Breast Cancer Liquid Biopsy Stratification
Breast Cancer Liquid Biopsy Stratification
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.
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.
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.