Apoptosis and
Apoptosis and Fas/FasL Fas/FasL Pathway: Role of Pathway: Role of FAS FAS and and FASL FASL Functional Functional Polymorphisms Polymorphisms
in Prostate Cancer Development
in Prostate Cancer Development
Aos meus pais e ao amor da minha vida,
por todo o apoio, amor e carinho
Curso de Mestrado em Medicina e Oncologia Molecular
Apoptosis and Fas/FasL Pathway: Role of FAS and FASL Functional Polymorphisms in
Prostate Cancer Development
Orientador: Prof. Doutor Rui Medeiros
Dissertação de Mestrado do Licenciado
Luís Carlos Oliveira Lima
DISSERTAÇÃO DE CANDIDATURA AO GRAU DE MESTRE APRESENTADA À FACULDADE DE MEDICINA DA UNIVERSIDADE DO PORTO
Ao Prof. Doutor Rui Medeiros, orientador deste trabalho, por permitir a realização do mesmo, por me ter inserido no seu grupo de trabalho e por toda a paciência, dedicação, motivação e amizade. Em especial por confiar e acreditar no meu trabalho.
Ao Prof. Lúcio pela oportunidade de entrar no fascinante mundo da Oncologia e por todo o apoio constante.
Ao Núcleo Regional do Norte da Liga Portuguesa Contra o Cancro, em particular ao Dr. Vítor Veloso, por me ter concedido a bolsa que permitiu a realização deste trabalho.
Ao Dr. Francisco Lobo, Dr. António Morais e ao Dr. Fernando Calais da Silva pelo apoio na parte clínica.
Aos meus colegas do Grupo de Oncologia Molecular, por todo o apoio e alegria constantes. Em especial ao Ricardo, pela enorme ajuda na revisão deste trabalho.
À Ana Coelho e à Raquel toda ajuda, comentários na execução e escrita deste trabalho e em especial, o facto de se terem tornado boas amigas.
Aos meus grandes amigos André, Dennis e ao meu irmão pelo forte apoio, companhia e amizade que demonstraram desde sempre. Amigos como estes são difíceis de encontrar.
Ao Tiago, à Noggy e à Carina, por todos os bons momentos que me
À Helena, à Rita e à Di que embora tenham estado mais longe, o seu apoio, preocupação e amizade foram constantes.
À Lena por todo o amor e carinho constantes, por seres a razão da minha vida e por me dares força para acordar de manhã e enfrentar o dia.
AMO-TE MUITO...
A toda a minha família pelo apoio incondicional. Em especial aos meus Avós pelo carinho e por tudo o que fizeram por mim. Ao meu Pai e à minha Mãe por todos os sacríficios e por terem sempre acreditado em mim.
A ti Avó, quem me dera que tivesses aqui...
ABBREVIATIONS
A – Adenine
Apaf -1 – Apoptotic protease activating factor 1 APC – adenomatous polyposis coli
Bak – Bcl-2 homologous antagonist/killer Bax – Bcl-2–associated X protein
Bcl-2 – B-cell lymphoma 2 Bid – BCL-2 interacting domain BRCA1 – breast cancer 1
CAD – Caspase-activated DNase CI – Confidence interval
CpG - Cytosine and guanine separated by a phosphate CTL – Cytotoxic T cell
dATP – 2’-deoxyadenosine 5'-triphosphate DD – Death domain
DED - Death effector domain
DISC - Death-inducing signalling complex DNA – Deoxyribonucleic acid
dNTP – Deoxyribonucleotide triphosphate
DR5 – Decoy receptor 5
EDTA – Ethylene diamine tetracetic acid Egr-3 – Early growth response gene-3
FADD – Fas-associated death domain contain protein FasL – Fas ligand
G – Guanine
GAS – Interferon-gamma activated sequence
ICAD – Inihibitor of CAD
MHC – Major histocompatibility complex MMP – Matrix metalloproteinase
NF-AT – Nuclear factor of activated T-cells NF-κB – Nuclear factor-kappa B
NGF – Nerve growth factor NK – Natural killer
OR – Odds ratio
PBS – Phosphate buffer saline PCR – Polymerase chain reaction
PIN – Prostatic intraepithelial neoplasia
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PSA – Prostate specific antigen
RFLP – Restriction fragment length polymorphism RNA – Ribonucleic acid
