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Chen J, Sun Q, Wang Y, Yin W. Revealing the key role of cuproptosis in osteoporosis via the bioinformatic analysis and experimental validation of cuproptosis-related genes. Mamm Genome 2024; 35:414-431. [PMID: 38904833 DOI: 10.1007/s00335-024-10049-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 06/14/2024] [Indexed: 06/22/2024]
Abstract
The incidence of osteoporosis has rapidly increased owing to the ageing population. Cuproptosis, a novel mechanism that regulates cell death, may be a new therapeutic approach. However, the relevance of cuproptosis in the immune microenvironment and osteoporosis immunotherapy is still unknown. We intersected the differentially expressed genes from osteoporotic samples with 75 cuproptosis-related genes to identify 16 significantly expressed cuproptosis genes. We further explored the connection between the cuproptosis pattern, immune microenvironment, and immunotherapy. The weighted gene co-expression network analysis algorithm was used to identify cuproptosis phenotype-associated genes, and we used quantitative real-time PCR and immunohistochemistry in mouse femur tissues to verify hub gene (MAP2K2, FDX1, COX19, VEGFA, CDKN2A, and NFE2L2) expression. Six hub genes and 59 cuproptosis phenotype-associated genes involved in immunisation were identified among the osteoporosis and control groups, and the majority of these 59 genes were enriched in the inflammatory response, as well as in signal transducers, Janus kinase, and transcription pathway activators. In addition, two different clusters of cuproptosis were found, and immune infiltration analysis showed that gene Cluster 1 had a greater immune score and immune infiltration level. Further analysis revealed that three key genes (COX19, MAP2K2, and FDX1) were highly correlated with immune cell infiltration, and external experiments validated the association of these three genes with the prognosis of osteoporosis. We used the three key mRNAs COX19, MAP2K2, and FDX1 as a classification model that may systematically elucidate the complex connection between cuproptosis and the immune microenvironment of osteoporosis. New insights into osteoporosis pathogenesis and immunotherapy prospects may be gained from this study.
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Affiliation(s)
- Jianxing Chen
- Department of Joint Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150000, China
| | - Qifeng Sun
- Department of Joint Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150000, China
| | - Yi Wang
- Department of Joint Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150000, China
| | - Wenzhe Yin
- Department of Joint Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150000, China.
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2
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Zhao C, Zhu X, Liu H, Dong Q, Sun J, Sun B, Wang G, Wang X. The prognostic and immune significance of SLAMF9 in pan-cancer and validation of its role in colorectal cancer. Sci Rep 2024; 14:17899. [PMID: 39095516 PMCID: PMC11297030 DOI: 10.1038/s41598-024-68134-y] [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: 07/19/2024] [Indexed: 08/04/2024] Open
Abstract
SLAMF9, a member of the conserved lymphocyte activation molecules family (SLAMF), has been less investigated compared to other SLAMs, especially concerning its implications across various cancer types. In our systematic pan-cancer investigation, we observed elevated SLAMF9 expression in various tumor tissues, which was correlated with reduced patient survival across most malignancies. Correlation analyses further revealed significant associations between SLAMF9 expression and immune cell infiltrates, immune checkpoint inhibitors, tumor mutation load, microsatellite instability, and epithelial-mesenchymal transition (EMT) scores. Cell-based assays demonstrated that SLAMF9 knockdown attenuated the proliferative, motile, and invasive capacities of colorectal cancer (CRC) cells. In a nude mouse xenograft model, suppression of SLAMF9 expression substantially inhibited tumor growth. These findings highlight the potential of SLAMF9 as a prognostic and therapeutic biomarker across tumors, with notable implications for CRC cell proliferation and migration.
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Affiliation(s)
- Chunmei Zhao
- Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong City, 226001, Jiangsu Province, China
| | - Xingjia Zhu
- Medical School of Nantong University, Affiliated Hospital of Nantong University, Nantong, 226001, Jiangsu Province, China
| | - Huimin Liu
- Clinical Laboratory, Nantong Third People's Hospital, Affiliated Nantong Hospital 3 of Nantong University, Nantong, Jiangsu, China
| | - Qingyu Dong
- Medical School of Nantong University, Affiliated Hospital of Nantong University, Nantong, 226001, Jiangsu Province, China
| | - Jing Sun
- Medical School of Nantong University, Affiliated Hospital of Nantong University, Nantong, 226001, Jiangsu Province, China
| | - Baolan Sun
- Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong City, 226001, Jiangsu Province, China
| | - Guihua Wang
- Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong City, 226001, Jiangsu Province, China.
| | - Xudong Wang
- Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong City, 226001, Jiangsu Province, China.
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3
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Liu Y, Yi T, Meng S, Zhao X, Chen X, Zhang Y. Trichostatin A-modified vaccine provides superior protection against ovarian cancer formation and development. Braz J Med Biol Res 2024; 57:e12874. [PMID: 38775545 PMCID: PMC11101164 DOI: 10.1590/1414-431x2024e12874] [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: 10/31/2023] [Accepted: 03/21/2024] [Indexed: 05/25/2024] Open
Abstract
More attention has been paid to immunotherapy for ovarian cancer and the development of tumor vaccines. We developed a trichostatin A (TSA)-modified tumor vaccine with potent immunomodulating activities that can inhibit the growth of ovarian cancer in rats and stimulate immune cell response in vivo. TSA-treated Nutu-19 cells inactivated by X-ray radiation were used as a tumor vaccine in rat ovarian cancer models. Prophylactic and therapeutic experiments were performed with TSA-modified tumor vaccine in rats. Flow cytometry and ELISpot assays were conducted to assess immune response. Immune cell expression in the spleen and thymus were detected by immunohistochemical staining. GM-CSF, IL-7, IL-17, LIF, LIX, KC, MCP-1, MIP-2, M-CSF, IP-10/CXCL10, MIG/CXCL9, RANTES, IL-4, IFN-γ, and VEGF expressions were detected with Milliplex Map Magnetic Bead Panel immunoassay. TSA vaccination in therapeutic and prophylactic models could effectively stimulate innate immunity and boost the adaptive humoral and cell-mediated immune responses to inhibit the growth and tumorigenesis of ovarian cancer. This vaccine stimulated the thymus into reactivating status and enhanced infiltrating lymphocytes in tumor-bearing rats. The expression of key immunoregulatory factors were upregulated in the vaccine group. The intensities of infiltrating CD4+ and CD8+ T cells and NK cells were significantly increased in the vaccine group compared to the control group (P<0.05). This protection was mainly dependent on the IFN-γ pathway and, to a much lesser extent, by the IL-4 pathway. The tumor cells only irradiated by X-ray as the control group still showed a slight immune effect, indicating that irradiated cells may also cause certain immune antigen exposure, but the efficacy was not as significant as that of the TSA-modified tumor vaccine. Our study revealed the potential application of the TSA-modified tumor vaccine as a novel tumor vaccine against tumor refractoriness and growth. These findings offer a better understanding of the immunomodulatory effects of the vaccine against latent tumorigenesis and progression. This tumor vaccine therapy may increase antigen exposure, synergistically activate the immune system, and ultimately improve remission rates. A vaccine strategy designed to induce effective tumor immune response is being considered for cancer immunotherapy.
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Affiliation(s)
- Yingwei Liu
- Department of Gynecology, First Affiliated Hospital of Chongqing
Medical University, Chongqing, China
| | - Tao Yi
- Department of Gynecology & Obstetrics, West China Second
Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Shenglan Meng
- National Key Laboratory of Biotherapy and Cancer Center, West
China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xia Zhao
- Department of Gynecology & Obstetrics, West China Second
Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiancheng Chen
- National Key Laboratory of Biotherapy and Cancer Center, West
China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yanna Zhang
- Department of Blood Transfusion, Sichuan Provincial People’s
Hospital, University of Electronic Science and Technology of China, Chengdu,
Sichuan, China
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4
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Yang SD, Chen MZ, Yang DF, Hu SB, Zheng DD. IL-6 significantly correlated with the prognosis in low-grade glioma and the mediating effect of immune microenvironment. Medicine (Baltimore) 2024; 103:e38091. [PMID: 38728467 PMCID: PMC11081577 DOI: 10.1097/md.0000000000038091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 04/11/2024] [Indexed: 05/12/2024] Open
Abstract
To screen immune-related prognostic biomarkers in low-grade glioma (LGG), and reveal the potential regulatory mechanism. The differential expressed genes (DEGs) between alive and dead patients were initially identified, then the key common genes between DEGs and immune-related genes were obtained. Regarding the key DEGs associated with the overall survival (OS), their clinical value was assessed by Kaplan-Meier, RCS, logistic regression, ROC, and decision curve analysis methods. We also assessed the role of immune infiltration on the association between key DEGs and OS. All the analyses were based on the TGCA-LGG data. Finally, we conducted the molecular docking analysis to explore the targeting binding of key DEGs with the therapeutic agents in LGG. Among 146 DEGs, only interleukin-6 (IL-6) was finally screened as an immune-related biomarker. High expression of IL-6 significantly correlated with poor OS time (all P < .05), showing a linear relationship. The combination of IL-6 with IDH1 mutation had the most favorable prediction performance on survival status and they achieved a good clinical net benefit. Next, we found a significant relationship between IL-6 and immune microenvironment score, and the immune microenvironment played a mediating effect on the association of IL-6 with survival (all P < .05). Detailly, IL-6 was positively related to M1 macrophage infiltration abundance and its biomarkers (all P < .05). Finally, we obtained 4 therapeutic agents in LGG targeting IL-6, and their targeting binding relationships were all verified. IL6, as an immune-related biomarker, was associated with the prognosis in LGG, and it can be a therapeutic target in LGG.
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Affiliation(s)
- Shi-Di Yang
- Department of Neurosurgery, Ningbo Medical Centre LiHuiLi Hospital, Ningbo, Zhejiang, China
| | - Meng-Zong Chen
- Department of Neurosurgery, Ningbo Medical Centre LiHuiLi Hospital, Ningbo, Zhejiang, China
| | - Deng-Feng Yang
- Department of Neurosurgery, Ningbo Medical Centre LiHuiLi Hospital, Ningbo, Zhejiang, China
| | - Shao-Bo Hu
- Department of Neurosurgery, Ningbo Medical Centre LiHuiLi Hospital, Ningbo, Zhejiang, China
| | - Dong-Dong Zheng
- Department of Neurosurgery, Ningbo Medical Centre LiHuiLi Hospital, Ningbo, Zhejiang, China
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Ni S, Liang Q, Jiang X, Ge Y, Jiang Y, Liu L. Prognostic models for immunotherapy in non-small cell lung cancer: A comprehensive review. Heliyon 2024; 10:e29840. [PMID: 38681577 PMCID: PMC11053285 DOI: 10.1016/j.heliyon.2024.e29840] [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: 09/26/2023] [Revised: 04/11/2024] [Accepted: 04/16/2024] [Indexed: 05/01/2024] Open
Abstract
The introduction of immune checkpoint inhibitors (ICIs) has revolutionized the treatment of lung cancer. Given the limited clinical benefits of immunotherapy in patients with non-small cell lung cancer (NSCLC), various predictors have been shown to significantly influence prognosis. However, no single predictor is adequate to forecast patients' survival benefit. Therefore, it's imperative to develop a prognostic model that integrates multiple predictors. This model would be instrumental in identifying patients who might benefit from ICIs. Retrospective analysis and small case series have demonstrated the potential role of these models in prognostic prediction, though further prospective investigation is required to evaluate more rigorously their application in these contexts. This article presents and summarizes the latest research advancements on immunotherapy prognostic models for NSCLC from multiple omics perspectives and discuss emerging strategies being developed to enhance the domain.
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Affiliation(s)
- Siqi Ni
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Qi Liang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Xingyu Jiang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yinping Ge
- The Friendship Hospital of Ili Kazakh Autonomous Prefecture Ili & Jiangsu Joint Institute of Health, Yining 835000, Xinjiang Uygur Autonomous Regio, China
| | - Yali Jiang
- The Friendship Hospital of Ili Kazakh Autonomous Prefecture Ili & Jiangsu Joint Institute of Health, Yining 835000, Xinjiang Uygur Autonomous Regio, China
| | - Lingxiang Liu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
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6
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Peng H, Wu X, Cui X, Liu S, Liang Y, Cai X, Shi M, Zhong R, Li C, Liu J, Wu D, Gao Z, Lu X, Luo H, He J, Liang W. Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study. Transl Lung Cancer Res 2024; 13:763-784. [PMID: 38736486 PMCID: PMC11082711 DOI: 10.21037/tlcr-23-800] [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: 12/02/2023] [Accepted: 03/15/2024] [Indexed: 05/14/2024]
Abstract
Background Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear. Methods Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted. Results An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods. Conclusions This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.
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Affiliation(s)
- Haoxin Peng
- Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing, China
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Nanshan School, Guangzhou Medical University, Guangzhou, China
| | - Xiangrong Wu
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Nanshan School, Guangzhou Medical University, Guangzhou, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiaoli Cui
- Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology Co., Ltd., Shenzhen, China
| | - Shaopeng Liu
- Department of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China
- Department of Artificial Intelligence Research, Pazhou Lab, Guangzhou, China
| | - Yueting Liang
- Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiuyu Cai
- Department of General Internal Medicine, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Cener for Cancer Medicine, Guangzhou, China
| | - Mengping Shi
- Department of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China
| | - Ran Zhong
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Caichen Li
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jun Liu
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Dongfang Wu
- Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology Co., Ltd., Shenzhen, China
| | - Zhibo Gao
- Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology Co., Ltd., Shenzhen, China
| | - Xu Lu
- Department of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China
- Department of Artificial Intelligence Research, Pazhou Lab, Guangzhou, China
| | - Haitao Luo
- Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology Co., Ltd., Shenzhen, China
| | - Jianxing He
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Wenhua Liang
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Medical Oncology, The First People’s Hospital of Zhaoqing, Zhaoqing, China
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Shen L, Li A, Cui J, Liu H, Zhang S. Integration of single-cell RNA-seq and bulk RNA-seq data to construct and validate a cancer-associated fibroblast-related prognostic signature for patients with ovarian cancer. J Ovarian Res 2024; 17:82. [PMID: 38627854 PMCID: PMC11020192 DOI: 10.1186/s13048-024-01399-z] [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: 05/09/2023] [Accepted: 03/21/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND To establish a prognostic risk profile for ovarian cancer (OC) patients based on cancer-associated fibroblasts (CAFs) and gain a comprehensive understanding of their role in OC progression, prognosis, and therapeutic efficacy. METHODS Data on OC single-cell RNA sequencing (scRNA-seq) and total RNA-seq were collected from the GEO and TCGA databases. Seurat R program was used to analyze scRNA-seq data and identify CAFs clusters corresponding to CAFs markers. Differential expression analysis was performed on the TCGA dataset to identify prognostic genes. A CAF-associated risk signature was designed using Lasso regression and combined with clinicopathological variables to develop a nomogram. Functional enrichment and the immune landscape were also analyzed. RESULTS Five CAFs clusters were identified in OC using scRNA-seq data, and 2 were significantly associated with OC prognosis. Seven genes were selected to develop a CAF-based risk signature, primarily associated with 28 pathways. The signature was a key independent predictor of OC prognosis and relevant in predicting the results of immunotherapy interventions. A novel nomogram combining CAF-based risk and disease stage was developed to predict OC prognosis. CONCLUSION The study highlights the importance of CAFs in OC progression and suggests potential for innovative treatment strategies. A CAF-based risk signature provides a highly accurate prediction of the prognosis of OC patients, and the developed nomogram shows promising results in predicting the OC prognosis.
