What if the future of HER2-positive breast cancer patients was written in miRNAs? An exploratory analysis from NeoALTTO study

Abstract

Background: Neoadjuvant therapy with dual HER2 blockade improved pathological complete response (pCR) rate in HER2-positive breast cancer patients. Nevertheless, it would be desirable to identify patients exquisitely responsive to single agent trastuzumab to minimize or avoid overtreatment. Herein, we evaluated the predictive and prognostic value of basal primary tumor miRNA expression profile within the trastuzumab arm of NeoALTTO study (ClinicalTrials.gov Identifier: NCT00553358).

Methods: RNA samples from baseline biopsies were randomized into training (n = 45) and testing (n = 47) sets. After normalization, miRNAs associated with Event-free survival (EFS) and pCR were identified by univariate analysis. Multivariate models were implemented to generate specific signatures which were first confirmed, and then analyzed together with other clinical and pathological variables.

Results: We identified a prognostic signature including hsa-miR-153-3p (HR 1.831, 95% CI: 1.34-2.50) and hsa-miR-219a-5p (HR 0.629, 95% CI: 0.50-0.78). For two additional miRNAs (miR-215-5p and miR-30c-2-3p), we found a statistically significant interaction term with pCR (p.interaction: 0.017 and 0.038, respectively). Besides, a two-miRNA signature was predictive of pCR (hsa-miR-31-3p, OR 0.70, 95% CI: 0.53-0.92, and hsa-miR-382-3p, OR: 1.39, 95% CI: 1.01-1.91). Notably, the performance of this predictive miRNA signature resembled that of the genomic classifiers PAM50 and TRAR, and did not improve when the extended models were fitted.

Conclusion: Analyses of primary tumor tissue miRNAs hold the potential of a parsimonious tool to identify patients with differential clinical outcomes after trastuzumab based neoadjuvant therapy.

Keywords: HER2; biomarkers; breast cancer; microRNA; trastuzumab.

Conflict of interest statement

Dr. S. Di Cosimo received speaking fees from Novartis Pharma, and Pierre‐Fabre outside this work and is the recipient of the IG 20774 from Fondazione Associazione Italiana Ricerca sul Cancro (AIRC). Dr. S. El‐abed received grant from Novartis during the conduct of the study, and grants from Roche/Genentech and Pfizer outside the submitted work. Dr. Nuciforo received grants from Novartis for the submitted work and from Novartis, Roche/Genentech, MSD Oncology, Bayer, and Targos outside the submitted work. Dr. Rimm has no conflict of interest related to this work. Unrelated to the topic of the paper, Dr. Rimm has received honoraria and/or grants and/or instrument support from Akoya, Amgen, AstraZeneca, BMS, Cell Signaling Technology, Cepheid, Danaher, Konica/Minolta, Lilly, Merck, NanoString, Navigate Biopharma, NextCure, Odonate, Paige.AI, Roche, Sanofi, and Ventana. None of that funding was related to this work. Dr. Gombos: no conflict of interest related to this publication. Other COI: advisory board (Institution): Lilly, Daiichi Sankyo; travel grants: Pfizer. Dr. Huober J received research funding from Celgene, Novartis, Hexal, Lilly; honoraria from Lilly, Novartis, Roche, Pfizer, AstraZeneca, MSD, Celgene; Eisai, Abbvie, Seagen, Gilead; has consulting advisory relationship with Lilly, Novartis, Roche, Pfizer, Hexal, AstraZeneca, MSD, Celgene, Abbvie, Seagen, Gilead; travel expenses from Roche, Pfizer, Novartis, Celgene, Daiichi. Dr. Wang Y is employee at Novartis and holds Novartis stock. Dr. M Bajji's institution, Institut Jules Bordet, has received a research grant for the conduct of the NeoALTTO study. The other authors have no conflict of interest to declare.

© 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Figures

FIGURE 1

NeoALTTO miRNA analysis flow diagram of frozen tissue samples. Following quality check, 285 out of 340 RNA samples considered suitable for miRNA profile. Samples then randomized in a training set (n = 142) and a testing (n = 143) set

FIGURE 2

Receiver operating characteristic (ROC) curve of the final signature of miR‐31‐3p and miR‐382‐3p