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Mi X, Kang C, Hou S, Gao Y, Hao L, Gao X. Mining and exploration of appendicitis nursing targets: An observational study. Medicine (Baltimore) 2024; 103:e38667. [PMID: 38941398 DOI: 10.1097/md.0000000000038667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/30/2024] Open
Abstract
Appendicitis is an inflammation caused by obstruction of the appendiceal lumen or termination of blood supply leading to appendiceal necrosis followed by secondary bacterial infection. The relationship between TYROBP gene and the nursing of appendicitis remains unclear. The appendicitis dataset GSE9579 profile was downloaded from the gene expression omnibus database generated from GPL571. Differentially expressed genes were screened, followed by weighted gene co-expression network analysis, functional enrichment analysis, gene set enrichment analysis, construction and analysis of protein-protein interaction network, Comparative Toxicogenomics Database analysis, and immune infiltration analysis. Heatmaps of gene expression levels were plotted. A total of 1570 differentially expressed genes were identified. According to gene ontology analysis, they were mainly enriched in organic acid metabolic process, condensed chromosome kinetochore, oxidoreductase activity. In Kyoto Encyclopedia of Gene and Genome analysis, they mainly concentrated in metabolic pathways, P53 signaling pathway, PPAR signaling pathway. The soft threshold power in weighted gene co-expression network analysis was set to 12. Through the construction and analysis of protein-protein interaction network, 5 core genes (FCGR2A, IL1B, ITGAM, TLR2, TYROBP) were obtained. Heatmap of core gene expression levels revealed high expression of TYROBP in appendicitis samples. Comparative Toxicogenomics Database analysis found that core genes (FCGR2A, IL1B, ITGAM, TLR2, TYROBP) were closely related to abdominal pain, gastrointestinal dysfunction, fever, and inflammation occurrence. TYROBP gene is highly expressed in appendicitis, and higher expression of TYROBP gene indicates worse prognosis. TYROBP may serve as a molecular target for appendicitis and its nursing.
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Affiliation(s)
- Xihua Mi
- Gastrointestinal Rehabilitation Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
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Xia H, Zhang H, Ruan Z, Zhang H, Sun L, Chen H, Zhou Y, Zhang L, Bian D, Zhu X, Zhang J, Sun F, Yu H, Song N, Liu X, Zhu Y, Zhang H, He W, Chen J, Yang J, Chen G, Xie S, Tang D, Zhang X, Duan L, Zhao D, Li Q, Zhang P, Jiang G. Neoadjuvant camrelizumab (an anti-PD-1 antibody) plus chemotherapy or apatinib (a VEGFR-2 inhibitor) for initially unresectable stage II-III non-small-cell lung cancer: a multicentre, two-arm, phase 2 exploratory study. Signal Transduct Target Ther 2024; 9:145. [PMID: 38871690 PMCID: PMC11176298 DOI: 10.1038/s41392-024-01861-w] [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: 10/30/2023] [Revised: 04/29/2024] [Accepted: 05/10/2024] [Indexed: 06/15/2024] Open
Abstract
This multicentre, two-arm, phase 2 study aimed to explore the efficacy and safety of neoadjuvant camrelizumab plus chemotherapy or apatinib in patients with initially unresectable stage II-III non-small-cell lung cancer (NSCLC). Eligible patients regardless of PD-L1 expression received neoadjuvant camrelizumab 200 mg and platinum-doublet chemotherapy every 3 weeks (arm A) or those with PD-L1-positive tumors received neoadjuvant camrelizumab and apatinib 250 mg once daily (arm B), for 2-4 cycles, followed by surgery. The primary endpoint was major pathological response (MPR) rate. Thirty patients in arm A and 21 in arm B were enrolled. Surgery rates were 50.0% (15/30) in arm A and 42.9% (9/21) in arm B, with all patients achieving R0 resections. Of these patients, the MPR and pathological complete response rates were both 20.0% (95% CI 4.3-48.1) in arm A and were 55.6% (95% CI 21.2-86.3) and 11.1% (95% CI 0.3-48.2) in arm B, respectively. The corresponding objective response rates were 33.3% (95% CI 11.8-61.6) and 55.6% (95% CI 21.2-86.3). With a median follow-up of 22.4 months (95% CI 19.0-26.0), the median event-free survival was not reached (NR; 95% CI 13.6-NR) in arm A and 16.8 months (95% CI 8.6-NR) in arm B. Grade 3 or above treatment-related adverse events occurred in eight (26.7%) patients in arm A and three (14.3%) in arm B. Biomarker analysis showed baseline TYROBP expression was predictive of treatment response in arm B. Neoadjuvant camrelizumab plus chemotherapy or apatinib exhibits preliminary efficacy and manageable toxicity in patients with initially unresectable stage II-III NSCLC.
