Prospective Breast Cancer Biobanking Project
Conditions: Breast Cancer
Sponsor: Helse Stavanger HF

Prospective   Breast Cancer  Biobanking
(PBCB)
Project description - 
Document  date July, 20, 2020 (200720)

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Project description - 200720
Long-term molecular monitoring of 
operable breast cancer patients 
Project description 
Content 
1. Introduction
3 
1.1 Main challenges in breast cancer
3 
1.2 Circulating tumor DNA
3 
1.3 Circulating tumor cells
4 
1.4 Metabolomics
4 
1.5 microRNA in extracellular vesicles
4 
1.6 Integrative molecular monitoring for recurrence detection
5 
2. Impact on Patient Care
5 
3. Objectives and expected results
5 
4. Experimental approach
6 
4.1 Study Design
6 
4.2  Choice of Methodology and Analysis
7 
WP 1: Circulating tumor DNA (ctDNA) 
7 
WP2: Circulating tumor cells 
8 
WP 3: Metabolic analyses 
8 
WP 4: Circulating microRNA from sEVs 
9 
WP 5: DNA sequencing of tissue biopsies 
9 
WP 6: Analyses of Healthy Controls 
9 
WP 7: Integrative analysis 
10 
4.3 Statistical power 
10 
4.4 Organization and Collaboration 
10 
4.5 Communication 
11 
4.6 Plans for Implementation 
12 
5. Expected significance to the field
12 
6. Relevance to the call
12 
7. User Involvement
12 
8. Ethical Considerations
12 
9. References
13 

Project description - 200720 
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Project description - 200720 
1. Introduction
1.1 Main challenges in breast cancer 
Breast cancer remains the most frequent female malignancy in the Western world1. Although the 
incidence still increases, mortality has declined the last two decades due to early detection by 
screening programs and improved adjuvant systemic treatment2. Presently, treatment algorithms 
comprise surgery and radiation combined with adjuvant systemic treatment, which consists of 
chemotherapy, endocrine and targeted biological modalities directed towards potential systemic 
spread of cancer cells3. The clinical decision making process is based upon stratification of patients into 
high-risk and low-risk groups, based on various clinical and tumor-biological markers measured in the 
resected primary tumors4,5. According to this risk assessment, high-risk patients are currently offered 
adjuvant systemic chemotherapy3. Despite this, both early (< 5 years after diagnosis) and late relapses 
(> 5 years after diagnosis) occur, and as a consequence 586 women died from breast cancer in Norway 
in 20172. Thus, there is a need for more accurate diagnostics to guide treatment and more sensitive 
methods for detection of both early and late recurrences. Primary tumor assessment restricted to thin 
tissue sections  do not necessarily reflect the characteristics of residual cancer cells, either because of 
primary tumor heterogeneity or evolutionary changes in residual tumor cells during therapy6. Thus, a 
more comprehensive assessment of the tumor cell phenotype both before treatment, during therapy 
(residual tumor material) and in the subsequent 10-year follow-up window  may enhance 
administration and personalization of systemic treatment. 
Current follow-up during and after treatment is primarily focused on detection of local relapse by 
various imaging methods and by clinical examination3. Unfortunately, high-resolution imaging 
technologies can only detect larger groups of tumor cells (i.e. 1-5 mm) and not minimal residual disease 
or micrometastases7. Thus, it is  a paradox that current practice does not include searches for early 
systemic relapse even though the distant metastatic lesions will kill the patient if they become clinically 
overt. In this respect, there is a need for new and enhanced biomarkers to sensitively monitor the 
disease, with the intention of detecting disease recurrence much earlier. New or prolonged  systemic 
treatment  (i.e. chemotherapy or endocrine therapy)  may be adapted accordingly.  Recent evidence 
suggests that residual tumor cell material can be found in peripheral blood samples and provide the 
requested biomarkers, as described in further detail below (recently reviewed8). 
1.2 Circulating tumor DNA 
Circulating tumor DNA (ctDNA) is cell-free tumor-derived DNA present in the plasma fraction of a 
cancer patient’s blood9. It may originate from apoptotic and necrotic tumor cells in the primary tumor, 
metastases or circulation, as well as being directly released from viable tumor cells10. Tumor-specific 
mutations have been utilized to distinguish ctDNA from other circulating DNA11. Furthermore, 
substantial evidence supports the idea that ctDNA detection may provide therapeutically relevant, 
predictive and prognostic information in breast cancer12,13. It has also been shown that mutation 
tracking in serial blood samples from patients with early breast cancer results in increased sensitivity 
for detection of systemic relapse, with a median lead-time of 8 months over radiological imaging13. In 
a recent report,  the same group even demonstrated a median lead time of 10.7 months for ctDNA-
based detection of recurrence in an enlarged cohort14. A potential for monitoring of treatment 
response during chemotherapy has also been demonstrated12.  
Further, striking genetic disparities between primary tumor, metastases and disseminated tumor cells 
for the same patients have been reported for several solid cancers15. This further strengthens the use 
of ctDNA analysis as it is expected that the ctDNA pool will reflect the total tumor burden in a cancer 
patient and consequently contain DNA from all tumor subclones. Accordingly, ctDNA analysis is a non-
invasive and more exhaustive alternative to metastatic tissue biopsies for mutational analysis in breast 
cancer16, that can also be feasible for serial sampling in disease monitoring and tumor evolution 

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Project description -200720 
studies. Moreover, ctDNA assessment is a central part of the recently published CancerSeek 
technology for early detection of solid cancers17. 
1.3 Circulating tumor cells 
Circulating tumor cells (CTCs) are tumor cells that have detached from the primary tumor or 
metastases either by passive tumor cell shedding, or by an active mechanism involving the epithelial-
to-mesenchymal transition (EMT)18. EMT is presumed to be required for invasion and metastatic 
dissemination as the tumor cells acquire mesenchymal features during this process, resulting in 
increased motility, invasiveness and resistance to apoptosis19. Due to the very low frequency of CTCs 
in blood (1 CTC per billion blood cells), it is technically challenging to identify and distinguish them from 
normal epithelial cells. Detection of CTCs is therefore usually preceded by an enrichment procedure 
based on selection of CTCs expressing a specific surface marker (eg. EpCAM, positive selection) or by 
depletion of blood cells (eg. CD45, negative selection). The most frequently used method for CTC 
detection, the CellSearch system, is dependent upon the presence of Epithelial Cell Adhesion Molecule 
(EpCAM)  on the cell surface. There is evidence that EpCAM is downregulated in a subset of CTCs due 
to the EMT process, encouraging the use of EpCAM-independent enrichment methods in future 
studies26,27. 
Around 15-25% of operable breast cancer patients will develop metastatic disease in their future, and 
there is good evidence that the detection of CTCs, both before and after adjuvant therapy, is of 
prognostic value in breast cancer patients20–23. In 2016, a large pooled analysis demonstrated an 
independent prognostic value of CTC detection in operable breast cancer21. Recently, the presence of 
CTCs two years after chemotherapy was also found to be associated with decreased survival in the 
SUCCESS trial23, while other studies report that CTCs can be detected even 5 years after primary 
diagnosis and are predictive of later relapse24,25.  
1.4 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 cells26,27, 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 outcome28–31. For example, increased 
tumor lactate and glycine levels are related to poor prognosis in patients with estrogen receptor (ER) 
positive cancer32. Metabolomic analyses of primary tumors have also demonstrated predictive value 
in relation to neoadjuvant treatment of patients with locally advanced disease31.  
Circulating metabolites have also been shown to provide prognostic information in operable breast 
cancer33–35 and further stratify risk within existing genetically determined risk categories34. 
Importantly, metabolomic alterations may arise directly or indirectly from micrometastatic disease, 
rather than primary tumor. Recently, we have shown that systemic lactate and pyruvate levels predict 
inferior outcome in patients with operable ER-positive breast cancers36. Tumor-adjacent tissue and 
immunological responses may also contribute to an altered metabolomic profile35. There is also 
evidence that metabolic profiling can be used for patient monitoring in some cancers37, although such 
evidence is still lacking in breast cancer. Therefore, we here intend to investigate whether 
postoperative monitoring by means of metabolic profiling in blood is useful for early detection of 
breast cancer recurrence.     
1.5 microRNA in extracellular vesicles 
microRNAs are small, noncoding RNA molecules that regulate gene expression. They offer great 
potential as biomarkers for cancer detection because of their remarkable stability in blood and 
characteristic expression in different diseases (reviewed in 38). microRNAs have also been found in a 

