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. 2016 Jun;9(6):456-65.
doi: 10.1158/1940-6207.CAPR-15-0363. Epub 2016 Mar 29.

Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype

Affiliations

Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype

Priyanka Kanth et al. Cancer Prev Res (Phila). 2016 Jun.

Abstract

Sessile serrated colon adenoma/polyps (SSA/P) are found during routine screening colonoscopy and may account for 20% to 30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. In addition, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing (RNA-Seq) was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon, and 20 control colon specimens. Differential expression and leave-one-out cross-validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1,422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n = 12) and sporadic SSA/Ps (n = 9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability. A smaller 7-gene panel showed high sensitivity and specificity in identifying BRAF-mutant, CpG island methylator phenotype high, and MLH1-silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. Cancer Prev Res; 9(6); 456-65. ©2016 AACR.

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Conflict of interest statement

Conflict of Interest: None

Figures

Figure 1
Figure 1
Differentially expressed annotated protein coding and non-coding RNAs in SSA/Ps and traditional hyperplastic polyps (HPs) identified by RNA sequencing. Panel A – Differentially expressed genes with a ≥ 2-fold change and FDR < 0.05 in SSA/Ps (n=12 for syndromic and n=9 for sporadic) compared to control right colon (n=10) and HPs (n=10) compared to control left colon (n=10). Panel B – Relative abundance of protein coding and non-coding RNAs differentially expressed in SSA/Ps. Non-coding RNAs included antisense non-coding RNAs, long intergenic non-coding RNAs (lincRNAs), pseudogenes and other miscellaneous RNAs including immunoglobulin and intronic RNAs.
Figure 2
Figure 2
Differentially expressed genes in syndromic and sporadic SSA/Ps and HPs by RNA sequencing. Panel A – Genes with ≥ 4-fold change and FDR < 0.05 in syndromic SSA/Ps (n=12), sporadic SSA/Ps (n=9) and HPs (n=10). Syndromic and sporadic SSA/Ps were compared to control right colon and HPs were compared to control left colon. Panel B – Relative expression of 27 protein-coding genes in syndromic SSA/Ps, sporadic SSA/Ps, HPs and control left and right colon. Log2 ratios comparing each individual sample to the mean of all samples were used for hierarchical clustering. Two right-sided HPs are labeled in red and five left-sided SSA/Ps are labeled in green. Panel C – Mean fold change expression of the same 27 protein coding genes described in Panel B in normal colon, adenomas, HPs and sporadic and syndromic SSA/Ps.
Figure 2
Figure 2
Differentially expressed genes in syndromic and sporadic SSA/Ps and HPs by RNA sequencing. Panel A – Genes with ≥ 4-fold change and FDR < 0.05 in syndromic SSA/Ps (n=12), sporadic SSA/Ps (n=9) and HPs (n=10). Syndromic and sporadic SSA/Ps were compared to control right colon and HPs were compared to control left colon. Panel B – Relative expression of 27 protein-coding genes in syndromic SSA/Ps, sporadic SSA/Ps, HPs and control left and right colon. Log2 ratios comparing each individual sample to the mean of all samples were used for hierarchical clustering. Two right-sided HPs are labeled in red and five left-sided SSA/Ps are labeled in green. Panel C – Mean fold change expression of the same 27 protein coding genes described in Panel B in normal colon, adenomas, HPs and sporadic and syndromic SSA/Ps.
Figure 3
Figure 3
Evaluation of a 28-gene signature to distinguish SSA/Ps from HPs. The 28-gene panel was developed using a leave-one-out cross validation approach on 31 independent serrated polyps (21 SSA/Ps and 10 HPs) samples. Panel A – Principal component analysis of the 28 gene log2 ratios for each individual serrated polyp compared to the mean of all serrated polyps. Principal component 1 (PC1) accounted for 28% of the variation in the data and separated most SSA/Ps (red) from HPs (blue). Twenty-eight of thirty-one serrated polyps (~90%) clustered correctly similar to the nominal error rate found in the cross validation results. Panel B – Relative expression (log of normalized reads (RPKM) of the same 28 genes described in Panel A in SSA/Ps and HPs. Six genes (circles) were overexpressed in SSA/Ps compared to HPs (range 2.8 to 3.7 fold) and 22 genes (squares) were underexpressed in SSA/Ps compared to HPs (range −2.2 to −6.7).
Figure 4
Figure 4
Evaluation of a 51 SSA/P gene signature in colon cancer RNA sequencing datasets from The Cancer Genome Atlas (TCGA). Panel A – Log2 ratios comparing individual colon cancers (n=72) and SSA/Ps (n=21) to the mean of 14 uninvolved and 10 control colon samples (n=24) were used for hierarchical clustering. “Tissue” color bar shows colon adenocarcinomas (orange) and SSA/Ps (yellow). “MSI status” color bar shows microsatellite stable (MSS) cancers (dark blue), MSI-H cancers (red) and MSI-L cancers (light orange). SSA/Ps and colon cancers not evaluated for MSI (light blue). Panel B – Percentage of TCGA colon cancers showing overexpression of FSCN1, ZIC2, ZIC5, CRYBA2, MUC6, TRNP1 and/or SEMG1 described in Table 1. 195 colon cancers with RNA expression and MLH1 methylation data in the TCGA database were evaluated using the cBioPortal for Cancer Genomics.

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