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Lu Z, Pan Y, Wang S, Wu J, Miao C, Wang Z. Multi-omics and immunogenomics analysis revealed PFKFB3 as a targetable hallmark and mediates sunitinib resistance in papillary renal cell carcinoma: in silico study with laboratory verification. Eur J Med Res 2024; 29:236. [PMID: 38622715 PMCID: PMC11017615 DOI: 10.1186/s40001-024-01808-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 03/22/2024] [Indexed: 04/17/2024] Open
Abstract
Glycolysis-related metabolic reprogramming is a central hallmark of human cancers, especially in renal cell carcinoma. However, the regulatory function of glycolytic signature in papillary RCC has not been well elucidated. In the present study, the glycolysis-immune predictive signature was constructed and validated using WGCNA, glycolysis-immune clustering analysis. PPI network of DEGs was constructed and visualized. Functional enrichments and patients' overall survival were analyzed. QRT-PCR experiments were performed to detect hub genes' expression and distribution, siRNA technology was used to silence targeted genes; cell proliferation and migration assays were applied to evaluate the biological function. Glucose concentration, lactate secretion, and ATP production were measured. Glycolysis-Immune Related Prognostic Index (GIRPI) was constructed and combined analyzed with single-cell RNA-seq. High-GIRPI signature predicted significantly poorer outcomes and relevant clinical features of pRCC patients. Moreover, GIRPI also participated in several pathways, which affected tumor immune microenvironment and provided potential therapeutic strategy. As a key glycolysis regulator, PFKFB3 could promote renal cancer cell proliferation and migration in vitro. Blocking of PFKFB3 by selective inhibitor PFK-015 or glycolytic inhibitor 2-DG significantly restrained renal cancer cells' neoplastic potential. PFK-015 and sunitinib could synergistically inhibit pRCC cells proliferation. Glycolysis-Immune Risk Signature is closely associated with pRCC prognosis, progression, immune infiltration, and therapeutic response. PFKFB3 may serve as a pivotal glycolysis regulator and mediates Sunitinib resistance in pRCC patients.
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Affiliation(s)
- Zhongwen Lu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, No.300 Guangzhou Road, Nanjing, 210029, China
| | - Yongsheng Pan
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, No.300 Guangzhou Road, Nanjing, 210029, China
- Department of Urology, The Second Affiliated Hospital of Nantong University, Nantong, China
| | - Songbo Wang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, No.300 Guangzhou Road, Nanjing, 210029, China
| | - Jiajin Wu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, No.300 Guangzhou Road, Nanjing, 210029, China.
| | - Chenkui Miao
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, No.300 Guangzhou Road, Nanjing, 210029, China.
| | - Zengjun Wang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, No.300 Guangzhou Road, Nanjing, 210029, China.
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Wu X, Liu P, Wang Q, Sun L, Wang Y. A prognostic model established using bile acid genes to predict the immunity and survival of patients with gastrointestinal cancer. ENVIRONMENTAL TOXICOLOGY 2024. [PMID: 38606991 DOI: 10.1002/tox.24287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/13/2024] [Accepted: 03/31/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND The metabolism of abnormal bile acids (BAs) is implicated in the initiation and development of gastrointestinal (GI) cancer. However, there was a lack of research on the molecular mechanisms of BAs metabolism in GI. METHODS Genes involved in BAs metabolism were excavated from public databases of The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, and Molecular Signatures Database (MSigDB). ConsensusClusterPlus was used to classify molecular subtypes for GI. To develop a RiskScore model for predicting GI prognosis, univariate Cox analysis was performed on the genes in protein-protein interaction (PPI) network, followed by using Lasso regression and stepwise regression to refine the model and to determine the key prognostic genes. Tumor immune microenvironment in GI patients from different risk groups was assessed using the ESTIMATE algorithm and enrichment analysis. Reverse transcription-quantitative real-time PCR (RT-qPCR), Transwell assay, and wound healing assay were carried out to validate the expression and functions of the model genes. RESULTS This study defined three molecular subtypes (C1, C2, and C3). Specifically, C1 had the best prognosis, while C3 had the worst prognosis with high immune checkpoint gene expression levels and TIDE scores. We selected nine key genes (AXIN2, ATOH1, CHST13, PNMA2, GYG2, MAGEA3, SNCG, HEYL, and RASSF10) that significantly affected the prognosis of GI and used them to develop a RiskScore model accordingly. Combining the verification results from a nomogram, the prediction of the model was proven to be accurate. The high RiskScore group was significantly enriched in tumor and immune-related pathways. Compared with normal gastric mucosal epithelial cells, the mRNA levels of the nine genes were differential in the gastric cancer cells. Inhibition of PNMA2 suppressed migration and invasion of the cancer cells. CONCLUSION We distinguished three GI molecular subtypes with different prognosis based on the genes related to BAs metabolism and developed a RiskScore model, contributing to the diagnosis and treatment of patients with GI.
