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Transcriptome profiles of carcinoma-in-situ and invasive non-small cell lung cancer as revealed by SAGE.

Lonergan KM, Chari R, Coe BP, Wilson IM, Tsao MS, Ng RT, Macaulay C, Lam S, Lam WL - PLoS ONE (2010)

Bottom Line: Expression of genes associated with epidermal development, and loss of expression of genes associated with mucociliary biology, are predominant features of CIS, largely shared with precancerous lesions.Additionally, expression of genes associated with xenobiotic metabolism/detoxification is a notable feature of CIS, and is largely maintained in invasive cancer.Additionally, up-regulated genes detected at extreme differences between CIS and invasive cancer may have potential to serve as biomarkers for early detection.

View Article: PubMed Central - PubMed

Affiliation: Genetics Unit, Integrative Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.

ABSTRACT

Background: Non-small cell lung cancer (NSCLC) presents as a progressive disease spanning precancerous, preinvasive, locally invasive, and metastatic lesions. Identification of biological pathways reflective of these progressive stages, and aberrantly expressed genes associated with these pathways, would conceivably enhance therapeutic approaches to this devastating disease.

Methodology/principal findings: Through the construction and analysis of SAGE libraries, we have determined transcriptome profiles for preinvasive carcinoma-in-situ (CIS) and invasive squamous cell carcinoma (SCC) of the lung, and compared these with expression profiles generated from both bronchial epithelium, and precancerous metaplastic and dysplastic lesions using Ingenuity Pathway Analysis. Expression of genes associated with epidermal development, and loss of expression of genes associated with mucociliary biology, are predominant features of CIS, largely shared with precancerous lesions. Additionally, expression of genes associated with xenobiotic metabolism/detoxification is a notable feature of CIS, and is largely maintained in invasive cancer. Genes related to tissue fibrosis and acute phase immune response are characteristic of the invasive SCC phenotype. Moreover, the data presented here suggests that tissue remodeling/fibrosis is initiated at the early stages of CIS. Additionally, this study indicates that alteration in copy-number status represents a plausible mechanism for differential gene expression in CIS and invasive SCC.

Conclusions/significance: This study is the first report of large-scale expression profiling of CIS of the lung. Unbiased expression profiling of these preinvasive and invasive lesions provides a platform for further investigations into the molecular genetic events relevant to early stages of squamous NSCLC development. Additionally, up-regulated genes detected at extreme differences between CIS and invasive cancer may have potential to serve as biomarkers for early detection.

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Analysis of the top 300 most abundant tags from the BE, CIS, and invasive cancer datasets.A. Cluster analysis of lung SAGE libraries. All SAGE libraries from this study, including five carcinoma in-situ libraries (CIS-1 through CIS-5), six invasive squamous cell carcinoma libraries (SCC-1 through SCC-6), one squamous metaplasia library (Met), and one squamous dysplasia library (Dys), as well as 14 bronchial epithelial libraries (BE-1 through BE-14), and two normal lung parenchyma SAGE libraries (LP-1, LP-2; accession GSE3708) generated in a previous study [19], [37], were analyzed by cluster analysis using an average-linkage algorithm. The top 300 most abundant tags were retained from each library, and analysis was based on 1128 unique tags in total. In the dendrogram, branch length represents distance. B–D. IPA functional analysis of the most abundant genes in the BE, CIS, and invasive cancer datasets. Tag-to-gene mappings for the top 300 most abundant tags from the BE, CIS, and SCC datasets, were used for IPA core analysis, consisting of 220, 231, and 233 IPA eligible mapped IDs, respectively. The three sets of data were displayed together using IPA core comparisons, and the five most significant functions within Physiological System Development and Function are shown for each of the three datasets. The data in B is sorted according to highest significance in BE, the data in C is sorted according to highest significance in CIS, and the data in D is sorted according to highest significance in invasive SCC. The orange line indicates the threshold limit of significance, preset at a p-value of 0.05. For a complete listing of the tags/mapped IDs used for this analysis see Table S1.
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pone-0009162-g002: Analysis of the top 300 most abundant tags from the BE, CIS, and invasive cancer datasets.A. Cluster analysis of lung SAGE libraries. All SAGE libraries from this study, including five carcinoma in-situ libraries (CIS-1 through CIS-5), six invasive squamous cell carcinoma libraries (SCC-1 through SCC-6), one squamous metaplasia library (Met), and one squamous dysplasia library (Dys), as well as 14 bronchial epithelial libraries (BE-1 through BE-14), and two normal lung parenchyma SAGE libraries (LP-1, LP-2; accession GSE3708) generated in a previous study [19], [37], were analyzed by cluster analysis using an average-linkage algorithm. The top 300 most abundant tags were retained from each library, and analysis was based on 1128 unique tags in total. In the dendrogram, branch length represents distance. B–D. IPA functional analysis of the most abundant genes in the BE, CIS, and invasive cancer datasets. Tag-to-gene mappings for the top 300 most abundant tags from the BE, CIS, and SCC datasets, were used for IPA core analysis, consisting of 220, 231, and 233 IPA eligible mapped IDs, respectively. The three sets of data were displayed together using IPA core comparisons, and the five most significant functions within Physiological System Development and Function are shown for each of the three datasets. The data in B is sorted according to highest significance in BE, the data in C is sorted according to highest significance in CIS, and the data in D is sorted according to highest significance in invasive SCC. The orange line indicates the threshold limit of significance, preset at a p-value of 0.05. For a complete listing of the tags/mapped IDs used for this analysis see Table S1.

