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Zhang Y, Liu YJ, Mei J, Yang ZX, Qian XP, Huang W. An Analysis Regarding the Association Between DAZ Interacting Zinc Finger Protein 1 (DZIP1) and Colorectal Cancer (CRC). Mol Biotechnol 2024:10.1007/s12033-024-01065-1. [PMID: 38334905 DOI: 10.1007/s12033-024-01065-1] [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: 11/09/2023] [Accepted: 12/21/2023] [Indexed: 02/10/2024]
Abstract
Colorectal cancer (CRC) is the third most common malignant disease worldwide, and its incidence is increasing, but the molecular mechanisms of this disease are highly heterogeneous and still far from being fully understood. Increasing evidence suggests that fibrosis mediated by abnormal activation of fibroblasts based in the microenvironment is associated with a poor prognosis. However, the function and pathogenic mechanisms of fibroblasts in CRC remain unclear. Here, combining scrna-seq and clinical specimen data, DAZ Interacting Protein 1 (DZIP1) was found to be expressed on fibroblasts and cancer cells and positively correlated with stromal deposition. Importantly, pseudotime-series analysis showed that DZIP1 levels were up-regulated in malignant transformation of fibroblasts and experimentally confirmed that DZIP1 modulates activation of fibroblasts and promotes epithelial-mesenchymal transition (EMT) in tumor cells. Further studies showed that DZIP1 expressed by tumor cells also has a driving effect on EMT and contributes to the recruitment of more fibroblasts. A similar phenomenon was observed in xenografted nude mice. And it was confirmed in xenograft mice that downregulation of DZIP1 expression significantly delayed tumor formation and reduced tumor size in CRC cells. Taken together, our findings suggested that DZIP1 was a regulator of the CRC mesenchymal phenotype. The revelation of targeting DZIP1 provides a new avenue for CRC therapy.
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Affiliation(s)
- Yu Zhang
- Comprehensive Cancer Center, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, 210008, Jiangsu, China
- Department of Medical Oncology, Affiliated Jinling Hospital, Medical School Nanjing University, Nanjing, 210029, Jiangsu, China
- Department of Oncology, Nanjing Tianyinshan Hospital, Nanjing, 211199, Jiangsu, China
| | - Yuan-Jie Liu
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Jia Mei
- Department of Pathology, Affiliated Jinling Hospital, Medical School Nanjing University, Nanjing, 210029, Jiangsu, China
| | - Zhao-Xu Yang
- Department of Medical Oncology, Affiliated Jinling Hospital, Medical School Nanjing University, Nanjing, 210029, Jiangsu, China
| | - Xiao-Ping Qian
- Comprehensive Cancer Center, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, 210008, Jiangsu, China.
- Comprehensive Cancer Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Clinical Cancer Institute of Nanjing University, Nanjing, 210008, Jiangsu, China.
| | - Wei Huang
- Department of Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China.
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Zhang YX, Lv J, Bai JY, Pu X, Dai EL. Identification of key biomarkers of the glomerulus in focal segmental glomerulosclerosis and their relationship with immune cell infiltration based on WGCNA and the LASSO algorithm. Ren Fail 2023; 45:2202264. [PMID: 37096442 PMCID: PMC10132234 DOI: 10.1080/0886022x.2023.2202264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023] Open
Abstract
OBJECTIVE The aim of our study was to identify key biomarkers of glomeruli in focal glomerulosclerosis (FSGS) and analyze their relationship with the infiltration of immune cells. METHODS The expression profiles (GSE108109 and GSE200828) were obtained from the GEO database. The differentially expressed genes (DEGs) were filtered and analyzed by gene set enrichment analysis (GSEA). MCODE module was constructed. Weighted gene coexpression network analysis (WGCNA) was performed to obtain the core gene modules. Least absolute shrinkage and selection operator (LASSO) regression was applied to identify key genes. ROC curves were employed to explore their diagnostic accuracy. Transcription factor prediction of the key biomarkers was performed using the Cytoscape plugin IRegulon. The analysis of the infiltration of 28 immune cells and their correlation with the key biomarkers were performed. RESULTS A total of 1474 DEGs were identified. Their functions were mostly related to immune-related diseases and signaling pathways. MCODE identified five modules. The turquoise module of WGCNA had significant relevance to the glomerulus in FSGS. TGFB1 and NOTCH1 were identified as potential key glomerular biomarkers in FSGS. Eighteen transcription factors were obtained from the two hub genes. Immune infiltration showed significant correlations with T cells. The results of immune cell infiltration and their relationship with key biomarkers implied that NOTCH1 and TGFB1 were enhanced in immune-related pathways. CONCLUSION TGFB1 and NOTCH1 may be strongly correlated with the pathogenesis of the glomerulus in FSGS and are new candidate key biomarkers. T-cell infiltration plays an essential role in the FSGS lesion process.