RR – relative risk
SE – Standard error sFas – Soluble Fas sFasL – Soluble FasL
SNPs – Single nucleotide polymorphisms SPSS – Statistical package for social sciences
STAT1 – Signal transducers and activator of transcription protein 1
T – Thymine
TILs – Tumor-infiltrating lymphocytes TNF –Tumor necrosis factor
TRAIL – TNF-related apoptosis inducing ligand
UCC – Urothelial cell carcinoma UV – Ultra-violet
INDEX
ABSTRACT ... XVI RESUMO...XX
1 Introduction ... 1
1.1 Cancer ... 3
1.2 Cancer Biology... 6
1.3 Polymorphisms ... 9
1.4 Apoptosis ... 10
1.5 Fas/FasL pathway... 13
1.5.1 Fas receptor... 14
1.5.2 Fas ligand (FasL) ... 16
1.5.3 Fas/FasL activation... 19
1.5.4 Fas/FasL pathway and cancer ... 24
1.5.5 FAS and FASL genes polymorphisms ... 27
1.6 Prostate Cancer ... 29
1.6.1 Incidence and mortality ... 29
1.6.2 Risk factors ... 31
1.6.3 Early Diagnosis ... 32
1.6.4 Diagnostic, Grade and Stage ... 33
2 Objectives ... 35
2.1 General Objectives... 37
2.2 Specif Aims ... 37
3 Material and methods... 39
3.1 Study population (Cases and controls) ... 41
3.1.1 Prostate cancer patients ... 41
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3.2 DNA extraction ... 43
3.3 DNA amplification... 44
3.3.1 FAS–670A/G polymorphism... 44
3.3.2 FASL–844T/C polymorphism ... 44
3.3.3 Identification of the obtained fragments ... 45
3.4 Polymorphisms analysis... 47
3.4.1 Digestion of FAS–670A/G polymorphism ... 47
3.4.2 Digestion of FASL– 844T/C polymorphim ... 48
3.5 Statistical analysis ... 49
4 Results ... 51
4.1 Genotypic frequencies for FAS–670A/G and FASL– 844T/C polymorphisms... 53
4.2 Patients clinical characteristics and FAS and FASL polymorphisms genotypes ... 55
4.3 Gene-gene interaction... 59
4.4 Normal population comparison... 61
5 Discussion ... 65
6 Conclusion and future perspectives ... 75
7 References ... 79
8 APPENDIXES ... 99
FIGURES INDEX
Figure 1 – Schematic representation of multistep carcinogenesis... 4
Figure 2 – Acquired Capabilities of Cancer ... 7
Figure 3 – Events leading to apoptosis... 10
Figure 4 – The sequential ultrastructural seen in necrosis (left) and apoptosis (right). ... 11
Figure 5 – Apoptosis induced by a white blood cell ... 13
Figure 6 – Chromosome 10 ideogram, FAS gene region (10q24.1) ... 14
Figure 7 – FAS gene location at chromosome 10... 14
Figure 8 – Schematic representation of TNF/NGF receptor family members .. 15
Figure 9 – Schemactic illustration of TNF family members... 17
Figure 10 – Chromosome 1 ideogram showing FASL gene region (1q23) ... 17
Figure 11 – FASL gene location at chromosome 10 in q23 region ... 17
Figure 12 – FASL gene promoter region showing transcription factors regions.18 Figure 13 – CTL-mediated killing of target cells... 18
Figure 14 – Illustration evidencing Fas trimerization to bind with FasL... 19
Figure 15 - Apoptosis signaling by Fas/FasL system, DISC formation. ... 21
Figure 16 - Apoptosis signalling via the Fas receptor: the pathways of type I and type II cells ... 22
Figure 17 - Apoptotic signal transduction induced by Fas ligand... 24
Figure 18 - Germline and somatic mutations of the FAS gene ... 25
Figure 19 – Schematic representation of Fas-mediated apoptosis and the role of soluble decoys... 26
Figure 20 - The Fas counterattack... 27
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Figure 21 - Age-standardised incidence and mortality rates for prostate cancer in
the world at year 2002 ... 30
Figure 22 – Age-standardised (European) incidence and mortality rates for prostate cancer in EU countries, 2006 estimates ... 30
Figure 23 – Fragments identification in agarose gels. ... 46
Figure 24 – FAS–670A/G polymorphism genotyping... 47