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Affiliation(s)
- Haoran Xia
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Han Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Zheng Ruan
- Department of Thoracic Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huibiao Zhang
- Department of Thoracic Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Liangdong Sun
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Hezhong Chen
- Department of Thoracic Surgery, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Yongxin Zhou
- Department of Thoracic-Cardiovascular Surgery, Tongji Hospital, Tongji University School of Medicine, Shanghai, China
| | - Lele Zhang
- Central Laboratory, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Dongliang Bian
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Xinsheng Zhu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jing Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Fenghuan Sun
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Huansha Yu
- Experimental Animal Center, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Nan Song
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Xiaogang Liu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Yuming Zhu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Haiping Zhang
- Department of Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Wenxin He
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jian Chen
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jie Yang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Guohan Chen
- Department of Thoracic Surgery, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Shiliang Xie
- Department of Thoracic-Cardiovascular Surgery, Tongji Hospital, Tongji University School of Medicine, Shanghai, China
| | - Dongfang Tang
- Department of Thoracic Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Xiaomiao Zhang
- Department of Thoracic Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liang Duan
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Deping Zhao
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
| | - Qinchuan Li
- Department of Thoracic Surgery, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
| | - Peng Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
| | - Gening Jiang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
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Jia W, Chen L, Hou S, Kang C, Deng H. TYROBP as a molecular target in cholangiocarcinoma, renal cancer and abdominal aortic aneurysm. Medicine (Baltimore) 2024; 103:e36843. [PMID: 38181271 PMCID: PMC10766282 DOI: 10.1097/md.0000000000036843] [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: 09/05/2023] [Accepted: 12/12/2023] [Indexed: 01/07/2024] Open
Abstract
Cholangiocarcinoma occurs when there is a malignant tumor in the bile duct system. Renal cancer originates from renal tubular epithelial cells. Abdominal aortic aneurysm (AAA) is a permanently localized dilation caused by a lesion or injury to abdominal aortic wall. However, the relationship between TYROBP and cholangiocarcinoma, renal cancer and AAA remains unclear. The profiles of cholangiocarcinoma dataset GSE107943, renal cell carcinoma dataset GSE213324, and AAA dataset GSE47472 were downloaded from the GEO database using the platforms GPL18573, GPL24676, and GPL10558. DEGs were screened, WGCNA was performed as well as construction and analysis of PPI network. Functional enrichment analysis, GSEA, heat map of gene expression, survival analysis, and immune infiltration analysis were performed. The most relevant diseases to core genes were found by CTD. The GSE107943 dataset identified 3383 DEGs for cholangiocarcinoma, GSE47472 identified 95 DEGs for abdominal aortic aneurysm, and GSE213324 identified 10245 DEGs for renal cell carcinoma. For the GSE107943 cholangiocarcinoma dataset, GO analysis revealed enrichment in immune response, cell adhesion, extracellular space, and oxidoreductase activity. KEGG analysis indicated enrichment in metabolic pathways, the PI3K-Akt signaling pathway, cell apoptosis, the cell cycle, and the NF-kappa B signaling pathway. In the GSE47472 AAA dataset, GO analysis showed enrichment in neuroblast differentiation, cardiac muscle myofilament complex, and alkaline binding. KEGG analysis indicated enrichment in mRNA surveillance pathway and purine metabolism. In the GSE213324 renal cell carcinoma dataset, GO analysis indicated enrichment in immune system processes, cell adhesion, and membrane parts. KEGG analysis showed enrichment in cytokine-cytokine receptor interaction, calcium signaling pathway, and hematopoietic cell lineage. Furthermore, for cholangiocarcinoma (GSE107943), enriched terms associated with DEGs were in metabolic pathways, cell apoptosis, and the cell cycle. For AAA (GSE47472), enriched terms were in alkaline binding and cellular redox homeostasis. For renal cell carcinoma (GSE213324), enriched terms were in biological adhesion, regulation of immune system processes, and cell surface. Common core genes (ADH6, AGXT, CYP3A43, TYROBP) were identified for cholangiocarcinoma, renal cell carcinoma, and AAA. ADH6 and TYROBP were associated with cholangiocarcinoma, AAA, renal tumors, kidney diseases, atherosclerosis, and inflammation. TYROBP is abnormally expressed in cholangiocarcinoma, renal cancer and abdominal aortic aneurysm.
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Affiliation(s)
- Wei Jia
- Gastrointestinal Rehabilitation Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, P. R. China
| | - Lei Chen
- Department of Vascular Surgery, Fuxing Hospital Affiliated to Capital Medical University, Beijing, P. R. China
| | - Shiyang Hou
- Gastrointestinal Rehabilitation Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, P. R. China
| | - Chunbo Kang
- Gastrointestinal Rehabilitation Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, P. R. China
| | - Hongru Deng
- Department of Vascular Surgery, Fuxing Hospital Affiliated to Capital Medical University, Beijing, P. R. China
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Gou H, Chen P, Wu W. FAM72 family proteins as poor prognostic markers in clear cell renal carcinoma. Biochem Biophys Rep 2023; 35:101506. [PMID: 37457361 PMCID: PMC10344709 DOI: 10.1016/j.bbrep.2023.101506] [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: 04/22/2023] [Revised: 06/08/2023] [Accepted: 06/24/2023] [Indexed: 07/18/2023] Open
Abstract
Purpose This study aimed to investigate the prognostic significance of the Family with Sequence Similarity 72 member (FAM72) gene family in clear cell renal carcinoma (ccRCC) using a bioinformatic approach. Patients and methods To investigate the association between FAM72 and ccRCC, we utilized various databases and analysis tools, including TCGA, GEPIA, Metscape, cBioPortal, and MethSurv. We conducted an analysis of FAM72 expression levels in ccRCC tissues compared to normal kidney tissues and performed univariate and multivariate Cox analysis to determine the relationship between FAM72 expression and patient prognosis. Furthermore, we carried out Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) to identify enriched biological processes associated with FAM72 expression. Additionally, we analyzed immune cell infiltration and the level of methylation in ccRCC patients. Our bioinformatic analysis revealed that FAM72 expression levels were significantly higher in ccRCC tissues than in normal kidney tissues. High expression of FAM72 was associated with poor prognosis in ccRCC patients and was found to be an independent prognostic factor for ccRCC. GO and GSEA analyses indicated that FAM72 was enriched in biological processes related to mitosis, cell cycle, and DNA metabolism. Moreover, we found a significant correlation between FAM72 and immune cell infiltration and the level of methylation in ccRCC patients. Conclusion Our findings suggest that FAM72 could serve as an unfavorable prognostic molecular marker for ccRCC. A comprehensive understanding of FAM72 could provide crucial insights into tumor progression and prognosis.
