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RNA Sequencing to Predict Response to Neoadjuvant Anti-HER2 Therapy: A Secondary Analysis of the NeoALTTO Randomized
Debora Fumagalli1, David Venet1, Michail Ignatiadis1
1Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium.
Importance:
In neoadjuvant trials, treatment of human epidermal growth factor receptor 2 (HER2)-positive breast cancers with dual HER2 blockade resulted in increased pathologic complete response (pCR) rates compared with each targeted agent alone. Amplification and/or overexpression of HER2 currently remains the only biomarker for therapeutic decisions, but it is insufficient to explain the heterogeneous response to anti-HER2 agents.
Objective:
To investigate the ability of clinically and biologically relevant genes and gene signatures (GSs) measured by RNA sequencing to predict the efficacy of anti-HER2 agents.
Design, Setting, And Participants:
The neoadjuvant NeoALTTO trial randomized 455 women with HER2-positive early-stage breast cancer to trastuzumab, lapatinib, or the combination for 6 weeks followed by the addition of weekly paclitaxel for 12 weeks, followed by 3 cycles of fluorouracil, epirubicin, and cyclophosphamide after surgery. The present substudy, which was planned in the NeoALTTO main protocol, evaluated the association of pretreatment gene expression levels defined using RNA sequencing with pCR and event-free survival (EFS).
Main Outcomes And Measures:
Gene expression-based biomarkers using RNA sequencing were examined for their association with response to anti-HER2 therapy and long-term outcome.
Results:
Sequencing data were available for 254 (56%) of the NeoALTTO participants (mean [SD] age of substudy participants, 48.8 [11.2] years). The expression of ERBB2/HER2 was the most significant predictor of pCR, followed by HER2-enriched subtype, ESR1, treatment arm, ER immunohistochemical analysis scores, Genomic Grade Index, immune, proliferation, and AKT/mTOR GSs. Adjusting for clinicopathological variables and treatment arms, ERBB2/HER2, HER2-enriched subtype, ESR1, and Genomic Grade Index remained significant. Immune GSs were associated with higher pCR only in the combination arm (odds ratio, 2.1; 95% CI, 1.2-4.0; interaction test P = .01), while the stroma GSs were significantly associated with higher pCR in the single arms and with lower pCR in the combination arm (odds ratio, 0.46; 95% CI, 0.25-0.84; P = .009). None of the evaluated variables was associated with EFS after correction for multiple testing, but this analysis was underpowered.
Conclusions And Relevance:
High levels of ERBB2/HER2 and low levels of ESR1 were associated with pCR in all treatment arms. In the combination arm, high expression of immune and stroma GSs were significantly associated with higher and lower pCR rates, respectively, and should be further explored as candidate predictive markers.
Trial Registration:
clinicaltrials.gov Identifier: NCT00553358.
Insights
Gene expression analysis in HER2-positive breast cancer reveals ERBB2/HER2 and ESR1 levels predict treatment response. Immune and stroma gene signatures show differential effects in combination therapy, suggesting potential predictive markers.
Area of Science:
- Oncology
- Genomics
- Translational Research
Background:
- Dual HER2 blockade improves pathologic complete response (pCR) in HER2-positive breast cancer.
- HER2 amplification/overexpression is the sole biomarker but insufficient for predicting heterogeneous responses to anti-HER2 agents.
Purpose of the Study:
- To assess if RNA sequencing-measured genes and gene signatures (GSs) can predict anti-HER2 agent efficacy.
- To identify novel biomarkers for predicting treatment response in HER2-positive breast cancer.
Main Methods:
- RNA sequencing was used to analyze pretreatment gene expression in 254 HER2-positive early-stage breast cancer patients from the NeoALTTO trial.
- The study investigated associations between gene expression, pCR, and event-free survival (EFS) following neoadjuvant anti-HER2 therapy.
Main Results:
- ERBB2/HER2 expression was the strongest predictor of pCR, followed by HER2-enriched subtype, ESR1, and Genomic Grade Index.
- Immune GSs correlated with higher pCR in the combination arm, while stroma GSs correlated with higher pCR in single-agent arms and lower pCR in the combination arm.
- No evaluated variables were significantly associated with EFS after multiple testing correction, though the analysis was underpowered.
Conclusions:
- High ERBB2/HER2 and low ESR1 levels are associated with pCR across all treatment arms.
- Immune and stroma gene signatures warrant further investigation as predictive markers, particularly in combination therapy settings.
- Gene expression profiling offers potential for personalized treatment strategies in HER2-positive breast cancer.