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Affiliation(s)
- Xin Wu
- Department of General Surgical Medicine, The First Medicine Center of PLA General Hospital, Beijing, China
| | - Peifa Liu
- Pathology Department, The First Medicine Center of PLA General Hospital, Beijing, China
| | - Qing Wang
- Department of General Surgical Medicine, The First Medicine Center of PLA General Hospital, Beijing, China
| | - Linde Sun
- Department of General Surgical Medicine, The First Medicine Center of PLA General Hospital, Beijing, China
| | - Yu Wang
- Department of General Surgical Medicine, The First Medicine Center of PLA General Hospital, Beijing, China
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Zhang X, Zeng B, Zhu H, Ma R, Yuan P, Chen Z, Su C, Liu Z, Yao X, Lawrence A, Liu Z, Zou J. Role of glycosphingolipid biosynthesis coregulators in malignant progression of thymoma. Int J Biol Sci 2023; 19:4442-4456. [PMID: 37781041 PMCID: PMC10535712 DOI: 10.7150/ijbs.83468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 08/14/2023] [Indexed: 10/03/2023] Open
Abstract
As the most common malignancy from mediastinum, the metabolic reprogramming of thymoma is important in its development. Nevertheless, the connection between the metabolic map and thymoma development is yet to be discovered. Thymoma was categorized into three subcategories by unsupervised clustering of molecular markers for metabolic pathway presentation in the TCGA dataset. Different genes and functions enriched were demonstrated through the utilization of metabolic Gene Ontology (GO) analysis. To identify the main contributors in the development of thymic malignancy, we utilized Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The prognosis of thymoma was evaluated by screening the essential pathways and genes using GSVA scores and machine learning classifiers. Furthermore, we integrated the transcriptomics findings with spectrum metabolomics investigation, detected through LC-MS/MS, in order to establish the essential controller network of metabolic reprogramming during thymoma progression. The thymoma prognosis is related to glycosphingolipid biosynthesis-lacto and neolacto series pathway, of what high B3GNT5 indicate poor survival. The investigation revealed that glycosphingolipid charts have a significant impact on metabolic dysfunction and could potentially serve as crucial targets in the clinical advancement of metabolic therapy.
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Affiliation(s)
- Xin Zhang
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Bo Zeng
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Haoshuai Zhu
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Rui Ma
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510655, China
| | - Ping Yuan
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510655, China
| | - Zhenguang Chen
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Chunhua Su
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Zhihao Liu
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Xiaojing Yao
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Aurora Lawrence
- School of Medicine, Stanford University, 450 Serra Mall, Stanford, CA 94305, USA
| | - Zhenguo Liu
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Jianyong Zou
- Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
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Caliskan A, Caliskan D, Rasbach L, Yu W, Dandekar T, Breitenbach T. Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learning. Comput Struct Biotechnol J 2023; 21:3293-3314. [PMID: 37333862 PMCID: PMC10276237 DOI: 10.1016/j.csbj.2023.06.002] [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: 02/18/2023] [Revised: 06/02/2023] [Accepted: 06/02/2023] [Indexed: 06/20/2023] Open
Abstract
Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.
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Lin F, Ke ZB, Chen H, Zheng WC, Dong RN, Cai H, Li XD, Wei Y, Zheng QS, Xue XY, Chen SH, Xu N. Integrative analysis developing and validating potential candidate biomarkers for cancer stemness features of pan-renal cell carcinoma. Cancer Invest 2023:1-17. [PMID: 37129517 DOI: 10.1080/07357907.2023.2209634] [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: 05/03/2023]
Abstract
In our study, 49 key genes significantly associated with renal cell carcinoma (RCC) stemness were obtained. Next, we developed a molecular prognostic signature associated with stemness features of pan-RCC. The difference in OS between high-risk and low-risk group was statistically significant (P < 0.05). The area under ROC curve for 1-years OS, 5-years OS and 10-years OS was 0.759, 0.712 and 0.918, respectively. The results of validation in TCGA cohort and ICGC cohort revealed the predictive capability of this signature. Further, we selected three genes and further validation showed that these three hub genes were potential hub biomarkers for pan-RCC stemness features.
