Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression analysis of human adenomas.

ABSTRACT: Gene expression profiling was carried out in 7 matched colon adenoma samples and normal mucosa to characterize the molecular mechanisms relevant to the etiology ofadenoma and human colorectal carcinoma development. Whole-transcriptome RNA sequencing of the 7 matched colon adenoma samples and normal mucosas.

ORGANISM(S): Homo sapiens

SUBMITTER: Jian Chen

PROVIDER: E-GEOD-72820 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Traditional serrated adenoma (TSA) remains the least understood of all the colorectal adenomas although these lesions have been associated with a significant cancer risk- twice that of the conventional adenoma (CAD) and of the sessile serrated adenoma (SSA/P). This study was performed to investigate the proteomic profiles of the different colorectal adenomas to better assess the pathogenesis of TSA. We performed a global quantitative expression profile of 44 colorectal adenomas (12 TSA, 15 CAD, 17 SSA/Ps) and 17 normal colonic mucosa, conserved as formalin-fixed paraffin-embedded samples, by the label-free quantification (LFQ) method. Unsupervised consensus hierarchical clustering applied to the whole proteomic profile of the 44 colorectal adenomas identified four subtypes. The C1 and C2 were well-individualized clusters composed of most of the CAD (14/15) and most of the SSA (13/17) respectively. This is consistent with the fact that CAD and SSA/Ps are homogeneous but distinct colorectal adenoma entities. In contrast, TSA were subdivided into C3 and C4 clusters that also contained CAD and SSA/Ps, consistent with the more heterogeneous entity of TSA at the morphological and molecular levels. The comparison of the proteome expression profile between the adenoma subtypes and normal colonic mucosa further confirmed the heterogeneous nature of TSA that merged either on CAD or SSA, while CAD and TSA formed homogeneous and distinct entities. Furthermore, we identified LEFTY1 a new potential marker for TSA that may be relevant for the TSA pathogenesis. LEFTY1 is an inhibitor of the Nodal/TGFb pathway that we found to be one of the most overexpressed proteins specifically in the TSA and confirmed by immunohistochemistry. Taken together, our study confirms that CAD and SSA form homogenous but distinct colorectal adenoma entities while TSA are an heterogeneous entity and may arise from either SSA or from normal mucosa that will evolve along the conventional adenoma pathway.

Project description:Transcriptional profiling of pre-malignant and malignant colorectal cancer lesions provides a means for temporally monitoring key molecular events underlying neoplastic progression. Unfortunately, the most widely used central dataset for colorectal cancer samples from The Cancer Genome Atlas (TCGA) does not contain adenoma samples, putting a greater reliance of in silico analyses and pre-clinical modelling on a handful of independent microarray experiments. Due to the differences in sample acquisition, preparation, downstream analysis and other parameters, results are often incongruent, hindering consensus building. Here, we developed a microarray meta-dataset consisting of 231 normal, 132 adenoma, and 342 colon cancer tissue samples (705 samples total) sourced from 12 independent microarray studies all using the Affymetrix HG U133 Plus 2.0 (GPL570) chip platform including GSE4183, GSE8671,GSE9348, GSE15960, GSE20916, GSE21510, GSE22598, GSE23194, GSE23878, GSE32323, GSE33113, and GSE37364. Individual datasets were pre-processed and normalized by frozen robust multiarray averaging (fRMA) before merging by matching probe sets. Batch effects were subsequently identified by Principal Component Analysis (PCA) and removed using ComBat. In addition, low variant probes were filtered from the meta-dataset before downstream analysis. Finally, biological signatures corresponding to cancer and adenoma samples were both quantitatively and functionally validated. Quantitative validation was performed by correlation analysis of LogFC values with the TCGA-COAD or other external GEO microarray datasets, respectively. Functional validation was carried out through predictive analyses using Ingenuity Pathway Analysis (IPA) and Gene Set Enrichment Analysis (GSEA). Overall, our meta-dataset provides a powerful tool for studying transcriptome-wide changes which occur during early dysplasia and malignant transformation of adenomas as well as colorectal cancer in general.

Dataset Information

Gene expression analysis of human adenomas.

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