshu Lu
- Hepatobiliary and Vascular Surgery, People's Hospital Affiliated to Shandong First Medical University, 271199, Shandong Province, China
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Cai H, Ke ZB, Chen JY, Li XD, Zhu JM, Xue YT, Ruan ZT, Wang Z, Lin F, Zheng QS, Wei Y, Xue XY, Xu N. Ubiquitin-specific protease 5 promotes bladder cancer progression through stabilizing Twist1. Oncogene 2024; 43:703-713. [PMID: 38218898 DOI: 10.1038/s41388-023-02936-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 12/17/2023] [Accepted: 12/22/2023] [Indexed: 01/15/2024]
Abstract
Aberrant activation of the epithelial-mesenchymal transition (EMT) pathway drives the development of solid tumors, which is precisely regulated by core EMT-related transcription factors, including Twist1. However, the expression pattern and regulatory mechanism of Twist1 in the progression of bladder cancer is still unclear. In this study, we explore the role of Twist1 in the progression of bladder cancer. We discovered that the EMT regulon Twist1 protein, but not Twist1 mRNA, is overexpressed in bladder cancer samples using RT-qPCR, western blot and immunohistochemistry (IHC). Mechanistically, co-immunoprecipitation (Co-IP) coupled with liquid chromatography and tandem mass spectrometry identified USP5 as a binding partner of Twist1, and the binding of Twist1 to ubiquitin-specific protease 5 (USP5) stabilizes Twist through its deubiquitinase activity to activate the EMT. Further studies found that USP5 depletion reduces cell proliferation, invasion and the EMT in bladder cancer cells, and ectopic expression of Twist1 rescues the adverse effects of USP5 loss on cell invasion and the EMT. A xenograft tumor model was used to reconfirmed the inhibitor effect of silencing USP5 expression on tumorigenesis in vivo. In addition, USP5 protein levels are significantly elevated and positively associated with Twist1 levels in clinical bladder cancer samples. Collectively, our study revealed that USP5-Twist1 axis is a novel regulatory mechanism driving bladder cancer progression and that approaches targeting USP5 may become a promising cancer treatment strategy.
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Affiliation(s)
- Hai Cai
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Zhi-Bin Ke
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Jia-Yin Chen
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Xiao-Dong Li
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Jun-Ming Zhu
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Yu-Ting Xue
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Zhong-Tian Ruan
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Zhen Wang
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Fei Lin
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Qing-Shui Zheng
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Yong Wei
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Xue-Yi Xue
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China.
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China.
- Fujian Key Laboratory of Precision Medicine for Cancer, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China.
| | - Ning Xu
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China.
- Department of Urology, National Region Medical center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China.
- Fujian Key Laboratory of Precision Medicine for Cancer, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China.
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Wang W, Zhang X, Jiang S, Xu P, Chen K, Li K, Wang F, Le X, Zhang K. A novel signature constructed by differential genes of muscle-invasive and non-muscle-invasive bladder cancer for the prediction of prognosis in bladder cancer. Front Immunol 2023; 14:1187286. [PMID: 37691944 PMCID: PMC10483405 DOI: 10.3389/fimmu.2023.1187286] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 07/26/2023] [Indexed: 09/12/2023] Open
Abstract
Background Bladder cancer (BCa) is a malignant tumor that usually forms cancer cells in the inner lining of the bladder. Hundreds of thousands of people worldwide have BCa diagnosed each year. The purpose of this study was to construct a prognostic model by differential expression of genes between muscular and non-muscular invasive BCa, and to investigate the prognosis of BCa patients. Methods The data of BCa patients was sourced from the GEO and TCGA database. Single-cell sequencing data was obtained from three patients in the GSE135337 database, and microarray data for verification was obtained from GSE32894. Univariate, Lasso and multivariate cox regression analyses were performed to construct the prognostic model. The prognostic features, immune features and drug sensitivity of the model were further evaluated. Single-cell data and microarray data were used to validate the differential expression of model genes between muscle-invasive and non-muscle-invasive BCa. The invasion and migration of BCa cells were evaluated using the transwell assay and wound-healing assay. The cell proliferation capacity was simultaneously evaluated using Colony formation experiments. The protein expression of the specific gene was detected by western blot analysis. Results We identified 183 differentially expressed muscle-invasive-related differential genes (MIRDGs), among which four were selected to establish a prognostic model. Based on our signature, patients in different groups displayed varying levels of immune infiltration and immunotherapy profiles. Single-cell sequencing data and microarray data confirmed that four invasion-related genes were expressed at higher levels in muscle-invasive BCa. Given the critical role of S100A9 in the progression of BCa, we performed further analysis. The results showed that protein expression of S100A9 was high in muscle-invasive BCa, and S100A9 knockdown could inhibit the proliferation, migration and invasion of BCa. Conclusion These findings demonstrated that the prognostic model for BCa patients was reasonably accurate and valid, and it may prove to be of considerable value for the treatment and prognosis of BCa patients in the future. S100A9 may become a better prognostic marker and potential therapeutic target to further guide clinical treatment decisions.
