Tumor heterogeneity and the combined
prognostic value of DNA ploidy and PTEN status in prostate cancer
Karolina Cyll
Institute for Cancer Genetics and Informatics Oslo University Hospital
Oslo, Norway
August, 2019
© Karolina Cyll, 2020
Series of dissertations submitted to the Faculty of Medicine, University of Oslo
ISBN 978-82-8377-758-1
All rights reserved. No part of this publication may be
reproduced or transmitted, in any form or by any means, without permission.
Cover: Hanne Baadsgaard Utigard.
Print production: Reprosentralen, University of Oslo.
III
First and foremost, I would like to thank all of the patients who participated in the projects incorporated in this thesis, and without whom this thesis would not have been possible. I also want to acknowledge the South-Eastern Norway Regional Health Authority for funding this project, and the University of Oslo for admitting me to the PhD program.
I owe my gratitude to my main supervisor, Prof. Håvard E. Greger Danielsen, who was my mentor in the field of cancer research and genomic instability. His knowledge is just as impressive as his ability to successfully lead the institute forward. Thank you for your guidance, patience and encouragement throughout this work. I am also very grateful to my co-supervisor, Dr. Erik Skaaheim Haug, for his excellent cooperation in the research projects, kindness and support and for continuously providing me with clinical data.
I want to thank all my co-authors; this work could not have been completed without your invaluable contributions. In particular, I would like to thank Dr. Andreas Kleppe and Dr. Tarjei Sveinsgjerd Hveem for helping me with statistical analysis of the data. I appreciate your keen eye for detail and the interesting discussions regarding my work and beyond. I have also appreciated the close collaboration with Dr. Ljiljana Vlatkovic. Your dedication and tremendous knowledge of pathology are truly inspiring. I am also grateful to Dr. Birgitte Carlsen and Dr.
Manohar Pradhan for your expertise and for always finding the time to help me despite your busy schedules. I would also like to thank Maria Isaksen, Krishanthi Gunathasan, Jonathan Gullesen, Marte Linjordet, Ingrid Elise Konow Weydahl, Ilyá Kostolomov and Rolf Anders Syvertsen for their excellent technical assistance. I am grateful to Marian Seiergren and Paul Callaghan for making the amazing figures and other visuals used in this work.
Furthermore, I would like to acknowledge all former and present colleagues from the Institute for Cancer Genetics and Informatics for creating a great scientific and social atmosphere. Very special thanks to Marna Lill Kjæreng, not only are you responsible for all of the success in the lab, but you have also been with me through thick and thin. Also, I would like to thank Elin Ersvær for sharing everyday ups and downs and being a great “secretary”. I would further like to thank Dr. Hanne Arenberg Askautrud for continuous support, enthusiasm and for having an open door whenever I was struggling. Thank you Dr. Wanja Kildal and Dr. Trine M. Reine for your
IV
support and assistance in constructively reviewing this manuscript. A very special thank you goes to Anna Kenseth for her editorial and digitalization help, and always finding ways to cheer me up.
On a private note, I want to thank my friends and family, especially Karl and Chelsea, for their constant support, encouragement and patience, and for always believing in me. And please do not worry, you do not have to read this thesis - ever.
Oslo, August 2019 Karolina Cyll
V
Acknowledgements ... III Abbreviations ... VII List of included papers ... IX
Motivation and aims of the study ... 1
Introduction ... 3
Cancer biomarkers ... 4
DNA organization and cell division ... 5
Genomic instability ... 8
Aneuploidy ... 8
Pathways to CIN and aneuploidy ... 9
Cellular responses to aneuploidy ... 9
Tumor heterogeneity ... 10
Anatomy and function of the normal prostate gland ... 11
Prostate cancer ... 12
Epidemiology of prostate cancer ... 13
Risk factors for prostate cancer ... 13
Clinical presentation and diagnostic tools ... 13
Staging and risk stratification... 19
Treatment options ... 22
Molecular alterations and tumor heterogeneity in prostate cancer ... 25
Prognostic biomarkers for prostate cancer ... 27
Patients and methods ... 31
Radical prostatectomy cohort... 31
Active surveillance cohort ... 35
Processing of radical prostatectomy-, biopsy- and TURP specimens ... 36
DNA ploidy analysis by image cytometry ... 38
DNA ploidy analysis on nuclear monolayers ... 42
DNA ploidy analysis on tissue sections ... 44
VI
Immunohistochemistry ... 44
Statistical analyses ... 47
Summary of papers and additional results ... 49
Discussion... 57
Methodological considerations ... 67
Conclusions ... 69
References ... 71
Errata ... 87 Papers I - III
VII
AKT AKT serine/threonine kinase 1
APC/C The anaphase-promoting complex/cyclosome
AR Androgen receptor
AS Active surveillance BCR Biochemical recurrence BRCA2 BRCA2 DNA repair associated
CAPRA Cancer of the Prostate Risk Assessment CAPRA-S CAPRA postsurgical
CENPC Centromere protein C
CI Confidence interval
CIN Chromosomal instability
cT Clinical T stage
DAB 3’3-diaminobenzidine tetrahydrochloride
DDR DNA damage response
DI DNA index
DRE Digital rectal examination EAU European Association of Urology EPE Extraprostatic extension
ERG ETS transcription factor ERG ETS Erythroblast transformation-specific FFPE Formalin-fixed paraffin-embedded FISH Fluorescence in situ hybridization FOXA1 Forkhead box A1
G1 Gap 1
G2 Gap 2
GGG Gleason grade group H&E Hematoxylin and eosin
HR Hazard ratio
HRP Horseradish peroxidase
ICGI Institute of Cancer Genetics and Informatics IHC Immunohistochemistry
IOD Integrated optical density
ISUP International Society of Urological Pathology LNI Lymph node involvement
M-phase Mitotic phase
mpMRI Multiparametric MRI MRI Magnetic resonance imaging MSI Microsatellite instability
VIII NKX3-1 NK3 homeobox 1
NRH Norwegian Radium Hospital NWS Nucleotyping Work Station OUH Oslo University Hospital PI3K Phosphoinositide 3-kinase PSA Prostate-specific antigen PSA-DT PSA doubling time pT Pathological T stage
PTEN Phosphatase and tensin homolog PWS Ploidy Work Station
RAD51 RAD51 recombinase
RB1 RB transcriptional corepressor 1
REK Regional Committees for Medical and Health Research Ethics RP Radical prostatectomy
RT Radiation therapy
SM Surgical margins
S-phase DNA synthesis phase
SPOP Speckle type BTB/POZ protein SVI Seminal vesicle invasion TCGA The Cancer Genome Atlas TFS Treatment-free survival TMA Tissue microarray
TMPRSS2 Transmembrane serine protease 2 TNM Tumor-node-metastasis
TP53 Tumor protein p53
TRUS Transrectal ultrasonography TTR Time to recurrence
TURP Transurethral resection of the prostate WHO World Health Organization
WW Watchful waiting
IX
This work is based on the following three papers referred to in the text by their roman numerals.
Paper I
Karolina Cyll*, Elin Ersvær*, Ljiljana Vlatkovic, Manohar Pradhan, Wanja Kildal, Marte Avranden Kjær, Andreas Kleppe, Tarjei S. Hveem, Birgitte Carlsen, Silje Gil, Sven Löffeler, Erik Skaaheim Haug, HåkonWæhre, Prasanna Sooriakumaran and Håvard E. Danielsen
*These authors contributed equally to this work.
Tumour heterogeneity poses a significant challenge to cancer biomarker research Br J Cancer 2017; 117: 367–75.
