Breast Cancer Detection, Breast Cancer - Ductal Carcinoma in Situ (DCIS), Breast Cancer (Early Breast Cancer), Breast Cancer Early Stage Breast Cancer (Stage 1-3), Breast Cancer Female, Breast Cancer - Female, Breast Cancer - Infiltrating Ductal Carcinoma, Breast Cancer With Low to Intermediate HER2 Expression
Conditions
Keywords
Breast cancer, Detection, Liquid biopsy, miRNAs
Brief summary
Cancer continues to be one of the most significant public health issues worldwide. Thanks to early detection, the mortality rate of certain types of cancer has decreased significantly. However, the lack of accessible, low-cost, non-invasive, non-toxic, and easy-to-implement diagnostic methods results in late diagnoses, leading to 1 in every 6 people dying from cancer today. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and are found both inside cells and in bodily fluids such as blood and urine. Several studies have demonstrated their role in human diseases, especially cancer, where tumors release miRNAs into the bloodstream that can be used as biomarkers for early detection. The research and development team at Oncoliq SAS identified a panel of miRNAs associated with breast cancer, with a detection performance of 82% sensitivity and 83% specificity, validated in exploratory and preliminary confirmatory studies. These results led to the filing of a patent based on liquid biopsy technology. The objective of this protocol is to establish a panel of miRNAs for the early detection of breast cancer using samples from breast cancer patients and a cancer-free control group. Validation of the miRNAs will be carried out through RT-qPCR. This stage constitutes the analytical validation of the biomarkers, with the goal of developing an algorithm capable of classifying individuals with and without breast cancer. In future stages, a pilot clinical trial is planned to evaluate test implementation and clinical validation.
Interventions
OTHERPeripheral blood draw
Collection of a blood sample for plasma isolation and miRNA analysis.
Sponsors
Oncoliq US Inc
Study design
Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
40 Years to 70 Years
Healthy volunteers
Yes
Inclusion criteria
Group 1 - Breast Cancer: Age between 40 and 70 years Diagnosis of breast cancer at any stage No prior surgical treatment No prior antineoplastic treatment Pathology report available at the time of enrollment Signed informed consent Group 2 - No Cancer (Control): Age between 50 and 70 years No diagnosis or personal history of any type of cancer Digital mammography and breast ultrasound showing no breast pathology (BI-RADS 1 or 2) Signed informed consent
Exclusion criteria
Refusal to sign the informed consent Communication issues that hinder understanding (hearing loss, blindness, intellectual disability, or dementia) Venipuncture for blood collection impracticable or posing a risk Personal history of previous cancer
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Enrollment of 300 Participants | October to December 2025 | Successful recruitment and enrollment of a total of 300 eligible participants across both study groups within the planned recruitment period. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Development of a Machine Learning Classification Algorithm | December 2025 to March 2026 | Creation and validation of a machine learning model capable of distinguishing between individuals with breast cancer and cancer-free controls based on blood-derived biomarkers. |
Countries
Argentina
Contacts
Primary ContactAdriana De Siervi, PhD in Molecular Biology
Backup ContactCamila Zaslavsky, Pharmacist
Outcome results
None listed