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Affiliation(s)
- Weizhuo Wang
- Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Xi Zhang
- Department of Urology, Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Silin Jiang
- Department of Urology, Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Peng Xu
- Department of Urology, Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Kang Chen
- Department of Urology, North China University of Science and Technology, Tangshan, China
| | - Kai Li
- Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Fei Wang
- Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Xiang Le
- Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Ke Zhang
- Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
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Font A, Domenech M, Ramirez JL, Marqués M, Benítez R, Ruiz de Porras V, Gago JL, Carrato C, Sant F, Lopez H, Castellano D, Malats N, Calle ML, Real FX. Predictive signature of response to neoadjuvant chemotherapy in muscle-invasive bladder cancer integrating mRNA expression, taxonomic subtypes, and clinicopathological features. Front Oncol 2023; 13:1155244. [PMID: 37588099 PMCID: PMC10426739 DOI: 10.3389/fonc.2023.1155244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 07/10/2023] [Indexed: 08/18/2023] Open
Abstract
Background and objective Neoadjuvant chemotherapy (NAC) followed by cystectomy is the standard of care in muscle-invasive bladder cancer (MIBC). Pathological response has been associated with longer survival, but no currently available clinicopathological variables can identify patients likely to respond, highlighting the need for predictive biomarkers. We sought to identify a predictive signature of response to NAC integrating clinical score, taxonomic subtype, and gene expression. Material and methods From 1994 to 2014, pre-treatment tumor samples were collected from MIBC patients (stage T2-4N0/+M0) at two Spanish hospitals. A clinical score was determined based on stage, hydronephrosis and histology. Taxonomic subtypes (BASQ, luminal, and mixed) were identified by immunohistochemistry. A custom set of 41 genes involved in DNA damage repair and immune response was analyzed in 84 patients with the NanoString nCounter platform. Genes related to pathological response were identified by LASSO penalized logistic regression. NAC consisted of cisplatin/methotrexate/vinblastine until 2000, after which most patients received cisplatin/gemcitabine. The capacity of the integrated signature to predict pathological response was assessed with AUC. Overall survival (OS) and disease-specific survival (DSS) were analyzed with the Kaplan-Meier method. Results LASSO selected eight genes to be included in the signature (RAD51, IFNγ, CHEK1, CXCL9, c-MET, KRT14, HERC2, FOXA1). The highest predictive accuracy was observed with the inclusion in the model of only three genes (RAD51, IFNɣ, CHEK1). The integrated clinical-taxonomic-gene expression signature including these three genes had a higher predictive ability (AUC=0.71) than only clinical score plus taxonomic subtype (AUC=0.58) or clinical score alone (AUC=0.56). This integrated signature was also significantly associated with OS (p=0.02) and DSS (p=0.02). Conclusions We have identified a predictive signature for response to NAC in MIBC patients that integrates the expression of three genes with clinicopathological characteristics and taxonomic subtypes. Prospective studies to validate these results are ongoing.
