Identification of potential drugs for diffuse large b-cell lymphoma based on bioinformatics and Connectivity Map database

Luo, Bin; Gu, Yutong; Wang, Xiaodong; Chen, Gang; Peng, Zhigang

doi:10.1016/j.prp.2018.09.013

Cited by 19 publications

(12 citation statements)

References 67 publications

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“…However, some dysregulated genes specific to DLBCL versus non-tumor controls cannot distinguish the subtypes ( Huang, Liu & Shen, 2019 ). Moreover, most related studies that focused on DLBCL and non-cancer controls were based on DEGs ( Huang, Liu & Shen, 2019 ; Luo et al, 2018 ) and discovered entirely different core hub genes. However, the complexity of DLBCL and the emergence of novel targeted therapies warrants more predictive personalized biomarkers for precision medicine.…”

Section: Discussionmentioning

confidence: 99%

“…Diffuse large B-cell lymphoma (DLBCL) is exceptionally heterogeneous and the most common aggressive non-Hodgkin lymphoma (NHL) subtype in adults. It is increasingly appreciated that its varied outcomes depend on the patients’ clinical and biological features ( Karube et al, 2018 ; Liu et al, 2019b ; Luo et al, 2018 ; Naresh et al, 2011 ). Despite several reports on the mechanism of DLBCL, its pathogenesis characterized by multiple abnormalities at different molecular levels remains unresolved.…”

Section: Introductionmentioning

confidence: 99%

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Integrated bioinformatics analysis reveals dynamic candidate genes and signaling pathways involved in the progression and prognosis of diffuse large B-cell lymphoma

Charwudzi

Meng

et al. 2021

PeerJ

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Background Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous malignancy with varied outcomes. However, the fundamental mechanisms remain to be fully defined. Aim We aimed to identify core differentially co-expressed hub genes and perturbed pathways relevant to the pathogenesis and prognosis of DLBCL. Methods We retrieved the raw gene expression profile and clinical information of GSE12453 from the Gene Expression Omnibus (GEO) database. We used integrated bioinformatics analysis to identify differentially co-expressed genes. The CIBERSORT analysis was also applied to predict tumor-infiltrating immune cells (TIICs) in the GSE12453 dataset. We performed survival and ssGSEA (single-sample Gene Set Enrichment Analysis) (for TIICs) analyses and validated the hub genes using GEPIA2 and an independent GSE31312 dataset. Results We identified 46 differentially co-expressed hub genes in the GSE12453 dataset. Gene expression levels and survival analysis found 15 differentially co-expressed core hub genes. The core genes prognostic values and expression levels were further validated in the GEPIA2 database and GSE31312 dataset to be reliable (p < 0.01). The core genes’ main KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichments were Ribosome and Coronavirus disease-COVID-19. High expressions of the 15 core hub genes had prognostic value in DLBCL. The core genes showed significant predictive accuracy in distinguishing DLBCL cases from non-tumor controls, with the area under the curve (AUC) ranging from 0.992 to 1.00. Finally, CIBERSORT analysis on GSE12453 revealed immune cells, including activated memory CD4+ T cells and M0, M1, and M2-macrophages as the infiltrates in the DLBCL microenvironment. Conclusion Our study found differentially co-expressed core hub genes and relevant pathways involved in ribosome and COVID-19 disease that may be potential targets for prognosis and novel therapeutic intervention in DLBCL.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrated bioinformatics analysis reveals dynamic candidate genes and signaling pathways involved in the progression and prognosis of diffuse large B-cell lymphoma

Charwudzi

Meng

et al. 2021

PeerJ

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“…Ushijima et al found that 5-fluorouracil and anisomycin play a synergies anti-cancer role in CRC [58]. The anticancer effect of anisomycin has been confirmed in osteosarcoma [59], chronic myeloid leukemia [60], renal carcinoma cells [61,62], ehrlich ascites carcinoma [63], diffuse large B-cell lymphoma [64], glioma [65] and CRC [66], but there has been no report on the anticancer effect of anisomycin in THCA. The present study firstly proposed that anisomycin has anticancer effect in THCA by bioinformatics analysis.…”