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Affiliation(s)
- Liang Shen
- Department of Obstetrics and Gynecology, Liaocheng People's Hospital, 67 Dongchang West Road, Liaocheng, Shandong, 252000, P.R. China
- Shandong University, Jinan, P.R. China
- Department of Gynecology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jingwuweiqi Road, Jinan, Shandong, 250021, P.R. China
| | - Aihua Li
- Department of Obstetrics and Gynecology, Liaocheng People's Hospital, 67 Dongchang West Road, Liaocheng, Shandong, 252000, P.R. China.
| | - Jing Cui
- Department of Oral and Maxillofacial Surgery, Jinan Stomatology Hospital, 101 Jingliu Road, Jinan, Shandong, 250001, P.R. China
- Central Laboratory of Jinan Stamotological Hospital, Jinan Key Laboratory of Oral Tissue Regeneration, 101 Jingliu Road, Jinan, Shandong, 250001, P.R. China
| | - Haixia Liu
- Department of Obstetrics, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jingwuweiqi Road, Jinan, Shandong, 250021, P.R. China
| | - Shiqian Zhang
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, P.R. China.
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Lv ZB, Zhang JJ, Xiang C. GDF10 and IDO1 as a thyroid cancer prognostic biomarker associated with immune infiltration. Heliyon 2024; 10:e27651. [PMID: 38509876 PMCID: PMC10950683 DOI: 10.1016/j.heliyon.2024.e27651] [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: 05/22/2023] [Revised: 03/04/2024] [Accepted: 03/05/2024] [Indexed: 03/22/2024] Open
Abstract
Objection The aim of this work is to screen the immune-related genes to predict the prognosis and provide a new direction of treatment for patients with thyroid cancer (THCA). Methods The mRNA and clinical features of THCA patients were collected from the Cancer Genome Atlas (TCGA) databases. The immune-related genes were obtained from the ImmPort databases. The bio-information methods were performed to screen the differential expression genes (DEGs) and genes related to immunity between the THCA patients and normal individuals. On this basis, the hub prognosis immunity genes were screened by Veen. The related genes were obtained by constructing the protein-protein interaction network. The enrichment analyses were performed based on the protein and protein interaction (PPI) related genes. The hub immune checkpoint was screened by correlation analysis. Finally, the hub gene and the immunity checkpoint-miRNA (or transcription factor, drug) interaction network were constructed. A drug-sensitive analysis also was performed. Results The GDF10 was screened. The PPI genes were enriched in the TGF-beta signaling pathway, signaling pathways regulating, the pluripotency of stem cells, Cytokine-cytokine receptor interaction, and so on. The hub immunity checkpoint IDO1 was obtained. The joint indicator of two hub genes was positively related to the thyroid differentiation score. Three interaction factors were found to be related to the two hub genes, and 7 kinds of drugs screened act on the two hub genes at the same time. Conclusion This work indicated that immune-related gene GDF10 and immune checkpoint IDO1 are important for the prognosis prediction of THCA patients, and immunity is involved in the proliferation, and differentiation of tumor cells.
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Affiliation(s)
- Zhao-bao Lv
- Breast and Thyroid Surgery, The Second Hospital of Liaocheng, Lingqing, 252600, Shandong, China
| | - Jun-jing Zhang
- Breast and Thyroid Surgery, The Second Hospital of Liaocheng, Lingqing, 252600, Shandong, China
| | - Cheng Xiang
- Thyroid Surgery, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China
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Zhang J, Wang X, Zhang Z, Ma F, Wang F. A novel tumor-associated neutrophil gene signature for predicting prognosis, tumor immune microenvironment, and therapeutic response in breast cancer. Sci Rep 2024; 14:5339. [PMID: 38438469 PMCID: PMC10912776 DOI: 10.1038/s41598-024-55513-8] [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: 08/23/2023] [Accepted: 02/24/2024] [Indexed: 03/06/2024] Open
Abstract
Tumor-associated neutrophils (TANs) can promote tumor progression. This study aimed to investigate the molecular signature that predict the prognosis and immune response of breast cancer (BRCA) based on TAN-related gene (TANRG) expression data. The RNA-seq data of BRCA were gathered from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) datasets. Univariate Cox regression analysis and the least absolute shrinkage and selection operator for selecting prognostic genes. A neo-TAN-related risk signature was constructed by multivariate Cox regression analysis. Time-dependent receiver operating characteristic (ROC) curve analyses and Kaplan-Meier analyses were performed to validate the signature in GEO cohorts and the triple-negative breast cancer (TNBC) subtype. We constructed an independent prognostic factor model with 11 TANRGs. The areas under the ROC curve (AUCs) of the TCGA training cohorts for 3-, 5-, and 7-year overall survival were 0.72, 0.73, and 0.73, respectively. The AUCs of the GEO test cohorts for 3-, 5-, and 7-year overall survival were 0.83, 0.89, and 0.94 (GSE25066) and 0.67, 0.69, and 0.73 (GSE58812), respectively. The proportion of immune subtypes differed among the different risk groups. The IC50 values differed significantly between risk groups and can be used as a guide for systemic therapy. The prognostic model developed by TANRGs has excellent predictive performance in BRCA patients. In addition, this feature is closely related to the prediction of survival, immune activity and treatment response in BRCA patients.
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Affiliation(s)
- Jianyou Zhang
- Department of Breast Disease, Weifang People's Hospital, Weifang, No.151, Guangwen Street, Kuiwen District, Shandong, China
| | - Xinbo Wang
- Department of Breast Disease, Weifang People's Hospital, Weifang, No.151, Guangwen Street, Kuiwen District, Shandong, China
| | - Zhonglai Zhang
- Department of General Surgery, Gaomi People's Hospital, Weifang, Shandong, China
| | - Fuyi Ma
- Department of Breast Disease, Weifang People's Hospital, Weifang, No.151, Guangwen Street, Kuiwen District, Shandong, China
| | - Feng Wang
- Department of Breast Disease, Weifang People's Hospital, Weifang, No.151, Guangwen Street, Kuiwen District, Shandong, China.
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10
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Song Z, Cao X, Wang X, Li Y, Zhang W, Wang Y, Chen L. A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma. Sci Rep 2024; 14:4621. [PMID: 38409243 PMCID: PMC10897395 DOI: 10.1038/s41598-024-55201-7] [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: 10/05/2023] [Accepted: 02/21/2024] [Indexed: 02/28/2024] Open
Abstract
As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.
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Affiliation(s)
- Zipei Song
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xincen Cao
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaokun Wang
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuting Li
- Department of Graduate Administration, Chinese PLA General Hospital, Beijing, China
| | - Weiran Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuheng Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Liang Chen
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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11
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Wu M, Gu S, Yang J, Zhao Y, Sheng J, Cheng S, Xu S, Wu Y, Ma M, Luo X, Zhang H, Wang Y, Zhao A. Comprehensive machine learning-based preoperative blood features predict the prognosis for ovarian cancer. BMC Cancer 2024; 24:267. [PMID: 38408960 PMCID: PMC10895771 DOI: 10.1186/s12885-024-11989-1] [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: 11/07/2023] [Accepted: 02/10/2024] [Indexed: 02/28/2024] Open
Abstract
PURPOSE Significant advancements in improving ovarian cancer (OC) outcomes have been limited over the past decade. To predict prognosis and improve outcomes of OC, we plan to develop and validate a robust prognosis signature based on blood features. METHODS We screened age and 33 blood features from 331 OC patients. Using ten machine learning algorithms, 88 combinations were generated, from which one was selected to construct a blood risk score (BRS) according to the highest C-index in the test dataset. RESULTS Stepcox (both) and Enet (alpha = 0.7) performed the best in the test dataset with a C-index of 0.711. Meanwhile, the low RBS group possessed observably prolonged survival in this model. Compared to traditional prognostic-related features such as age, stage, grade, and CA125, our combined model had the highest AUC values at 3, 5, and 7 years. According to the results of the model, BRS can provide accurate predictions of OC prognosis. BRS was also capable of identifying various prognostic stratifications in different stages and grades. Importantly, developing the nomogram may improve performance by combining BRS and stage. CONCLUSION This study provides a valuable combined machine-learning model that can be used for predicting the individualized prognosis of OC patients.
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Affiliation(s)
- Meixuan Wu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Sijia Gu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Jiani Yang
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Yaqian Zhao
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Jindan Sheng
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Shanshan Cheng
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Shilin Xu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Yongsong Wu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Mingjun Ma
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Xiaomei Luo
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Hao Zhang
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Yu Wang
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China.
| | - Aimin Zhao
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
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12
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Li H, Jiang Y, Chen J, Li Z, Zhang R, Wei Y, Zhao Y, Shen S, Chen F. Systematic characterization of m6A proteomics across 12 cancer types: a multi-omics integration study. Mol Omics 2024; 20:103-114. [PMID: 37942799 DOI: 10.1039/d3mo00171g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
The modification patterns of N6-methyladenosine (m6A) regulators and interacting genes are deeply involved in tumors. However, the effect of m6A modification patterns on human proteomics remains largely unknown. We evaluated the molecular characteristics and clinical relevance of m6A modification proteomics patterns among 1013 pan-cancer samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). More than half of the m6A proteins were expressed at higher levels in tumor tissues and presented oncogenic characteristics. Furthermore, we performed multi-omics analyses integrating with transcriptomics data of m6A regulators and interactive coding and non-coding RNAs and developed a m6A multi-omics signature to identify potential m6A modification target proteins across global proteomics. It was significantly associated with overall survival in nine cancer types, tumor mutation burden (P = 0.01), and immune checkpoints including PD-L1 (P = 4.9 × 10-8) and PD-1 (P < 0.01). We identified 51 novel proteins associated with the multi-omics signature (PFDR < 0.05). These proteins were functional through pathway enrichment analyses. The protein with the highest hit frequency was CHORDC1, which was significantly up-regulated in tumor tissues in nine cancer types. Its higher abundance was significantly associated with a poorer prognosis in seven cancer types. The identified m6A target proteins might provide infomation for the study of molecular mechanism of cancer.
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Affiliation(s)
- Hongru Li
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
| | - Yunke Jiang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
| | - Jiajin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 211166, Nanjing, China
| | - Zaiming Li
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
- China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yongyue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
- China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yang Zhao
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
- Key Laboratory of Biomedical Big Data of Nanjing Medical University, Nanjing 211166, China
| | - Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 211166, Nanjing, China
- China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 211166, Nanjing, China
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13
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Guo D, Liu J, Li S, Xu P. Analysis of m6A regulators related immune characteristics in ankylosing spondylitis by integrated bioinformatics and computational strategies. Sci Rep 2024; 14:2724. [PMID: 38302672 PMCID: PMC10834589 DOI: 10.1038/s41598-024-53184-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 01/29/2024] [Indexed: 02/03/2024] Open
Abstract
N6-methyladenosine (m6A) modification, as a common epigenetic modification, has been widely studied in autoimmune diseases. However, the role of m6A in the regulation of the immune microenvironment of ankylosing spondylitis (AS) remains unclear. Therefore, we aimed to investigate the effect of m6A modification on the immune microenvironment of AS. We first evaluated RNA modification patterns mediated by 26 m6A regulators in 52 AS samples and 20 healthy samples. Thereafter, an m6A related classifier composed of seven genes was constructed and could effectively distinguish healthy and AS samples. Then, the correlation between m6A regulators and immune characteristics were investigated, including infiltrating immunocytes, immune reactions activity, and human leukocyte antigen (HLA) genes expression. The results indicated that m6A regulators was closely correlated with immune characteristics. For example, EIF3A was significantly related to infiltrating immunocytes; IGF2BP2 and EIF3A were significant regulators in immune reaction of TGF-β family member, and the expression of HLA-DPA1 and HLA-E were affected by EIF3A and ALKBH5. Next, two distinct m6A expression patterns were identified through unsupervised clustering analysis, and diverse immune characteristics were found between them. A total of 5889 m6A phenotype-related genes were obtained between the two expression patterns, and their biological functions were revealed. Finally, we validated the expression status of m6A modification regulators using two additional datasets. Our findings illustrate that m6A modifications play a critical role in the diversity and complexity of the AS immune microenvironment.
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Affiliation(s)
- Da Guo
- Osteonecrosis and Joint Reconstruction Ward, Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China
| | - Jiayi Liu
- Xinglin College, Liaoning University of Traditional Chinese Medicine, Shenyang, 110167, Liaoning, China
| | - Shuang Li
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Peng Xu
- Osteonecrosis and Joint Reconstruction Ward, Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China.
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14
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Zhang H, Liu S, Wang Y, Huang H, Sun L, Yuan Y, Cheng L, Liu X, Ning K. Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers. iScience 2024; 27:108715. [PMID: 38226168 PMCID: PMC10788220 DOI: 10.1016/j.isci.2023.108715] [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: 08/17/2023] [Revised: 10/24/2023] [Accepted: 12/11/2023] [Indexed: 01/17/2024] Open
Abstract
Protein glycosylation is associated with the pathogenesis of various cancers. The utilization of certain glycans in cancer diagnosis models holds promise, yet their accuracy is not always guaranteed. Here, we investigated the utility of deep learning techniques, specifically random forests combined with transfer learning, in enhancing serum glycome's discriminative power for cancer diagnosis (including ovarian cancer, non-small cell lung cancer, gastric cancer, and esophageal cancer). We started with ovarian cancer and demonstrated that transfer learning can achieve superior performance in data-disadvantaged cohorts (AUROC >0.9), outperforming the approach of PLS-DA. We identified a serum glycan-biomarker panel including 18 serum N-glycans and 4 glycan derived traits, most of which were featured with sialylation. Furthermore, we validated advantage of the transfer learning scheme across other cancer groups. These findings highlighted the superiority of transfer learning in improving the performance of glycans-based cancer diagnosis model and identifying cancer biomarkers, providing a new high-fidelity cancer diagnosis venue.
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Affiliation(s)
- Haobo Zhang
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Si Liu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Yi Wang
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hanhui Huang
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Lukang Sun
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Youyuan Yuan
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Liming Cheng
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xin Liu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Kang Ning
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
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15
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Wang Q, Zheng C, Hou H, Bao X, Tai H, Huang X, Li Z, Li Z, Wang Q, Pan Q, Wang L, Zhou S, Bian Y, Pan Q, Gong A, Xu M. Interplay of Sphingolipid Metabolism in Predicting Prognosis of GBM Patients: Towards Precision Immunotherapy. J Cancer 2024; 15:275-292. [PMID: 38164288 PMCID: PMC10751665 DOI: 10.7150/jca.89338] [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: 08/21/2023] [Accepted: 10/16/2023] [Indexed: 01/03/2024] Open
Abstract
Background: In spite of numerous existing bio-surveillance systems for predicting glioma (GBM) prognosis, enhancing the efficacy of immunotherapy remains an ongoing conundrum. The continual scrutiny of the dynamic interplay between the sphingolipid metabolic pathway and tumor immunophenotypes has unveiled potential implications. However, the intricate orchestration of functional and regulatory mechanisms by long non-coding RNAs (lncRNAs) in GBM, particularly in the context of sphingolipid metabolism, remains cryptic. Methods: We harnessed established R packages to intersect gene expression profiles of GBM patients within the The Cancer Genome Atlas (TCGA) database with the compilation of sphingolipid metabolism genes from GeneCards. This enabled us to discern markedly distinct lncRNAs, which were subsequently deployed to construct a robust prognostic model utilizing Lasso-Cox regression analysis. We then scrutinized the immune microenvironment across various risk strata using the ssGSEA and CIBERSORT algorithms. To evaluate mutation patterns and drug resistance profiles within patient subgroups, we devised the "Prophytic" and "Maftools" packages, respectively. Results: Our investigation scrutinized lncRNAs linked to sphingolipid metabolism, utilizing glioma specimens from TCGA. We meticulously curated 1224 sphingolipid-associated genes gleaned from GeneCards and pinpointed 272 differentially expressed mRNAs via transcriptomic analysis. Enrichment analyses underscored their significance in sphingolipid processes. A prognostic model founded on 17 meticulously selected lncRNAs was systematically constructed and validated. This model adeptly stratified GBM patients into high- and low-risk categories, yielding highly precise prognostic insights. We also discerned correlations between immune cell infiltration and genetic mutation discrepancies, along with distinct therapeutic responses through drug sensitivity analysis. Notably, computational findings were corroborated through experimental validation by RT-PCR. Conclusion: In summation, our exhaustive inquiry underscores the multifaceted utility of the sphingolipid metabolic pathway as an autonomous diagnostic and prognostic indicator for glioma patients. Furthermore, we amalgamate a profusion of substantiated evidence concerning immune infiltration and gene mutations, thereby reinforcing the proposition that sphingolipid metabolism may function as a pivotal determinant in the panorama of immunotherapeutic interventions.
