This study explores early breast cancer, focusing on triple-negative and high-risk luminal subtypes. It combines single-cell RNA sequencing and spatial imaging of tumor samples collected at different time points during treatment. The aim is to better understand how cancer cells and immune cells interact and to identify biomarkers that can predict whether a patient will respond to chemo-immunotherapy or develop resistance.
The study assumes that early molecular and spatial changes at the single-cell level can predict treatment response. This knowledge could help doctors adapt therapies, avoiding unnecessary treatment while improving effectiveness. The project seeks to reveal, for the first time, how cellular diversity and spatial relationships contribute to treatment resistance and disease progression.
Tumor samples will be analyzed before treatment, after the first treatment cycle (C1D1), and at surgery. Only the biopsy taken after C1D1 is collected specifically for this study; all other samples come from routine clinical care.
Female patients aged ≥18 years.
ECOG performance status 0-1.
TNBC: ER and PR negative (IHC <10%) and HER2 negative (IHC 0-1+ or FISH non-amplified).
High-risk luminal (ER+/HER2-): ER positive (IHC ≥10%) HER2 negative (IHC 0-1+ or FISH non-amplified), with high-risk features (e.g., Grade 3, PR-negative, high proliferation, high TILS).
HER2-positive tumors.
Multifocal tumors - exclusion if a single index lesion cannot be identified and sampled; otherwise allowed if a representative lesion can be biopsied.
Known metastatic disease. 4 Clinical contraindications to the planned neoadjuvant therapy.
Single group
on treatment biopsy (after C1)
Procedure/SurgerySerial tumor tissue collection and analysis for the identification of early tumor response biomarkers. Tumor samples will be obtained at three predefined time points: (i) prior to initiation of treatment (baseline biopsy), (ii) after Cycle 1 Day 1 (C1D1) of therapy, and (iii) at the time of surgery (surgical specimen)
To characterize the dynamic changes in tumor and immune cell populations in TNBC and to prospectively collect serial samples from high-risk luminal (ER+/HER2-) breast cancer patients.
Gene expression levels per single-cell and relative cell clustering (%) by comparing pre-treatment, on-treatment (after first cycle of standard of care neoadiuvant therapy), and post-treatment (surgery or residual disease)
To correlate single-cell gene expression data with pCR and RD to identify predictive signatures of therapy response
pCR and RD will be evaluated across all collected timepoints (baseline, after C1 of neadiuvant standard of care therapy and at surgery)
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