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Affiliation(s)
- Albert Font
- Medical Oncology Department, Institut Català d’Oncologia, Hospital Universitari Germans Trias i Pujol, Badalona, Barcelona, Spain
- Badalona Applied Research Group in Oncology (B-ARGO), Germans Trias i Pujol Research Institute (IGTP), Badalona, Barcelona, Spain
| | - Montserrat Domenech
- Medical Oncology Department, Althaia Xarxa Assistencial Universitària de Manresa, Manresa, Spain
| | - Jose Luis Ramirez
- Hematology Service, Institut Català d'Oncologia (ICO) Badalona-Hospital Germans Trias i Pujol, Lymphoid Neoplasms Group, Josep Carreras Leukemia Research Institute (IJC), Badalona, Spain
| | - Miriam Marqués
- Epithelial Carcinogenesis Group, Spanish National Cancer Research Centre (CNIO) and CIBERONC, Madrid, Spain
| | - Raquel Benítez
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), and CIBERONC, Madrid, Spain
| | - Vicenç Ruiz de Porras
- Medical Oncology Department, Institut Català d’Oncologia, Hospital Universitari Germans Trias i Pujol, Badalona, Barcelona, Spain
- Badalona Applied Research Group in Oncology (B-ARGO), Germans Trias i Pujol Research Institute (IGTP), Badalona, Barcelona, Spain
| | - José L. Gago
- Urology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Barcelona, Spain
| | - Cristina Carrato
- Pathology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Barcelona, Spain
| | - Francesc Sant
- Pathology Department, Althaia Xarxa Assistencial Universitària de Manresa, Manresa, Spain
| | - Hector Lopez
- Urology Department, Althaia Xarxa Assistencial Universitària de Manresa, Manresa, Spain
| | - Daniel Castellano
- Medical Oncology Department, University Hospital 12 de Octubre, Madrid, Spain
| | - Nuria Malats
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), and CIBERONC, Madrid, Spain
| | - M. Luz Calle
- Biosciences Department, Faculty of Sciences, Technology, University of Vic-Central University of Catalonia, Vic, Barcelona, Spain
| | - Francisco X. Real
- Epithelial Carcinogenesis Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centre for Biomedical Research in Cancer Network (CIBERONC), Madrid, Spain
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
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Yao Z, Zhang H, Zhang X, Zhang Z, Jie J, Xie K, Li F, Tan W. Identification of tumor microenvironment-related signature for predicting prognosis and immunotherapy response in patients with bladder cancer. Front Genet 2022; 13:923768. [PMID: 36147509 PMCID: PMC9485450 DOI: 10.3389/fgene.2022.923768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 07/11/2022] [Indexed: 11/13/2022] Open
Abstract
The tumor microenvironment (TME) not only provides fertile soil for tumor growth and development but also widely involves immune evasion as well as the resistance towards therapeutic response. Accumulating interest has been attracted from the biological function of TME to its effects on patient outcomes and treatment efficacy. However, the relationship between the TME-related gene expression profiles and the prognosis of bladder cancer (BLCA) remains unclear. The TME-related genes expression data of BLCA were collected from The Cancer Genome Atlas (TCGA) database. NFM algorithm was used to identify the distinct molecular pattern based on the significantly different TME-related genes. LASSO regression and Cox regression analyses were conducted to identify TME-related gene markers related to the prognosis of BLCA and to establish a prognostic model. The predictive efficacy of the risk model was verified through integrated bioinformatics analyses. Herein, 10 TME-related genes (PFKFB4, P4HB, OR2B6, OCIAD2, OAS1, KCNJ15, AHNAK, RAC3, EMP1, and PRKY) were identified to construct the prognostic model. The established risk scores were able to predict outcomes at 1, 3, and 5 years with greater accuracy than previously known models. Moreover, the risk score was closely associated with immune cell infiltration and the immunoregulatory genes including T cell exhaustion markers. Notably, the predictive power of the model in immunotherapy sensitivity was verified when it was applied to patients with metastatic urothelial carcinoma (mUC) undergoing immunotherapy. In conclusion, TME risk score can function as an independent prognostic biomarker and a predictor for evaluating immunotherapy response in BLCA patients, which provides recommendations for improving patients’ response to immunotherapy and promoting personalized tumor immunotherapy in the future.
