Objective: Smoking is a prominent risk factor for lung cancer. However, it is not an established prognostic factor for lung cancer in clinics. To date, no gene test is available for diagnostic screening of lung cancer risk or prognostication of clinical outcome in smokers. This study sought to identify a smoking associated gene signature in order to provide a more precise diagnosis and prognosis of lung cancer in smokers.
Methods And Materials: An implication network based methodology was used to identify biomarkers by modeling crosstalk with major lung cancer signaling pathways. Specifically, the methodology contains the following steps: (1) identifying genes significantly associated with lung cancer survival; (2) selecting candidate genes which are differentially expressed in smokers versus non-smokers from the survival genes identified in Step 1; (3) from these candidate genes, constructing gene coexpression networks based on prediction logic for the smoker group and the non-smoker group, respectively; (4) identifying smoking-mediated differential components, i.e., the unique gene coexpression patterns specific to each group; and (5) from the differential components, identifying genes directly co-expressed with major lung cancer signaling hallmarks.
Results: A smoking-associated 6-gene signature was identified for prognosis of lung cancer from a training cohort (n=256). The 6-gene signature could separate lung cancer patients into two risk groups with distinct post-operative survival (log-rank P<0.04, Kaplan-Meier analyses) in three independent cohorts (n=427). The expression-defined prognostic prediction is strongly related to smoking association and smoking cessation (P<0.02; Pearson's Chi-squared tests). The 6-gene signature is an accurate prognostic factor (hazard ratio=1.89, 95% CI: [1.04, 3.43]) compared to common clinical covariates in multivariate Cox analysis. The 6-gene signature also provides an accurate diagnosis of lung cancer with an overall accuracy of 73% in a cohort of smokers (n=164). The coexpression patterns derived from the implication networks were validated with interactions reported in the literature retrieved with STRING8, Ingenuity Pathway Analysis, and Pathway Studio.
Conclusions: The pathway-based approach identified a smoking-associated 6-gene signature that predicts lung cancer risk and survival. This gene signature has potential clinical implications in the diagnosis and prognosis of lung cancer in smokers.
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http://dx.doi.org/10.1016/j.artmed.2012.01.001 | DOI Listing |
J Cardiothorac Surg
January 2025
Thoracic Surgery Unit, Careggi University Hospital, Largo Brambilla, 1, 50134, Florence, Italy.
Background: Lung cancer is the first cause of cancer-related death. Awake lung resection is a new frontier of the concept of minimally invasive surgery. Our purpose is to demonstrate the feasibility of this technique for lobar and sublobar lung resection in NSCLC patients.
View Article and Find Full Text PDFBackground: Metabolic pathways are known to significantly impact the development and advancement of lung cancer. This study sought to establish a signature related to butyrate metabolism that is specifically linked to lung adenocarcinoma (LUAD).
Methods: For the purpose of identifying butyrate metabolism-related differentially expressed genes (BMR-DEGs) in the TCGA-LUAD dataset, we introduced transcriptome data.
Discov Oncol
January 2025
Spinal Surgery Department, the Fourth People's Hospital of Jinan, No.50 Normal Road, Tianqiao District, Jinan, 250031, Shandong, China.
Background: It is known that genomic instability contributes to cancer development. Mitotically associated long non-coding RNA (MANCR) has been reported to promote genomic stability, suggesting its involvement in cancers. Therefore, this study was conducted to investigate the role of MANCR in non-small cell lung cancer (NSCLC).
View Article and Find Full Text PDFDiscov Oncol
January 2025
The School Public Health, Fujian Medical University, Fuzhou, 350122, Fujian, China.
The prognosis and treatment efficacy of lung adenocarcinoma (LUAD), a disease with a high incidence, remains unsatisfactory. Identifying new biomarkers and therapeutic targets for LUAD is essential. Chromosomal assembly factor 1B (CHAF1B), a p60 component of the CAF-1 complex, is closely linked to tumor incidence and cell proliferation.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Respiratory Department, Zhejiang Jinhua Guangfu Cancer Hospital, Jinhua, 310053, Zhejiang, China.
Background: Plasma proteins contribute to the identification, diagnosis, and prognosis of human illnesses, which may be conducive to understanding the molecular mechanism and diagnosis of Lung adenocarcinoma (LUAD).
Methods: We collected plasma samples from 28 healthy individuals (H) and 56 LUAD patients and analyzed them using LC-MS/MS-based proteomics to determine differential expression plasma proteins (DEPPs). Then, the DEPPs were subjected to a two-sample Mendelian randomization (MR) study based on an "Inverse variance weighted (IVW)" approach to investigate the causal relationships between DEPPs and LUAD.
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