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Project description - 200720 
subclass of extracellular vesicles now referred to as “small extracellular vesicles”39 (sEV; previously 
called exosomes; reviewed in 40).  There is evidence that sEVs play a role in signaling within and 
between cells and tissues40. Recent data also suggests that sEVs may act as messengers of metastasis, 
and assist in the formation of metastasis by “priming” the metastatic site to create a microenvironment 
that is conducive for cancer cells41. In addition to microRNAs, sEVs have been found to contain RNA, 
lipids, proteins, and metabolites. Analyses of the molecular content show that sEVs derived from tumor 
cells reflect the content of their ancestor cells42. Many studies have  shown that the content and 
especially microRNAs from these sEVs can be transferred and mediate biological effects in recipient 
cells43. Recent studies have also demonstrated different sEV miRNA profiles in peripheral blood from 
patients with breast cancer in different disease stages44, suggesting that sEV miRNAs may be promising 
biomarkers in breast cancer.  
1.6 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 sources45. 
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 disease47. The prognostic subclassification of breast cancers has 
for instance been refined and novel tumor-specific antigens identified47–50. Integrated molecular data 
have even been shown to have a higher prognostic power than separate molecular levels in breast 
cancer39. 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. 
2. Impact on Patient Care
Breast cancer patients have to live with a continuous risk of relapse for the rest of their lives, as 
occurrences can appear more than 20 years after surgery. This cruel fact is a major concern for both 
patients and clinicians. Therefore, endocrine treatment has been extended to last for 10 years after 
surgery. Standard follow-up of breast cancer patients during adjuvant chemotherapy is primarily 
focused on detection of local relapse (i.e. mammogram/ultrasound and clinical examination). 
Paradoxically, there is no search for systemic relapse, even though a poor outcome is unavoidable 
when systemic relapses are clinically manifested. Thus, there is a need for enhanced non-invasive 
surveillance that is cost-effective and easy to perform. Radiological imaging and PET scans have low 
sensitivity for small metastases, are resource-demanding and expensive. By investigating new 
circulating biomarkers in the current project, we want to provide new tools for more sensitive and less 
resource-demanding surveillance that can be offered systematically to all patients with operable 
breast cancer. Earlier detection of systemic relapses may allow for earlier therapeutic interventions  
which may  improve long-term survival and reduce  side effects from unnecessary treatment. Thus, the 
current project provides several potential positive benefits for  breast cancer patients and their next 
of kin.  
3. Objectives and expected results
Primary objective: To develop new diagnostic tools to detect breast cancer recurrences at the earliest 
possible time point, both by analysis of single molecular data sources and by integrative analysis of 
combined data. 
Specific sub-aims (figure 1): 

Project description - 200720 
6 
1.
To identify recurrence markers in peripheral blood by measuring circulating tumor DNA
(ctDNA), circulating tumor cells (CTCs), metabolites and sEV miRNA in peripheral blood
samples obtained every 6 months from patients with operable breast cancer who have
experienced disease recurrence during follow-up (WP1- 4).
2.
To investigate DNA aberrations in biopsies from primary tumor and metastasis (WP5) for
comparison with the blood sample results.
3.
To integrate the combined molecular markers of the blood and tissue samples to further refine
the monitoring potential (WP6).
Our hypotheses will be investigated in a case-control design within the Prospective Breast Cancer 
Biobank (PBCB) project  in the current study and validated in the overall cohort in a later phase when 
the follow-up times are longer. Validation in an independent patient cohort is the ultimate future goal. 
The long-term goal of the project is to implement our new diagnostic tools in an interventional study, 
where recurrence therapy is offered earlier than today, aiming at longer patient survival.
Figure 1: Overview of the project design and aims. 
4. Experimental approach
4.1 Study Design 
The current project application is based on the Prospective Breast Cancer Biobank (PBCB), which is a 
regional collaboration between Haukeland and Stavanger University Hospitals. In the PBCB project 
blood samples are collected from operable breast cancer patients at the time of diagnosis and every 6 

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Project description - 200720 
(Stavanger)/12 (Haukeland) months until disease recurrence or for a total of 11 years. In total, 1253 
patients have been recruited to this biobanking project.  
The current study is designed as a retrospective case-control follow-up study (figure 2), where PBCB  
patients who have already developed systemic metastases (n=50, group A in figure 2) are included as 
cases. These patients will be matched with a control group of patients who are recurrence-free at least 
5 years after surgery (n=50, group B in figure 2). A group of age-matched healthy individuals (n=50, 
group C) will also be included in the analyses for comparison. Having collected 6 blood samples in 
average from the patients in group A means there will be approximately 400 blood samples to analyze. 
Biopsies from the primary tumor biopsies and eventual metastases are available from the Departments 
of Pathology at both hospitals (Stavanger and Bergen).  
The study is organized in six work packages (WP) as described below (figure 1). Our hypothesis is that 
some of our proposed biomarkers will detect recurrence earlier than radiological imaging. If successful, 
the resulting biomarkers will be analyzed in the overall PBCB cohort in a future study and later 
validated in an independent patient cohort. 
Figure 2: Study design. Samples from patients  (A) with recurrent disease will be compared to early 
post-operative samples from patients without evidence of recurrence (B). 
4.2  Choice of Methodology and Analysis 
WP 1: 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 previously demonstrated the clinical relevance 
of ctDNA measurements in pancreatic cancer51, and they will now measure ctDNA levels in plasma 
samples from operable breast cancer patients using targeted deep sequencing.  By this approach the 
plasma sample will be examined for point mutations and copy number aberrations in ten frequently 
mutated genes using the “Oncomine Breast cfDNA Research Assay v2” (Thermo Fisher). The assay is 
based on molecular barcoding of templates and allows reproducible detection of mutations down to 
0,1% allele frequency. We have tested the assay and confirmed this sensitivity with commercial control 
samples. In a pilot study we also detected ctDNA in 5 of 16 patient plasma samples from operable 
patients, with a relative concentration as low as 1% compared to normal cell-free DNA (cfDNA). We 
also detected ctDNA in plasma from 3 of 4 breast cancer patients with recurrent disease. Analyses of 
serial blood samples further showed that mutations found in the primary tumors and metastases are 
present in plasma before and at the time of recurrent disease in these 3 patients. These are very 
encouraging results, and we will confirm variants with low allele frequencies by analysis of more 
plasma cfDNA and a preamplification-based setup for digital droplet PCR (ddPCR) to enable analysis of 
multiple variants in the same cfDNA volume52. The sequencing will be performed on our Ion Proton 
deep sequencing instrument (Thermo Fisher), whereas the ddPCR analysis will be accomplished with 

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Project description -200720 
our QX200 instrument (Bio-Rad). Both technologies have been applied for ctDNA detection in breast 
cancer in previous studies with success12,13. In addition, we will also sequence DNA from white blood 
cells  from the same patients to confirm that the variants we find originate from tumor cells and not 
from white blood cells53. 
In WP1, plasma samples from the included patients will be assessed by this approach, and the 50 
patients in the case group (A, section 4.1) will be compared to the plasma samples from the first 
postoperative sample from group B and the 50 control samples from healthy individuals (group C). 
ctDNA levels significantly above the levels in the control group (if measurable) will be interpreted as 
disease recurrence and the time for ctDNA-based recurrence detection compared to the time of 
radiological detection. The mutational profile from the primary tumor biopsy and the plasma samples 
will also be compared in order to reveal potential tumor heterogeneity. In addition, longitudinal 
changes in the mutation profile of ctDNA will be compared with disease development to shed light on 
the biological mechanisms causing disease relapses. 
WP2: Circulating tumor cells 
In our ongoing PBCB project, we enrichCTCs from peripheral blood samples by density centrifugation 
and subsequent immunomagnetic depletion of leukocytes using a new EpCAM-independent depletion 
strategy, termed MINDEC (Multi- marker Immuno-magnetic Negative Depletion Enrichment of CTCs), 
developed in our lab54. This method has superior recovery and enrichment rates54. Using EpCAM-
independent CTC enrichment, we expect to isolate both mesenchymal- and epithelial-like CTCs, in 
contrast to what is possible with the more conventional CellSearch method.  RNA is then isolated from 
the enriched fraction, to allow for CTC detection using specific mRNA markers being expressed at high 
levels in tumor cells and low levels in normal leukocytes as surrogate markers. Both epithelial-specific 
and markers related to the epithelial-mesenchymal transition are included in the marker panel. The 
mRNA markers are pre-amplified before they are quantified by real-time PCR. Elevated marker levels 
compared to the healthy control group reveal presence of CTCs in the patients’ blood samples. We 
have performed preliminary analyses of blood samples from six patients with recurrent disease and 
compared the data with analysis of blood samples from 163 recurrence-free patients and 30 healthy 
control samples. This analysis was encouraging as it revealed a much higher rate of positive samples 
from the patients with recurrent disease than those without known relapse.  The presence or level of 
CTCs in the analyzed samples will later be related to known prognostic factors, treatment effect and 
disease outcome. 
WP 3: Metabolic analyses 
Blood (serum) samples will be analyzed for metabolites within glycolysis-, citric acid-, amino acid and 
phospholipid metabolism; and detailed analysis of the lipid subfractions in serum will be performed. 
The concentrations of these metabolites will be determined by High Resolution Magnetic Resonance 
Spectroscopy (HR MRS). MRS offers precise identification of metabolites and high throughput, 
automated quantitative analysis. HR MRS will be performed at the MR Core Facility, Dept. of 
Circulation and Medical Imaging, NTNU. The MR Core Facility hosts state-of-the-art spectrometers with 
ultrashielded magnets operating at 600MHz for proton detection. Patient serum will be transported 
to the MR Core Facility at NTNU for analysis. Subsequently, the samples will be refrozen and 
transported back to Stavanger University Hospital (SUH) for future further analyses. Metabolomic 
analyses yield large amounts of data which will be analyzed by specialized multivariate statistical 
methods (chemometrics). Modelling biological pathways will be done by integrating multivariate 
statistics with biological databases (Human Metabolome Database (HMDB), Kyoto Encyclopedia of 
genes and genomes (KEGG)), using available tools (Metaboanalyst, integrated Pathway Analysis (IPA)). 
In the first phase, a more exhaustive statistical analysis will be performed to identify metabolic profiles 
associated with recurrent disease. In a validation phase, these profiles will be sought in all previous 
follow-up samples available from the relapsed patients. 

