Trial reportAnnals of oncology : official journal of the European Society for Medical Oncology2017
Pathway level alterations rather than mutations in single genes predict response to HER2-targeted therapies in the neo-ALTTO trial.
Trial report in Annals of oncology : official journal of the European Society for Medical Oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 43 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 73 citations in OpenAlex.
- Analysis of Pre- and Posttreatment Tissues from the SWOG S0800 Trial Reveals an Effect of Neoadjuvant Chemotherapy on the Breast Cancer Genome.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Trial
- Trial
- Integrated Analysis of RNA and DNA from the Phase III Trial CALGB 40601 Identifies Predictors of Response to Trastuzumab-Based Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018Trial
- Trial
- De-Escalation of Neoadjuvant Treatment for HER2-Positive Breast Cancer.International journal of cancer · 2026Review
- Tumor mutations predict HER2-targeted therapy resistance in primary HER2-positive breast cancer.NPJ breast cancer · 2026Article
- Activated Hippo Pathway is Associated with a Worse Response to Trastuzumab and Worse Survival in HER2-Positive Breast Cancer.Annals of surgical oncology · 2025Article
- Quantitative Proteomics Unveils the Synergistic Effects of Combination Drugs on Cytoskeleton Composition and Autophagy-Mediated Cell Death in Neuroblastoma.Journal of proteome research · 2025Article
- MADSP: predicting anti-cancer drug synergy through multi-source integration and attention-based representation learning.Bioinformatics (Oxford, England) · 2025Article
- Whole-exome profiles of inflammatory breast cancer and pathological response to neoadjuvant chemotherapy.Journal of translational medicine · 2024Article
- Improving drug response prediction via integrating gene relationships with deep learning.Briefings in bioinformatics · 2024Article
- Genetic mutations in HER2-positive breast cancer: possible association with response to trastuzumab therapy.Human genomics · 2023Article
- Article
- Accelerated glycolysis in tumor microenvironment is associated with worse survival in triple-negative but not consistently with ER+/HER2- breast cancer.American journal of cancer research · 2023Article
- Predictive biomarkers for molecularly targeted therapies and immunotherapies in breast cancer.Archives of pharmacal research · 2022Review
- Review
- Clinical implication of genetic composition and molecular mechanism on treatment strategies of HER2-positive breast cancers.Frontiers in oncology · 2022Review
- Can Systems Biology Advance Clinical Precision Oncology?Cancers · 2021Review
- Molecular Biomarkers Predict Pathological Complete Response of Neoadjuvant Chemotherapy in Breast Cancer Patients: Review.Cancers · 2021Review
- Concurrent mutations associated with trastuzumab-resistance revealed by single cell sequencing.Breast cancer research and treatment · 2021Article
Corrections and comments
- Erratum issued
- Erratum issued
- Erratum issued
Authors and funding
20 authors at 13 institutions in 10 countries.
Funding
Abstract
Background: We performed whole-exome sequencing of pretreatment biopsies and examined whether genome-wide metrics of overall mutational load, clonal heterogeneity or alterations at variant, gene, and pathway levels are associated with treatment response and survival. Patients and Methods: Two hundred and three biopsies from the NeoALTTO trial were analyzed. Mutations were called with MuTect, and Strelka, using pooled normal DNA. Associations between DNA alterations and outcome were evaluated by logistic and Cox-proportional hazards regression. Results: There were no recurrent single gene mutations significantly associated with pathologic complete response (pCR), except PIK3CA [odds ratio (OR) = 0.42, P = 0.0185]. Mutations in 33 of 714 pathways were significantly associated with response, but different genes were affected in different individuals. PIK3CA was present in 23 of these pathways defining a ‘trastuzumab resistance-network’ of 459 genes. Cases with mutations in this network had low pCR rates to trastuzumab (2/50, 4%) compared with cases with no mutations (9/16, 56%), OR = 0.035; P < 0.001. Mutations in the ‘Regulation of RhoA activity’ pathway were associated with higher pCR rate to lapatinib (OR = 14.8, adjusted P = 0.001), lapatinib + trastuzumab (OR = 3.0, adjusted P = 0.09), and all arms combined (OR = 3.77, adjusted P = 0.02). Patients (n = 124) with mutations in the trastuzumab resistance network but intact RhoA pathway had 2% (1/41) pCR rate with trastuzumab alone (OR = 0.026, P = 0.001) but adding lapatinib increased pCR rate to 45% (17/38, OR = 1.68, P = 0.3). Patients (n = 46) who had no mutations in either gene set had 6% pCR rate (1/15) with lapatinib, but had the highest pCR rate, 52% (8/15) with trastuzumab alone. Conclusions: Mutations in the RhoA pathway are associated with pCR to lapatinib and mutations in a PIK3CA-related network are associated with resistance to trastuzumab. The combined mutation status of these two pathways could define patients with very low response rate to trastuzumab alone that can be augmented by adding lapatinib or substituting trastuzumab with lapatinib.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.