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Affiliation(s)
- Qi Wang
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China
| | - Chuanhua Zheng
- Department of Neurosurgery, the Affiliated Hospital of Youjiang Medical University for Nationalities, Guangxi, China
| | - Hanjin Hou
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Xin Bao
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Huading Tai
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Xufeng Huang
- Faculty of Dentistry, University of Debrecen, Debrecen, Hungary
| | - Zhengrui Li
- Department of Oral and Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology & National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - Zhangzuo Li
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Qiaowei Wang
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Qi Pan
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Longbin Wang
- Department of Clinical Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Shujing Zhou
- Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Yanjie Bian
- Xinxiang Medical University, Xinxiang, China
| | - Qier Pan
- Department of Endocrinology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China
| | - Aihua Gong
- Department of Cell Biology, School of Medicine, Jiangsu University, Zhenjiang, China
| | - Min Xu
- Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China
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16
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Jiang XY, Hu JJ, Wang R, Zhang WY, Jin QQ, Yang YT, Mei J, Hong L, Yao H, Tao F, Li JJ, Liu Y, Zhang L, Chen SX, Chen G, Song Y, Zhou SG. Cuproptosis-Associated lncRNA Gene Signature Establishes New Prognostic Profile and Predicts Immunotherapy Response in Endometrial Carcinoma. Biochem Genet 2023:10.1007/s10528-023-10574-8. [PMID: 38108937 DOI: 10.1007/s10528-023-10574-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 10/26/2023] [Indexed: 12/19/2023]
Abstract
Uterine corpus endometrial carcinoma (UCEC), a prevalent kind of cancerous tumor in female reproductive system that has a dismal prognosis in women worldwide. Given the very limited studies of cuproptosis-related lncRNAs (CRLs) in UCEC. Our purpose was to construct a prognostic profile based on CRLs and explore its assess prognostic value in UCEC victims and its correlation with the immunological microenvironment. METHODS 554 UCEC tumor samples and 23 normal samples' RNA-seq statistics and clinical details were compiled from data in the TCGA database. CRLs were obtained using Pearson correlation analysis. Using LASSO Cox regression, multivariate Cox regression, and univariate Cox regression analysis, six CRLs are confirmed to develop a risk prediction model at last.We identified two main molecular subtypes and observed that multilayer CRLs modifications were related to patient clinicopathological features, prognosis, and tumor microenvironment (TME) cell infiltration characteristics, and then we verified the prognostic hallmark of UCEC and examined its immunological landscape.Finally, using qRT-PCR, model hub genes' expression patterns were confirmed. RESULTS A unique CRL signature was established by the combination of six differently expressed CRLs that were highly linked with the prognosis of UCEC patients. According to their CRLs signatures, the patients were divided into two groups: the low-risk and the high-risk groups. Compared to individuals at high risk, patients at low risk had higher survival rates (p < 0.001). Additionally, Cox regression reveals that the profiles of lncRNAs linked to cuproptosis may independently predict prognosis in UCEC patients. The 1-, 3-, and 5-year risks' respective receiver operating characteristics (ROC) exhibited AUC values of 0.778, 0.810, and 0.854. Likewise, the signature could predict survival in different groups based on factors like stage, age, and grade, among others. Further investigation revealed differences between the different risk score groups in terms of drug sensitivity,immune cell infiltration,tumor mutation burden (TMB) score and microsatellite instability (MSI) score. Compared to the group of high risk, the low-risk group had greater rates of TMB and MSI. Results from qRT-PCR revealed that in UCEC vs normal tissues, AC026202.2, NRAV, AC079466.2, and AC090617.5 were upregulated,while LINC01545 and AL450384.1 were downregulated. CONCLUSIONS Our research clarified the relationship between CRLs signature and the immunological profile and prognosis of UCEC.This signature will establish the framework for future investigations into the endometrial cancer CRLs mechanism as well as the exploitation of new diagnostic tools and new therapeutic.
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Affiliation(s)
- Xi-Ya Jiang
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Jing-Jing Hu
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Reproduction, The First Affiliated Hospital of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Rui Wang
- Department of Clinical Laboratory, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
| | - Wei-Yu Zhang
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Qin-Qin Jin
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Yin-Ting Yang
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Jie Mei
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Lin Hong
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Hui Yao
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Feng Tao
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Jie-Jie Li
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Yu Liu
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Li Zhang
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Shun-Xia Chen
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Guo Chen
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China
| | - Yang Song
- Department of Pain, The First Affiliated Hospital of Anhui Medical University, Hefei, 230032, Anhui, China.
| | - Shu-Guang Zhou
- Department of Gynecology and Obstetrics, Maternity and Child Healthcare Hospital Affiliated to Anhui Medical University, Anhui Province Maternity and Child Healthcare Hospital, Hefei, 230001, Anhui, China.
- Department of Gynecology and Obstetrics, The Fifth Clinical College of Anhui Medical University, Hefei, 230032, Anhui, China.
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Kim T, Lim H, Jun S, Park J, Lee D, Lee JH, Lee JY, Bang D. Globally shared TCR repertoires within the tumor-infiltrating lymphocytes of patients with metastatic gynecologic cancer. Sci Rep 2023; 13:20485. [PMID: 37993659 PMCID: PMC10665396 DOI: 10.1038/s41598-023-47740-2] [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: 04/15/2023] [Accepted: 11/17/2023] [Indexed: 11/24/2023] Open
Abstract
Gynecologic cancer, including ovarian cancer and endometrial cancer, is characterized by morphological and molecular heterogeneity. Germline and somatic testing are available for patients to screen for pathogenic variants in genes such as BRCA1/2. Tissue expression levels of immunogenomic markers such as PD-L1 are also being used in clinical research. The basic therapeutic approach to gynecologic cancer combines surgery with chemotherapy. Immunotherapy, while not yet a mainstream treatment for gynecologic cancers, is advancing, with Dostarlimab recently receiving approval as a treatment for endometrial cancer. The goal remains to harness stimulated immune cells in the bloodstream to eradicate multiple metastases, a feat currently deemed challenging in a typical clinical setting. For the discovery of novel immunotherapy-based tumor targets, tumor-infiltrating lymphocytes (TILs) give a key insight on tumor-related immune activities by providing T cell receptor (TCR) sequences. Understanding the TCR repertoires of TILs in metastatic tissues and the circulation is important from an immunotherapy standpoint, as a subset of T cells in the blood have the potential to help kill tumor cells. To explore the relationship between distant tissue biopsy regions and blood circulation, we investigated the TCR beta chain (TCRβ) in bulk tumor and matched blood samples from 39 patients with gynecologic cancer. We found that the TCR clones of TILs at different tumor sites were globally shared within patients and had high overlap with the TCR clones in peripheral blood.
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Affiliation(s)
- Taehoon Kim
- Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea
| | - Hyeonseob Lim
- Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea
| | - Soyeong Jun
- Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea
| | - Junsik Park
- Department of Obstetrics and Gynecology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea
| | - Dongin Lee
- Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea
| | - Ji Hyun Lee
- Department of Clinical Pharmacology and Therapeutics, College of Medicine, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Korea
- Department of Biomedical Science and Technology, Kyung Hee Medical Science Research Institute, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Korea
| | - Jung-Yun Lee
- Department of Obstetrics and Gynecology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
| | - Duhee Bang
- Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
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18
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Wu Z, Lin Q, Sheng L, Chen W, Liang M, Wu D, Ke Y. A novel immune-related risk-scoring system associated with the prognosis and response of cervical cancer patients treated with radiation therapy. Front Mol Biosci 2023; 10:1297774. [PMID: 38028542 PMCID: PMC10667679 DOI: 10.3389/fmolb.2023.1297774] [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: 09/20/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023] Open
Abstract
Objective: The tumor microenvironment plays a critical role in the radiotherapy and immunotherapy response of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Radioresistance is a key factor in treatment failure among patients who receive radical radiotherapy. Thus, new immune-related biomarkers associated with radiotherapy response in CESC are needed. Methods: In this study, the CIBERSORT and ESTIMATE methods were applied to determine the percentage of tumor-infiltrating cells and the number of immune components in 103 CESCs treated with radiotherapy from The Cancer Genome Atlas (TCGA) database. The main dysregulated genes were subjected to multivariate and univariate analyses. The prognostic value of this system was studied via receiver operating characteristic curve and survival analysis. For further confirmation, the biomarkers' expression levels and predictive value were validated by immunohistochemistry (IHC) and qRT-PCR. The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in cervical cancer patients treated with radiation therapy. Results: Data for 17 radioresistant and 86 radiosensitive tumors were obtained from the The Cancer Genome Atlas database. 53 immune-related DEGs were identified. GO and KEGG analyses revealed that the DEGs were enriched in protein kinase B signaling, growth factors in cytokines, the MAPK pathway and the PI3K-Akt pathway. Then, 14 key immune-related genes built a risk scoring model were deemed prognostic in CESC with radiotherapy. The area under the curve (AUC) of the model was 0.723, and the high-risk group presented worse outcomes than the low-risk group. In addition, the high-risk group tended to have persistent tumors (p = 0.001). The high expression of WT1 and SPOUYT4 were associated with relapse, the high expression of Angiotensinogen and MIEN1 were associated with nonrelapse. Analysis of the immune microenvironment indicated that M0 macrophages, M2 macrophages, activated mast cells and resting memory CD4+ T cells were positively correlated with the risk score (p < 0.05). Conclusion: The novel immune-related risk scoring system has some advantages in predicting the prognosis and treatment response of cervical cancer patients treated with radiotherapy. Moreover, it might provide novel clues for providing targeted immune therapy to these patients.
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Affiliation(s)
- Zhuna Wu
- Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Qiuya Lin
- Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Liying Sheng
- Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Weihong Chen
- Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Meili Liang
- Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Danni Wu
- Department of Operation, The Second Hospital of Jinjiang, Quanzhou, China
| | - Yumin Ke
- Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
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19
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Zhu Z, Feng W, Tan XY, Gu PC, Song W, Ma HT. Immune-related gene prognostic index (IRGPI) for lung adenocarcinoma predicts patient prognosis and immunotherapy response. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2023; 16:260-281. [PMID: 37970331 PMCID: PMC10641371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 08/28/2023] [Indexed: 11/17/2023]
Abstract
OBJECTIVE We searched for a predictive biomarker that also predicts whether patients would benefit from immune checkpoint blockade (ICB) treatment from a few angles, because existing biomarkers no longer wholly replicate the interconnections of distinctive elements in the tumor microenvironment (TME). METHODS We identified 55 pivotal IRGs by performing a WGCNA and univariate Cox regression analysis on a lung adenocarcinoma dataset from the TCGA database. The IRGPI model was then constructed using multivariate Cox regression analysis, which identified 16 genes and verified the use of the GSE68465 database. The AUC of the IRGPI was compared to those of the current biomarkers to determine its predictive potential. Then we examined the molecular and immunological properties of ICB and assessed its effectiveness using CTLA4 expression and TIDE. RESULTS Patients with a high IRGPI had a later clinical stage, more severe symptoms, and a worse prognosis. Patients with a low IRGPI had a higher immune escape potential and were less responsive to immunotherapy. CONCLUSION The IRGPI may be a biomarker for determining the prognosis of patients and whether they respond favorably to ICB therapy.
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Affiliation(s)
- Zheng Zhu
- Department of Thoracic Surgery, Suzhou Dushu Lake Hospital (Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University), Soochow UniversityNo. 9 Chongwen Road, Suzhou 215000, Jiangsu, China
| | - Wei Feng
- Department of Thoracic Surgery, Suzhou Dushu Lake Hospital (Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University), Soochow UniversityNo. 9 Chongwen Road, Suzhou 215000, Jiangsu, China
| | - Xiao-Yan Tan
- Department of Thoracic Surgery, Suzhou Dushu Lake Hospital (Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University), Soochow UniversityNo. 9 Chongwen Road, Suzhou 215000, Jiangsu, China
| | - Pin-Chao Gu
- Department of Thoracic Surgery, Suzhou Dushu Lake Hospital (Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University), Soochow UniversityNo. 9 Chongwen Road, Suzhou 215000, Jiangsu, China
| | - Wei Song
- Emergency Department, Suzhou Dushu Lake Hospital (Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University), Soochow UniversityNo. 9 Chongwen Road, Suzhou 215000, Jiangsu, China
| | - Hai-Tao Ma
- Department of Thoracic Surgery, Suzhou Dushu Lake Hospital (Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University), Soochow UniversityNo. 9 Chongwen Road, Suzhou 215000, Jiangsu, China
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20
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Tang Q, Zhang H, Tang R. Identification of two immune subtypes and four hub immune-related genes in ovarian cancer through multiple analysis. Medicine (Baltimore) 2023; 102:e35246. [PMID: 37800814 PMCID: PMC10553066 DOI: 10.1097/md.0000000000035246] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 08/24/2023] [Indexed: 10/07/2023] Open
Abstract
Immune classification of ovarian cancer (OV) becomes more and more influential for its immunotherapy. However, current studies had few immune subtypes of OV. It is urgent to explore the immune subtypes and deeper hub immune-related genes (IRGs) of OV for follow-up treatment. A total number of 379 OV samples were obtained from UCSC online website. Single sample gene set enrichment analysis of 29 immune gene sets was used for identifying immune subtypes of OV and gene set variation analysis were used for exploring the hallmarks and Kyoto Encyclopedia of Genes and Genomes pathways of immune types. Two immunity subtypes (Immunity_H and Immunity_L) were identified by single sample gene set enrichment analysis. The OV patients in Immunity_H group had longer overall survival compared with those in Immunity_L group. The Immunity_H had higher stromal score, immune score and estimate score and the tumor purity had the adverse tendency. Besides, the gene set variation analysis enrichment results showed positive relationship between improved immunoreaction and pathways correlated to classical signaling pathway (PI3K/AKT/MTOR, P53, TNFA/NFkB signaling pathways) and immune responses (T/B cell receptor signaling pathways and primary immunodeficiency). Furthermore, 4 hub IRGs (CCR5, IL10RA, ITGAL and PTPRC) were jointly dug by weighted gene co-expression network construction and Cytoscape. Our team also explored the mutations of 4 hub IRGs and PTPRC showed nearly 7% amplification. Besides, 8 immune-checkpoint genes had higher expression in Immuity_H group compared with Immuity_L group, except CD276. The correlation between PD-1/PD-L1 and 4 hub IRGs were explored and gene set enrichment analysis were conducted to explore the underlying mechanisms of PTPRC in OV. Finally, western-blotting showed PTPRC could regulate immune checkpoint PD-L1 expression via JAK-STAT signaling pathway. In a word, 2 immune subtypes and 4 hub IRGs of OV were identified by multiple analysis.