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Affiliation(s)
- Hui Gou
- Department of Pharmacy, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
| | - Ping Chen
- Department of Pharmacy, Suining Central Hospital, Suining, 629000, China
| | - Wenbing Wu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, 646000, China
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Wan B, Yang Y, Zhang Z. Identification of Differentially Methylated Genes Associated with Clear Cell Renal Cell Carcinoma and Their Prognostic Values. JOURNAL OF ENVIRONMENTAL AND PUBLIC HEALTH 2023; 2023:8405945. [PMID: 36793506 PMCID: PMC9925242 DOI: 10.1155/2023/8405945] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/21/2022] [Accepted: 11/25/2022] [Indexed: 02/09/2023]
Abstract
Objective Renal cell carcinoma (RCC) is a heterogeneous disease comprising histologically defined subtypes among which clear cell RCC (ccRCC) accounts for 70% of all RCC cases. DNA methylation constitutes a main part of the molecular mechanism of cancer evolution and prognosis. In this study, we aim to identify differentially methylated genes related to ccRCC and their prognostic values. Methods The GSE168845 dataset was downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between ccRCC tissues and paired tumor-free kidney tissues. DEGs were submitted to public databases for functional and pathway enrichment analysis, protein-protein interaction (PPI) analysis, promoter methylation analysis, and survival correlation analysis. Results In the setting of |log2FC| ≥ 2 and adjusted p value <0.05 during differential expression analysis of the GSE168845 dataset, 1659 DEGs between ccRCC tissues and paired tumor-free kidney tissues were sorted out. The most enriched pathways were "T cell activation" and "cytokine-cytokine receptor interaction." After PPI analysis, 22 hub genes related to ccRCC stood out, among which CD4, PTPRC, ITGB2, TYROBP, BIRC5, and ITGAM exhibited higher methylation levels, and BUB1B, CENPF, KIF2C, and MELK exhibited lower methylation levels in ccRCC tissues compared with paired tumor-free kidney tissues. Among these differentially methylated genes, TYROBP, BIRC5, BUB1B, CENPF, and MELK were significantly correlated with the survival of ccRCC patients (p < 0.001). Conclusion Our study indicates the DNA methylation of TYROBP, BIRC5, BUB1B, CENPF, and MELK may be promising results for the prognosis of ccRCC.
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Affiliation(s)
- Bin Wan
- Department of Urology, The First People's Hospital of Jiujiang, Jiujiang, Jiangxi 332000, China
| | - Yang Yang
- Department of Urology, The First People's Hospital of Jiujiang, Jiujiang, Jiangxi 332000, China
| | - Zhuo Zhang
- Department of Urology, The First People's Hospital of Jiujiang, Jiujiang, Jiangxi 332000, China
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Bioinformatics-based identification of lipid- and immune-related biomarkers in abdominal aortic aneurysms. Heliyon 2023; 9:e13622. [PMID: 36879746 PMCID: PMC9984436 DOI: 10.1016/j.heliyon.2023.e13622] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 02/01/2023] [Accepted: 02/06/2023] [Indexed: 02/12/2023] Open
Abstract
Background Abdominal aortic aneurysm (AAA) manifest as a natural inflammatory process with permanent dilation and terminal rupture. Nevertheless, the pathogenesis of AAA remains a mystery, and treatment is still controversial. Lipid metabolism and immune system are involved in AAA progression, which has been well documented. However, lipid- and immune-related (LIR) biomarkers need to be further elucidated. Methods The AAA-related datasets were retrieved from the GEO database, and the datasets were analyzed for differential gene expression by NetworkAnalyst. GO and KEGG pathway enrichment analysis of differentially expressed mRNA (DE-mRNA) was performed using Metscape, and LIR DE-mRNA was further screened. AAA rat model was constructed using porcine pancreatic elastase to verify the differential expression of LIR DE-mRNA. Results The GSE47472 and GSE57691 datasets respectively identified 614 (containing 381 down-regulated and 233 up-regulated DE-mRNAs) and 384 (containing 218 down-regulated and 164 up-regulated DE-mRNAs) DE-mRNAs. Intersection and union of DE-mRNAs were 13 and 983, respectively. The main terms involved in the union of DE-mRNAs included "immune system process", "metabolic process", "Chemokine signaling pathway", "hematopoietic cell lineage" and "Cholesterol metabolism". In vivo experiments revealed that LIR DE-mRNAs of PDIA3, TYROBP, and HSPA1A were significantly low expression in AAA abdominal aortic tissues, and HCK and SERPINE1 were significantly high expression, which is consistent with the bioinformatics analysis. Conclusions PDIA3, TYROBP, HSPA1A, HCK and SERPINE1 may serve as LIR biomarkers of AAA, which provides new insights and theoretical guidance for the future treatment, early prevention and progression of AAA.