Paper II
Karolina Cyll, Andreas Kleppe, Wanja Kildal, Elin Ersvær, Ljiljana Vlatkovic, Manohar Pradhan, Hanne A. Askautrud, Erik Skaaheim Haug,Håkon Wæhre and Håvard E. Danielsen Prognostic value of PTEN and DNA ploidy status in prostate cancer in the context of intratumor heterogeneity
Manuscript
Paper II
Karolina Cyll, Erik Skaaheim Haug, Birgitte Carlsen, Manohar Pradhan, Sven Löffeler, Elin Ersvær, Wanja Kildal, Karin Sebakk, Rolf Anders Syvertsen, Knut Liestøl, Hanne A. Askautrud, Andreas Kleppe andHåvard E. Danielsen
DNA ploidy and PTEN status as biomarkers in active surveillance for low and intermediate risk prostate cancer patients
Manuscript
1
Prostate cancer is the second most frequently diagnosed cancer in men worldwide and it is a significant contributor to cancer-related mortality. Prostate cancer is a heterogeneous and complex disease for which clinical management is challenging. Given its slow growth, in a significant number of patients it will never lead to any harm if left untreated. Others may develop metastasis and die as a consequence of the disease. Although decades of research have improved detection and treatment options, distinguishing indolent from potentially aggressive prostate tumors remains a challenge. This results in substantial overtreatment of patients with potentially harmless cancers, with associated cost and side-effects, but also in undertreatment of patients with aggressive disease.
Prognostic markers that improve prostate cancer risk stratification are urgently needed.
Prognostic biomarkers could serve to optimize active surveillance protocols in terms of patient selection and timing for intervention. Furthermore, they may aid in identifying patients at high risk of recurrence after radical prostatectomy who would benefit from adjuvant treatment.
Although several molecular, tissue-based prognostic biomarkers have been proposed, none of them has yet been incorporated into the clinical decision making. One of the main challenges is the intratumor heterogeneity, giving uneven distribution of a biomarker within a tumor. The intratumor heterogeneity in prostate cancer is largely ignored in biomarker studies.
The main aim of this study was to obtain more knowledge of the extent of intratumor heterogeneityand its effect on tissue-based prognostic biomarkers in prostate cancer. We studied the prognostic value of DNA ploidy and PTEN (phosphatase and tensin homolog) expression, separately and in combination, in multiple tumor samples from each patient. These biomarkers are among the most relevant prognostic markers in prostate cancer. DNA ploidy is a measure of cellular DNA content and PTEN is a tumor suppressor. Alterations in the status of these biomarkers may be indicative of genomic instability, which underlies continuous tumor progression and intratumor heterogeneity.
2
Paper I: “Tumor heterogeneity poses a significant challenge to cancer biomarker research”
x To study the extent of intratumor heterogeneity in radical prostatectomy specimens and biopsy cores from patients included in the active surveillance program using Gleason scoring, DNA ploidy and PTEN expression
x To investigate the consequences of intratumor heterogeneity by comparing the prognostic value of DNA ploidy status assessed in one versus multiple samples
Paper II: “Prognostic value of PTEN and DNA ploidy status in prostate cancer in the context of tumor heterogeneity”
x To investigate the prognostic value of DNA ploidy and PTEN status as single biomarkers ina cohort of prostate cancer patients treated with radical prostatectomy by analyzing multiple samples from each patient
x To determine the prognostic value of a novel biomarker combining estimates of DNA ploidy and PTEN status
Paper III: “DNA ploidy and PTEN status as biomarkers in active surveillance for low and intermediate risk prostate cancer patients”
x To investigate whether the combined DNA ploidy PTEN status could aid in improving decision making for patients enrolled in active surveillance
3
In of 2015, about 8.8 million people died of cancer [1]. Owing to the tremendous advances in our understanding of the disease, millions of cancer patients live longer due to early detection and treatment. However, the number of cancer cases and deaths is expected to increase as the global population is growing and aging [1].
Cancer is characterized by uncontrolled proliferation of abnormal cells that can invade nearby tissues and metastasize to distant organs. Carcinogenesis can be induced by spontaneous errors during cell division, inheritance and exposure to mutagenic environmental factors or viruses [2–
5]. Currently, there are two main types of alterations thought to be involved in cancer development: genetic and epigenetic [6]. Genetic alterations are defined as permanent changes in the DNA sequence, and can occur at several different levels in the genome [7]. Epigenetic alterations represent heritable changes that alter the gene expression without changing the DNA sequence [8]. Either of these alterations can be classified according to its consequences for cancer development. “Driver alterations” provide fitness advantages and are under positive selection during the cancer progression, whereas “passenger alterations” occur as a byproduct of cancer growth. Genes that are altered in cancer can be divided into proto-oncogenes and tumor suppressor genes. These are genes that regulate fundamental cellular processes and are carefully controlled in normal cells, although in a counterbalanced manner. Proto-oncogene products usually promote cell growth and division, whereas tumor suppressors are involved in cell growth inhibition and programmed cell death. A proto-oncogene can contribute to cancer after becoming an oncogene due to up-regulating mutations. In contrast, tumor suppressors can become carcinogenic as a result of mutations causing loss or reduction of function [6,7,9].
Most cancers share biological capabilities distinguishing them from healthy cells. In two influential reviews, Douglas Hanahan and Robert Weinberg organized these traits into hallmarks of cancer that govern the transformation of normal cells to cancer cells (Figure 1) [10,11]. The acquisition of these hallmarks is enabled by genome instability, which accelerates the mutation rate [11]. The majority of prognostic biomarkers are functionally associated with ‘hallmark’
4
features of cancer. However, individual cells within a given tumor often display variability in these traits [12].
Figure 1: The hallmarks of cancer, proposed by Hanahan and Weinberg. This figure lists the six initial hallmarks of cancer proposed in 2000 (sustainment of proliferative signaling, evasion of growth suppressors, limitless replicative potential, activation of evasion and metastasis, and induction of angiogenesis) [10], as well as the two enabling characteristics crucial to the acquisition of the six hallmark capabilities, genome instability and mutation and tumor-promoting inflammation, and the two new emerging hallmarks: deregulating cellular energetics and avoiding immune destruction, added in 2011 [11]. Modified from Hanahan and Weinberg [11], Copyright 2011, with permission from Elsevier.
A biomarker can be defined as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” [13]. Biomarkers are useful tools in cancer management, and can be divided into distinct categories based on their application. Detection biomarkers are indicative of the presence of cancer in the body. A diagnostic biomarker can determine cancer status, such as tumor grade or stage. Prognostic biomarkers can forecast the likely outcome of the disease, whereas predictive biomarkers provide information on the likely benefit of a certain treatment.
The performance of a biomarker can be judged on its sensitivity (how frequent it is present in the disease state) and its specificity (how frequent it is lacking from the normal situation). For
5
clinical purposes, a biomarker’s positive predictive value (the proportion of positives that are true positives) and its negative predictive value (the number of negatives that are true negatives) are of particular importance [13].
In eukaryotic cells, DNA is packed with histone proteins into chromatin (Figure 2). This enables packaging of DNA into a volume that fits within the nucleus and contributes to the control of gene expression. Chromosomes represent the highest level of chromatin condensation and become visible as distinct structures only when cells prepare for cell division.
Every cell has a defined number of chromosome sets in its genome (n), referred to as ploidy. A cell that has only one complete set of chromosomes is haploid (1n) e.g. human germ cells.
Euploid cells have an exact multiple of the haploid number of chromosome sets. Most human somatic cells are diploid as they carry two sets (2n) of chromosomes, where each set is composed of 23 chromosomes. Polyploidy is defined as having a chromosome number that is a multiple greater than two of the haploid number. Tetraploidy is a form of polyploidy in which a cell has four complete sets of chromosomes (4n). An unbalanced number of chromosome sets that is not an exact multiple of the haploid number, is termed aneuploidy.
