[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100658077":3},{"organization":4,"outcomesModule":7,"designInfo":27,"detailedDescription":26,"studyPopulation":26,"armGroups":33,"interventions":41,"overallOfficials":52,"centralContacts":56,"locations":62,"responsibleParty":76,"collaborators":26,"id":78,"slug":79,"hasResults":80,"nctId":81,"briefTitle":82,"officialTitle":82,"acronym":83,"eligibilityCriteria":84,"healthyVolunteers":80,"sex":85,"minAge":86,"maxAge":26,"enrollmentInfo":87,"targetDuration":26,"studyType":90,"phases":91,"briefSummary":92,"conditions":93,"keywords":26,"overallStatus":95,"whyStopped":26,"lastUpdateSubmitDate":96,"lastUpdatePostDateStruct":97,"startDateStruct":100,"completionDateStruct":102,"leadSponsor":104,"locationsCount":105},{"fullName":5,"class":6},"Centre Antoine Lacassagne","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":16,"otherOutcomes":26},[9,13],{"measure":10,"description":11,"timeFrame":12},"Predictive performance of targeted metabolites and histological response","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.","From enrollment to the end of treatment and follow-up - 8 months.",{"measure":14,"description":15,"timeFrame":12},"Consistency of metabolites between plasma and tumor biopsies","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.",[17,20,23],{"measure":18,"description":19,"timeFrame":12},"Performance of a metabolomic signature using machine learning","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.",{"measure":21,"description":22,"timeFrame":12},"Variations of tryptophan pathway metabolites","Variations in tryptophan pathway metabolites will be evaluated by semi-quantitative correlation with the clinical-biological response.",{"measure":24,"description":25,"timeFrame":12},"Prediction of radiological response by targeted metabolites","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.",null,{"allocation":28,"interventionModel":29,"interventionModelDescription":26,"primaryPurpose":30,"observationalModel":26,"timePerspective":26,"maskingInfo":31},"NA","SINGLE_GROUP","DIAGNOSTIC",{"masking":32,"maskingDescription":26,"whoMasked":26},"NONE",[34],{"label":35,"type":36,"description":37,"interventionNames":38},"Neoadjuvant chemo-immunotherapy","EXPERIMENTAL","Patients receiving neoadjuvant chemo-immunotherapy according to the study protocol.",[39,40],"Biological: Blood sampling","Procedure: Tumor sampling",[42,47],{"type":43,"name":44,"description":45,"armGroupLabels":46,"otherNames":26},"BIOLOGICAL","Blood 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.",[35],{"type":48,"name":49,"description":50,"armGroupLabels":51,"otherNames":26},"PROCEDURE","Tumor 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.",[35],[53],{"name":54,"affiliation":5,"role":55},"Caroline BAILLEUX","PRINCIPAL_INVESTIGATOR",[57],{"name":58,"role":59,"phone":60,"phoneExt":26,"email":61},"Study coordinator","CONTACT","+33 (0)4 92 03 17 78","DRCI-Promotion@nice.unicancer.fr",[63],{"facility":5,"status":26,"city":64,"state":26,"zip":65,"country":66,"countryCode":67,"cosmosGeoPoint":68,"geoPoint":73,"contacts":74},"Nice","06189","France","FR",{"type":69,"coordinates":70},"Point",[71,72],7.26608,43.70313,{"lat":72,"lon":71},[75],{"name":58,"role":59,"phone":60,"phoneExt":26,"email":61},{"type":77,"investigatorFullName":26,"investigatorTitle":26,"investigatorAffiliation":26,"oldNameTitle":26,"oldOrganization":26},"SPONSOR","100658077","emergence-of-predictive-metabolomic-biomarkers-of-response-to-neoadjuvant-chemoimmunotherapy-in-triple-negative-breast-cancer-100658077",false,"NCT07847398","Emergence of Predictive Metabolomic Biomarkers of Response to Neoadjuvant Chemoimmunotherapy in Triple-Negative Breast Cancer.","EMMENEO-TN","Inclusion Criteria:\n\n* Age 18 years or older.\n* 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 \\\u003C 10%, PR \\\u003C 10%, HER2 0, and HER2 low).\n* Patient requiring the placement of a localization clip as part of their standard clinical care management.\n* Patient who has read the information sheet and signed the informed consent.\n* Patient affiliated with a Social Security health insurance scheme.\n\nExclusion Criteria:\n\n* Metastatic breast cancer documented by staging workup (PET scan or thoraco-abdomino-pelvic CT scan + bone scan).\n* Patient who has undergone primary surgery.\n* INR \\\u003C 1.5; Platelets \\\u003C 50,000\u002F$\\\\mu$L.\n* Patient presenting with multiple primary malignant tumors.\n* Patient with HIV infection, Hepatitis C, or active Hepatitis B.\n* Patient taking:\n* Dual antiplatelet therapy: Acetylsalicylic acid + Clopidogrel without the possibility of suspending Clopidogrel for 5 days,\n* Ticagrelor without the possibility of suspension for 5 days,\n* Prasugrel without the possibility of suspension for 7 days,\n* Vitamin K antagonists (acenocoumarol, warfarin, or fluindione) with INR \\\u003C 2 or \\> 3, without the possibility of suspension.","FEMALE","18 Years",{"count":88,"type":89},50,"ESTIMATED","INTERVENTIONAL",[28],"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).\n\nThe main objectives are to determine:\n\n* whether targeted metabolic pathways, specifically tryptophan and diacetylspermine metabolism, are associated with histological response to neoadjuvant treatment;\n* whether untargeted metabolomics combined with machine learning approaches can identify novel biomarkers predictive of treatment response.\n\nParticipants will:\n\n* 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;\n* provide a blood sample before initiation of neoadjuvant chemo-immunotherapy;\n* 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.\n\nThe study does not modify the patient's standard therapeutic management.",[94],"Triple-negative Breast Cancer (TNBC), Stage II-III","NOT_YET_RECRUITING","2026-09-28",{"date":98,"type":99},"2026-09-29","ACTUAL",{"date":101,"type":89},"2026-10",{"date":103,"type":89},"2029-05",{"name":5,"class":6},1]