| ISSN |
2218-4333 (online) |
| 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/ |
| Copyright |
©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Oncology |
| Manuscript Type |
Retrospective Cohort Study |
| Article Title |
iCEMIGE: Integration of CEll-morphometrics, MIcrobiome, and GEne biomarker signatures for risk stratification in breast cancers
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Xuanyu Mao, Jesus Perez-Losada, Mar Abad, Marta Rodríguez-González, Cesar A. Rodríguez, Jian-Hua Mao and Hang Chang |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| the Department of Defense (DoD) BCRP |
BC190820 |
| the National Cancer Institute (NCI) at the National Institutes of Health (NIH) |
R01CA184476 |
| MCIN/AEI/10.13039/501100011039 |
PID2020-118527RB-I00 |
| MCIN/AEI/10.13039/501100011039 |
PDC2021-121735-I00 |
| the “European Union Next Generation EU/PRTR.” the Regional Government of Castile and León |
CSI144P20 |
|
| Corresponding Author |
Jian-Hua Mao, BSc, MSc, PhD, Adjunct Professor, Senior Scientist, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, United States. jhmao@lbl.gov |
| Key Words |
Prognosis; Multimodal data integration; Cellular morphometrics signature; Microbiome signature; Gene signature; Breast cancer |
| 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. |
| Publish Date |
2022-07-22 09:38 |
| Citation |
Mao XY, Perez-Losada J, Abad M, Rodríguez-González M, Rodríguez CA, Mao JH, Chang H. iCEMIGE: Integration of CEll-morphometrics, MIcrobiome, and GEne biomarker signatures for risk stratification in breast cancers. World J Clin Oncol 2022; 13(7): 616-629 |
| URL |
https://www.wjgnet.com/2218-4333/full/v13/i7/616.htm |
| DOI |
https://dx.doi.org/10.5306/wjco.v13.i7.616 |
