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Exon-array profiling unlocks clinically and biologically relevant gene signatures from formalin-fixed paraffin-embedded tumour samples.

Hall JS, Leong HS, Armenoult LS, Newton GE, Valentine HR, Irlam JJ, Möller-Levet C, Sikand KA, Pepper SD, Miller CJ, West CM - Br. J. Cancer (2011)

Bottom Line: Differential gene expression was confirmed using Quantigene, a multiplex bead-based alternative to qRT-PCR.Quantigene analysis of the top 26 differentially expressed genes correctly partitioned cervix samples as SCC or AC.FFPE samples can be profiled using Exon arrays to derive gene expression signatures that are sufficiently robust to be applied to independent data sets, identify novel biology and design assays for independent platform validation.

View Article: PubMed Central - PubMed

Affiliation: Translational Radiobiology Group, School of Cancer and Enabling Sciences, Manchester Academic Health Science Centre, The University of Manchester, Wilmslow Road, Manchester M20 4BX, UK.

ABSTRACT

Background: Degradation and chemical modification of RNA in formalin-fixed paraffin-embedded (FFPE) samples hamper their use in expression profiling studies. This study aimed to show that useful information can be obtained by Exon-array profiling archival FFPE tumour samples.

Methods: Nineteen cervical squamous cell carcinoma (SCC) and 9 adenocarcinoma (AC) FFPE samples (10-16-year-old) were profiled using Affymetrix Exon arrays. The gene signature derived was tested on a fresh-frozen non-small cell lung cancer (NSCLC) series. Exploration of biological networks involved gene set enrichment analysis (GSEA). Differential gene expression was confirmed using Quantigene, a multiplex bead-based alternative to qRT-PCR.

Results: In all, 1062 genes were higher in SCC vs AC, and 155 genes higher in AC. The 1217-gene signature correctly separated 58 NSCLC into SCC and AC. A gene network centered on hepatic nuclear factor and GATA6 was identified in AC, suggesting a role in glandular cell differentiation of the cervix. Quantigene analysis of the top 26 differentially expressed genes correctly partitioned cervix samples as SCC or AC.

Conclusion: FFPE samples can be profiled using Exon arrays to derive gene expression signatures that are sufficiently robust to be applied to independent data sets, identify novel biology and design assays for independent platform validation.

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Related in: MedlinePlus

Identification of novel markers of SCC and AC based on TP63 transcript correlation. Hierarchical clustering of genes and samples was based on Pearson's correlation.
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fig3: Identification of novel markers of SCC and AC based on TP63 transcript correlation. Hierarchical clustering of genes and samples was based on Pearson's correlation.

Mentions: The squamous histology marker p63 (McCluggage, 2007) was detected in all 19 SCC, but none of the 9 AC (Figures 2A and B). Twenty-six separate probesets target TP63 on the arrays. Nineteen of the 26 probesets were detected (DABG P<0.05; Figure 2C) and 18 were differentially expressed between AC and SCC (FDR <0.01; absolute fold-change >2); only 1, ‘2657668', was not. The complete agreement with the immunohistochemistry data shows that Exon array measurements of FFPE RNA reflect genuine changes at the protein level. Given these data we compared genes which correlated and anti-correlated with TP63 gene expression, as a method for identifying putative novel markers of SCC and AC (Figure 3). TP63 correlating genes included well-known markers, such as KRT5 (R2=0.93), along with novel genes such as CTA-55I10.1 (R2=0.95). TP63 anti-correlated genes included MUC13 (R2=−0.81) and EPS8L3 (R2=−0.92).


Exon-array profiling unlocks clinically and biologically relevant gene signatures from formalin-fixed paraffin-embedded tumour samples.

Hall JS, Leong HS, Armenoult LS, Newton GE, Valentine HR, Irlam JJ, Möller-Levet C, Sikand KA, Pepper SD, Miller CJ, West CM - Br. J. Cancer (2011)

Identification of novel markers of SCC and AC based on TP63 transcript correlation. Hierarchical clustering of genes and samples was based on Pearson's correlation.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3065290&req=5

fig3: Identification of novel markers of SCC and AC based on TP63 transcript correlation. Hierarchical clustering of genes and samples was based on Pearson's correlation.
Mentions: The squamous histology marker p63 (McCluggage, 2007) was detected in all 19 SCC, but none of the 9 AC (Figures 2A and B). Twenty-six separate probesets target TP63 on the arrays. Nineteen of the 26 probesets were detected (DABG P<0.05; Figure 2C) and 18 were differentially expressed between AC and SCC (FDR <0.01; absolute fold-change >2); only 1, ‘2657668', was not. The complete agreement with the immunohistochemistry data shows that Exon array measurements of FFPE RNA reflect genuine changes at the protein level. Given these data we compared genes which correlated and anti-correlated with TP63 gene expression, as a method for identifying putative novel markers of SCC and AC (Figure 3). TP63 correlating genes included well-known markers, such as KRT5 (R2=0.93), along with novel genes such as CTA-55I10.1 (R2=0.95). TP63 anti-correlated genes included MUC13 (R2=−0.81) and EPS8L3 (R2=−0.92).

Bottom Line: Differential gene expression was confirmed using Quantigene, a multiplex bead-based alternative to qRT-PCR.Quantigene analysis of the top 26 differentially expressed genes correctly partitioned cervix samples as SCC or AC.FFPE samples can be profiled using Exon arrays to derive gene expression signatures that are sufficiently robust to be applied to independent data sets, identify novel biology and design assays for independent platform validation.

View Article: PubMed Central - PubMed

Affiliation: Translational Radiobiology Group, School of Cancer and Enabling Sciences, Manchester Academic Health Science Centre, The University of Manchester, Wilmslow Road, Manchester M20 4BX, UK.

ABSTRACT

Background: Degradation and chemical modification of RNA in formalin-fixed paraffin-embedded (FFPE) samples hamper their use in expression profiling studies. This study aimed to show that useful information can be obtained by Exon-array profiling archival FFPE tumour samples.

Methods: Nineteen cervical squamous cell carcinoma (SCC) and 9 adenocarcinoma (AC) FFPE samples (10-16-year-old) were profiled using Affymetrix Exon arrays. The gene signature derived was tested on a fresh-frozen non-small cell lung cancer (NSCLC) series. Exploration of biological networks involved gene set enrichment analysis (GSEA). Differential gene expression was confirmed using Quantigene, a multiplex bead-based alternative to qRT-PCR.

Results: In all, 1062 genes were higher in SCC vs AC, and 155 genes higher in AC. The 1217-gene signature correctly separated 58 NSCLC into SCC and AC. A gene network centered on hepatic nuclear factor and GATA6 was identified in AC, suggesting a role in glandular cell differentiation of the cervix. Quantigene analysis of the top 26 differentially expressed genes correctly partitioned cervix samples as SCC or AC.

Conclusion: FFPE samples can be profiled using Exon arrays to derive gene expression signatures that are sufficiently robust to be applied to independent data sets, identify novel biology and design assays for independent platform validation.

Show MeSH
Related in: MedlinePlus