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

Title: Multi-Gene Prognostic Signatures and Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in ER-Positive, HER2-Negative Breast Cancer Patients
Authors: Mazo, ClaudiaBarron, StephenMooney, CatherineGallagher, William M.
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Date: 1-May-2020
Online since: 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.
Funding Details: 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
Keywords: Breast cancerMulti-gene prognostic signatureNeoadjuvant chemotherapyBreast cancer treatmentPathological complete responseTumor-infiltrating lymphocytes LYMPHOCYTESEstrogen receptor
DOI: 10.3390/cancers12051133
Language: en
Status of Item: Peer reviewed
ISSN: 2072-6694
This item is made available under a Creative Commons License:
Appears in Collections:Conway Institute Research Collection
Computer Science Research Collection
Biomolecular and Biomedical Science Research Collection

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