Prospective Breast Cancer Biobanking

A. Early detection of systemic relapses in breast cancer.

WP 1. Analysis of primary tumor.

Analysis of primary tumor and metastases (Pathology group). In this work package both DNA and RNA from the primary tumors of 125 high-risk (Luminal-B) patients will be analyzed by next-generation sequencing (NGS). Furthermore, the investigators will also analyze DNA and RNA from the available metastatic lesions (currently material available for 3/8) that have appeared, and will appear during the study period.

MiRNA and mRNA will be profiled using PureLink™ miRNA Isolation Kit (Invitrogen), Dynabeads mRNA direct micro kit (Ambion),) and Ion total RNA-seq kit V2 (Life Technologies) on our Ion Proton NGS instrument. Bioinformatic analyses of paired mRNA and microRNA expression profiles will be used to reveal differentially expressed microRNAs between patients with and without recurrences under treatment. These data will be linked to our previous studies and used to identify target candidates for microRNA analysis in exosomes and TEPs.

In addition, NGS will also be performed on DNA from the primary tumors and metastases to verify DNA mutations especially in ER and other known oncogenes, including those examined in WP3. The DNA sequencing will be performed using the Oncomine Comprehensive Assay. This is an amplicon based approach analyzing hotspot SNVs, indels, and CNVs. These analyses will provide us with a biological understanding and background knowledge for each of the individual tumor, and these datasets can also be compared to the recently published data.

WP 2. Circulating tumor celles (CTC).

Circulating tumor cells (Oncology group) Circulating tumor cells are being enriched from peripheral blood samples by density centrifugation and subsequent immunomagnetic depletion of leucocytes. The oncology group has recently developed and published a new depletion method, termed MINDEC (Multi- marker Immuno- magnetic Negative Depletion Enrichment of CTCs), which has superior recovery and enrichment rates. RNA and DNA are isolated simultaneously from the enriched fraction, to allow CTC detection by both RNA and DNA-based approaches. Specific mRNA markers, with high levels in tumor cells and low levels in normal leukocytes, are being pre-amplified and quantified by real-time PCR as surrogate markers for CTCs. Both epithelial-specific markers and markers related to epithelial mesenchymal transition are part of the marker panel. Until now, the investigatorshave analyzed 170 consecutive blood samples from the larger PBCB cohort, enriched by the MINDEC procedure and found evidence for CTCs in about 20% of the samples (from both low- and high-risk patients), a finding that encourages us to continue this project. The investigators have also analyzed blood samples from 30 healthy female volunteers for comparison. All collected blood samples from 125 high-risk patients will be analyzed (around 575 samples). The presence or level of CTCs in the analyzed samples will later be compared to known prognostic factors, treatment effect and disease outcome.

WP 3. circulating tumor DNA (ctDNA).

Tumor-specific mutations can be utilized as markers for ctDNA because they are not present in normal cells and normal plasma DNA. The oncology group has recently demonstrated the clinical relevance of ctDNA measurements in pancreatic cancer. The investigators will now measure ctDNA levels in plasma samples from high-risk breast cancer patients by targeted next-generation sequencing. The recently released "Oncomine breast cfDNA assay" (Thermo Fisher) will be used to detect mutations in a panel of ten genes that are frequently mutated in breast cancer. The assay is based on molecular barcoding of templates and allows reproducible detection of mutations down to 0,1% control samples. Taking the low concentration of cell free DNA (=cfDNA) in plasma into account (typically 10 ng per ml blood), a sensitivity of 0,1% is considered sufficient. The sequencing will be performed on our Ion Proton NGS instrument (Life Technologies). The pre-operative blood sample and yearly follow-up samples from the 125 high-risk patients will be analyzed in this WP. Blood samples from 30 healthy female volunteers have already been collected and will be analyzed for comparison.

The presence and level of tumor-specific mutations will be analyzed in relation to treatment effect and disease outcome. The mutational profile in the primary tumor biopsy and the plasma samples will be compared in order to reveal potential heterogeneity. In addition, longitudinal changes in the mutation profile of ctDNA will be compared with disease development to potentially shed some light on the biological mechanisms causing treatment resistance or late disease relapses.

WP 4. microRNA (miRNA)

Circulating microRNA from exosomes and TEPs (Pathology group) Total RNA will be isolated from exosomes and TEPs from the blood samples taken before and during treatment. The investigators have recently established methods for isolation of total RNA from exosomes (using exoRNeasy serum Plasma kit (Qiagen) and miRCURY RNA isolation kit (Exiqon)) and TEPs. Using the mentioned protocol, total RNA from exosomes has already been isolated from all the 125 high risk patients first visit/before treatment, additionally from the last blood samples collected will from these patients, total RNA will be isolated from both exosomes and TEPs. Furthermore, microRNA profile will be performed on the isolated RNA using the pipeline and platform already established for our Ion Proton instrument. These profiles will be compared with the bioinformatic analysis of mRNA-miRNA profiles from the primary tumor (WP1) and the samples taken before treatment. MicroRNA that are not present in the tissue sample and/or in the blood sample before treatment, but do appear in blood right before a recurrence appears can then be retrospectively traced in previous blood samples in order to see how sensitive these microRNAs are in predicting treatment resistance. MicroRNA profile from TEPs will be compared to the microRNA profile from exosomes and to the mRNA-miRNA profiles from the primary tumor (WP1, to see if TEPs reflects the tumor and if they have the potential to predict relapse.