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Project description - 200720 
WP 4: Circulating microRNA from sEVs 
Total RNA will be isolated from sEVs in plasma samples using the exoRNeasy Serum/Plasma kit 
(Qiagen), which isolates sEVs and sEV-contained RNA in a two-step process. In a first phase, microRNA 
profiling will be performed on the isolated RNA  using PureLink™ miRNA Isolation Kit (Invitrogen) and 
Ion total RNA-seq kit V2 (Thermo Fisher) on our Ion Proton deep sequencing instrument. This 
experimental pipeline has already been established in our lab. MicroRNAs that are differentially 
expressed in the blood samples obtained from 50 patients at the time of recurrence (group A, figure 
2), in comparison to the blood samples from patients in the control arm (group B, figure 2) and the 
normal control (C) group, will be identified. The most promising candidates will be analyzed in blood 
samples taken from patient group A at earlier time points by quantitative reverse transcription PCR 
(RT-qPCR). In a preliminary analysis, sEVs and microRNA have been isolated and analyzed in four 
patients with systemic relapse that were disease-, age- and BMI-matched with non-recurrent patients; 
these patients have been analyzed for eight miRNAs by RT-qPCR (miR-10a, miR-1246, miR-16-5p, miR-
18b, miR-99, miR-451 and miR-505-3p). These preliminary results show that our methods work and 
that these microRNAs are present in sEVs at measurable levels. Differences in expression levels are 
observed as well, but currently no statistics have been applied due to the low number of samples. 
WP 5: DNA sequencing of tissue biopsies 
DNA from the primary tumors of 100 operable breast cancer patients (group A and B, figure 2) will be 
analyzed by deep sequencing using the Oncomine Comprehensive Assay. This is an amplicon-based 
approach, analyzing hotspot SNVs, indels, and CNVs. Furthermore, we will also analyze DNA from the 
50 metastatic lesions, if tissue is available. Identified variants will be compared with the variants found 
in ctDNA. In addition, these analyses will provide us with a biological understanding and background 
knowledge for each of the individual tumors 
WP 6: Analyses of Healthy Controls 
Objective: Collection of blood samples and questionnaires from 200 healthy women who attend 
mammography at Old Stavanger Hospital, for comparison with women who have breast cancer, in 
various research projects. Inclusion takes place on Wednesdays from the morning of. We expect to be 
able to include about 36 participants per inclusion day (6 per hour x 2 employees x 3 hours = 36 
participants) 
Research question: What is the contribution of the cancer disease itself on various analyses in the 
various WPs we have planned for the patients?  
Strategy: To answer this question, we will need blood samples from healthy normal women to 
compare them with the patients. The healthy women should be representative for the age of our 
breast cancer patients. This will be achieved by accrue healthy women attending the mammography 
screening program.  
Inclusion:  
• Will only take place in Stavanger University Hospital.
• Women entering the waiting room are informed about the research project by the host. Receives a
consent form and questionnaire
• Participants sit in waiting rooms and fill out a questionnaire, write during the consent
• Participants submit questionnaires to the host or in the mailbox
• Host refers to blood sampling / PBCB staff retrieves from waiting room
• Mammography personnel pick up mammograms at their convenience (are flexible in order of their
patients).
Blood sampling procedure: 

Project description - 200720 
10 
Performs as ordinary a PBCB (REK 2010/1957) inclusion as possible. 
1) Ask about the date of birth and sign the lab requisition. Ask if they have menstruation, possibly the
first day last while, if they have fasted (both food and medicine).
2) Take blood tests:
a. 1 x serum 9mL
b. 4 x plasma 9mL (one set cold, three kept at room temperature)
c. 1 x plasma 4 mL (whole blood)
d. 1 x CPT
3) Turn the tubes 8 times
4) Label the tubes with labels from fresh controls kit
Analyses: The analyses on the healthy normal women will be the same as in the various WPs in this 
project description. 
WP 7: Integrative analysis 
As a consequence of all our different analyses in WP1-5, large datasets of complementary molecular 
information will be available for combined analyses. As a first step, a multivariable logistic regression 
will be performed using the candidate biomarkers or variables suggested in the different WPs, in 
addition to clinical, histopathological and tumor molecular information from the primary tumor. 
Candidate variables will be analyzed for independent information content and co-variability. This 
analysis will provide a combined risk score with a cutoff for early detection of recurrence in breast 
cancer patients, which may be validated in other biobanks. Furthermore, an exploratory combined 
analysis of the datasets will be performed in order to extract corresponding biological information 
between the different molecular levels. In this way we may discover potentially novel subtypes by 
combining weak yet consistent alteration patterns across data types55. In this analysis, the full datasets 
from each analysis will be combined. Nonlinear classification methods (PLSDA, K-Nearest Neighbors 
classification, Random Forest, Elastic net variable selection) and clustering methods (iCluster, 
intNMF)55,56 will be performed and compared to obtain the best predictive performance for recurrence 
detection and to develop models which describe the biological systems. Finally, we will apply 
supervised machine learning techniques (artificial intelligence) for optimal distinction between 
recurrence and non-recurrence 57. 
4.3 Statistical power 
Calculations demonstrated that 50 cases (patients with recurrence) and 50 controls (patients without 
recurrence) are sufficient to give a matched case-control study power of 0.80. This sample size is based 
on the assumption that the probability of a positive biomarker score is 20% in the control group, with 
an odds ratio of 3.41 for developing recurrence in patients with biomarker positive scores. The 
estimated Sample size calculations were performed using STATA 15.1 software (power mcc command). 
We are also testing whether our new biomarkers can detect disease progression earlier than 
conventional radiological imaging. This can be assessed by a one-sample t test of the time difference 
between ctDNA and imaging compared to the null hypothesis that there is no difference. We obtained 
estimates for the population mean time difference (median 10.7 months) from a recent report 
presenting similar data for 144 patients with  cancer14. The test power of a single-sample t test with a 
population difference of 10.7 months, standard deviation 20 months, and 50 included patients is 96% 
(power.t.test function in R).  
4.4 Organization and Collaboration 
This project is based upon a multiregional collaboration, in which the blood samples are provided  from 
the regional PBCB-biobank headed by Prof. Gunnar Mellgren in Bergen and Prof. Håvard Søiland in 

