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He X, Hu S, Wang C, Yang Y, Li Z, Zeng M, Song G, Li Y, Lu Q. Predicting prostate cancer recurrence: Introducing PCRPS, an advanced online web server. Heliyon 2024; 10:e28878. [PMID: 38623253 PMCID: PMC11016622 DOI: 10.1016/j.heliyon.2024.e28878] [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: 08/27/2023] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 04/17/2024] Open
Abstract
Background Prostate cancer (PCa) is one of the leading causes of cancer death in men. About 30% of PCa will develop a biochemical recurrence (BCR) following initial treatment, which significantly contributes to prostate cancer-related deaths. In clinical practice, accurate prediction of PCa recurrence is crucial for making informed treatment decisions. However, the development of reliable models and biomarkers for predicting PCa recurrence remains a challenge. In this study, the aim is to establish an effective and reliable tool for predicting the recurrence of PCa. Methods We systematically screened and analyzed potential datasets to predict PCa recurrence. Through quality control analysis, low-quality datasets were removed. Using meta-analysis, differential expression analysis, and feature selection, we identified key genes associated with recurrence. We also evaluated 22 previously published signatures for PCa recurrence prediction. To assess prediction performance, we employed nine machine learning algorithms. We compared the predictive capabilities of models constructed using clinical variables, expression data, and their combinations. Subsequently, we implemented these machine learning models into a user-friendly web server freely accessible to all researchers. Results Based on transcriptomic data derived from eight multicenter studies consisting of 733 PCa patients, we screened 23 highly influential genes for predicting prostate cancer recurrence. These genes were used to construct the Prostate Cancer Recurrence Prediction Signature (PCRPS). By comparing with 22 published signatures and four important clinicopathological features, the PCRPS exhibited a robust and significantly improved predictive capability. Among the tested algorithms, Random Forest demonstrated the highest AUC value of 0.72 in predicting PCa recurrence in the testing dataset. To facilitate access and usage of these machine learning models by all researchers and clinicians, we also developed an online web server (https://urology1926.shinyapps.io/PCRPS/) where the PCRPS model can be freely utilized. The tool can also be used to (1) predict the PCa recurrence by clinical information or expression data with high accuracy. (2) provide the possibility of PCa recurrence by nine machine learning algorithms. Furthermore, using the PCRPS scores, we predicted the sensitivity of 22 drugs from GDSC2 and 95 drugs from CTRP2 to the samples. These predictions provide valuable insights into potential drug sensitivities related to the PCRPS score groups. Conclusion Overall, our study provides an attractive tool to further guide the clinical management and individualized treatment for PCa.
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Affiliation(s)
| | | | - Chen Wang
- Department of Urology, Hunan Provincial People's Hospital (The 1st Affiliated Hospital of Hunan Normal University), China
| | - Yongjun Yang
- Department of Urology, Hunan Provincial People's Hospital (The 1st Affiliated Hospital of Hunan Normal University), China
| | - Zhuo Li
- Department of Urology, Hunan Provincial People's Hospital (The 1st Affiliated Hospital of Hunan Normal University), China
| | - Mingqiang Zeng
- Department of Urology, Hunan Provincial People's Hospital (The 1st Affiliated Hospital of Hunan Normal University), China
| | - Guangqing Song
- Department of Urology, Hunan Provincial People's Hospital (The 1st Affiliated Hospital of Hunan Normal University), China
| | - Yuanwei Li
- Department of Urology, Hunan Provincial People's Hospital (The 1st Affiliated Hospital of Hunan Normal University), China
| | - Qiang Lu
- Department of Urology, Hunan Provincial People's Hospital (The 1st Affiliated Hospital of Hunan Normal University), China
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Zhong Q, Sun R, Aref AT, Noor Z, Anees A, Zhu Y, Lucas N, Poulos RC, Lyu M, Zhu T, Chen GB, Wang Y, Ding X, Rutishauser D, Rupp NJ, Rueschoff JH, Poyet C, Hermanns T, Fankhauser C, Rodríguez Martínez M, Shao W, Buljan M, Neumann JF, Beyer A, Hains PG, Reddel RR, Robinson PJ, Aebersold R, Guo T, Wild PJ. Proteomic-based stratification of intermediate-risk prostate cancer patients. Life Sci Alliance 2024; 7:e202302146. [PMID: 38052461 PMCID: PMC10698198 DOI: 10.26508/lsa.202302146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 11/22/2023] [Accepted: 11/23/2023] [Indexed: 12/07/2023] Open
Abstract
Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.