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Lv XQ, Zhang KB, Guo X, Pei L, Li F. Higher TYROBP and lower SOX6 as predictive biomarkers for poor prognosis of clear cell renal cell carcinoma: A pilot study. Medicine (Baltimore) 2022; 101:e30658. [PMID: 36595751 PMCID: PMC9794311 DOI: 10.1097/md.0000000000030658] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Clear cell renal carcinoma (ccRCC) is the most common subtype of renal cancer, accounting for approximately 75% of all histological types of renal cancer, and is the leading cause of death from renal cancer. However, the molecular mechanism of tyrosine kinase binding protein (TYROBP) and sex-determining region Y Box-6 (SOX6) in the ccRCC was not precise. METHODS Bioinformatics analysis was performed to explore the hub role of TYROBP and SOX6 on the ccRCC. A total of 6 patients with clear cell renal cell carcinoma (ccRCC) were recruited. HE staining was performed to observe the pathology result of ccRCC. Immunohistochemistry and Immunofluorescence assay was made to detect the protein expression of TYROBP. Total RNA was extracted using TRIzol to examine the mRNA expression of TYROBP via the Real time quantitative polymerase chain reaction. The strong correlation between the expression of TYROBP and the survival time of ccRCC patients was performed by the BP neural network and support vector machine. RESULTS Compared with the control group, the expression of SOX6 was downregulated in the samples with ccRCC. However, the expression of TYROBP was higher in the samples with ccRCC than in the control group. Compared with the patients with high SOX6 expression, the patients with low SOX6 expression have a poor survival prognosis (HR=0.39, P < .05). However, the patients with high TYROBP expression have a shorter survival time than the patients with low TYROBP expression (HR=1.66, P < .05). The genes related with TYROBP and SOX6 are mainly enriched in the regulation of cell activation, leukocyte activation, negative regulation of cell activation, myeloid leukocyte activation, positive regulation of response to external stimulus, immune response-regulating signaling pathway. The interaction between TYROBP, SOX6, and kidney neoplasms was drawn, and the inference score of TYROBP and SOX6 on the kidney neoplasms was high. CONCLUSION In conclusion, TYROBP is highly expressed in renal clear cell carcinoma, and when this molecule is highly expressed, the survival prognosis of renal carcinoma is poor. TYROBP and SOX6 may be potential targets for diagnosing and treating renal clear cell carcinoma.
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Affiliation(s)
- Xian-Qiang Lv
- Department of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Kai-bo Zhang
- Department of plastic surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Xu Guo
- Lab of Gambridge Analytica, Heping Road, Shijiazhuang, Hebei Province, China
| | - Long Pei
- Department of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Feng Li
- Department of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
- * Correspondence: Feng Li, Department of Urology, The Fourth Hospital of Hebei Medical University, No.12 Jiankang Road Shijiazhuang, Hebei Province 050011, China (e-mail: )
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Möller S, Saul N, Projahn E, Barrantes I, Gézsi A, Walter M, Antal P, Fuellen G. Gene co-expression analyses of health(span) across multiple species. NAR Genom Bioinform 2022; 4:lqac083. [PMID: 36458022 PMCID: PMC9706456 DOI: 10.1093/nargab/lqac083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 08/20/2022] [Accepted: 10/31/2022] [Indexed: 12/03/2022] Open
Abstract
Health(span)-related gene clusters/modules were recently identified based on knowledge about the cross-species genetic basis of health, to interpret transcriptomic datasets describing health-related interventions. However, the cross-species comparison of health-related observations reveals a lot of heterogeneity, not least due to widely varying health(span) definitions and study designs, posing a challenge for the exploration of conserved healthspan modules and, specifically, their transfer across species. To improve the identification and exploration of conserved/transferable healthspan modules, here we apply an established workflow based on gene co-expression network analyses employing GEO/ArrayExpress data for human and animal models, and perform a comprehensive meta-study of the resulting modules related to health(span), yielding a small set of literature backed health(span) candidate genes. For each experiment, WGCNA (weighted gene correlation network analysis) was used to infer modules of genes which correlate in their expression with a 'health phenotype score' and to determine the most-connected (hub) genes (and their interactions) for each such module. After mapping these hub genes to their human orthologs, 12 health(span) genes were identified in at least two species (ACTN3, ANK1, MRPL18, MYL1, PAXIP1, PPP1CA, SCN3B, SDCBP, SKIV2L, TUBG1, TYROBP, WIPF1), for which enrichment analysis by g:profiler found an association with actin filament-based movement and associated organelles, as well as muscular structures. We conclude that a meta-study of hub genes from co-expression network analyses for the complex phenotype health(span), across multiple species, can yield molecular-mechanistic insights and can direct experimentalists to further investigate the contribution of individual genes and their interactions to health(span).
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Affiliation(s)
- Steffen Möller
- To whom correspondence should be addressed. Tel: +49 381 494 7361; Fax: +49 381 494 7203;
| | - Nadine Saul
- Humboldt-University of Berlin, Institute of Biology, Berlin, Germany
| | - Elias Projahn
- Rostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany
| | - Israel Barrantes
- Rostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany
| | - András Gézsi
- Budapest University of Technology and Economics, Department of Measurement and Information Systems, Budapest, Hungary
| | - Michael Walter
- Rostock University Medical Center, Institute for Clinical Chemistry and Laboratory Medicine, Rostock, Germany
| | - Péter Antal
- Budapest University of Technology and Economics, Department of Measurement and Information Systems, Budapest, Hungary
| | - Georg Fuellen
- Rostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany
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Zhao HC, Chen CZ, Song HQ, Wang XX, Zhang L, Zhao HL, He JF. Single-cell RNA Sequencing Analysis Reveals New Immune Disorder Complexities in Hypersplenism. Front Immunol 2022; 13:921900. [PMID: 35865544 PMCID: PMC9294158 DOI: 10.3389/fimmu.2022.921900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 05/30/2022] [Indexed: 11/13/2022] Open
Abstract
Hypersplenism (HS) is a concomitant symptom of liver or blood disease. Not only does the treatment of HS face challenges, but the transcriptome of individual cells is also unknown. Here, the transcriptional profiles of 43,037 cells from four HS tissues and one control tissue were generated by the single-cell RNA sequencing and nine major cell types, including T-cells, B-cells, NK cells, hematopoietic stem cells, neutrophil cells, mast cells, endothelial cells, erythrocytes, and dendritic cells were identified. Strikingly, the main features were the lack of CCL5+ B-cells in HS and the presence of SESN1+ B cells in HS with hepatocellular carcinoma (HS-HCC). In cell-cell interaction analysis, CD74-COPA and CD94-HLA-E in HS were found to be up-regulated. We further explored HS-specifically enriched genes (such as FKBP5, ADAR, and RPS4Y1) and found that FKBP5 was highly expressed in HCC-HS, leading to immunosuppression. Taken together, this research provides new insights into the genetic characteristics of HS via comprehensive single-cell transcriptome analysis.