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Affiliation(s)
- Fei Lin
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Zhi-Bin Ke
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Hang Chen
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Wen-Cai Zheng
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Ru-Nan Dong
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Hai Cai
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Xiao-Dong Li
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Yong Wei
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Qing-Shui Zheng
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Xue-Yi Xue
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Shao-Hao Chen
- Department of Urology, Urology Research Institute, 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
- Fujian Key Laboratory of Precision Medicine for Cancer, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
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Song T, He K, Ning J, Li W, Xu T, Yu W, Rao T, Cheng F. Evaluation of aliphatic acid metabolism in bladder cancer with the goal of guiding therapeutic treatment. Front Oncol 2022; 12:930038. [PMID: 36059672 PMCID: PMC9433665 DOI: 10.3389/fonc.2022.930038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 07/28/2022] [Indexed: 11/13/2022] Open
Abstract
Urothelial bladder cancer (BLCA) is a common internal malignancy with a poor prognosis. The re-programming of lipid metabolism is necessary for cancer cell growth, proliferation, angiogenesis and invasion. However, the role of aliphatic acid metabolism genes in bladder cancer patients has not been explored. The samples’ gene expression and clinicopathological data were obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Univariate, multivariate, and LASSO Cox regression were used to develop a BLCA prognostic model. GSVA was used to assess function, whereas pRRophetic was used to assess chemotherapeutic drug sensitivity. The twelve-gene signature may define the tumor immune milieu, according to the risk score model. We compared the expression of aliphatic acid metabolism genes in malignant and non-cancerous tissues and chose 90 with a false discovery rate of 0.05 for The Cancer Genome Atlas cohort. The prognostic risk score model can effectively predict BLCA OS. A nomogram including age, clinical T stage, gender, grade, pathological stage, and clinical M stage was developed as an independent BLCA prognostic predictor. The halfmaximal inhibitory concentration (IC50) was used to assess chemotherapeutic medication response. Sorafenib and Pyrimethamine were used to treat patients with low risk scores more sensitively than patients with high risk scores. Immunotherapy candidates with CMS1 exhibited higher risk ratings. The aliphatic acid prognostic risk score model can assess metabolic trends. Clinical stage and molecular subtype may be used to categorize individuals using the risk score.With this new paradigm, future cancer treatment and immunotherapy may be tailored to the patient’s exact requirements.
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Affiliation(s)
- Tianbao Song
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Kaixiang He
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jinzhuo Ning
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Wei Li
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Tao Xu
- Department of Urology, Huanggang Central Hospital, Huanggang, China
| | - Weimin Yu
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ting Rao
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
- *Correspondence: Fan Cheng, ; Ting Rao,
| | - Fan Cheng
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
- *Correspondence: Fan Cheng, ; Ting Rao,
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7
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Yu G, Liang B, Yin K, Zhan M, Gu X, Wang J, Song S, Liu Y, Yang Q, Ji T, Xu B. Identification of Metabolism-Related Gene-Based Subgroup in Prostate Cancer. Front Oncol 2022; 12:909066. [PMID: 35785167 PMCID: PMC9243363 DOI: 10.3389/fonc.2022.909066] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/19/2022] [Indexed: 12/28/2022] Open
Abstract
Prostate cancer is still the main male health problem in the world. The role of metabolism in the occurrence and development of prostate cancer is becoming more and more obvious, but it is not clear. Here we firstly identified a metabolism-related gene-based subgroup in prostate cancer. We used metabolism-related genes to divide prostate cancer patients from The Cancer Genome Atlas into different clinical benefit populations, which was verified in the International Cancer Genome Consortium. After that, we analyzed the metabolic and immunological mechanisms of clinical beneficiaries from the aspects of functional analysis of differentially expressed genes, gene set variation analysis, tumor purity, tumor microenvironment, copy number variations, single-nucleotide polymorphism, and tumor-specific neoantigens. We identified 56 significant genes for non-negative matrix factorization after survival-related univariate regression analysis and identified three subgroups. Patients in subgroup 2 had better overall survival, disease-free interval, progression-free interval, and disease-specific survival. Functional analysis indicated that differentially expressed genes in subgroup 2 were enriched in the xenobiotic metabolic process and regulation of cell development. Moreover, the metabolism and tumor purity of subgroup 2 were higher than those of subgroup 1 and subgroup 3, whereas the composition of immune cells of subgroup 2 was lower than that of subgroup 1 and subgroup 3. The expression of major immune genes, such as CCL2, CD274, CD276, CD4, CTLA4, CXCR4, IL1A, IL6, LAG3, TGFB1, TNFRSF4, TNFRSF9, and PDCD1LG2, in subgroup 2 was almost significantly lower than that in subgroup 1 and subgroup 3, which is consistent with the results of tumor purity analysis. Finally, we identified that subgroup 2 had lower copy number variations, single-nucleotide polymorphism, and neoantigen mutation. Our systematic study established a metabolism-related gene-based subgroup to predict outcomes of prostate cancer patients, which may contribute to individual prevention and treatment.
