A 3-gene biomarker signature to predict response to taxane-based neoadjuvant chemotherapy in breast cancer

Autor: Martina Schad, Alessandro Romualdi, Jim Kallarackal, Stefano Bianco, Florian Burger
Rok vydání: 2020
Předmět:
0301 basic medicine
Oncology
medicine.medical_treatment
Cell Membranes
Cancer Treatment
Gene Expression
Biochemistry
0302 clinical medicine
Breast Tumors
Medicine and Health Sciences
Neoadjuvant therapy
Data Processing
Multidisciplinary
Pharmaceutics
Neoadjuvant Therapy
030220 oncology & carcinogenesis
Cohort
Medicine
Biomarker (medicine)
Female
Taxoids
Cellular Structures and Organelles
Information Technology
Research Article
Clinical Oncology
Computer and Information Sciences
medicine.medical_specialty
Science
Antineoplastic Agents
Breast Neoplasms
Cancer Chemotherapy
03 medical and health sciences
Breast cancer
Drug Therapy
Diagnostic Medicine
Internal medicine
Breast Cancer
DNA-binding proteins
Cancer Detection and Diagnosis
Genetics
Biomarkers
Tumor
medicine
Chemotherapy
Humans
Gene Regulation
RNA
Messenger
Survival analysis
Adaptor Proteins
Signal Transducing
Taxane
Receiver operating characteristic
business.industry
Calcium-Binding Proteins
Biology and Life Sciences
Cancers and Neoplasms
Membrane Proteins
Proteins
Cell Biology
medicine.disease
Survival Analysis
Regulatory Proteins
NFI Transcription Factors
030104 developmental biology
Relative risk
Clinical Medicine
Transcriptome
business
Biomarkers
Transcription Factors
Zdroj: PLoS ONE, Vol 15, Iss 3, p e0230313 (2020)
PLoS ONE
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0230313
Popis: Breast cancer is the most common cancer in women worldwide, affecting one in eight women in their lifetime. Taxane-based chemotherapy is routinely used in the treatment of breast cancer. The purpose of this study was to develop and validate a predictive biomarker to improve the benefit/risk ratio for that cytotoxic chemotherapy. We explicitly strived for a biomarker that enables secure translation into clinical practice. We used genome-wide gene expression data of the Hatzis et al. discovery cohort of 310 patients for biomarker development and three independent cohorts with a total of 567 breast cancer patients for validation. We were able to develop a biomarker signature that consists of just the three gene products ELF5, SCUBE2 and NFIB, measured on RNA level. Compared to Hatzis et al., we achieved a significant improvement in predicting responders and non-responders in the Hatzis et al. validation cohort with an area under the receiver operating characteristics curve of 0.73 [95% CI, 69%-77%]. Moreover, we could confirm the performance of our biomarker on two further independent validation cohorts. The overall performance on all three validation cohorts expressed as area under the receiver operating characteristics curve was 0.75 [95% CI, 70%-80%]. At the clinically relevant classifier's operation point to optimize the exclusion of non-responders, the biomarker correctly predicts three out of four patients not responding to neoadjuvant taxane-based chemotherapy, independent of the breast cancer subtype. At the same time, the response rate in the group of predicted responders increased to 42% compared to 23% response rate in all patients of the validation cohorts.
Databáze: OpenAIRE
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