Exploration of the typical features of tubulovillous adenoma using in-depth quantitative proteomics analysis

ABSTRACT

This present study aimed to explore the typical protein features of tubulovillous adenoma (TVA) using proteomic and bioinformatic analyses. Tandem mass tag (TMT)-based quantitative proteomic analyses were conducted on normal mucosa, tubular adenoma, TVA and adenocarcinoma tissues. We identified 5,665 proteins categorized into seven clusters based on Pearson’s correlation analysis. The bioinfomatic analysis showed mitochondrial and metabolism-related events were typical characteristics of TVA and mitochondrial-, ribosome- and matrisome-related biological processes may contribute to carcinogenesis. PLOD3 was identified as a key protein associated with the malignant potential of TVA and promoted the viability of adenoma organoids. The Cancer Genome Atlas (TCGA) analysis revealed PLOD3 as a risk factor for disease-free and overall survival. Furthermore, the PLOD3 expression correlated negatively with the abundance of B cells, CD8 + T cells, CD4 + T cells, neutrophils, macrophages and myeloid dendritic cells. In conclusion, enhanced metabolic and mitochondrial reprogramming are typical features of TVA, and PLOD3 might be related to the “immune desert” phenotype and contribute to TVA tumorigenesis and colorectal cancer development.

KEYWORDS:

• Tubulovillous adenoma
• tumorigenesis
• PLOD3
• quantitative proteomics
• metabolic reprogramming
• tumor microenvironment

Authors’ Contributions

Y.X. and L.X. conceived the study; Y.Z. performed data preprocessing; Y.Z. performed primary analysis and wrote the article. C.L., M.P. and J.L. performed and supervised the experiments. All authors read and approved the final manuscript.

Acknowledgements

The authors thank Wen-yun Hou, Yan-pan Gao and Dan Luo for their guidance in organizing the manuscript and assisting in the experiments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data Availability

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the iProX partner repository with the dataset identifier: PXD023899.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This study was supported by the National Natural Science Foundation of China (No. 81702933) and CAMS Innovation Fund for Medical Sciences(No. 2017-I2M-1-001);National Natural Science Foundation of China;CAMS Innovation Fund for Medical Sciences.