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Project description - 200720 
Stavanger. The tissues samples are provided by the departments of Pathology from both Stavanger 
and Haukeland University Hospitals. Metabolic analyses are performed at NTNU and bioinformatic 
analyses are performed in close collaboration with the University in Oslo. Breast cancer research at 
SUH is based upon a close collaboration between the three research groups from the Department of 
Breast & Endocrine Surgery, Department of Hematology & Oncology and the Department of Pathology; 
this 
collaboration 
is 
also 
part 
of 
the 
national 
breast 
cancer 
research 
network 
(www.breastcancerresearch.no).  
The applicant, senior researcher and chief engineer Kjersti Tjensvoll (PhD), is a member of the research 
group for Cancer and Medical Physics, led by Dr. Bjørnar Gilje at the Department of Hematology and 
Oncology, SUS. She works in close collaboration with Professor Oddmund Nordgård and together they 
have extensive experience in the field of liquid biopsies. Dr. Tjensvoll will in this project be the principal 
investigator of WP1, and also participate in WP2. Professor Nordgård will be responsible for the 
bioinformatic analysis of WP1 as he has considerable experience in bioinformatics related to cfDNA 
sequencing. Professor Nordgård will also be the PI for WP2, and participate to the computational 
analyses of WP5 and WP6. Kristin Løge Aanestad (MD), who applies for a PhD grant in a separate 
application, will also be responsible for laboratory analyses in WP1 and WP2 (see PhD application). 
Professor Emiel Janssen from the Department of Pathology will be the PI of WP4 and 5 and supervise 
postdoc Marie Austdal in her work with WP3-6. Dr Austdal will also be responsible for WP3 and WP6 
in the current project. She was awarded a postdoc grant from Helse Vest last year, based on the same 
work packages as described here. 
Key collaborators for this project are: Prof. Håvard Søiland (leader of Stavanger Breast Cancer Study 
Group and founder of the PBCB study), head of department Bjørnar Gilje (group leader Research group 
for Cancer and Medical Physics), Prof. Tone Frost Bathen (Leader of the MR Cancer group, Dept. of 
Circulation and Medical Imaging, NTNU). The MR Cancer group is internationally recognized as one of 
the most experienced groups in large scale metabolomics analyses of intact cancer tissue and biofluids. 
Prof. Lars A. Akslen (head of the Center for Cancer Biomarkers, Dept. of Pathology, Haukeland 
University Hospital) will be participating in WP5 and will provide tissue samples from the patients in 
Bergen that will be analysed in WP5. He has extensive experience in biomarker discovery and breast 
cancer research. Prof. Håvard Søiland together with Prof. Gunnar Mellgren at Haukeland University 
Hospital is responsible for the PBCB material. Kristin Jonsdottir, PhD, is constituted leader for Stavanger 
Breast Cancer Study Group and will be co-PI for the miRNA profiling of sEVs (WP3). Tone Lende (MD), 
is head of the Department of Breast and Endocrine Surgery at SUS. Professor Ole Christian Lingjærde 
is the leader of the Research group for biomedical informatics at the UiO. He has been involved in 
several "omics" integration projects. He will be co-supervisor for the postdoc, with special focus on the 
integrated molecular monitoring in WP5. Miram Ragle Aure, PhD, is experienced in miRNA/mRNA 
analyses in breast cancer and integration of 'omics' data. She will be an important collaborator in WP3 
and a future collaborator for validation of our results. 
4.5 Communication 
We plan to communicate the results in peer-reviewed international journals and in a popular form in 
local newspapers and the web sites www.brystkreftforskning.no and www.forskning.no. The following 
tentative scientific titles are planned:  
1.
Relapse detection in operable breast cancer by assessment of circulating tumor DNA
2.
The prognostic relevance of circulating tumor cell detection in pre-operative blood samples
from high-risk patients with operable breast cancer.
3.
Metabolomic monitoring of operable breast cancer patients for recurrence, pre- and post-
operative

Project description - 200720 
12 
4.
Pre- and post-operative vesicular microRNA detection in operable breast cancer in relation to
clinicopathological factors and preliminary survival data
5.
Monitoring of operable breast cancer patients by detection of microRNA from sEVs
6.
Integrated data analysis of  liquid biopsies in monitoring of operable breast cancer patients
4.6 Plans for Implementation 
We want to design new studies that link our circulating biomarkers to clinical interventions, such as 
treatment choices and change of therapy. These studies will be organized through the national breast 
cancer network that we already participate in. If the interventional studies are successful, the next step 
will be to organize systematic surveillance of operated breast cancer patients through the Norwegian 
Breast Cancer Group, based on yearly assessment of the new circulating biomarkers in peripheral 
blood samples. 
5. Expected significance to the field
This project may change the way patients with operable breast cancer are followed after surgery. We 
anticipate a new surveillance scheme consisting of yearly blood samples examined for the new markers 
provided by the current study. We also foresee a change in therapy regimen in response to early 
evidence of relapse. This change of therapeutic regimen will, however, require future studies in which 
the survival benefit of such interventions is demonstrated. 
6. Relevance to the call
This project is a collaboration between three research groups at Stavanger University Hospital (SUH: 
Department of Hematology and Oncology, Department of Pathology and Department of Breast and 
Endocrine Surgery) in addition to professor Gunnar Mellgren (Haukeland University Hospital), who is 
among one of the initiators of the ”Prospective Breast Cancer Biobank” (PBCB). Although the collection 
of samples to this unique biobank is still ongoing, our focus is now on utilization of the samples and a 
large integrated analysis were we will combine data from analysis of both tissue, plasma and serum 
samples stored in the PBCB biobank. This project has the potential to allow for a more extensive follow-
up through personalized monitoring as well as development of more sensitive diagnostic tools for 
detection of systemic disease at an early stage. If successful, new biomarkers may reduce the use of 
resource-demanding radiological imaging. This again will hopefully expedite a change of treatment and 
thereby result in more effective treatment of breast cancer patients leading to an improved long-term 
survival.    
7. User Involvement
The PBCB group at Stavanger University Hospital has an active collaboration with the Regional Breast 
Cancer Society representing all breast cancer patients in our region. Two members of this society are 
included in our regular PBCB meetings as active partners of the user involvement program and have 
provided valuable input into several aspects of the PBCB project. The user representatives have 
contributed to project meetings by presenting their experience with breast cancer diagnostics and 
treatment, and their participation in research projects. They have also evaluated the information 
letters, the questionnaires and our interaction with patients in the PBCB project. 
8. Ethical Considerations
The Prospective Breast Cancer Biobank project is approved by the regional ethical committee (no. 
210.04 and 127.97). PBCB is also approved in REK-Nord (no.2010/1957-4) and HOD (no.2007- 07/758). 
The current biomarker project is approved by REK Vest (2015/2010).  

Project description - 200720 
13 
9. References
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Receptor-Positive Breast Cancer: A Secondary Analysis of a Randomized Clinical Trial. JAMA 
Oncol. 4, 1700–1706 (2018). 
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in Breast Cancer Using NMR Metabolic Profiles. Methods Mol. Biol. Clifton NJ 1711, 167–189
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factors using MR metabolomics. J Proteome Res 9, 972–9 (2010).
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35. Hart, C. D. et al. Serum Metabolomic Profiles Identify ER-Positive Early Breast Cancer Patients at
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cancer through next-generation sequencing. J Clin Invest 121, 3810–3818 (2011).

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15 
48. Curtis, C. et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals
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1 
1. Project Title
Prospective Breast Cancer Biobanking (PBCB) 
– Towards  personalized treatment and monitoring of breast cancer
2. Introduction
Presently, there is no monitoring of early systemic relapse in the follow-up care for breast cancer
patients, despite the knowledge that distant metastatic lesions will eventually kill the patient should
they become clinically overt. Breast cancer is the most frequent and deadly form of cancer among
women worldwide. 1 In 2015, 3324 new cases of breast cancer and 663 deaths due to breast
cancer were registered in Norway. Moreover, there are currently 42 000 breast cancer survivors in
Norway who must cope with various phases of the disease. 2 Disease incidence in Norway is
doubled over the last 50 years3 in line with the pattern that has been observed across most of
the Western world.
In essence, our project portfolio provides new knowledge towards a more personalized 
monitoring and treatment approach. Due to the potential systemic spread of breast cancer cells from 
the primary tumor at the point of diagnosis, current treatment algorithms combine surgery and 
adjuvant systemic treatment such as chemotherapy, endocrine and targeted biological modalities.4 
Unfortunately, despite this multipronged strategy both early and late relapse still occur, leading to 
deaths from breast cancer. Our overarching aim is therefore to improve existing treatment and to  
identify new biomarkers in order to avoid both over- and under-treatment of breast cancer patients 
through detection of robust novel predictive biomarkers for better classification of the tumor itself, 
combined with long-term monitoring of patients in order to increase future survival.5    
Based on drawbacks with our retrospective study from 2006, where lack of available 
serum and reliable clinical data jeopardized the final analyses6 we felt encouraged to start the 
Prospective Breast Cancer Biobank (PBCB) in 2010. This is an ongoing regional collaboration 
between Haukeland University Hospital (HUS) and Stavanger University Hospital (SUS), supported 
by Helse Vest from the start. In our prospective biobank we have, since 2011, consecutively 
recruited o p e r a b l e  breast cancer patients and have now enrolled 1017 patients from the 
catchment area of the two hospitals. A broad panel of tissue samples, liquid biopsies and 
Patient Reported Outcome Measures (PROM) are being collected per operatively, biannually and 
annually respectively. Combined with longitudinal follow-up over 11 years PBCB will create a 
solid base for numerous projects with over 10 000 person-years in various analyses. National and 
international collaborators have given the PBCB-project their scientific recognition. Importantly, 
this collaboration platform is now producing clinically embedded studies, based on key clinical 
issues with an innovative approach.   
The concomitant increment of breast cancer and obesity across Western populations over 
the past 50 years suggest a causal relationship.7 Interaction between the cancer cell and the tumor 
adjacent adipocytes may explain the malicious phenotypical behavior of some tumors through 
paracrine signaling and by inducing inflammation.8 Signal interactions between the adjacent adipose 
tissue and the primary tumor offer possibilities of detecting novel biomarkers that can enable better 
definition of breast cancer sub types. This micro environmental interaction may also be used to 
explore new molecular and metabolic profiling in cancer cells and in liquid biopsies, to establish 
novel biomarkers for an early warning of systemic relapse.  
Tamoxifen is still an extensively used Estrogen Receptor (ER) antagonist and the drug of 
choice in endocrine adjuvant therapy for pre-menopausal patients and, in concert with aromatase 
inhibitors for postmenopausal patients.9  Tamoxifen is a pro-drug which is metabolized by liver 
enzymes to various serum levels of active metabolites with a more than 10-fold inter-individual 
difference. 6,10 As of today, no method has been established to deal with this problem. Controversies 
exist over whether CYP2D6 genotyping or serum levels of active metabolites can be used to 
evaluate ER inhibition and its effect on survival. Recently, our group has showed that metabolite-
guided therapy is a promising approach to avoid under-treatment of breast cancer patients receiving 
Project description - 200720 