Ploidy can be assessed by cytogenetic (karyotyping) and cytometric methods. Karyotyping provides information about the number and structure of chromosomes, but can only be performed in cell cultures after cells have been arrested during mitosis. In cytometric methods ploidy is analyzed by measuring the DNA content of cells. Thus, these methods can be used in archival material and non-dividing cells.
6
Figure 2: Model of chromatin condensation needed to achieve the packaging observed in metaphase chromosomes. At the simplest level, chromatin is a double-stranded helical structure of DNA which is wrapped 1.65 times around the complex of eight histones, producing fibers 11 nanometers (nm) wide, which stack up against one another in organized arrays to produce 30-nm fibers. These 30-nm fibers then form a series of loops, averaging 300 nm in length, which condense into 700-nm wide fibers. Tight coiling of the 700-nm fibers produces the chromatids of a metaphase chromosome. The structure and proper function of chromosomes are maintained by specialized repetitive DNA sequences called telomeres and centromeres. Figure by Marian Seiergren and Karolina Cyll.
During cell division, new chromosome sets are made and transmitted to daughter cells. The eukaryotic cell cycle is composed of two main phases: the interphase and the mitotic phase (M- phase) [14]. The interphase can be subdivided into three phases: gap 1 (G1), synthesis (S) and gap 2 (G2) (Figure 3). Cells enter the cell cycle through G1-phase, where they grow in size and prepare for DNA replication. During the S-phase, the DNA content is doubled. Then, the cell stays in G2-phase until all the machinery necessary for the M-phase is available. M-phase is composed of two main steps: mitosis and cytokinesis. Mitosis constitutes of the pairing and separation of the duplicated chromosomes. Cytokinesis is the physical process whereby the cell
7
splits into two daughter cells. The cell cycle progression is strictly regulated by a network of pathways that include cell cycle checkpoints and DNA damage repair (DDR). The cell cycle checkpoints trigger the essential processes of the cell cycle such as DNA replication, mitosis and cytokinesis. Those checkpoints are regulated by various cell cycle molecules: cyclins, cyclin- dependent kinases and inhibitors, levels of which undergo strict control in order to ensure successful cell division [14]. Cell cycle dysregulation results in unscheduled proliferations and ploidy abnormalities [15,16].
Figure 3: The cell cycle. The upper panel illustrates the phases of the cell cycle and major checkpoints regulating cell division. The first checkpoint is in G1-phase where the cell commits to cell cycle entry and chromosome duplication. When the cell detects defects (e.g. DNA damage), G1 checkpoint prevents progression from G1 to S-phase. The transition from G2 to M-phase is regulated by G2 checkpoint which can be activated due to DNA damage. The progression through the mitotic phase is monitored by the mitotic checkpoint until all chromosomes are properly aligned along the metaphase plate and attached to the mitotic spindle. The bottom panel depicts the subsequent phases of the mitotic phase: prophase, prometaphase, metaphase, anaphase and telophase (exemplified in a cell with three chromosomes). Figure by Marian Seiergren and Elin Ersvær.
Abbreviations: G1, Gap 1; G2, Gap 2; S, DNA synthesis phase; M, Mitotic phase.
8
Genomic instability may be defined as dynamic accumulation of genomic alterations [17,18]. It is present in all stages of cancer and is considered as an enabling hallmark of cancer, which accelerates the mutation rate and facilitates acquisition of other hallmarks [11,18]. Somatic and germline mutations in genes involved in the maintenance of genomic stability are dominant in most cancer types in The Cancer Genome Atlas (TCGA) cohorts, which molecularly characterized over 20.000 primary cancer samples from 33 cancer types [19]. While genomic instability is a characteristic of most human cancers, cancer genomes vary in both the amount and type of genomic instability they harbor [17,20].
The most commonly described types of genomic instability are microsatellite instability (MSI) and chromosomal instability (CIN) [17,21]. MSI refers to alterations in the length of microsatellites, which are simple tandem repeats of one to six nucleotides, scattered in the human genome [22]. The integrity of microsatellites is maintained by the mismatch repair system, which is responsible for correcting errors introduced during DNA replication [23]. MSI is caused by a deficiency in mismatch repair genes and is commonly found in colorectal and endometrial cancer [17,19,21]. CIN is described as an increased rate of change in chromosome number and structure over time [17,21,24]. The presence of numerical alterations can induce structural alterations and vice versa [25–28]. CIN is a dynamic process, which can only be detected by measurements of the time-based cell-to-cell variability in living cells [29]. However, difference in ploidy among cells, caused by unequal distribution of chromosomes, is used as a surrogate marker for CIN [24,30]. CIN is common in most sporadic types of cancers [18,30] and is generally associated with aggressive disease [30–32].
Aneuploidy is a characteristic of human cancers, suggested to play a key role in carcinogenesis [16,20,33–38]. Aneuploidy is the presence of altered number of chromosomes or chromosome arms [39]. These alterations follow a non-random pattern that implies that they are more likely to be cancer drivers rather than passengers [33]. It has been suggested that the number of tumor suppressor genes and oncogenes encoded on each chromosome predicts the likelihood that a
9
given chromosome is preferentially gained or lost in tumors [33]. Aneuploid cancer cells are generally genetically unstable with frequent errors in chromosome segregation [17,40–42].
Recently, a study performed in the TCGA cohorts found that aneuploidy was positively correlated with the rate of somatic mutations [20].
There are several ways by which a cell may become aneuploid, including: defects in the mitotic and DDR checkpoints, kinetochore-microtubule dynamics, chromosome cohesion, centrosome and telomere defects as well as epigenetic alterations (reviewed in [8,39,40,43]). Aneuploid cells can arise directly from diploid cells or indirectly through an unstable tetraploid intermediate [44,45]. Tetraploid cells can be generated by various mechanisms, e.g. endoreplication (replication of the nuclear genome in the absence of mitosis), cell fusion, programmed stop in cytokinesis, mitotic slippage and DNA replication or repair defects (reviewed in [45,46]).
Mutations that lead to tetraploidization have been shown to be implicated in CIN and carcinogenesis
(
reviewed in [46]). Under benign conditions, the presence of tetraploid cells is normal in e.g. liver, urinary bladder and seminal vesicles (reviewed in [47]).
The cellular response to aneuploidy varies depending on the organism and the cellular context.
Aneuploidy affects a broad spectrum of cellular processes and usually is lethal; however, extra copies of chromosomes containing genes that promote cell survival can be advantageous under various selective pressures [35,48–50]. One of the mechanisms that could support the survival of aneuploid cells is an increase in the number of chromosome sets. Tetraploidy may allow cells with DNA damage to survive by buffering mutational effects through extra chromosomes [45,48]. Alternately, aneuploid cells can revert to euploidy by losing their extra chromosomes if they induce a significant growth disadvantage [48]. The effect of aneuploidy can also be minimized through increased protein degradation, activation of the DDR that buffers CIN- induced apoptosis and the impairment of signaling pathways that limit proliferation [40,51].
10
Heterogeneity is a well-established trait of cancer [12,52]. Tumor heterogeneity implies that individual tumor cells differ with regard to their genomes, epigenomes, transcriptomes and proteomes [12]. Heterogeneity can occur both between tumors (intertumor heterogeneity) and within tumors (intratumor heterogeneity), or during the course of disease progression (temporal heterogeneity) (Figure 4) [12,53]. Intratumor heterogeneity refers to the presence of several subclones that show distinct gene expression in different tumor regions. Intratumor heterogeneity is found in most solid tumors, however some cancers, such melanoma, lung and prostate cancer, are more heterogeneous than others [54].