Figure 25 – FASL–844T/C polymorphism genotyping ... 48
TABLES INDEX
TABLE 1. Patients clinical characteristics ... 42 TABLE 2. Prevalence and OR of FAS–670 and FASL–844 Genotypes Among Prostate Cancer Patients and Controls ... 53 TABLE 3. Patients Clinical Characteristics and FAS–670A/G and FASL–844T/C Genotypes ... 55 TABLE 4. FAS and FASL Genotype Distribution in Patients Stratified by PSA Level and Risk Assessment ... 56 TABLE 5. FAS and FASL Genotype Distribution in Patients Stratified by Gleason Grade and Risk Assessment ... 57 TABLE 6. FAS and FASL Genotype Distribution in Patients Stratified by Disease Status and Risk Assessment... 58 TABLE 7. Prevalence and OR of FAS–670 and FASL–844 Genotype Interaction Among Prostate Cancer Patients and Controls ... 59 TABLE 8. FAS and FASL Genotype Interaction Distribution in Patients Stratified by PSA Level, Gleason Grade and Disease Status and Risk Assessment ... 60 TABLE 9. Comparative Study of FAS–670A/G Genotype Frequencies in Normal Controls from Different Populations... 62 TABLE 10. Comparative Study of FASL–844T/C Genotype Frequencies in Normal Controls from Different Populations... 63
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The Fas/FasL system is one of the major pathways in apoptosis and is important in the regulation of cell proliferation and tumor cell growth. Functional promoter polymorphisms on Fas receptor gene (FAS–670A/G) and in its ligand (FASL–844T/C) alter their transcriptional activity. The role of FAS and FASL polymorphisms in prostate cancer has not been studied.
Using the PCR-based restriction fragment-length polymorphism methodology, FAS gene locus -670 and FASL gene locus -844 genotypes were evaluated in DNA samples from 936 men: 674 prostate cancer patients and 262 healthy controls.
It was found that FAS–670 AG and GG genotypes represent a significantly protection for extra-capsular invasion. Taken together, these data show a significantly 72% protection was found for G allele carriers. A protective association between FASL–844 CC genotype for higher PSA levels was also found.
It is well known that FAS–670 G allele reduces the transcriptional activity of FAS gene and FASL–844 CC genotype is associated with higher expression of FasL. It can be suggested that FAS–670 G allele may reduce sFas levels, which derive from FAS gene by alternative splicing, preventing the apoptotic inhibition caused by the soluble form. On the other hand, FASL–844 CC genotype appears to enhance apoptosis of prostate cancer cells reducing PSA levels.
Therefore, FAS and FASL polymorphisms might be involved in prostate cancer development.
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O sistema Fas/FasL é uma das vias de apoptose mais importantes, sendo essencial na regulação da proliferação celular e do crescimento tumoral.
Polimorfismos funcionais nos promotores dos genes do receptor Fas (FAS–
670A/G) e no seu ligando (FASL–844T/C) parecem alterar a transcrição destes genes. Ainda não foi estudado o papel dos polimorfismos FAS–670A/G e FASL–
844T/C no cancro da próstata.
Recorrendo à técnica de PCR – RFLP foram analisadas amostras de DNA de 936 indivíduos do sexo masculino: 657 dos quais pacientes com carcinoma da próstata e 247 dadores sem doença oncológica.
Os resultados deste estudo mostram um efeito protector nos portadores dos genótipos AG e GG do polimorfismo FAS–670 para invasão extra-capsular.
Os indivíduos portadores do alelo G possuem uma protecção de 72% para doença avançada. Foi também demonstrada uma associação estatisticamente significativa entre o genótipo CC do polimorfismo FASL–844 e níveis de PSA elevados.