2 
long-term endocrine tamoxifen treatment.11 As 75% of all breast tumors are ER positive a 
personalized monitoring of tamoxifen treated patients may result in a significant impact on the 
clinical management of breast cancer patients.  
Moreover, the high discontinuation level (up to 50%) over a 5-year period of tamoxifen 
outside clinical trials12 impacts on survival.13 Sound prospective studies are therefore needed to 
identify risk factors relating to patients’ non-adherence to tamoxifen. Both these tamoxifen related 
topics have become highly relevant due to the recent extension from 5 to 10 year adjuvant 
tamoxifen treatment in clinical guidelines.13 Our findings will contribute to personalize treatment 
and increase the quality in clinical management of these patients. 
As blood represents the biological interface between the primary tumor, the micro 
environment and the distant metastases, they form an ideal medium as “liquid biopsies” to monitor 
the patient`s cancer biology. 14 There is a need for identifying novel circulating biomarkers which 
can enable clinicians to detect and target the relapse with various treatment modalities while it is 
still at a microscopic level — thereby having a better chance to cure the patient.15 Circulating 
biomarkers that are considered promising in this context are circulating tumor cells (CTC), 
circulating tumor DNA (ctDNA) and microRNA (from exosomes and from Tumor Educated 
Platelets (TEPs), which all are stable tumor derived compounds feasible for collection, storage and 
analysis. However, there is a gap in knowledge of how these biomarker groups can be utilized in 
monitoring of patients.  
3. Project Objectives and Goals/Milestones
Project objectives
Primary objective: 
Our primary objective is to continue the unique biobanking of tissue and liquid biopsies from 
women with early breast cancer (Stage I and II) in Western Norway through biannual follow-up in 
an 11-year perspective. This is a large undertaking, which will ultimately establish the basis for 
early detection of systemic relapse in these women and therapeutic drug monitoring of tamoxifen, 
both to improve long term survival of breast cancer patients.     
Secondary objectives: 
To achieve the primary objective, the PBCB project portfolio is organized into 4 work packages 
(WPs) reflecting the secondary objectives.  
1. To continue the prospective accrual and follow up (until 11 years) of 1200 operable breast
cancer patients collecting blood, urine, tissue and PROM data.  (WP-1)
2. To establish the Master Database for PBCB – containing both HUS and SUS data (WP-1).
3. To validate the clinical relevance of direct measurement of active tamoxifen metabolites in
serum (therapeutic drug monitoring (TDM)) in breast cancer patients adjuvantly treated with
tamoxifen (WP-2).
4. To identify risk factors for patients’ low adherence to tamoxifen (WP-2)
5. To establish the necessary biological material for investigation of the clinical relevance of new
circulating tumor biomarkers in plasma for treatment monitoring and early detection of
systemic relapse (WP-3).
6. To validate our results and implement them in clinical trials (WP-4).
Project description - 200720 

3 
4. Feasibility
4.1. Study Design, Choice of Methodology and Analysis 
Population  
At the regional level, approximately 700 new breast cancer patients are diagnosed annually in Helse 
Vest. Of these, more than 500 belong to the catchment area of HUS and SUS (approx. 310 and 
220 respectively). Women diagnosed with operable breast cancer (Stage I and II) at HUS and SUS   
are consecutively invited to participate in the PBCB- project, i.e. to be followed-up prospectively 
for 11 years. One unique population feature is that people who live in this catchment area rarely 
move home or seek care elsewhere. Hence, a near-complete follow-up of patients is possible, 
creating population based cohorts of highly committed patients. To illustrate, the drop-out rate is 
only 6% at SUS. Furthermore, every Norwegian citizen has a unique personal social security 
number allowing coupling of information to various nationwide registries including the Norwegian 
Cancer Registry, the Cause of Death Registry, and Statistics Norway. Therefore, a complete follow 
up of patients is facilitated, creating a robust population-based prospective biobank of women with 
early stage breast cancer.     
Liquid biopsies 
The “liquid biopsy kit” comprises various blood sample tubes (Serum, EDTA plasma, EDTA 
whole blood, PAX-gene and CPT-tubes) and urine (Figure 1). The protocol is relatively time 
consuming as it involves both adequate “patient side” drawing of the various blood samples and 
immediate further processing in the lab. All samples are aliquoted and stored at -80 C. It takes about 
one hour to fulfil the sampling protocol for one patient. Importanly, plasma is sampled at +4C for 
assessment of cytokines and CPT-tubes make DNA  isolation from lymphocytes possible. This has 
made research on chronic fatigue together with Prof. Timothy Lash and prof.  Mylin Torres, 
Atlanta, US (see 4.2.3.) possible. Definitely, the liquid biopsies represent a gold mine for future 
research on breasr cancer.     
Tissues 
At SUS, fresh frozen tumor tissue is obtained from the surgical specimens where the tumor > 10 
mm in diameter. Otherwise, paraffin embedded tumor tissue is available from the diagnostic 
biobanks at both HUS and SUS for all patients. Moreover, we aim to improve the definition of breast 
cancer by studying the role of inflammation at the invasive front of the tumor. 
WP-1.  Population based collection of   liquid biopsies, tissue and PROM-data from 
patients with early stage breast cancer in Western Norway. 
Figure 1.    Sampling protocol in  PBCB  
Project description - 200720 

4 
Recently, this phenomenon has been recognized as one of the new hallmarks of cancer.16 There is 
also a clear link between obesity (BMI above 30kg/m2) and breast cancer incidence.17 It consists of 
two parts and is powered to enroll 75 patients from the PBCB-cohort. We have developed an 
original protocol for tumor and adipose tissue sampling (Figure 2) and a pilot study showed 
excellent yield of RNA from adipocytes included morphological control. Presently, 22 patients are 
enrolled at SUS and accrual is ongoing. This study is also closely linked to WP-3 and will serve as 
bases for a PhD project when all samples are obtained.    
Patient reported outcome measures (PROM) 
To enable identifying patients who are at high risk of discontinue tamoxifen various Patient 
Reported Outcome Measures (PROM) are collected once a year (Fig. 3). The PROM-data are 
obtained at baseline and thereafter yearly from all patients at SUS. The PROM-data consists of 1. 
Basic health and clinical data; 2. HRQoL instruments (EORTC QLQ-C30, EORTC QLQ-BR23 and 
FACT B); 3. Hospital Anxiety and Depression Scale, HAD; 4. Fatigue instruments=Fatigue Impact 
Scale, FIS; Fatigue Severity Scale (FSS) and VAS (visual analog scale)-fatigue; 5. Side effect 
questionnaires; 6. Joint-pain questionnaire; 7. The Mishel Uncertainty in Illness Scale, MUIS; 8. 
Food habits questionnaire and the 9. ROMA III questionnaire for bowel complaints (IBD and IBS).  
Some of the PROMs require a trained study nurse /research coordinator to guide the patient in their 
completion. At HUS, PROM data are obtained annually from 160 patients.  
Sampling schedule in the PBCB protocol 
At SUS the liquid biopsies are biannually and annually at HUS. PROM-data are collected yearly 
at SUS from all patients. At HUS, the PROM data is collected once a year from a cohort of 160 
patients. The total follow-up is 11 years (Figure 3). 
Figure 2. Study design of the “Paracrine-
study”.  
Part 1. Analysis of gene expression to 
identify inflammatory factors involved in 
the paracrine signaling between the 
invasive front  in  12 Luminal A (LumA), 
12 Luminal B (LumB), 12 HER-2 and 12 
Basal Like (BL) breast cancer subtypes 
and the juxta-tumoral  paracrine adipose 
tissue (PAT) (n=48 all together). The 
adipose tissue is sampled from the edge 
of the tumor +  3 biopsies in radial 
gradients  out in the adipose tissue from 
this point.  
Part 2. Characterization of the potential 
correlation between t factors from part 1 
and related to three Body Mass Index 
(BMI) groups with 25 patients in each 
group (n=75 all together) 
NGS; Next generation sequencing
Figure 3. 
Sampling 
schedule in the 
PBCB protocol 
Project description - 200720 