Mentions: Cluster analysis yielded anticipated grouping of SAGE libraries, attesting to sample quality. For this analysis, the 300 most abundant tags were retained from each library, yielding a merged list of 1128 unique tags. Average linkage clustering analysis based on the 1128 most abundant SAGE tags, reveals that all cancer libraries (both CIS and invasive SCC) cluster together, and separately from the BE libraries (Figure 2A). We note some clustering of the invasive SCC libraries (four out of six). Similar clustering is observed when using the top 500 or top 1000 unique tags per library (data not shown).


Transcriptome profiles of carcinoma-in-situ and invasive non-small cell lung cancer as revealed by SAGE.

Lonergan KM, Chari R, Coe BP, Wilson IM, Tsao MS, Ng RT, Macaulay C, Lam S, Lam WL - PLoS ONE (2010)

Analysis of the top 300 most abundant tags from the BE, CIS, and invasive cancer datasets.A. Cluster analysis of lung SAGE libraries. All SAGE libraries from this study, including five carcinoma in-situ libraries (CIS-1 through CIS-5), six invasive squamous cell carcinoma libraries (SCC-1 through SCC-6), one squamous metaplasia library (Met), and one squamous dysplasia library (Dys), as well as 14 bronchial epithelial libraries (BE-1 through BE-14), and two normal lung parenchyma SAGE libraries (LP-1, LP-2; accession GSE3708) generated in a previous study [19], [37], were analyzed by cluster analysis using an average-linkage algorithm. The top 300 most abundant tags were retained from each library, and analysis was based on 1128 unique tags in total. In the dendrogram, branch length represents distance. B–D. IPA functional analysis of the most abundant genes in the BE, CIS, and invasive cancer datasets. Tag-to-gene mappings for the top 300 most abundant tags from the BE, CIS, and SCC datasets, were used for IPA core analysis, consisting of 220, 231, and 233 IPA eligible mapped IDs, respectively. The three sets of data were displayed together using IPA core comparisons, and the five most significant functions within Physiological System Development and Function are shown for each of the three datasets. The data in B is sorted according to highest significance in BE, the data in C is sorted according to highest significance in CIS, and the data in D is sorted according to highest significance in invasive SCC. The orange line indicates the threshold limit of significance, preset at a p-value of 0.05. For a complete listing of the tags/mapped IDs used for this analysis see Table S1.
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Related In: Results  -  Collection

