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Metastatic Breast Cancer: Biomolecular Characterization and Targeted Therapy

Kimbung, Siker LU (2014) In Lund University, Faculty of Medicine Doctoral Dissertation Series 2014:70.
Abstract (Swedish)
Popular Abstract in English

Every year globally, an estimated 1.7 million women are diagnosed with breast cancer, while over half a million are killed by this disease. The principal cause of death is metastasis, which is the spreading of the cancer cells from the breast to other vital organs like the brain, liver or lungs, resulting in organ failure and subsequently death. Even though the past decades have seen significant progress in the management of patients with primary breast cancer, when the tumor is still localized in the breast, the prevention and treatment of metastases is however lagging behind. Many women still get disseminated disease, sometimes decades after successful surgical removal and treatment of the... (More)
Popular Abstract in English

Every year globally, an estimated 1.7 million women are diagnosed with breast cancer, while over half a million are killed by this disease. The principal cause of death is metastasis, which is the spreading of the cancer cells from the breast to other vital organs like the brain, liver or lungs, resulting in organ failure and subsequently death. Even though the past decades have seen significant progress in the management of patients with primary breast cancer, when the tumor is still localized in the breast, the prevention and treatment of metastases is however lagging behind. Many women still get disseminated disease, sometimes decades after successful surgical removal and treatment of the primary tumor. Unfortunately, a metastasis diagnosis is conceived to be a “death sentence” by many people since metastatic disease is incurable by current medical interventions.

Huge efforts have been made by researchers and oncologists to characterize the properties of a breast cancer that makes it spread and grow in particular vital organs and identify factors that make the cancer cells sensitive or resistant to treatment. The research described in this thesis has primarily aimed to unravel the molecular similarities and differences of breast cancer tumors as they progress from the localized tumors in the breast to deadly metastatic tumors in distant vital organs. In addition, we have investigated a novel treatment option for eradicating a subset of breast cancers presenting with mutations in the BRCA1 gene, which are associated with an inferior outcome and are currently difficult to treat despite the poor prognosis.

In paper I, we investigated the stability of conventional biomarkers (ER, PR and HER2) and molecular subtypes of tumors across tumor progression stages. These biomarkers are used by clinicians to make decisions regarding prognosis and therapeutic management of patients with metastatic breast cancer. This research question is very important because, when a metastasis is diagnosed nowadays, only the biomarker status of the primary tumor is used for decision making, ignoring the possibility that a drift in biomarker expression may have occurred in the metastasis which may modify response to treatment and ultimately, affect the length of survival. We found that, on average, biomarker expression was often conserved between primary tumors and metastases from the same patient. However, more frequently than expected by chance, and in a clinically relevant number of cases, a change in biomarker status occurred and this conversion was shown to affect the length of survival, probably due to lack of response to the treatment received since these biomarkers are also predictors of response to treatments administered. More interestingly, and a novel finding, we observed that the molecular subtype, which is a more accurate estimation of the biological phenotype of a breast cancer compared to only using the single biomarkers like ER, PR and HER2, was more unstable across tumor progression stages. Tumors expressing the single biomarker ER can be stratified into two molecular subtypes; luminal A and luminal B. Luminal B tumors are more aggressive tumors requiring a more intensive and radical treatment approach because of their poor prognosis characteristic. Since all the luminal subtypes express ER, a change from a luminal A to B phenotype will be undetected by analyzing only the biomarker ER. We detected a molecular subtype change which may require a modification of treatment in a significant number of patients. Our results emphasize a need to re-test biomarker expression in metastases to enable better management of patients with metastatic breast cancer.

In paper II, we studied and compared patterns in the global expression of all genes in clinical metastases biopsies collected from different organs. Specifically, we searched for liver metastasis selective genes which could be used as markers for predicting if and when a primary breast cancer will spread. We observed that the global gene expression pattern in metastases was similar to what has been previously described in primary tumors. In addition, by using a combination of different statistical and bioinformatics analyses, we identified a set of 17 liver metastasis selective genes which showed significant potential in predicting time to recurrence after primary tumor diagnosis and treatment. Importantly, this signature could identify patients within the luminal A molecular subtype at risk of developing metastatic disease after shorter intervals following primary tumor diagnosis and treatment. This result is clinically significant because patients with luminal A tumors are often considered to have a good prognosis, yet, they still account for a small but clinically relevant number of patients diagnosed with metastatic disease. Metastasis remains the root cause of cancer related deaths, hence accurate identification of all patients at risk of developing disseminated disease is important.

The goal of paper III was to test the ability of the liver metastasis selective gene, CLDN2, to predict the potential of a primary tumor to spread specifically to the liver. With the exception of the brain, liver metastases are the most lethal type of breast cancer metastases. We showed that high CLDN2 expression in the primary tumor was significantly associated and prognostic of an early liver relapse. This result is important because CLDN2 may serve as a marker to guide surveillance (where to focus screening) of patients after primary tumor diagnosis. It has been reported that early detection of an isolated liver metastasis could lead to more radical therapeutic interventions, which may improve the quality of life and prolong the survival for patients diagnosed with liver metastases, which is relatively short compared to patients with metastases in the bone or lungs.

Finally, in paper IV, our aim was to test the novel combination of two compounds specifically targeting distinct genetic defects found in BRCA1 mutated breast cancer cells. These compounds inhibit two key enzymes; PARP1, which is important for fixing breaks in the DNA, and PI3K, which is important for maintaining cell growth and survival. Our results indicated a superior growth inhibitory and killing effect of the combination compared to each of the single agents. If validated in clinical studies, this therapeutic strategy may greatly benefit patients diagnosed with this deleterious subset of breast cancer.