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Affiliation(s)
| | | | | | | | | | | | - Fei Li
- *Correspondence: Fei Li, ; Wanlong Tan,
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Prediction of Prognosis and Recurrence of Bladder Cancer by ECM-Related Genes. J Immunol Res 2022; 2022:1793005. [PMID: 35450397 PMCID: PMC9018183 DOI: 10.1155/2022/1793005] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/01/2022] [Indexed: 12/24/2022] Open
Abstract
Background Bladder cancer (BLCA) is one of the most common cancers and ranks ninth among all cancers. Extracellular matrix (ECM) genes activate a number of pathways that facilitate tumor development. This study is aimed at providing models to predict BLCA survival and recurrence by ECM genes. Methods Expression data from BLCA samples in GSE32894, GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts were downloaded and analyzed. The ECM-related genes were obtained by differentially expressed gene analysis, stage-associated gene analysis, and random forest variable selection. The ECM was constructed in GSE32894 by the hub ECM-related genes and validated in GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts. The correlations of the ECM score with cells (T cells, fibroblasts, etc.) and the response to immunotherapeutic drugs were investigated. Four machine learning models were selected and used to construct models to predict the recurrence of BLCA. A total of 15 paired BLCA and normal tissue specimens, human immortalized uroepithelial cell lines, and bladder cancer cell lines were selected for the validation of the difference in expression of FSTL1 between normal tissues and BLCA. Results Six ECM genes (CTHRC1, MMP11, COL10A1, FSTL1, SULF1, and COL5A3) were recognized to be the hub ECM-related genes. The ECM score of each BLCA patient was calculated using these six selected ECM-related genes. BLCA patients with a high ECM score group had significantly lower overall survival rates than patients in the low ECM score group. We found that the ECM score was positively associated with immune cells and fibroblasts and negatively correlated with tumor purity. When treated with immunotherapy, BLCA patients with a high ECM score presented a high response rate and better prognosis. We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence. Based on the RT-qPCR results of FSTL1 gene expression, there was an overall decrease in the mRNA expression of FSTL1 in cancer tissues compared to their adjacent normal tissues. Subsequent in vitro validation demonstrated that the FSTL1 expression was downregulated at the gene and protein level compared to that in SVH cells. Conclusion Taken together, our results indicate that ECM-related genes correlate with immune cells, overall survival, and recurrence of BLCA. This study provides a machine learning model for predicting the survival and recurrence of BLCA patients.
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Liu Z, Pan R, Li W, Li Y. Comprehensive Analysis of Cell Cycle-Related Genes in Patients With Prostate Cancer. Front Oncol 2022; 11:796795. [PMID: 35087757 PMCID: PMC8787043 DOI: 10.3389/fonc.2021.796795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
This study aimed to identify critical cell cycle-related genes (CCRGs) in prostate cancer (PRAD) and to evaluate the clinical prognostic value of the gene panel selected. Gene set variation analysis (GSVA) of dysregulated genes between PRAD and normal tissues demonstrated that the cell cycle-related pathways played vital roles in PRAD. Patients were classified into four clusters, which were associated with recurrence-free survival (RFS). Moreover, 200 prognostic-related genes were selected using the Kaplan-Meier (KM) survival analysis and univariable Cox regression. The prognostic CCRG risk score was constructed using random forest survival and multivariate regression Cox methods, and their efficiency was validated in Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70770. We identified nine survival-related genes: CCNL2, CDCA5, KAT2A, CHTF18, SPC24, EME2, CDK5RAP3, CDC20, and PTTG1. Based on the median risk score, the patients were divided into two groups. Then the functional enrichment analyses, mutational profiles, immune components, estimated half-maximal inhibitory concentration (IC50), and candidate drugs were screened of these two groups. In addition, the characteristics of nine hub CCRGs were explored in Oncomine, cBioPortal, and the Human Protein Atlas (HPA) datasets. Finally, the expression profiles of these hub CCRGs were validated in RWPE-1 and three PRAD cell lines (PC-3, C4-2, and DU-145). In conclusion, our study systematically explored the role of CCRGs in PRAD and constructed a risk model that can predict the clinical prognosis and immunotherapeutic benefits.