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Affiliation(s)
- Qin Tang
- Department of Obstetrics and Gynecology, The Jingmen Center Hospital, Jingmen, PR China
| | - Haojie Zhang
- Department of Operating Room, The Jingmen Center Hospital, Jingmen, PR China
| | - Rong Tang
- Department of Pathology, The Jingmen Center Hospital, Jingmen, PR China
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21
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Yang Z, Zhu J, Yang T, Tang W, Zheng X, Ji S, Ren Z, Lu F. Comprehensive analysis of the lncRNAs-related immune gene signatures and their correlation with immunotherapy in lung adenocarcinoma. Br J Cancer 2023; 129:1397-1408. [PMID: 37543671 PMCID: PMC10628174 DOI: 10.1038/s41416-023-02379-8] [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: 11/05/2022] [Revised: 07/06/2023] [Accepted: 07/25/2023] [Indexed: 08/07/2023] Open
Abstract
BACKGROUND Long non-coding RNAs (lncRNAs)-related immune genes (lrRIGs) play a crucial role in the development and progression of lung adenocarcinoma (LUAD). However, reliable prognostic signatures based on lrRIGs have not yet been identified. METHODS We screened lrRIGs associated with the prognosis of LUAD using The Cancer Genome Atlas (TCGA) database and then established a novel prognostic nine-gene signature composed of CD79A, INHA, SHC3, LIFR, TNFRSF11A, GPI, F2RL1, SEMA7A and WFDC2 through bioinformatic approaches. A risk score derived from this gene signature was used to divide LUAD patients into the low- and high-risk groups. The latter was confirmed to have markedly worse overall survival (O.S.). A nomogram was developed using the risk score and other independent prognostic elements, demonstrating excellent performance in predicting the O.S. rate of LUAD patients. RESULTS We observed that the infiltration of diverse immune cell subtypes and response to immunotherapy and chemotherapy significantly differed between the low- and high-risk groups. CONCLUSIONS Overall, stratification based on this gene signature could be used to guide better therapeutic management and improve outcomes for LUAD patients.
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Affiliation(s)
- Zhengyan Yang
- Joint National Laboratory for Antibody Drug Engineering, the First Affiliated Hospital, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Jianling Zhu
- Joint National Laboratory for Antibody Drug Engineering, the First Affiliated Hospital, School of Basic Medical Sciences, Henan University, Kaifeng, China
- Department of Immunology, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Tiantian Yang
- Joint National Laboratory for Antibody Drug Engineering, the First Affiliated Hospital, School of Basic Medical Sciences, Henan University, Kaifeng, China
- Department of Immunology, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Wenjun Tang
- Joint National Laboratory for Antibody Drug Engineering, the First Affiliated Hospital, School of Basic Medical Sciences, Henan University, Kaifeng, China
- Department of Immunology, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Xiaowei Zheng
- Department of Clinical Laboratory, Puyang Hospital of Traditional Chinese Medicine, Puyang, China
| | - Shaoping Ji
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Zhiguang Ren
- Joint National Laboratory for Antibody Drug Engineering, the First Affiliated Hospital, School of Basic Medical Sciences, Henan University, Kaifeng, China.
- Institute of Traditional Chinese Medicine, Henan University, Kaifeng, China.
| | - Feng Lu
- Joint National Laboratory for Antibody Drug Engineering, the First Affiliated Hospital, School of Basic Medical Sciences, Henan University, Kaifeng, China.
- Department of Immunology, School of Basic Medical Sciences, Henan University, Kaifeng, China.
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22
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Chen L, Gao W, Lin L, Sha C, Li T, Chen Q, Wei H, Yang M, Xing J, Zhang M, Zhao S, Xu W, Li Y, Long L, Zhu X. A methylation- and immune-related lncRNA signature to predict ovarian cancer outcome and uncover mechanisms of chemoresistance. J Ovarian Res 2023; 16:186. [PMID: 37674251 PMCID: PMC10483746 DOI: 10.1186/s13048-023-01260-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 08/13/2023] [Indexed: 09/08/2023] Open
Abstract
Tumor-associated lncRNAs regulated by epigenetic modification switches mediate immune escape and chemoresistance in ovarian cancer (OC). However, the underlying mechanisms and concrete targets have not been systematically elucidated. Here, we discovered that methylation modifications played a significant role in regulating immune cell infiltration and sensitizing OC to chemotherapy by modulating immune-related lncRNAs (irlncRNAs), which represent tumor immune status. Through deep analysis of the TCGA database, a prognostic risk model incorporating four methylation-related lncRNAs (mrlncRNAs) and irlncRNAs was constructed. Twenty-one mrlncRNA/irlncRNA pairs were identified that were significantly related to the overall survival (OS) of OC patients. Subsequently, we selected four lncRNAs to construct a risk signature predictive of OS and indicative of OC immune infiltration, and verified the robustness of the risk signature in an internal validation set. The risk score was an independent prognostic factor for OC prognosis, which was demonstrated via multifactorial Cox regression analysis and nomogram. Moreover, risk scores were negatively related to the expression of CD274, CTLA4, ICOS, LAG3, PDCD1, and PDCD1LG2 and negatively correlated with CD8+, CD4+, and Treg tumor-infiltrating immune cells. In addition, a high-risk score was associated with a higher IC50 value for cisplatin, which was associated with a significantly worse clinical outcome. Next, a competing endogenous RNA (ceRNA) network and a signaling pathway controlling the infiltration of CD8+ T cells were explored based on the lncRNA model, which suggested a potential therapeutic target for immunotherapy. Overall, this study constructed a prognostic model by pairing mrlncRNAs and irlncRNAs and revealed the critical role of the FTO/RP5-991G20.1/hsa-miR-1976/MEIS1 signaling pathway in regulating immune function and enhancing anticancer therapy.
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Affiliation(s)
- Lu Chen
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
- Department of Gynaecology and Obstetrics, Taixing People's Hospital, Taixing, Jiangsu, China
| | - Wujiang Gao
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
- Department of Gynaecology and Obstetrics, Yangzhou First People's Hospital, Yangzhou, Jiangsu, China
| | - Li Lin
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
| | - Chunli Sha
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
- Department of Gynaecology and Obstetrics, The First People's Hospital of Nantong City, Nantong, Jiangsu, China
| | - Taoqiong Li
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
| | - Qi Chen
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
| | - Hong Wei
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
| | - Meiling Yang
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
- Department of Gynaecology and Obstetrics, The First People's Hospital of Nantong City, Nantong, Jiangsu, China
| | - Jie Xing
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
| | - Mengxue Zhang
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
| | - Shijie Zhao
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China
| | - Wenlin Xu
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China.
| | - Yuefeng Li
- Medical school, Jiangsu University, No. 301, Xuefu Road, Zhenjiang City, 212031, Jiangsu Province, China.
| | - Lulu Long
- Oncology Department, Affiliated People's Hospital of jiangsu university, No. 8, Dianli Road, Zhenjiang City, 212001, Jiangsu Province, China.
| | - Xiaolan Zhu
- Reproductive Medicine Center, The Fourth Affiliated Hospital of Jiangsu University, No. 20, Zhengdong Road, Zhenjiang City, 212001, Jiangsu Province, China.
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23
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Bukłaho PA, Kiśluk J, Nikliński J. Diagnostics and treatment of ovarian cancer in the era of precision medicine - opportunities and challenges. Front Oncol 2023; 13:1227657. [PMID: 37746296 PMCID: PMC10516548 DOI: 10.3389/fonc.2023.1227657] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 08/21/2023] [Indexed: 09/26/2023] Open
Abstract
Due to predictions of increasing incidences and deaths from ovarian cancer, this neoplasm is a challenge for modern health care. The advent of NGS technology has made it possible to understand the molecular characteristics of many cancers, including ovarian cancer. The data obtained in research became the basis for the development of molecularly targeted therapies thus leading to the entry of NGS analysis into the diagnostic process of oncological patients. This review presents targeted therapies currently in preclinical or clinical trials, whose promising results offer hope for their use in clinical practice in the future. As more therapeutic options emerge, it will be necessary to modify molecular diagnostic regimens to select the best treatment for a given patient. New biomarkers are needed to predict the success of planned therapy. An important aspect of public health is molecular testing in women with a familial predisposition to ovarian cancer enabling patients to be included in prevention programs. NGS technology, despite its high throughput, poses many challenges, from the quality of the diagnostic material used for testing to the interpretation of results and classification of sequence variants. The article highlights the role of molecular testing in ongoing research and also its role in the diagnostic and therapeutic process in the era of personalized medicine. The spread of genetic testing in high-risk groups, the introduction of more targeted therapies and also the possibility of agnostic therapies could significantly improve the health situation for many women worldwide.
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Affiliation(s)
- Patrycja Aleksandra Bukłaho
- Department of Clinical Molecular Biology, Medical University of Bialystok, Bialystok, Poland
- Doctoral School, Medical University of Bialystok, Bialystok, Poland
| | - Joanna Kiśluk
- Department of Clinical Molecular Biology, Medical University of Bialystok, Bialystok, Poland
| | - Jacek Nikliński
- Department of Clinical Molecular Biology, Medical University of Bialystok, Bialystok, Poland
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24
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Yang D, Duan MH, Yuan QE, Li ZL, Luo CH, Cui LY, Li LC, Xiao Y, Zhu XY, Zhang HL, Feng GK, Liu GC, Deng R, Li JD, Zhu XF. Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors. J Transl Med 2023; 21:586. [PMID: 37658364 PMCID: PMC10472577 DOI: 10.1186/s12967-023-04422-x] [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: 03/29/2023] [Accepted: 08/06/2023] [Indexed: 09/03/2023] Open
Abstract
BACKGROUND As the most lethal gynecologic cancer, ovarian cancer (OV) holds the potential of being immunotherapy-responsive. However, only modest therapeutic effects have been achieved by immunotherapies such as immune checkpoint blockade. This study aims to propose a generalized stroma-immune prognostic signature (SIPS) to identify OV patients who may benefit from immunotherapy. METHODS The 2097 OV patients included in the study were significant with high-grade serous ovarian cancer in the III/IV stage. The 470 immune-related signatures were collected and analyzed by the Cox regression and Lasso algorithm to generalize a credible SIPS. Correlations between the SIPS signature and tumor microenvironment were further analyzed. The critical immunosuppressive role of stroma indicated by the SIPS was further validated by targeting the major suppressive stroma component (CAFs, Cancer-associated fibroblasts) in vitro and in vivo. With four machine-learning methods predicting tumor immune subtypes, the stroma-immune signature was upgraded to a 23-gene signature. RESULTS The SIPS effectively discriminated the high-risk individuals in the training and validating cohorts, where the high SIPS succeeded in predicting worse survival in several immunotherapy cohorts. The SIPS signature was positively correlated with stroma components, especially CAFs and immunosuppressive cells in the tumor microenvironment, indicating the critical suppressive stroma-immune network. The combination of CAFs' marker PDGFRB inhibitors and frontline PARP inhibitors substantially inhibited tumor growth and promoted the survival of OV-bearing mice. The stroma-immune signature was upgraded to a 23-gene signature to improve clinical utility. Several drug types that suppress stroma-immune signatures, such as EGFR inhibitors, could be candidates for potential immunotherapeutic combinations in ovarian cancer. CONCLUSIONS The stroma-immune signature could efficiently predict the immunotherapeutic sensitivity of OV patients. Immunotherapy and auxiliary drugs targeting stroma could enhance immunotherapeutic efficacy in ovarian cancer.
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Affiliation(s)
- Dong Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Mei-Han Duan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
- Department of Medical Imaging, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Qiu-Er Yuan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
- Department of Gynecological Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Zhi-Ling Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Chuang-Hua Luo
- Department of Gynecological Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Lan-Yue Cui
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Li-Chao Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Ying Xiao
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
- Department of Intensive Care Unit, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Xian-Ying Zhu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
- Department of Intensive Care Unit, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Hai-Liang Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Gong-Kan Feng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Guo-Chen Liu
- Department of Gynecological Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Rong Deng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China.
| | - Jun-Dong Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China.
- Department of Gynecological Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China.
| | - Xiao-Feng Zhu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China.
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Li Z, Peng L, Sun L, Si J. A link between mitochondrial damage and the immune microenvironment of delayed onset muscle soreness. BMC Med Genomics 2023; 16:196. [PMID: 37612729 PMCID: PMC10464284 DOI: 10.1186/s12920-023-01621-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 07/31/2023] [Indexed: 08/25/2023] Open
Abstract
BACKGROUND Delayed onset muscle soreness (DOMS) is a self-healing muscle pain disorder. Inflammatory pain is the main feature of DOMS. More and more researchers have realized that changes in mitochondrial morphology are related to pain. However, the role of mitochondria in the pathogenesis of DOMS and the abnormal immune microenvironment is still unknown. METHODS Mitochondria-related genes and gene expression data were obtained from MitoCarta3.0 and NCBI GEO databases. The network of mitochondrial function and the immune microenvironment of DOMS was constructed by computer algorithm. Subsequently, the skeletal muscle of DOMS rats was subjected to qPCR to verify the bioinformatics results. DOMS and non-DOMS histological samples were further studied by staining and transmission electron microscopy. RESULTS Bioinformatics results showed that expression of mitochondria-related genes was changed in DOMS. The results of qPCR showed that four hub genes (AMPK, PGC1-α, SLC25A25, and ARMCX1) were differentially expressed in DOMS. These hub genes are related to the degree of skeletal muscle immune cell infiltration, mitochondrial respiratory chain complex, DAMPs, the TCA cycle, and mitochondrial metabolism. Bayesian network inference showed that IL-6 and PGC1-α may be the main regulatory genes of mitochondrial damage in DOMS. Transmission electron microscopy revealed swelling of skeletal muscle mitochondria and disorganization of myofilaments. CONCLUSIONS Our study found that skeletal muscle mitochondrial damage is one of the causes of inflammatory factor accumulation in DOMS. According to the screened-out hub genes, this study provides a reference for follow-up clinical application.
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Affiliation(s)
- Zheng Li
- College of Sport Human Sciences, Harbin Sport University, No. 1, Dacheng Road, Nangang District, 150008, Harbin, China
| | - Lina Peng
- College of Sport Human Sciences, Harbin Sport University, No. 1, Dacheng Road, Nangang District, 150008, Harbin, China
| | - Lili Sun
- College of Sport Human Sciences, Harbin Sport University, No. 1, Dacheng Road, Nangang District, 150008, Harbin, China.
| | - Juncheng Si
- College of Sport Human Sciences, Harbin Sport University, No. 1, Dacheng Road, Nangang District, 150008, Harbin, China
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He X, Su Y, Liu P, Chen C, Chen C, Guan H, Lv X, Guo W. Machine learning-based immune prognostic model and ceRNA network construction for lung adenocarcinoma. J Cancer Res Clin Oncol 2023; 149:7379-7392. [PMID: 36939925 DOI: 10.1007/s00432-023-04609-1] [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: 10/20/2022] [Accepted: 01/27/2023] [Indexed: 03/21/2023]
Abstract
PURPOSE Lung adenocarcinoma (LUAD) is a malignant tumor with a high lethality rate. Immunotherapy has become a breakthrough in cancer treatment and improves patient survival and prognosis. Therefore, it is necessary to find new immune-related markers. However, the current research on immune-related markers in LUAD is not sufficient. Therefore, there is a need to find new immune-related biomarkers to help treat LUAD patients. METHODS In this study, a bioinformatics approach combined with a machine learning approach screened reliable immune-related markers to construct a prognostic model to predict the overall survival (OS) of LUAD patients, thus promoting the clinical application of immunotherapy in LUAD. The experimental data were obtained from The Cancer Genome Atlas (TCGA) database, including 535 LUAD and 59 healthy control samples. Firstly, the Hub gene was screened using a bioinformatics approach combined with the Support Vector Machine Recursive Feature Elimination algorithm; then, a multifactorial Cox regression analysis by constructing an immune prognostic model for LUAD and a nomogram to predict the OS rate of LUAD patients. Finally, the regulatory mechanism of Hub genes in LUAD was analyzed by ceRNA. RESULTS Five genes, ADM2, CDH17, DKK1, PTX3, and AC145343.1, were screened as potential immune-related genes in LUAD. Among them, ADM2 and AC145343.1 had a good prognosis in LUAD patients (HR < 1) and were novel markers. The remaining three genes screened were associated with poor prognosis in LUAD patients (HR > 1). In addition, the experimental results showed that patients in the low-risk group had better OS rates than those in the high-risk group (P < 0.001). CONCLUSION In this paper, we propose an immune prognostic model to predict OS rate in LUAD patients and show the correlation between five immune genes and the level of immune-related cell infiltration. It provides new markers and additional ideas for immunotherapy in patients with LUAD.
