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Cui M, Wu H, An Y, Liu Y, Wei L, Qi X. Identification of important modules and biomarkers in diabetic cardiomyopathy based on WGCNA and LASSO analysis. Front Endocrinol (Lausanne) 2024; 15:1185062. [PMID: 38469146 PMCID: PMC10926887 DOI: 10.3389/fendo.2024.1185062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 01/25/2024] [Indexed: 03/13/2024] Open
Abstract
Background Diabetic cardiomyopathy (DCM) lacks specific and sensitive biomarkers, and its diagnosis remains a challenge. Therefore, there is an urgent need to develop useful biomarkers to help diagnose and evaluate the prognosis of DCM. This study aims to find specific diagnostic markers for diabetic cardiomyopathy. Methods Two datasets (GSE106180 and GSE161827) from the GEO database were integrated to identify differentially expressed genes (DEGs) between control and type 2 diabetic cardiomyopathy. We assessed the infiltration of immune cells and used weighted coexpression network analysis (WGCNA) to construct the gene coexpression network. Then we performed a clustering analysis. Finally, a diagnostic model was built by the least absolute shrinkage and selection operator (LASSO). Results A total of 3066 DEGs in the GSE106180 and GSE161827 datasets. There were differences in immune cell infiltration. According to gene significance (GS) > 0.2 and module membership (MM) > 0.8, 41 yellow Module genes and 1474 turquoise Module genes were selected. Hub genes were mainly related to the "proteasomal protein catabolic process", "mitochondrial matrix" and "protein processing in endoplasmic reticulum" pathways. LASSO was used to construct a diagnostic model composed of OXCT1, CACNA2D2, BCL7B, EGLN3, GABARAP, and ACADSB and verified it in the GSE163060 and GSE175988 datasets with AUCs of 0.9333 (95% CI: 0.7801-1) and 0.96 (95% CI: 0.8861-1), respectively. H9C2 cells were verified, and the results were similar to the bioinformatics analysis. Conclusion We constructed a diagnostic model of DCM, and OXCT1, CACNA2D2, BCL7B, EGLN3, GABARAP, and ACADSB were potential biomarkers, which may provide new insights for improving the ability of early diagnosis and treatment of diabetic cardiomyopathy.
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Affiliation(s)
- Min Cui
- School of Medicine, Nankai University, Tianjin, China
| | - Hao Wu
- School of Medicine, Nankai University, Tianjin, China
- Department of Cardiology, Tianjin Union Medical Center, Tianjin, China
| | - Yajuan An
- School of Graduate Studies, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yue Liu
- School of Medicine, Nankai University, Tianjin, China
- Department of Cardiology, Tianjin Union Medical Center, Tianjin, China
| | - Liping Wei
- School of Medicine, Nankai University, Tianjin, China
- Department of Cardiology, Tianjin Union Medical Center, Tianjin, China
| | - Xin Qi
- School of Medicine, Nankai University, Tianjin, China
- Department of Cardiology, Tianjin Union Medical Center, Tianjin, China
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Wu Y, Chen S, Yang X, Sato K, Lal P, Wang Y, Shinkle AT, Wendl MC, Primeau TM, Zhao Y, Gould A, Sun H, Mudd JL, Hoog J, Mashl RJ, Wyczalkowski MA, Mo CK, Liu R, Herndon JM, Davies SR, Liu D, Ding X, Evrard YA, Welm BE, Lum D, Koh MY, Welm AL, Chuang JH, Moscow JA, Meric-Bernstam F, Govindan R, Li S, Hsieh J, Fields RC, Lim KH, Ma CX, Zhang H, Ding L, Chen F. Combining the Tyrosine Kinase Inhibitor Cabozantinib and the mTORC1/2 Inhibitor Sapanisertib Blocks ERK Pathway Activity and Suppresses Tumor Growth in Renal Cell Carcinoma. Cancer Res 2023; 83:4161-4178. [PMID: 38098449 PMCID: PMC10722140 DOI: 10.1158/0008-5472.can-23-0604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 07/17/2023] [Accepted: 09/25/2023] [Indexed: 12/18/2023]
Abstract
Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs. SIGNIFICANCE The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors.