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Affiliation(s)
- Qing Zhong
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Rui Sun
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Adel T Aref
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Zainab Noor
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Asim Anees
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Yi Zhu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Natasha Lucas
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Rebecca C Poulos
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Mengge Lyu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Tiansheng Zhu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Guo-Bo Chen
- Urology & Nephrology Center, Department of Urology, Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Yingrui Wang
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Xuan Ding
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Dorothea Rutishauser
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Niels J Rupp
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Jan H Rueschoff
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Cédric Poyet
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
| | - Thomas Hermanns
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
| | - Christian Fankhauser
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
- Department of Urology, Cantonal Hospital Lucerne, Lucerne, Switzerland
| | | | - Wenguang Shao
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Marija Buljan
- Empa - Swiss Federal Laboratories for Materials Science and Technology, St. Gallen, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | | | - Peter G Hains
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Roger R Reddel
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Phillip J Robinson
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
- Faculty of Science, University of Zürich, Zürich, Switzerland
| | - Tiannan Guo
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Peter J Wild
- Goethe University Frankfurt, Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
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Liu L, Li Y, Tang S, Yang B, Zhang Q, Xiao R, Hou X, Liu C, Ma L. Gleason Score-related MT1L as biomarker for prognosis in prostate adenocarcinoma and contribute to tumor progression in vitro. Int J Biol Markers 2023:3936155231156458. [PMID: 37192745 DOI: 10.1177/03936155231156458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
BACKGROUND The Gleason Score is well correlated with biological behavior and prognosis in prostate adenocarcinoma (PRAD). This study was derived to determine the clinical significance and function of Gleason-Score-related genes in PRAD. METHODS RNA-sequencing profiles and clinical data were extracted from the The Cancer Genome Atlas PRAD database. The Gleason-Score-related genes were screened out by the Jonckheere-Terpstra rank-based test. The "limma" R package was performed for differentially expressed genes. Next, a Kaplan-Meier survival analysis was performed. Correlation MT1L expression levels with tumor stage, non-tumor tissue stage, radiation therapy, and residual tumor were analyzed. Further, MT1L expression was detected in PRAD cell lines by reverse transcription-quantitative polymerase chain reaction assay. Overexpression of MT1L was constructed and used for cell count kit-8, flow cytometric assay, transwell assay, and wound-healing assay. RESULTS Survival analysis showed 15 Gleason-Score-related genes as prognostic biomarkers in PRAD. The high-frequency deletion of MT1L was verified in PRAD. Furthermore, MT1L expression was decreased in PRAD cell lines than RWPE-1 cells, and overexpression of MT1L repressed cell proliferation and migration, and induced apoptosis in PC-3 cells. CONCLUSION Gleason-Score-related MT1L may serve as a biomarker of poor prognostic biomarker in PRAD. In addition, MT1L plays a tumor suppressor in PRAD progression, which is beneficial for PRAD diagnosis and treatment research.
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Affiliation(s)
- Lei Liu
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Yaping Li
- Department of Medicine, Acornmed Biotechnology Co., Ltd, Beijing, China
| | - Shiying Tang
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Bin Yang
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Qiming Zhang
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Ruotao Xiao
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Xiaofei Hou
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Cheng Liu
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Lulin Ma
- Department of Urology, Peking University Third Hospital, Beijing, China
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Samaržija I, Trošelj KG, Konjevoda P. Prognostic Significance of Amino Acid Metabolism-Related Genes in Prostate Cancer Retrieved by Machine Learning. Cancers (Basel) 2023; 15:cancers15041309. [PMID: 36831650 PMCID: PMC9954451 DOI: 10.3390/cancers15041309] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 02/11/2023] [Accepted: 02/16/2023] [Indexed: 02/22/2023] Open
Abstract
Prostate cancer is among the leading cancers according to both incidence and mortality. Due to the high molecular, morphological and clinical heterogeneity, the course of prostate cancer ranges from slow growth that usually does not require immediate therapeutic intervention to aggressive and fatal disease that spreads quickly. However, currently available biomarkers cannot precisely predict the course of a disease, and novel strategies are needed to guide prostate cancer management. Amino acids serve numerous roles in cancers, among which are energy production, building block reservoirs, maintenance of redox homeostasis, epigenetic regulation, immune system modulation and resistance to therapy. In this article, by using The Cancer Genome Atlas (TCGA) data, we found that the expression of amino acid metabolism-related genes is highly aberrant in prostate cancer, which holds potential to be exploited in biomarker design or in treatment strategies. This change in expression is especially evident for catabolism genes and transporters from the solute carrier family. Furthermore, by using recursive partitioning, we confirmed that the Gleason score is strongly prognostic for progression-free survival. However, the expression of the genes SERINC3 (phosphatidylserine and sphingolipids generation) and CSAD (hypotaurine generation) can refine prognosis for high and low Gleason scores, respectively. Therefore, our results hold potential for novel prostate cancer progression biomarkers.