The biological mechanisms underlying intratumor heterogeneity remain unclear. One explanation is genetic instability and tumor evolution, which can contribute to both spatial and temporal tumor heterogeneity [12,53,55]. The elevated rate of chromosome missegregation in tumor cells with CIN and large-scale chromosomal alterations disrupting multiple genes may increase the intratumor heterogeneity [55]. Tumor evolution is a dynamic process that arises through the course of disease progression [56]. It involves selection and adaption of events that may provide a selective growth advantage by overcoming various selective pressures. Tumor evolution is often driven by random acceleration in the rate of genomic alterations. As a result of tumor evolution and genomic instability, cells with different genomic alterations emerge and expand, or disappear after clonal selection in different regions of the tumor during the course of disease progression, resulting in tumor heterogeneity [55,57].
Intratumor heterogeneity poses significant challenges for the detection and use of cancer biomarkers. Variations in the distribution of some biomarkers within a tumor can hinder accurate cancer diagnosis and the selection of the most appropriate treatment. This is due to the fact that cancer diagnosis relies on biopsy samples, which represent only a small fraction of a tumor [58].
Consequently, there may be lack of concordance in a biomarker’s status among core biopsies obtained from different areas of the same tumor. A study by Gerlinger et al. [59] showed that gene-expression signatures of good and poor prognosis can be detected in the same tumor, depending on which region was sampled.
11
Figure 4: Illustration of different types of tumor heterogeneity. Figure by Marian Seiergren and Karolina Cyll.
The prostate is the largest accessory gland of the male reproductive system. It produces and secretes prostatic fluid, which constitutes about 20–25% of the semen, and contains i.a. prostate- specific antigen (PSA). The growth and proper function of the prostate gland depend on androgen steroid hormones, mainly testosterone and dihydrotestosterone [60]. The prostate is situated in the lower region of the smaller pelvis, under the urinary bladder and in front of the rectum. The prostate is a glandular and muscular organ surrounded by a “pseudocapsule”. The normal adult prostate comprises of 30 to 50 branched tubuloalveolar glands, which are lined by a basal layer of low cuboidal epithelium covered by a layer of columnar secretory cells. The basal cell layer separates the secretory cells from the basement membrane [60]. The glandular tissue of the prostate may be subdivided into three distinct zones: peripheral (65%–70% of volume), central (25% of volume) and transitional (5%–10% of volume)(Figure 5) [61].The glands of the transitional zone often undergo benign prostatic hyperplasia, which can be treated by transurethral resection of the prostate (TURP) [62]. The non-glandular components of the prostate include the preprostatic sphincter, fibromuscular stroma, blood vessels and nerves. The fibromuscular stroma is composed of smooth muscle cells that are often separated by bands of dense fibrous tissue[60,63].
12
Figure 5: Anatomical location and zones of the prostate gland. The prostate gland is situated beneath the urinary bladder and next to the seminal vesicles. It wraps around the urethra and the ejaculatory ducts, stemming from the seminal vesicles. Anatomically, it can be divided into three main zones: the peripheral zone located posteriorly and partly anteriorly, the central zone surrounding the ejaculatory duct and the transitional zone which surrounds the urethra. Figure by Marian Seiergren and Karolina Cyll.
Most commonly, prostate cancers arise from the peripheral zone of the prostate [61]. The vast majority (>90%) of prostate cancers are acinar adenocarcinomas [64], i.e. cancers of the glandular epithelial cells. Other prostate cancer types include ductal adenocarcinomas, squamous cell carcinomas, urothelial carcinoma, basal cell carcinoma, and neuroendocrine tumors, specifically small-cell carcinoma [65]. Most primary prostate cancers are multifocal, i.e. consist of multiple tumor nodules separated from each other by normal tissue [66]. The tumor nodule with the highest Gleason score, highest stage or largest volume is often referred to as an index tumor [67].
13
Prostate cancer is the second most frequently diagnosed cancer in men and the fifth leading cause of cancer death in men, worldwide [68]. As of 2015, 14.4 million individuals were estimated to have the disease, with great variations in incidence rates throughout the world [69].
The incidence of prostate cancer has increased significantly in the last 40 years, while death rates, in the majority of developed countries, have been decreasing [70]. In Norway, prostate cancer is the most common cancer in men, accounting for 27% (4.983 cases) of all cancers diagnosed in men in 2017. The five-year relative survival has increased from 56.5% in 1977–81, to 93.9% in 2012–17 [71].
Age, family history and race are the strongest established risk factors for prostate cancer [72].
Prostate cancer develops in the vast majority of aging men. In a seminal autopsy study from 1994, Sakr et al. [73] found cancer foci in 2%, 29%, 32%, 55%, and 64% of prostates of men over 20, 30, 40, 50, and 60 years of age, respectively. The median age at diagnosis in Norway in 2013–17 was 69 years [71]. Family history is another important risk factor for prostate cancer.
Men with a first-degree relative with prostate cancer have a two- to three-fold higher risk of developing the disease relative to men without a family history [74]. In addition, men with hereditary prostate cancer who are diagnosed at a younger age, more often present with a higher disease stage and have a higher risk of disease recurrence after radical prostatectomy (RP) [75].
The risk of prostate cancer also differs between races, with an increased risk among men of African descent and a decreased risk among men of Asian descent [68].
Prostate cancer may have no specific presenting symptoms and is often asymptomatic at the time of diagnosis [76]. Prostate tumors often have a slow growth rate [77]. Observational studies following men with untreated localized prostate cancer found that most early-stage cancers had an indolent courseduring the patient’s lifetime [78–80]. These studies reported overall prostate cancer-specific mortality between 16% and 29% during 20–32 years of follow-up. The risk of death from competing causes was higher than the risk of death from prostate cancer. The highest
14
increase in rates of local progression, metastatic disease and prostate cancer mortality was observed after 15 years of follow-up [78,79].
The main diagnostic tools for detection of prostate cancer are digital rectal examination (DRE), PSA testing and prostate tissue biopsies. Lately, magnetic resonance imaging (MRI) has become a useful imaging modality in prostate cancer diagnostics [72].
DIGITAL RECTAL EXAMINATION
Digital rectal examination (DRE) is a fundamental part of the clinical examination of a patient suspected to have prostate cancer, and is traditionally used for clinical tumor staging. DRE can detect tumors in the posterior and lateral part of the gland, but not those situated “anteriorly”. Its sensitivity depends both on the stage of the tumor and the experience of the examiner, and the reproducibility of DRE for detecting prostate cancer among urologists is only fair [81].However, DRE is still of importance as it can detect clinically aggressive tumors in the absence of elevated PSA levels [82].
PROSTATE-SPECIFIC ANTIGEN
Prostate specific antigen (PSA) is a protein produced by both normal secretory epithelial cells and cancerous prostate cells. PSA can be detected in blood samples due to urinary infections, benign prostatic hyperplasia and prostate cancer [83], and its levels increase with age and prostate size [84]. In the mid-1980s, PSA testing was adapted for detection of prostate cancer [85], which contributed to an increased incidence of prostate cancer [86].
