Genetic Aberration Analysis in Thai Colorectal Adenoma and Early-Stage Adenocarcinoma Patients by Whole-Exome Sequencing

Abstract

Colorectal adenomas are precursor lesions of colorectal adenocarcinoma. The transition from adenoma to carcinoma in patients with colorectal cancer (CRC) has been associated with an accumulation of genetic aberrations. However, criteria that can screen adenoma progression to adenocarcinoma are still lacking. This present study is the first attempt to identify genetic aberrations, such as the somatic mutations, copy number variations (CNVs), and high-frequency mutated genes, found in Thai patients. In this study, we identified the genomic abnormality of two sample groups. In the first group, five cases matched normal-colorectal adenoma-colorectal adenocarcinoma. In the second group, six cases matched normal-colorectal adenomas. For both groups, whole-exome sequencing was performed. We compared the genetic aberration of the two sample groups. In both normal tissues compared with colorectal adenoma and colorectal adenocarcinoma analyses, somatic mutations were observed in the tumor suppressor gene APC (Adenomatous polyposis coli) in eight out of ten patients. In the group of normal tissue comparison with colorectal adenoma tissue, somatic mutations were also detected in Catenin Beta 1 (CTNNB1), Family With Sequence Similarity 123B (FAM123B), F-Box And WD Repeat Domain Containing 7 (FBXW7), Sex-Determining Region Y-Box 9 (SOX9), Low-Density Lipoprotein Receptor-Related Protein 5 (LRP5), Frizzled Class Receptor 10 (FZD10), and AT-Rich Interaction Domain 1A (ARID1A) genes, which are involved in the Wingless-related integration site (Wnt) signaling pathway. In the normal tissue comparison with colorectal adenocarcinoma tissue, Kirsten retrovirus-associated DNA sequences (KRAS), Tumor Protein 53 (TP53), and Ataxia-Telangiectasia Mutated (ATM) genes are found in the receptor tyrosine kinase-RAS (RTK–RAS) signaling pathway and p53 signaling pathway, respectively. These results suggest that APC and TP53 may act as a potential screening marker for colorectal adenoma and early-stage CRC. This preliminary study may help identify patients with adenoma and early-stage CRC and may aid in establishing prevention and surveillance strategies to reduce the incidence of CRC.

Discovering Innate Driver Variants for Risk Assessment of Early Colorectal Cancer Metastasis

“…The datasets were chosen by multiple criteria: (i) the CRC cohort consisted of both metastasis and non-metastasis cases; (ii) the mutation profiles were determined by WES; and (iii) the clinical information such as metastasis status was acquirable. Results show that three datasets met all criteria and were included in the OR analysis: PRJNA494574 (10 samples) ( 57 ), PRJNA514428 (24 samples) ( 58 ), and PRJNA246044 (19 samples) ( 41 ). Of these 53 CRC samples, 28 had either lymphatic metastasis or distal metastasis, and the remaining 25 did not observe metastasis by the time of experiment.…”

Genomic, Microbial and Immunological Microenvironment of Colorectal Polyps

“…Whole-exome sequencing and targeted sequencing of 149 polyp samples showed that serrated adenomas and conventional adenomas had similar frequencies of somatic mutations, but with distinctive driver mutations consistent with their differing genetic origins [ 23 ]. Combined, exome-wide studies of conventional adenomas reveal that APC, KRAS, PIK3CA, TP53 and SMAD4 genes affecting Wnt, RAS, PI3K, p53 and TGF-beta signaling pathways are amongst those most commonly altered, often with significantly increasing mutation prevalence in development from non-advanced conventional adenomas to advanced conventional adenomas to CRC [ 23 , 24 , 25 , 26 , 27 , 28 ].…”

Exploration of the Key Proteins in the Normal-Adenoma-Carcinoma Sequence of Colorectal Cancer Evolution Using In-Depth Quantitative Proteomics

“…Based on the major principle of carcinogenesis, the majority of studies on colorectal cancer have employed a genomic analysis approach to explore the N-A-C sequence [6][7][8][9][10][11]. Some researchers attempted to identify the driver events of this sequence at the level of transcriptomics by investigating original or public RNA sequencing data [12,13].…”