WP 5. Metabolomics

Metabolomics is the study of small molecules comprising substrates, intermediates and end products of cellular metabolism, such as amino acids, sugars and small organic acids. The metabolic state of cancer cells is substantially altered compared to normal cells, a fact that can be utilized for diagnostic purposes. Specific metabolic signatures from tumor tissue provide additional information for determination of breast cancer subtypes and prediction of outcome1. For example, increased tumor lactate and glycine levels are related to poor prognosis in patients with estrogen receptor (ER) positive cancer. Metabolomic analyses of primary tumors have also demonstrated predictive value in relation to neoadjuvant treatment of patients with locally advanced disease.

Circulating metabolites have also been shown to provide prognostic information in operable breast cancer and further stratify risk within existing genetically determined risk categories. Importantly, metabolomic alterations may arise directly or indirectly from micrometastatic disease, rather than primary tumor. Recently, the investigators have shown that systemic lactate and pyruvate levels predict inferior outcome in patients with operable ER-positive breast cancers. Tumor-adjacent tissue and immunological responses may also contribute to an altered metabolomic profile. There is also evidence that metabolic profiling can be used for patient monitoring in some cancers, although such evidence is still lacking in breast cancer. Therefore, the investigators intend to investigate whether postoperative monitoring by means of metabolic profiling in blood is useful for early detection of breast cancer recurrence.

WP 6. Integrative molecular monitoring for recurrence detection

New technology has revolutionized the level of biological information that can be obtained from clinical samples, represented by the new "omics" terms genomics, transcriptomics, metabolomics, etc. The availability of such big datasets, even in the public domain, has encouraged the development of integrative methods that can extract vital information from multiple combined data sources. Surprising new connections between omics-datasets have been revealed by such approaches, exemplified by a link between cell-free DNA fragmentation and gene expression46. Accordingly, our knowledge about breast cancer has also been extended by integrative approaches, resulting in a more comprehensive understanding of the disease. The prognostic subclassification of breast cancers has for instance been refined and novel tumor-specific antigens identified. Integrated molecular data have even been shown to have a higher prognostic power than separate molecular levels in breast cancer. Thus, a combined analysis of the genetic (ctDNA), transcriptomic (miRNA) and metabolomic data levels in peripheral blood samples is therefore planned in the current project to maximize their joint biomarker potential in operable breast cancer.

Sample size calculations.

The investigators performed sample size calculations using SPSS Sample Power software. These calculations demonstrated that 125 high-risk patients should be sufficient to give a log rank test power of 80%, when testing the prognostic value of ctDNA/CTC detection before surgery. The sample size calculations were based on the qualified assumption that the average 5-year survival rate in the high-risk group is 90%, whereas it is 75% and 95% in the ctDNA/CTC positive and negative subgroups, respectively. Of the estimated 125 patients, 30 were assumed positive for ctDNA/CTC and 95 negative.

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B. Improve drug monitoring of tamoxifen in breast cancer

About 75% of all breast cancer belong to the luminal subtypes, which express the hormonal receptors Estrogen Receptor and Progesterone Receptor. These patients are treated with the anti estrogenic drugs; tamoxifen and/or aromatase inhibitors. The two most active tamoxifen metabolites are Z-4OHtam and Z-4OHNDtam (Z-endoxifen) have 30-100 times higher affinity for ER than tamoxifen. These metabolites ultimately constitute the blocking effect at the ER-level aiming to eradicate micro metastatic disease and are responsible for the improved survival following the establishment of this adjuvant systemic treatment. Direct measurement of these metabolites bypasses all disturbances from the diversity of CYP2D6 activity i.e. alternative metabolic pathways, adherence to the drug and inhibiting drug interactions. Our novel LC / MS-MS methodology takes into account all of the above-mentioned variables and provides a functional read-out report of the serum level of the active tamoxifen metabolites in the individual patient. This method can also distinguish between the inactive and active isomers of Endoxifen and 4-OHtam, which are the most active ER-blocking metabolites of tamoxifen. In collaboration with the Oslo Breast Cancer Research Group, the investigators have recently shown in a retrospective observational study that patients with low serum concentrations of Z-4OHtam \< 3.26 nM or Z-Endoxifen \< 9.00 nM (about 12% of all patients) have significant worse breast cancer specific and total survival than patients with serum concentrations above these thresholds(adjusted HR = 4.3; CI95 = 1.9-13.6) (red curves in Figure 4). Patients with a very high level of these metabolites (approximately 12% of patients) had no breast-specific endpoints Now, the investigators need to validate this discovery in independent patient materials. If validated, this will be of direct clinical benefit for 25% of ER + breast cancer patients planning adj

• Fatigue [Time frame: 0 - 10 years]
• Work life participation [Time frame: 0-3 years]
• Adherence to endocrine treatment [Time frame: 0-10 years]
• Discontinuation of taking endocrine treatment [Time frame: 0-10 years]