Whole-transcriptome analysis links trastuzumab sensitivity of breast tumors to both HER2 dependence and immune cell infiltration
Bibliographic record
Abstract
// Tiziana Triulzi 1, * , Loris De Cecco 2, * , Marco Sandri 1 , Aleix Prat 3, 4 , Marta Giussani 1 , Biagio Paolini 5 , Marialuisa L. Carcangiu 5 , Silvana Canevari 2 , Alberto Bottini 6 , Andrea Balsari 1, 7 , Sylvie Menard 1 , Daniele Generali 6 , Manuela Campiglio 1 , Serena Di Cosimo 8 , Elda Tagliabue 1 1 Department of Experimental Oncology and Molecular Medicine, Molecular Targeting Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy 2 Department of Experimental Oncology and Molecular Medicine, Functional Genomics Core Facility, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy 3 Translational Genomics Group, Vall d’Hebron Institute of Oncology, Barcelona, Spain 4 Medical Oncology Department, Hospital Clínic i Provincial, Barcelona, Spain 5 Department of Pathology, Anatomic Pathology A Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy 6 Dipartimento di Terapia Molecolare e Farmacogenomica, Istituti Ospitalieri di Cremona, Italy 7 Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Italy 8 Department of Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy * These authors have contributed equally to this work Correspondence to: Tagliabue E, e-mail: elda.tagliabue@istitutotumori.mi.it Keywords: breast cancer, trastuzumab benefit, gene expression profiling, lymphocytes Received: April 22, 2015 Accepted: June 19, 2015 Published: July 01, 2015 ABSTRACT While results thus far demonstrate the clinical benefit of trastuzumab, some patients do not respond to this therapy. To identify a molecular predictor of trastuzumab benefit, we conducted whole-transcriptome analysis of primary HER2+ breast carcinomas obtained from patients treated with trastuzumab-containing therapies and correlated the molecular portrait with treatment benefit. The estimated association between gene expression and relapse-free survival allowed development of a trastuzumab risk model (TRAR), with ERBB2 and ESR1 expression as core elements, able to identify patients with high and low risk of relapse. Application of the TRAR model to 24 HER2+ core biopsies from patients treated with neo-adjuvant trastuzumab indicated that it is predictive of trastuzumab response. Examination of TRAR in available whole-transcriptome datasets indicated that this model stratifies patients according to response to trastuzumab-based neo-adjuvant treatment but not to chemotherapy alone. Pathway analysis revealed that TRAR-low tumors expressed genes of the immune response, with higher numbers of CD8-positive cells detected immunohistochemically compared to TRAR-high tumors. The TRAR model identifies tumors that benefit from trastuzumab-based treatment as those most enriched in CD8-positive immune infiltrating cells and with high ERBB2 and low ESR1 mRNA levels, indicating the requirement for both features in achieving trastuzumab response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".