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Affiliation(s)
- Zehua Liu
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Rongfang Pan
- Department of Nutrition, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Wenxian Li
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yanjiang Li
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
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EGF-induced nuclear translocation of SHCBP1 promotes bladder cancer progression through inhibiting RACGAP1-mediated RAC1 inactivation. Cell Death Dis 2022; 13:39. [PMID: 35013128 PMCID: PMC8748695 DOI: 10.1038/s41419-021-04479-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 12/01/2021] [Accepted: 12/14/2021] [Indexed: 12/12/2022]
Abstract
Bladder cancer is a highly heterogeneous and aggressive malignancy with a poor prognosis. EGF/EGFR activation causes the detachment of SHC-binding protein 1 (SHCBP1) from SHC adapter protein 1 (SHC1), which subsequently translocates into the nucleus and promotes cancer development via multiple signaling pathways. However, the role of the EGF-SHCBP1 axis in bladder cancer progression remains unexplored. Herein, we report that SHCBP1 is upregulated in bladder cancer tissues and cells, with cytoplasmic or nuclear localization. Released SHCBP1 responds to EGF stimulation by translocating into the nucleus following Ser273 phosphorylation. Depletion of SHCBP1 reduces EGF-induced cell migration and invasiveness of bladder cancer cells. Mechanistically, SHCBP1 binds to RACGAP1 via its N-terminal domain of amino acids 1 ~ 428, and this interaction is enhanced following EGF treatment. Furthermore, SHCBP1 facilitates cell migration by inhibiting RACGAP-mediated GTP-RAC1 inactivation, whose activity is indispensable for cell movement. Collectively, we demonstrate that the EGF-SHCBP1-RACGAP1-RAC1 axis acts as a novel regulatory mechanism of bladder cancer progression, which offers a new clinical therapeutic strategy to combat bladder cancer.
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9
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Lai C, Zhang C, Lv H, Huang H, Ke X, Zhou C, Chen H, Chen S, Zhou L. A novel prognostic model predicts overall survival in patients with nasopharyngeal carcinoma based on clinical features and blood biomarkers. Cancer Med 2021; 10:3511-3523. [PMID: 33973727 PMCID: PMC8178501 DOI: 10.1002/cam4.3839] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 02/25/2021] [Accepted: 02/26/2021] [Indexed: 01/15/2023] Open
Abstract
This study aims to develop and validate a novel prognostic model to estimate overall survival (OS) in nasopharyngeal carcinoma (NPC) patients based on clinical features and blood biomarkers. We assessed the model's incremental value to the TNM staging system, clinical treatment, and Epstein‐Barr virus (EBV) DNA copy number for individual OS estimation. We retrospectively analyzed 519 consecutive patients with NPC. A prognostic model was generated using the Lasso regression model in the training cohort. Then we compared the predictive accuracy of the novel prognostic model with TNM staging, clinical treatment, and EBV DNA copy number using concordance index (C‐index), time‐dependent ROC (tdROC), and decision curve analysis (DCA). Subsequently, we built a nomogram for OS incorporating the prognostic model, TNM staging, and clinical treatment. Finally, we stratified patients into high‐risk and low‐risk groups according to the model risk score, and we analyzed the survival time of these two groups using Kaplan–Meier survival plots. All results were validated in the independent validation cohort. Using the Lasso regression, we established a prognostic model consisting of 13 variables with respect to patient prognosis. The C‐index, tdROC, and DCA showed that the prognostic model had good predictive accuracy and discriminatory power in the training cohort than did TNM staging, clinical treatment, and EBV DNA copy number. Nomogram consisting of the prognostic model, TNM staging, clinical treatment, and EBV DNA copy number showed some superior net benefit. Based on the model risk score, we split the patients into two subgroups: low‐risk (risk score ≤ −1.423) and high‐risk (risk score > −1.423). There were significant differences in OS between the two subgroups of patients. Similar results were observed in the validation cohort. The proposed novel prognostic model based on clinical features and serological markers may represent a promising tool for estimating OS in NPC patients.
