Metastasis from lung adenocarcinoma can occur swiftly to multiple organs within months of diagnosis. The mechanisms that confer this rapid metastatic capacity to lung tumors are unknown. Activation of the canonical WNT/TCF pathway is identified here as a determinant of metastasis to brain and bone during lung adenocarcinoma progression. Gene expression signatures denoting WNT/TCF activation are associated with relapse to multiple organs in primary lung adenocarcinoma. Metastatic subpopulations isolated from independent lymph node-derived lung adenocarcinoma cell lines harbor a hyperactive WNT/TCF pathway. Reduction of TCF activity in these cells attenuates their ability to form brain and bone metastases in mice, independently of effects on tumor growth in the lungs. The WNT/TCF target genes HOXB9 and LEF1 are identified as mediators of chemotactic invasion and colony outgrowth. Thus, a distinct WNT/TCF signaling program through LEF1 and HOXB9 enhances the competence of lung adenocarcinoma cells to colonize the bones and the brain. For a video summary of this article, see the PaperFlick file available with the online Supplemental Data.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2742946 | PMC |
| http://dx.doi.org/10.1016/j.cell.2009.04.030 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The effectiveness of sequential afatinib and furmonertinib in an advanced lung adenocarcinoma with rare compound EGFR mutation (L833V/H835L).
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 PDFInterpreting Lung Cancer Health Disparity between African American Males and European American Males.
Proceedings (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 PDFThe role of PCBP1 in carbon ion-induced ferroptosis and inhibition of lung adenocarcinoma proliferation.
Front 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.
A CT-based deep learning model for preoperative prediction of spread through air spaces in clinical stage I lung adenocarcinoma.
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.
Preoperative CT-based radiomics nomogram to predict the micropapillary pattern in lung adenocarcinoma of size 2 cm or less.
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.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!