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Affiliation(s)
- Yun Xia Zhang
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
- Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, China
| | - Juan Lv
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
- Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, China
| | - Jun Yuan Bai
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
- Affiliated Hospital of Gansu University of Chinese Medicine, Lanzhou, China
| | - XiaoWei Pu
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
| | - En Lai Dai
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
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Zhang YX, Bai JY, Pu X, Lv J, Dai EL. An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA-miRNA-lncRNA/circRNA networks. Ren Fail 2023; 45:2284212. [PMID: 38013448 PMCID: PMC11001368 DOI: 10.1080/0886022x.2023.2284212] [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: 05/01/2023] [Accepted: 11/11/2023] [Indexed: 11/29/2023] Open
Abstract
OBJECTIVE The purpose of this study was to identify potential biomarkers in the tubulointerstitium of focal segmental glomerulosclerosis (FSGS) and comprehensively analyze its mRNA-miRNA-lncRNA/circRNA network. METHODS The expression data (GSE108112 and GSE200818) were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Identification and enrichment analysis of differentially expressed genes (DEGs) were performed. the PPI networks of the DEGs were constructed and classified using the Cytoscape molecular complex detection (MCODE) plugin. Weighted gene coexpression network analysis (WGCNA) was used to identify critical gene modules. Least absolute shrinkage and selection operator regression analysis were used to screen for key biomarkers of the tubulointerstitium in FSGS, and the receiver operating characteristic curve was used to determine their diagnostic accuracy. The screening results were verified by quantitative real-time-PCR (qRT-PCR) and Western blot. The transcription factors (TFs) affecting the hub genes were identified by Cytoscape iRegulon. The mRNA-miRNA-lncRNA/circRNA network for identifying potential biomarkers was based on the starBase database. RESULTS A total of 535 DEGs were identified. MCODE obtained eight modules. The green module of WGCNA had the greatest association with the tubulointerstitium in FSGS. PPARG coactivator 1 alpha (PPARGC1A) was screened as a potential tubulointerstitial biomarker for FSGS and verified by qRT-PCR and Western blot. The TFs FOXO4 and FOXO1 had a regulatory effect on PPARGC1A. The ceRNA network yielded 17 miRNAs, 32 lncRNAs, and 50 circRNAs. CONCLUSIONS PPARGC1A may be a potential biomarker in the tubulointerstitium of FSGS. The ceRNA network contributes to the comprehensive elucidation of the mechanisms of tubulointerstitial lesions in FSGS.
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Affiliation(s)
- Yun Xia Zhang
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
- Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, China
| | - Jun Yuan Bai
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
- Affiliated Hospital of Gansu University of Chinese Medicine, Lanzhou, China
| | - XiaoWei Pu
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
| | - Juan Lv
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
- Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, China
| | - En Lai Dai
- College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, China
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Gong Y, Liu X, Sahu A, Reddy AV, Wang H. Exploration of hub genes, lipid metabolism, and the immune microenvironment in stomach carcinoma and cholangiocarcinoma. ANNALS OF TRANSLATIONAL MEDICINE 2022; 10:834. [PMID: 36034995 PMCID: PMC9403925 DOI: 10.21037/atm-22-3530] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/02/2022] [Indexed: 01/11/2023]
Abstract
Background Gastric cancer (GC) is the 5th most common cause of cancer in the world and the 3rd largest cause of cancer-related death. It is usually associated with a variety of cancers, of which cholangiocarcinoma (CCA) combined with GC accounts for about 1.6%. This study sought to examine the hub genes and role of lipid metabolism in the development and diagnosis of GC and CCA. Methods To screen potential hub genes, The Cancer Genome Atlas (TCGA) data sets, including the GC (STAD, dataset of GC) and CCA (CHOL, dataset of CCA) data sets, were used to conduct a differentially expressed gene (DEG) analysis and an enrichment analysis of the DEGs. A weighted-gene co-expression network analysis (WGCNA) was conducted to identify the significant gene module and then find the hub genes in the module. To verify the 4 hub genes, we conducted a differentiation analysis of the 4 genes in GC and CCA and found that there were differences. A survival analysis of the hub genes was performed and mutations were mapped. Additionally, tumor immune microenvironment (TIME) and immune analyses were performed to evaluate how lipid metabolism affects the development of GC with CCA. Results The principal component analysis showed that both GC and CCA had distinct up-regulated and down-regulated genes, which are involved in a variety of metabolic processes. Upon WGCNA, the turquoise and blue modules were meaningful, and the hub genes were identified from these 2 modules. Four hub genes were identified: amyloid beta precursor protein binding family B member 1 (APBB1), Homo sapiens armadillo repeat containing X-linked 1 (ARMCX1), DAZ interacting zinc finger protein 1 (DZIP1), and methionine sulfoxide reductase B3 (MSRB3). In survival analysis, increased expression of the 4 hub genes was associated with inferior survival outcomes, with variations in all 4 genes. Additionally, we demonstrated that genes related to lipid metabolism had an effect on immune function. Conclusions APBB1, ARMCX1, DZIP1, and MSRB3 affect the development of GC and CCA and can be used as biomarkers. The expression of lipid metabolism genes is related to the TIME of patients with GC and CCA.
