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Huang J, Zhou J, Xue X, Dai T, Zhu W, Jiao S, Wu H, Meng Q. Identification of aging-related genes in diagnosing osteoarthritis via integrating bioinformatics analysis and machine learning. Aging (Albany NY) 2024; 16:153-168. [PMID: 38175691 PMCID: PMC10817387 DOI: 10.18632/aging.205357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/13/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Osteoarthritis (OA) is one of the main causes of pain and disability in the world, it may be caused by many factors. Aging plays a significant role in the onset and progression of OA. However, the mechanisms underlying it remain unknown. Our research aimed to uncover the role of aging-related genes in the progression of OA. METHODS In Human OA datasets and aging-related genes were obtained from the GEO database and the HAGR website, respectively. Bioinformatics methods including Gene Ontology (GO), Kyoto Encyclopedia of Genes Genomes (KEGG) pathway enrichment, and Protein-protein interaction (PPI) network analysis were used to analyze differentially expressed aging-related genes (DEARGs) in the normal control group and the OA group. And then weighted gene coexpression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO) regression, and the Random Forest (RF) machine learning algorithms were used to find the hub genes. RESULTS Four overlapping hub genes: HMGB2, CDKN1A, JUN, and DDIT3 were identified. According to the nomogram model and receiver operating characteristic (ROC) curve analysis, four hub DEARGs had good diagnostic value in distinguishing normal from OA. Furthermore, the qRT-PCR test demonstrated that HMGB2, CDKN1A, JUN, and DDIT3 mRNA expression levels were lower in OA group than in normal group. CONCLUSION Finally, these four-hub aging-related genes may help us understand the underlying mechanism of aging in osteoarthritis and could be used as possible diagnostic and therapeutic targets.
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Affiliation(s)
- Jian Huang
- Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
- Department of Traumatic Orthopedics, The Central Hospital of Xiaogan, Hubei 432100, China
| | - Jiangfei Zhou
- Department of Orthopedics, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Xiang Xue
- Department of Orthopedics, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Tianming Dai
- Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Weicong Zhu
- Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Songsong Jiao
- Department of Orthopedics, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Hang Wu
- Department of Traumatic Orthopedics, The Central Hospital of Xiaogan, Hubei 432100, China
| | - Qingqi Meng
- Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
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Zhang C, Lin Q, Li C, Qiu Y, Chen J, Zhu X. Comprehensive analysis of the prognostic implication and immune infiltration of CISD2 in diffuse large B-cell lymphoma. Front Immunol 2023; 14:1277695. [PMID: 38155967 PMCID: PMC10754510 DOI: 10.3389/fimmu.2023.1277695] [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: 08/15/2023] [Accepted: 11/15/2023] [Indexed: 12/30/2023] Open
Abstract
Background Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell lymphoma in adults. CDGSH iron sulfur domain 2 (CISD2) is an iron-sulfur protein and plays a critical role of cell proliferation. The aberrant expression of CISD2 is associated with the progression of multiple cancers. However, its role in DLBCL remains unclear. Methods The differential expression of CISD2 was identified via public databases, and quantitative real-time PCR (qRT-PCR) and western blot were used to identifed the expression of CISD2. We estimated the impact of CISD2 on clinical prognosis using the Kaplan-Meier plotter. Meanwhile, the drug sensitivity of CISD2 was assessed using CellMiner database. The 100 CISD2-related genes from STRING obtained and analyzed using the LASSO Cox regression. A CISD2 related signature for risk model (CISD2Risk) was established. The PPI network of CISD2Risk was performed, and functional enrichment was conducted through the DAVID database. The impacts of CISD2Risk on clinical features were analyzed. ESTIMATE, CIBERSORT, and MCP-counter algorithm were used to identify CISD2Risk associated with immune infiltration. Subsequently, Univariate and multivariate Cox regression analysis were applied, and a prognostic nomogram, accompanied by a calibration