Triple-negative Breast Cancer (TNBC), Stage II-III
Conditions
Brief summary
The goal of this study is to investigate whether specific metabolic profiles can predict response to neoadjuvant chemo-immunotherapy in patients with stage II and III triple-negative breast cancer (TNBC). The main objectives are to determine: * whether targeted metabolic pathways, specifically tryptophan and diacetylspermine metabolism, are associated with histological response to neoadjuvant treatment; * whether untargeted metabolomics combined with machine learning approaches can identify novel biomarkers predictive of treatment response. Participants will: * undergo image-guided tumor sampling during the standard-of-care placement of the tumor localization clip, prior to initiation of neoadjuvant chemo-immunotherapy, in accordance with routine clinical practice at the study center; * provide a blood sample before initiation of neoadjuvant chemo-immunotherapy; * provide a second blood sample during the course of standard treatment; continue to receive routine clinical care, including imaging assessments and surgical management, according to standard clinical practice. The study does not modify the patient's standard therapeutic management.
Interventions
BIOLOGICALBlood sampling
Two blood samples will be collected during neoadjuvant chemo-immunotherapy: one at Cycle 1, Day 1 (C1D1) of Sequence 1, prior to treatment initiation, and one at Cycle 3, Day 1 (C3D1) of Sequence 2, prior to treatment administration. Blood samples will be used for metabolomic analyses of plasma.
PROCEDURETumor sampling
Two tumor core biopsy samples will be collected under radiological guidance during placement of the localization clip, prior to initiation of neoadjuvant chemo-immunotherapy, in accordance with standard procedures at the study site. One core will be used for pathological confirmation of tumor tissue and the other will be collected for research purposes and used for subsequent molecular analyses.
Sponsors
Centre Antoine Lacassagne
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Age 18 years or older. * Female patient with stage II and III triple-negative breast cancer, requiring neoadjuvant chemo-immunotherapy according to the KEYNOTE-522 regimen or any neoadjuvant treatment including chemotherapy and immunotherapy validated in standard care or a clinical trial, regardless of the treatment regimen (ER \< 10%, PR \< 10%, HER2 0, and HER2 low). * Patient requiring the placement of a localization clip as part of their standard clinical care management. * Patient who has read the information sheet and signed the informed consent. * Patient affiliated with a Social Security health insurance scheme.
Exclusion criteria
* Metastatic breast cancer documented by staging workup (PET scan or thoraco-abdomino-pelvic CT scan + bone scan). * Patient who has undergone primary surgery. * INR \< 1.5; Platelets \< 50,000/$\\mu$L. * Patient presenting with multiple primary malignant tumors. * Patient with HIV infection, Hepatitis C, or active Hepatitis B. * Patient taking: * Dual antiplatelet therapy: Acetylsalicylic acid + Clopidogrel without the possibility of suspending Clopidogrel for 5 days, * Ticagrelor without the possibility of suspension for 5 days, * Prasugrel without the possibility of suspension for 7 days, * Vitamin K antagonists (acenocoumarol, warfarin, or fluindione) with INR \< 2 or \> 3, without the possibility of suspension.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Predictive performance of targeted metabolites and histological response | From enrollment to the end of treatment and follow-up - 8 months. | The predictive performance of targeted metabolites (tryptophan pathway and diacetylspermine) to predict post-surgical histological response will be evaluated using the area under the ROC curve (AUC), with an AUC target \> 0.8. Histological response will be assessed according to the Residual Cancer Burden (RCB) classification, ranging from RCB0 (pathological complete response) to RCB3 (presence of extensive residual disease), based on the results obtained from the surgical specimen of breast surgery. |
| Consistency of metabolites between plasma and tumor biopsies | From enrollment to the end of treatment and follow-up - 8 months. | The consistency of variations in metabolites of interest between plasma samples and tumor biopsies will be evaluated by a semi-quantitative correlation between the two compartments. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Performance of a metabolomic signature using machine learning | From enrollment to the end of treatment and follow-up - 8 months. | The performance of a metabolomic signature (untargeted analysis), established notably using machine learning methods, to predict post-surgical histological response will be evaluated by the AUC, with a target \> 0.8. |
| Variations of tryptophan pathway metabolites | From enrollment to the end of treatment and follow-up - 8 months. | Variations in tryptophan pathway metabolites will be evaluated by semi-quantitative correlation with the clinical-biological response. |
| Prediction of radiological response by targeted metabolites | From enrollment to the end of treatment and follow-up - 8 months. | The predictive performance of targeted metabolites to predict radiological response to neoadjuvant chemo-immunotherapy will be evaluated by the AUC, with a target \> 0.8. |
Countries
France
Contacts
CONTACTStudy coordinator
PRINCIPAL_INVESTIGATORCaroline BAILLEUX
Centre Antoine Lacassagne
Outcome results
None listed