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Identification of hub genes associated with the pathogenesis of diffuse large B-cell lymphoma subtype one characterized by host response via integrated bioinformatic analyses.
Zhou, Lingna; Ding, Liya; Gong, Yuqi; Zhao, Jing; Xin, Gong; Zhou, Ren; Zhang, Wei.
Affiliation
  • Zhou L; Department of Pathology and Physiology, Cancer Institute, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Ding L; Key Laboratory of Disease Proteomics of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Gong Y; Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Zhao J; Department of Pathology and Pathophysiology, Institute of Pathology and Forensic Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Xin G; Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Zhou R; Department of Pathology and Pathophysiology, Institute of Pathology and Forensic Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Zhang W; Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
PeerJ ; 8: e10269, 2020.
Article in En | MEDLINE | ID: mdl-33240622
BACKGROUND: Host response diffuse large B-cell lymphoma (HR DLBCL) shares features of histologically defined T-cell/histiocyte-rich B-cell lymphoma, including fewer genetic abnormalities, frequent splenic and bone marrow involvement, and younger age at presentation. HR DLBCL is inherently less responsive to the standard treatment for DLBCL. Moreover, the mechanism of infiltration of HR DLBCL with preexisting abundant T-cells and dendritic cells is unknown, and their associated underlying immune responses incompletely defined. Here, hub genes and pathogenesis associated with HR DLBCL were explored to reveal molecular mechanisms and treatment targets. METHODS: Differentially expressed genes were identified in three datasets (GSE25638, GSE44337, GSE56315). The expression profile of the genes in the GSE53786 dataset was used to constructed a co-expression network. Protein-protein interactions analysis in the modules of interest identified candidate hub genes. Then screening of real hub genes was carried out by survival analysis within the GSE53786 and GSE10846 datasets. Expression of hub genes was validated in the Gene expression profiling interactive analysis, Oncomine databases and human tissue specimens. Functional enrichment analysis and Gene set enrichment analysis were utilized to investigate the potential mechanisms. Tumor Immune Estimation Resource and The Cancer Genome Atlas were used to mine the association of the hub gene with tumor immunity, potential upstream regulators were predicted using bioinformatics tools. RESULTS: A total of 274 common differentially expressed genes were identified. Within the key module, we identified CXCL10 as a real hub gene. The validation of upregulated expression level of CXCL10 was consistent with our study. CXCL10 might have a regulatory effect on tumor immunity. The predicted miRNA (hsa-mir-6849-3p) and transcription factor (IRF9) might regulate gene expression in the hub module.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: PeerJ Year: 2020 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: PeerJ Year: 2020 Document type: Article Affiliation country: Country of publication: