Residential College | false |
Status | 已發表Published |
A Neural Network–Based Scoring System for Predicting Prognosis and Therapy in Breast Cancer | |
Deng, Min1; Chen, Xinyu2; Qiu, Jiayue2; Liu, Guiyou3; Huang, Chen2 | |
2024-08-21 | |
Source Publication | Current Protocols |
ISSN | 2691-1299 |
Volume | 4Issue:8Pages:e1122 |
Abstract | Breast cancer is a prevalent malignancy affecting women worldwide. Currently, there are no precise molecular biomarkers with immense potential for accurately predicting breast cancer development, which limits clinical management options. Recent evidence has highlighted the importance of metastatic and tumor-infiltrating immune cells in modulating the antitumor therapy response. However, the prognostic value of using these features in combination, and their potential for guiding individualized treatment for breast cancer, remains vague. To address this challenge, we recently developed the metastatic and immunogenomic risk score (MIRS), a comprehensive and user-friendly scoring system that leverages advanced bioinformatics methods to facilitate transcriptomics data analysis. To help users become familiar with the MIRS tool and apply it effectively in analyzing new breast cancer datasets, we describe detailed protocols that require no advanced programming skills. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Calculating a MIRS score from transcriptomics data. Basic Protocol 2: Predicting clinical outcomes from MIRS scores. Basic Protocol 3: Evaluating treatment responses and guiding therapeutic strategies in breast cancer patients. Basic Protocol 4: Guidelines for utilizing the MIRS webtool. |
Keyword | Breast Cancer r Therapeutic Strategies Tumor Microenvironment |
DOI | 10.1002/cpz1.1122 |
URL | View the original |
Indexed By | ESCI |
Language | 英語English |
WOS Research Area | Biochemistry & Molecular Biology |
WOS Subject | Biochemical Research Methods |
WOS ID | WOS:001295161300001 |
Publisher | WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA |
Scopus ID | 2-s2.0-85201602062 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | Faculty of Health Sciences Cancer Centre Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau |
Corresponding Author | Huang, Chen |
Affiliation | 1.MOE Frontier Science Center for Precision Oncology, Cancer Center, Faculty of Health Sciences, University of Macau, Taipa, Macao 2.Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Taipa, Macao 3.Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China |
First Author Affilication | Cancer Centre |
Corresponding Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Deng, Min,Chen, Xinyu,Qiu, Jiayue,et al. A Neural Network–Based Scoring System for Predicting Prognosis and Therapy in Breast Cancer[J]. Current Protocols, 2024, 4(8), e1122. |
APA | Deng, Min., Chen, Xinyu., Qiu, Jiayue., Liu, Guiyou., & Huang, Chen (2024). A Neural Network–Based Scoring System for Predicting Prognosis and Therapy in Breast Cancer. Current Protocols, 4(8), e1122. |
MLA | Deng, Min,et al."A Neural Network–Based Scoring System for Predicting Prognosis and Therapy in Breast Cancer".Current Protocols 4.8(2024):e1122. |
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