Image analysis of prostate cancer tissue biomarkers
Författare
Summary, in Swedish
Popular Abstract in English
Prostate cancer is one of the most common cancers in the world and the second most
common in men. The western world has the highest incidence rates. The causes of
prostate cancer are not yet clear, however a number of risk factors have been
identified such as familial history, ethnicity, diet and genetic events. Prostate cancer
affects primarily elderly men with the majority of the cases happening above 65
years of age. If caught at an early stage, prostate cancer is curable by removal of the
whole prostate whereas advanced or recurrent disease is lethal and only palliative
methods are available for patients.
Nowadays the tools to diagnose the disease include PSA blood test and a rectal
examination conducted by a pathologist to detect suspicious lumps. PSA is a protein
produced by the prostate; when its amount goes up beyond a certain level, it may
indicate cancer or other pathological conditions that are not life threatening. The
only way to be sure that a patient harbours a tumour in the prostate, is to perform a
biopsy (generally from multiple areas at once) and analyse it using a microscope.
The problem with blood PSA test is that it unfortunately detects many false
positives. This can expose the patient to unnecessary treatment and side effects.
The biopsy is used not only to diagnose, but also to assess the potential
aggressiveness of the disease by looking at the architecture of the tumour lesions
and assigning the so-called “Gleason grade”. The Gleason grade is a prognostic tool,
meaning that it is able to predict, to a certain extent, the development of the disease
and the response to treatments.
In order to improve both diagnosis and prognosis, we need more reliable markers.
A class of such markers is represented by proteins present in the prostatic tissue.
Traditionally the way to look at them is by using a normal light microscope,
however, this technique is slow and prone to errors and inconsistencies.
In this thesis we investigated the role of ERG, TATI, PSA and AR proteins in
prostate cancer by using novel methodologies based on Time Resolved
Fluorescence Imaging, digital imaging and automated image analysis.
In paper I we analysed the expression of ERG and TATI in prostate cancer from
4177 patients with a localized disease. We observed that the two proteins were
mutually exclusive, as cancer cells that expressed one, did not express the other.
This finding is very important because confirms the heterogeneity of prostate cancer
66
and identifies different families of cancer cells. As a result, the research could focus
on targeted therapies and personalized treatments.
In paper II, III and IV we introduced the use of image analysis to study tissue
biomarkers. In paper II and III we develop a system for automatic analysis of PSA
and AR in tissue sections employing mathematical algorithms for alignment of
images, recognition of specific areas of interest within the tissue, and quantification
of the markers in those areas. To quantify the markers, we used a novel fluorescence
technique that has several advantages over other existing methods. Moreover the
use of computerized image analysis allows for consistent and reproducible
assessment of tissue sections. Our methods allowed us to observe some interesting
expression patterns of the proteins in different clusters of tumour cells and in normal
tissue. This kind of differential expression would need to be analysed further to
uncover some aspects of the disease. Finally in paper IV we developed an algorithm
for automated Gleason grading, which is a system that resembles the pathologist
analysis. The system was able to recognize with high accuracy the different Gleason
grades and it represents a promising supporting tool for aiding pathologists’ work
and possibly increasing the accuracy of prognosis.
Prostate cancer is one of the most common cancers in the world and the second most
common in men. The western world has the highest incidence rates. The causes of
prostate cancer are not yet clear, however a number of risk factors have been
identified such as familial history, ethnicity, diet and genetic events. Prostate cancer
affects primarily elderly men with the majority of the cases happening above 65
years of age. If caught at an early stage, prostate cancer is curable by removal of the
whole prostate whereas advanced or recurrent disease is lethal and only palliative
methods are available for patients.
Nowadays the tools to diagnose the disease include PSA blood test and a rectal
examination conducted by a pathologist to detect suspicious lumps. PSA is a protein
produced by the prostate; when its amount goes up beyond a certain level, it may
indicate cancer or other pathological conditions that are not life threatening. The
only way to be sure that a patient harbours a tumour in the prostate, is to perform a
biopsy (generally from multiple areas at once) and analyse it using a microscope.
The problem with blood PSA test is that it unfortunately detects many false
positives. This can expose the patient to unnecessary treatment and side effects.
The biopsy is used not only to diagnose, but also to assess the potential
aggressiveness of the disease by looking at the architecture of the tumour lesions
and assigning the so-called “Gleason grade”. The Gleason grade is a prognostic tool,
meaning that it is able to predict, to a certain extent, the development of the disease
and the response to treatments.
In order to improve both diagnosis and prognosis, we need more reliable markers.
A class of such markers is represented by proteins present in the prostatic tissue.
Traditionally the way to look at them is by using a normal light microscope,
however, this technique is slow and prone to errors and inconsistencies.
In this thesis we investigated the role of ERG, TATI, PSA and AR proteins in
prostate cancer by using novel methodologies based on Time Resolved
Fluorescence Imaging, digital imaging and automated image analysis.
In paper I we analysed the expression of ERG and TATI in prostate cancer from
4177 patients with a localized disease. We observed that the two proteins were
mutually exclusive, as cancer cells that expressed one, did not express the other.
This finding is very important because confirms the heterogeneity of prostate cancer
66
and identifies different families of cancer cells. As a result, the research could focus
on targeted therapies and personalized treatments.
In paper II, III and IV we introduced the use of image analysis to study tissue
biomarkers. In paper II and III we develop a system for automatic analysis of PSA
and AR in tissue sections employing mathematical algorithms for alignment of
images, recognition of specific areas of interest within the tissue, and quantification
of the markers in those areas. To quantify the markers, we used a novel fluorescence
technique that has several advantages over other existing methods. Moreover the
use of computerized image analysis allows for consistent and reproducible
assessment of tissue sections. Our methods allowed us to observe some interesting
expression patterns of the proteins in different clusters of tumour cells and in normal
tissue. This kind of differential expression would need to be analysed further to
uncover some aspects of the disease. Finally in paper IV we developed an algorithm
for automated Gleason grading, which is a system that resembles the pathologist
analysis. The system was able to recognize with high accuracy the different Gleason
grades and it represents a promising supporting tool for aiding pathologists’ work
and possibly increasing the accuracy of prognosis.
Avdelning/ar
- Urologisk cancerforskning, Malmö
- BioCARE: Biomarkers in Cancer Medicine improving Health Care, Education and Innovation
Publiceringsår
2015
Språk
Engelska
Publikation/Tidskrift/Serie
Lund University Faculty of Medicine Doctoral Dissertation Series
Volym
2015:65
Fulltext
Dokumenttyp
Doktorsavhandling
Förlag
Division of Urological Cancers
Ämne
- Urology and Nephrology
- Cancer and Oncology
Nyckelord
- prostate cancer
- image analysis
- Time Resolved Fluorescence
- automated Gleason
- PSA
- AR
- fusion gene
- TMAs
Status
Published
Forskningsgrupp
- Urological cancer, Malmö
ISBN/ISSN/Övrigt
- ISSN: 1652-8220
- ISBN: 978-91-7619-144-6
Försvarsdatum
28 maj 2015
Försvarstid
13:00
Försvarsplats
Lecture Hall, Pathology building, Jan Waldenströms gata 59, Malmö
Opponent
- Johan Lundin (MD, PhD)