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Affiliation(s)
- Yuda Gong
- Department of General Surgery, Fudan University Zhongshan Hospital, Shanghai, China
| | - Xuan Liu
- Department of General Surgery, Fudan University Zhongshan Hospital, Shanghai, China
| | - Arvind Sahu
- Department of Oncology, Goulburn Valley Health, Shepparton, Victoria, Australia
| | - Abhinav V Reddy
- Department of Radiation Oncology & Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Sidney Kimmel Cancer Center, Baltimore, MD, USA
| | - Haiyu Wang
- Department of General Surgery, Fudan University Zhongshan Hospital, Shanghai, China
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Liu YJ, Yin SY, Zeng SH, Hu YD, Wang MQ, Huang P, Li JP. Prognostic Value of LHFPL Tetraspan Subfamily Member 6 (LHFPL6) in Gastric Cancer: A Study Based on Bioinformatics Analysis and Experimental Validation. Pharmgenomics Pers Med 2021; 14:1483-1504. [PMID: 34848995 PMCID: PMC8612673 DOI: 10.2147/pgpm.s332345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 10/26/2021] [Indexed: 12/17/2022] Open
Abstract
Purpose The identification of biomarkers and effective therapeutic targets for gastric cancer (GC), the most common cause of cancer-related deaths around the world, is currently a major focus in research. Here, we examined the utility of LHFPL6 as a prognostic biomarker and therapeutic target for GC. Methods We explored the clinical relevance, function, and molecular role of LHFPL6 in GC using the MethSurv, cBioPortal, TIMER, Gene Expression Profiling Interactive Analysis, ONCOMINE, MEXPRESS, and EWAS Atlas databases. The GSE118919, GSE29272, and GSE13861 datasets were used for differential expression analysis. Using The Cancer Genome Atlas, we developed a Cox regression model and assessed the clinical significance of LHFPLs. In addition, we used the “CIBERSORT” algorithm to make reliable immune infiltration estimations. Western blot and immunohistochemistry were used to examine protein expression. Cell migration and invasion were assessed using transwell experiments. THP-1-derived macrophages and GC cells were co-cultured in order to model tumor–macrophage interactions in vitro. The levels of CD206 and CD163 were measured using immunofluorescence assays. The results were visualized with the “ggplot2” and “circlize” packages. Results Our results showed that in GC, LHFPL6 overexpression was significantly associated with a poor prognosis. Our findings also suggested that LHFPL6 may be involved in the activation of the epithelial–mesenchymal transition. Furthermore, LHFPL6 expression showed a positive correlation with the abundance of M2 macrophages, which are potent immunosuppressors. Conclusion LHFPL6 could be a prognostic biomarker and therapeutic target for GC.
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Affiliation(s)
- Yuan-Jie Liu
- Department of Oncology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, Jiangsu, 215600, People's Republic of China.,Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Sheng-Yan Yin
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Shu-Hong Zeng
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Yi-Dou Hu
- Department of Oncology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, Jiangsu, 215600, People's Republic of China
| | - Meng-Qi Wang
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Pan Huang
- Department of Oncology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, Jiangsu, 215600, People's Republic of China
| | - Jie-Pin Li
- Department of Oncology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, Jiangsu, 215600, People's Republic of China.,Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
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