curve, was constructed to predict 1-, 3-, and 5-years survival probabilities. Results CISD2 was upregulated in DLBCL patients comparing with normal controls via public datasets, similarly, CISD2 was highly expressed in DLBCL cell lines. Overexpression of CISD2 was associated with poor prognosis in DLBCL patients based on the GSE31312, the GSE32918, and GSE93984 datasets (P<0.05). Nine drugs was considered as a potential therapeutic agents for CISD2. By using the LASSO cox regression, twenty seven genes were identified to construct CISD2Risk, and biological functions of these genes might be involved in apoptosis and P53 signaling pathway. The high CISD2Risk value had a worse prognosis and therapeutic effect (P<0.05). The higher stromal score, immune score, and ESTIMATE score were associated with lowe CISD2Risk value, CISD2Risk was negatively correlated with several immune infiltrating cells (macrophages M0 and M1, CD8 T cells, CD4 naïve T cells, NK cell, etc) that might be correlated with better prognosis. Additionally, The high CISD2Risk was identified as an independent prognostic factor for DLBCL patients using both univariate and multivariate Cox regression. The nomogram produced accurate predictions and the calibration curves were in good agreement. Conclusion Our study demonstrates that high expression of CISD2 in DLBCL patients is associated with poor prognosis. We have successfully constructed and validated a good prognostic prediction and efficacy monitoring for CISD2Risk that included 27 genes. Meanwhile, CISD2Risk may be a promising evaluator for immune infiltration and serve as a reference for clinical decision-making in DLBCL patients.
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Affiliation(s)
- ChaoFeng Zhang
- Department of Haematology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China
- Department of Hematology and Rheumatology, The Affiliated Hospital of Putian University, Putian, China
- The School of Basic Medicine, Putian University, Putian, China
| | - Qi Lin
- Department of Pharmacy, The Affiliated Hospital of Putian University, Putian, China
| | - ChunTuan Li
- Department of Haematology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China
| | - Yang Qiu
- The School of Basic Medicine, Putian University, Putian, China
| | - JingYu Chen
- The School of Basic Medicine, Putian University, Putian, China
| | - XiongPeng Zhu
- Department of Haematology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China
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Liu Y, Wang J, Shen X, Li L, Zhang N, Wang X, Tang B. A novel angiogenesis-related scoring model predicts prognosis risk and treatment responsiveness in diffuse large B-cell lymphoma. Clin Exp Med 2023; 23:3781-3797. [PMID: 37402040 DOI: 10.1007/s10238-023-01127-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 06/22/2023] [Indexed: 07/05/2023]
Abstract
Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous disease with varying therapeutic responses and prognoses. Angiogenesis is a crucial factor in lymphoma growth and progression, but no scoring model based on angiogenesis-related genes (ARGs) has been developed for prognostic evaluation of DLBCL patients. In this study, we used univariate Cox regression to identify prognostic ARGs and found two distinct clusters of DLBCL patients in the GSE10846 dataset based on the expression of these prognostic ARGs. These two clusters had different prognoses and immune cell infiltration. Using LASSO regression analysis, we constructed a novel seven-ARG-based scoring model in GSE10846 dataset, and it was further validated in the GSE87371 dataset. The DLBCL patients were divided into high- and low-score groups based on the median risk score as a cut-off. The high-score group had a worse prognosis and showed higher expression of immune checkpoints, M2 macrophages, myeloid-derived suppressor cells, and regulatory T cells, indicating a stronger immunosuppressive environment. DLBCL patients in high-score group were resistant to doxorubicin and cisplatin, which are components of frequently used chemotherapy regimens, but more sensitive to gemcitabine and temozolomide. Using RT-qPCR, we found that two candidate risk genes, RAPGEF2 and PTGER2, were over-expressed in DLBCL tissues compared with control tissues. Taken together, the ARG-based scoring model provides a promising direction for the prognosis and immune status of DLBCL patients, and benefits the development of personalized treatment for DLBCL patients.