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Affiliation(s)
- Guopeng Yu
- Department of Urology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Bo Liang
- The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Keneng Yin
- 174 Clinical College, Anhui Medical University, Hefei, China
| | - Ming Zhan
- Department of Urology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xin Gu
- Department of Urology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jiangyi Wang
- Department of Urology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shangqing Song
- Department of Urology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yushan Liu
- Department of Urology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- *Correspondence: Bin Xu, ; Tianhai Ji, ; Qing Yang, ; Yushan Liu,
| | - Qing Yang
- Department of Urology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- *Correspondence: Bin Xu, ; Tianhai Ji, ; Qing Yang, ; Yushan Liu,
| | - Tianhai Ji
- 174 Clinical College, Anhui Medical University, Hefei, China
- Department of Pathology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- *Correspondence: Bin Xu, ; Tianhai Ji, ; Qing Yang, ; Yushan Liu,
| | - Bin Xu
- Department of Urology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- *Correspondence: Bin Xu, ; Tianhai Ji, ; Qing Yang, ; Yushan Liu,
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Safaei S, Sajed R, Saeednejad Zanjani L, Rahimi M, Fattahi F, Ensieh Kazemi-Sefat G, Razmi M, Dorafshan S, Eini L, Madjd Z, Ghods R. Overexpression of cytoplasmic dynamin 2 is associated with worse outcomes in patients with clear cell renal cell carcinoma. Cancer Biomark 2022; 35:27-45. [DOI: 10.3233/cbm-210514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND: Dynamin 2 (DNM2) involved in tumor progression in various malignancies. OBJECTIVE: For the first time, we evaluated DNM2 expression pattern, its association with clinicopathological characteristics and survival outcomes in RCC subtypes. METHODS: We evaluated the DNM2 expression pattern in RCC tissues as well as adjacent normal tissue using immunohistochemistry on tissue microarray (TMA) slides. RESULTS: Our findings revealed increased DNM2 expression in RCC samples rather than in adjacent normal tissues. The results indicated that there was a statistically significant difference between cytoplasmic expression of DNM2 among subtypes of RCC in terms of intensity of staining, percentage of positive tumor cells, and H-score (P= 0.024, 0.049, and 0.009, respectively). The analysis revealed that increased cytoplasmic expression of DNM2 in ccRCC is associated with worse OS (log rank: P= 0.045), DSS (P= 0.049), and PFS (P= 0.041). Furthermore, cytoplasmic expression of DNM2 was found as an independent prognostic factor affecting DSS and PFS in multivariate analysis. CONCLUSIONS: Our results indicated that DNM2 cytoplasmic expression is associated with tumor aggressiveness and poor outcomes. DNM2 could serve as a promising prognostic biomarker and therapeutic target in patients with ccRCC.
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Affiliation(s)
- Sadegh Safaei
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
- Oncopathology Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Roya Sajed
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
- Oncopathology Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | | | - Mandana Rahimi
- Hasheminejad Kidney Center, Pathology department, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Fahimeh Fattahi
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
- Oncopathology Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Golnaz Ensieh Kazemi-Sefat
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mahdieh Razmi
- Oncopathology Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Shima Dorafshan
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
- Oncopathology Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Leila Eini
- Oncopathology Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran
- Division of Histology, Department of Basic Science, Faculty of Veterinary Medicine, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Zahra Madjd
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
- Oncopathology Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Roya Ghods
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
- Oncopathology Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran
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Zhang YF, Ma C, Qian XP. Development and external validation of a novel nomogram for predicting cancer-specific survival in patients with ascending colon adenocarcinoma after surgery: a population-based study. World J Surg Oncol 2022; 20:126. [PMID: 35439983 PMCID: PMC9020108 DOI: 10.1186/s12957-022-02576-4] [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: 12/25/2021] [Accepted: 03/17/2022] [Indexed: 11/23/2022] Open
Abstract
