ArticleCommunications medicine2025
Predicting the response to immunotherapy from gene expression data in HER2-negative breast cancer.
Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundThe addition of immunotherapy in the neoadjuvant setting is showing promising results for HER2- and triple-negative breast cancer patients, but pathological complete response is observed only in a fraction of patients. The aim of the present work was to investigate if ARIADNE, an algorithmic strategy to analyze gene expression data from bioptic samples based on epithelial-mesenchymal phenotypes, can predict the response to immunotherapy in HER2- patients.
methodsWe considered gene expression data for HER2-breast cancer patients treated with pembrolizumab in addition to chemotherapy (n = 69) and with chemotherapy alone (n = 179) from the I-SPY 2 trial. We stratified patients in two risk groups (low/high risk) according to the score of the ARIADNE algorithm and studied an additional cytokine signature. To better understand the significance of our results, we studied the interactions among genes in the PD-L1 pathway and analyzed single-cell data from TNBC patients treated with pembrolizumab.
resultsOur results show that ARIADNE predicts differential response to immunotherapy: the high-risk group has a pathological complete response (pCR) rate of 26% as compared with 62% for the low-risk group (OR 4.7, with 1.68-11.32 95% CI and p < 0.01). We also find significant correlations between a cytokine score and the rate of pCR. The ability of ARIADNE to predict pCR is associated with regulatory activity within the PD-L1 pathway. Comparison between ARIADNE and other immunological genomic signatures shows no correlations. The study of single-cell data showed that patients responding to immunotherapy display a larger number of exhausted T-cells than non-responders.
conclusionsOur analysis shows that ARIADNE is predictive of the response to immunotherapy, but not to chemotherapy, in HER2- patients.
Identifiers
What OpenQuestion holds
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.