Identification of genes and pathways involved in malignant pleural mesothelioma using bioinformatics methods

Liu, Xingsheng; Qian, Kun; Lu, Gaojun; Chen, Peng; Zhang, Yi

doi:10.1186/s12920-021-00954-7

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…In these studies, genes specifically associated to the ECM component, structural constituents, organization, and receptor interaction were found overexpressed. These genes resulted in being involved in different protein-protein interaction (PPI) networks, gene ontology (GO), biological processes (BC), and molecular functions [37,38], and were also validated in MPM cell line models [39].…”

Section: Extracellular Matrix and Stroma Componentsmentioning

confidence: 99%

Pathological Characterization of Tumor Immune Microenvironment (TIME) in Malignant Pleural Mesothelioma

Napoli

Listì

Zambelli

et al. 2021

Cancers

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Malignant pleural mesothelioma (MPM) is a rare and highly aggressive disease that arises from pleural mesothelial cells, characterized by a median survival of approximately 13–15 months after diagnosis. The primary cause of this disease is asbestos exposure and the main issues associated with it are late diagnosis and lack of effective therapies. Asbestos-induced cellular damage is associated with the generation of an inflammatory microenvironment that influences and supports tumor growth, possibly in association with patients’ genetic predisposition and tumor genomic profile. The chronic inflammatory response to asbestos fibers leads to a unique tumor immune microenvironment (TIME) composed of a heterogeneous mixture of stromal, endothelial, and immune cells, and relative composition and interaction among them is suggested to bear prognostic and therapeutic implications. TIME in MPM is known to be constituted by immunosuppressive cells, such as type 2 tumor-associated macrophages and T regulatory lymphocytes, plus the expression of several immunosuppressive factors, such as tumor-associated PD-L1. Several studies in recent years have contributed to achieve a greater understanding of the pathogenetic mechanisms in tumor development and pathobiology of TIME, that opens the way to new therapeutic strategies. The study of TIME is fundamental in identifying appropriate prognostic and predictive tissue biomarkers. In the present review, we summarize the current knowledge about the pathological characterization of TIME in MPM.

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Section: Extracellular Matrix and Stroma Componentsmentioning

confidence: 99%

Pathological Characterization of Tumor Immune Microenvironment (TIME) in Malignant Pleural Mesothelioma

Napoli

Listì

Zambelli

et al. 2021

Cancers

View full text Add to dashboard Cite

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“…These key genes can be used as biomarkers and can be utilized for early diagnosis, survival prediction, drug target identification, and drug response observation [5][6][7][8][9][10][11]. Bioinformatics analyses have been employed to identify important genes and pathways involved in the disease process of malignant pleural mesothelioma [12][13][14]. Bioinformatics approach has also identified upregulation of spliceosomal genes, especially SF3B1 [15] and haploinsufficiency of BAP1 gene [16] are associated with MPM.…”

Section: Original Articlementioning

confidence: 99%

A network-biology approach for identification of key genes and pathways involved in malignant peritoneal mesothelioma

2021

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Comprehensive Analysis Identifies Hyaluronan Mediated Motility Receptor and Cell Division Cycle 25C as Potential Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma

Zhang,

Xu,

Han

et al. 2024

Cancer Control

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Introduction Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide, but its pathogenic mechanisms remain unclear. This study aimed to identify the potential biomarkers underlying the diagnosis and treatment of HNSCC. Methods Weighted gene co-expression network analysis (WGCNA) followed by pathway enrichment analysis, analysis of infiltrating immune cells, survival analysis, and methylation analysis were applied to identify the potential hub genes underlying the prognosis of HNSCC. The expression of hub genes was validated by immunofluorescence staining. Results A total of 10,274 differentially expressed genes (DEGs) were identified. Through WGCNA, the yellow module ( R2 = 0.33, P = 2e-14) was confirmed to be the most significantly associated with the histological grade of HNSCC, and the “Cell Cycle” proved to be the most enriched signaling pathway. Based on the results of survival analysis and immune cell infiltration, 10 hub genes ( HMMR, CENPK, AURKA, CDC25C, FEN1, CKS1B, MAJIN, PCLAF, SPC25, and STAG3) were identified. Eight of these (excluding MAJIN and STAG3) were confirmed by performing survival analysis using another dataset (GSE41613). Further, we identified 4 methylation loci in 3 hub genes (cg15122828 and cg20554926 in HMMR, cg12519992 in CDC25C, and cg2655739 in KIAA0101/PCLAF) as being significantly related to survival. Finally, we demonstrated the high mRNA and protein expression of HMMR and CDC25C in HNSCC patients. Conclusion Two real hub genes ( HMMR and CDC25C) and 3 methylation loci were identified that could potentially serve as prognostic and therapeutic targets for HNSCC, which is significant for studying the pathological mechanisms underlying HNSCC and for developing novel therapies for this disease.

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Identification of genes and pathways involved in malignant pleural mesothelioma using bioinformatics methods

Cited by 4 publications

References 25 publications

Pathological Characterization of Tumor Immune Microenvironment (TIME) in Malignant Pleural Mesothelioma

Pathological Characterization of Tumor Immune Microenvironment (TIME) in Malignant Pleural Mesothelioma

A network-biology approach for identification of key genes and pathways involved in malignant peritoneal mesothelioma

Comprehensive Analysis Identifies Hyaluronan Mediated Motility Receptor and Cell Division Cycle 25C as Potential Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma

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