Background This study aimed to develop and validate a novel nomogram to predict the cancer-specific survival (CSS) of patients with ascending colon adenocarcinoma after surgery. Methods Patients with ascending colon adenocarcinoma were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database from 1973 to 2015 and randomly divided into a training set (5930) and a validation set (2540). The cut-off values for age, tumour size and lymph node ratio (LNR) were calculated via X-tile software. In the training set, independent prognostic factors were identified using univariate and multivariate Cox analyses, and a nomogram incorporating these factors was subsequently built. Data from the validation set were used to assess the reliability and accuracy of the nomogram and then compared with the 8th edition of the American Joint Committee on Cancer (AJCC) tumour-node-metastasis (TNM) staging system. Furthermore, external validation was performed from a single institution in China. Results A total of 8470 patients were enrolled from the SEER database, 5930 patients were allocated to the training set, 2540 were allocated to the internal validation set and a separate set of 473 patients was allocated to the external validation set. The optimal cut-off values of age, tumour size and lymph node ratio were 73 and 85, 33 and 75 and 4.9 and 32.8, respectively. Univariate and multivariate Cox multivariate regression revealed that age, AJCC 8th edition T, N and M stage, carcinoembryonic antigen (CEA), tumour differentiation, chemotherapy, perineural invasion and LNR were independent risk factors for patient CSS. The nomogram showed good predictive ability, as indicated by discriminative ability and calibration, with C statistics of 0.835 (95% CI, 0.823–0.847) and 0.848 (95% CI, 0.830–0.866) in the training and validation sets and 0.732 (95% CI, 0.664–0.799) in the external validation set. The nomogram showed favourable discrimination and calibration abilities and performed better than the AJCC TNM staging system. Conclusions A novel validated nomogram could effectively predict patients with ascending colon adenocarcinoma after surgery, and this predictive power may guide clinicians in accurate prognostic judgement.
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Affiliation(s)
- Yi Fan Zhang
- Department of Radiotherapy, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou, 221000, China.,Comprehensive Cancer Center, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, 210000, China
| | - Cheng Ma
- Department of Gastrointestinal Surgery, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou, 221000, China
| | - Xiao Ping Qian
- Comprehensive Cancer Center, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, 210000, China. .,Comprehensive Cancer Center, Nanjing Drum Tower Hospital, Medical School of Nanjing University, Clinical Cancer Institute of Nanjing University, Nanjing, 210000, China.
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10
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Meng M, Lan T, Tian D, Qin Z, Li Y, Li J, Cao H. Integrative Bioinformatics Analysis Demonstrates the Prognostic Value of Chromatin Accessibility Biomarkers in Clear Cell Renal Cell Carcinoma. Front Oncol 2022; 11:814396. [PMID: 34993155 PMCID: PMC8724435 DOI: 10.3389/fonc.2021.814396] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 11/24/2021] [Indexed: 01/22/2023] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) accounts for 75%–85% of renal cell carcinoma (RCC) and has a poor 5-year survival rate. In recent years, medical advancement has promoted the understanding of the histopathological and molecular characterization of ccRCC; however, the carcinogenesis and molecular mechanisms of ccRCC remain unclear. Chromatin accessibility is an essential determinant of cellular phenotype. This study aimed to explore the potential role of chromatin accessibility in the development and progression of ccRCC. By the combination of open-access genome-wide chromatin accessibility profiles and gene expression profiles in ccRCC, we obtained a total of 13,474 crucial peaks, corresponding to 5,120 crucial genes and 9,185 differentially expressed genes. Moreover, two potential function modules (P2 and G4) that contained 129 upregulated genes were identified via the weighted gene co-expression network analysis (WGCNA). Furthermore, we obtained five independent predictors (FSCN1, SLC17A9, ANKRD13B, ADCY2, and MAPT), and a prognostic model was established based on these genes through the least absolute shrinkage and selection operator-proportional hazards model (LASSO-Cox) analysis. This model can stratify the ccRCC samples into a high-risk and a low-risk group, from which the patients have distinct prognosis. Further analysis demonstrated a completely different immune cell infiltration pattern between these two risk groups. This study also suggested that mast cell resting is associated with the prognosis of ccRCC and could be a target of immunotherapy. Overall, this study indicated that chromatin accessibility plays an essential role in ccRCC. The five prognostic chromatin accessibility biomarkers and the prognostic immune cells can provide a new direction for the treatment of ccRCC.