As a diagnostic tool, PSA has a high sensitivity but low specificity for prostate cancer. PSA is a continuous parameter, with higher levels indicating greater likelihood of prostate cancer, precluding an optimal PSA threshold for detecting non-palpable but clinically significant prostate cancer [83,87]. Commonly, a threshold level of >4 ng/ml has been used to prompt biopsies in order to confirm a cancer diagnosis [83]. However, more aggressive cancer cells may lose their PSA producing properties, resulting in lower levels of PSA in aggressive prostate cancer [88–90]. Contemporary data indicate that PSA testing identifies disease 6 to 13 years before it presents clinically [91], and contributes to more favorable 10 year outcomes following conservative management than those reported from older cohorts [92]. On the other hand, such
15
early detection also results in over-diagnosis and over-treatment of indolent tumors that would not have caused clinical consequences during a man’s lifetime [93]. The Norwegian Directorate of Health [94] recommends against population-based PSA screening. Around 45% of Norwegian men over 40 years old have been exposed to PSA testing between 1999 and 2011 [95].
PSA test is also used as a marker of residual prostate cancer or disease progression after treatment [83]. However, a subsequent increase in PSA, termed as biochemical recurrence (BCR),does not necessarily indicate a poor outcome. Only approximately 30% of patients with BCR after primary surgery develop clinical recurrence [96], and 16% die from their disease [97].
In addition to the total PSA level, there are several variations of the PSA measurement that take into consideration additional factors, such as the prostate volume (PSA density) and the rate of change in PSA levels over time (PSA velocity or PSA doubling time (PSA-DT)).
MAGNETIC RESONANCE IMAGING
Magnetic resonance imaging (MRI) can be used for the prostate cancer diagnosis and staging [98–100]. MRI uses the electromagnetic properties of hydrogen molecules to collect information about organs and other tissues, which is then converted to an image. MRI captures the difference in magnetic properties between tumors and surrounding normal tissue. Magnet in a MRI system is rated using a unit of measure known as Tesla (T). Multiparametric MRI (mpMRI) using 1.5 T and 3 T magnetic resonance scanners, with or without an endorectal coil, has improved prostate imagingdue to its high resolution and soft-tissue contrast [99]. The visibility of prostate tumors on mpMRI depends on tumor volume, grade, histology, and location [101]. Interpretation of prostate mpMRI requires experience [102] and agreement among readers is poor to moderate [103,104]. It has been shown that mpMRI can detect prostate cancer and index tumors with high sensitivity [98,105,106]. mpMRI is also a valuable tool for detecting clinically significant prostate cancer in patients with a prior negative biopsy and a persistently elevated or increasing PSA level [107]. Moreover, mpMRI appears promising for reducing the number of biopsies in the management of patients on active surveillance (AS) [108,109], and it has already been incorporated in AS protocols in several published studies [110–112].
16
PROSTATIC NEEDLE BIOPSIES
The need for prostatic biopsies is usually determined by the PSA level, a suspicious DRE, patient’s age and comorbidities, as well as potential therapeutic consequences [113]. Prostatic biopsy is an invasive procedure that may lead to complications such as infections and bleeding [114]. During the procedure, a tissue sample is captured by a prostate biopsy gun using a special needle with a side-notch that is inserted into the prostate. A single biopsy core corresponds to about 0.003% of the whole prostate [58]. The first protocols used sextant biopsies [115].
Currently, a systematic 10–12 core biopsy scheme is the standard procedure in prostate cancer diagnosis [87,94]. The biopsy procedure is usually done with transrectal ultrasonography (TRUS) guidance. Performing MRI before a prostatic biopsy has been recently suggested to improve samplingefficacy [116,117]. It has been shown that MRI-targeted biopsies have greater maximum cancer core length and identify more patients with Gleason grade 4 and 5 than the systematic biopsies [118].
GLEASON GRADING
The Gleason grading system is the gold-standard of histologic grading of prostate cancer, and is used for determining prognosis and guiding treatment decisions. Gleason grading is solely based on the assessment of architectural patterns (grades) seen on hematoxylin-eosin (H&E) stained prostatic tissue sections, at low to medium magnification. The Gleason grading system was introduced by Donald F. Gleason in the 1960s [119], and replaced the former World Health Organization (WHO) grading system in Norway in 2001 [94].
The original Gleason grading system has been gradually refined following new insights into the biology of lesions of the prostate and their prognostic relevance. Extensive revisions were made at two consensus meetings conducted by the International Society of Urological Pathology (ISUP) in 2005 [120,121] and 2014 [122]. Currently, only Gleason grades 3 through 5 and Gleason scores ranging from 6 to 10, are assessed (Figure 6). Some of the original Gleason grade 3 growth patterns have been shifted to Gleason grade 4, which lead to an increased proportion of cancers assigned Gleason score 3+4 or 4+3 [123,124]. Contemporary Gleason grade 3 consists of only well-formed glands with very low metastatic potential, and thus patients with pure Gleason
17
score 3+3 at RP have excellent prognosis [125,126]. Needle biopsies and RP specimens are graded in different ways. Gleason score for biopsies is composed of the most prevalent and the highest grade. In case of multiple biopsy cores with different Gleason scores, each core is reported separately and the highest Gleason score is commonly used to determine treatment [127]. Gleason score for RP specimens is composed of the two most common grades present in a tumor. If there are three grades with a very minor component of a higher grade, then the higher grade is reported as a minor (tertiary) grade for Gleason score 3+4 and Gleason score 4+3 [127].
In cases of multifocal tumors, separate Gleason scores are assigned to only one or at most two index tumors [127]. A recommendation from the 2014 consensus meetings was to report the percentage of grade 4 in both needle biopsies and RP specimens with Gleason score 7 to better inform treatment decisions. A subsequent study has shown that increasing percent of grade 4 at RP correlates with an increased risk of BCR after RP [128].
Figure 6: Histologic grades in prostate cancer. Gleason grade 3 has moderately differentiated and recognizable glands; Gleason grade 4 has poorly differentiated and often fused glands, and consists of four distinct morphological subtypes: fused, poorly formed, cribriform, and glomeruloid; Gleason grade 5 has two patterns; either with no glandular differentiation or cribriform glands with central comedonecrosis. Figure by Karolina Cyll and Manohar Pradhan.
Another important outcome of the 2014 ISUP meeting was the proposal of arranging Gleason scores into five prognostically distinct categories referred to as Gleason grade groups (GGGs) or ISUP grades [122,129]. The GGGs range from 1 to 5 (Table 1), where GGG 1 indicates the most favorable prognosis and GGG 5 the least favorable prognosis. In a study involving five large prostate cancer centers, GGGs were validated by the likelihood of BCR on 20 854 patients who underwent RP and 5501 patients treated with radiotherapy [130]. The GGGs were adopted by the 2016 WHO classification of tumors of the prostate [131].
18
Table 1: The 2014 International Society of Urological Pathology (ISUP) grading system [122].
Gleason grade group
Gleason
score Histological definition
1 ≤6 Only individual discrete well-formed glands
2 3+4=7 Predominantly well-formed glands with lesser component of poorly- formed/fused/cribriform glands
3 4+3=7 Predominantly poorly- formed/fused/cribriform glands with lesser component of well-formed glands
4
4+4=8 3+5=8 5+3=8
Only poorly-formed/fused/cribriform glands Predominantly well-formed glands and lesser component lacking glands
Predominantly lacking glands and lesser component of well-formed glands 5 ≥9 Lacks gland formation (or with necrosis) with or w/o poorly
formed/fused/cribriform glands
Incorporation of cribriform pattern and intraductal carcinoma into GGGs could be the next modification of current grading system [132]. Cribriform pattern is a Gleason pattern 4 subgroup associated with worse prognosis than the other Gleason 4 growth patterns [133–135]. Intraductal carcinoma is an infiltration prostatic ducts by prostatic adenocarcinoma, and it has also been associated with poor prognosis [136–138]. It has been reported that cribriform pattern and intraductal carcinoma are associated with increased genomic instability and distinct genomic alterations such as loss of expression of phosphatase and tensin homolog (PTEN) [139–141].
