Retrospective Cohort Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Jul 24, 2022; 13(7): 616-629
Published online Jul 24, 2022. doi: 10.5306/wjco.v13.i7.616
iCEMIGE: Integration of CEll-morphometrics, MIcrobiome, and GEne biomarker signatures for risk stratification in breast cancers
Xuan-Yu Mao, Jesus Perez-Losada, Mar Abad, Marta Rodríguez-González, Cesar A Rodríguez, Jian-Hua Mao, Hang Chang
Xuan-Yu Mao, Jian-Hua Mao, Hang Chang, Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, 94720, United States
Jesus Perez-Losada, Instituto de Biología Molecular y Celular del Cáncer, Universidad de Salamanca, Salamanca 37007, Spain
Mar Abad, Marta Rodríguez-González, Department of Pathology, Universidad de Salamanca, Salamanca 37007, Spain
Cesar A Rodríguez, Department of Medical Oncology, Universidad de Salamanca, Salamanca 37007, Spain
Author contributions: Perez-Losada J, Chang H, and Mao JH planned the project; Chang H, Mao XY, Perez-Losada JP, and Mao JH wrote the manuscript; Mao XY, Chang H, and Mao JH designed the algorithm, performed the bioinformatics analyses, and conducted statistical tests; Abad M, Rodríguez-González M, and Rodríguez CA provided pathological and clinical interpretation; All authors have read and edited the manuscript; Chang H and Mao JH are accountable for communications with requests for reagents and resources; Mao JH and Chang H contributed equally to these senior authors.
Supported by This work was supported by the Department of Defense (DoD) BCRP, No. BC190820; the National Cancer Institute (NCI) at the National Institutes of Health (NIH), No. R01CA184476; MCIN/AEI/10.13039/501100011039, No. PID2020-118527RB-I00, and No. PDC2021-121735-I00; and the “European Union Next Generation EU/PRTR.” the Regional Government of Castile and León, No. CSI144P20. Lawrence Berkeley National Laboratory (LBNL) is a multi-program national laboratory operated by the University of California for the DOE under contract DE AC02-05CH11231.
Institutional review board statement: There was no requirement for ethical approval by Institutional Review Board since this study only involves data from public databases. The authors are responsible for the accuracy or integrity of any aspects of this study.
Informed consent statement: The data used in this study are from the public databases. Therefore, the informed consent is not applicable.
Conflict-of-interest statement: All the authors declare no conflicts of interest.
Data sharing statement: All data used in the study were downloaded from a publicly available source (GDCportal and cBioPortal).
STROBE statement: All the authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Jian-Hua Mao, BSc, MSc, PhD, Adjunct Professor, Senior Scientist, Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, United States. jhmao@lbl.gov
Received: February 9, 2022
Peer-review started: February 9, 2022
First decision: April 13, 2022
Revised: April 24, 2022
Accepted: June 3, 2022
Article in press: June 3, 2022
Published online: July 24, 2022
Processing time: 162 Days and 10.3 Hours
Core Tip

Core Tip: Cancer heterogeneity consistently results in a large variation in the prognosis of patients after a certain treatment. The discovery of biomarkers for predicting prognosis can significantly assist clinical oncologists in making treatment decisions for cancer patients. Our results revealed that iCEMIGE (integration of cell-morphometrics, microbiome, and gene biomarker signatures) significantly improves risk stratification of BC patients. The clinical utility of iCEMIGE needs to be further validated in retrospective and prospective cohort studies to determine whether the iCEMIGE score can provide sufficient predictive information to stratify patients by risk and guide treatment. If so, the iCEMIGE score could assist clinicians in decision-making about cancer treatment and enable more personalized cancer therapy.