Identification of genomic alterations of perineural invasion in patients with stage II colorectal cancer

Abstract

Background The molecular mechanism of perineural invasion (PNI) in stage Ⅱ colorectal cancer (CRC) remains not to be defined clearly. This study aims to identify the genomic aberrations related to PNI in stage Ⅱ CRC.Methods Using array-based comparative genomic hybridization (array-CGH), primary tumor tissues and paracancerous normal tissues of stage Ⅱ CRC from 5 patients with PNI and 5 patients without PNI were analyzed. We also identified genomic aberrations by using Genomic Workbench and MD-SeeGH. Furthermore, Gene ontology (GO) and Pathway analysis for these array-CGH data was performed to determine the most likely biological effects of these genes.Results The most frequent gains in stage Ⅱ CRC were at 7q11.21-q11.22, 8p11.21, 8p12-p11.23, 8q11.1-q11.22, 13q12.13-q12.2, and 20q11.21-q11.23 and the most frequent losses were at 17p13.1-p12, 8p23.2, and 118q11.2-q23. Four high-level amplifications at 8p11.23-p11.22, 18q21.1, 19q11-q12, and 20q11.21-q13.32 and homozygous deletions at 20p12.1 were discovered in Stage II CRC. Gains at 7q11.21-q22.1, 16p11.2, 17q23.3-q25.3, 19p13.3-p12, and 20p13-p11.1, and losses at 11q11-q12.1, 11p15.5-p15.1, 18p11.21, and 18q21.1-q23 were more commonly found in patients with PNI by frequency plot comparison together with detailed genomic analysis. It is also observed that gains at 8q11.1-q24.3, 9q13-q34.3, and 13q12.3-q13.1, and losses at 3q26.1, 8p23.3-p12, 17p13.3-p11.2, and 21q22.12 occurred more frequently in patients without PNI. GO and Pathway analysis revealed that the genes in two groups were enriched in specific pathways.Conclusions These involved genomic changes in the PNI of stage Ⅱ CRC will contribute to reveal the mechanisms underlying PNI and provide candidate biomarkers.

Tumor Deposits and Perineural Invasion had Comparable Impacts on the Survival of Patients With Non-metastatic Colorectal Adenocarcinoma: A Population-Based Propensity Score Matching and Competing Risk Analysis

“… 27 Compared with PNI-positive patients, the expression of FLT1, FBXW7, FGFR1, SLC20A2, and SERPINI1 was significantly up-regulated in PNI-negative group. 28 However, detailed molecular mechanism of TD and PNI still remains unclear.…”

A clinical‐radiomics model incorporating T2‐weighted and diffusion‐weighted magnetic resonance images predicts the existence of lymphovascular invasion / perineural invasion in patients with colorectal cancer

“…Moreover, MRI‐based radiomics has only been used to investigate LVI in breast and endometrial cancer 33,34 . In previous studies, several researchers have analyzed subjective imaging characteristics determined by radiologists and combined clinical–pathological or gene expression factors to predict LVI/PNI in patients with CRC before surgery 7,35 . However, there had been no reports on lymphovascular invasion of rectal cancer using radiomics until a recent study by Zhang et al 19 .…”

“…33,34 In previous studies, several researchers have analyzed subjective imaging characteristics determined by radiologists and combined clinical-pathological or gene expression factors to predict LVI/PNI in patients with CRC before surgery. 7,35 However, there had been no reports on lymphovascular invasion of rectal cancer using radiomics until a recent study by Zhang et al 19 that found a multimodal (MR/CT) radiomics model to have excellent sensitivity (93.8%) but limited specificity (72.7%) for detecting lymphovascular invasion in rectal cancer. Radiomics mainly improves the prediction performance of medical images by improving analysis and using computer algorithms to extract thousands of quantitative features.…”