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Affiliation(s)
- Yige Wu
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - Siqi Chen
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - Xiaolu Yang
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Kazuhito Sato
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - Preet Lal
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Yuefan Wang
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Andrew T. Shinkle
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Michael C. Wendl
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri
- McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri
| | - Tina M. Primeau
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Yanyan Zhao
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Alanna Gould
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Hua Sun
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - Jacqueline L. Mudd
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Jeremy Hoog
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - R. Jay Mashl
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - Matthew A. Wyczalkowski
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - Chia-Kuei Mo
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - Ruiyang Liu
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - John M. Herndon
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri
- Department of Surgery, Washington University in St. Louis, St. Louis, Missouri
| | - Sherri R. Davies
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Di Liu
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Xi Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Yvonne A. Evrard
- Frederick National Laboratory for Cancer Research, Frederick, Maryland
| | - Bryan E. Welm
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
| | - David Lum
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
| | - Mei Yee Koh
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
| | - Alana L. Welm
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
| | - Jeffrey H. Chuang
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut
| | - Jeffrey A. Moscow
- Investigational Drug Branch, National Cancer Institute, Bethesda, Maryland
| | | | - Ramaswamy Govindan
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri
| | - Shunqiang Li
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri
| | - James Hsieh
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Ryan C. Fields
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri
| | - Kian-Huat Lim
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri
| | - Cynthia X. Ma
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Li Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri
| | - Feng Chen
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri
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Li Y, Sundquist K, Vats S, Hong MG, Wang X, Chen Y, Hedelius A, Saal LH, Sundquist J, Memon AA. Mitochondrial heteroplasmic shifts reveal a positive selection of breast cancer. J Transl Med 2023; 21:696. [PMID: 37798736 PMCID: PMC10557196 DOI: 10.1186/s12967-023-04534-4] [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: 06/26/2023] [Accepted: 09/19/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND Breast cancer is, despite screening, not always detected early enough and is together with other tumor types known to shed genetic information in circulation. Unlike single-copy nuclear DNA, mitochondrial DNA (mtDNA) copies range from 100s to 10,000s per cell, thus providing a potentially alternative to identify potential missing cancer information in circulation at an early stage. METHODS To characterize mitochondrial mutation landscapes in breast cancer, whole mtDNA sequencing and bioinformatics analyses were performed on 86 breast cancer biopsies and 50 available matched baseline cancer-free whole blood samples from the same individuals, selected from a cohort of middle-aged women in Sweden. To determine whether the mutations can be detected in blood plasma prior to cancer diagnosis, we further designed a nested case-control study (n = 663) and validated the shortlisted mutations using droplet digital PCR. RESULTS We detected different mutation landscapes between biopsies and matched whole blood samples. Compared to whole blood samples, mtDNA from biopsies had higher heteroplasmic mutations in the D-loop region (P = 0.02), RNR2 (P = 0.005), COX1 (P = 0.037) and CYTB (P = 0.006). Furthermore, the germline mtDNA mutations had higher heteroplasmy level than the lost (P = 0.002) and de novo mutations (P = 0.04). The nonsynonymous to synonymous substitution ratio (dN/dS) was higher for the heteroplasmic mutations (P = 7.25 × 10-12) than that for the homoplasmic mutations, but the de novo (P = 0.06) and lost mutations (P = 0.03) had lower dN/dS than the germline mutations. Interestingly, we found that the critical regions for mitochondrial transcription: MT-HSP1 (odds ratio [OR]: 21.41), MT-TFH (OR: 7.70) and MT-TAS2 (OR: 3.62), had significantly higher heteroplasmic mutations than the rest of the D-loop sub-regions. Finally, we found that the presence of mt.16093T > C mutation increases 67% risk of developing breast cancer. CONCLUSIONS Our findings show that mitochondrial genetic landscape changes during cancer pathogenesis and positive selection of mtDNA heteroplasmic mutations in breast cancer. Most importantly, the mitochondrial mutations identified in biopsies can be traced back in matched plasma samples and could potentially be used as early breast cancer diagnostic biomarkers.
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Affiliation(s)
- Yanni Li
- Center for Primary Health Care Research, Lund University/Region Skåne, Malmö, Sweden.
- Center for Primary Health Care Research Wallenberg Laboratory, Skåne University Hospital, 5th floor, Inga Marie Nilssons gata 53, S-205 02, Malmö, Sweden.
| | - Kristina Sundquist
- Center for Primary Health Care Research, Lund University/Region Skåne, Malmö, Sweden
- Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Functional Pathology, Center for Community-Based Healthcare Research and Education (CoHRE), School of Medicine, Shimane University, Matsue, Japan
| | - Sakshi Vats
- Center for Primary Health Care Research, Lund University/Region Skåne, Malmö, Sweden
| | - Mun-Gwan Hong
- Science for Life Laboratory, Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Stockholm University, Solna, Sweden
| | - Xiao Wang
- Center for Primary Health Care Research, Lund University/Region Skåne, Malmö, Sweden
| | - Yilun Chen
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, Medicon Village, Lund, Sweden
| | - Anna Hedelius
- Center for Primary Health Care Research, Lund University/Region Skåne, Malmö, Sweden
| | - Lao H Saal
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, Medicon Village, Lund, Sweden
| | - Jan Sundquist
- Center for Primary Health Care Research, Lund University/Region Skåne, Malmö, Sweden
- Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Functional Pathology, Center for Community-Based Healthcare Research and Education (CoHRE), School of Medicine, Shimane University, Matsue, Japan
| | - Ashfaque A Memon
- Center for Primary Health Care Research, Lund University/Region Skåne, Malmö, Sweden
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Wu X, Li F, Xie W, Gong B, Fu B, Chen W, Zhou L, Luo L. A novel oxidative stress-related genes signature associated with clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma. Front Oncol 2023; 13:1184841. [PMID: 37601683 PMCID: PMC10435754 DOI: 10.3389/fonc.2023.1184841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 06/26/2023] [Indexed: 08/22/2023] Open
Abstract
Background Oxidative stress plays a significant role in the tumorigenesis and progression of tumors. We aimed to develop a prognostic signature using oxidative stress-related genes (ORGs) to predict clinical outcome and provide light on the immunotherapy responses of clear cell renal cell carcinoma (ccRCC). Methods The information of ccRCC patients were collected from the TCGA and the E-MTAB-1980 datasets. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) were conducted to screen out overall survival (OS)-related genes. Then, an ORGs risk signature was built by multivariate Cox regression analyses. The performance of the risk signature was evaluated with Kaplan-Meier (K-M) survival. The ssGSEA and CIBERSORT algorithms were performed to evaluate immune infiltration status. Finally, immunotherapy responses was analyzed based on expression of several immune checkpoints. Results A prognostic 9-gene signature with ABCB1, AGER, E2F1, FOXM1, HADH, ISG15, KCNMA1, PLG, and TEK. The patients in the high risk group had apparently poor survival (TCGA: p < 0.001; E-MTAB-1980: p < 0.001). The AUC of the signature was 0.81 at 1 year, 0.76 at 3 years, and 0.78 at 5 years in the TCGA, respectively, and was 0.8 at 1 year, 0.82 at 3 years, and 0.83 at 5 years in the E-MTAB-1980, respectively. Independent prognostic analysis proved the stable clinical prognostic value of the signature (TCGA cohort: HR = 1.188, 95% CI =1.142-1.236, p < 0.001; E-MTAB-1980 cohort: HR =1.877, 95% CI= 1.377-2.588, p < 0.001). Clinical features correlation analysis proved that patients in the high risk group were more likely to have a larger range of clinical tumor progression. The ssGSEA and CIBERSORT analysis indicated that immune infiltration status were significantly different between two risk groups. Finally, we found that patients in the high risk group tended to respond more actively to immunotherapy. Conclusion We developed a robust prognostic signature based on ORGs, which may contribute to predict survival and guide personalize immunotherapy of individuals with ccRCC.