Section: Figure 15 Wgcna Network Of Degs Between Low-and High-cahm Phenotypesmentioning

confidence: 99%

Expression level of long non-coding RNA colon adenocarcinoma hypermethylated serves as a novel prognostic biomarker in patients with thyroid carcinoma

Xiao

2021

Bioscience Reports

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This study attempts to identify the prognostic value and potential mechanism of action of colorectal adenocarcinoma hypermethylated(CAHM) in thyroid carcinoma(THCA) by using the RNA sequencing dataset from The Cancer Genome Atlas(TCGA). The functional mechanism of CAHM was explored by using RNA sequencing dataset and multiple functional enrichment analysis approaches. Connectivity map online analysis tool was also used to predict CAHM targeted drugs. Survival analysis suggests that THCA patients with high CAHM expression have lower risk of death than these low CAHM expression(Log-rank P=0.022, adjusted P=0.011, HR=0.187, 95%CI=0.051-0.685). Function enrichment of CAHM co-expression genes suggests that CAHM may play a role in the following biological processes: DNA repair, cell adhesion, DNA replication, vascular endothelial growth factor receptor, Erb-B2 receptor tyrosine kinase 2, ErbB and thyroid hormone signaling pathways. Function enrichment of DEGs between low- and high-CAHM phenotype suggests that different CAHM expression levels may have the following differences in biological processes in THCA: cell adhesion, cell proliferation, extracellular signal regulated kinase 1(ERK1) and ERK2 cascade, G-protein coupled receptor, chemokine, and phosphatidylinositol-3-kinase-Akt signaling pathways. Connectivity map have identified five drugs (levobunolol, NU-1025, quipazine, anisomycin and sulfathiazole) for CAHM targeted therapy in THCA. Gene set enrichment analysis suggest that low CAHM phenotype were notably enriched in p53, nuclear factor kappa B, Janus kinase-signal transducer and activators of transcription, tumor necrosis factor, epidermal growth factor receptor and other signaling pathways. In the present study, we have identified CAHM may be serve as a novel prognostic biomarkers for predicting overall survival in patients with THCA.

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“…However, some dysregulated genes specific to DLBCL versus non-tumor controls cannot distinguish the subtypes (Huang et al, 2019). Moreover, most related studies that focused on DLBCL and noncancer controls were based on DEGs (Huang et al, 2019;Luo et al, 2018) and discovered entirely different core hub genes. However, the complexity of DLBCL and the emergence of novel targeted therapies warrants more predictive personalized biomarkers for precision medicine.…”

Section: However Dysregulated Ribosomal Proteins Have Been Reported To Play Various Critical Roles Inmentioning

confidence: 99%

Peer Review #2 of "Integrated bioinformatics analysis reveals dynamic candidate genes and signaling pathways involved in the progression and prognosis of diffuse large B-cell lymphoma (v0.1)"

2021

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Identification of potential drugs for diffuse large b-cell lymphoma based on bioinformatics and Connectivity Map database

Cited by 19 publications

References 67 publications

Integrated bioinformatics analysis reveals dynamic candidate genes and signaling pathways involved in the progression and prognosis of diffuse large B-cell lymphoma

Integrated bioinformatics analysis reveals dynamic candidate genes and signaling pathways involved in the progression and prognosis of diffuse large B-cell lymphoma

Expression level of long non-coding RNA colon adenocarcinoma hypermethylated serves as a novel prognostic biomarker in patients with thyroid carcinoma

Peer Review #2 of "Integrated bioinformatics analysis reveals dynamic candidate genes and signaling pathways involved in the progression and prognosis of diffuse large B-cell lymphoma (v0.1)"

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