Breast Cancer Liquid Biopsy Stratification (BALIBISTRA)

October 7, 2022 updated by: Medical University of Graz
Breast cancer is the most common cancer in Austrian women. Estimation of prognosis and treatment strategies is increasingly being dependent on stratification of tumors into different entities or classes. Currently, clinical routine stratification of tumors is mostly based on hormone receptor, HER2 status, and estimation of proliferation. However, a more robust and objective classification of tumors can be achieved by elucidation of further biological properties, which is also of increasing significance, as novel anticancer therapies are based on biological mechanisms. Consequently, available information from molecular analyses is increasingly being implemented in routine diagnostic assays with the aim to improve stratification for optimal treatment selection. To date the most extensive molecular-based taxonomy of breast cancer has been achieved by a classification based on combining gene expression and somatic copy number alterations (SCNAs), referred to as integrative clusters. Tissue biopsies are the current gold standard to attain such a classification. However, they can often be difficult to obtain in the metastatic setting and are subject to sampling bias due to intratumor heterogeneity. "Liquid biopsies" are, among other analytes, based on the analysis of cell-free DNA (cfDNA) which contains circulating tumor DNA (ctDNA), i.e. DNA fragments shed from normal and tumor cells into the blood, in patients with cancer. cfDNA can be obtained minimally invasive with a blood draw, allows for the "real time" analysis of tumor DNA from the circulation, and blood samples can be repeated at any time point, which is especially important for monitoring response to therapy. The investigator's group has extensive expertise in the analysis of cfDNA and has developed a plethora of approaches for ctDNA analysis. Recently, the investigators have developed a new approach, which relates to nucleosome positions and gene expression. cfDNA fragments have been associated with the release of DNA from apoptotic cells after enzymatic processing and hence consist mainly of mono-nucleosomal DNA. By performing whole-genome sequencing of cfDNA the investigators could demonstrate that at transcriptional start sites, the nucleosome occupancy results in different read-depth coverage patterns in expressed and silent genes. By employing machine learning for gene classification, the investigators were able to classify genes in cells releasing their DNA into the circulation as expressed. The main hypothesis of the project is that integrative breast cancer clusters can be established from directly blood without the need for an invasive tissue biopsy. Hence, the study aims include refining stratification of patients for an improved selection of treatment strategies. Furthermore, the investigators will obtain novel insights into the biology of metastatic breast cancer, so that this project will have important implications for patients, clinical oncologists, pathologists, pharmacologists, and all basic researchers interested in cancer.

Study Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

Detailed Description

The investigators collected 340 plasma samples from 144 clinically annotated patients with detailed clinical data. All plasma samples were already analyzed by plasma-Seq, an approach, which measures copy number from sequence read depth, for a first evaluation of somatic copy number alterations (SCNAs). As this project represents a feasibility study, the investigators want to evaluate to what extend cis-acting alterations can be determined, i.e. establish the corresponding gene expression changes via nucleosome position mapping as previously published by our group. The results will be corroborated by analyses of the corresponding primary tumor by SCNA-seq and RNA-seq.

From the 340 plasma samples the investigators selected 59 as representative for being either luminal (i.e. those with amplifications at 17q23, 11q13/q14, 8p12, 8q, and gains of 16p and 1q; n=25), basal (i.e. gains of 8q, 10p, 12p and various amplifications occurring due to the high-genomic instability; n=25), and ERBB2/HER2 (i.e. high-level amplification on 17q, centered and including the HER2 gene; n=9). These samples will be sequenced with high coverage (70x) so that both mutations and nucleosome positions can be extracted from the obtained sequences.

Study Type

Observational

Enrollment (Anticipated)

59

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Graz, Austria, 8010
        • Medical University of Graz

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 99 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

Female

Sampling Method

Probability Sample

Study Population

The study includes women with proven histological diagnosis of breast cancer and appropriate clinical data.

Participants were recruited at the Medical University Hospital of Graz.

Description

Inclusion Criteria:

Histological diagnosis of breast cancer, availability of primary tumor tissue and plasma DNA with a high ctDNA content.

Exclusion Criteria:

Patient rejects the participation.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Evaluating as proof-of-concept the ability to stratify patients solely based on a detailed plasma DNA analysis
Time Frame: Three years
Clinico-pathological characteristics including prior and subsequent therapies were recorded for each patient. For each patient a standard classification into luminal, basal, ERBB2/HER2 was conducted and is available.
Three years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Michael R Speicher, MD, Medical University of Graz

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 1, 2018

Primary Completion (Anticipated)

October 1, 2023

Study Completion (Anticipated)

October 1, 2023

Study Registration Dates

First Submitted

June 18, 2019

First Submitted That Met QC Criteria

June 18, 2019

First Posted (Actual)

June 20, 2019

Study Record Updates

Last Update Posted (Actual)

October 10, 2022

Last Update Submitted That Met QC Criteria

October 7, 2022

Last Verified

October 1, 2022

More Information

Terms related to this study

Other Study ID Numbers

  • BreastctDNA01

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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