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Affiliation(s)
- Xin Wu
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Fenghua Li
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Wenjie Xie
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Binbin Gong
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Bin Fu
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Weimin Chen
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Libo Zhou
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Lianmin Luo
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
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Li J, Wang S, Chi X, He Q, Tao C, Ding Y, Wang J, Zhao J, Wang W. Identification of heterogeneous subtypes and a prognostic model for gliomas based on mitochondrial dysfunction and oxidative stress-related genes. Front Immunol 2023; 14:1183475. [PMID: 37334354 PMCID: PMC10272431 DOI: 10.3389/fimmu.2023.1183475] [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: 03/10/2023] [Accepted: 05/22/2023] [Indexed: 06/20/2023] Open
Abstract
Objective Mitochondrial dysfunction and oxidative stress are known to involved in tumor occurrence and progression. This study aimed to explore the molecular subtypes of lower-grade gliomas (LGGs) based on oxidative stress-related and mitochondrial-related genes (OMRGs) and construct a prognostic model for predicting prognosis and therapeutic response in LGG patients. Methods A total of 223 OMRGs were identified by the overlap of oxidative stress-related genes (ORGs) and mitochondrial-related genes (MRGs). Using consensus clustering analysis, we identified molecular subtypes of LGG samples from TCGA database and confirmed the differentially expressed genes (DEGs) between clusters. We constructed a risk score model using LASSO regression and analyzed the immune-related profiles and drug sensitivity of different risk groups. The prognostic role of the risk score was confirmed using Cox regression and Kaplan-Meier curves, and a nomogram model was constructed to predict OS rates. We validated the prognostic role of OMRG-related risk score in three external datasets. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) staining confirmed the expression of selected genes. Furthermore, wound healing and transwell assays were performed to confirm the gene function in glioma. Results We identified two OMRG-related clusters and cluster 1 was significantly associated with poor outcomes (P<0.001). The mutant frequencies of IDH were significantly lower in cluster 1 (P<0.05). We found that the OMRG-related risk scores were significantly correlated to the levels of immune infiltration and immune checkpoint expression. High-risk samples were more sensitive to most chemotherapeutic agents. We identified the prognostic role of OMRG-related risk score in LGG patients (HR=2.665, 95%CI=1.626-4.369, P<0.001) and observed that patients with high-risk scores were significantly associated with poor prognosis (P<0.001). We validated our findings in three external datasets. The results of qRT-PCR and IHC staining verified the expression levels of the selected genes. The functional experiments showed a significant decrease in the migration of glioma after knockdown of SCNN1B. Conclusion We identified two molecular subtypes and constructed a prognostic model, which provided a novel insight into the potential biological function and prognostic significance of mitochondrial dysfunction and oxidative stress in LGG. Our study might help in the development of more precise treatments for gliomas.