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Affiliation(s)
- Meng Meng
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,National Supercomputer Center in Guangzhou, Sun Yat-sen University, Guangzhou, China
| | - Tianjun Lan
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Oral & Maxillofacial Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Duanqing Tian
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zeman Qin
- Department of Stomatology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yu Li
- Department of Laboratory Medicine, Peking University Shenzhen Hospital, Shenzhen, China
| | - Jinsong Li
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Oral & Maxillofacial Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Haotian Cao
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Oral & Maxillofacial Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
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11
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Mohamed Abd-El-Halim Y, El Kaoutari A, Silvy F, Rubis M, Bigonnet M, Roques J, Cros J, Nicolle R, Iovanna J, Dusetti N, Mas E. A glycosyltransferase gene signature to detect pancreatic ductal adenocarcinoma patients with poor prognosis. EBioMedicine 2021; 71:103541. [PMID: 34425307 PMCID: PMC8379629 DOI: 10.1016/j.ebiom.2021.103541] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 07/26/2021] [Accepted: 07/29/2021] [Indexed: 12/12/2022] Open
Abstract
Background Pancreatic ductal adenocarcinoma (PDAC) is characterized by an important heterogeneity, reflected by different clinical outcomes and chemoresistance. During carcinogenesis, tumor cells display aberrant glycosylated structures, synthetized by deregulated glycosyltransferases, supporting the tumor progression. In this study, we aimed to determine whether PDAC could be stratified through their glycosyltransferase expression profiles better than the current binary classification (basal-like and classical) in order to improve detection of patients with poor prognosis. Methods Bioinformatic analysis of 169 glycosyltransferase RNA sequencing data were performed for 74 patient-derived xenografts (PDX) of resected and unresectable tumors. The Australian cohort of International Cancer Genome Consortium and the microarray dataset from Puleo patient's cohort were used as independent validation datasets. Findings New PDAC stratification based on glycosyltransferase expression profile allowed to distinguish different groups of patients with distinct clinical outcome (p-value = 0.007). A combination of 19 glycosyltransferases differentially expressed in PDX defined a glyco-signature, whose prognostic value was validated on datasets including resected whole tumor tissues. The glyco-signature was able to discriminate three clusters of PDAC patients on the validation cohorts, two clusters displaying a short overall survival compared to one cluster having a better prognosis. Both poor prognostic clusters having different glyco-profiles in Puleo patient's cohort were correlated with stroma activated or desmoplastic subtypes corresponding to distinct microenvironment features (p-value < 0.0001). Besides, differential expression and enrichment analyses revealed deregulated functional pathways specific to different clusters. Interpretation This study identifies a glyco-signature relevant for a prognostic use, potentially applicable to resected and unresectable PDAC. Furthermore, it provides new potential therapeutic targets. Funding This work was supported by INCa (Grants number 2018-078 and 2018-079), Fondation ARC (Grant number ARCPJA32020070002326), Cancéropôle PACA, DGOS (labelization SIRIC, Grant number 6038), Amidex Foundation and Ligue Nationale Contre le Cancer and by institutional fundings from INSERM and the Aix-Marseille Université.
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Affiliation(s)
- Yousra Mohamed Abd-El-Halim
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France
| | - Abdessamad El Kaoutari
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France
| | - Françoise Silvy
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France
| | - Marion Rubis
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France
| | - Martin Bigonnet
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France
| | - Julie Roques
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France
| | - Jérôme Cros
- Department of Pathology, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, France
| | - Rémy Nicolle
- Programme Cartes d'Identité des Tumeurs (CIT), Ligue Nationale Contre Le Cancer, Paris, France
| | - Juan Iovanna
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France
| | - Nelson Dusetti
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France.
| | - Eric Mas
- Cancer Research Center of Marseille, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France.
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12
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Liu B, Li F, Liu M, Xu Z, Gao B, Wang Y, Zhou H. Prognostic Roles of Phosphofructokinase Platelet in Clear Cell Renal Cell Carcinoma and Correlation with Immune Infiltration. Int J Gen Med 2021; 14:3645-3658. [PMID: 34321910 PMCID: PMC8312753 DOI: 10.2147/ijgm.s321337] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Accepted: 07/08/2021] [Indexed: 12/24/2022] Open
Abstract
Background Abnormal expression of phosphofructokinase platelet (PFKP) has been reported in various cancer types. However, the role of PFKP in clear cell renal cell carcinoma (ccRCC) remains unclear. Methods In this study, the PFKP expression levels in various cancers were systemically described by integrating multiple kinds of publicly available databases. The relationship between PFKP expression and clinical prognosis of ccRCC patients was analyzed based on the TCGA database. Furthermore, PFKP-related genes and the top 10 hub genes were identified. The enrichment analysis, PPI network, and the relationship between PFKP and tumor-infiltrating immune cells were conducted to explore why PFKP was associated with clinical outcomes in ccRCC patients. Results PFKP was significantly highly expressed in kidney cancer, especially in ccRCC. Moreover, patients with low expression of PFKP were correlated with poor 5-year and 10-year overall survival (OS) (P < 0.05). Low PFKP expression was a risk factor associated with decreased OS in subgroups including males, females, grade 3–4, and stage III–IV (all P < 0.05). GO and KEGG enrichment analyses showed that 10 hub genes were mainly enriched in the tumor immune response. Finally, PFKP expression level was highly correlated with the infiltration of B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell. Conclusion In short, our findings suggested that PFKP is highly expressed in ccRCC significantly and facilitated tumor immune response which in turn associated with a good prognosis.