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Affiliation(s)
- Yu Liu
- Department of Infectious Disease, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China
| | - Jinhua Wang
- Department of Hematology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, Liaoning, People's Republic of China
| | - Xiaochen Shen
- Department of Pathology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China
| | - Li Li
- Department of Hematology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, Liaoning, People's Republic of China
| | - Ning Zhang
- Department of Thyroid Surgery, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China
| | - Xiaobo Wang
- Department of Hematology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, Liaoning, People's Republic of China.
| | - Bo Tang
- Department of Hematology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, Liaoning, People's Republic of China.
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Ke P, Zhu Q, Xu T, Yang X, Wang Y, Qiu H, Wu D, Bao X, Chen S. Identification and validation of a 7-genes prognostic signature for adult acute myeloid leukemia based on aging-related genes. Aging (Albany NY) 2023; 15:5826-5853. [PMID: 37367950 PMCID: PMC10333094 DOI: 10.18632/aging.204843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 06/10/2023] [Indexed: 06/28/2023]
Abstract
To explore effects of aging-related genes (ARGs) on the prognosis of Acute Myeloid Leukemia (AML), a seven-ARGs signature was developed and validated in AML patients. The numbers of seven-ARG sequences were selected to construct the survival prognostic signature in TCGA-LAML cohort, and two GEO datasets were used independently to verify the prognostic values of signature. According to seven-ARGs signature, patients were categorized into two subgroups. Patients with high-risk prognostic score were defined as HRPS-group/high-risk group, while others were set as LRPS-group/low-risk group. HRPS-group presented adverse overall survival (OS) than LRPS-group in TCGA-AML cohort (HR=3.39, P<0.001). In validation, the results emphasized a satisfactory discrimination in different time points, and confirmed the poor OS of HRPS-group both in GSE37642 (HR=1.96, P=0.001) and GSE106291 (HR=1.88, P<0.001). Many signal pathways, including immune- and tumor-related processes, especially NF-κB signaling, were highly enriched in HRPS-group. Coupled with high immune-inflamed infiltration, the HRPS-group was highly associated with the driver gene and oncogenic signaling pathway of TP53. Prediction of blockade therapy targeting immune checkpoint indicated varied benefits base on the different ARGs signature score, and the results of predicted drug response suggested that Pevonedistat, an inhibitor of NEDD8-activating enzyme, targeting NF-κB signaling, may have potential therapeutic value for HRPS-group. Compared with clinical factors alone, the signature had an independent value and more predictive power of AML prognosis. The 7-ARGs signature may help to guide clinical-decision making to predict drug response, and survival in AML patients.
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Affiliation(s)
- Peng Ke
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Qian Zhu
- Soochow Hopes Hematonosis Hospital, Suzhou, China
| | - Ting Xu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Xiaofei Yang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Ying Wang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Huiying Qiu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Depei Wu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Xiebing Bao
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Suning Chen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
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Peng L, Chen H, Wang Z, He Y, Zhang X. Identification and validation of a classifier based on hub aging-related genes and aging subtypes correlation with immune microenvironment for periodontitis. Front Immunol 2022; 13:1042484. [PMID: 36389665 PMCID: PMC9663931 DOI: 10.3389/fimmu.2022.1042484] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 10/18/2022] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Periodontitis (PD), an age-related disease, is characterized by inflammatory periodontal tissue loss, and with the general aging of the global population, the burden of PD is becoming a major health concern. Nevertheless, the mechanism underlying this phenomenon remains indistinct. We aimed to develop a classification model for PD and explore the relationship between aging subtypes and the immune microenvironment for PD based on bioinformatics analysis. MATERIALS AND METHODS The PD-related datasets were acquired from the Gene Expression Omnibus (GEO) database, and aging-related genes (ARGs) were obtained from the Human Aging Genomic Resources (HAGR). Four machine learning algorithms were applied to screen out the hub ARGs. Then, an artificial neural network (ANN) model was constructed and the accuracy of the model was validated by receiver operating characteristic (ROC) curve analysis. The clinical effect of the model was evaluated by decision curve analysis (DCA). Consensus clustering was employed to determine the aging expression subtypes. A series of bioinformatics analyses were performed to explore the PD immune microenvironment and its subtypes. The hub aging-related modules were defined using weighted correlation network analysis (WGCNA). RESULTS Twenty-seven differentially expressed ARGs were dysregulated and a classifier based on four hub ARGs (BLM, FOS, IGFBP3, and PDGFRB) was constructed to diagnose PD with excellent accuracy. Subsequently, the mRNA levels of the hub ARGs were validated by quantitative real-time PCR (qRT-PCR). Based on differentially expressed ARGs, two aging-related subtypes were identified. Distinct biological functions and immune characteristics including infiltrating immunocytes, immunological reaction gene sets, the human leukocyte antigen (HLA) gene, and immune checkpoints were revealed between the subtypes. Additionally, the black module correlated with subtype-1 was manifested as the hub aging-related module and its latent functions were identified. CONCLUSION Our findings highlight the critical implications of aging-related genes in modulating the immune microenvironment. Four hub ARGs (BLM, FOS, IGFBP3, and PDGFRB) formed a classification model, and accompanied findings revealed the essential role of aging in the immune microenvironment for PD, providing fresh inspiration for PD etiopathogenesis and potential immunotherapy.