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Affiliation(s)
- Changchun Lai
- Department Of Clinical Laboratory, Maoming People's Hospital, Maoming, P. R. China
| | - Chunning Zhang
- Department Of First Tumor, Maoming People's Hospital, Maoming, P. R. China
| | - Hualiang Lv
- Department of Pulmonary and Critical Care Medicine, Maoming People's Hospital, Maoming, P. R. China
| | - Hanqing Huang
- Department of Thoracic Surgery, Maoming People's Hospital, Maoming, P. R. China
| | - Xia Ke
- Department Of Clinical Laboratory, Maoming People's Hospital, Maoming, P. R. China
| | - Chuchan Zhou
- Department Of Clinical Laboratory, Maoming People's Hospital, Maoming, P. R. China
| | - Hao Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Shulin Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China.,Research Center for Translational Medicine, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, P.R. China
| | - Lei Zhou
- Department Of Pathology Laboratory, Maoming People's Hospital, Maoming, P. R. China
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Six Glycolysis-Related Genes as Prognostic Risk Markers Can Predict the Prognosis of Patients with Head and Neck Squamous Cell Carcinoma. BIOMED RESEARCH INTERNATIONAL 2021; 2021:8824195. [PMID: 33628816 PMCID: PMC7889344 DOI: 10.1155/2021/8824195] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 01/10/2021] [Accepted: 01/15/2021] [Indexed: 02/06/2023]
Abstract
Objective Head and neck squamous cell carcinoma (HNSCC) is one of the worst-prognosis malignant tumors. This study used bioinformatic analysis of the transcriptome sequencing data of HNSCC and the patients' survival and clinical data to construct a prediction signature of glycolysis-related genes as the prognostic risk markers. Methods Gene expression profile data about HNSCC tissues (n = 498) and normal tissues in the head and neck (n = 44) were got from The Cancer Genome Atlas (TCGA), as well as patients' survival and clinical data. Then, we obtained core genes; their expression in head and neck squamous cell carcinoma tissues is significantly different from that in normal head and neck tissues. The predicted glycolysis-related genes are screened through univariate Cox regression analysis, and then, the prognostic risk markers were constructed through further correction of multivariate Cox regression analysis. The Kaplan-Meier curve and receiver operating characteristic curve are used to analyze the potential value of these risk markers in diagnosis and prognosis. We also evaluated that the glycolysis-related prognostic risk markers composed of 6 oncogenes are correlated with clinical features, such as age, gender, grade, and clinical stage of the tumor, by univariate and multivariate Cox regression analyses. Results Differentially expressed glycolytic genes in HNSCC tissues and normal head and neck tissues were screened from TCGA databases using the bioinformatic method. We confirmed a set of six glycolytic genes that were significantly associated with OS in the test series. According to our analysis, the prognostic risk markers composed of HPRT1, STC2, PLCB3, GPR87, PYGL, and SLC5A12 may be an independent risk factor for the prognosis of HNSCC. Conclusions Through this analysis, we constructed new prognostic risk markers related to glycolysis as a prognostic risk marker for patients with HNSCC and provided new ideas and molecular targets for the research and individualized treatment of HNSCC.
