Clinical trial · Observational
Tumor-microenvironment Spatial Interaction to Identify Markers of Resistance to Therapy in HER2+ Breast Cancer Patients
A Retrospective Observational Study Characterizing Tumour-microenvironment Spatial Interaction Aimed at the Identification of New Markers of Resistance to Therapy in HER2-positive Breast Cancer Patients
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This retrospective observational study aims at the comparison of the tumour-microenvironment tissue architecture before and after neo-adjuvant therapy in samples from HER2-positive (HER2+) breast cancer (BrCa) patients that display residual invasive disease in the breast/lymph node at surgery after standard-of-care combined chemotherapy and trastuzumab treatment. The working hypothesis of the investigators is that: Therapy imposes a selective pressure on tumour-microenvironment features promoting resistance to treatment. Participant that have already undergone neo-adjuvant treatment as part of their regular medical care for HER2-positive breast cancer will provide access to formalin-fixed paraffin-embedded (FFPE) samples taken before and after therapy. Tumoral, peri-tumoral and stromal regions of each specimen will be analyzed with the ultimate goal to identify new biomarkers (and putative targets) of resistance to therapy.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| HER2-positive Breast Cancer | HER2-Positive Breast Carcinoma | ALIAS | 0.90 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (5)
- measure
- number of different cells per each phenotype
- timeFrame
- before and within 3 months from neo-adjuvant therapy (at surgery)
- description
- Cell types will be classified based on the expression of specific lineage/phenotype markers.
- measure
- density of each phenotype
- timeFrame
- before and within 3 months from neo-adjuvant therapy (at surgery)
- description
- Cell phenotype densities will be calculated by dividing the number of total cells counted by the total area of the tissue acquired.
- measure
- fraction of proliferative/active cells of each phenotype
- timeFrame
- before and within 3 months from neo-adjuvant therapy (at surgery)
- description
- The proportion of cells positive for the proliferation marker Ki67 will be assessed per cell phenotype. To assess the proportion of active immune cells, we will quantify the expression level of activation markers.
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: 1. Participant is willing and able to give informed consent for participation in the study. 2. Patient underwent the following procedure before surgery: biopsy, sequential chemotherapy comprising treatment with antracyclines (AC/EC q21, 4 cycles) followed by taxanes (paclitaxel 1,8,15 q21 for 12 weeks) in combination with the anti-HER2 antibody trastuzumab. 3. Specimen collected at surgery display residual invasive disease in the breast/lymph node. Exclusion Criteria: 1. pre-existing conditions or concurrent diagnoses; 2. concomitant use of other medications during neo-adjuvant treatment; 3. quality of stored specimen does not meet the standard for Imaging Mass Cytometry analysis.
References
Publications (1)
- BACKGROUNDWang XQ, Danenberg E, Huang CS, Egle D, Callari M, Bermejo B, Dugo M, Zamagni C, Thill M, Anton A, Zambelli S, Russo S, Ciruelos EM, Greil R, Gyorffy B, Semiglazov V, Colleoni M, Kelly CM, Mariani G, Del Mastro L, Biasi O, Seitz RS, Valagussa P, Viale G, Gianni L, Bianchini G, Ali HR. Spatial predictors of immunotherapy response in triple-negative breast cancer. Nature. 2023 Sep;621(7980):868-876. doi: 10.1038/s41586-023-06498-3. Epub 2023 Sep 6. PMID 37674077