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Affiliation(s)
- Hai-chao Zhao
- The Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- Department of Hepatobiliary Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Chang-zhou Chen
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, Shanghai, China
- Institute of Biomedical Sciences, Fudan University, Shanghai, China
| | - Huang-qin Song
- The Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Xiao-xiao Wang
- The Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Lei Zhang
- Department of Hepatobiliary Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- Hepatic Surgery Center, Institute of Hepato-Pancreato-Biliary Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hao-liang Zhao
- The Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- Department of Hepatobiliary Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- *Correspondence: Jie-feng He, ; Hao-liang Zhao,
| | - Jie-feng He
- The Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- Department of Hepatobiliary Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- *Correspondence: Jie-feng He, ; Hao-liang Zhao,
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Identification of Immune-Related Markers in Hepatocellular Carcinoma Based on Gene Co-expression Network. Biochem Genet 2022; 60:2552-2569. [PMID: 35633444 DOI: 10.1007/s10528-022-10235-2] [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: 12/17/2021] [Accepted: 05/02/2022] [Indexed: 11/02/2022]
Abstract
Hepatocellular carcinoma (HCC) is a major cause of cancer-related death throughout the world, with constant increasing morbidity and mortality. Existing studies suggest that immunotherapy is beneficial to the treatment of advanced HCC. At present, it is imperative to identify biomarkers suitable for HCC immunotherapy. In this paper, the mRNA expression data of HCC were downloaded from The Cancer Genome Atlas, and Stromal Score, Immune Score and ESTIMATE Score of each sample were calculated. Weighted gene co-expression network analysis clustered the pretreated genes into eight modules. The brown module that was remarkably associated with Immune Score was identified by module eigengene-immune trait analysis, in which genes were mainly enriched in immune-related pathways. Four hub genes (CCR5, CD53, ITGB2, and TYROBP) related to tumor immunity, were screened out by intramodular gene connectivity combined with protein-protein interaction network topology analysis. Kaplan-Meier survival analysis presented a correlation between high expression of CCR5 and CD53, and better prognoses of HCC patients. TIMER analysis revealed a positive correlation between expression of each hub gene and immune cell infiltration level, and a positive correlation between the expression of each hub gene and the expression of immunosuppressive factors CTLA4 and PDCD1. Gene set enrichment analysis displayed that there was an evident difference in the activation of cytokines and the activation of immune signal transduction-related pathways between high- and low-expression groups of each hub gene. In conclusion, this study identified four potential genetic markers associated with HCC immunity and assessed their association with HCC patient's prognosis and immune microenvironment. The study results are expected to provide theoretical guidance for immunotherapy of HCC patients.
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Li J, Shi H, Yuan Z, Wu Z, Li H, Liu Y, Lu M, Lu M. The role of SPI1-TYROBP-FCER1G network in oncogenesis and prognosis of osteosarcoma, and its association with immune infiltration. BMC Cancer 2022; 22:108. [PMID: 35078433 PMCID: PMC8790913 DOI: 10.1186/s12885-022-09216-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 01/20/2022] [Indexed: 12/27/2022] Open
Abstract
Osteosarcoma is an aggressive malignant bone sarcoma worldwide. A causal gene network with specific functions underlying both the development and progression of OS was still unclear. Here we firstly identified the differentially expressed genes (DEGs) between control and OS samples, and then defined the hub genes and top clusters in the protein–protein interaction (PPI) network of these DEGs. By focusing on the hub gene TYROBP in the top 1 cluster, a conserved TYROBP co-expression network was identified. Then the effect of the network on OS overall survival was analyzed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and Gene Set Enrichment Analysis (GSEA) were used to explore the functions of the network. XCell platform and ssGSEA algorithm were conducted to estimate the status of immune infiltration. ChEA3 platform, GSEA enrichment analysis, and Drug Pair Seeker (DPS) were used to predict the key transcription factor and its upstream signal. We identified the downregulated SPI1-TYROBP-FCER1G network in OS, which were significantly enriched in immune-related functions. We also defined a two-gene signature (SPI1/FCER1G) that can predict poorer OS overall survival and the attenuated immune infiltration when downregulated. The SPI1-TYROBP-FCER1G network were potentially initiated by transcription factor SPI1 and would lead to the upregulated CD86, MHC-II, CCL4/CXCL10/CX3CL1 and hence increased immune infiltrations. With this study, we could better explore the mechanism of OS oncogenesis and metastasis for developing new therapies.