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11
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Meng H, Jiang X, Cui J, Yin G, Shi B, Liu Q, Xuan H, Wang Y. Genomic Analysis Reveals Novel Specific Metastatic Mutations in Chinese Clear Cell Renal Cell Carcinoma. BIOMED RESEARCH INTERNATIONAL 2020; 2020:2495157. [PMID: 33062672 PMCID: PMC7545427 DOI: 10.1155/2020/2495157] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 07/03/2020] [Accepted: 08/17/2020] [Indexed: 02/07/2023]
Abstract
Clear cell renal cell carcinoma (ccRCC) accounts for more than 75% of renal cell carcinoma. Nearly 25% of ccRCC patients were diagnosed with metastasis. Though the genomic profile of ccRCC has been widely studied, the difference between localized and metastatic ccRCC was not clarified. Primary tumor samples and matched whole blood were collected from 106 sporadic patients diagnosed with renal clear cell carcinoma at Qilu Hospital of Shandong University from January 2017 to November 2019, and 17 of them were diagnosed with metastasis. A hybridization capture-based next-generation sequencing of 618 cancer-related genes was performed to investigate the somatic and germline variants, tumor mutation burden (TMB), and microsatellite instability (MSI). Five genes with significantly different prevalence were identified in the metastatic group, especially TOP1 (17.65% vs. 0%) and SNCAIP (17.65% vs. 0%). The altered frequency of PBRM1 (0% vs. 27%) and BAP1 (24% vs. 10%) differed between the metastatic and nonmetastatic groups, which may relate to the prognosis. Of these 106 patients, 42 patients (39.62%) had at least one alteration in DNA damage repair (DDR) genes, including 58.82% of metastatic ccRCC patients and 35.96% of ccRCC patients without metastasis. Ten pathogenic or likely pathogenic (P/LP) variants were identified in 11 sporadic clear cell renal cell carcinoma patients (10.38%), including rarely reported ATM (n=1), MUTYH (n=1), NBN (n=1), RAD51D (n=1), and BRCA2 (n=1). No significant difference in the ratio of P/LP variant carriers or TMB was identified between the metastatic and nonmetastatic groups. We found a unique genomic feature of Chinese metastatic ccRCC patients with a higher prevalence of alterations in DDR, TOP1, and SNCAIP. Further investigated studies and drug development are needed in the future.
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Affiliation(s)
- Hui Meng
- Department of Urology, Qilu Hospital of Shandong University, 107 Jinan Culture Road, Jinan, 250012 Shandong, China
| | - Xuewen Jiang
- Department of Urology, Qilu Hospital of Shandong University, 107 Jinan Culture Road, Jinan, 250012 Shandong, China
| | - Jianfeng Cui
- Department of Urology, Qilu Hospital of Shandong University, 107 Jinan Culture Road, Jinan, 250012 Shandong, China
| | - Gang Yin
- Department of Urology, Qilu Hospital of Shandong University, 107 Jinan Culture Road, Jinan, 250012 Shandong, China
| | - Benkang Shi
- Department of Urology, Qilu Hospital of Shandong University, 107 Jinan Culture Road, Jinan, 250012 Shandong, China
| | - Qi Liu
- Life Healthcare Medical Laboratory Co., Ltd., Hangzhou, 310052 Zhejiang, China
| | - He Xuan
- Life Healthcare Medical Laboratory Co., Ltd., Hangzhou, 310052 Zhejiang, China
| | - Yu Wang
- Reproductive Medicine Center, Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, 107 Jinan Culture Road, Jinan, 250012 Shandong, China
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12
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AEBP1 is a Novel Oncogene: Mechanisms of Action and Signaling Pathways. JOURNAL OF ONCOLOGY 2020; 2020:8097872. [PMID: 32565808 PMCID: PMC7273425 DOI: 10.1155/2020/8097872] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 04/13/2020] [Indexed: 12/29/2022]
Abstract
Adipocyte enhancer-binding protein 1 (AEBP1) is a transcriptional repressor involved in the regulation of critical biological processes including adipogenesis, mammary gland development, inflammation, macrophage cholesterol homeostasis, and atherogenesis. Several years ago, we first reported the ability of AEBP1 to exert a positive control over the canonical NF-κB pathway. Indeed, AEBP1 positively regulates NF-κB activity via its direct interaction with IκBα, a key NF-κB inhibitor. AEBP1 overexpression results in uncontrollable activation of NF-κB, which may have severe pathogenic outcomes. Recently, the regulatory relationship between AEBP1 and NF-κB pathway has been of great interest to many researchers primarily due to the implication of NF-κB signaling in critical cellular processes such as inflammation and cancer. Since constitutive activation of NF-κB is widely implicated in carcinogenesis, AEBP1 overexpression is associated with tumor development and progression. Recent studies sought to explore the effects of the overexpression of AEBP1, as a potential oncogene, in different types of cancer. In this review, we analyze the effects of AEBP1 overexpression in a variety of malignancies (e.g., breast cancer, glioblastoma, bladder cancer, gastric cancer, colorectal cancer, ovarian cancer, and skin cancer), with a specific focus on the AEBP1-mediated control over the canonical NF-κB pathway. We also underscore the ability of AEBP1 to regulate crucial cancer-related events like cell proliferation and apoptosis in light of other key pathways (e.g., PI3K-Akt, sonic hedgehog (Shh), p53, parthanatos (PARP-1), and PTEN). Identifying AEBP1 as a potential biomarker for cancer prognosis may lead to a novel therapeutic target for the prevention and/or treatment of various types of cancer.