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Jin Z, Peng F, Zhang C, Tao S, Xu D, Zhu Z. Expression, regulating mechanism and therapeutic target of KIF20A in multiple cancer. Heliyon 2023; 9:e13195. [PMID: 36798768 PMCID: PMC9925975 DOI: 10.1016/j.heliyon.2023.e13195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 01/15/2023] [Accepted: 01/19/2023] [Indexed: 01/26/2023] Open
Abstract
Kinesin family member 20A (KIF20A) is a member of the kinesin family. It transports chromosomes during mitosis, plays a key role in cell division. Recently, studies proved that KIF20A was highly expressed in cancer. High expression of KIF20A was correlated with poor overall survival (OS). In this review, we summarized all the cancer that highly expressed KIF20A, described the role of KIF20A in cancer. We also organized phase I and phase II clinical trials of KIF20A peptides vaccine. All results indicated that KIF20A was a promising therapeutic target for multiple cancer.
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Key Words
- ATP, adenosine triphosphate
- BTC, biliary tract cancer
- CPC, chromosomal passenger complex
- CTL, cytotoxic T lymphocyte
- Cancer
- Cdk1, cyclin-dependent kinase 1
- DLG5, discs large MAGUK scaffold protein 5
- EMT, epithelial-mesenchymal transition
- Expression
- FoxM1, forkhead box protein M1
- GC, gastric cancer
- GEM, gemcitabine
- Gli2, glioma-associated oncogene 2
- HLA, human leukocyte antigen
- HNMT, head-and-neck malignant tumor
- IRF, interferon regulatory factor
- JAK, Janus kinase
- KIF20A
- KIF20A, kinesin family member 20A
- LP, long peptide
- MHC I, major histocompatibility complex I
- MKlp2, mitotic kinesin-like protein 2
- Mad2, mitotic arrest deficient 2
- OS, overall survival
- PBMC, peripheral blood mononuclear cell
- Plk1, polo-like kinase 1
- Regulating mechanisms
- Therapeutic target
- circRNA, circular RNA
- miRNA, microRNA
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Affiliation(s)
- Zheng Jin
- Department of Respirology & Allergy, The Third Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong Province, China
| | - Fei Peng
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Baylor College of Medicine, Houston, Texas, USA
| | - Chao Zhang
- Guangzhou Women and Children's Medical Center, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Shuang Tao
- Department of Otorhinolaryngology Head and Neck Surgery, Longgang Central Hospital of Shenzhen, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, China
| | - Damo Xu
- Department of Respirology & Allergy, The Third Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong Province, China,State Key Laboratory of Respiratory Disease for Allergy at Shenzhen University, Shenzhen Key Laboratory of Allergy and Immunology, Shenzhen University School of Medicine, Shenzhen, Guangdong Province, China,Corresponding author. Department of Respirology & Allergy, The Third Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong Province, China.
| | - Zhenhua Zhu
- Department of Orthopaedic Trauma, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong Province, China,Corresponding author. Department of Orthopaedic Trauma, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong Province, China.
