Patients with stage II-III Triple negative breast cancer (TNBC) candidates to receive neoadjuvant chemotherapy (NACT) +/- immune checkpoint inhibitor (ICI) will be included. Several samples from different tissues will be analyzed through different omics to establish predictive biomarkers of response to the treatment. Multiple algorithms will then be used to look for an integrative predictive algorithm that incorporates multi-parameter inputs in order to develop a clinical tool to assist clinicians in the process of treatment decision-making in TNBC.
The combination of pembrolizumab, an immune checkpoint inhibitor (ICI), with neoadjuvant chemotherapy (NACT) increases pathologic complete response (pCR) and event-free survival (EFS) in patients with early triple negative breast cancer (eTNBC). However, not all patients equally benefit from a treatment that may have relevant adverse events (AEs). Objectives: (1) To establish predictive biomarkers of response to NACT + ICI in eTNBC by correlating data coming from different layers of omics performed in different tissues, together with imaging, with pCR, EFS, and overall survival (OS). (2) To integrate data generated from (1), and clinical data, and explore multivariate predictive models of response to NACT + ICI. Methods: Patients with stage II-III TNBC candidates to receive NACT +/- ICI will be included. Collected samples and type of analysis: (1) Tumor tissue (baseline and from residual disease after NACT): whole genome sequencing (WGS) and RNA-Seq will be performed (Hartwig sequencing platform and analytical pipeline), tissue immune phenotyping (PD-L1, T and B infiltrating lymphocytes, among others), and microbiome analysis (16S rRNA); (2) Blood (before and during NACT): circulating tumor DNA (ctDNA) analysis (targeted gene panel and shallow WGS), T-cell receptor beta (TCR-β) repertoire sequencing and analysis (ImmunoSeq hsTCRβ kit and immunoSEQ), and peripheral blood mononuclear cells (PBMCs) phenotyping; (3) Stools and saliva (before and during NACT): microbiome analysis (16S rRNA); (4) Breast MRI imaging (before and after NACT): radiomics analysis. Multiple algorithms including Multiple Kernel Learning, Multi-Omics Factor Analysis (MOFA) and Method for the Functional Integration of Spatial and Temporal Omics data (MEFISTO) will then be used to look for an integrative predictive algorithm that incorporates multi-parameter inputs. The aim is to provide more personalized treatment efficacy and risk for relapse estimates. Expected outcome: To develop a clinical tool to assist clinicians in the process of treatment decision-making in eTNBC, in order to maximize patient's benefit and quality of life, while minimizing AEs and financial burden to the health system.
Study Type
OBSERVATIONAL
Enrollment
100
Whole genome sequencing (WGS) will be performed in tumor tissue from baseline and from residual disease after neoadjuvant chemotherapy (NACT), if present.
RNA-Sequencing will be performed in tumor tissue from baseline and from residual disease after NACT (if present).
Microbiome analysis will be performed in stools and saliva before, during NACT and at the end of adjuvant systemic therapy if adjuvant systemic therapy is clinically indicated.
ctDNA analysis will be performed in plasma before and during NACT.
TCR-β repertoire sequencing will be performed in plasma before and during NACT.
PBMCs phenotyping will be performed in plasma before and during NACT.
Pembrolizumab will be given in combination with standard NACT.
Standard NACT will be given.
Vall d'Hebron Institute of Oncology
Barcelona, Spain
RECRUITINGPathologic complete response (pCR) rate at definitive surgery
The rate (given as a percentage) of patients with a pCR at definitive surgery using the definition of ypT0/Tis ypN0 (i.e., no invasive residual in breast or nodes; noninvasive breast residuals allowed) from the American Joint Committee on Cancer (AJCC) staging criteria
Time frame: after neoadjuvant treatment and surgery, up to approximately 27-30 weeks
Event-free survival (EFS)
EFS is defined as the time from the start of neoadjuvant treatment to any of the following events: progression of disease that precludes surgery, local or distant recurrence, second primary malignancy (breast or other cancers) or death due to any cause
Time frame: Up to approximately 60 months
Overall survival (OS)
OS is defined as the time from starting neoadjuvant treatment until death due to any cause
Time frame: Up to approximately 60 months
Identification of biomarkers to predict clinical outcomes (pCR at definitive surgery, EFS, OS).
The clinical data (pCR at definitive surgery, EFS, OS) will be integrated with the results from the multiomics platform and multivariate predictive models of response to neoadjuvant chemotherapy (NACT) + immune checkpoint inhibitor (ICI) will be explored. Precisely, the multiomics platform will analyze: 1. RNA-Sequencing of the initial tumor and residual disease (if present) 2. microbiome analysis of the saliva and feces, 3. circulating tumor DNA (ctDNA) analysis (targeted gene panel and shallow WGS), 4. Tissue immune phenotyping, 5. T-cell receptor beta (TCR-β) repertoire sequencing and analysis using ImmunoSeq hsTCRβ kit and immunoSEQ, 6. Breast MRI imaging (before and after NACT), Multiple algorithms including Multiple Kernel Learning, Multi-Omics Factor Analysis (MOFA) and Method for the Functional Integration of Spatial and Temporal Omics data (MEFISTO) will then be used to look for an integrative predictive algorithm that incorporates multi-parameter inputs.
Time frame: After all data are analyzed, up to approximately 60 months
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