Project title: A Groundbreaking Research Project aiming to Improve Cancer Diagnosis, Treatment, and Survival in Taiwan by National Cheng Kung University Hospital Program title: Colon and gastric cancer screening and longitudinal surveillance in high-risk groups

Using Whole Genome Translatome Analysis to Identify the Actionable Biomarker in Different types of Colon Polyps

Joseph T. Tseng 1, Jui-Wen Kang2, Bor-Shyang Sheu2, Jenq-Chang Lee3

曾大千 ，康瑞文，許博翔，李政昌

1Institute of Bioinformatics and Biosignal Transduction, NCKU, Tainan, 2Department of Internal Medicine, 3Department of Surgery, NCKU Hospital, Tainan

Background: Colorectal cancer is the most common cancer in Taiwan. Through FIT screening, its incidence and mortality decline due to removal of colon polyps. Postpolypectomy surveillance is important to prevent interval cancer. Clinically, hyperplastic polyps(HP) and serrated adenoma(SSA), which have different surveillance interval, are difficult to distinguish from endoscopic image and pathology examination. Ribosome profiling or ribo-seq is a new technique to analyze what kinds of the mRNAs engaged in the translation process, also named as translatome analysis. It can provide the genome-wide information on protein synthesis in vivo, and fill the technological gap existing between our abilities to quantify the transcriptome and the proteome to get the gene expression profile, which more closely related to cell physiology than RNA-seq data.

Aims: Using the ribosome profiling technique to identify the key biomarker to distinguish the hyperplastic polyps and serrated adenoma.

Methods: Ribo-seq was performed on 5 SSAs, 5 HPs, 5 tubular adenomas(TA), and 5 villous tubular adenomas(VTA). The statistically method to identify the differential gene expression among the different group of polyps were used to define the unique gene signature of SSAs.

Results: Based on the PCA analysis, the four types of polyps showed distinctly different gene expression profiles. However, the expression patterns among the 5 patients with the same histology type of polyps are similar (r=0.9). The gene expression profile of SSA displays significantly different from TA or VTA( r value around 0.5), but close related to HP (r=0.74). Compared with the expression pattern of SSA and HP, several biomarker genes (IGLL5, IGJ, TFF1 and REG4) were found to distinguish SSA from HP.

Conclusions:

The consistent result of different patient samples with same histology type of polyps and the distinct gene expression pattern among different types of polyps indicate the polys Ribo-seq technology could be a promising tool to identify the key biomarker for clinical diagnosis and decision making. Further validation study is warranted.