Estes resultados sugerem que o alelo G do polimorfismo FAS–670 poderá reduzir os níveis de sFAS, que resulta de “splicing” alternativo do gene FAS, evitando assim o efeito inibidor da apoptose desta forma solúvel. Por outro lado, o genótipo CC do polimorfismo FASL–844 parece aumentar a apoptose das células tumorais de carcinoma da próstata, reduzindo os níveis de PSA.
Assim, os polimorfismos dos genes FAS e FASL poderão estar envolvidos no desenvolvimento do carcinoma da próstata.
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1.1 Cancer
Cancer is a leading cause of death worldwide, only overcomed by cardiovascular diseases, responsible for 13% of all death worldwide and 10 million newly cases are detected every year [1, 2]. In Portugal cancer-associated mortality follows worlds tendency [3].
Cancer is a group of diseases which share common features. It may affect any organ or tissue in the body, and the disease characteristics may differ from organ to organ [4].
The word neoplasia comes from the Greek neo + plasia meaning literally
“new growth” and new growth is a neoplasm. The term tumor was originally applied to the swelling caused by inflammation. Neoplasms may also induce swellings, but by long precedent, the non-neoplastic usage of tumor has passed into limbo; thus, in clinical practice, neoplasm and tumor are used interchangeably [5]. There are two large classes of neoplasms: benign tumors and malignant tumors.
Generally, a benign tumor grows slowly and remains localized. Although it pushes surrounding normal tissue aside, it does not infiltrate adjacent tissues or spread by blood and lymphatic channels to distant sites. Usually, a benign tumor can be completely removed surgically without difficulty. Histologically, the cells in a benign tumor appear mature and closely resemble the normal cells from which the tumor was derived [6].
Opposite to a benign tumor, malignant neoplasms are composed of less well-differentiated cells, grows more rapidly, and infiltrates the surrounding tissues rather than growing by expansion. Frequently, the infiltrating strands of tumor find
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their way into the vascular and lymphatic channels. Tumor cells may be carried in the lymphatics to reach the lymph nodes, where they establish secondary sites of tumor growth not connected with the originally tumor. Tumor cells may also gain access to the bloodstream and be carried to distant sites, leading to secondary tumor deposits throughout the body (metastasis) [6].
The continuous cells proliferation and the acquisition of genetic alterations are the basis of the process of tumor emergence – carcinogenesis. This usually slow multistep transformation process of normal cells into neoplastic cells, during several years, involves three steps: initiation, promotion/transformation and progression (Figure 1).
Figure 1 – Schematic representation of multistep carcinogenesis [7].
Initiation is characterized by alteration of the cell’s genetic material leading to a non-lethal mutation through the action of a carcinogenic agent [4]. Promotion and transformation are the longer phases of carcinogenesis and consist in genetic defects accumulation giving selective advantage to an initiated cell, that becomes
aggressive depending on their metastatic profile (invasion and growth in other tissues and organs).
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1.2 Cancer Biology
It is widely refered that cancer is a complex disease. Several studies have previously shown that numerous genetic events are involved in carcinogenesis, although the molecular mechanisms implicated in tumor development remain largely unknown.
Dynamic alterations in multiple sites of the genome are a cancer cell characteristic property. Carcinogenesis involves several steps which reflects the genetic alterations that promote progressive malignant transformation of normal cells [10]. Non-lethal damage in DNA are the ground for of carcinogenesis, and it can be either inherited or acquired throughout life by the action of environmental agents exposure (chemical compounds, radiation and infectious agents) [4]. The exact number of DNA alterations necessary for tumor development is still unknown and depends on the type of alteration, or tumor. Actually, the mainstay of cancer research is to identify these alterations, develop new therapeutic targets and prevention strategies, to achieve successful treatments [11].
Malignant tumors are the result of several DNA alterations initially in a single cell, and then passed to its clones, that origin loss of normal function, uncontrolled cell growth, invasion of adjacent tissues and eventually metastasis.
