Identification of genes associated with the onset of colorectal cancer by transcriptomic analyses of the adenoma-carcinoma sequence. Identification of genes associated with the onset of colorectal cancer by transcriptomic analyses of the adenoma-carcinoma sequence

In the carcinogenesis of colorectal cancer (CRC), the stepwise progression from adenoma to carcinoma is marked by a series of specific genetic alterations of known oncogenes and tumor suppressor genes. However, many patient-matched features of the transcriptome involved in the adenoma-carcinoma sequence remain unidentified. The aim of this study was to identify genes associated with the process of CRC formation by analyzing the characteristics of the transcriptome during tumor formation. Six dynamic expression patterns specific to tumor formation were characterized for the first time. Dysregulation of metabolic pathways, suppression of the immune system, and activation of canonical pathways related to cancer were associated with the adenoma-carcinoma sequence. Among a cluster of genes positively correlated with tumor formation, TPD52L1 was identified as a gene that induced oncologic behaviors and a biomarker for poor prognosis. Overall design: Triplicate tissue samples (primary CRC, adjacent normal tissue, and adenoma; n = 15) were collected from five patients with CRC prior to any therapy at Zhongshan Hospital, and stored in RNAlater™ Stabilization Solution.Total RNA samples were extracted with the TRIzol™ Reagent (Thermo Fisher Scientific). Ribosomal-RNA-depleted and strand-specific libraries were constructed with the Ribo-Zero Gold Kit (Illumina, Inc., San Diego, CA, USA) and TruSeq Stranded Total RNA Sample Prep Kit (Illumina, Inc.), and sequenced using the HiSeq 2500 Sequencing System (Illumina, Inc.) by Genergy BioTech Co., Ltd. (Delhi, India). Cleaned RNAseq data were aligned to the human GRCh38 reference assembly using the HISAT2 alignment program [50]. Only uniquely mapped reads were retained for reads counting with HTseq [51]. DEGs were identified with the R package DESeq2 [52]. To identify the DEGs between two tissue specimens in different transitional stages, the Wald test in DESeq2 was applied with a false discovery rate (FDR) of 1. To identify DEGs in all three tissue types, the likelihood-ratio test (LRT) was used with an FDR threshold of <0.05.