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Li M, Zhang J, Zhang Z, Qian Y, Qu W, Jiang Z, Zhao B. Identification of Transcriptional Pattern Related to Immune Cell Infiltration With Gene Co-Expression Network in Papillary Thyroid Cancer. Front Endocrinol (Lausanne) 2022; 13:721569. [PMID: 35185791 PMCID: PMC8854657 DOI: 10.3389/fendo.2022.721569] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 01/06/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND A growing body of evidence suggests that immune cell infiltration in cancer is closely related to clinical outcomes. However, there is still a lack of research on papillary thyroid cancer (PTC). METHODS Based on single-sample gene set enrichment analysis (SSGSEA) algorithm and weighted gene co-expression network analysis (WGCNA) tool, the infiltration level of immune cell and key modules and genes associated with the level of immune cell infiltration were identified using PTC gene expression data from The Cancer Genome Atlas (TCGA) database. In addition, the co-expression network and protein-protein interactions network analysis were used to identify the hub genes. Moreover, the immunological and clinical characteristics of these hub genes were verified in TCGA and GSE35570 datasets and quantitative real-time polymerase chain reaction (PCR). Finally, receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value of hub genes. RESULTS Activated B cell, activated dendritic cell, CD56bright natural killer cell, CD56dim natural killer cell, Eosinophil, Gamma delta T cell, Immature dendritic cell, Macrophage, Mast cell, Monocyte, Natural killer cell, Neutrophil and Type 17 T helper cell were significantly changed between PTC and adjacent normal groups. WGCNA results showed that the black model had the highest correlation with the infiltration level of activated dendritic cells. We found 14 hub genes whose expression correlated to the infiltration level of activated dendritic cells in both TCGA and GSE35570 datasets. After validation in the TCGA dataset, the expression level of only 5 genes (C1QA, HCK, HLA-DRA, ITGB2 and TYROBP) in 14 hub genes were differentially expressed between PTC and adjacent normal groups. Meanwhile, the expression levels of these 5 hub genes were successfully validated in GSE35570 dataset. Quantitative real-time PCR results showed the expression of these 4 hub genes (except C1QA) was consistent with the results in TCGA and GSE35570 dataset. Finally, these 4 hub genes had diagnostic value to distinguish PTC and adjacent normal controls. CONCLUSIONS HCK, HLA-DRA, ITGB2 and TYROBP may be key diagnostic biomarkers and immunotherapy targets in PTC.
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Affiliation(s)
- Meiye Li
- Department of Endocrinology, No. 960 Hospital of PLA Joint Logistics Support Force, Jinan, China
| | - Jimei Zhang
- School of Pharmacy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Zongjing Zhang
- Department of Endocrinology, No. 960 Hospital of PLA Joint Logistics Support Force, Jinan, China
| | - Ying Qian
- Department of Endocrinology, No. 960 Hospital of PLA Joint Logistics Support Force, Jinan, China
| | - Wei Qu
- Department of Endocrinology, No. 960 Hospital of PLA Joint Logistics Support Force, Jinan, China
| | - Zhaoshun Jiang
- Department of Endocrinology, No. 960 Hospital of PLA Joint Logistics Support Force, Jinan, China
- *Correspondence: Baochang Zhao, ; Zhaoshun Jiang,
| | - Baochang Zhao
- School of Life Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
- *Correspondence: Baochang Zhao, ; Zhaoshun Jiang,
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Wang X, Wang L, Xu W, Wang X, Ke D, Lin J, Lin W, Bai X. Classification of Osteosarcoma Based on Immunogenomic Profiling. Front Cell Dev Biol 2021; 9:696878. [PMID: 34336848 PMCID: PMC8323066 DOI: 10.3389/fcell.2021.696878] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 06/14/2021] [Indexed: 01/01/2023] Open
Abstract
Accumulating evidence has supported that osteosarcoma is heterogeneous, and several subtypes have been identified based on genomic profiling. Immunotherapy is revolutionizing cancer treatment and is a promising therapeutic strategy. In contrast, few studies have identified osteosarcoma classification based on immune biosignatures, which offer the optimal stratification of individuals befitting immunotherapy. Here, we classified osteosarcoma into two clusters: immunity high and immunity low using the single-sample gene-set enrichment analysis and unsupervised hierarchical clustering. Immunity_H subtype was associated with high immune cells infiltration, a favorable prognosis, benefit to immunotherapy, high human leukocyte antigen gene expression, and activated immune signal pathway indicating an immune-hot phenotype. On the contrary, the Immunity_L subtype was correlated with low immune cell infiltration, poor prognosis, and cancer-related pathway, indicating an immune-cold phenotype. We also identified TYROBP as a key immunoregulatory gene associated with CD8+ T cell infiltration by multiplex immunohistochemistry. Finally, we established an immune-related prognostic model that predicted the survival time of osteosarcoma. In conclusion, we established a new classification system of osteosarcoma based on immune signatures and identified TYROBP as a key immunoregulatory gene. This stratification had significant clinical outcomes for estimating prognosis, as well as the immunotherapy of osteosarcoma patients.