According to the current recommendations [142], patients with intraductal carcinoma and/or cribriform pattern histology on needle biopsy should not be managed by AS.
Gleason grading is subjective and intra- and interobserver variability occurs. On re-examining routine clinical material, Donald Gleason duplicated exactly his previous scores approximately 50% of times [143]. Subsequent studies reported intraobserver variability in 23%–57% of cases [144,145] and interobserver variability is reported in 22%–53% of the cases [144,146–148]. The reproducibility of the new GGGs among expert uropathologists was highest for GGG 1 and GGG 5 (moderate agreement) and lowest for GGG 3 (fair agreement) [149]. The most accurate Gleason scores are achieved when tumors are evaluated by expert uropathologists [148,150].
Figure 7 depicts our unpublished evaluation of Gleason scores assigned by non-uropathologists and an uropathologist. We observed better distinction between the different Gleason scores, especially for the Gleason scores 3+4 and 4+3, when Gleason grading was performed by an uropathologist compared to the non-uropathologists.
19
Figure 7: Kaplan-Meier curves of recurrence probability after radical prostatectomy (RP) grouped by Gleason scores assigned by three non-uropathologists (left) and an uropathologists (right).
Gleason grading was performed according to the 2005 International Society of Urological Pathology (ISUP) consensus guidelines [120] in RP specimens from a subset of patients (n=180) from the RP cohort. The final Gleason scores from the non-uropathologists were given as a consensus score.
Due to the extensive morphological heterogeneity of prostate cancer [151] and the limited amount of tissue sampled in a biopsy, GGG assessed on biopsy differs from the GGG in the prostate after RP in about 40% of patients [124,152,153]. The grade discordance is particularly high for GGG 3, and it is observed in 50%–67% of patients [124,152–154]. The most frequent discordant finding is undergrading of the GGG at biopsy, which occurs in up to 36% of cases with GGG 1 [124,152,154]. An approximately equal number of patients with GGG 2 at biopsy are over- or undergraded, while patients with GGG 3 at biopsy are mostly overgraded [124, 152,154].
Prostate cancer is staged according to the primary tumor (T), regional lymph node (N), and distant metastasis (M) classification (TNM) by either the International Union Against Cancer (UICC) [155] or the American Joint Commission on Cancer (AJCC) [156]. The TNM stage is based on four main categories (T1–T4), with subgroups, describing the local extent of the tumor (Table 2). The clinical T (cT) stage is traditionally based on DRE and biopsy findings.
Pathological T (pT) stage can be only determined after RP, and depends on the presence of extraprostatic extension (EPE), seminal vesicle invasion (SVI),status of surgical margins (SM) and pelvic lymph node involvement (LNI). The interobserver variability in tumor staging is reported in 13%–42% of cases [146–148,157].
20
Table 2: Tumor Node Metastasis (TNM) classification of prostate cancer. Adapted from Amin et al. [156].
Primary tumor (T)
Clinical tumor stage TX Primary tumor cannot be assessed
T0 No evidence of primary tumor
T1 Clinically inapparent tumor not palpable or visible by imaging
T1a Tumor incidental histologic finding in ≤5% of tissue resected (at time of TURP) T1b Tumor incidental histologic finding in >5% of tissue resected (at time of TURP) T1c Tumor identified by needle biopsy (because of elevated PSA level)
T2 Tumor confined within the prostate T2a Tumor involves one-half of one lobe or less
T2b Tumor involves more than one-half of one lobe, but not both lobes T2c Tumor involves both lobes
T3 Tumor extends through the prostatic capsule T3a Extracapsular extension (unilateral or bilateral) T3b Tumor invading seminal vesicle(s)
T4 Tumor fixed or invades adjacent structures other than seminal vesicles Pathologic tumor stage
pT2 Organ confined
pT3 Extraprostatic extension
pT3a Extraprostatic extension or microscopic invasion of the bladder neck pT3b Seminal vesicle invasion
pT4 Tumor is fixed or invades adjacent structures other than the seminal vesicles Regional lymph nodes (N)
Clinical (cN)
NX Regional lymph nodes were not assessed N0 No regional lymph node metastasis N1 Metastasis in regional lymph node(s) Pathologic (pN)
pNX Regional nodes not sampled pN0 No positive regional nodes pN1 Metastases in regional nodes(s)
Distant metastasis (M) M0 No distant metastasis
M1 Distant metastasis
M1a Non-regional lymph nodes(s) M1b Bone(s)
M1c Other site(s) with or without bone disease
Abbreviations: TURP = transurethral resection of the prostate; PSA = prostate specific antigen.
21
Prognosis and management of prostate cancer is mainly based on parameters such as PSA level, T stage and Gleason score at the time of biopsy or after RP. Several risk assessment methods have been developed to help doctors and patients make appropriate treatment decisions. The most commonly used risk classification systems are: the D’Amico Risk Stratification [158] and the Cancer of the Prostate Risk Assessment (CAPRA) score [159]. The D’Amico Risk Stratification estimates risk of BCR after RP from PSA level, Gleason score and tumor stage.
Several other risk stratification systems such as the European Association of Urology (EAU) and the Norwegian Directorate of Health system from 2016 (Table 3) [94] are derived from the D’Amico Risk Stratification.
Table 3: Risk stratification of prostate cancer. The table is adapted from the guidelines for prostate cancer published by Norwegian Directorate of Health [94].
Risk cT stage PSA (ng/ml) Gleason score
Low risk ≤T2a AND <10 AND ≤ 6
Intermediate risk T2b–T2c OR ≥10 <20 OR =7
High risk ≥T3 OR ≥20 OR 8-10
Abbreviations: cT stage – Clinical tumor stage; PSA – prostate specific antigen.
In addition to PSA level, T stage and Gleason score, which are included in the D’Amico risk stratification, the CAPRA score also includes age and percentage of positive biopsy cores [159]
(Table 4). The CAPRA score is categorized to give three CAPRA risk groups: low risk (score 0 to 2), intermediate risk (score 3 to 5) and high risk (score 6 to 12) [159]. The CAPRA score has been validated to predict pT stage, metastatic progression and prostate cancer-specific mortality following treatment [160].
The postsurgical CAPRA score (CAPRA-S) was developed to aid in predicting patient outcomes following RP, and it is based on preoperative PSA and pathologic parameters determined at the time of the surgery (Table 4) [161]. The CAPRA-S score has been validated in several patient cohorts as a predictor of BCR and cancer-specific mortality (reviewed in [162]).
22
Table 4: The CAPRA and the CAPRA-S scores. The table is adapted from Cooperberg et al. [159,161].
CAPRA score CAPRA-S score
Variable Level Points Variable Level Points
PSA (ng/ml)
2.0-6 0
PSA (ng/ml)
0-6 0
6.1-10 1 6.1-10 1
10.1-20 2 10.1-20 2
20.1-30 3 >20 3
>30 4
Gleason
2-6 0
Gleason 1-3/1-3 0 3+4 1
1-3/4-5 1 4+3 3
4-5/1-5 3 8-10 4
T stage T1/T2 0
SM Negative 0
T3a 1 Positive 1
% pos bx <34% 0
SVI No 0
≥34% 1 Yes 1
Age <50 0
EPE No 0
≥50 1 Yes 1
LNI No 0
Yes 1
Abbreviations: CAPRA = Cancer of the Prostate Risk Assessment; CAPRA-S = postsurgical CAPRA; PSA = prostate- specific antigen; pos bx = positive biopsy; SM = surgical margin; SVI = seminal vesicle invasion; EPE = extraprostatic extension; LNI = lymph node involvement.