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Affiliation(s)
- Junsheng Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
| | - Siyu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiaojing Chi
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Qiheng He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
| | - Chuming Tao
- Department of Neurosurgery, Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yaowei Ding
- Department of Clinical Diagnosis, Laboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jia Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
| | - Jizong Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
- Savaid Medical School, University of the Chinese Academy of Sciences, Beijing, China
| | - Wen Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing, China
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Cui Y, Yuan Q, Chen J, Jiang J, Guan H, Zhu R, Li N, Liu W, Wang C. Determination and characterization of molecular heterogeneity and precision medicine strategies of patients with pancreatic cancer and pancreatic neuroendocrine tumor based on oxidative stress and mitochondrial dysfunction-related genes. Front Endocrinol (Lausanne) 2023; 14:1127441. [PMID: 37223030 PMCID: PMC10200886 DOI: 10.3389/fendo.2023.1127441] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/15/2023] [Indexed: 05/25/2023] Open
Abstract
Background Mitochondria are significant both for cellular energy production and reactive oxygen/nitrogen species formation. However, the significant functions of mitochondrial genes related to oxidative stress (MTGs-OS) in pancreatic cancer (PC) and pancreatic neuroendocrine tumor (PNET) are yet to be investigated integrally. Therefore, in pan-cancer, particularly PC and PNET, a thorough assessment of the MTGs-OS is required. Methods Expression patterns, prognostic significance, mutation data, methylation rates, and pathway-regulation interactions were studied to comprehensively elucidate the involvement of MTGs-OS in pan-cancer. Next, we separated the 930 PC and 226 PNET patients into 3 clusters according to MTGs-OS expression and MTGs-OS scores. LASSO regression analysis was utilized to construct a novel prognostic model for PC. qRT-PCR(Quantitative real-time PCR) experiments were performed to verify the expression levels of model genes. Results The subtype associated with the poorest prognosis and lowerest MTGs-OS scores was Cluster 3, which could demonstrate the vital function of MTGs-OS for the pathophysiological processes of PC. The three clusters displayed distinct variations in the expression of conventional cancer-associated genes and the infiltration of immune cells. Similar molecular heterogeneity was observed in patients with PNET. PNET patients with S1 and S2 subtypes also showed distinct MTGs-OS scores. Given the important function of MTGs-OS in PC, a novel and robust MTGs-related prognostic signature (MTGs-RPS) was established and identified for predicting clinical outcomes for PC accurately. Patients with PC were separated into the training, internal validation, and external validation datasets at random; the expression profile of MTGs-OS was used to classify patients into high-risk (poor prognosis) or low-risk (good prognosis) categories. The variations in the tumor immune microenvironment may account for the better prognoses observed in high-risk individuals relative to low-risk ones. Conclusions Overall, our study for the first time identified and validated eleven MTGs-OS remarkably linked to the progression of PC and PNET, and elaborated the biological function and prognostic value of MTGs-OS. Most importantly, we established a novel protocol for the prognostic evaluation and individualized treatment for patients with PC.
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Affiliation(s)
- Yougang Cui
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Department of Gastrointestinal Surgery, The Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China
| | - Qihang Yuan
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Junhong Chen
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Jian Jiang
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Hewen Guan
- Department of Dermatology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Ruiping Zhu
- Department of Pathology, Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China
| | - Ning Li
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Department of General Surgery, Wafangdian Central Hospital, Dalian, Liaoning, China
| | - Wenzhi Liu
- Department of Gastrointestinal Surgery, The Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China
| | - Changmiao Wang
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
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Tong S, Xia M, Xu Y, Sun Q, Ye L, Yuan F, Wang Y, Cai J, Ye Z, Tian D. Identification and validation of a novel prognostic signature based on mitochondria and oxidative stress related genes for glioblastoma. J Transl Med 2023; 21:136. [PMID: 36814293 PMCID: PMC9948483 DOI: 10.1186/s12967-023-03970-6] [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: 11/26/2022] [Accepted: 02/05/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND Mitochondria represent a major source of reactive oxygen species (ROS) in cells, and the direct increase in ROS content is the primary cause of oxidative stress, which plays an important role in tumor proliferation, invasion, angiogenesis, and treatment. However, the relationship between mitochondrial oxidative stress-related genes and glioblastoma (GBM) remains unclear. This study aimed to investigate the value of mitochondria and oxidative stress-related genes in the prognosis and therapeutic targets of GBM. METHODS We retrieved mitochondria and oxidative stress-related genes from several public databases. The LASSO regression and Cox analyses were utilized to build a risk model and the ROC curve was used to assess its performance. Then, we analyzed the correlation between the model and immunity and mutation. Furthermore, CCK8 and EdU assays were utilized to verify the proliferative capacity of GBM cells and flow cytometry was used to analyze apoptosis rates. Finally, the JC-1 assay and ATP levels were utilized to detect mitochondrial function, and the intracellular ROS levels were determined using MitoSOX and BODIPY 581/591 C11. RESULTS 5 mitochondrial oxidative stress-related genes (CTSL, TXNRD2, NUDT1, STOX1, CYP2E1) were screened by differential expression analysis and Cox analysis and incorporated in a risk model which yielded a strong prediction accuracy (AUC value = 0.967). Furthermore, this model was strongly related to immune cell infiltration and mutation status and could identify potential targeted therapeutic drugs for GBM. Finally, we selected NUDT1 for further validation in vitro. The results showed that NUDT1 was elevated in GBM, and knockdown of NUDT1 inhibited the proliferation and induced apoptosis of GBM cells, while knockdown of NUDT1 damaged mitochondrial homeostasis and induced oxidative stress in GBM cells. CONCLUSION Our study was the first to propose a prognostic model of mitochondria and oxidative stress-related genes, which provided potential therapeutic strategies for GBM patients.
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Affiliation(s)
- Shiao Tong
- grid.412632.00000 0004 1758 2270Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Minqi Xia
- grid.412632.00000 0004 1758 2270Department of Endocrinology & Metabolism, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yang Xu
- grid.412632.00000 0004 1758 2270Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Qian Sun
- grid.412632.00000 0004 1758 2270Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Liguo Ye
- grid.412632.00000 0004 1758 2270Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Fanen Yuan
- grid.412632.00000 0004 1758 2270Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yixuan Wang
- grid.412632.00000 0004 1758 2270Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jiayang Cai
- grid.412632.00000 0004 1758 2270Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhang Ye
- grid.412632.00000 0004 1758 2270Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Daofeng Tian
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China.