5 
Master Database 
The PBCB biobank has generated a huge amount of clinical-, PROM- and laboratory analysis data 
that needs to be digitalized to be of use in our prospective research. Since the start of PBCB only 
data from a few patients have been plotted. The amount of data to be processed and inserted into the 
database increases weekly. An example: 1,200 patients x 10 PROM x 11 years would create 
132,000 PROM entities. In addition, a large amount of laboratory data from the various WPs will 
soon be available. We have developed a database for PROM-data and started plotting the data.  
Therefore, there is an urgent need for qualified personnel who can continue the handling of this vast 
amount of PROM-data and clinical data. This co-worker will take care of both HUS and SUS data 
in the coming 3-year period. This work will be done under supervision of prof. Jan Terje Kvaløy at 
UiS. 
Work load and organizing of the work force 
Presently, the number of enrolled patients is 1017. The final accrual aim is N=1200, and these 
patients will be followed for a period of 11 years with blood and urine samples obtained every six 
months. Presently, approximately 30% of the patients have completed Year 3 assessments.  When 
fully enrolled, PBCB will create up-to 1200 x 2 = 2400 visits every year, 50-60 patients a week, 10-
12 patients a day. To take care of one patient takes 1 hour. In addition, if a patient experiences 
disease recurrence, a tissue biopsy of the metastases and monthly blood samples (for three months) 
are collected after recurrence discovery. Currently, ten patients have been diagnosed with a 
recurrence with monthly liquid biopsies taken for 6 months.  
The accumulated amount of blood samples that have to be drawn, spinned and stored needs 
dedicated research coordinators/study nurses. Today, the sampling is organized partly from Helse 
Vest (“overførte midler fra 2016”) and by allocation of internal resources. However, this is not 
sufficient to cover the growing workload of sampling and biobanking. Work on the master database 
has commenced but we need human resources for it to be completed and remain up-dated during 
the project period.  
Since PBCB is the largest biobank project on liquid biopsies at SUS (i.e. with 200 000 expected 
aliquots), we are invited to participate in the pilot phase of the new robot based biobank system 
(LabVantage) in Helse Vest and the integration of the new biobank identification/tracking software. 
Moreover, our unique prospective sampling design has attracted attention from Biobank Norway 
offering a collaboration for future projects of mutual interests.   
A.Therapeutic Drug Monitoring 
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 methodology10 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.18 In
collaboration with the Oslo Breast Cancer Research Group (OSBREAC; see 4.2.2), we have
recently shown in a retrospective observational study11 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
WP-2.  Optimizing tamoxifen treatment: Therapeutic Drug Monitoring (TDM) and 
increased adherence 
Project description - 200720 

6 
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 (green curves in Figure 4) . 11 
Now, we 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 adjuvant tamoxifen 
treatment. Such therapeutic drug monitoring (TDM) could identify risk patients with inadequate 
levels of active tamoxifen metabolites. This could lead to a dose increase or switch to an alternative 
endocrine treatment form in these patients. Patients with very high metabolite levels can continue 
on tamoxifen and do not need to switch to an aromatase inhibitor.  
Thus, TDM may turn out to be a paradigmatic shift in endocrine tam treatment of ER-positive 
breast cancer. Importantly, the distance from “bench to bed” in this study is very short due to our 
recent findings, a feasible method and over 30 years of experience with tamoxifen in the clinical 
setting. A revised version of this paper 11 will be submitted to Breast Cancer Research within 
20. Sept. 2017.
Validation Cohort 1 
In an OSBREAC study, Secondary Adjuvant Treatment with Taxanes (SATT), 19 with over 1,000 
patients enrolled, there are 750 patients who have started tamoxifen. 11% of them have recurrence 
or died of breast cancer.  Here we have bone marrow plasma samples from most of the participants 
1 year after this treatment. The number of patients who have taken Tamoxifen and are relevant for 
studying tamoxifen metabolites will be 453 patients from this study. Of these, 11.7% have relapsed 
or died of breast cancer during the observation period (i.e. 60 endpoints). This material constitutes 
an appropriate material validation as there is an adequate number of patients, follow-up time and 
sufficient amount of endpoints. 
Validation Cohort 2 
We have established a collaboration with Prof. Helena Jernström at the University of Lund, 
Sweden. Here, serum samples from adjuvantly tamoxifen treated breast cancer patients are 
available for analysis. The clinical follow-up is completed and the database is established. The 
median follow-up time is 7 years and there are 30 breast cancer related endpoints.   
Power analysis 
If we anticipate 12 % of the patients belong to the low metabolite group, HR = 4.3 , = 0.05 and 
=0.20 the number of needed endpoints = 35. If we pool the OSLO and LUND cohorts (i.e. 90 
endpoints) we will have 80% power to detect a HR of 2.5 or larger.  
B. Adherence to endocrine treatment
The underlying causes of low adherence to endocrine treatment are complex and consist of both
biological (metabolic differences in tam/estradiol levels) and psychosocial factors.20 We aim to
design an algorithm helping clinicians to identify risk factors for low adherence in breast cancer
patients in the PBCB-cohort. This algorithm will identify patients with a high risk of becoming non-
adherent and  make the patient follow-up more focused and individualized. The 10 PROMs collected in
WP-1 (e.g. HRQoL, Depression, uncertainty in Illness, fatigue, side effects) are used to map the
psychosocial factors and side effects. Blood samples from the PBCB biobank will be used to map
the metabolite profile; Furthermore, we have access to the Norwegian Registry of prescription
(Reseptregisteret) to control for use of prescribed drug. In addition to the anti-ER effect, the tam
metabolite profile may also be associated with side effects, specifically to the concentration of tam
and its de-methylated metabolites in serum. 21
WP-3.  Personalized Monitoring of Breast Cancer Patients (PerMoBreCan) novel 
biomarkers for early detection of early systemic relapse 

7 
PBCB serves as a crucial basis for the PerMoBreCan (Personalized Monitoring of Breast Cancer 
Patients) project. Now, we need funding to cover the operating costs for PBCB to serve this project 
portfolio. PerMoBreCan offers original contributions with regard to detection of new biomarkers of 
s y s t e m i c  relapse in early breast cancer. This prospective observational study will characterize 
the tumor-biological line from the primary tumor, and circulating biomarkers from the metastasis. 
This study is powered to enroll 125 high-risk breast cancer patients from the PBCB-cohort at SUS. 
Funding will also be sought through other applications for the PerMoBreCan project.  
Primary tumor analyses 
Genome-wide expression profiles have shown that breast cancer patients could be divided into 
subgroups with different prognosis.22 The PBCB material will be used to isolate and sequence total 
RNA from the primary tumor of high-risk patients by the Ion Proton system for Next Generation 
Sequencing (NGS). The primary tumor samples will be checked for mutations especially in ER and 
other known oncogenes, and characterization of differentially expressed microRNAs and mRNAs 
between patients with and without recurrences under treatment. As proliferation is the most 
important prognostic and predictive in breast cancer it will be assessed by the novel “Ki-67 
Adjusted Mitotic Score” (KAMS) approach. KAMS and centrosome amplification will be 
performed in collaboration with Dr. Aneja at Georgia State University (Atlanta, USA)    (See 4.2.3). 
 Circulating tumor markers 
a) Circulating tumor cells (CTCs) have been shown to provide prognostic information in
metastatic and non-metastatic breast cancer patients, and have been used successfully for
monitoring the effects of chemotherapy in the metastatic setting.23 The PBCB biobank will be used
to enrich circulating tumor cells (CTCs) from peripheral blood. Presently, 133 patients from the
PBCB-cohort have been analyzed. Unpublished data confirm high feasibility of the method in
our cohort.
b) Circulating tumor DNA (ctDNA) is extracellular tumor-derived DNA that originates from
apoptotic and necrotic cells in the primary tumor, metastatic lesions or in circulation (CTCs). 7
ctDNA detection may also provide therapeutically relevant, predictive and prognostic information
in breast cancer.24 The PBCB material will be used to establish a gene panel including 50 gene
regions/genes highly mutated in breast cancer and to perform sequencing of multiple target
genes/gene regions by NGS.
c) MicroRNAs are promising biomarkers for cancer detection and treatment response monitoring in
breast cancer.25,26 The PBCB material will be used to perform microRNA profiling on RNA isolated
from exosomes and Tumor Educated Platelets (TEPs). We will compare tissue microRNA profiles
from tumors sensitive to adjuvant chemotherapy with profiles from resistant metastatic tumors.
III.
Analyses of the metastatic lesion.
In patients who experience relapse, biopsies from the lesions will be taken as well as liquid biopsies
every month to monitor the treatment. All markers obtained from the primary tumor analysis,
CTCs, ctDNAs and microRNAs will be compared with the metastases.
PBCB is part of an inter-regional network on breast cancer (with Oslo University Hospital and 
NTNU, Trondheim).27 This collaboration allows for the necessary validation of all statistically 
relevant biomarkers in large patient cohorts. 
- PBCB Bergen: N=685 patients with annual blood samples.
- OSLO-2: N=2000, a consecutive study collecting tissue/blood from breast cancer patients with
primary operable disease (Stage I and II) in Southeastern Norway.28 This network will provide the
necessary infrastructure for performing interventional studies with randomized controlled design.
Funding for this WP is not included in this application. Long term planning and funding will be
WP-4.  Validation and implementation in clinical trials 
Project description - 200720 

 
8 
sought in due time through collaboration with Oslo Breast Cancer Research Group    (see 4.2.2).    
  
