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Identification and Validation of a Potential Marker of Tissue Quality Using Gene Expression Analysis of Human Colorectal Tissue.

Lange N, Unger FT, Schöppler M, Pursche K, Juhl H, David KA - PLoS ONE (2015)

Bottom Line: Tissue quality can be measured by changes in levels of gene expression and can be influenced by many factors including pre-analytical conditions, ischemic effects and the surgical collection procedure itself.Both microarray analysis and qPCR revealed regulator of G-protein signaling 1 (RGS1) as a potential marker of CRC tissue quality and eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) as a potential reference gene of post-operative tissue quality.Larger studies with additional time points and endpoints will be needed to confirm these results.

View Article: PubMed Central - PubMed

Affiliation: Indivumed GmbH, Hamburg, Germany.

ABSTRACT
Correlative studies have identified numerous biomarkers that are individualizing therapy across many medical specialties, including oncology. Accurate interpretation of these studies requires the collection of tissue samples of sufficient quality. Tissue quality can be measured by changes in levels of gene expression and can be influenced by many factors including pre-analytical conditions, ischemic effects and the surgical collection procedure itself. However, as yet there are no reliable biomarkers of tissue quality at researchers' disposal. The aim of the current study was to identify genes with expression patterns that fluctuated reproducibly in response to typical post-surgical stress (ischemia) in order to identify a specific marker of tissue quality. All tissue samples were obtained from patients with primary colorectal carcinoma (CRC) (N = 40) either via colonoscopy prior to surgery, or by surgical resection. Surgically resected tissue samples were divided into three groups and subjected to cold ischemia for 10, 20 or 45 minutes. Normal colorectal tissue and CRC tissue was analyzed using microarray and quantitative real-time PCR (qPCR). Comparing changes in gene expression between pre- and post-surgical tissue using microarray analysis identified a list of potential tissue quality biomarkers and this list was validated using qPCR. Results revealed that post-operative ischemia significantly alters gene expression in normal and CRC tissue samples. Both microarray analysis and qPCR revealed regulator of G-protein signaling 1 (RGS1) as a potential marker of CRC tissue quality and eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) as a potential reference gene of post-operative tissue quality. Larger studies with additional time points and endpoints will be needed to confirm these results.

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qPCR gene expression analysis of six target genes in response to ischemia.Time-dependent gene expression of CYR61(A), RGS1(B), DUSP1(C), DUOX2(D), SLC6A14(E) and EEF1A1(F) in normal (N) compared with tumor (T) tissue from 20 patients shown in Box-Whisker Plots. Boxes represent first and third quartile, whiskers represent minima and maxima, solid lines within boxes indicate medians. Results are displayed as fold changes normalized to sample NC4/N0. Kruskal-Wallis test and Dunn’s multiple comparison test were used for statistical analysis. Significant changes in gene expression between N0 and N10/N20 or N45 as well as between T0 and T10/T20 or T45 are indicated N = normal tissue; T = tumor tissue; 0 = before surgery; 10, 20, 45 = 10, 20, 45 minutes after resection; * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.
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pone.0133987.g002: qPCR gene expression analysis of six target genes in response to ischemia.Time-dependent gene expression of CYR61(A), RGS1(B), DUSP1(C), DUOX2(D), SLC6A14(E) and EEF1A1(F) in normal (N) compared with tumor (T) tissue from 20 patients shown in Box-Whisker Plots. Boxes represent first and third quartile, whiskers represent minima and maxima, solid lines within boxes indicate medians. Results are displayed as fold changes normalized to sample NC4/N0. Kruskal-Wallis test and Dunn’s multiple comparison test were used for statistical analysis. Significant changes in gene expression between N0 and N10/N20 or N45 as well as between T0 and T10/T20 or T45 are indicated N = normal tissue; T = tumor tissue; 0 = before surgery; 10, 20, 45 = 10, 20, 45 minutes after resection; * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.

Mentions: To validate the microarray results a qPCR assay was developed and the mRNA expression of six chosen genes (CYR61, RGS1, DUOX2, SLC6A14, EEF1A1 and DUSP1) that fluctuated reproducibly in normal and tumor colorectal tissue groups in response to ischemia were analyzed. As it is well known that degraded RNA negatively influences the outcome of qPCR analyses, RNA quality was determined. Individual as well as mean RIN values from all patient samples are shown in S1 Fig. Mean RIN values were high (RIN ≥7.9) and 88.75% of individual samples (142/160) showed RIN values ≥7.5 threshold. Furthermore, 11.25% samples (18/160) showed RIN values of between 5 and 7.5. RNA was therefore of sufficient quality for reliable qPCR quantification [7]. The stably expressed reference genes, GAPDH and UBC[8], were used for normalization of the qPCR results. Fig 2shows the changes in expression of the six target genes. Consistent with the microarray results, qPCR analysis revealed a statistically significant up-regulation of CYR61, DUSP1 and RGS1 as well as a statistically significant down-regulation of SLC6A14 and DUOX2 in normal ischemic tissue samples compared with the pre-surgical sample (Fig 2). When gene expression was compared between ischemic time points (N10/N20; N10/N45; N20/N45) no differences were observed. Furthermore, expression of EEF1A1 was unchanged when comparing expression in normal and tumor tissue samples after resection (Fig 2F). In contrast, the results obtained from tumor tissue samples were more heterogeneous. Although expression of CYR61, DUSP1 and RGS1 was detected, only RGS1 showed significant up-regulation in tumor tissue across all time points of ischemia (Fig 2B). Furthermore, statistical analysis revealed no significant decrease in the expression of SLC6A14 and DUOX2 in response to ischemia.