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Affiliation(s)
- Xinwen Wang
- The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Bone and Joint Degeneration Diseases, Guangzhou, China
| | - Liangming Wang
- Department of Orthopedics, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Weifeng Xu
- Department of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Xinwu Wang
- Department of Orthopedics, The First Hospital of Putian City, Putian, China
| | - Dianshan Ke
- Department of Orthopedics, Jiangmen People's Hospital, Jiangmen, China
| | - Jinluan Lin
- Department of Orthopedics, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Wanzun Lin
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Xiaochun Bai
- The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Bone and Joint Degeneration Diseases, Guangzhou, China
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Lu J, Peng Y, Huang R, Feng Z, Fan Y, Wang H, Zeng Z, Ji Y, Wang Y, Wang Z. Elevated TYROBP expression predicts poor prognosis and high tumor immune infiltration in patients with low-grade glioma. BMC Cancer 2021; 21:723. [PMID: 34162355 PMCID: PMC8220692 DOI: 10.1186/s12885-021-08456-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/03/2021] [Indexed: 11/19/2022] Open
Abstract
Background Tyrosine protein tyrosine kinase binding protein (TYROBP) binds non-covalently to activated receptors on the surface of various immune cells, and mediates signal transduction and cellular activation. It is dysregulated in various malignancies, although little is known regarding its role in low-grade glioma. The aim of this study is to explore the clinicopathological significance, prognostic value and immune signature of TYROBP expression in low-grade glioma (LGG). Methods The differentially expressed genes (DEGs) between glioma samples and normal tissues were identified from two GEO microarray datasets using the limma package. The DEGs overlapping across both datasets were functionally annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. STRING database was used to establish the protein-protein interaction (PPI) of the DEGs. The PPI network was visualized by Cytoscape and cytoHubba, and the core module and hub genes were identified. The expression profile of TYROBP and patient survival were validated in the Oncomine, GEPIA2 and CGGA databases. The correlation between TYROBP expression and the clinicopathologic characteristics were evaluated. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were performed by R based on the LGG data from TCGA. The TIMER2.0 database was used to determine the correlation between TYROBP expression and tumor immune infiltrating cells in the LGG patients. Univariate and multivariate Cox regression analyses were performed to determine the prognostic impact of clinicopathological factors via TCGA database. Results Sixty-two overlapping DEGs were identified in the 2 datasets, and were mainly enriched in the response to wounding, focal adhesion, GTPase activity and Parkinson disease pathways. TYROBP was identified through the PPI network and cytoHubba. TYROBP expression levels were significantly higher in the LGG tissues compared to the normal tissues, and was associated with worse prognosis and poor clinicopathological parameters. In addition, GSEA showed that TYROBP was positively correlated to neutrophil chemotaxis, macrophage activation, chemokine signaling pathway, JAK-STAT signaling pathway, and negatively associated with gamma aminobutyric acid signaling pathway, neurotransmitter transport, neuroactive ligand receptor intersection etc. TIMER2.0 and ssGSEA showed that TYROBP expression was significantly associated with the infiltration of neutrophils, macrophages, myeloid dendritic cells and monocytes. The infiltration of the M2 phenotype macrophages, cancer-associated fibroblasts and myeloid dendritic cells correlated to worse prognosis in LGG patients. Finally, multivariate analysis showed that elevated TYROBP expression is an independent risk factor for LGG. Conclusion TYROBP is dysregulated in LGG and correlates with immune infiltration. It is a potential therapeutic target and prognostic marker for LGG.
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Affiliation(s)
- Jiajie Lu
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
| | - Yuecheng Peng
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
| | - Rihong Huang
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
| | - Zejia Feng
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
| | - Yongyang Fan
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
| | - Haojian Wang
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
| | - Zhaorong Zeng
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
| | - Yunxiang Ji
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China.
| | - Yezhong Wang
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China.
| | - Zhaotao Wang
- Department of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People's Republic of China.
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Liu F, Yang Z, Zheng L, Shao W, Cui X, Wang Y, Jia J, Fu Y. A Tumor Progression Related 7-Gene Signature Indicates Prognosis and Tumor Immune Characteristics of Gastric Cancer. Front Oncol 2021; 11:690129. [PMID: 34195091 PMCID: PMC8238374 DOI: 10.3389/fonc.2021.690129] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 05/17/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Gastric cancer is a common gastrointestinal malignancy. Since it is often diagnosed in the advanced stage, its mortality rate is high. Traditional therapies (such as continuous chemotherapy) are not satisfactory for advanced gastric cancer, but immunotherapy has shown great therapeutic potential. Gastric cancer has high molecular and phenotypic heterogeneity. New strategies for accurate prognostic evaluation and patient selection for immunotherapy are urgently needed. METHODS Weighted gene coexpression network analysis (WGCNA) was used to identify hub genes related to gastric cancer progression. Based on the hub genes, the samples were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between the subtypes, a gastric cancer risk model was constructed through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis. The differences in prognosis, clinical features, tumor microenvironment (TME) components and immune characteristics were compared between subtypes and risk groups, and the connectivity map (CMap) database was applied to identify potential treatments for high-risk patients. RESULTS WGCNA and screening revealed nine hub genes closely related to gastric cancer progression. Unsupervised clustering according to hub gene expression grouped gastric cancer patients into two subtypes related to disease progression, and these patients showed significant differences in prognoses, TME immune and stromal scores, and suppressive immune checkpoint expression. Based on the different expression patterns between the subtypes, we constructed a gastric cancer risk model and divided patients into a high-risk group and a low-risk group based on the risk score. High-risk patients had a poorer prognosis, higher TME immune/stromal scores, higher inhibitory immune checkpoint expression, and more immune characteristics suitable for immunotherapy. Multivariate Cox regression analysis including the age, stage and risk score indicated that the risk score can be used as an independent prognostic factor for gastric cancer. On the basis of the risk score, we constructed a nomogram that relatively accurately predicts gastric cancer patient prognoses and screened potential drugs for high-risk patients. CONCLUSIONS Our results suggest that the 7-gene signature related to tumor progression could predict the clinical prognosis and tumor immune characteristics of gastric cancer.