The progression from normal to tumor cell is a slow process involving accumulation of genetic modifications in proto-oncogenes (genes which induces cell proliferation), tumor suppressor genes (genes generally involved in cell division inhibition), DNA repair genes and apoptosis regulation genes [8].
proliferative autonomy that must be abrogated for cancers to arise. They enumerated six essential properties which must be altered to dictate malignant growth: self-sufficiency in growth signals; insensitivity to growth-inhibitory signals;
evasion to programmed cell death; limitless replicative potential; sustained angiogenesis; and tissue invasion and metastasis (Figure 2) [10].
Figure 2 – Acquired Capabilities of Cancer: diagram representing the six properties of cancer [10]
The acquisition of these alterations could be different in terms of mechanism and timeline. The number of mutations needed to obtain certain properties could also vary leading yet to the same result [11]. On the other hand, cellular mechanisms that are necessary to prevent carcinogenesis are different between individuals, due to inter-individual genetic variability of polymorphic genes that regulates those processes [12].
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Host genetic variability may account for the explanation of unknown cancer development susceptibilities. Genes involved in susceptibility might be stratified according to their penetrance, in high penetrance genes, generally implicated in hereditary cancer, such as BRCA1 and APC genes, and low penetrance genes generally involved in sporadic cancer, which are common genes with minor allelic variants that influence cancer [13].
In the last years, low penetrance genes as those involved in DNA repair, maintenance of genomic integrity, proliferation, differentiation, metabolism or in apoptosis became an important research target. Although these genes have a minor impact in terms of individual cancer risk, they might be important when analyzed the population attributable risk. These findings may help develop prevention and treatment strategies for high risk individuals [12].
Host characteristics influence neoplasia development; therefore it is essential to understand individual genetic variants (i.e. polymorphisms) to define a genetic profile that will allow stratification of individuals risk groups for cancer development.
Molecular epidemiology stands in the evaluation of potential genetic and environmental risk factors, analyzed at molecular level, in the contribution to etiology, distribution and worldwide prevention of the cancer.
1.3 Polymorphisms
Polymorphisms are DNA sequence alterations that exist in normal population, being present in, at least, 1% of the population [14]. The most common variations in human genome are single nucleotide polymorphisms (SNPs), which are polymorphisms with only one nucleotide substitution [15].
These genetic variants are defined as low penetrance susceptibility alleles, providing an altered risk for cancer development. This risk appears to be influenced by individual SNPs profile in key genes for cancer susceptibility [14].
The association between exposure factor (polymorphism) and the disease is evaluated by relative risk (RR) estimation, indicating the probability of disease development in the group of polymorphic variant carriers. The great majority of molecular epidemiology studies on cancer are of case-control type; therefore RR is evaluated through Odds Ratio (OR). OR represents an association magnitude and supplies helpful information on causality and definition of attributable risk, which is the proportion of all cases that is attributed to the risk factor [16].
SNPs and haplotypes analysis in cancer research may contribute to the determination of high risk groups and help cancer prevention and development of new therapeutic orientations.
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1.4 Apoptosis
Apoptosis is important in developing organisms and in eliminating unwanted or potentially dangerous cells (Figure 3). Abnormal regulation of apoptosis is implicated in the development of certain diseases, such as viral infections, autoimmune diseases, neurodegenerative disorders, immunologic deficiencies and cancer. The acquired ability to resist the apoptotic stimuli is one of the primary characteristics of a malignant cell, from which alterations in components of apoptotic pathways emerge as key mechanism in cancer development [17].
Figure 3 – Events leading to apoptosis. In cells unable to repair genetic damage, apoptosis has a key role in their elimination [18].
Apoptosis can be distinguished from necrosis, which occurs as a result of injury, complement attack, severe hypoxia and hyperthermia leading to cell death accompanied by inflammation. The Greek word apoptosis, meaning “dropping off”
or “falling off” (as in petals from flowers or leaves from trees), was first proposed in 1972 by Kerr and colleagues [19] to designate the cell death process that is morphologically accompanied by cell shrinkage, membrane blebbing, chromatin condensation, genomic autodigestion into nucleosomal fragments and phagocytosis by the neighboring cells [20] (Figure 4).
Figure 4 – The sequential ultrastructural seen in necrosis (left) and apoptosis (right) [5].