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pone-0009162-g002: Analysis of the top 300 most abundant tags from the BE, CIS, and invasive cancer datasets.A. Cluster analysis of lung SAGE libraries. All SAGE libraries from this study, including five carcinoma in-situ libraries (CIS-1 through CIS-5), six invasive squamous cell carcinoma libraries (SCC-1 through SCC-6), one squamous metaplasia library (Met), and one squamous dysplasia library (Dys), as well as 14 bronchial epithelial libraries (BE-1 through BE-14), and two normal lung parenchyma SAGE libraries (LP-1, LP-2; accession GSE3708) generated in a previous study [19], [37], were analyzed by cluster analysis using an average-linkage algorithm. The top 300 most abundant tags were retained from each library, and analysis was based on 1128 unique tags in total. In the dendrogram, branch length represents distance. B–D. IPA functional analysis of the most abundant genes in the BE, CIS, and invasive cancer datasets. Tag-to-gene mappings for the top 300 most abundant tags from the BE, CIS, and SCC datasets, were used for IPA core analysis, consisting of 220, 231, and 233 IPA eligible mapped IDs, respectively. The three sets of data were displayed together using IPA core comparisons, and the five most significant functions within Physiological System Development and Function are shown for each of the three datasets. The data in B is sorted according to highest significance in BE, the data in C is sorted according to highest significance in CIS, and the data in D is sorted according to highest significance in invasive SCC. The orange line indicates the threshold limit of significance, preset at a p-value of 0.05. For a complete listing of the tags/mapped IDs used for this analysis see Table S1.
Mentions: Cluster analysis yielded anticipated grouping of SAGE libraries, attesting to sample quality. For this analysis, the 300 most abundant tags were retained from each library, yielding a merged list of 1128 unique tags. Average linkage clustering analysis based on the 1128 most abundant SAGE tags, reveals that all cancer libraries (both CIS and invasive SCC) cluster together, and separately from the BE libraries (Figure 2A). We note some clustering of the invasive SCC libraries (four out of six). Similar clustering is observed when using the top 500 or top 1000 unique tags per library (data not shown).

Bottom Line: Expression of genes associated with epidermal development, and loss of expression of genes associated with mucociliary biology, are predominant features of CIS, largely shared with precancerous lesions.Additionally, expression of genes associated with xenobiotic metabolism/detoxification is a notable feature of CIS, and is largely maintained in invasive cancer.Additionally, up-regulated genes detected at extreme differences between CIS and invasive cancer may have potential to serve as biomarkers for early detection.

View Article: PubMed Central - PubMed

Affiliation: Genetics Unit, Integrative Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.

ABSTRACT

Background: Non-small cell lung cancer (NSCLC) presents as a progressive disease spanning precancerous, preinvasive, locally invasive, and metastatic lesions. Identification of biological pathways reflective of these progressive stages, and aberrantly expressed genes associated with these pathways, would conceivably enhance therapeutic approaches to this devastating disease.

Methodology/principal findings: Through the construction and analysis of SAGE libraries, we have determined transcriptome profiles for preinvasive carcinoma-in-situ (CIS) and invasive squamous cell carcinoma (SCC) of the lung, and compared these with expression profiles generated from both bronchial epithelium, and precancerous metaplastic and dysplastic lesions using Ingenuity Pathway Analysis. Expression of genes associated with epidermal development, and loss of expression of genes associated with mucociliary biology, are predominant features of CIS, largely shared with precancerous lesions. Additionally, expression of genes associated with xenobiotic metabolism/detoxification is a notable feature of CIS, and is largely maintained in invasive cancer. Genes related to tissue fibrosis and acute phase immune response are characteristic of the invasive SCC phenotype. Moreover, the data presented here suggests that tissue remodeling/fibrosis is initiated at the early stages of CIS. Additionally, this study indicates that alteration in copy-number status represents a plausible mechanism for differential gene expression in CIS and invasive SCC.

Conclusions/significance: This study is the first report of large-scale expression profiling of CIS of the lung. Unbiased expression profiling of these preinvasive and invasive lesions provides a platform for further investigations into the molecular genetic events relevant to early stages of squamous NSCLC development. Additionally, up-regulated genes detected at extreme differences between CIS and invasive cancer may have potential to serve as biomarkers for early detection.

Show MeSH
Related in: MedlinePlus