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8
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Cao S, Chen C, Gu D, Wang Z, Xu G. Establishment and external verification of an oxidative stress-related gene signature to predict clinical outcomes and therapeutic responses of colorectal cancer. Front Pharmacol 2023; 13:991881. [PMID: 36860211 PMCID: PMC9968941 DOI: 10.3389/fphar.2022.991881] [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: 07/12/2022] [Accepted: 10/11/2022] [Indexed: 02/15/2023] Open
Abstract
Objective: Accumulated evidence highlights the biological significance of oxidative stress in tumorigenicity and progression of colorectal cancer (CRC). Our study aimed to establish a reliable oxidative stress-related signature to predict patients' clinical outcomes and therapeutic responses. Methods: Transcriptome profiles and clinical features of CRC patients were retrospectively analyzed from public datasets. LASSO analysis was used to construct an oxidative stress-related signature to predict overall survival, disease-free survival, disease-specific survival, and progression-free survival. Additionally, antitumor immunity, drug sensitivity, signaling pathways, and molecular subtypes were analyzed between different risk subsets through TIP, CIBERSORT, oncoPredict, etc. approaches. The genes in the signature were experimentally verified in the human colorectal mucosal cell line (FHC) along with CRC cell lines (SW-480 and HCT-116) through RT-qPCR or Western blot. Results: An oxidative stress-related signature was established, composed of ACOX1, CPT2, NAT2, NRG1, PPARGC1A, CDKN2A, CRYAB, NGFR, and UCN. The signature displayed an excellent capacity for survival prediction and was linked to worse clinicopathological features. Moreover, the signature correlated with antitumor immunity, drug sensitivity, and CRC-related pathways. Among molecular subtypes, the CSC subtype had the highest risk score. Experiments demonstrated that CDKN2A and UCN were up-regulated and ACOX1, CPT2, NAT2, NRG1, PPARGC1A, CRYAB, and NGFR were down-regulated in CRC than normal cells. In H2O2-induced CRC cells, their expression was notably altered. Conclusion: Altogether, our findings constructed an oxidative stress-related signature that can predict survival outcomes and therapeutic response in CRC patients, thus potentially assisting prognosis prediction and adjuvant therapy decisions.
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Affiliation(s)
- Sha Cao
- Department of Oncology, The First People’s Hospital of Lianyungang, Lianyungang, China
| | - Cheng Chen
- Department of Oncology, The First People’s Hospital of Lianyungang, Lianyungang, China
| | - Dezhi Gu
- Department of Gastrointestinal Surgery, The First People’s Hospital of Lianyungang, Lianyungang, China
| | - Zhengdong Wang
- Department of Gastrointestinal Surgery, The First People’s Hospital of Lianyungang, Lianyungang, China
| | - Guanghui Xu
- Department of Oncology, The First People’s Hospital of Lianyungang, Lianyungang, China,*Correspondence: Guanghui Xu,
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9
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Yang L, Xiong J, Li S, Liu X, Deng W, Liu W, Fu B. Mitochondrial metabolic reprogramming-mediated immunogenic cell death reveals immune and prognostic features of clear cell renal cell carcinoma. Front Oncol 2023; 13:1146657. [PMID: 37213288 PMCID: PMC10196130 DOI: 10.3389/fonc.2023.1146657] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 04/11/2023] [Indexed: 05/23/2023] Open
Abstract
Background Mitochondrial metabolic reprogramming (MMR)-mediated immunogenic cell death (ICD) is closely related to the tumor microenvironment (TME). Our purpose was to reveal the TME characteristics of clear cell renal cell carcinoma (ccRCC) by using them. Methods Target genes were obtained by intersecting ccRCC differentially expressed genes (DEGs, tumor VS normal) with MMR and ICD-related genes. For the risk model, univariate COX regression and K-M survival analysis were used to identify genes most associated with overall survival (OS). Differences in the TME, function, tumor mutational load (TMB), and microsatellite instability (MSI) between high and low-risk groups were subsequently compared. Using risk scores and clinical variables, a nomogram was constructed. Predictive performance was evaluated by calibration plots and receiver operating characteristics (ROC). Results We screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy. We also identified the three genes (CENPA, TIMP1, and MYCN) as potential therapeutic targets, of which MYCN is a novel biomarker. Additionally, the nomogram performed well in both TCGA (1-year AUC=0.862) and E-MTAB-1980 cohorts (1-year AUC=0.909). Conclusions Our model and nomogram allow accurate prediction of patients' prognoses and immunotherapy responses.
