Recruiting

Mechanisms of Response and Resistance to Innovative Treatments in Patients With Locally Advanced or Metastatic Breast Cancer

Ample evidence has highlighted the significant clinical benefit of novel therapies for many patients with advanced breast cancer (aBC). The use of CDK inhibitors, antibody-drug conjugates (ADCs), immune checkpoint inhibitors (ICIs), and PARP inhibitors as first-line or subsequent treatments has improved progression-free survival (PFS) rates compared to conventional therapies. In selected cases, these treatments have also increased overall survival (OS), reshaping the therapeutic landscape for advanced breast…

ClinicalTrials.gov IDNCT07066917
PhaseNot Applicable
Enrollment150
SponsorHellenic Cooperative Oncology Group
Age18 Years and older
SexFEMALE
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Conditions studied

Metastatic Breast Cancer

About this study

Ample evidence has highlighted the significant clinical benefit of novel therapies for many patients with advanced breast cancer (aBC). The use of CDK inhibitors, antibody-drug conjugates (ADCs), immune checkpoint inhibitors (ICIs), and PARP inhibitors as first-line or subsequent treatments has improved progression-free survival (PFS) rates compared to conventional therapies. In selected cases, these treatments have also increased overall survival (OS), reshaping the therapeutic landscape for advanced breast cancer. However, several key questions remain unanswered. For example, what should be the first-line treatment when multiple effective options are available? Determining the optimal sequence of drugs in successive lines of therapy is another major challenge. Furthermore, the development of resistance to treatment and the occurrence of severe adverse events that may lead to early discontinuation or fatal outcomes are pressing concerns. That said, identifying robust predictive biomarkers of response or resistance is crucial for ensuring that patients receive the most effective treatment while avoiding unnecessary exposure to therapies that could cause harm without benefit. Additionally, when multiple effective options exist, selecting the optimal treatment algorithm for each patient based on clinical, pathological, and molecular biomarkers is essential. We herein, aim at employing high throughput methodologies, such as Whole Exome Sequencing, circulating tumour DNA (ctDNA) analysis, digital pathology and radiomics analyses, as well as real-world data obtained both from patients records for the training of a ML-based algorithm that can predict response or resistance to a specific treatment, based on the genetic make-up of the patient and the molecular profile of the tumour.

Primary outcomes

Eligibility information

Inclusion Criteria: * Eligible patients will be 18 years of age and older * Histologically confirmed, advanced breast cancer. * Diagnosis of i) hormone receptor positive and/or ii) HER2-positive or -low or iii) triple negative breast cancer (TNBC). * Patients will be included in the analysis after receiving at least one treatment cycle. Exclusion Criteria: * Diagnosis of early breast cancer at time of enrollment * Unwillingness to provide informed consent * Unwillingness to provide biological specimen * Lack of comprehensive clinical data

Study locations

Before you participate: Varda Clinical is an independent discovery tool, not the study sponsor or a medical provider. Eligibility can only be determined by the official study team. Discuss potential risks and benefits with a qualified healthcare professional.

Source: ClinicalTrials.gov. Record last refreshed by Varda Clinical: 2026-10-20.