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Gene expression subtraction of non-cancerous lung from smokers and non-smokers with adenocarcinoma, as a predictor for smokers developing lung cancer.

Stav D, Bar I, Sandbank J - J. Exp. Clin. Cancer Res. (2008)

Bottom Line: The genes subtraction resulted in disclosure of 36 genes with high score.They were subsequently mapped and sorted based on location, cellular components, and biochemical activity.In addition, since these genes originating from non-cancerous lung, which is the major area of the lungs, a sample from an induced sputum may represent it.

View Article: PubMed Central - HTML - PubMed

Affiliation: Pulmonary Institute, Assaf Harofeh Medical Center, Zerrifin 70300, Israel. dstav@asaf.health.gov.il

ABSTRACT

Background: Lung cancer is the commonest cause of cancer death in developed countries. Adenocarcinoma is becoming the most common form of lung cancer. Cigarette smoking is the main risk factor for lung cancer. Long-term cigarettes smoking may be characterized by genetic alteration and diffuse injury of the airways surface, named field cancerization, while cancer in non-smokers is usually clonally derived. Detecting specific genes expression changes in non-cancerous lung in smokers with adenocarcinoma may give us instrument for predicting smokers who are going to develop this malignancy.

Objectives: We described the gene expression in non-cancerous lungs from 21 smoker patients with lung adenocarcinoma and compare it to gene expression in non-cancerous lung tissue from 10 non-smokers with primary lung adenocarcinoma.

Methods: Total RNA was isolated from peripheral non-cancerous lung tissue. The cDNA was hybridized to the U133A GeneChip array. Hierarchical clustering analysis on genes obtained from smokers and non-smokers, after subtracting were exported to the Ingenuity Pathway Analysis software for further analysis.

Results: The genes subtraction resulted in disclosure of 36 genes with high score. They were subsequently mapped and sorted based on location, cellular components, and biochemical activity. The gene functional analysis disclosed 20 genes, which are involved in cancer process (P = 7.05E-5 to 2.92E-2).

Conclusion: Detected genes may serve as a predictor for smokers who may be at high risk of developing lung cancer. In addition, since these genes originating from non-cancerous lung, which is the major area of the lungs, a sample from an induced sputum may represent it.

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Related in: MedlinePlus

Gene network is from IPA analysis. Gene interaction is shown, red colored up-regulated, green colored suppressed. Color intensity is relative to expression. Genes along canonical pathways that were not changed at transcript level are not colored. The arrow pointed toward the direction of positive regulation.
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Figure 1: Gene network is from IPA analysis. Gene interaction is shown, red colored up-regulated, green colored suppressed. Color intensity is relative to expression. Genes along canonical pathways that were not changed at transcript level are not colored. The arrow pointed toward the direction of positive regulation.

Mentions: The clinical profile of the patients is shown in Table 1. This includes patients' pulmonary function data, which showed that 12 smokers had chronic obstructive pulmonary disease (COPD)(FEV1 < 75%), whereas none of the non-smokers own this limitation. GeneSpring hierarchical clustering was applied to gene expression profiles. We subtracted highly expressed genes of non-smokers from smokers this disclosed 36 genes that were expressed differently between smoker and non-smokers. The Ingenuity analysis and sorting of the 36 genes according theirs expression (bolded and italic over-expressed) or suppressed (normal) while forming networks (Table 2). The first network includes very high scored and focus genes, which are involved in cell death, cancer and inflammatory processes. The following networks with lower score (but still high) and focus genes, included genes that are involved in cellular assembly and organization, cellular function and maintenance. The illustrated network (Fig. 1) (serve as a paradigm) demonstrates the intensity of genes over-expressed (red) or suppressed (green) in smokers compared to non-smokers, and their genes network formation. The network includes genes that are cancer promoters and tumor suppressors such as FYN HSPA8, YWHAZ, LEPR and TGFBR2, IRF2, EP3000 respectively. The suppression of the genes EGR1 and STAT1 correlates with active tumor formation. Many networks include fewer genes in spite of being scored high. This is probably due to lack of knowledge.