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Affiliation(s)
- Bin Liu
- Department of Urology, the First Hospital of Jilin University, Changchun, 130021, Jilin, People's Republic of China
| | - Faping Li
- Department of Urology, the First Hospital of Jilin University, Changchun, 130021, Jilin, People's Republic of China
| | - Mingdi Liu
- Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun, 130021, Jilin, People's Republic of China
| | - Zhixiang Xu
- Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun, 130021, Jilin, People's Republic of China
| | - Baoshan Gao
- Department of Urology, the First Hospital of Jilin University, Changchun, 130021, Jilin, People's Republic of China
| | - Yishu Wang
- Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun, 130021, Jilin, People's Republic of China
| | - Honglan Zhou
- Department of Urology, the First Hospital of Jilin University, Changchun, 130021, Jilin, People's Republic of China
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13
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Guo H, Li Y, Liu Y, Chen L, Gao Z, Zhang L, Zhou N, Guo H, Shi B. Prognostic Role of the Ubiquitin Proteasome System in Clear Cell Renal Cell Carcinoma: A Bioinformatic Perspective. J Cancer 2021; 12:4134-4147. [PMID: 34093816 PMCID: PMC8176417 DOI: 10.7150/jca.53760] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 04/24/2021] [Indexed: 12/24/2022] Open
Abstract
Background: Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the urinary system. The ubiquitin proteasome system (UPS) plays an important role in the generation, metabolism and survival of tumor. We are aimed to make a comprehensive exploration of the UPS's role in ccRCC with bioinformatic tools, which may contribute to the understanding of UPS in ccRCC, and give insight for further research. Methods: The UPS-related genes (UPSs) were collected by an integrative approach. The expression and clinical data were downloaded from TCGA database. R soft was used to perform the differentially expressed UPSs analysis, functional enrichment analysis. We also estimated prognostic value of each UPS with the help of GEPIA database. Two predicting models were constructed with the differentially expressed UPSs and prognosis-related genes, respectively. The correlations of risk score with clinical characteristics were also evaluated. Data of GSE29609 cohort were obtained from GEO database to validate the prognostic models. Results: We finally identified 91 differentially expressed UPSs, 48 prognosis related genes among them, and constructed a prognostic model with 18 UPSs successfully, the AUC was 0.760. With the help of GEPIA, we found 391 prognosis-related UPSs, accounting for 57.84% of all UPSs. Another prognostic model was constructed with 28 prognosis-related genes of them, and with a better AUC of 0.825. Additionally, our models can also stratify patients into high and low risk groups accurately in GSE29609 cohort. Similar prognostic values of our models were observed in the validated GSE29609 cohort. Conclusions: UPS is dysregulated in ccRCC. UPS related genes have significant prognostic value in ccRCC. Models constructed with UPSs are effective and applicable. An abnormal ubiquitin proteasome system should play an important role in ccRCC and be worthy of further study.
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Affiliation(s)
- Hongda Guo
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
| | - Yan Li
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
| | - Yaxiao Liu
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
| | - Lipeng Chen
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
| | - Zhengdong Gao
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
| | - Lekai Zhang
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
| | - Nan Zhou
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
| | - Hu Guo
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
| | - Benkang Shi
- Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, China.,Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Jinan, P.R. China
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14
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Chu G, Xu T, Zhu G, Liu S, Niu H, Zhang M. Identification of a Novel Protein-Based Signature to Improve Prognosis Prediction in Renal Clear Cell Carcinoma. Front Mol Biosci 2021; 8:623120. [PMID: 33842538 PMCID: PMC8027127 DOI: 10.3389/fmolb.2021.623120] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 03/08/2021] [Indexed: 12/16/2022] Open
Abstract
Background Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney cancer, and its incidence and mortality are not optimistic. It is well known that tumor-related protein markers play an important role in cancer detection, prognosis prediction, or treatment selection, such as carcinoembryonic antigen (CEA), programmed cell death 1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and cytotoxic T lymphocyte antigen 4 (CTLA-4), so a comprehensive analysis was performed in this study to explore the prognostic value of protein expression in patients with ccRCC. Materials and Methods Protein expression data were obtained from The Cancer Proteome Atlas (TCPA), and clinical information were downloaded from The Cancer Genome Atlas (TCGA). We selected 445 patients with complete information and then separated them into a training set and testing set. We performed univariate, least absolute shrinkage and selection operator (LASSO) Cox analyses to find prognosis-related proteins (PRPs) and constructed a protein signature. Then, we used stratified analysis to fully verify the prognostic significance of the prognostic-related protein signature score (PRPscore). Besides, we also explored the differences in immunotherapy response and immune cell infiltration level in high and low score groups. The consensus clustering analysis was also performed to identify potential cancer subgroups. Results From the training set, a total of 233 PRPs were selected, and a seven-protein signature was constructed, including ACC1, AR, MAPK, PDK1, PEA15, SYK, and BRAF. Based on the PRPscore, patients could be divided into two groups with significantly different overall survival rates. Univariate and multivariate Cox regression analyses proved that this signature was an independent prognostic factor for patients (P < 0.001). Moreover, the signature showed a high ability to distinguish prognostic outcomes among subgroups, and the low score group had a better prognosis (P < 0.001) and better immunotherapy response (P = 0.003) than the high score group. Conclusion We constructed a novel protein signature with robust predictive power and high clinical value. This will help to guide the disease management and individualized treatment of ccRCC patients.