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Affiliation(s)
- Limin Peng
- College of Stomatology, Chongqing Medical University, Chongqing, China,Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China,Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
| | - Hang Chen
- College of Stomatology, Chongqing Medical University, Chongqing, China,Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China,Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
| | - Zhenxiang Wang
- College of Stomatology, Chongqing Medical University, Chongqing, China,Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China,Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
| | - Yujuan He
- Department of Laboratory Medicine, Key Laboratory of Diagnostic Medicine (Ministry of Education), Chongqing Medical University, Chongqing, China
| | - Xiaonan Zhang
- College of Stomatology, Chongqing Medical University, Chongqing, China,Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China,Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China,*Correspondence: Xiaonan Zhang,
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Yan J, Yuan W, Zhang J, Li L, Zhang L, Zhang X, Zhang M. Identification and Validation of a Prognostic Prediction Model in Diffuse Large B-Cell Lymphoma. Front Endocrinol (Lausanne) 2022; 13:846357. [PMID: 35498426 PMCID: PMC9048048 DOI: 10.3389/fendo.2022.846357] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous group with varied pathophysiological, genetic, and clinical features, accounting for approximately one-third of all lymphoma cases worldwide. Notwithstanding that unprecedented scientific progress has been achieved over the years, the survival of DLBCL patients remains low, emphasizing the need to develop novel prognostic biomarkers for early risk stratification and treatment optimization. METHOD In this study, we screened genes related to the overall survival (OS) of DLBCL patients in datasets GSE117556, GSE10846, and GSE31312 using univariate Cox analysis. Survival-related genes among the three datasets were screened according to the criteria: hazard ratio (HR) >1 or <1 and p-value <0.01. Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analysis were used to optimize and establish the final gene risk prediction model. The TCGA-NCICCR datasets and our clinical cohort were used to validate the performance of the prediction model. CIBERSORT and ssGSEA algorithms were used to estimate immune scores in the high- and low-risk groups. RESULTS We constructed an eight-gene prognostic signature that could reliably predict the clinical outcome in training, testing, and validation cohorts. Our prognostic signature also performed distinguished areas under the ROC curve in each dataset, respectively. After stratification based on clinical characteristics such as cell-of-origin (COO), age, eastern cooperative oncology group (ECOG) performance status, international prognostic index (IPI), stage, and MYC/BCL2 expression, the difference in OS between the high- and low-risk groups was statistically significant. Next, univariate and multivariate analyses revealed that the risk score model had a significant prediction value. Finally, a nomogram was established to visualize the prediction model. Of note, we found that the low-risk group was enriched with immune cells. CONCLUSION In summary, we identified an eight-gene prognostic prediction model that can effectively predict survival outcomes of patients with DLBCL and built a nomogram to visualize the perdition model. We also explored immune alterations between high- and low-risk groups.
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Affiliation(s)
- Jiaqin Yan
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wei Yuan
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou University, Zhengzhou, China
| | - Junhui Zhang
- Otorhinolaryngology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ling Li
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lei Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xudong Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mingzhi Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Mingzhi Zhang,
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