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Affiliation(s)
| | | | | | | | | | | | - Bin Fu
- *Correspondence: Bin Fu, ; Weipeng Liu,
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10
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Zhang C, Li Y, Qian J, Zhu Z, Huang C, He Z, Zhou L, Gong Y. Identification of a claudin-low subtype in clear cell renal cell carcinoma with implications for the evaluation of clinical outcomes and treatment efficacy. Front Immunol 2022; 13:1020729. [PMID: 36479115 PMCID: PMC9719924 DOI: 10.3389/fimmu.2022.1020729] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 11/01/2022] [Indexed: 11/22/2022] Open
Abstract
Background In bladder and breast cancer, the claudin-low subtype is widely identified, revealing a distinct tumor microenvironment (TME) and immunological feature. Although we have previously identified individual claudin members as prognostic biomarkers in clear cell renal cell carcinoma (ccRCC), the existence of an intrinsic claudin-low subtype and its interplay with TME and clinical outcomes remains unclear. Methods Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA)- kidney clear cell carcinoma (KIRC) cohort and E-MTAB-1980 were derived as the training and validation cohorts, respectively. In addition, GSE40435, GSE53757, International Cancer Genome Consortium (ICGC) datasets, and RNA-sequencing data from local ccRCC patients were utilized as validation cohorts for claudin clustering based on silhouette scores. Using weighted correlation network analysis (WGCNA) and multiple machine learning algorithms, including least absolute shrinkage and selection operator (LASSO), CoxBoost, and random forest, we constructed a claudin-TME related (CTR) risk signature. Furthermore, the CTR associated genomic characteristics, immunity, and treatment sensitivity were evaluated. Results A claudin-low phenotype was identified and associated with an inferior survival and distinct TME and cancer immunity characteristics. Based on its interaction with TME, a risk signature was developed with robust prognostic prediction accuracy. Moreover, we found its association with a claudin-low, stem-like phenotype and advanced clinicopathological features. Intriguingly, it was also effective in kidney chromophobe and renal papillary cell carcinoma. The high CTR group exhibited genomic characteristics similar to those of claudin-low phenotype, including increased chromosomal instability (such as deletions at 9p) and risk genomic alterations (especially BAP1 and SETD2). In addition, a higher abundance of CD8 T cells and overexpression of immune checkpoints, such as LAG3, CTLA4 and PDCD1, were identified in the high CTR group. Notably, ccRCC patients with high CTR were potentially more sensitive to immune checkpoint inhibitors; their counterparts could have more clinical benefits when treated with antiangiogenic drugs, mTOR, or HIF inhibitors. Conclusion We comprehensively evaluated the expression features of claudin genes and identified a claudin-low phenotype in ccRCC. In addition, its related signature could robustly predict the prognosis and provide guide for personalizing management strategies.
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Affiliation(s)
- Cuijian Zhang
- Department of Urology, Peking University First Hospital, Beijing, China,Institute of Urology, Peking University, Beijing, China,National Urological Cancer Center, Peking University First Hospital, Beijing, China
| | - Yifan Li
- Department of Urology, Peking University First Hospital, Beijing, China,Institute of Urology, Peking University, Beijing, China,National Urological Cancer Center, Peking University First Hospital, Beijing, China
| | - Jinqin Qian
- Department of Urology, Peking University First Hospital, Beijing, China,Institute of Urology, Peking University, Beijing, China,National Urological Cancer Center, Peking University First Hospital, Beijing, China
| | - Zhenpeng Zhu
- Department of Urology, Peking University First Hospital, Beijing, China,Institute of Urology, Peking University, Beijing, China,National Urological Cancer Center, Peking University First Hospital, Beijing, China
| | - Cong Huang
- Department of Urology, Peking University First Hospital, Beijing, China,Institute of Urology, Peking University, Beijing, China,National Urological Cancer Center, Peking University First Hospital, Beijing, China
| | - Zhisong He
- Department of Urology, Peking University First Hospital, Beijing, China,Institute of Urology, Peking University, Beijing, China,National Urological Cancer Center, Peking University First Hospital, Beijing, China
| | - Liqun Zhou
- Department of Urology, Peking University First Hospital, Beijing, China,Institute of Urology, Peking University, Beijing, China,National Urological Cancer Center, Peking University First Hospital, Beijing, China
| | - Yanqing Gong
- Department of Urology, Peking University First Hospital, Beijing, China,Institute of Urology, Peking University, Beijing, China,National Urological Cancer Center, Peking University First Hospital, Beijing, China,*Correspondence: Yanqing Gong,
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11
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Wang X, Xu Y, Dai L, Yu Z, Wang M, Chan S, Sun R, Han Q, Chen J, Zuo X, Wang Z, Hu X, Yang Y, Zhao H, Hu K, Zhang H, Chen W. A novel oxidative stress- and ferroptosis-related gene prognostic signature for distinguishing cold and hot tumors in colorectal cancer. Front Immunol 2022; 13:1043738. [PMID: 36389694 PMCID: PMC9660228 DOI: 10.3389/fimmu.2022.1043738] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 10/17/2022] [Indexed: 08/10/2023] Open
Abstract
Oxidative stress and ferroptosis exhibit crosstalk in many types of human diseases, including malignant tumors. We aimed to develop an oxidative stress- and ferroptosis-related gene (OFRG) prognostic signature to predict the prognosis and therapeutic response in patients with colorectal cancer (CRC). Thirty-four insertion genes between oxidative stress-related genes and ferroptosis-related genes were identified as OFRGs. We then performed bioinformatics analysis of the expression profiles of 34 OFRGs and clinical information of patients obtained from multiple datasets. Patients with CRC were divided into three OFRG clusters, and differentially expressed genes (DEGs) between clusters were identified. OFRG clusters correlated with patient survival and immune cell infiltration. Prognosis-related DEGs in three clusters were used to calculate the risk score, and a prognostic signature was constructed according to the risk score. In this study, patients in the low-risk group had better prognosis, higher immune cell infiltration levels, and better responses to fluorouracil-based chemotherapy and immune checkpoint blockade therapy than high-risk patients; these results were successfully validated with multiple independent datasets. Thus, low-risk CRC could be defined as hot tumors and high-risk CRC could be defined as cold tumors. To further identify potential biomarkers for CRC, the expression levels of five signature genes in CRC and adjacent normal tissues were further verified via an in vitro experiment. In conclusion, we identified 34 OFRGs and constructed an OFRG-related prognostic signature, which showed excellent performance in predicting survival and therapeutic responses for patients with CRC. This could help to distinguish cold and hot tumors in CRC, and the results might be helpful for precise treatment protocols in clinical practice.