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Affiliation(s)
- Xiaoqian He
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Ying Su
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Pei Liu
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Cheng Chen
- College of Software, Xinjiang University, Urumqi, 830046, China.
| | - Chen Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Haoqin Guan
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Xiaoyi Lv
- College of Software, Xinjiang University, Urumqi, 830046, China.
| | - Wenjia Guo
- Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, 830011, China.
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27
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Xu PH, Chen S, Wang Y, Jin S, Wang J, Ye D, Zhu X, Shen Y. FGFR3 mutation characterization identifies prognostic and immune-related gene signatures in bladder cancer. Comput Biol Med 2023; 162:106976. [PMID: 37301098 DOI: 10.1016/j.compbiomed.2023.106976] [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: 10/11/2022] [Revised: 03/31/2023] [Accepted: 04/22/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND Immunotherapy and FGFR3-targeted therapy play an important role in the management of locally advanced and metastatic bladder cancer (BLCA). Previous studies indicated that FGFR3 mutation (mFGFR3) may be involved in the alterations of immune infiltration, which may affect the priority or combination of these two treatment regimes. However, the specific impact of mFGFR3 on the immunity and how FGFR3 regulates the immune response in BLCA to affect prognosis remain unclear. In this study, we aimed to elucidate the immune landscape associated with mFGFR3 status in BLCA, screen immune-related gene signatures with prognostic value, and construct and validate a prognostic model. METHODS ESTIMATE and TIMER were used to assess the immune infiltration within tumors in the TCGA BLCA cohort based on transcriptome data. Further, the mFGFR3 status and mRNA expression profiles were analyzed to identify immune-related genes that were differentially expressed between patients with BLCA with wild-type FGFR3 or mFGFR3 in the TCGA training cohort. An FGFR3-related immune prognostic score (FIPS) model was established in the TCGA training cohort. Furthermore, we validated the prognostic value of FIPS with microarray data in the GEO database and tissue microarray from our center. Multiple fluorescence immunohistochemical analysis was performed to confirm the relationship between FIPS and immune infiltration. RESULTS mFGFR3 resulted in differential immunity in BLCA. In total, 359 immune-related biological processes were enriched in the wild-type FGFR3 group, whereas none were enriched in the mFGFR3 group. FIPS could effectively distinguish high-risk patients with poor prognosis from low-risk patients. The high-risk group was characterized by a higher abundance of neutrophils; macrophages; and follicular helper, CD4, and CD8 T-cells than the low-risk group. In addition, the high-risk group exhibited higher expression of PD-L1, PD-1, CTLA-4, LAG-3, and TIM-3 than the low-risk group, indicating an immune-infiltrated but functionally suppressed immune microenvironment. Furthermore, patients in the high-risk group exhibited a lower mutation rate of FGFR3 than those in the low-risk group. CONCLUSIONS FIPS effectively predicted survival in BLCA. Patients with different FIPS exhibited diverse immune infiltration and mFGFR3 status. FIPS might be a promising tool for selecting targeted therapy and immunotherapy for patients with BLCA.
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Affiliation(s)
- Pei-Hang Xu
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Siyuan Chen
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China; Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yanhao Wang
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shengming Jin
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jun Wang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in Southern China, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
| | - Dingwei Ye
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Xiaodong Zhu
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China; Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
| | - Yijun Shen
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
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Sun Z, Chen X, Huang X, Wu Y, Shao L, Zhou S, Zheng Z, Lin Y, Chen S. Cuproptosis and Immune-Related Gene Signature Predicts Immunotherapy Response and Prognosis in Lung Adenocarcinoma. Life (Basel) 2023; 13:1583. [PMID: 37511958 PMCID: PMC10381686 DOI: 10.3390/life13071583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 07/07/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
Cuproptosis and associated immune-related genes (IRG) have been implicated in tumorigenesis and tumor progression. However, their effects on lung adenocarcinoma (LUAD) have not been elucidated. Therefore, we investigated the impact of cuproptosis-associated IRGs on the immunotherapy response and prognosis of LUAD using a bioinformatical approach and in vitro experiments analyzing clinical samples. Using the cuproptosis-associated IRG signature, we classified LUAD into two subtypes, cluster 1 and cluster 2, and identified three key cuproptosis-associated IRGs, NRAS, TRAV38-2DV8, and SORT1. These three genes were employed to establish a risk model and nomogram, and to classify the LUAD cohort into low- and high-risk subgroups. Biofunctional annotation revealed that cluster 2, remarkably downregulating epigenetic, stemness, and proliferation pathways activity, had a higher overall survival (OS) and immunoinfiltration abundance compared to cluster 1. Real-time quantitative PCR (RT-qPCR) validated the differential expression of these three genes in both subgroups. scRNA-seq demonstrated elevated expression of NRAS and SORT1 in macrophages. Immunity and oncogenic and stromal activation pathways were dramatically enriched in the low-risk subgroup, and patients in this subgroup responded better to immunotherapy. Our data suggest that the cuproptosis-associated IRG signature can be used to effectively predict the immunotherapy response and prognosis in LUAD. Our work provides enlightenment for immunotherapy response assessment, prognosis prediction, and the development of potential prognostic biomarkers for LUAD patients.
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Affiliation(s)
- Zihao Sun
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Xiujing Chen
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Xiaoning Huang
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Yanfen Wu
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Lijuan Shao
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Key Laboratory of Cancer Immunotherapy of Guangdong Higher Education Institutes, Guangzhou 510080, China
| | - Suna Zhou
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Zhu Zheng
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Yiguang Lin
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Key Laboratory of Cancer Immunotherapy of Guangdong Higher Education Institutes, Guangzhou 510080, China
- Research & Development Division, Guangzhou Anjie Biomedical Technology Co., Ltd., Guangzhou 510535, China
| | - Size Chen
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Key Laboratory of Cancer Immunotherapy of Guangdong Higher Education Institutes, Guangzhou 510080, China
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Lai W, Hu W, Liang Y, Yang L, Mao C, Tao T, Wang X, Xiao D, Liu S, Tao Y. New mouse genetic model of breast cancer from IKKα defects in dendritic cells revealed by single-cell RNA sequencing. Cell Discov 2023; 9:72. [PMID: 37460530 PMCID: PMC10352231 DOI: 10.1038/s41421-023-00553-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 04/12/2023] [Indexed: 07/20/2023] Open
Affiliation(s)
- Weiwei Lai
- NHC Key Laboratory of Carcinogenesis, Cancer Research Institute and School of Basic Medicine, Department of Pathology, Xiangya Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Central South University, Changsha, Hunan, China
| | - Wanshan Hu
- NHC Key Laboratory of Carcinogenesis, Cancer Research Institute and School of Basic Medicine, Department of Pathology, Xiangya Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Central South University, Changsha, Hunan, China
| | - Yinming Liang
- Laboratory of Genetic Regulators in the Immune System, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, Henan, China
| | - Lifang Yang
- NHC Key Laboratory of Carcinogenesis, Cancer Research Institute and School of Basic Medicine, Department of Pathology, Xiangya Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Central South University, Changsha, Hunan, China
| | - Chao Mao
- NHC Key Laboratory of Carcinogenesis, Cancer Research Institute and School of Basic Medicine, Department of Pathology, Xiangya Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Central South University, Changsha, Hunan, China
| | - Tania Tao
- NHC Key Laboratory of Carcinogenesis, Cancer Research Institute and School of Basic Medicine, Department of Pathology, Xiangya Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Central South University, Changsha, Hunan, China
| | - Xiang Wang
- Department of Thoracic Surgery, Hunan Key Laboratory of Tumor Models and Individualized Medicine, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Desheng Xiao
- NHC Key Laboratory of Carcinogenesis, Cancer Research Institute and School of Basic Medicine, Department of Pathology, Xiangya Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Central South University, Changsha, Hunan, China.
| | - Shuang Liu
- Department of Oncology, Institute of Medical Sciences, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Yongguang Tao
- NHC Key Laboratory of Carcinogenesis, Cancer Research Institute and School of Basic Medicine, Department of Pathology, Xiangya Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Central South University, Changsha, Hunan, China.
- Department of Oncology, Institute of Medical Sciences, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
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30
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Shi Y, Jing B, Xi R. Comprehensive analysis of neoantigens derived from structural variation across whole genomes from 2528 tumors. Genome Biol 2023; 24:169. [PMID: 37461029 DOI: 10.1186/s13059-023-03005-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 07/02/2023] [Indexed: 07/20/2023] Open
Abstract
BACKGROUND Neoantigens are critical for anti-tumor immunity and have been long-envisioned as promising therapeutic targets. However, current neoantigen analyses mostly focus on single nucleotide variations (SNVs) and indel mutations and seldom consider structural variations (SVs) that are also prevalent in cancer. RESULTS Here, we develop a computational method termed NeoSV, which incorporates SV annotation, protein fragmentation, and MHC binding prediction together, to predict SV-derived neoantigens. Analysis of 2528 whole genomes reveals that SVs significantly contribute to the neoantigen repertoire in both quantity and quality. Whereas most neoantigens are patient-specific, shared neoantigens are identified with high occurrence rates in breast, ovarian, and gastrointestinal cancers. We observe extensive immunoediting on SV-derived neoantigens, especially on clonal events, which suggests their immunogenic potential. We also demonstrate that genomic alteration-related neoantigen burden, which integrates SV-derived neoantigens, depicts the tumor-immune interplay better than tumor neoantigen burden and may improve patient selection for immunotherapy. CONCLUSIONS Our study fills the gap in the current neoantigen repertoire and provides a valuable resource for cancer vaccine development.
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Affiliation(s)
- Yang Shi
- School of Mathematical Sciences, Peking University, Beijing, China
| | - Biyang Jing
- School of Life Sciences, Peking University, Beijing, China
| | - Ruibin Xi
- School of Mathematical Sciences, Peking University, Beijing, China.
- Center for Statistical Science, Peking University, Beijing, China.
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31
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Zheng PF, Hong XQ, Liu ZY, Zheng ZF, Liu P, Chen LZ. m6A regulator-mediated RNA methylation modification patterns are involved in the regulation of the immune microenvironment in ischaemic cardiomyopathy. Sci Rep 2023; 13:5904. [PMID: 37041267 PMCID: PMC10090050 DOI: 10.1038/s41598-023-32919-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 04/04/2023] [Indexed: 04/13/2023] Open
Abstract
The role of RNA N6-methyladenosine (m6A) modification in the regulation of the immune microenvironment in ischaemic cardiomyopathy (ICM) remains largely unclear. This study first identified differential m6A regulators between ICM and healthy samples, and then systematically evaluated the effects of m6A modification on the characteristics of the immune microenvironment in ICM, including the infiltration of immune cells, the human leukocyte antigen (HLA) gene, and HALLMARKS pathways. A total of seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15 and YTHDF3, were identified using a random forest classifier. A diagnostic nomogram based on these seven key m6A regulators could effectively distinguish patients with ICM from healthy subjects. We further identified two distinct m6A modification patterns (m6A cluster-A and m6A cluster-B) that are mediated by these seven regulators. Meanwhile, we also noted that one m6A regulator, WTAP, was gradually upregulated, while the others were gradually downregulated in the m6A cluster-A vs. m6A cluster-B vs. healthy subjects. In addition, we observed that the degree of infiltration of the activated dendritic cells, macrophages, natural killer (NK) T cells, and type-17 T helper (Th17) cells gradually increased in m6A cluster-A vs. m6A cluster-B vs. healthy subjects. Furthermore, m6A regulators, including FTO, YTHDC1, YTHDF3, FMR1, ZC3H13, and RBM15 were significantly negatively correlated with the above-mentioned immune cells. Additionally, several differential HLA genes and HALLMARKS signalling pathways between the m6A cluster-A and m6A cluster-B groups were also identified. These results suggest that m6A modification plays a key role in the complexity and diversity of the immune microenvironment in ICM, and seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15, and YTHDF3, may be novel biomarkers for the accurate diagnosis of ICM. Immunotyping of patients with ICM will help to develop immunotherapy strategies with a higher level of accuracy for patients with a significant immune response.
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Affiliation(s)
- Peng-Fei Zheng
- Cardiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, ChangshaHunan, 410000, China
- Clinical Research Center for Heart Failure in Hunan Province, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
- Epidemiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Xiu-Qin Hong
- Clinical Research Center for Heart Failure in Hunan Province, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
- Epidemiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Zheng-Yu Liu
- Cardiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, ChangshaHunan, 410000, China
- Clinical Research Center for Heart Failure in Hunan Province, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
- Epidemiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Zhao-Fen Zheng
- Cardiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, ChangshaHunan, 410000, China
- Clinical Research Center for Heart Failure in Hunan Province, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
- Epidemiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Peng Liu
- Department of Cardiology, The Central Hospital of ShaoYang, No. 36 QianYuan Lane, Daxiang District, Shaoyang, 422000, Hunan, China.
| | - Lu-Zhu Chen
- Department of Cardiology, The Central Hospital of ShaoYang, No. 36 QianYuan Lane, Daxiang District, Shaoyang, 422000, Hunan, China.
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Pirrotta S, Masatti L, Corrà A, Pedrini F, Esposito G, Martini P, Risso D, Romualdi C, Calura E. signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.07.530940. [PMID: 36945491 PMCID: PMC10028855 DOI: 10.1101/2023.03.07.530940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Over the last decade, many studies and some clinical trials have proposed gene expression signatures as a valuable tool for understanding cancer mechanisms, defining subtypes, monitoring patient prognosis, and therapy efficacy. However, technical and biological concerns about reproducibility have been raised. Technical reproducibility is a major concern: we currently lack a computational implementation of the proposed signatures, which would provide detailed signature definition and assure reproducibility, dissemination, and usability of the classifier. Another concern regards intratumor heterogeneity, which has never been addressed when studying these types of biomarkers using bulk transcriptomics. With the aim of providing a tool able to improve the reproducibility and usability of gene expression signatures, we propose signifinder, an R package that provides the infrastructure to collect, implement, and compare expression-based signatures from cancer literature. The included signatures cover a wide range of biological processes from metabolism and programmed cell death, to morphological changes, such as quantification of epithelial or mesenchymal-like status. Collected signatures can score tumor cell characteristics, such as the predicted response to therapy or the survival association, and can quantify microenvironmental information, including hypoxia and immune response activity. signifinder has been used to characterize tumor samples and to investigate intra-tumor heterogeneity, extending its application to single-cell and spatial transcriptomic data. Through these higher-resolution technologies, it has become increasingly apparent that the single-sample score assessment obtained by transcriptional signatures is conditioned by the phenotypic and genetic intratumor heterogeneity of tumor masses. Since the characteristics of the most abundant cell type or clone might not necessarily predict the properties of mixed populations, signature prediction efficacy is lowered, thus impeding effective clinical diagnostics. Through signifinder, we offer general principles for interpreting and comparing transcriptional signatures, as well as suggestions for additional signatures that would allow for more complete and robust data inferences. We consider signifinder a useful tool to pave the way for reproducibility and comparison of transcriptional signatures in oncology.
