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  • Wang, Gongming  (5)
  • 1
    In: Thoracic Cancer, Wiley, Vol. 14, No. 23 ( 2023-08), p. 2275-2287
    Abstract: Serine protease inhibitors clade B serpins (SERPINBs) are the largest subclass of protease inhibitors, once thought of as a tumor suppressor gene family. However, some SERPINBs exhibit functions unrelated to the inhibition of catalytic activity. Methods The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Gene Set Cancer Analysis (GSCA), and cBioPortal databases were utilized to investigate SERPINBs expression, prognostic correlation, and genomic variation in 33 cancer types. We also conducted a comprehensive transcriptome analysis in multiple lung adenocarcinoma (LUAD) cohorts to reveal the molecular mechanism of SERPINB5 in LUAD. Then, qPCR and immunohistochemistry were used to verify the expression and prognostic value of SERPINB5 in LUAD patients. Furthermore, knockdown and overexpression of SERPINB5 in LUAD cell lines were performed to evaluate cell proliferation, migration, invasion, and epithelial‐mesenchymal transition (EMT). Results The expression of SERPINB5 was upregulated and demethylated in LUAD, and its abnormally high expression was significantly correlated with poor overall survival (OS). In addition, the expression of SERPINB5 was analyzed to determine its prognostic value in LUAD and confirmed that SERPINB5 was an independent predictor of LUAD in TCGA and GEO cohorts and qPCR validation with 106 clinical samples. At last, A knockdown of SERPINB5 in LUAD cells reduced proliferation, migration, and EMT. Proliferation, migration, and invasion are promoted by the overexpression of SERPINB5. Conclusion Therefore, SERPINB5 has shown potential as a prognostic biomarker for LUAD, and it may become a potential therapeutic target for lung adenocarcinoma.
    Type of Medium: Online Resource
    ISSN: 1759-7706 , 1759-7714
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2559245-2
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  • 2
    Online Resource
    Online Resource
    Frontiers Media SA ; 2023
    In:  Frontiers in Medicine Vol. 10 ( 2023-4-26)
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 10 ( 2023-4-26)
    Abstract: Lung cancer is one of the cancers with the highest morbidity and mortality. During the last decade, the trends of clinical characteristics, surgical treatments and survival of lung cancer patients in China have remained unclear. Methods All lung cancer patients operated on from 2011 to 2020 were identified in a prospectively maintained database of Sun Yat-sen University Cancer Center. Results A total of 7,800 lung cancer patients were included in this study. Within the past 10 years, the average age at diagnosis of the patients remained stable, the proportion of asymptomatic, female and nonsmoking patients increased, and the average tumor size decreased from 3.766 to 2.300 cm. In addition, the proportion of early stage and adenocarcinoma increased, while that of squamous cell carcinoma decreased. Among the patients, the proportion of patients having video-assisted thoracic surgery increased. More than 80% of the patients underwent lobectomy and systematic nodal dissection over the 10 years. Additionally, both the average postoperative length of stay and 1-, 3-, and 6-month postoperative mortality decreased. Moreover, the 1-, 3-, and 5-year overall survival (OS) rates of all the operable patients increased from 89.8, 73.9, and 63.8% to 99.6, 90.7, and 80.8%, respectively. The 5-year OS rates of the patients with stage I, II, and III lung cancer were 87.6, 79.9, and 59.9%, respectively, which were higher than those in other published data. Conclusion There were significant changes in the clinicopathological characteristics, surgical treatments and survival outcomes of the patients with operable lung cancer from 2011 to 2020.
    Type of Medium: Online Resource
    ISSN: 2296-858X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2775999-4
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  • 3
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Molecular Biosciences Vol. 9 ( 2022-8-10)
    In: Frontiers in Molecular Biosciences, Frontiers Media SA, Vol. 9 ( 2022-8-10)
    Abstract: Background: The tumor microenvironment (TME) is involved in the development and progression of lung carcinomas. A deeper understanding of TME landscape would offer insight into prognostic biomarkers and potential therapeutic targets investigation. To this end, we aimed to identify the TME components of lung cancer and develop a prognostic signature to predict overall survival (OS). Methods: Expression data was retrieved from The Cancer Genome Atlas (TCGA) database and differentially expressed TME-related genes were calculated between tumor and normal tissues. Then nonnegative matrix factorization (NMF) clustering was used to identify two distinct subtypes. Results: Our analysis yielded a gene panel consisting of seven TME-related genes as candidate signature set. With this panel, our model showed that the high-risk group experienced a shorter survival time. This model was further validated by an independent cohort with data from Gene Expression Omnibus (GEO) database (GSE50081 and GSE13213). Additionally, we integrated the clinical factors and risk score to construct a nomogram for predicting prognosis. Our data suggested less immune cells infiltration but more fibroblasts were found in tumor tissues derived from patients at high-risk and those patients exhibited a worse immunotherapy response. Conclusion: The signature set proposed in this work could be an effective model for estimating OS in lung cancer patients. Hopefully analysis of the TME could have the potential to provide novel diagnostic, prognostic and therapeutic opportunities.
    Type of Medium: Online Resource
    ISSN: 2296-889X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2814330-9
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  • 4
    In: Biology, MDPI AG, Vol. 12, No. 6 ( 2023-06-02), p. 808-
    Abstract: Recent studies have highlighted the combination of activation of host immunogenic cell death (ICD) and tumor-directed cytotoxic strategies. However, overall multiomic analysis of the intrinsic ICD property in lung adenocarcinoma (LUAD) has not been performed. Therefore, the aim of this study was to develop an ICD-based risk scoring system to predict overall survival (OS) and immunotherapeutic efficacy in patients. In our study, both weighted gene co-expression network analysis (WGCNA) and LASSO-Cox analysis were utilized to identify ICDrisk subtypes (ICDrisk). Moreover, we identify genomic alterations and differences in biological processes, analyze the immune microenvironment, and predict the response to immunotherapy in patients with pan-cancer. Importantly, immunogenicity subgroup typing was performed based on the immune score (IS) and microenvironmental tumor neoantigens (meTNAs). Our results demonstrate that ICDrisk subtypes were identified based on 16 genes. Furthermore, high ICDrisk was proved to be a poor prognostic factor in LUAD patients and indicated poor efficacy of immune checkpoint inhibitor (ICI) treatment in patients with pan-cancer. The two ICDrisk subtypes displayed distinct clinicopathologic features, tumor-infiltrating immune cell patterns, and biological processes. The ISlowmeTNAhigh subtype showed low intratumoral heterogeneity (ITH) and immune-activated phenotypes and correlated with better survival than the other subtypes within the high ICDrisk group. This study suggests effective biomarkers for the prediction of OS in LUAD patients and immunotherapeutic response across Pan-cancer and contributes to enhancing our understanding of intrinsic immunogenic tumor cell death.
    Type of Medium: Online Resource
    ISSN: 2079-7737
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2661517-4
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  • 5
    In: Bioactive Materials, Elsevier BV, Vol. 36 ( 2024-06), p. 238-255
    Type of Medium: Online Resource
    ISSN: 2452-199X
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
    detail.hit.zdb_id: 2970496-0
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