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Affiliation(s)
- Xu Wang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yuanmin Xu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Longfei Dai
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Zhen Yu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Ming Wang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Shixin Chan
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Rui Sun
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Qijun Han
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jiajie Chen
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xiaomin Zuo
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Zhenglin Wang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xianyu Hu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yang Yang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Hu Zhao
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Kongwang Hu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Huabing Zhang
- Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei, Anhui, China
- The First Affiliated Chuzhou Hospital of Anhui Medical University, Chuzhou, Anhui, China
| | - Wei Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
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12
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Wang F, Su Q, Li C. Identidication of novel biomarkers in non-small cell lung cancer using machine learning. Sci Rep 2022; 12:16693. [PMID: 36202977 PMCID: PMC9537298 DOI: 10.1038/s41598-022-21050-5] [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: 07/06/2022] [Accepted: 09/22/2022] [Indexed: 11/16/2022] Open
Abstract
Lung cancer is one of the leading causes of cancer-related deaths worldwide, and non-small cell lung cancer (NSCLC) accounts for a large proportion of lung cancer cases, with few diagnostic and therapeutic targets currently available for NSCLC. This study aimed to identify specific biomarkers for NSCLC. We obtained three gene-expression profiles from the Gene Expression Omnibus database (GSE18842, GSE21933, and GSE32863) and screened for differentially expressed genes (DEGs) between NSCLC and normal lung tissue. Enrichment analyses were performed using Gene Ontology, Disease Ontology, and the Kyoto Encyclopedia of Genes and Genomes. Machine learning methods were used to identify the optimal diagnostic biomarkers for NSCLC using least absolute shrinkage and selection operator logistic regression, and support vector machine recursive feature elimination. CIBERSORT was used to assess immune cell infiltration in NSCLC and the correlation between biomarkers and immune cells. Finally, using western blot, small interfering RNA, Cholecystokinin-8, and transwell assays, the biological functions of biomarkers with high predictive value were validated. A total of 371 DEGs (165 up-regulated genes and 206 down-regulated genes) were identified, and enrichment analysis revealed that these DEGs might be linked to the development and progression of NSCLC. ABCA8, ADAMTS8, ASPA, CEP55, FHL1, PYCR1, RAMP3, and TPX2 genes were identified as novel diagnostic biomarkers for NSCLC. Monocytes were the most visible activated immune cells in NSCLC. The knockdown of the TPX2 gene, a biomarker with a high predictive value, inhibited A549 cell proliferation and migration. This study identified eight potential diagnostic biomarkers for NSCLC. Further, the TPX2 gene may be a therapeutic target for NSCLC.
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Affiliation(s)
- Fangwei Wang
- Department of Respiratory Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Qisheng Su
- Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Chaoqian Li
- Department of Respiratory Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China.
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13
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Cheng X, Deng W, Zhang Z, Zeng Z, Liu Y, Zhou X, Zhang C, Wang G. Novel amino acid metabolism‐related gene signature to predict prognosis in clear cell renal cell carcinoma. Front Genet 2022; 13:982162. [PMID: 36118874 PMCID: PMC9478740 DOI: 10.3389/fgene.2022.982162] [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: 06/30/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Amino acid metabolism (AAM) deregulation, an emerging metabolic hallmark of malignancy, plays an essential role in tumour proliferation, invasion, and metastasis. However, the expression of AAM-related genes and their correlation with prognosis in clear cell renal cell carcinoma (ccRCC) remain elusive. This study aims to develop a novel consensus signature based on the AAM-related genes. Methods: The RNA-seq expression data and clinical information for ccRCC were downloaded from the TCGA (KIRC as training dataset) and ArrayExpress (E-MTAB-1980 as validation dataset) databases. The AAM‐related differentially expressed genes were screened via the “limma” package in TCGA cohorts for further analysis. The machine learning algorithms (Lasso and stepwise Cox (direction = both)) were then utilised to establish a novel consensus signature in TCGA cohorts, which was validated by the E-MTAB-1980 cohorts. The optimal cutoff value determined by the “survminer” package was used to categorise patients into two risk categories. The Kaplan-Meier curve, the receiver operating characteristic (ROC) curve, and multivariate Cox regression were utilised to evaluate the prognostic value. The nomogram based on the gene signature was constructed, and its performance was analysed using ROC and calibration curves. Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were conducted on its potential mechanisms. The relationship between the gene signature and key immune checkpoint, N6-methyladenosine (m6A)-related genes, and sensitivity to chemotherapy was assessed. Results: A novel consensus AMM‐related gene signature consisting of IYD, NNMT, ACADSB, GLDC, and PSAT1 is developed to predict prognosis in TCGA cohorts. Kaplan-Meier survival shows that overall survival in the high-risk group was more dismal than in the low-risk group in the TCGA cohort, validated by the E-MTAB-1980 cohort. Multivariate regression analysis also demonstrates that the gene signature is an independent predictor of ccRCC. Immune infiltration analysis highlighted that the high-risk group indicates an immunosuppressive microenvironment. It is also closely related to the level of key immune checkpoints, m6A modification, and sensitivity to chemotherapy drugs. Conclusion: In this study, a novel consensus AAM-related gene signature is developed and validated as an independent predictor to robustly predict the overall survival from ccRCC, which would further improve the clinical outcomes.