Treatment decisions for prostate cancer patients should take into account several factors such as patient’s age, general health status, life expectancy, the risk of dying from the cancer, patient’s own expectations to the treatment’s outcome and the balance of benefits and side effects of each therapy. Men diagnosed with localized prostate cancer (defined as no identifiable regional lymph nodes or distant metastases) have three primary treatment options: RP, radiotherapy (RT) and observation either by active surveillance (AS) for men with long life expectancy or watchful waiting (WW) in older or comorbid men. These treatment options will be described in more detail below. Locally advanced and metastatic disease can be treated with androgen deprivation therapy, chemotherapy and immunotherapy [163,164].
23
RADICAL PROSTATECTOMY
Radical prostatectomy (RP) involves removal of the entire prostate gland and resection of both seminal vesicles, along with sufficient surrounding tissue in order to obtain a negative margin.
The use of RP as prostate cancer treatment increased in the late 1980s and 1990s [165,166] after introduction of nerve-sparing surgery [167] and refinements to the surgical technique. Nerve- sparing surgery increases the chance of preserving erectile function but it may be associated with higher rate of positive margins in patients with pT2 tumors is the procedures is performed bilaterally [168,169]. The benefits of RP are largest in patients younger than 65 years at diagnosis and those with intermediate disease [170,171]. Side effects of RP include erectile dysfunction and urinary incontinence [168,172].
RADIOTHERAPY
The aim of radiotherapy (RT) is to kill rapidly proliferating cancer cells by inducing unrepairable DNA damage. RT can be used as the primary treatment, as salvage treatment (second curative attempt) in case of cancer recurrence after radical surgery or as a palliative treatment. Immediate radiotherapy after RP can reduce the risk of recurrence and death [173]. RT may result in several complications including a reduced quality of life related to bowel function, erectile dysfunction and urinary incontinence [168,172].
Active surveillance (AS) is defined as a strategy of close observation of patients with localized prostate cancer, with the intention to avoid or postpone curative treatment, but still be able to initiate it if there is a sign of tumor progression. The aim of AS is to reduce the overtreatment of patients with low-risk disease, which number increased as a consequence of the use of early detection strategies such as PSA testing and prostate biopsies [91,174]. Most of these patients are unlikely to experience disease progression in their life time [79,80], and will accordingly not benefit from immediate RP or RT [171,175]. The idea of AS is attributed to Laurence Klotz, who in 2004 published initial outcomes of AS patients with “good risk” prostate cancer treated with RP at the time of PSA-DT increase or histological progression [176]. Since then, several AS cohorts with up to 10-years follow-up reported cancer-specific survival ranging from 97% to 100% [110,177–179], indicating that AS could be a safe alternative for low risk patients and
24
selected patients with intermediate risk disease. According to the rapport from the National quality register for prostate cancer [180], approximately 80% of patients in low risk and 30% of patients with intermediate risk disease, according to the EAU risk stratification, were followed with AS in 2017 in Norway.
There are currently no consensus guidelines on criteria for inclusion of patients in AS, follow-up strategies, or triggers for treatment [111,181]. The selection criteria of most AS programs are largely based on the Epstein biopsy criteria for insignificant tumor (GGG 1, ≤2 positive cores, PSA density ൏0.15 ng/mL, <50% of cancer involvement in any core) [182] or the D’Amico criteria for low-risk cancer (≤cT2a and PSA<10 ng/ml and GGG 1) [158]. The recommendations from the Norwegian Directorate of Health from 2015 are based on the initial protocol for AS in the Prostate cancer Research International: Active Surveillance (PRIAS) program (https://www.prias-project.org/). This protocol was refined during the course of the trial due to the low number of men complying with the initial treatment recommendations and high rates of overtreatment [110,183]. The updated PRIAS protocol includes patients with GGG 2 if they are 70 years or older. Also, several published AS studies reported inclusion of patients with intermediate risk features such as GGG 2 and/orPSA 10–20 ng/ml [177,184–187]. Monitoring of patients in AS is most commonly done by periodic DRE, PSA measurements, prostate biopsies and MRI [112,181,188]. The reasons for ending AS are mostly initiation of curative treatment, transferal to WW or patient’s death [177,184,189]. The choice between curative treatment and continued observation relies mainly on standard clinical parameters such as PSA level, Gleason score, stage and measures of tumor extent (either on biopsies or on images from different modalities) [111,112,181,190]. Curative treatment may also be triggered by patient’s request [111]. In published AS cohorts, most patients are treated due to histologic upgrading (27%–
100%) or PSA progression (13%–48%), whereas up to 13% are treated without any evidence of progression [191]. Large AS studies reported that approximately 70% of patients avoided curative treatment at a median of five years of AS [110,177–179].
WW is an option for patients who are not eligible for AS due to short life expectancy or comorbidities. In contrast to AS, patients under WW have less intense follow-up and are only offered palliative therapy to manage symptoms of disease progression [87]. In studies published before the early 2000s, terms “active surveillance” and “watchful waiting” were often used synonymously and stood for no initial treatment, usually followed by hormonal treatment, if and
25
when the symptoms occurred. The EAU guidelines from 2011 made a clear distinction between these two observation strategies [192].
Prostate cancer development and progression involve alterations in numerous genetic pathways, though only a few abnormalities in specific genes are highly recurrent [193–195]. Germline mutations were found in ~5% of the samples from the prostate adenocarcinoma TCGA cohort, and were almost exclusive to genes related to maintenance of genomic stability [19]. The predominating somatic mutations occur in phosphoinositide 3-kinase (PI3K) signaling pathways and genes involved in maintenance of genomic stability and chromatin modifications [19,196,197]. Various studies suggest that prostate cancer is likely driven by large-scale genomic alterations, such as copy number changes and structural chromosomal rearrangements, which have been observed in parallel to metastatic progression [198,199].
In primary clinically localized prostate cancer, mutations most commonly occur in speckle type BTB/POZ protein (SPOP) (11%) and forkhead box A1 (FOXA1) (3%) genes [195,200]. Somatic copy number alterationsare found in 89% of primary prostate tumors, but normally only affect a small portion of the genome [201]. Deletions are more common compared to amplifications, and are usually found on chromosomes 8p, 10q, 13q and 17p [202]. These chromosome arms include genes such as NK3 homeobox 1 (NKX3-1), PTEN, BRCA2 DNA repair associated (BRCA2), RB transcriptional corepressor 1 (RB1) and tumor protein p53 (TP53). Castration-resistant metastatic prostate cancer exhibits increased chromosomal alteration rates, which may indicate increased genomic instability as the disease progresses [202,203]. These tumors often show amplification of chromosome X, which includes androgen receptor (AR) [202].
The most common chromosomal rearrangement in prostate cancer are fusions of androgen- regulated promoters with members of the erythroblast transformation-specific (ETS) family of transcription factors (most commonly ETS transcription factor ERG (ERG)) [204]. The ETS gene’s fusion partner is most often transmembrane serine protease 2 (TMPRSS2), however involvement of other androgen-related genes has also been demonstrated in these oncogenic fusions in prostate cancer [205]. These alterations are the basis for the submolecular
26
classification of prostate cancer into ETS-positive and ETS-negative tumors. Deletion or mutation of PTEN and TP53 occur morefrequently in ETS-positive cancers [200], while SPOP mutations are more common in ETS-negative tumors [200,202]. In the prostate adenocarcinoma TCGA cohort, 74% of primary tumors could be assigned to one of seven molecular subtypes based on the presence of four gene fusions and three genetic mutations [195]. However, the genetic complexity found in most advanced prostate cancers precludes their classification into distinct subgroups based on a genetic profile [202].