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Affiliation(s)
| | - Laura Masatti
- Department of Biology, University of Padua, Padua, Italy
| | - Anna Corrà
- Department of Biology, University of Padua, Padua, Italy
| | | | - Giovanni Esposito
- Immunology and Molecular Oncology Diagnostic Unit of The Veneto Institute of Oncology IOV – IRCCS, Padua, Italy
| | - Paolo Martini
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Davide Risso
- Department of Statistical Sciences, University of Padua, Italy
| | | | - Enrica Calura
- Department of Biology, University of Padua, Padua, Italy
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Li S, Liu H, Ruan Z, Guo R, Sun C, Tang Y, Huang X, Gao T, Hao S, Li H, Song N, Su Y, Ning F, Li Z, Chang T. Landscape analysis of m6A modification regulators related biological functions and immune characteristics in myasthenia gravis. J Transl Med 2023; 21:166. [PMID: 36864526 PMCID: PMC9983271 DOI: 10.1186/s12967-023-03947-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 02/01/2023] [Indexed: 03/04/2023] Open
Abstract
BACKGROUND N6-methyladenosine (m6A) modification has been recognized to play fundamental roles in the development of autoimmune diseases. However, the implication of m6A modification in myasthenia gravis (MG) remains largely unknown. Thus, we aimed to systematically explore the potential functions and related immune characteristics of m6A regulators in MG. METHODS The GSE85452 dataset with MG and healthy samples was downloaded from Gene Expression Omnibus (GEO) database. m6A modification regulators were manually curated. The targets of m6A regulators were obtained from m6A2Target database. The differential expressed m6A regulators in GSE85452 dataset were identified by "limma" package and were validated by RT-PCR. Function enrichment analysis of dysregulated m6A regulators was performed using "clusterProfiler" package. Correlation analysis was applied for analyzing the relationships between m6A regulators and immune characteristics. Unsupervised clustering analysis was used to identify distinct m6A modification subtypes. The differences between subtypes were analyzed, including the expression level of all genes and the enrichment degree of immune characteristics. Weighted gene co-expression network analysis (WGCNA) was conducted to obtain modules associated with m6A modification subtypes. RESULTS We found that CBLL1, RBM15 and YTHDF1 were upregulated in MG samples of GSE85452 dataset, and the results were verified by RT-PCR in blood samples from19 MG patients and 19 controls. The targeted genes common modified by CBLL1, RBM15, and YTHDF1 were mainly enriched in histone modification and Wnt signaling pathway. Correlation analysis showed that three dysregulated m6A regulators were closely associated with immune characteristics. Among them, RBM15 possessed the strongest correlation with immune characteristics, including CD56dim natural killer cell (r = 0.77, P = 0.0023), T follicular helper cell (r = - 0.86, P = 0.0002), Interferon Receptor (r = 0.78, P = 0.0017), and HLA-DOA (r = 0.64, P = 0.0200). Further two distinct m6A modification patterns mediated by three dysregulated m6A regulators was identified. Bioinformatics analysis found that there were 3029 differentially expressed genes and different immune characteristics between two m6A modification patterns. Finally, WGCNA analysis obtained a total of 12 modules and yellow module was the most positively correlated to subtype-2. CONCLUSION Our findings suggested that m6A RNA modification had an important effect on immunity molecular mechanism of MG and provided a new perspective into understanding the pathogenesis of MG.
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Affiliation(s)
- Shuang Li
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Hui Liu
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China.,Xi'an Medical University, Xi'an, 710021, Shaanxi, China
| | - Zhe Ruan
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Rongjing Guo
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Chao Sun
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Yonglan Tang
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Xiaoxi Huang
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Ting Gao
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Sijia Hao
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Huanhuan Li
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Na Song
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Yue Su
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Fan Ning
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Zhuyi Li
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China
| | - Ting Chang
- Department of Neurology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, 710038, Shaanxi, China.
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Li T, Jiang N, Bai Y, Liu T, Zhao Z, Xu X, Zhang Y, Wei F, Sun R, Liu S, Li J, Guo H, Yang R. Prediction of immune infiltration and prognosis for patients with urothelial bladder cancer based on the DNA damage repair-related genes signature. Heliyon 2023; 9:e13661. [PMID: 36873527 PMCID: PMC9976330 DOI: 10.1016/j.heliyon.2023.e13661] [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: 05/22/2022] [Revised: 01/30/2023] [Accepted: 02/07/2023] [Indexed: 02/15/2023] Open
Abstract
Objectives To analyze the correlations between the expression and effect of DNA damage repair genes and the immune status and clinical outcomes of urothelial bladder cancer (BLCA) patients. In addition, we evaluate the efficacy and value of utilizing the DNA damage repair genes signature as a prognosis model for BLCA. Methods Two subtype groups (C1 and C2) were produced based on the varied expression of DNA damage repair genes. Significantly differentiated genes and predicted enriched gene pathways were obtained between the two subtypes. Seven key genes were obtained from the DNA damage repair-related genes and a 7-gene signature prognosis model was established based on the key genes. The efficacy and accuracy of this model in prognosis prediction was evaluated and verified in two independent databases. Also, the difference in biological functions, drug sensitivity, immune infiltration and affinity between the high-risk group and low-risk group was analyzed. Results The DNA damage repair gene signature could significantly differentiate the BLCA into two molecular subgroups with varied genetic expression and enriched gene pathways. Seven key genes were screened out from the 232 candidate genes for prognosis prediction and a 7-gene signature prognosis model was established based on them. Two independent patient cohorts (TCGA cohort and GEO cohort) were utilized to validate the efficacy of the prognosis model, which demonstrated an effective capability to differentiate and predict the overall survival of BLCA patients. Also, the high-risk group and low-risk group derived from the 7-gene model exhibited significantly differences in drug sensitivity, immune infiltration status and biological pathways enrichment. Conclusions Our established 7-gene signature model based on the DNA damage repair genes could serve as a novel prognosis predictive tool for BLCA. The differentiation of BLCA patients based on the 7-gene signature model may be of great value for the appropriate selection of specific chemotherapy agents and immune-checkpoint blockade therapy administration.
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Affiliation(s)
- Tianhang Li
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Ning Jiang
- Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, China
| | - Yuhao Bai
- Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, China
| | - Tianyao Liu
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Zihan Zhao
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Xinyan Xu
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Yulin Zhang
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Fayun Wei
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Rui Sun
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Siyang Liu
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Jiazheng Li
- Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China
| | - Hongqian Guo
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
| | - Rong Yang
- Department of Urology, Affiliated Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, China
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MARCO is a potential prognostic and immunotherapy biomarker. Int Immunopharmacol 2023; 116:109783. [PMID: 36773567 DOI: 10.1016/j.intimp.2023.109783] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 01/11/2023] [Accepted: 01/21/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Macrophage receptor with collagenous structure (MARCO), a novel immune checkpoint expressed on tumor-associated macrophages, has antitumor therapeutic properties. However, the association between MARCO and patient prognosis, immune infiltration, and ICI immunotherapy needs to be studied urgently. METHODS MARCO distribution in cancer tissues was investigated using the TCGA and GTEx databases. The PrognoScan and KM Plotter databases was used to assess the MARCO prognosis. TIMER2.0, GEPIA, cBioPortal, and GSEA all confirmed the link between MARCO and immune infiltration, mutation profile, and enrichment pathway analysis. Data visualization was implemented by R language. RESULTS In general, MARCO had a substantial impact on the prognosis of cancer patients and was expressed differently in cancer and adjacent normal tissues. High expression of MARCO was associated with poorer OS in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), lung squamous cell carcinoma (LUSC), colon adenocarcinoma (COAD), and prostate adenocarcinoma (PRAD). However, high expression of MARCO had a better PFI in brain lower-grade glioma (LGG) and skin cutaneous melanoma (SKCM). We discovered that MARCO expression was lowest in pancreatic adenocarcinoma (PAAD) and rectum adenocarcinoma (READ) stage 1, BLCA stage 2, LUSC and stomach adenocarcinoma (STAD) stage 3, and liver hepatocellular carcinoma (LIHC) stage 4. Subsequently, we analyzed the correlation between MARCO and 47 immune checkpoints and observed that MARCO was positively connected with CD80, CD86, and leukocyte-associated immunoglobulin-like receptor 1(LAIR1) in most cancers. In COAD, MARCO has the most microsatellite instability (MSI). In addition, we discovered that high expression of MARCO patients had a better prognosis after immune checkpoint inhibitor (ICI) treatment in SKCM. Finally, GSEA revealed a significant correlation between MARCO and TNF/NFκB signaling, KRAS signaling, PI3K/AKT/mTOR pathway, IL-6-STAT3 signaling, TGFβ pathway, and p53 pathway. CONCLUSION This study comprehensively investigated the relationship between MARCO and clinical prognosis, immune infiltration, and ICI immunotherapy in various cancers. We demonstrated the potential of MARCO as an emerging biomarker, exploring new avenues for future tumor immunotherapy.
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Zheng PF, Zhou SY, Zhong CQ, Zheng ZF, Liu ZY, Pan HW, Peng JQ. Identification of m6A regulator-mediated RNA methylation modification patterns and key immune-related genes involved in atrial fibrillation. Aging (Albany NY) 2023; 15:1371-1393. [PMID: 36863715 PMCID: PMC10042702 DOI: 10.18632/aging.204537] [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: 11/28/2022] [Accepted: 02/11/2023] [Indexed: 03/04/2023]
Abstract
The role of m6A in the regulation of the immune microenvironment in atrial fibrillation (AF) remains unclear. This study systematically evaluated the RNA modification patterns mediated by differential m6A regulators in 62 AF samples, identified the pattern of immune cell infiltration in AF and identified several immune-related genes associated with AF. A total of six key differential m6A regulators between healthy subjects and AF patients were identified by the random forest classifier. Three distinct RNA modification patterns (m6A cluster-A, -B and -C) among AF samples were identified based on the expression of 6 key m6A regulators. Differential infiltrating immune cells and HALLMARKS signaling pathways between normal and AF samples as well as among samples with three distinct m6A modification patterns were identified. A total of 16 overlapping key genes were identified by weighted gene coexpression network analysis (WGCNA) combined with two machine learning methods. The expression levels of the NCF2 and HCST genes were different between controls and AF patient samples as well as among samples with the distinct m6A modification patterns. RT-qPCR also proved that the expression of NCF2 and HCST was significantly increased in AF patients compared with control participants. These results suggested that m6A modification plays a key role in the complexity and diversity of the immune microenvironment of AF. Immunotyping of patients with AF will help to develop more accurate immunotherapy strategies for those with a significant immune response. The NCF2 and HCST genes may be novel biomarkers for the accurate diagnosis and immunotherapy of AF.
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Affiliation(s)
- Peng-Fei Zheng
- Cardiology Department, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
- Clinical Research Center for Heart Failure in Hunan Province, Furong, Changsha 410000, Hunan, China
- Institute of Cardiovascular Epidemiology, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
| | - Sen-Yu Zhou
- Institute of Cardiovascular Epidemiology, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
- The First Affiliated Hospital of Hunan Normal University (Hunan Provincial People’s Hospital), Furong, Changsha 410000, Hunan, China
| | - Chang-Qing Zhong
- Cardiology Department, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
- Clinical Research Center for Heart Failure in Hunan Province, Furong, Changsha 410000, Hunan, China
- Institute of Cardiovascular Epidemiology, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
| | - Zhao-Fen Zheng
- Cardiology Department, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
- Clinical Research Center for Heart Failure in Hunan Province, Furong, Changsha 410000, Hunan, China
- Institute of Cardiovascular Epidemiology, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
| | - Zheng-Yu Liu
- Cardiology Department, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
- Clinical Research Center for Heart Failure in Hunan Province, Furong, Changsha 410000, Hunan, China
- Institute of Cardiovascular Epidemiology, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
| | - Hong-Wei Pan
- Cardiology Department, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
- Clinical Research Center for Heart Failure in Hunan Province, Furong, Changsha 410000, Hunan, China
- Institute of Cardiovascular Epidemiology, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
| | - Jian-Qiang Peng
- Cardiology Department, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
- Clinical Research Center for Heart Failure in Hunan Province, Furong, Changsha 410000, Hunan, China
- Institute of Cardiovascular Epidemiology, Hunan Provincial People’s Hospital, Furong, Changsha 410000, Hunan, China
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Guo Z, Qi X, Li Z, Yang J, Sun Z, Li P, Chen M, Cao Y. Development and validation of an immune-related gene signature for prognosis in Lung adenocarcinoma. IET Syst Biol 2023; 17:27-38. [PMID: 36728032 PMCID: PMC9931057 DOI: 10.1049/syb2.12057] [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: 04/19/2022] [Revised: 12/26/2022] [Accepted: 01/06/2023] [Indexed: 02/03/2023] Open
Abstract
The most common type of lung cancer tissue is lung adenocarcinoma. The TCGA-LUAD cohort retrieved from the TCGA dataset was considered the internal training cohort, while GSE68465 and GSE13213 datasets from the GEO database were used as the external test cohort. The TCGA-LUAD cohort was classified into two immune subtypes using single-sample gene set enrichment analysis of the immune gene set and unsupervised clustering analysis. The ESTIMATE algorithm, the CIBERSORT algorithm, and HLA family expression levels again validated the reliability of this typing. We performed Venn analysis using immune-related genes from the immport dataset and differentially expressed genes from the subtypes to retrieve differentially expressed immune genes (DEIGs). In addition, DEIGs were used to construct a prognostic model with the least absolute shrinkage and selection operator regression analysis. A reliable risk model consisting of 11 DEIGs, including S100P, INHA, SEMA7A, INSL4, CD40LG, AGER, SERPIND1, CD1D, CX3CR1, SFTPD, and CD79A, was then built, and its reliability was further confirmed by ROC curve and calibration plot analysis. The high-risk score subgroup had a poor prognosis and a lower tumour immune dysfunction and exclusion score, indicating a greater likelihood of anti-PD-1/cytotoxic T lymphocyte antigen 4 benefit.
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Affiliation(s)
- Zehuai Guo
- The First Clinical School of Guangzhou University of Chinese MedicineGuangzhouChina
| | - Xiangjun Qi
- The First Clinical School of Guangzhou University of Chinese MedicineGuangzhouChina
| | - Zeyun Li
- The First Clinical School of Guangzhou University of Chinese MedicineGuangzhouChina
| | - Jianying Yang
- The First Clinical School of Guangzhou University of Chinese MedicineGuangzhouChina
| | - Zhe Sun
- The First Clinical School of Guangzhou University of Chinese MedicineGuangzhouChina
| | - Peiqin Li
- The First Clinical School of Guangzhou University of Chinese MedicineGuangzhouChina
| | - Ming Chen
- The First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhouChina
| | - Yang Cao
- The First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhouChina
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Su X, Gao H, Qi Z, Xu T, Wang G, Luo H, Cheng P. Prediction of immune subtypes and overall survival in lung squamous cell carcinoma. Curr Med Res Opin 2023; 39:289-298. [PMID: 36245361 DOI: 10.1080/03007995.2022.2129231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
OBJECTIVE Lung squamous cell carcinoma (LUSC), one of the most common subtypes of lung cancer, is a leading cause of cancer-caused deaths in the world. It has been well demonstrated that a deep understanding of the tumor environment in cancer would be helpful to predict the prognosis of patients. This study aimed to evaluate the tumor environment in LUSC, and to construct an efficient prognosis model involved in specific subtypes. METHODS Four expression files were downloaded from the Gene Expression Omnibus (GEO) database. Three datasets (GSE19188, GSE2088, GSE6044) were considered as the testing group and the other dataset (GSE11969) was used as the validation group. By performing LUSC immune subtype consensus clustering (CC), LUSC patients were separated into two immune subtypes comprising subtype 1 (S1) and subtype 2 (S2). Weighted gene co-expression network (WGCNA) and least absolute shrinkage and selection operator (LASSO) were performed to identify and narrow down the key genes among subtype 1 related genes that were closely related to the overall survival (OS) of LUSC patients. Using immune subtype related genes, a prognostic model was also constructed to predict the OS of LUSC patients. RESULTS It showed that LUSC patients in the S1 immune subtype exhibited a better OS than in the S2 immune subtype. WGCNA and LASSO analyses screened out important immune subtype related genes in specific modules that were closely associated with LUSC prognosis, followed by construction of the prognostic model. Both the testing datasets and validation dataset confirmed that the prognostic model could be efficiently used to predict the OS of LUSC patients in subtype 1. CONCLUSION We explored the tumor environment in LUSC and established a risk prognostic model that might have the potential to be applied in clinical practice.