Gene expression subtraction of non-cancerous lung from smokers and non-smokers with adenocarcinoma, as a predictor for smokers developing lung cancer.

Stav D, Bar I, Sandbank J - J. Exp. Clin. Cancer Res. (2008)

Gene network is from IPA analysis. Gene interaction is shown, red colored up-regulated, green colored suppressed. Color intensity is relative to expression. Genes along canonical pathways that were not changed at transcript level are not colored. The arrow pointed toward the direction of positive regulation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2570656&req=5

Figure 1: Gene network is from IPA analysis. Gene interaction is shown, red colored up-regulated, green colored suppressed. Color intensity is relative to expression. Genes along canonical pathways that were not changed at transcript level are not colored. The arrow pointed toward the direction of positive regulation.
Mentions: The clinical profile of the patients is shown in Table 1. This includes patients' pulmonary function data, which showed that 12 smokers had chronic obstructive pulmonary disease (COPD)(FEV1 < 75%), whereas none of the non-smokers own this limitation. GeneSpring hierarchical clustering was applied to gene expression profiles. We subtracted highly expressed genes of non-smokers from smokers this disclosed 36 genes that were expressed differently between smoker and non-smokers. The Ingenuity analysis and sorting of the 36 genes according theirs expression (bolded and italic over-expressed) or suppressed (normal) while forming networks (Table 2). The first network includes very high scored and focus genes, which are involved in cell death, cancer and inflammatory processes. The following networks with lower score (but still high) and focus genes, included genes that are involved in cellular assembly and organization, cellular function and maintenance. The illustrated network (Fig. 1) (serve as a paradigm) demonstrates the intensity of genes over-expressed (red) or suppressed (green) in smokers compared to non-smokers, and their genes network formation. The network includes genes that are cancer promoters and tumor suppressors such as FYN HSPA8, YWHAZ, LEPR and TGFBR2, IRF2, EP3000 respectively. The suppression of the genes EGR1 and STAT1 correlates with active tumor formation. Many networks include fewer genes in spite of being scored high. This is probably due to lack of knowledge.

Bottom Line: The genes subtraction resulted in disclosure of 36 genes with high score.They were subsequently mapped and sorted based on location, cellular components, and biochemical activity.In addition, since these genes originating from non-cancerous lung, which is the major area of the lungs, a sample from an induced sputum may represent it.

View Article: PubMed Central - HTML - PubMed

Affiliation: Pulmonary Institute, Assaf Harofeh Medical Center, Zerrifin 70300, Israel. dstav@asaf.health.gov.il

ABSTRACT

Background: Lung cancer is the commonest cause of cancer death in developed countries. Adenocarcinoma is becoming the most common form of lung cancer. Cigarette smoking is the main risk factor for lung cancer. Long-term cigarettes smoking may be characterized by genetic alteration and diffuse injury of the airways surface, named field cancerization, while cancer in non-smokers is usually clonally derived. Detecting specific genes expression changes in non-cancerous lung in smokers with adenocarcinoma may give us instrument for predicting smokers who are going to develop this malignancy.

Objectives: We described the gene expression in non-cancerous lungs from 21 smoker patients with lung adenocarcinoma and compare it to gene expression in non-cancerous lung tissue from 10 non-smokers with primary lung adenocarcinoma.

Methods: Total RNA was isolated from peripheral non-cancerous lung tissue. The cDNA was hybridized to the U133A GeneChip array. Hierarchical clustering analysis on genes obtained from smokers and non-smokers, after subtracting were exported to the Ingenuity Pathway Analysis software for further analysis.

Results: The genes subtraction resulted in disclosure of 36 genes with high score. They were subsequently mapped and sorted based on location, cellular components, and biochemical activity. The gene functional analysis disclosed 20 genes, which are involved in cancer process (P = 7.05E-5 to 2.92E-2).

Conclusion: Detected genes may serve as a predictor for smokers who may be at high risk of developing lung cancer. In addition, since these genes originating from non-cancerous lung, which is the major area of the lungs, a sample from an induced sputum may represent it.

Show MeSH
Related in: MedlinePlus