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Zhang C, Gou X, He W, Yang H, Yin H. A glycolysis-based 4-mRNA signature correlates with the prognosis and cell cycle process in patients with bladder cancer. Cancer Cell Int 2020; 20:177. [PMID: 32467671 PMCID: PMC7238531 DOI: 10.1186/s12935-020-01255-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 05/10/2020] [Indexed: 12/17/2022] Open
Abstract
Background Bladder cancer is one of the most prevalent malignancies worldwide. However, traditional indicators have limited predictive effects on the clinical outcomes of bladder cancer. The aim of this study was to develop and validate a glycolysis-related gene signature for predicting the prognosis of patients with bladder cancer that have limited therapeutic options. Methods mRNA expression profiling was obtained from patients with bladder cancer from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) was conducted to identify glycolytic gene sets that were significantly different between bladder cancer tissues and paired normal tissues. A prognosis-related gene signature was constructed by univariate and multivariate Cox analysis. Kaplan–Meier curves and time-dependent receiver operating characteristic (ROC) curves were utilized to evaluate the signature. A nomogram combined with the gene signature and clinical parameters was constructed. Correlations between glycolysis-related gene signature and molecular characterization as well as cancer subtypes were analyzed. RT-qPCR was applied to analyze gene expression. Functional experiments were performed to determine the role of PKM2 in the proliferation of bladder cancer cells. Results Using a Cox proportional regression model, we established that a 4-mRNA signature (NUP205, NUPL2, PFKFB1 and PKM) was significantly associated with prognosis in bladder cancer patients. Based on the signature, patients were split into high and low risk groups, with different prognostic outcomes. The gene signature was an independent prognostic indicator for overall survival. The ability of the 4-mRNA signature to make an accurate prognosis was tested in two other validation datasets. GSEA was performed to explore the 4-mRNA related canonical pathways and biological processes, such as the cell cycle, hypoxia, p53 pathway, and PI3K/AKT/mTOR pathway. A heatmap showing the correlation between risk score and cell cycle signature was generated. RT-qPCR revealed the genes that were differentially expressed between normal and cancer tissues. Experiments showed that PKM2 plays essential roles in cell proliferation and the cell cycle. Conclusion The established 4‑mRNA signature may act as a promising model for generating accurate prognoses for patients with bladder cancer, but the specific biological mechanism needs further verification.
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Affiliation(s)
- Chen Zhang
- 2Department of Gynecology and Obstetrics, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Chongqing, 400016 China.,4Chongqing Key Laboratory of Maternal and Fetal Medicine, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Chongqing, 400016 China
| | - Xin Gou
- 1Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Chongqing, 400016 China
| | - Weiyang He
- 1Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Chongqing, 400016 China
| | - Huaan Yang
- Department of Urology, Yubei District People's Hospital, No. 69 Jianshe Road, Chongqing, 400016 China
| | - Hubin Yin
- 1Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Chongqing, 400016 China.,3Central Laboratory, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Chongqing, 400016 China
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