4.2 Organization and Collaboration 
4.2.1 The regional PBCB-platform 
PBCB has expanded during the last 7 years, forming a basis for important regional research based on 
collaboration between Haukeland University Hospital and Stavanger University Hospital. Regional 
meetings are held twice a year, with a research group consisting of 22 members who represent a 
wide spectrum in the field of breast cancer research (breast cancer surgeons, pathologist, oncologist, 
radiologists, endocrinologists, molecular biologists, nurses, cultural studies researcher and lab 
personnel). We have complete organization, procedures, personnel, and policies for recruiting 
patients, collecting biological specimens, data, questionnaires, and a plan for establishing the Master 
Database. Steering committee: Håvard Søiland, Gunnar Mellgren*, Turid Aas, Jørn V. Sagen, 
Jennifer Gjerde, Ernst Lien and Tone Hoel Lende. The PBCB study group has published 68 papers 
over last 5 years (see attachment). *Prof. Mellgren is head of PBCB-Bergen. He has published 
49 papers over the last 5 years (mean IF=6.19). H-index=27. He has supervised 28 master 
students, 13 PhD candidates and 10 postdoctoral fellows.  
 
4.2.2 National collaboration 
A network collaboration South-East Norway (funded by the South-Eastern Norway Regional Health 
Authority) is established (Head of the OSBREAC group is Kristine Kleivi Sahlberg), which 
allows for validation of our data in the OSLO-2 study (WP-4). In addition, we participate in a large 
national neo-adjuvant study with 8 different treatment arms (PETREMAC). In this study we will 
analyze proliferation and microRNA expression (Pathology/SUS) and ctDNA in blood from 
participating patients (Oncology/SUS). Furthermore, collaboration with Prof. Bjørn Naume 
(OSBREAC) secures access to the SATT-study for validation of the tamoxifen metabolites study in 
WP-2. He is also head of the Norwegian Breast Cancer Group (NBCG). Prof. Jan Terje Kvaløy, 
statistician at UiS/SUS, will supervise the process of establishing the master database in PBCB 
(WP-1). 
 
4.2.3 International collaboration 
Prof. Timothy Lash is a highly experienced medical epidemiologist with a great international 
reputation in cancer epidemiology and studies on cancer biomarkers. He is head of Department of 
Epidemiology, Rollins School of Public Health, Emory University, Atlanta GA, USA. His expert 
knowledge in molecular biology and testing of the validity of various cancer biomarkers (PROBE) will 
be important for WP-2 and 3. Prof. Mylin Torres at Emory University, Atlanta, US,  is the director 
of the Winship's Glenn Family Breast Center. Together with Timothy Lash and Mylin Torres we 
have started a project on biological mechanisms for chronic fatigue in breast cancer survivors with a 
basis in the PBCB-patients and the PBCB biobank material.   The PBCP-group also has a long-term 
collaboration with the European Institute of Oncology in Milano, Italy (Dr. Bernardo Bonanni). 
Recently, we have published several papers in collaboration with this group. Dr. Bonanni will also 
contribute in WP-2 and WP-3. The pathology group at SUS currently collaborates with prof. Ritu 
Aneja (Atlanta) on a large cohort of triple negative breast cancer patients, investigating centrosome 
amplification/proliferation/leucocyte infiltration and exosome sequencing in correlation to disease 
outcome (WP-3). Moreover, the PBCB regional study group has a close collaboration with 
Importantly, we have also established a collaboration with Prof. Helena Jernström in University 
of Lund, Sweden where serum samples from tamoxifen treated patients are available to validate the 
findings of active tamoxifen metabolites in WP-2.   
 
4.3 Budget 
The budget plan is a continuation of the former support from Helse Vest in 2010 and 2013. In the 
present application, we apply for 1,500 000 NOK annually for 3 years, a total sum of 4,500 000 

9 
NOK in this 3-year period (See e-application). Importantly, the PBCB project is in urgent need of 
two study nurses/lab personnel divided between HUS and SUS who can handle the growing amount 
samples to be collected from accrued patients and patients in follow-up. Just as urgent is the need of 
a qualified person who can serve both HUS and SUS in order to continue building and maintaining 
the Master Database during this project period under supervision of Prof. Kvaløy. Notably, WP-1 is 
the basis of WP-2 and WP-3 in this application. Therefore, the budget is given priority to this in the 
present application. A separate application will be submitted for the PerMoBreCan study in WP-3.       
4.4. Plan for Milestones and Dissemination
Milestones of the WPs in the present application 
of the PBCB-project portfolio 2017 – 19 
Estimated 
Timeline 
Completion of 1st time visit of 1200 breast cancer patients (WP-1) 
Q4 2019 
Collect liquid biopsies and PROM data from ~1000 patients in follow-up (WP-1) 
Q4 2020 
Building the Master Database in PBCB at SUS and HUS (WP-1) 
Q4 2020 
Finish of tissue collection in 75 patients in the paracrine study (WP-1) 
Q1 2020 
Finish anlysis of PROM- & adhernce data for risk assessment of non-adherence (WP-1) 
Q1 2020 
Analyses of tamoxifen metabolites in the SATT- study /Oslo  (WP-2) 
Q3 2018 
Analyses of tamoxifen metabolites in Lund-material /Sweden  (WP-2) 
Q2 2020 
Isolate microRNA from TEPs in the PBCB material (WP-3) 
Q4 2019 
Dissemination 
Scientific findings will be reported in reputable international peer review journals and presented at 
conferences regionally, nationally and internationally. Results will also be communicated directly to 
user organizations and clinical milieus. The hospital's website (www.sus.no) provides information 
about the biobank for general public. Results will be communicated to the public though social 
media channels (Facebook & Twitter) and through mass media (regional & national newspapers, 
radio & television).  
4.5 Plans for Implementation 
Tamoxifen is an established and cheap drug without any special economical conflict of interests to 
analyze. The LS/MS/MS method for measuring tamoxifen metabolites is established in the core 
facility at University of Bergen and the Hormonlaboratoriet at HUS. The method is accurate, 
feasible and has capacity to analyze tamoxifen metabolites in serum from all breast cancer patients 
in Norway allocated to this treatment. We have established contact with Norwegian Breast Cancer 
Group (NBCG) for evaluation of the results from the validation study in WP-2. Hence, we have all 
the resources and contacts needed for a rapid implementation of therapeutic drug monitoring of 
tamoxifen in Norway. Circulating biomarkers of early systemic relapse can easily be obtained from 
a simple blood sample in the follow-up of the patients. A second adjuvant treatment may then be 
given. Implementation of these results will be performed through internal validation between our 
centers and external validation through our inter-regional/national network on breast cancer. 
Importantly, forthcoming novel treatment options (e.g. immune therapy) will demand novel disease 
markers to meet the requirement for sufficient clinical management of the future breast cancer 
patient. The PBCB-project portfolio represents a bold and highly innovative approach to meet 
this coming need. The innovation potential will be evaluated through the project period and contact 
will be made with Bergen Teknologioverføring (BTO) in Bergen and Validé TTO in Stavanger when 
relevant. 
5. User Involvement
PBCB has an active collaboration with two user representatives from the regional breast cancer
society (Brystkreftforeningen), a breast cancer advocacy group in our region. Both serve as active
partners in the user involvement program (Brukermedvirkning) and take part in our project
meetings. They are both breast cancer survivors and have provided valuable input into several