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Chen J, Sun M, Chen C, Jiang B, Fang Y. Identification of hub genes and their correlation with infiltration of immune cells in MYCN positive neuroblastoma based on WGCNA and LASSO algorithm. Front Immunol 2022; 13:1016683. [PMID: 36311753 PMCID: PMC9596756 DOI: 10.3389/fimmu.2022.1016683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 09/28/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe prognosis of MYCN positive NB is poor, and there is no targeted drug for N-myc at present. This study aims to screen out hub genes closely related to MYCN, analyze the relationship between hub genes and NB microenvironment, and provide basis for molecular targeted therapy of MYCN positive NB.MethodsWe combined the microarray data of GSE45547 (n=649) and GSE49710 (n=498), screened the DEGs between MYCN positive (n=185) and MYCN negative NB (n=951), performed WGCNA, Lasso regression and Roc analyses on the merged matrix, and obtained the hub genes related to MYCN in the training group. We performed ssGSEA on the experimental group to calculate the infiltration level of 28 kinds of immune cells in each sample, compared the differences of immune cell infiltration between MYCN positive and MYCN negative group. The influences of hub genes on the distribution of each immune cell were also analyzed by ssGSEA. The expression differences of the three hub genes were verified in the E-MTAB-8248 cohort (n=223), and the correlation between hub genes and prognosis of NB was calculated by Kaplan-Meier method in GSE62564 (n=498) and the validation group. We also verified the expression differences of hub genes by qRT-PCR in SK-N-BE(2), SKNDZ, Kelly and SH-SY5Y cell lines.ResultsHere were 880 DEGs including 420 upregulated and 460 downregulated genes in MYCN positive NB in the training group. Overlap of the DEGs and WGCNA networks identified four shared genes, namely, ZNF695, CHEK1, C15ORF42 and EXO1, as candidate hub genes in MYCN positive NB. Three core genes, ZNF695, CHEK1 and C15ORF42, were finally identified by Lasso regression and Roc analyses. ZNF695, CHEK1 and C15ORF42 were highly expressed in MYCN positive NB tissues and cell lines. These three genes were closely related to the prognosis of children with NB. Except that Activated CD4 T cell and Type2 T helper cell increased, the infiltration levels of the other 26 cells decreased significantly in MYCN positive NB tissues. The infiltration levels of Type2 T helper cell and Activated CD4 T cell were also significantly positively correlated with the expression levels of the three hub genes.ConclusionZNF695, CHEK1 and C15ORF42 are highly expressed in MYCN positive NB, and their expression levels are negatively correlated with the prognosis of children with NB. The infiltration levels of Activated CD4 T cell and Type2 T helper cell increased in the microenvironment of MYCN positive NB and were significantly positively correlated with the expression levels of the three hub genes. The results of this study provide that ZNF695, CHEK1 and C15ORF42 may be potential prognostic markers and immunotherapy targets for MYCN positive NB.
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Affiliation(s)
- Ji Chen
- Department of General Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Mengjiao Sun
- Department of Hematology and Oncology, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Chuqin Chen
- Department of Hematology and Oncology, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Bin Jiang
- Department of General Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Bin Jiang, ; Yongjun Fang,
| | - Yongjun Fang
- Department of Hematology and Oncology, Children’s Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Bin Jiang, ; Yongjun Fang,
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A radiation resistance related index for biochemical recurrence and tumor immune environment in prostate cancer patients. Comput Biol Med 2022; 146:105711. [PMID: 35701253 DOI: 10.1016/j.compbiomed.2022.105711] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 05/08/2022] [Accepted: 06/04/2022] [Indexed: 11/20/2022]
Abstract
PURPOSE To establish and verify a novel radiation resistance related index for predicting biochemical recurrence and tumor immune environment in prostate cancer (PCa) patients. MATERIALS AND METHODS The transcriptome information of PCa were obtained from GEO and TCGA portal. We identified radiation resistance related genes (RRGs) between radioresistant and radiosensitive PCa cells. We conducted multivariate Cox analysis to construct a novel radiation resistance related index for predicting biochemical recurrence (BCR)-free survival (BCRFS). Internal and external validations were conducted. Preliminary experimental verifications were performed. RESULTS We identified 194 differentially expressed RRGs and three radiation resistance related molecular clusters for PCa. Moreover, we established a novel radiation resistance related index and succeeded in conducting internal and external validations. High-risk populations meant significantly worse BCRFS in training, testing and validating cohort. The area under receiver operating characteristic curve were 0.809, 0.698, and 0.712 in training, testing, and validating cohort. The immune microenvironment was significantly different between high and low-risk score patients. Preliminary experiment identified and validated three potential biomarkers related to radiation resistance (ZNF695, TM4SF19, CCDC3) of PCa. CONCLUSIONS This study successfully established and verified a novel radiation resistance related index, which had an excellent performance in predicting BCR and tumor immune microenvironment in patients with PCa.