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Affiliation(s)
- Xiaomei Su
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Hui Gao
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Zhongchun Qi
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Tao Xu
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Guangjie Wang
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Hong Luo
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
| | - Peng Cheng
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu City, Sichuan Province, P.R. China
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Fan W, Chen X, Li R, Zheng R, Wang Y, Guo Y. A prognostic risk model for ovarian cancer based on gene expression profiles from gene expression omnibus database. Biochem Genet 2023; 61:138-150. [PMID: 35761155 DOI: 10.1007/s10528-022-10232-5] [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: 11/25/2021] [Accepted: 04/18/2022] [Indexed: 01/24/2023]
Abstract
This study explored prognostic genes of ovarian cancer and built a prognostic model based on these genes to predict patient's survival, which is of great significance for improving treatment of ovarian cancer. GSE26712 dataset was downloaded from Gene Expression Omnibus database as training set, while OV-AU dataset was downloaded from ICGC website as validation set. All genes in GSE26712 were analyzed by univariate Cox regression, Lasso regression, and multivariate Cox regression analyses. Then prognosis-related feature genes were screened to construct a multivariate risk model. Meanwhile, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed on samples in the high/low-risk groups using Gene Set Enrichment Analysis (GSEA) software. Finally, survival curve and receiver operating characteristic curve were drawn to verify the validity of the model. Ten feature genes related to prognosis of ovarian cancer were obtained: CMTM6, COLGALT1, F2R, GPR39, IGFBP3, RNF121, MTMR9, ORAI2, SNAI2, ZBTB16. GSEA enrichment analysis showed that there were notable differences in biological pathways such as gap junctions and homologous recombination between the high/low-risk groups. Through further verification of training set and validation set, the 10-gene prognostic model was found to be effective for the prognosis of ovarian cancer patients. In this study, we constructed a 10-gene prognostic model which predicted the prognosis of ovarian cancer patients well by integrating clinical prognostic parameters. It may have certain reference value for subsequent clinical treatment research of ovarian cancer patients and help in clinical treatment decision-making.
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Affiliation(s)
- Wei Fan
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China
| | - Xiaoyun Chen
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China
| | - Ruiping Li
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China
| | - Rongfang Zheng
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China
| | - Yunyun Wang
- Lanzhou University Second Hospital, Lanzhou City, 730030, Gansu Province, China
| | - Yuzhen Guo
- Department of Gynecology, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou City, 730030, Gansu Province, China.
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Peng H, Li X, Luan Y, Wang C, Wang W. A novel prognostic model related to oxidative stress for treatment prediction in lung adenocarcinoma. Front Oncol 2023; 13:1078697. [PMID: 36798829 PMCID: PMC9927401 DOI: 10.3389/fonc.2023.1078697] [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: 10/24/2022] [Accepted: 01/05/2023] [Indexed: 02/01/2023] Open
Abstract
Background The prognostic model based on oxidative stress for lung adenocarcinoma (LUAD) remains unclear. Methods The information of LUAD patients were acquired from TCGA dataset. We also collected two external datasets from GEO for verification. Oxidative stress-related genes (ORGs) were extracted from Genecards. We performed machine learning algorithms, including Univariate Cox regression, Random Survival Forest, and Least Absolute Shrinkage and Selection Operator (Lasso) analyses on the ORGs to build the OS-score and OS-signature. We drew the Kaplan-Meier and time-dependent receiver operating characteristic curve (ROC) to evaluate the efficacy of the OS-signature in predicting the prognosis of LUAD. We used GISTIC 2.0 and maftool algorithms to explore Genomic mutation of OS-signature. To analyze characteristic of tumor infiltrating immune cells, ESTIMATE, TIMER2.0, MCPcounter and ssGSEA algorithms were applied, thus evaluating the immunotherapeutic strategies. Chemotherapeutics sensitivity analysis was based on pRRophetic package. Finally, PCR assays was also used to detect the expression values of related genes in the OS-signature in cell lines. Results Ten ORGs with prognostic value and the OS-signature containing three prognostic ORGs were identified. The significantly better prognosis of LUAD patients was observed in LUAD patients. The efficiency and accuracy of OS-signature in predicting prognosis for LUAD patients was confirmed by survival ROC curves and two external validation data sets. It was clearly observed that patients with high OS-scores had lower immunomodulators levels (with a few exceptions), stromal score, immune score, ESTIMATE score and infiltrating immune cell populations. On the contrary, patients with higher OS-scores were more likely to have higher tumor purity. PCR assays showed that, MRPL44 and CYCS were significantly higher expressed in LUAD cell lines, while CAT was significantly lower expressed. Conclusion The novel oxidative stress-related model we identified could be used for prognosis and treatment prediction in lung adenocarcinoma.
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Affiliation(s)
| | | | | | | | - Wei Wang
- Department of Thoracic Surgery, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, Shijiazhuang, Hebei, China
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Wu X, Xie W, Gong B, Fu B, Chen W, Zhou L, Luo L. Development of a TGF-β signaling-related genes signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma. Front Oncol 2023; 13:1124080. [PMID: 36776317 PMCID: PMC9911835 DOI: 10.3389/fonc.2023.1124080] [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: 12/14/2022] [Accepted: 01/16/2023] [Indexed: 01/28/2023] Open
Abstract
Background Transforming growth factor (TGF)-β signaling is strongly related to the development and progression of tumor. We aimed to construct a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical prognosis and immunotherapy responses of patients with clear cell renal cell carcinoma (ccRCC). Methods The gene expression profiles and corresponding clinical information of ccRCC were collected from the TCGA and the ArrayExpress (E-MTAB-1980) databases. LASSO, univariate and multivariate Cox regression analyses were conducted to construct a prognostic signature in the TCGA cohort. The E-MTAB-1980 cohort were used for validation. Kaplan-Meier (K-M) survival and time-dependent receiver operating characteristic (ROC) were conducted to assess effectiveness and reliability of the signature. The differences in gene enrichments, immune cell infiltration, and expression of immune checkpoints in ccRCC patients showing different risks were investigated. Results We constructed a seven gene (PML, CDKN2B, COL1A2, CHRDL1, HPGD, CGN and TGFBR3) signature, which divided the ccRCC patients into high risk group and low risk group. The K-M analysis indicated that patients in the high risk group had a significantly shorter overall survival (OS) time than that in the low risk group in the TCGA (p < 0.001) and E-MTAB-1980 (p = 0.012). The AUC of the signature reached 0.77 at 1 year, 0.7 at 3 years, and 0.71 at 5 years in the TCGA, respectively, and reached 0.69 at 1 year, 0.72 at 3 years, and 0.75 at 5 years in the E-MTAB-1980, respectively. Further analyses confirmed the risk score as an independent prognostic factor for ccRCC (p < 0.001). The results of ssGSEA that immune cell infiltration degree and the scores of immune-related functions were significantly increased in the high risk group. The CIBERSORT analysis indicated that the abundance of immune cell were significantly different between two risk groups. Furthermore, The risk score was positively related to the expression of PD-1, CTLA4 and LAG3.These results indicated that patients in the high risk group benefit more from immunotherapy. Conclusion We constructed a novel TGF-β signaling-related genes signature that could serve as an promising independent factor for predicting clinical prognosis and immunotherapy responses in ccRCC patients.
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Gu Y, Wang Z, Wang R, Yang Y, Tong P, Lv S, Xiao L, Wang Z. N6-methyladenine regulator-mediated RNA methylation modification patterns in immune microenvironment regulation of osteoarthritis. Front Genet 2023; 14:1113515. [PMID: 36777725 PMCID: PMC9908960 DOI: 10.3389/fgene.2023.1113515] [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: 12/01/2022] [Accepted: 01/13/2023] [Indexed: 01/27/2023] Open
Abstract
Background: Osteoarthritis is a common chronic degenerative disease, and recently, an increasing number of studies have shown that immunity plays an important role in the progression of osteoarthritis, which is exacerbated by local inflammation. The role of N6-methyladenine (m6A) modification in immunity is being explored. However, the role of m6A modification in regulating the immune microenvironment of osteoarthritis remains unknown. In this study, we sought to discuss the association between the N6-methyladenine (m6A) modification and the immune microenvironment of osteoarthritis. Methods: First, the data and gene expression profiles of 139 samples, including 33 healthy samples and 106 osteoarthritis samples, were obtained from the Genetics osteoARthritis and Progression (GARP) study. Then the differences in m6A regulators between healthy individuals and osteoarthritis patients were analyzed. The correlation between m6A regulators and immune characteristics was also investigated by single-sample gene set enrichment analysis (ssGSEA). Principal component analysis (PCA), Gene Set Variation Analysis (GSVA) enrichment analysis, weighted gene coexpression network analysis (WGCNA), and Associated R packages were used to identify the m6A phenotype and its biological functions. Results: A total of 23 m6A regulators were involved in this study. We found a close correlation between most m6A regulators in all samples as well as in osteoarthritis samples. VIRMA and LRPPRC were the most highly correlated m6A regulators and showed a positive correlation, whereas VIRMA and RBM15B were the most negatively correlated. M6A regulators are associated with osteoarthritis immune characteristics. For example, MDSC cell abundance was strongly correlated with RBM15B and HNRNPC. Meanwhile, RBM15B and HNRNPC were important effectors of natural killer cell immune responses. IGFBP3 is an important regulator of cytolytic activity immune function. We performed an unsupervised consensus cluster analysis of the osteoarthritis samples based on the expression of 23 m6A regulators. Three different m6A subtypes of osteoarthritis were identified, including 27 samples in subtype C1, 21 samples in subtype C2, and 58 samples in subtype C3. Different m6A subtypes have unique biological pathways and play different roles in the immune microenvironment of osteoarthritis. Conclusion: The m6A modification plays a crucial role in the diversity and complexity of the immune microenvironment in osteoarthritis.
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Affiliation(s)
- Yong Gu
- Translational Medical Innovation Center, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, China,Department of Orthopedics, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, China
| | - Zhengming Wang
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China,Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Rui Wang
- The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Chinese Medicine, Hangzhou, China
| | - Yunshang Yang
- Translational Medical Innovation Center, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, China,Department of Orthopedics, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, China
| | - Peijian Tong
- The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Chinese Medicine, Hangzhou, China
| | - Shuaijie Lv
- The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Chinese Medicine, Hangzhou, China,*Correspondence: Zhirong Wang, ; Long Xiao, ; Shuaijie Lv,
| | - Long Xiao
- Translational Medical Innovation Center, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, China,Department of Orthopedics, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, China,*Correspondence: Zhirong Wang, ; Long Xiao, ; Shuaijie Lv,
| | - Zhirong Wang
- Translational Medical Innovation Center, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, China,Department of Orthopedics, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, China,*Correspondence: Zhirong Wang, ; Long Xiao, ; Shuaijie Lv,
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Liu CJ, Hu FF, Xie GY, Miao YR, Li XW, Zeng Y, Guo AY. GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels. Brief Bioinform 2023; 24:6957252. [PMID: 36549921 DOI: 10.1093/bib/bbac558] [Citation(s) in RCA: 106] [Impact Index Per Article: 106.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/16/2022] [Indexed: 12/24/2022] Open
Abstract
Cancer initiation and progression are likely caused by the dysregulation of biological pathways. Gene set analysis (GSA) could improve the signal-to-noise ratio and identify potential biological insights on the gene set level. However, platforms exploring cancer multi-omics data using GSA methods are lacking. In this study, we upgraded our GSCALite to GSCA (gene set cancer analysis, http://bioinfo.life.hust.edu.cn/GSCA) for cancer GSA at genomic, pharmacogenomic and immunogenomic levels. In this improved GSCA, we integrated expression, mutation, drug sensitivity and clinical data from four public data sources for 33 cancer types. We introduced useful features to GSCA, including associations between immune infiltration with gene expression and genomic variations, and associations between gene set expression/mutation and clinical outcomes. GSCA has four main functional modules for cancer GSA to explore, analyze and visualize expression, genomic variations, tumor immune infiltration, drug sensitivity and their associations with clinical outcomes. We used case studies of three gene sets: (i) seven cell cycle genes, (ii) tumor suppressor genes of PI3K pathway and (iii) oncogenes of PI3K pathway to prove the advantage of GSCA over single gene analysis. We found novel associations of gene set expression and mutation with clinical outcomes in different cancer types on gene set level, while on single gene analysis level, they are not significant associations. In conclusion, GSCA is a user-friendly web server and a useful resource for conducting hypothesis tests by using GSA methods at genomic, pharmacogenomic and immunogenomic levels.
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Affiliation(s)
- Chun-Jie Liu
- Wuhan University of Science and Technology and Huazhong University of Science and Technology
| | - Fei-Fei Hu
- Wuhan University of Science and Technology
| | - Gui-Yan Xie
- Huazhong University of Science and Technology
| | - Ya-Ru Miao
- Huazhong University of Science and Technology
| | - Xin-Wen Li
- Wuhan University of Science and Technology
| | - Yan Zeng
- Wuhan University of Science and Technology
| | - An-Yuan Guo
- Huazhong University of Science and Technology
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Identification and Analysis of Potential Immune-Related Biomarkers in Endometriosis. J Immunol Res 2023; 2023:2975581. [PMID: 36660246 PMCID: PMC9845045 DOI: 10.1155/2023/2975581] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/03/2022] [Accepted: 12/06/2022] [Indexed: 01/12/2023] Open
Abstract
Background Endometriosis is an inflammatory gynecological disease leading to deep pelvic pain, dyspareunia, and infertility. The pathophysiology of endometriosis is complex and depends on a variety of biological processes and pathways. Therefore, there is an urgent need to identify reliable biomarkers for early detection and accurate diagnosis to predict clinical outcomes and aid in the early intervention of endometriosis. We screened transcription factor- (TF-) immune-related gene (IRG) regulatory networks as potential biomarkers to reveal new molecular subgroups for the early diagnosis of endometriosis. Methods To explore potential therapeutic targets for endometriosis, the Gene Expression Omnibus (GEO), Immunology Database and Analysis Portal (ImmPort), and TF databases were used to obtain data related to the recognition of differentially expressed genes (DEGs), differentially expressed IRGs (DEIRGs), and differentially expressed TFs (DETFs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DETFs and DEIRGs. Then, DETFs and DEIRGs were further validated in the external datasets of GSE51981 and GSE1230103. Then, we used quantitative real-time polymerase chain reaction (qRT-PCR) to verify the hub genes. Simultaneously, the Pearson correlation analysis and protein-protein interaction (PPI) analyses were used to indicate the potential mechanisms of TF-IRGs at the molecular level and obtain hub IRGs. Finally, the receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic value of the hub IRGs. Results We screened a total of 94 DETFs and 121 DEIRGs in endometriosis. Most downregulated DETFs showed decreased expression in the endometria of moderate/severe endometriosis patients. The top-ranked upregulated DEIRGs were upregulated in the endometra of infertile women. Functional analysis showed that DETFs and DEIRGs may be involved in the biological behaviors and pathways of endometriosis. The TF-IRG PPI network was successfully constructed. Compared with the control group, high C3, VCAM1, ITGB2, and C3AR1 expression had statistical significance in endometriosis among the hub DEIRGs. They also showed higher sensitivity and specificity by ROC analysis for the diagnosis of endometriosis. Finally, compared with controls, C3 and VCAM1 were highly expressed in endometriosis tissue samples. In addition, they also showed high specificity and sensitivity for diagnosing endometriosis. Conclusion Overall, we discovered the TF-IRG regulatory network and analyzed 4 hub IRGs that were closely related to endometriosis, which contributes to the diagnosis of endometriosis. Additionally, we verified that DETFs or DEIRGs were associated with the clinicopathological features of endometriosis, and external datasets also confirmed the hub IRGs. Finally, C3 and VCAM1 were highly expressed in endometriosis tissue samples compared with controls and may be potential biomarkers of endometriosis, which are helpful for the early diagnosis of endometriosis.
