Background: Derlin 3 (DERL3) is downregulated in colorectal cancer (CRC) samples. Its level is closely linked to lymphatic metastasis or distant metastasis rate in CRC patients. However, its biological behavior in lung adenocarcinoma were rarely reported. The aim of this study is to investigate the ectopic expression of DERL3 in lung adenocarcinoma tissues and its effect on the invasion and metastasis of lung adenocarcinoma A549 cell line to reveal the possible mechanism of invasion and metastasis of lung adenocarcinoma.
Methods: Lung adenocarcinoma microarray gene chip data included 3 cases of lymph node metastasis and 3 cases of lung adenocarcinoma tissue without lymph node metastasis. The GEDS and Kaplan-Meier plot queries the survival curve and expression level of DERL3. Western blot was used to detect the expression of DERL3 in lung adenocarcinoma cells. The efficiency of knockdown DERL3 gene was detected by Western blot assay. Transwell detected the number of cells passing through the basement membrane of the transwell. EDU assay detected cell proliferation ability. Western blot detected the expression of epithelial-mesenchymal transition related proteins E-cadherin and Vimentin.
Results: The microarray gene chip results showed that compared with lung adenocarcinoma tissues without lymph node metastasis, 1,314 mRNAs in lung adenocarcinoma tissues with lymph node metastasis were up-regulated, 400 mRNAs were down (P<0.05). The expression of DERL3 increased in lung adenocarcinoma (P<0.05). The results of survival curve showed that the lung cancer patients with high expression of DERL3 with poor prognosis (P<0.05). Western blot results indicated that plasmid transfection was successful. Knockdown of DERL3 suppressed the ability of proliferation, invasion and migration in A549 cells (P<0.05). After knockdown of DERL3, the expression level of Vimentin was decreased, while E-cadherin expression increased (P<0.05).
Conclusions: Knockdown of DERL3 inhibited the proliferation, invasion and metastasis of A549 cells.
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http://dx.doi.org/10.3779/j.issn.1009-3419.2020.104.22 | DOI Listing |
Anticancer Drugs
January 2025
Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning.
Uncommon atypical mutations account for 10-15% of all epidermal growth factor receptor (EGFR) activating mutations in nonsmall-cell lung cancer (NSCLC). Tumors harboring rare EGFR mutations show highly heterogeneous responses to EGFR tyrosine kinase inhibitors (TKIs). There is insufficient clinical evidence for uncommon types of EGFR mutations, especially those with compound EGFR mutations.
View Article and Find Full Text PDFProceedings (IEEE Int Conf Bioinformatics Biomed)
December 2024
Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, USA.
Lung cancer remains a predominant cause of cancer-related deaths, with notable disparities in incidence and outcomes across racial and gender groups. This study addresses these disparities by developing a computational framework leveraging explainable artificial intelligence (XAI) to identify both patient- and cohort-specific biomarker genes in lung cancer. Specifically, we focus on two lung cancer subtypes, Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC), examining distinct racial and sex-specific cohorts: African American males (AAMs) and European American males (EAMs).
View Article and Find Full Text PDFFront Public Health
January 2025
School of Public Health, Gansu University of Chinese Medicine, Lanzhou, China.
Objective: To investigate the role of PCBP1 in the inhibition of lung adenocarcinoma proliferation by carbon irradiation.
Methods: A549 cells were irradiated with different doses of carbon ions to observe clonal survival and detect changes in cell proliferation. Whole transcriptome sequencing and the Illumina platform were used to analyze the differentially expressed genes in A549 cells after carbon ion irradiation.
Front Oncol
January 2025
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Objective: To develop and validate a deep learning signature for noninvasive prediction of spread through air spaces (STAS) in clinical stage I lung adenocarcinoma and compare its predictive performance with conventional clinical-semantic model.
Methods: A total of 513 patients with pathologically-confirmed stage I lung adenocarcinoma were retrospectively enrolled and were divided into training cohort (n = 386) and independent validation cohort (n = 127) according to different center. Clinicopathological data were collected and CT semantic features were evaluated.
Front Oncol
January 2025
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Purpose: To develop and validate a radiomics nomogram model for predicting the micropapillary pattern (MPP) in lung adenocarcinoma (LUAD) tumors of ≤2 cm in size.
Methods: In this study, 300 LUAD patients from our institution were randomly divided into the training cohort (n = 210) and an internal validation cohort (n = 90) at a ratio of 7:3, besides, we selected 65 patients from another hospital as the external validation cohort. The region of interest of the tumor was delineated on the computed tomography (CT) images, and radiomics features were extracted.
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