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Feng D, Shi X, Zhang F, Xiong Q, Wei Q, Yang L. Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy. Front Immunol 2022; 13:839362. [PMID: 35280985 PMCID: PMC8908254 DOI: 10.3389/fimmu.2022.839362] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 02/07/2022] [Indexed: 02/05/2023] Open
Abstract
Background We aimed to construct and validate an energy metabolism-related gene prognostic index (EMRGPI) to predict biochemical recurrence (BCR) in patients undergoing radical prostatectomy. Methods We used Lasso and COX regression analysis to orchestrate the EMRGPI in the TCGA database, and the prognostic value of EMRGPI was further validated externally using the GSE46602. All analyses were conducted with R version 3.6.3 and its suitable packages. Results SDC1 and ADH1B were finally used to construct the risk formula. We classified the 430 tumor patients in the TCGA database into two groups, and patients in the high-risk group had a higher risk of BCR than those in the low-risk group (HR: 1.98, 95%CI: 1.18-3.32, p=0.01). Moreover, in the GSE46602, we confirmed that the BCR risk in the high-risk group was 3.86 times higher than that in the low-risk group (95%CI: 1.61-9.24, p=0.001). We found that patients in the high-risk group had significantly higher proportions of residual tumor, older age, and T stage. SDC1 and ADH1B were significantly expressed low in the normal tissues when compared to the tumor tissues, which were opposite at the protein level. The spearman analysis showed that EMRGPI was significantly associated with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score. In addition, the EMRGPI was positively associated with the 54 immune checkpoints, among which CD80, ADORA2A, CD160, and TNFRSF25 were significantly related to the BCR-free survival of PCa patients undergoing RP. Conclusions The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing radical prostatectomy.
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Affiliation(s)
- Dechao Feng
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Xu Shi
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Facai Zhang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiao Xiong
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiang Wei
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Lu Yang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
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Feng D, Shi X, Xiong Q, Zhang F, Li D, Yang L. A Gene Prognostic Index Associated With Epithelial-Mesenchymal Transition Predicting Biochemical Recurrence and Tumor Chemoresistance for Prostate Cancer. Front Oncol 2022; 11:805571. [PMID: 35096608 PMCID: PMC8790245 DOI: 10.3389/fonc.2021.805571] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 12/14/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND We aimed to establish a novel epithelial-mesenchymal transition (EMT)-related gene prognostic index (EMTGPI) associated with biochemical recurrence (BCR) and drug resistance for prostate cancer (PCa). METHODS We used Lasso and Cox regression analysis to establish the EMTGPI. All analyses were conducted with R version 3.6.3 and its suitable packages. RESULTS We established the EMTGPI based on SFRP4 and SPP1. Patients in high-risk group had 2.23 times of BCR risk than those in low-risk group (p = 0.003), as well as 2.36 times of metastasis risk (p = 0.053). In external validation, we detected similar diagnostic efficacy and prognostic value in terms of BCR free survival. For drug resistance, we observe moderately diagnostic accuracy of EMTGPI score (AUC: 0.804). We found that PDCD1LG2 (p = 0.04) and CD96 (p = 0.01) expressed higher in BCR patients compared with their counterpart. For TME analysis, we detected that CD8+ T cells and M1 macrophages expressed higher in BCR group. Moreover, stromal score (p = 0.003), immune score (p = 0.01), and estimate score (p = 0.003) were higher in BCR patients. We found that EMTGPI was significantly related to HAVCR2 (r: 0.34), CD96 (r: 0.26), CD47 (r: 0.22), KIR3DL1 (r: -0.21), KLRD1 (r: -0.21), and CD2 (r: 0.21). In addition, we observed that EMTGPI was significantly associated with M1 macrophages (r: 0.6), M2 macrophages (r: -0.33), monocytes (r: -0.18), neutrophils (r: -0.43), CD8+ T cells (r: 0.13), and dendritic cells (r: 0.37). PHA-793887 was the common drug sensitive to SPP1 and SFRP4, and PC3 and DU145 were the common PCa-related cell lines of SPP1, SFRP4, and PHA-793887. CONCLUSIONS We concluded that the EMTGPI score based on SFRP4 and SPP1 could be used to predict BCR for PCa patients. We confirmed the impact of immune evasion on the BCR process of PCa.
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Affiliation(s)
| | | | | | | | | | - Lu Yang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
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