In summary, the results we present in this thesis shed more light onto the complexity of the process of breast cancer progression and we propose methods of improving prediction of outcome, disease monitoring and treatment, which will facilitate the personalization of therapy for women diagnosed with breast cancer. (Less)
Abstract
Metastasis is a complex process that remains a major challenge in the clinical management of cancer, because most cancer-related deaths are attributed to disseminated disease rather than the primary tumor. Despite the significant advances in the prediction of prognosis, and therapeutic management of primary breast cancers, coupled with the substantial improvement in our understanding of the molecular determinants of metastasis, breast cancer relapse and death rates remain unacceptably high.

The aim of the research presented in this thesis was to characterize the biomolecular heterogeneity of breast cancer across tumor progression stages and to identify novel biomarkers and therapeutic strategies which may improve prognostication... (More)
Metastasis is a complex process that remains a major challenge in the clinical management of cancer, because most cancer-related deaths are attributed to disseminated disease rather than the primary tumor. Despite the significant advances in the prediction of prognosis, and therapeutic management of primary breast cancers, coupled with the substantial improvement in our understanding of the molecular determinants of metastasis, breast cancer relapse and death rates remain unacceptably high.

The aim of the research presented in this thesis was to characterize the biomolecular heterogeneity of breast cancer across tumor progression stages and to identify novel biomarkers and therapeutic strategies which may improve prognostication and personalization of therapy for women diagnosed with metastatic breast cancer.

By analysis of tumor biopsies collected at different stages of disease progression, we showed that, in general, the phenotype of the primary tumor is typically conserved during tumor progression. However, in a clinically relevant number of cases, a phenotypic drift in biomarkers and tumor molecular subtypes occurs longitudinally with disease progression, with a change to a more aggressive phenotype being associated with an inferior clinical outcome. We also uncovered that breast cancer liver metastases are transcriptionally different from metastases in other anatomical sites and identified candidate liver metastasis-selective genes with the potential to specifically predict liver metastatic relapse and more generally, the time to any recurrence in early stage breast cancer. Furthermore, we demonstrated that co-targeting of PARP1 and PI3K may represent an improved and specific treatment strategy for BRCA1 deficient breast cancers.

The results we present continue to emphasize the clinical significance of breast cancer heterogeneity and highlight possible ways to improve the accuracy of predicting prognosis and effectively treating patients with metastatic disease, a step towards achieving the promise of personalized cancer management and overcoming the clinical burden of metastatic breast cancer. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Associate Professor Sørlie, Therese, Department of Genetics, Institute for Cancer Research OUS Radiumhospitalet, Oslo, Norway
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Metastatic breast cancer, biomarker conversion, liver metastasis-selective genes, prognosis, BRCA1, PARP1
in
Lund University, Faculty of Medicine Doctoral Dissertation Series
volume
2014:70
pages
152 pages
publisher
Oncology, MV
defense location
Föreläsningssalen, plan 3, Klinikgatan 5, Lund
defense date
2014-06-12 09:00
ISSN
1652-8220
ISBN
978-91-87651-97-7
language
English
LU publication?
yes
id
a48d72ee-5444-4432-937d-a582e03d6fb8 (old id 4522918)
date added to LUP
2014-08-12 14:17:14
date last changed
2016-09-19 08:44:48
@phdthesis{a48d72ee-5444-4432-937d-a582e03d6fb8,
  abstract     = {Metastasis is a complex process that remains a major challenge in the clinical management of cancer, because most cancer-related deaths are attributed to disseminated disease rather than the primary tumor. Despite the significant advances in the prediction of prognosis, and therapeutic management of primary breast cancers, coupled with the substantial improvement in our understanding of the molecular determinants of metastasis, breast cancer relapse and death rates remain unacceptably high. <br/><br>
The aim of the research presented in this thesis was to characterize the biomolecular heterogeneity of breast cancer across tumor progression stages and to identify novel biomarkers and therapeutic strategies which may improve prognostication and personalization of therapy for women diagnosed with metastatic breast cancer. <br/><br>
By analysis of tumor biopsies collected at different stages of disease progression, we showed that, in general, the phenotype of the primary tumor is typically conserved during tumor progression. However, in a clinically relevant number of cases, a phenotypic drift in biomarkers and tumor molecular subtypes occurs longitudinally with disease progression, with a change to a more aggressive phenotype being associated with an inferior clinical outcome. We also uncovered that breast cancer liver metastases are transcriptionally different from metastases in other anatomical sites and identified candidate liver metastasis-selective genes with the potential to specifically predict liver metastatic relapse and more generally, the time to any recurrence in early stage breast cancer. Furthermore, we demonstrated that co-targeting of PARP1 and PI3K may represent an improved and specific treatment strategy for BRCA1 deficient breast cancers.<br/><br>
The results we present continue to emphasize the clinical significance of breast cancer heterogeneity and highlight possible ways to improve the accuracy of predicting prognosis and effectively treating patients with metastatic disease, a step towards achieving the promise of personalized cancer management and overcoming the clinical burden of metastatic breast cancer.},
  author       = {Kimbung, Siker},
  isbn         = {978-91-87651-97-7},
  issn         = {1652-8220},
  keyword      = {Metastatic breast cancer,biomarker conversion,liver metastasis-selective genes,prognosis,BRCA1,PARP1},
  language     = {eng},
  pages        = {152},
  publisher    = {Oncology, MV},
  school       = {Lund University},
  series       = {Lund University, Faculty of Medicine Doctoral Dissertation Series},
  title        = {Metastatic Breast Cancer: Biomolecular Characterization and Targeted Therapy},
  volume       = {2014:70},
  year         = {2014},
}