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  5. Multi-Gene Prognostic Signatures and Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in ER-Positive, HER2-Negative Breast Cancer Patients
 
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Multi-Gene Prognostic Signatures and Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in ER-Positive, HER2-Negative Breast Cancer Patients

Author(s)
Mazo, Claudia  
Barron, Stephen  
Mooney, Catherine  
Gallagher, William M.  
Uri
http://hdl.handle.net/10197/12179
Date Issued
2020-05-01
Date Available
2021-05-19T16:12:01Z
Abstract
Determining which patients with early-stage breast cancer should receive chemotherapy is an important clinical issue. Chemotherapy has several adverse side effects, impacting on quality of life, along with significant economic consequences. There are a number of multi-gene prognostic signatures for breast cancer recurrence but there is less evidence that these prognostic signatures are predictive of therapy benefit. Biomarkers that can predict patient response to chemotherapy can help avoid ineffective over-treatment. The aim of this work was to assess if the OncoMasTR prognostic signature can predict pathological complete response (pCR) to neoadjuvant chemotherapy, and to compare its predictive value with other prognostic signatures: EndoPredict, Oncotype DX and Tumor Infiltrating Leukocytes. Gene expression datasets from ER-positive, HER2-negative breast cancer patients that had pre-treatment biopsies, received neoadjuvant chemotherapy and an assessment of pCR were obtained from the Gene Expression Omnibus repository. A total of 813 patients with 66 pCR events were included in the analysis. OncoMasTR, EndoPredict, Oncotype DX and Tumor Infiltrating Leukocytes numeric risk scores were approximated by applying the gene coefficients to the corresponding mean probe expression values. OncoMasTR, EndoPredict and Oncotype DX prognostic scores were moderately well correlated according to the Pearson’s correlation coefficient. Association with pCR was estimated using logistic regression. The odds ratio for a 1 standard deviation increase in risk score, adjusted for cohort, were similar in magnitude for all four signatures. Additionally, the four signatures were significant predictors of pCR. OncoMasTR added significant predictive value to EndoPredict, Oncotype DX and Tumor Infiltrating Leukocytes signatures as determined by bivariable and trivariable analysis. In this in silico analysis, OncoMasTR, EndoPredict, Oncotype DX, and Tumor Infiltrating Leukocytes were significantly predictive of pCR to neoadjuvant chemotherapy in ER-positive and HER2-negative breast cancer patients.
Sponsorship
Enterprise Ireland
European Commission Horizon 2020
Irish Research Council
Science Foundation Ireland
Type of Material
Journal Article
Publisher
MDPI
Journal
Cancers
Volume
12
Issue
5
Copyright (Published Version)
2020 the Authors
Subjects

Breast cancer

Multi-gene prognostic...

Neoadjuvant chemother...

Breast cancer treatme...

Pathological complete...

Tumor-infiltrating ly...

Estrogen receptor

DOI
10.3390/cancers12051133
Language
English
Status of Item
Peer reviewed
ISSN
2072-6694
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by/3.0/ie/
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Multi-Gene Prognostic Signatures and Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in ER-positive.pdf

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1.38 MB

Format

Adobe PDF

Checksum (MD5)

6d2397c529da8e07bed55a6a38fbd485

Owning collection
Computer Science Research Collection
Mapped collections
Biomolecular and Biomedical Science Research Collection•
Conway Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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