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Cheng X, Hu Y, Gui G, Hu X, Zhu J, Shi B, Bu S. Roles of Pyroptosis-Related Genes in the Diagnosis and Subtype Classification of Periodontitis. J Immunol Res 2023; 2023:8757233. [PMID: 37090158 PMCID: PMC10114156 DOI: 10.1155/2023/8757233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 12/27/2022] [Accepted: 03/18/2023] [Indexed: 04/25/2023] Open
Abstract
Pyroptosis is widely involved in many diseases, including periodontitis. Nonetheless, the functions of pyroptosis-related genes (PRGs) in periodontitis are still not fully elucidated. Therefore, we aimed to investigate the role of PRGs in periodontitis. Three datasets (GSE10334, GSE16134, and GSE173078) from the Gene Expression Omnibus (GEO) were selected to analyze the differences in expression values of the PRGs between nonperiodontitis and periodontitis tissue samples using difference analysis. Following this, five hub PRGs (charged multivesicular body protein 2B, granzyme B, Z-DNA-binding protein 1, interleukin-1β, and interferon regulatory factor 1) predicting periodontitis susceptibility were screened by establishing a random forest model, and a predictive nomogram model was constructed on the basis of these genes. Decision curve analysis suggested that the PRG-based predictive nomogram model could provide clinical benefits to patients. Three distinct PRG patterns (cluster A, cluster B, and cluster C) in the periodontitis samples were revealed according to the 48 significant PRGs, and the difference in the immune cell infiltration among the three patterns was explored. We observed that all infiltrating immune cells, except type 2 T helper cells, differ significantly among the three patterns. To quantify the PRG patterns, the PRG score was calculated by principal component analysis. According to the results, cluster B had the highest PRG score, followed by cluster A and cluster C. In conclusion, PRGs significantly contribute to the development of periodontitis. Our study of PRG patterns might open up a new avenue to guide individualized treatment plans for patients with periodontitis.
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Affiliation(s)
- Xiaofan Cheng
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yifang Hu
- Department of Geriatric Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Guan Gui
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoya Hu
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Zhu
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Bowei Shi
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shoushan Bu
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Li L, Li J. Correlation of tumor mutational burden with prognosis and immune infiltration in lung adenocarcinoma. Front Oncol 2023; 13:1128785. [PMID: 36959799 PMCID: PMC10028277 DOI: 10.3389/fonc.2023.1128785] [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: 12/21/2022] [Accepted: 02/20/2023] [Indexed: 03/09/2023] Open
Abstract
Background Tumor mutational burden (TMB) plays an important role in the evaluation of immunotherapy efficacy in lung adenocarcinoma (LUAD). Objective To improve the clinical management of LUAD by investigating the prognostic value of TMB and the relationship between TMB and immune infiltration. Methods TMB scores were calculated from the mutation data of 587 LUAD samples from The Cancer Genome Atlas (TCGA), and patients were divided into low-TMB and high-TMB groups based on the quartiles of the TMB score. Differentially expressed genes (DEGs), immune cell infiltration and survival analysis were compared between the low-TMB and high-TMB groups. We queried the expression of genes in lung cancer tissues through the GEPIA online database and performed experimental validation of the function of aberrant genes expressed in lung cancer tissues. Results We obtained sample information from TCGA for 587 LUAD patients, and the results of survival analysis for the high- and low- TMB groups suggested that patients in the high-TMB group had lower survival rates than those in the low-TMB group. A total of 756 DEGs were identified in the study, and gene set enrichment analysis (GSEA) showed that DEGs in the low-TMB group were enriched in immune-related pathways. Among the differentially expressed genes obtained, 15 immune-related key genes were screened with the help of ImmPort database, including 5 prognosis-related genes (CD274, PDCD1, CTLA4, LAG3, TIGIT). No difference in the expression of PDCD1, CTLA4, LAG3, TIGIT in lung cancer tissues and differential expression of CD274 in lung cancer tissues. Conclusions The survival rate of LUAD patients with low TMB was better than that of LUAD patients with high TMB. CD274 expression was down regulated in human LUAD cell lines H1299, PC-9, A549 and SPC-A1, which inhibited malignant progression of A549 cells.
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Affiliation(s)
- Lin Li
- Department of Thoracic Oncology, Jiangxi Cancer Hospital, Nanchang, China
| | - Junyu Li
- Department of Radiation Oncology, Jiangxi Cancer Hospital, Nanchang, China
- Jiangxi Health Committee Key (JHCK) Laboratory of Tumor Metastasis, Jiangxi Cancer Hospital, Nanchang, China
- *Correspondence: Junyu Li,
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Chen L, Xu N, Wang P, Zhu H, Zhang Z, Yang Z, Zhang W, Guo H, Lin J. Nanoalbumin-prodrug conjugates prepared via a thiolation-and-conjugation method improve cancer chemotherapy and immune checkpoint blockade therapy by promoting CD8 + T-cell infiltration. Bioeng Transl Med 2023; 8:e10377. [PMID: 36684090 PMCID: PMC9842047 DOI: 10.1002/btm2.10377] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 07/07/2022] [Accepted: 07/16/2022] [Indexed: 01/25/2023] Open
Abstract
Protein-drug conjugates are emerging tools to combat cancers. Here, we adopted an indirect thiolation-and-conjugation method as a general strategy to prepare protein-drug conjugates. We found for the first time that this method led to the formation of nanometric conjugates, probably due to the formation of intermolecular disulfide bonds, which facilitated enhanced uptake by cancer cells. As a proof-of-concept application in cancer therapy, a nanometric albumin-doxorubicin prodrug conjugate (NanoAlb-proDOX) was prepared. The nanometric size promoted its uptake by cancer cells, and the prodrug characteristic defined its selective cytotoxicity toward cancer cells in vitro and reduced side effects in vivo. In multiple tumor xenograft models, nanometric NanoAlb-proDOX showed superior antitumor activity and synergy with immune checkpoint blockade, probably due to the synergistically enhanced tumor CD8+ T-cell infiltration and activation. Hence, the thiolation-and-conjugation strategy may serve as a generally applicable method for preparing drug conjugates, and the proof-of-concept nanometric albumin-doxorubicin conjugate may be a good choice for antitumor therapy with the ability to co-stimulate the efficacy of immune checkpoint blockade.
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Affiliation(s)
- Long Chen
- Department of PharmacyPeking University Third Hospital, College of Chemistry and Molecular Engineering, Peking UniversityBeijingChina
| | - Nuo Xu
- Department of PharmacyPeking University Third Hospital, College of Chemistry and Molecular Engineering, Peking UniversityBeijingChina
| | - Pan Wang
- Department of Obstetrics and GynecologyPeking University Third HospitalBeijingChina
| | - Haichuan Zhu
- Institute of Biology and Medicine, College of Life and Health Sciences, Wuhan University of Science and TechnologyWuhanChina
| | - Zijian Zhang
- Institute of Biology and Medicine, College of Life and Health Sciences, Wuhan University of Science and TechnologyWuhanChina
| | - Zhanqun Yang
- Department of PharmacyPeking University Third Hospital, College of Chemistry and Molecular Engineering, Peking UniversityBeijingChina
| | - Wenyuan Zhang
- Department of PharmacyPeking University Third Hospital, College of Chemistry and Molecular Engineering, Peking UniversityBeijingChina
| | - Hongyan Guo
- Department of Obstetrics and GynecologyPeking University Third HospitalBeijingChina
| | - Jian Lin
- Department of PharmacyPeking University Third Hospital, College of Chemistry and Molecular Engineering, Peking UniversityBeijingChina
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Zheng X, Gao W, Zhang Z, Xue X, Mijiti M, Guo Q, Wusiman D, Wang K, Zeng X, Xue L, Guo Z, An C, Wu Y. Identification of a seven-lncRNAs panel that serves as a prognosis predictor and contributes to the malignant progression of laryngeal squamous cell carcinoma. Front Oncol 2023; 13:1106249. [PMID: 37205188 PMCID: PMC10188209 DOI: 10.3389/fonc.2023.1106249] [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: 12/08/2022] [Accepted: 04/11/2023] [Indexed: 05/21/2023] Open
Abstract
Background Laryngeal squamous cell carcinoma (LSCC) is one of the most frequent head and neck cancers worldwide. Long non-coding RNAs (lncRNAs) play a critical role in tumorigenesis. However, the clinical significance of lncRNAs in LSCC remains largely unknown. Methods In this study, transcriptome sequencing was performed on 107 LSCC and paired adjacent normal mucosa (ANM) tissues. Furthermore, RNA expression and clinical data of 111 LSCC samples were obtained from The Cancer Genome Atlas (TCGA) database. Bioinformatics analysis were performed to construct a model for predicting the overall survival (OS) of LSCC patients. Moreover, we investigated the roles of lncRNAs in LSCC cells through loss-of-function experiments. Results A seven-lncRNAs panel including ENSG00000233397, BARX1-DT, LSAMP-AS1, HOXB-AS4, MNX1-AS1, LINC01385, and LINC02893 was identified. The Kaplan-Meier analysis demonstrated that the seven-lncRNAs panel was significantly associated with OS (HR:6.21 [3.27-11.81], p-value<0.0001), disease-specific survival (DSS) (HR:4.34 [1.83-10.26], p-value=0.0008), and progression-free interval (PFI) (HR:3.78 [1.92-7.43], p-value=0.0001). ROC curves showed the seven-lncRNAs panel predicts OS with good specificity and sensitivity. Separately silencing the seven lncRNAs inhibited the proliferation, migration, and invasion capacity of LSCC cells. Conclusion Collectively, this seven-lncRNAs panel is a promising signature for predicting the prognosis of LSCC patients, and these lncRNAs could serve as potential targets for LSCC treatment.
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Affiliation(s)
- Xiwang Zheng
- Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Shanxi Province Clinical Medical Research Center for Precision Medicine of Head and Neck Cancer, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Wei Gao
- Department of Otolaryngology Head & Neck Surgery, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China
- Shenzhen Institute of Otolaryngology & Key Laboratory of Otolaryngology, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China
- *Correspondence: Wei Gao, ; Changming An, ; Yongyan Wu,
| | - Zhe Zhang
- Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China
| | - Xuting Xue
- Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Shanxi Province Clinical Medical Research Center for Precision Medicine of Head and Neck Cancer, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Maierhaba Mijiti
- Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Qingbo Guo
- Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Dilinaer Wusiman
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kai Wang
- Department of Otolaryngology Head & Neck Surgery, Southern University of Science and Technology Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Xianhai Zeng
- Department of Otolaryngology Head & Neck Surgery, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China
- Shenzhen Institute of Otolaryngology & Key Laboratory of Otolaryngology, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China
| | - Lingbin Xue
- Department of Otolaryngology Head & Neck Surgery, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China
- Shenzhen Institute of Otolaryngology & Key Laboratory of Otolaryngology, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China
| | - Zekun Guo
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Changming An
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Wei Gao, ; Changming An, ; Yongyan Wu,
| | - Yongyan Wu
- Department of Otolaryngology Head & Neck Surgery, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China
- Shenzhen Institute of Otolaryngology & Key Laboratory of Otolaryngology, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China
- *Correspondence: Wei Gao, ; Changming An, ; Yongyan Wu,
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Abstract
There is no evidence showing that the expression of procollagen C-endopeptidase enhancer (PCOLCE) is associated with human tumors, and pan-cancer analysis is not available. Based on public databases such as the cancer genome atlas, we investigated the potential role of PCOLCE expression in 33 different human tumors. PCOLCE expression in 11 tumors was significantly correlated with tumor prognosis and was a prognostic predictor for pancreatic adenocarcinoma, thymoma and CES. We also found that PCOLCE expression correlated with the immune microenvironment of tumors and the level of cancer-associated fibroblast infiltration. PCOLCE is a potential predictor of small molecule targeted drugs and immune checkpoint inhibitors. Finally, we found by enrichment analysis that PCOLCE localizes to extracellular structures and the extracellular matrix and exerts substantial effects on tumors through the PI3K-Akt and AGE-RAGE signaling pathways. We have a preliminary and relatively comprehensive understanding of the role of PCOLCE in various tumors.
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Affiliation(s)
- Hui Gao
- Department of Breast Surgery, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, PR China
| | - Qiuyun Li
- Department of Breast Surgery, The Affiliated Cancer Hospital of Guangxi Medical University, Nanning, PR China
- * Correspondence: Qiuyun Li, Department of Breast Surgery, The Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530000, PR China (e-mail: )
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Molecular Characterization and Clinical Characteristics of m5C-Based RNA Methylation in Spinal Cord Injury: Validated by qPCR. Int J Genomics 2022; 2022:5433860. [PMID: 36582430 PMCID: PMC9794433 DOI: 10.1155/2022/5433860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 07/25/2022] [Accepted: 12/03/2022] [Indexed: 12/31/2022] Open
Abstract
Aberrant patterns of 5-methylcytosine (m5C)-based ribonucleic acid (RNA) methylation have critical roles in various human diseases, but their importance in spinal cord injury (SCI) is largely unknown. We explore the expression patterns and potential roles of m5C-based regulators of RNA modification after SCI. We analyzed 16 m5C-based regulators of RNA modification in tissues with SCI and normal rats from the Gene Expression Omnibus database. We constructed a "gene signature" of m5C-based regulators of RNA modification to predict the prognosis of SCI using least absolute shrinkage and selection operator regression and random-forest strategy. We found that the m5C-related genes, deoxyribonucleic acid (DNA) methyltransferase1 (Dnmt1), methyl-CpG binding domain protein 2 (Mbd2), ubiquitin-like with PHD and ring finger domains 1 (Uhrf1), uracil-N-glycosylase (Ung), and zinc finger and BTB(brica-brac, tramtrack, and broad) domain containing 38 (Zbtb38) had high expression, and zinc finger and BTB domain containing 4 (Zbtb4) had low expression in SCI. Analysis of the correlation between the gene sets of m5C-based regulators of RNA modification and immune-cell infiltration and immune response revealed Dnmt1, DNA methyltransferases 3A (Dnmt3a), Mbd2, and Ung to be positive regulators of the immune microenvironment, and Zbtb4 may negatively regulate the immune environment. Then, two molecular subtypes were identified based on 16 m5C-regulated genes. Functional-enrichment analysis of differentially expressed genes between different patterns of m5C-based modification was undertaken. Through the creation of a protein-protein interaction network, we screened 11 hub genes. We demonstrated their importance between SCI group and sham group using real-time reverse transcription-quantitative polymerase chain reaction in rat model. Expression of hub genes did not correlate with mitophagy but was positively correlated with endoplasmic reticulum stress (ERS), which suggested that there may be differences in ERS between different patterns of m5C-based modification. This present study explored and discovered the close link between m5C regulators-related genes and SCI. We also hope our findings may contribute to further mechanistic and therapeutic research on the role of key m5C regulators after SCI.
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