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Affiliation(s)
- Guangdi Chu
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Ting Xu
- Department of Geratology, The 971th Hospital of PLA Navy, Qingdao, China
| | - Guanqun Zhu
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Shuaihong Liu
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Haitao Niu
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Mingxin Zhang
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
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15
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Czyzyk-Krzeska MF, Landero Figueroa JA, Gulati S, Cunningham JT, Meller J, ShamsaeI B, Vemuri B, Plas DR. Molecular and Metabolic Subtypes in Sporadic and Inherited Clear Cell Renal Cell Carcinoma. Genes (Basel) 2021; 12:genes12030388. [PMID: 33803184 PMCID: PMC7999481 DOI: 10.3390/genes12030388] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/02/2021] [Accepted: 03/04/2021] [Indexed: 01/18/2023] Open
Abstract
The promise of personalized medicine is a therapeutic advance where tumor signatures obtained from different omics platforms, such as genomics, transcriptomics, proteomics, and metabolomics, in addition to environmental factors including metals and metalloids, are used to guide the treatments. Clear cell renal carcinoma (ccRCC), the most common type of kidney cancer, can be sporadic (frequently) or genetic (rare), both characterized by loss of the von Hippel-Lindau (VHL) gene that controls hypoxia inducible factors. Recently, several genomic subtypes were identified with different prognoses. Transcriptomics, proteomics, metabolomics and metallomic data converge on altered metabolism as the principal feature of the disease. However, in view of multiple biochemical alterations and high level of tumor heterogeneity, identification of clearly defined subtypes is necessary for further improvement of treatments. In the future, single-cell combined multi-omics approaches will be the next generation of analyses gaining deeper insights into ccRCC progression and allowing for design of specific signatures, with better prognostic/predictive clinical applications.
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Affiliation(s)
- Maria F. Czyzyk-Krzeska
- Department of Cancer Biology, University of Cincinnati, Cincinnati, OH 45267, USA; (J.T.C.); (B.V.); (D.R.P.)
- Department of Veterans Affairs, Cincinnati Veteran Affairs Medical Center, Cincinnati, OH 45220, USA
- Department of Pharmacology and System Biology, College of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA; (J.A.L.F.); (J.M.)
- Correspondence:
| | - Julio A. Landero Figueroa
- Department of Pharmacology and System Biology, College of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA; (J.A.L.F.); (J.M.)
- Agilent Metallomics Center of the Americas, Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Shuchi Gulati
- Division of Hematology and Oncology, Department of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA;
| | - John T. Cunningham
- Department of Cancer Biology, University of Cincinnati, Cincinnati, OH 45267, USA; (J.T.C.); (B.V.); (D.R.P.)
| | - Jarek Meller
- Department of Pharmacology and System Biology, College of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA; (J.A.L.F.); (J.M.)
- Department of Biomedical Informatics, University of Cincinnati, Cincinnati, OH 45267, USA
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH 45267, USA;
- Department of Electrical Engineering and Computer Science, College of Engineering and Applied Sciences, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Behrouz ShamsaeI
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH 45267, USA;
| | - Bhargav Vemuri
- Department of Cancer Biology, University of Cincinnati, Cincinnati, OH 45267, USA; (J.T.C.); (B.V.); (D.R.P.)
| | - David R. Plas
- Department of Cancer Biology, University of Cincinnati, Cincinnati, OH 45267, USA; (J.T.C.); (B.V.); (D.R.P.)
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