Knockdown of G‐protein‐signaling modulator 2 promotes metastasis of non‐small‐cell lung cancer by inducing the expression of Snail

Deng, Mingming; Liu, Bofang; Zhang, Zhe; Yang, Chong‐Ren; Wang, Yizhe; Wang, Ximing; Lv, Qing; Yang, Xianghong; Hou, Kezuo; Che, Xiaofang; Qu, Xiujuan; Liu, Yunpeng; Zhang, Ye; Hu, Xuejun

doi:10.1111/cas.14519

Cited by 18 publications

(15 citation statements)

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“…GPSM2 plays the role of an oncogene in liver cancer [ 60 ], breast cancer [ 61 ], and pancreatic cancer [ 62 ]. In addition, GPSM2 can inhibit the proliferation and metastasis of lung cancer cells, and the specific mechanism is related to the AKT/ERK pathway [ 63 , 64 ]…”

Section: Discussionmentioning

confidence: 99%

Identification of an extracellular vesicle-related gene signature in the prediction of pancreatic cancer clinical prognosis

Wang

Zhou

et al. 2020

Bioscience Reports

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Although Extracellular vesicles (EVs)in body fluid have been considered to be ideal biomarkers for cancer diagnosis and prognosis, it is still difficult to distinguish EVs derived from tumor tissue and normal tissue. Therefore, the prognostic value of tumor- specific EVs was evaluated through related molecules in pancreatic tumor tissue. NA sequencing data of pancreatic adenocarcinoma(PAAD) were acquired from The Cancer Genome Atlas(TCGA) and International Cancer Genome Consortium(ICGC). EV-related genes in pancreatic cancer were obtained from exoRBase. Protein-protein interaction (PPI) network analysis was used to identify modules related to clinical stage. CIBERSORT was used to assess the abundance of immune and non-immune cells in the tumor microenvironment. A total of 12 PPI modules were identified, and the 3-PPI-MOD was identified based on the randomForest package. The genes of this model are involved in DNA damage and repair and cell membrane-related pathways. The independent external verification cohorts showed that the 3-PPI-MOD can significantly classify patient prognosis. Moreover, compared with the model constructed by pure gene expression, the 3-PPI-MOD showed better prognostic value. The expression of genes in the 3-PPI-MOD had a significant positive correlation with immune cells. Genes related to the hypoxia pathway were significantly enriched in the high-risk tumors predicted by the 3-PPI-MOD. External databases were used to verify the gene expression in the 3-PPI-MOD. The 3-PPI-MOD had satisfactory predictive performance and could be used as a prognostic predictive biomarker for pancreatic cancer.

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Section: Discussionmentioning

confidence: 99%

Identification of an extracellular vesicle-related gene signature in the prediction of pancreatic cancer clinical prognosis

Wang

Zhou

et al. 2020

Bioscience Reports

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“…Gene set enrichment analysis (GSEA) was performed as previously described (12). The MSigDB KEGG gene set was used as a reference.…”

Section: Gene Set Enrichment Analysismentioning

confidence: 99%

Identification of Inflammation-Related Biomarker Lp-PLA2 for Patients With COPD by Comprehensive Analysis

et al. 2021

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PurposeChronic obstructive pulmonary disease (COPD) is a complex and persistent lung disease and lack of biomarkers. The aim of this study is to screen and verify effective biomarkers for medical practice.MethodsDifferential expressed genes analysis and weighted co-expression network analysis were used to explore potential biomarker. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene set enrichment analysis (GSEA) analysis were used to explore potential mechanism. CIBERSORTx website was used to evaluate tissue-infiltrating immune cells. Enzyme-linked immunosorbent assay (ELISA) was used to assess the concentrations of the Lp-PLA2 in serum.ResultsTen genes were selected via combined DEGs and WGCNA. Furthermore, PLA2G7 was choose based on validation from independent datasets. Immune infiltrate and enrichment analysis suggest PLA2G7 may regulate immune pathway via macrophages. Next, Lp-PLA2(coded by PLA2G7 gene) level was upregulated in COPD patients, increased along with The Global Average of COPD (GOLD) stage. In additional, Lp-PLA2 level was significant correlate with FEV1/FVC, BMI, FFMI, CAT score, mMRC score and 6MWD of COPD patients. Finally, the predictive efficiency of Lp-PLA2 level (AUC:0.796) and derived nomogram model (AUC:0.884) in exercise tolerance was notably superior to that of the sit-to-stand test and traditional clinical features.ConclusionLp-PLA2 is a promising biomarker for COPD patients and is suitable for assessing exercise tolerance in clinical practice.

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“…Gene set enrichment analysis (GSEA) was performed as previously described [8]. The MSigDB KEGG gene set was used as a reference.…”

Section: Gene Set Enrichment Analysismentioning

confidence: 99%

Lipoprotein-associated phospholipase A2 predicts exercise tolerance in COPD patients

Deng

Yin²,

Zhang

et al. 2021

Preprint

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Background & aimsImpaired exercise tolerance is a clinical feature of chronic obstructive pulmonary disease (COPD) associated with disease progression and increased mortality. The 6-minute walk test (6MWT) is a reliable and widely used measure of exercise capacity. However, it is not commonly used in primary medical institutions because it requires a suitable venue and professional training. Developing a simple tool to assess exercise tolerance is important. Molecular biomarkers show potential for evaluating the clinical outcomes (mortality, exacerbation) of COPD patients. The aim of this study was to identify simple and effective biomarkers to predict poor exercise tolerance in COPD patients.MethodsTen genes were selected by weighted correlation network analysis and differentially expressed gene analysis. Validation in an independent dataset led to the identification of PLA2G7, which was verified as a potential biomarker in COPD by bioinformatics analysis. The concentration of lipoprotein-associated phospholipase A2 (Lp-PLA2), which is encoded by the PLA2G7 gene, was assessed by enzyme-linked immunosorbent assay in a prospective validation cohort. The predictive capacity of Lp-PLA2 for 6-minute walk distance (6MWD) < 350 m was assessed using the area under the receiver operating characteristic curve (AUC). Traditional clinical features and Lp-PLA2 levels were incorporated into a nomogram to build a predictive model for poor exercise tolerance.ResultsThe final cohort included 92 stable COPD patients and 16 healthy smokers. Lp-PLA2 was upregulated in COPD patients and increased along with GOLD stage. Lp-PLA2 level was significant correlated with FEV1/FVC, BMI, FFMI, CAT score, mMRC score, and 6MWD in COPD patients. The predictive efficacy of Lp-PLA2 level (AUC: 0.796) and the derived nomogram model (AUC: 0.884) for exercise tolerance was superior to that of the sit-to-stand test and traditional clinical features.ConclusionLp-PLA2 is a promising biomarker for COPD patients and is suitable for assessing exercise tolerance in clinical practice.

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Knockdown of G‐protein‐signaling modulator 2 promotes metastasis of non‐small‐cell lung cancer by inducing the expression of Snail

Cited by 18 publications

References 30 publications

Identification of an extracellular vesicle-related gene signature in the prediction of pancreatic cancer clinical prognosis

Identification of an extracellular vesicle-related gene signature in the prediction of pancreatic cancer clinical prognosis

Identification of Inflammation-Related Biomarker Lp-PLA2 for Patients With COPD by Comprehensive Analysis

Lipoprotein-associated phospholipase A2 predicts exercise tolerance in COPD patients

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