Li LS, Guo XY, Sun K. Recent advances in blood-based and artificial intelligence-enhanced approaches for gastrointestinal cancer diagnosis. World J Gastroenterol 2021; 27(34): 5666-5681 [PMID: 34629793 DOI: 10.3748/wjg.v27.i34.5666]
Corresponding Author of This Article
Kun Sun, PhD, Assistant Professor, Institute of Cancer Research, Shenzhen Bay Laboratory, Rm B302, Guangming International Innovation Center, Guangming District, Shenzhen 518132, Guangdong Province, China. sunkun@szbl.ac.cn
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastroenterol. Sep 14, 2021; 27(34): 5666-5681 Published online Sep 14, 2021. doi: 10.3748/wjg.v27.i34.5666
Recent advances in blood-based and artificial intelligence-enhanced approaches for gastrointestinal cancer diagnosis
Li-Shi Li, Xiang-Yu Guo, Kun Sun
Li-Shi Li, School of Chemical Biology and Biotechnology, Shenzhen Graduate School, Peking University, Shenzhen 518055, Guangdong Province, China
Li-Shi Li, Xiang-Yu Guo, Kun Sun, Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen 518132, Guangdong Province, China
Kun Sun, BGI-Shenzhen, Shenzhen 518083, Guangdong Province, China
Author contributions: Sun K outlined the article; Li LS and Guo XY performed the literature review and wrote the paper; Sun K revised the manuscript critically for important intellectual content and approved the final version for submission.
Supported byGuangdong Basic and Applied Basic Research Foundation, No. 2019A1515110173; BGI-research, No. BGIRSZ2020007; and Shenzhen Bay Laboratory.
Conflict-of-interest statement: There is no conflict of interest associated with any of the senior author or other coauthors who contributed their efforts in this manuscript.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Kun Sun, PhD, Assistant Professor, Institute of Cancer Research, Shenzhen Bay Laboratory, Rm B302, Guangming International Innovation Center, Guangming District, Shenzhen 518132, Guangdong Province, China. sunkun@szbl.ac.cn
Received: January 27, 2021 Peer-review started: January 27, 2021 First decision: May 2, 2021 Revised: May 14, 2021 Accepted: August 3, 2021 Article in press: August 3, 2021 Published online: September 14, 2021 Processing time: 225 Days and 3 Hours
Abstract
Gastrointestinal (GI) cancers are among the most common cancer types and leading causes of cancer-related deaths worldwide. There is a tremendous clinical need for effective early diagnosis for better healthcare of GI cancer patients. In this article, we provide a short overview of the recent advances in GI cancer diagnosis. In the first part, we discuss the applications of blood-based biomarkers, such as plasma circulating cell-free DNA, circulating tumor cells, extracellular vesicles, and circulating cell-free RNA, for cancer liquid biopsies. In the second part, we review the current trends of artificial intelligence (AI) for pathology image and tissue biopsy analysis for GI cancer, as well as deep learning-based approaches for purity assessment of tissue biopsies. We further provide our opinions on the future directions in blood-based and AI-enhanced approaches for GI cancer diagnosis, and we think that these fields will have more intensive integrations with clinical needs in the near future.
Core Tip: Recent studies have discovered a variety of blood-based biomarkers with great potential in improving the diagnosis and surveillance of gastrointestinal (GI) cancers. In this article, we review the latest advances in the diagnosis of various GI cancers, focusing on emerging blood-based liquid biopsy assays and artificial intelligence-enhanced approaches. We also discuss purity assessment approaches for tissue biopsies, which is an important issue in cancer studies, especially those applicable in metastatic GI cancers.