Prostate cancer is characterized by extensive intratumor heterogeneity [206–208]. In addition, the majority of cases are multifocal, where multiple distinct tumor foci with different pathologic characteristics are present within a prostate gland [66,151]. The origin of multifocal prostate cancer can be monoclonal (derived from one clonal population) or polyclonal (derived from two or more clonal populations) [207–212]. Numerous studies, using several approaches, have identified genetic heterogeneity in different regions of a single prostate cancer focus, as well as between different prostate cancer foci in the same patient [207,208,213–215]. Moreover, analysis of serially collected TURP specimens from patients treated with androgen ablation revealed different genetic alterations at each time point [214].
27
Gleason score and PSA are currently the only prognostic biological markers for prostate cancer management in clinical routine. However, they fall short in explaining the observed variation in clinical outcome from patient to patient [175,216–219].To date, a multitude of molecular tissue- based biomarkers have been evaluated for their potential role in predicting disease outcome.
DNA ploidy and PTEN status are one of the most extensively studied biomarkers for prostate cancer. Recently, several commercially-available genomic tests such as Prolaris, Oncotype Dx and Decipher have gained interest [220]. However, none of the molecular tissue biomarkers have been incorporated in prostate cancer management. Wei et al. [213] investigated the impact of tumor heterogeneity on Oncotype DX, Prolaris and Decipher assays. The authors analyzed 26 tissue cores sampled from index tumour and other lesions from four multifocal RP specimens.
The study demonstrated that the large extent of inter- and intratumour heterogeneity precludes the use of these platforms on a single biopsy for determining appropriate treatment.
PTEN
The PTEN tumor suppressor gene is located at chromosome 10q23, a locus that is highly susceptible to mutations in human cancers [221,222]. Germline mutations of PTEN are the underlying genetic cause of cancer predisposition syndromes such as Cowden disease, while somatic PTEN mutations are observed in many cancer types, such as glioma, prostate, kidney and breast cancer [222–224]. Homozygous deletion of PTEN in mice leads to embryonic lethality, and PTEN heterozygous mutant mice have a high incidence of cancer [225,226].
Functionally, PTEN encodes for a dual specificity protein and lipid phosphatase. PTEN protein can be found both in the cytoplasm and in the nucleus (Figure 8). The lipid phosphatase activity of PTEN predominates in the cytoplasmic compartment, where it opposes the phosphoinositide 3-kinase (PI3K)/AKT serine/threonine kinase 1 (AKT) pathway, which regulates a number of cellular processes including cell growth, metabolism, proliferation and survival (reviewed in [227]). The protein phosphatase activity of PTEN is generally nuclear and has a variety of functions. Nuclear PTEN is involved in maintenance of genomic stability and control of cell cycle progression by i.a. suppressing cyclin D1 activity, binding to the anaphase-promoting
28
complex/cyclosome (APC/C) E3 ligase and maintaining centromere stability by interacting with centromere protein C (CENPC) [227–229]. Furthermore, it has been shown that nuclear PTEN controls a DNA repair process by transcriptional regulation of AR and RAD51 recombinase (RAD51) levels, which is a key protein involved in DDR [227,230].
PTEN function is regulated by various molecular mechanisms. Most commonly, PTEN function is compromised by homo- and heterozygous genomic deletion, but other mechanisms such as genomic rearrangements, mutations, methylation of the PTEN promoter region, transcriptional repression and microRNA regulation have also been described [227]. In addition, PTEN activity is modulated by post-translational modifications and protein–protein interactions [227,231]. In the vast majority of prostate tumors, PTEN is inactivated by homo- or heterozygous genomic deletion; PTEN inactivation by mutations or methylation occurs in <10% of cases (reviewed in [232]).
Loss of at least one PTEN gene allele or PTEN protein loss are reported in 11% to 41% of localized tumors and up to 77% of castration-resistant tumors, as shown by either fluorescence in situ hybridization (FISH), immunohistochemistry (IHC) or sequencing [28,199–201,233]. PTEN loss is associated with features of aggressive prostate cancer, including higher Gleason score and presence of EPE and SVI [234–238]. PTEN loss has been associated with disease upgrading or non-organ confined disease at RP [239–241], shorter time to biochemical recurrence after RP [242,243], and death from prostate cancer [244–246]. In a recent study, Leapman et al. [247]
found that the PTEN protein status alone offered comparable discrimination of the risk of metastasis or death from prostate cancer relative to a commercial RNA amplification-based multigene panel. In an AS cohort that included patients with GGG 1, PTEN loss was associated with an increased risk of subsequent biopsy upgrading, discontinuation of AS, and adverse histopathological features in RP specimen [241]. In addition, studies suggest that PTEN could be a promising predictive biomarker for response to drugs targeting the PI3K/AKT pathway [248,249].
Intratumor heterogeneity in PTEN protein expression was found in 2%–35% of cases [234,240,244,245,250,251]. Studies using tissue microarrays (TMA) observed heterogeneous PTEN status in 2–14 % of the patients [234,235,244]. Higher rates (35%) of heterogeneity were
29
reported in a study that analyzed PTEN expression on a single whole section representing index tumor from 77 RP specimens [250].
Figure 8: Functions of PTEN in cytoplasm and nucleus. In the cytoplasm, phosphatase and tensin homologue (PTEN) dephosphorylates phosphatidylinositol 3,4,5-trisphosphate) to phosphatidylinositol 4,5-bisphosphate (PIP2), antagonizing the function of phosphoinositide 3‑kinase(PI3K) activity, which converts PIP2 to PIP3. Following PTEN loss, accumulated PIP3 leads to activation of AKT serine/threonine kinase 1 (AKT). Active AKT drives cell survival, proliferation, metabolism and cell cycle progression. In the nucleus, PTEN functions in a PI3K-independent manner to regulate cell cycle progression and gene transcription as well as to counteract genomic instability and DNA damage. Figure by Marian Seiergren and Karolina Cyll.
Abbreviations: P, phosphorylation; APC/C, anaphase-promoting complex/cyclosome; G1, Gap 1; G2, Gap 2; S, Synthesis phase; M, Mitotic phase.
30 DNA PLOIDY
Ploidy alterations are associated with past or ongoing genomic instability, and are generally indicative of poor prognosis (reviewed in [24,30]). Ploidy status can be assessed in a relatively cost-effective and high-throughput manner by measuring of nuclear DNA content with flow or image cytometry [30]. Since development of these methods, numerous studies have shown the prognostic value of DNA ploidy in various cancer types, including prostate cancer [30,252].
Patients with diploid tumors usually had significantly better prognosis than patients with non- diploid tumors (tetraploid and aneuploid) [30,252]. In several studies, DNA ploidy status assessed in RP specimens was an independent predictor of disease recurrence [253–258], death from prostate cancer [259]or BCR [260]. Others observed that DNA ploidy status did not add much information over that provided by established prognostic factors [261,262]. When assessed in biopsy specimens, DNA ploidy status was a significant predictor of overall survival [263], death from prostate cancer [264,265] or relapse after brachytherapy [266]. Several studies have shown a significant correlation between high Gleason score and the non-diploid DNA status in RP specimens [267–270].
Intratumor heterogeneity in DNA ploidy status has been reported in 4%–56% of cases [263,271–
278]. The majority of studies that have investigated heterogeneity in DNA ploidy status included a small number of patients and samples [275–278].The lowest rates of heterogeneity in DNA ploidy status were reported in a study that analyzed only an average of two samples per patient [278] and in a study performed in needle biopsies [263]. The study by Warzynski et al. [274] is the largest published study of intratumor heterogeneity in DNA ploidy. Intratumor heterogeneity was found in DNA ploidy in 40% of 75 patients with an average of four samples examined.
