Genetic Features of Lung Adenocarcinoma with Ground- Glass Opacity: What Causes the Invasiveness of Lung Adenocarcinoma?

Kim, Dohun; Lee, Jong‐Young; Yoo, Jin Young; Cho, Jun Yeun

doi:10.5090/kjtcs.20.013

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…Genes that are associated with FEV1 in later stages are FRG2C and CHRM3. Gene FRG2C has been found in the non‐ground‐glass opacity LUAD, and it has been indicated to have significant biological functions related to the cell cycle and proliferation 37 . Gene CHRM3 controls smooth muscle contraction and its stimulation causes secretion of the glandular tissue.…”

Section: Application To Tcga Datasetsmentioning

confidence: 99%

Robust nonparametric integrative analysis to decipher heterogeneity and commonality across subgroups using sparse boosting

Luo

Sun

2022

Statistics in Medicine

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In many biomedical problems, data are often heterogeneous, with samples spanning multiple patient subgroups, where different subgroups may have different disease subtypes, stages, or other medical contexts. These subgroups may be related, but they are also expected to have differences with respect to the underlying biology. The heterogeneous data presents a precious opportunity to explore the heterogeneities and commonalities between related subgroups. Unfortunately, effective statistical analysis methods are still lacking. Recently, several novel methods based on integrative analysis have been proposed to tackle this challenging problem. Despite promising results, the existing studies are still limited by ignoring data contamination and making strict assumptions of linear effects of covariates on response. As such, we develop a robust nonparametric integrative analysis approach to identify heterogeneity and commonality, as well as select important covariates and estimate covariate effects. Possible data contamination is accommodated by adopting the Cauchy loss function, and a nonparametric model is built to accommodate nonlinear effects. The proposed approach is based on a sparse boosting technique. The advantages of the proposed approach are demonstrated in extensive simulations. The analysis of The Cancer Genome Atlas data on glioblastoma multiforme and lung adenocarcinoma shows that the proposed approach makes biologically meaningful findings with satisfactory prediction.

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Section: Application To Tcga Datasetsmentioning

confidence: 99%

Robust nonparametric integrative analysis to decipher heterogeneity and commonality across subgroups using sparse boosting

Luo

Sun

2022

Statistics in Medicine

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Comparative genomics between matched solid and lepidic portions of semi-solid lung adenocarcinomas

Woodard¹,

Ding²,

Cho³

et al. 2023

Lung Cancer

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SGO2 as a Prognostic Biomarker Correlated with Cell Proliferation, Migration, Invasion, and Epithelial-Mesenchymal Transition in Lung Adenocarcinoma

Chen,

Xiang

2024

Front. Biosci. (Landmark Ed)

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Background: Lung adenocarcinoma (LUAD) is the predominant histological subtype among non-small cell lung cancer cases, representing approximately 40% of all cases. Shugoshin 2 (SGO2) is implicated in tumorigenesis and tumor progression. This study aimed to uncover a potential role of SGO2 in the LUAD. Methods: Data related to gene mRNA expression and clinical information were obtained from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), and the Cancer Cell Line Encyclopedia (CCLE) databases. Cell Counting Kit-8 (CCK-8), Transwell, scratch assay, and flow cytometry were applied to investigate the biological functions of SGO2 in the LUAD. Western blot was conducted to detect the protein expression. Results: Through pan-cancer analysis, SGO2 was found to be consistently overexpressed in 25 of 33 cancer types, including LUAD. In vitro assays revealed that SGO2 knockdown significantly impeded cell proliferation, cell migration, invasion and epithelial-mesenchymal transition (EMT), whereas its overexpression promoted these abilities. Flow cytometry confirmed that SGO2 contributed to cell cycle progression and reduced cell apoptosis. Furthermore, SGO2 facilitated cell proliferation and regulated cell cycle through upregulating recombinant E2F transcription factor 1 (E2F1). Conclusions: Our study demonstrated that SGO2 was up-regulated in pan-cancers including LUAD and its high expression was strongly associated with poor overall survival (OS) and progression-free survival (PFS) of patients with LUAD. SGO2 promoted cell proliferation, cell migration, invasion and EMT of A549 cells. Additionally, E2F1 was involved in regulation of cell cycle and cell proliferation mediated by SGO2. This research elucidated the oncogenic significance of SGO2 in LUAD, proposing its potential as a prognostic biomarker and a promising target for therapeutic interventions.

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Genetic Features of Lung Adenocarcinoma with Ground- Glass Opacity: What Causes the Invasiveness of Lung Adenocarcinoma?

Cited by 3 publications

References 26 publications

Robust nonparametric integrative analysis to decipher heterogeneity and commonality across subgroups using sparse boosting

Robust nonparametric integrative analysis to decipher heterogeneity and commonality across subgroups using sparse boosting

Comparative genomics between matched solid and lepidic portions of semi-solid lung adenocarcinomas

SGO2 as a Prognostic Biomarker Correlated with Cell Proliferation, Migration, Invasion, and Epithelial-Mesenchymal Transition in Lung Adenocarcinoma

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