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. 2016 Apr 20:17:42.
doi: 10.1186/s12931-016-0346-3.

Gene-expression profiles in lung adenocarcinomas related to chronic wood smoke or tobacco exposure

Alette Ortega-Gómez  1   2 , Claudia Rangel-Escareño  3 , Camilo Molina-Romero  1 , Eleazar Omar Macedo-Pérez  1 , Alejandro Avilés-Salas  4 , Alejandra Lara-García  5 , Gerardo Alanis-Funes  6 , Rubén Rodríguez-Bautista  1 , Alfredo Hidalgo-Miranda  7 , Oscar Arrieta  8   9
Affiliations

Gene-expression profiles in lung adenocarcinomas related to chronic wood smoke or tobacco exposure

Alette Ortega-Gómez et al. Respir Res. .

Abstract

Background: Tobacco-smoke is the major etiological factor related to lung cancer. However, other important factor is chronic wood smoke exposure (WSE). Approximately 30 % of lung cancer patients in Mexico have a history of WSE, and present different clinical, pathological and molecular characteristics compared to tobacco related lung cancer, including differences in mutational profiles. There are several molecular alterations identified in WSE associated lung cancer, however most studies have focused on the analysis of changes in several pathogenesis related proteins.

Methods: Our group evaluated gene expression profiles of primary lung adenocarcinoma, from patients with history of WSE or tobacco exposure. Differential expression between these two groups were studied through gene expression microarrays.

Results: Results of the gene expression profiling revealed 57 statistically significant genes (p < 0.01). The associated biological functional pathways included: lipid metabolism, biochemistry of small molecules, molecular transport, cell morphology, function and maintenance. A highlight of our analysis is that three of the main functional networks represent 37 differentially expressed genes out of the 57 found. These hubs are related with ubiquitin C, GABA(A) receptor-associated like protein; and the PI3K/AKT and MEK/ERK signaling pathways.

Conclusion: Our results reflect the intrinsic biology that sustains the development of adenocarcinoma related to WSE and show that there is a different gene expression profile of WSE associated lung adenocarcinoma compared to tobacco exposure, suggesting that they arise through different carcinogenic mechanisms, which may explain the clinical and mutation profile divergences between both lung adenocarcinomas.

Keywords: Gene expression profiles; Microarray analysis; Non-small cell lung carcinoma; Tobacco smoke; Wood smoke exposure.

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Figures

Fig. 1
Fig. 1
Consort
Fig. 2
Fig. 2
Volcano Plot showing gene differential expression of patients with adenocarcinoma and history of wood smoke exposure vs. tobacco smoke exposure. Fold changes are represented in log2 base along the x-axis and the level of trust in the form of –log10 (p < 0.001) along the y-axis. The cut off value of 10−2 used is 2 on the y-axis (top right and left corners). Red and green dots represent up and down-regulated genes respectively: Fold change (≥1.2) and significance level (p < 0.001). Other colors: yellow indicates significant but low fold change, magenta shows not statistically robust changes and blue shows low fold change with low statistical significance
Fig. 3
Fig. 3
Heat map result of an unsupervised hierarchical clustering of genes significantly different (p < 0.01) of NSCLC adenocarcinoma exposed to wood smoke versus tobacco smoke. Each column represents a patient and each row a gene. The heat map indicates the level of gene expression. Red: high expression; Green: Low expression
Fig. 4
Fig. 4
Network 1 (Score: 28/Ratio: 0.353/p value: 1.48E-24). Genes (p < 0.01) in wood smoke exposure in NSCLC around the UBC gene. Red mark: up-regulated genes. Green mark: down-regulated genes. The node shapes denote enzymes (formula image), phosphatases (formula image), kinases (formula image), peptidases (formula image), G-protein coupled receptor (formula image), transmembrane receptor (formula image), cytokines (formula image), growth factor (formula image), ion channel (formula image), transporter (formula image), translation factor (formula image), nuclear receptor (formula image), transcription factor (formula image) and other (formula image)
Fig. 5
Fig. 5
Network 2 (Score: 28/Ratio: 0.375/p value: 6.11E-25). Genes (p < 0.01) in wood smoke exposure in NSCLC around the GABARAPL1 gene. Red mark: up-regulated genes. Green mark: down-regulated genes. The node shapes denote enzymes (formula image), phosphatases (formula image), kinases (formula image), peptidases (formula image), G-protein coupled receptor (formula image), transmembrane receptor (formula image), cytokines (formula image), growth factor (formula image), ion channel (formula image), transporter (formula image), translation factor (formula image), nuclear receptor (formula image), transcription factor (formula image) and other (formula image)
Fig. 6
Fig. 6
Network 3 (Score: 26/Ratio: 0.134/p value: 2.09E-17). Genes (p < 0.01) in wood smoke exposure in NSCLC around the PI3K/AKT and MEK/ERK signaling pathways. Red mark: up-regulated genes. Green mark: down-regulated genes. The node shapes denote enzymes (formula image), phosphatases (formula image), kinases (formula image), peptidases (formula image), G-protein coupled receptor (formula image), transmembrane receptor (formula image), cytokines (formula image), growth factor (formula image), ion channel (formula image), transporter (formula image), translation factor (formula image), nuclear receptor (formula image), transcription factor (formula image) and other (formula image)
Fig. 7
Fig. 7
Overlapping networks and related genes (p < 0.01) in wood smoke exposure in NSCLC. Red mark: up-regulated genes. Green mark: down-regulated genes. Purple lines reflect the sites of intersections between our study genes (p < 0.01) and the main canonical networks (PI3K/AKT and MEK/ERK) associated with NSCLC. The node shapes denote enzymes (♦), phosphatases (formula image), kinases (formula image), peptidases (formula image), G-protein coupled receptor ( ), transmembrane receptor ( ), cytokines (formula image), growth factor (formula image), ion channel (formula image), transporter ( ), translation factor (formula image), nuclear receptor (formula image), transcription factor (formula image) and other (formula image)
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