Lee LX, Li SC. Hunting down the dominating subclone of cancer stem cells as a potential new therapeutic target in multiple myeloma: An artificial intelligence perspective. World J Stem Cells 2020; 12(8): 706-720 [PMID: 32952853 DOI: 10.4252/wjsc.v12.i8.706]
Corresponding Author of This Article
Shengwen Calvin Li, PhD, Professor, Neuro-oncology and Stem Cell Research Laboratory, CHOC Children's Research Institute, Children's Hospital of Orange County, 1201 W La Veta Ave., Orange, CA 92868, United States. shengwel@uci.edu
Research Domain of This Article
Oncology
Article-Type of This Article
Therapeutic and Diagnostic Guidelines
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 Stem Cells. Aug 26, 2020; 12(8): 706-720 Published online Aug 26, 2020. doi: 10.4252/wjsc.v12.i8.706
Hunting down the dominating subclone of cancer stem cells as a potential new therapeutic target in multiple myeloma: An artificial intelligence perspective
Lisa X Lee, Shengwen Calvin Li
Lisa X Lee, Division of Hematology/Oncology, Department of Medicine, Chao Family Comprehensive Cancer Center, UCI Health, Orange, CA 92868, United States
Shengwen Calvin Li, Neuro-oncology and Stem Cell Research Laboratory, CHOC Children's Research Institute, Children's Hospital of Orange County, Orange, CA 92868, United States
Shengwen Calvin Li, Department of Neurology, University of California-Irvine School of Medicine, Orange, CA 92868, United States
Author contributions: Lee LX and Li SC conceived and wrote the manuscript; both revised the manuscript; and all authors approved the final version submitted.
Supported bythe CHOC-UCI Joint Research Award (in part).
Conflict-of-interest statement: The authors declare no conflict of interest.
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: Shengwen Calvin Li, PhD, Professor, Neuro-oncology and Stem Cell Research Laboratory, CHOC Children's Research Institute, Children's Hospital of Orange County, 1201 W La Veta Ave., Orange, CA 92868, United States. shengwel@uci.edu
Received: May 18, 2020 Peer-review started: May 18, 2020 First decision: June 5, 2020 Revised: July 8, 2020 Accepted: August 14, 2020 Article in press: August 14, 2020 Published online: August 26, 2020 Processing time: 99 Days and 23.2 Hours
Core Tip
Core tip: Current methods for determining prognosis in multiple myeloma are limited. The prototype device called Multi-Phase Laser-cavitation Single Cell Analyzer can perform reverse transcriptase polymerase chain reaction (RT-PCR) on single cells in a one-step microfluidics chip platform. The ability of the microfluidics chip platform to enrich plasma cell content by depleting CD45+ white blood cells has been demonstrated. Further studies will need to combine single-cell selection with RT-PCR to further enhance the diagnostic capabilities of this technology. This platform has the potential to be used for clinical risk stratification in multiple myeloma as well as minimal residual disease monitoring and selection of therapies to modulate the development of resistance.