10 
aspects of the PBCB projects. For the WPs, the end-users will be the future breast cancer patient. 
They will get a more personalized follow-up program and hopefully a much more sophisticated and 
appropriate surveillance and treatment of systemic relapse.  
6. Ethical Considerations
All patients have given written consent to participate in the various projects. PBCB got the main
formal biobank approval (WP-1) in 2010 by REK-Nord #2010/1957). The collection of PROM data
are in REK- Nord #2011/2161. The PerMoBreCan project (WP-2) is approved in REK-Nord
#2015/2010.The paracrine project (WP-3) in REK-Nord #2013/25. The validation and
implementation of validated biomarkers will have to be approved by the regional ethical committee
and the Norwegian Breast Cancer group (NBCG).
7. References 
1. Globocan. Available from: http://globocan.iarc.fr/factsheets/populations/factsheet.asp?uno=900 - WOMEN.
2. Cancer in Norway 2015 . https://www.kreftregisteret.no/Generelt/Publikasjoner/Cancer-in-Norway/cancer-in-norway-2015
3. Cancer Registry of Norway, Cancer in Norway 2015. Available from:
4. www. nbcg.no Norwegian Breast Cancer Group [Cited Aug. 14, 2017].
5. Goldhirsch, A., et al., Annals of Oncology, 2013.
6. Lien, E.A., et al.,  Breast Cancer Res Treat, 2013.
7. Reeves, G.K., et al.,   BMJ, 2007. 335(7630): p. 1134.
8. Wang, Y.Y., et al.,   Cancer Lett, 2012. 324(2): p. 142-51.
9. Mouridsen, H., et al.,  N Engl J Med, 2009. 361(8): p. 766-76.
10. Gjerde, J., et al.,  Breast Cancer Res Treat, 2012. 134(2): p. 693-700.
11. Helland T, et al & Søiland H.. Revison of paper to BCR Sept 2017 
12.Owusu, C., et al.,  Clin Oncol, 2008. 26(4): p. 549-55.
13.Davies, C., et al.,  Lancet, 2013. 381(9869): p. 805-16.
14.Alix-Panabieres, C. and K. Pantel,  Cancer Discov, 2016. 6(5): p. 479-91.
15.Synnestvedt, M., et al.,   2012. 12: p. 616.
16.Hanahan, D. and R.A. Weinberg,  Cell, 2011. 144(5): p. 646-74.
17.Renehan, A.G., et al.,  Lancet, 2008. 371(9612): p. 569-78.
18.Kiyotani, K., et al.,   Drug Metab Pharmacokinet, 2012. 27(1): p. 122-31.
19.Naume B,  et al.   Clinical Oncology 2014;32:p. 3848-57.
20.Hagen, K.B., et al.,  Breast, 2016. 28: p. 100-6.
21.Gallicchio, L., et al.,   Breast Cancer Res Treat, 2004. 85(1): p. 89-97.
22.Sorlie, T., et al.,   Proc Natl Acad Sci U S A, 2001. 98(19): p. 10869-74.
23.Rack, B., et al.,  J Natl Cancer Inst, 2014. 106(5).
24.Garcia-Murillas I et al.   Science translational medicine 2015;7:302ra133.
25.Wang, F., et al.,  Molecules, 2014. 19(5): p. 6282-93.
26.Egeland, N.G., et al.,  J Mol Sci, 2015. 16(10): p. 24243-75.
27.Regional Network for Breast Cancer. 2015. at http://breastcancerresearch.no/.)
28. Aure, M.R., et al.,   Genome Med, 2015. 7(1): p. 21.
Project description - 200720 

Overall research protocol for the study of work life participation 
in Breast Cancer Survivorship 
Background 
Treatment of breast cancer employs all surgery, chemotherapy, radiation therapy and various 
targeted therapy options like antiestrogen and anti HER-2 therapy.These treatment options 
create bothersome side effects both in a short term and long term perspective. Importantly, 
more complex relationships between oncological therapy modalities and subjective health 
complaints in breast cancer patients are recently discovered (1). Fatigue, anxiety and 
depression scores are probably functional read outs of the total treatment burden. The anti 
cancer treatment has also a substantial impact on Quality of Life and social aspects for the 
cancer survivors which extends to work life participation. Sick leave (SL) five years after the 
breast cancer diagnosis is more dependent on social factors than on illness (2). Hence, breast 
cancer hits the women twice; first the disease burden then the sosio-economic worries. Breast 
cancer survivors have almost 3 x higher risk of receiving disability pension (DP) compared to 
cancer –free patients in a retrospective register based study (3). However, this study was 
based on mostly abandoned oncological treatment regimens. 
Aims 
The aim of this study is to identify risk factors for becoming a long term SL, WAA or DP 
receiver by an in-depth qualitative analysis and mixed-method approach by triangulating 
PROM data, clinical/biological data and the NAV-data. Use of NAV-data as endpoints will 
provide valuable information to clinicians and general practitioners who may optimize the 
follow-up also in regards to work-life participation. Hence we have a robust study design to 
identy fisk factors for high SL, WAA and DP rates.  Ultimately, we aim to lower the 
financial expenses breast cancer generates to society. 
Project description - 200720 
Project description - 200720 
Project description - 200720 

Study design / material & methods. 
The study design is an observational study where we will in the present study map the rates 
of and denty fisk factors for high SL, WAA and DP among breast cancer survivors with the 
up-to date treatment schedules.  We will follow a 4-step translational approach: 
1.  We will first conduct an exploratory qualitative study using document analysis of 
health and work life policy in the Norwegian context, combined with empirical data 
from semi- structured interviews and focus group with 20 high risk patients) to be 
analyzed thematically. The theoretical framework for this qualitative project is derived 
from symbolic interactionism in which uncovering and understanding meaning in 
specific contexts is a goal. Since meaningful social and professional interactions are 
important for psychosocial rehabilitation of breast cancer individuals symbolic 
interactionism is an appropriate methodological framework.  This qualitative approach 
will create the bases of the approach in the PROM based and NAV-database oriented 
studies below. 
2. NAV- data
We currently collaborate with vice director Anneline Christine Teigen and senior
consultant Günter Olsborg in NAV-Rogaland and the Mikrodata section at Statistics
Norway (SSB). The aim for this collaboration is gain more knowledge about the use
of social security services among breast cancer patients together with the NAV- 
Rogaland experts and together with SSB use the FD-trygd database to obtain reliable
prospective sociodemographic data on SLs (both short & long term), Work
Assessment Allowance (WAA) (Arbeidsavklaringspenger) and DPs (both time limited
& life long) for each patients in the present PerMoBreCan study.
3.
Patient reported outcome measure (PROM) data is obtained at baseline and thereafter
yearly from all PerMoBreCan patients. The PROM data consists of 1.HRQoL
instruments (EORTC QLQ-C30,EORTC QLQ-BR23 and FACT B), 2.Hospital Anxiety
and Depression Scale, HAD, 3. Fatigue instruments Fatique Impact Scale, FIS;
Fatugue Severity Scale (FSS) and VAS-fatigue, 4.Side effects questionnaires, 5. Joint- 
pain questionnaire, 6. The Mishel Uncertainty in Illness Scale, MUIS; and 7. Food
habits questionnaire and the 8.ROMA III questionnaire of bowel complaints (IBD and
IBS).
Project description - 200720 

4.
Biomarker identification.
All patients attending this study will be screened on circulating biomarkers releated to
fatigue. These biomarkers are on the protein level, genetic expression level and also on the
epigenetic level. Our long-established pleasant cooperation with prof. Roald Omdal at
Stavanger University  Hospital, who is a clinical immuologist and transaltional fatigue
researcher, is committed to conduct these analyses in his research lab.
Collaborations 
In addition to the collaboration with NAV, we have a close collaboration with Prof. Roald 
Omdal who is a clinical immunologist and translational fatigue researcher, and will perform 
the analyses of various biomarkers related to fatigue. Moreover, an important collaboration is 
established with Prof. Elisabeth Severinsson (University College of Southeast Norway) 
and Ass. Prof. Kari Nyheim Solbrække (University of Oslo) to include qualtitative and 
mixed-method designs. Coworkers in the Breast Cancer Surgery group and the Oncology 
group will work together to elaborate on this WP. 
REFS: 
1.Hagen KB, Aas T, Eriksen H, Kvaløy JT, Søiland H, Lind R. Fatigue, anxiety and depression overrule the role
of oncological treatment in predicting self-reported health complaints in women with breast cancer compared to 
healthy controls. The Breast, 2016. In Press. 
2.Torp, Nielsen, Gudbergsson, Fosså & Dahl: Sick leave patterns among 5 year cancer survivors: A registry- 
based retrospective cohort study, Journal of Cancer Survivorship June 2012, doi: 10.1007/s11764-012-0228-8. 
3. Beate Hauglann, Jūratė Šaltytė Benth, Sophie D. Fosså, Alv A. Dahl: A cohort study of permanently reduced
work ability in breast cancer patients. J Cancer Surviv (2012) 6:345–356, DOI 10.1007/s11764-012-0215-0 
Project description - 200720