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Affiliation(s)
- Xiaofeng Cheng
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Jiangxi Institute of Urology, Nanchang, China
| | - Wen Deng
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Jiangxi Institute of Urology, Nanchang, China
| | - Zhicheng Zhang
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Jiangxi Institute of Urology, Nanchang, China
| | - Zhenhao Zeng
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Jiangxi Institute of Urology, Nanchang, China
| | - Yifu Liu
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Jiangxi Institute of Urology, Nanchang, China
| | - Xiaochen Zhou
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Jiangxi Institute of Urology, Nanchang, China
| | - Cheng Zhang
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Jiangxi Institute of Urology, Nanchang, China
| | - Gongxian Wang
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Jiangxi Institute of Urology, Nanchang, China
- *Correspondence: Gongxian Wang,
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14
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Huang H, Cai Y, Hong X, Gao W, Tang J, Zhang S, Xu Z. T cell proliferation-related genes: Predicting prognosis, identifying the cold and hot tumors, and guiding treatment in clear cell renal cell carcinoma. Front Genet 2022; 13:948734. [PMID: 36118894 PMCID: PMC9478955 DOI: 10.3389/fgene.2022.948734] [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: 05/20/2022] [Accepted: 08/12/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Immunotherapy has become a new direction of current research because the effect of traditional radiotherapy and chemotherapy on clear cell renal cell carcinoma (ccRCC) is not satisfactory. T cell proliferation-related genes (TRGs) play a pivotal role in tumor progression by regulating the proliferation, activity, and function of immune cells. The purpose of our study is to construct and verify a prognostic model based on TRGs and to identify tumor subtypes that may guide treatment through comprehensive bioinformatics analyses. Methods: RNA sequencing data, clinical information, and somatic mutation data of ccRCC are obtained from The Cancer Genome Atlas (TCGA) database. We identified the prognosis-related TRGs which were differentially expressed between normal and tumor tissues. After dividing the patients into a train set and a test set according to proportion 1:1 randomly, the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were performed to construct a risk-stratified model. Its prediction performance was verified. Then, Gene Set Enrichment Analysis (GSEA), principal component analysis (PCA), tumor microenvironment (TME) analysis, and the half-maximal inhibitory concentration (IC50) prediction were performed between the different groups of patients. To further discuss the immunotherapy between hot and cold tumors, we divided all patients into two clusters based on TRGs through unsupervised learning. Analyzing the gene mutation and calculating the tumor mutation burden (TMB), we further explored the relationship between somatic mutations and grouping or clustering. Results: Risk-stratified model and nomogram predict the prognosis of ccRCC patients accurately. Functional enrichment analyses suggested that TRGs mainly focused on the biological pathways related to tumor progression and immune response. Different tumor microenvironment, drug resistance, and TMB can be distinguished clearly according to both risk stratification and tumor subtype clustering. Conclusion: In this study, a new stratification model of ccRCC based on TRGs was established, which can accurately predict the prognosis of patients. IC50 prediction may guide the application of anti-tumor drugs. The distinction between hot and cold tumors provides a reference for clinical immunotherapy.
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15
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Li H, Cong X, Sui J, Jiang Z, Fu K, Huan Y, Cao R, Tian W, Feng Y. Baicalin enhances the thermotolerance of mouse blastocysts by activating the ERK1/2 signaling pathway and preventing mitochondrial dysfunction. Theriogenology 2022; 178:85-94. [PMID: 34808561 DOI: 10.1016/j.theriogenology.2021.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 11/05/2021] [Accepted: 11/13/2021] [Indexed: 10/19/2022]
Abstract
Heat stress causes oxidative damage and induces excessive cell apoptosis and thus affects the development and/or even causes the death of preimplantation embryos. The effects of baicalin on the developmental competence of heat-stressed mouse embryos were investigated in this experiment. Two-cell embryos were cultured in the presence of baicalin and subjected to heat stress (42 °C for 1 h) at their blastocyst stage followed by continuous culture at 37 °C until examination. The results showed that heat stress (H group) increased reactive oxygen species (ROS) production, apoptosis and even embryo death, along with reductions in both mitochondrial activity and membrane potential (ΔΨm). Both heat stress (H group) and inhibition of the ERK1/2 signaling pathway (U group) led to significantly reduced expression levels of the genes c-fos, AP-1 and ERK2, and the phosphorylation of ERK1/2 and c-Fos, along with significantly increased c-Jun mRNA expression and phosphorylation levels. These negative effects of heat stress on the ERK1/2 signaling pathway were neutralized by baicalin treatment. To explore the signal transduction mechanism of baicalin in improving embryonic tolerance to heat stress, mitochondrial quality and apoptosis rate in the mouse blastocysts were also examined. Baicalin was found to up-regulate the expression of mtDNA and TFAM mRNA, increased mitochondria activity and ΔΨm, and improved the cellular mitochondria quality of mouse blastocysts undergoing heat stress. Moreover, baicalin decreased Bax transcript abundance in blastocyst, along with an increase in the blastocyst hatching rate, which were negatively affected by heat stress. Our findings suggest that baicalin improves the developmental capacity and quality of heat-stressed mouse embryos via a mechanism whereby mitochondrial quality is improved by activating the ERK1/2 signaling pathway and inducing anti-cellular apoptosis.
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Affiliation(s)
- Huatao Li
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China
| | - Xia Cong
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China
| | - Junxia Sui
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China
| | - Zhongling Jiang
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China
| | - Kaiqiang Fu
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China
| | - Yanjun Huan
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China
| | - Rongfeng Cao
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China
| | - Wenru Tian
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China.
| | - Yanni Feng
- Laboratory of Animal Reproductive Physiology and Disease, College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China.
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