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Affiliation(s)
- Fen Liu
- Department of Microbiology/Key Laboratory for Experimental Teratology of the Chinese Ministry of Education, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
- Key Laboratory of Infection and Immunity of Shandong Province, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Zongcheng Yang
- Department of Implantology, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, China
| | - Lixin Zheng
- Department of Microbiology/Key Laboratory for Experimental Teratology of the Chinese Ministry of Education, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
- Key Laboratory of Infection and Immunity of Shandong Province, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Wei Shao
- Department of Microbiology/Key Laboratory for Experimental Teratology of the Chinese Ministry of Education, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
- Key Laboratory of Infection and Immunity of Shandong Province, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xiujie Cui
- Department of Microbiology/Key Laboratory for Experimental Teratology of the Chinese Ministry of Education, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
- Key Laboratory of Infection and Immunity of Shandong Province, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yue Wang
- Department of Microbiology/Key Laboratory for Experimental Teratology of the Chinese Ministry of Education, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
- Key Laboratory of Infection and Immunity of Shandong Province, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Jihui Jia
- Department of Microbiology/Key Laboratory for Experimental Teratology of the Chinese Ministry of Education, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
- Key Laboratory of Infection and Immunity of Shandong Province, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yue Fu
- School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
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Marchioni M, Rivas JG, Autran A, Socarras M, Albisinni S, Ferro M, Schips L, Scarpa RM, Papalia R, Esperto F. Biomarkers for Renal Cell Carcinoma Recurrence: State of the Art. Curr Urol Rep 2021; 22:31. [PMID: 33886004 PMCID: PMC8062344 DOI: 10.1007/s11934-021-01050-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/18/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE OF REVIEW We aim to summarize the current state of art about the possible use of biomarkers for predicting renal cell carcinoma (RCC) recurrence after curative treatment. In addition, we aim to provide a snapshot about the clinical implication of biomarkers use for follow-up planification. RECENT FINDINGS A wide variety of biomarkers have been proposed. RCC biomarkers have been individuated in tumoral tissue, blood, and urine. A variety of molecules, including proteins, DNA, and RNA, warrant a good accuracy for RCC recurrence and progression prediction. Their use in prediction models might warrant a better patients' risk stratification. Future prognostic models will probably include a combination of classical features (tumor grade, stage, etc.) and novel biomarkers. Such models might allow a more accurate treatment and follow-up planification.
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Affiliation(s)
- Michele Marchioni
- Unit of Urology, Department of Medical, Oral and Biotechnological Sciences, SS. Annunziata Hospital, "G. d'Annunzio University", Chieti, Italy.
- Department of Medical, Oral and Biotechnological Sciences, University "G. D'Annunzio" Chieti-Pescara, Via dei Vestini, Campus universitario, 66100, Chieti, Italy.
| | | | - Anamaria Autran
- Department of Urology, Fundacion Jimemez Diaz, Madrid, Spain
| | - Moises Socarras
- Instituto de Cirugia Urologica Avanzada (ICUA), Madrid, Spain
| | - Simone Albisinni
- Urology Department, Université Libre de Bruxelles, Erasme Hospital, Brussels, Belgium
| | - Matteo Ferro
- Department of Urology, European Institute of Oncology (IEO), IRCCS, Milan, Italy
| | - Luigi Schips
- Unit of Urology, Department of Medical, Oral and Biotechnological Sciences, SS. Annunziata Hospital, "G. d'Annunzio University", Chieti, Italy
| | | | - Rocco Papalia
- Department of Urology, Campus Bio-Medico University, Rome, Italy
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Wang L, Lin Y, Yuan Y, Liu F, Sun K. Identification of TYROBP and FCER1G as Key Genes with Prognostic Value in Clear Cell Renal Cell Carcinoma by Bioinformatics Analysis. Biochem Genet 2021; 59:1278-1294. [PMID: 33786672 DOI: 10.1007/s10528-021-10061-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 03/16/2021] [Indexed: 12/22/2022]
Abstract
The involvement of aberrantly expressed genes in the pathogenesis and progression of various human malignancies has been widely reported, including clear cell renal cell carcinoma (ccRCC). This study aimed to identify potential crucial genes in ccRCC and further investigate the role of these genes in ccRCC prognosis. Three gene expression profiles (GSE3, GSE6344 and GSE53000) were downloaded from GEO database. GEO2R was performed to identify the differentially expressed genes (DEGs) between ccRCC and normal samples. GO analysis and KEGG pathway enrichment analysis were applied for the function analysis. The DEGs were mapped into the PPI network, then the hub genes were identified and verified using the ONCOMINE database. Kaplan-Meier plotter was used to evaluate of the prognostic value of the identified hub genes. A total of 113 DEGs were identified from the three gene expression profiles, including 64 up-regulated genes and 69 down-regulated genes. DEGs were observed to be enriched in biological processes related to the progress and pathogenesis of human cancers. According to PPI network, 5 hub genes were collected, including TYROBP, C1QB, ITGB2, CD53 and FCER1G. Among them, CD53 was newly identified, and Kaplan-Meier survival curves suggested that high expression of CD53 was significantly associated with poor survival in ccRCC patients (log-rank P < 0.01). The present results may provide new insight into the understanding of molecular mechanisms and the clinical prognosis of ccRCC.
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Affiliation(s)
- Licheng Wang
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University, Shandong, 250014, China.,Department of Urology, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Yun Lin
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University, Shandong, 250014, China
| | - Yi Yuan
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University, Shandong, 250014, China
| | - Fei Liu
- Department of General Surgery, The First Affiliated Hospital of Shandong First Medical University, 16766 Jingshi Road, Jinan, 250014, Shandong, China.
| | - Kai Sun
- Department of General Surgery, The First Affiliated Hospital of Shandong First Medical University, 16766 Jingshi Road, Jinan, 250014, Shandong, China.
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