Identification and Validation of a Potential Marker of Tissue Quality Using Gene Expression Analysis of Human Colorectal Tissue.

Lange N, Unger FT, Schöppler M, Pursche K, Juhl H, David KA - PLoS ONE (2015)

qPCR gene expression analysis of six target genes in response to ischemia.Time-dependent gene expression of CYR61(A), RGS1(B), DUSP1(C), DUOX2(D), SLC6A14(E) and EEF1A1(F) in normal (N) compared with tumor (T) tissue from 20 patients shown in Box-Whisker Plots. Boxes represent first and third quartile, whiskers represent minima and maxima, solid lines within boxes indicate medians. Results are displayed as fold changes normalized to sample NC4/N0. Kruskal-Wallis test and Dunn’s multiple comparison test were used for statistical analysis. Significant changes in gene expression between N0 and N10/N20 or N45 as well as between T0 and T10/T20 or T45 are indicated N = normal tissue; T = tumor tissue; 0 = before surgery; 10, 20, 45 = 10, 20, 45 minutes after resection; * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.
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pone.0133987.g002: qPCR gene expression analysis of six target genes in response to ischemia.Time-dependent gene expression of CYR61(A), RGS1(B), DUSP1(C), DUOX2(D), SLC6A14(E) and EEF1A1(F) in normal (N) compared with tumor (T) tissue from 20 patients shown in Box-Whisker Plots. Boxes represent first and third quartile, whiskers represent minima and maxima, solid lines within boxes indicate medians. Results are displayed as fold changes normalized to sample NC4/N0. Kruskal-Wallis test and Dunn’s multiple comparison test were used for statistical analysis. Significant changes in gene expression between N0 and N10/N20 or N45 as well as between T0 and T10/T20 or T45 are indicated N = normal tissue; T = tumor tissue; 0 = before surgery; 10, 20, 45 = 10, 20, 45 minutes after resection; * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.
Mentions: To validate the microarray results a qPCR assay was developed and the mRNA expression of six chosen genes (CYR61, RGS1, DUOX2, SLC6A14, EEF1A1 and DUSP1) that fluctuated reproducibly in normal and tumor colorectal tissue groups in response to ischemia were analyzed. As it is well known that degraded RNA negatively influences the outcome of qPCR analyses, RNA quality was determined. Individual as well as mean RIN values from all patient samples are shown in S1 Fig. Mean RIN values were high (RIN ≥7.9) and 88.75% of individual samples (142/160) showed RIN values ≥7.5 threshold. Furthermore, 11.25% samples (18/160) showed RIN values of between 5 and 7.5. RNA was therefore of sufficient quality for reliable qPCR quantification [7]. The stably expressed reference genes, GAPDH and UBC[8], were used for normalization of the qPCR results. Fig 2shows the changes in expression of the six target genes. Consistent with the microarray results, qPCR analysis revealed a statistically significant up-regulation of CYR61, DUSP1 and RGS1 as well as a statistically significant down-regulation of SLC6A14 and DUOX2 in normal ischemic tissue samples compared with the pre-surgical sample (Fig 2). When gene expression was compared between ischemic time points (N10/N20; N10/N45; N20/N45) no differences were observed. Furthermore, expression of EEF1A1 was unchanged when comparing expression in normal and tumor tissue samples after resection (Fig 2F). In contrast, the results obtained from tumor tissue samples were more heterogeneous. Although expression of CYR61, DUSP1 and RGS1 was detected, only RGS1 showed significant up-regulation in tumor tissue across all time points of ischemia (Fig 2B). Furthermore, statistical analysis revealed no significant decrease in the expression of SLC6A14 and DUOX2 in response to ischemia.

Bottom Line: Tissue quality can be measured by changes in levels of gene expression and can be influenced by many factors including pre-analytical conditions, ischemic effects and the surgical collection procedure itself.Both microarray analysis and qPCR revealed regulator of G-protein signaling 1 (RGS1) as a potential marker of CRC tissue quality and eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) as a potential reference gene of post-operative tissue quality.Larger studies with additional time points and endpoints will be needed to confirm these results.

View Article: PubMed Central - PubMed

Affiliation: Indivumed GmbH, Hamburg, Germany.

ABSTRACT
Correlative studies have identified numerous biomarkers that are individualizing therapy across many medical specialties, including oncology. Accurate interpretation of these studies requires the collection of tissue samples of sufficient quality. Tissue quality can be measured by changes in levels of gene expression and can be influenced by many factors including pre-analytical conditions, ischemic effects and the surgical collection procedure itself. However, as yet there are no reliable biomarkers of tissue quality at researchers' disposal. The aim of the current study was to identify genes with expression patterns that fluctuated reproducibly in response to typical post-surgical stress (ischemia) in order to identify a specific marker of tissue quality. All tissue samples were obtained from patients with primary colorectal carcinoma (CRC) (N = 40) either via colonoscopy prior to surgery, or by surgical resection. Surgically resected tissue samples were divided into three groups and subjected to cold ischemia for 10, 20 or 45 minutes. Normal colorectal tissue and CRC tissue was analyzed using microarray and quantitative real-time PCR (qPCR). Comparing changes in gene expression between pre- and post-surgical tissue using microarray analysis identified a list of potential tissue quality biomarkers and this list was validated using qPCR. Results revealed that post-operative ischemia significantly alters gene expression in normal and CRC tissue samples. Both microarray analysis and qPCR revealed regulator of G-protein signaling 1 (RGS1) as a potential marker of CRC tissue quality and eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) as a potential reference gene of post-operative tissue quality. Larger studies with additional time points and endpoints will be needed to confirm these results.

No MeSH data available.


Related in: MedlinePlus