Two main pathways of apoptosis, known as intrinsic and extrinsic pathways have been described. In the intrinsic pathway signals come from within the cell, namely the mitochondria, which acts as an integrating sensor of multiple death insults releasing cytochrome-c to the cytosol that will trigger caspases activation [21]. On the opposite, the extrinsic pathway requires interaction of cell surface
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molecules (transmembrane death receptors) with respective ligands, triggering the recruitment and assembly of multiprotein complexes that activate downstream caspases. Tumor cells can be eliminated by cytotoxic immune cells through this mechanism [21].
1.5 Fas/FasL pathway
The Fas/FasL system is one of the major pathways in apoptosis and is important to regulate cell proliferation and tumor cell growth. Fas (also known as CD95 or APO-1) is a cell surface receptor that interacts with its natural ligand FasL (also known as CD95L) to initiate the death signal cascade, resulting in apoptotic cell death [22, 23].
Fas and FasL play an important roles in various types of physiologic apoptosis [24]: elimination of self-reactive T cells during peripheral clonal selection;
deletion of activated mature T cells at the end of an immune response; elimination of target cells such as virus-infected cells or cancer cells by cytotoxic T lymphocytes (CTLs) and by natural killer (NK) cells (Figure 5); deletion of self- reacting B cells; and killing of inflammatory cells at “immune-privileged” sites such as the eye.
Figure 5 – Apoptosis induced by a white blood cell [18]
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1.5.1 Fas receptor
The Fas receptor was discovered in 1989 by two groups, Trauth and colleagues who named it APO-1 [23], and by Yonehara and co-workers who also described a cell surface molecule named Fas that could be triggered to induce cytotoxicity by an agonistic monoclonal antibody [25]. Later sequencing and cloning of those proteins showed that these two molecules were the same [26].
Fas is widely expressed, with predominant expression in thymocytes and activated T cells and abundant expression in the liver, heart, kidney and lung [27, 28]. FAS gene is encoded in 9 exons, spanning a 12kb region on human chromosome 10 at q24.1 (Figures 6 and 7) [29, 30].
Figure 6 – Chromosome 10 ideogram, FAS gene region (10q24.1) is highlighted (EntrezGene, NCBI®)
Figure 7 – FAS gene location at chromosome 10 (EntrezGene, NCBI®)
Structurally, Fas is a type I transmembrane cell surface receptor of approximately 45 to 52 kDa (335 amino acids) containing three cysteine-rich extracellular domains at the amino-terminus, which are responsible for ligand binding, and an intracytoplasmic death domain (DD) of about 80 amino acids that is essential for transducing the apoptotic signal [31, 32].
Fas belongs to the tumor necrosis factor (TNF)/nerve growth factor (NGF) receptor family [32], which includes Fas, type I and II TNF receptors (TNFR1 and TNFR2), the low affinity NGF receptor, B cell antigen CD40, T cell antigen OX40, CD27, 4-1BB and Hodgkin’s lymphoma cell surface antigen CD30 (Figure 8) [32].
New members were added to this family, such as death receptor 3 (DR3), and two receptors for TNF-related apoptosis inducing ligand (TRAIL), DR4 and DR5 [33].
Members of this family have an extracellular region rich in cystine residues that can be divided in 3-6 subdomains. The overall molecular homology of Fas with other members of the family is around 24-30% [32], and a strong similarity in the cytoplasmic domain between Fas and TNFR1 was shown, indicating that the conserved domain is essential for apoptotic signal transduction [34].
Figure 8 – Schematic representation of TNF/NGF receptor family members, which includes Fas receptor [35]
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The soluble form of Fas receptor (sFas) is generated by alternative splicing and lacks the transmembrane domain [36, 37]. Hence, soluble Fas has not the capability of transducing apoptotic signaling after binding to FasL and competes with transmembrane Fas for FasL binding, antagonizing Fas-FasL apoptotic pathway [37]. Concordantly, aberrant expression of soluble Fas is mechanistically involved in the pathogenesis of certain autoimmune diseases [38-40] and is present in various types of cancer [41-45].
1.5.2 Fas ligand (FasL)
Cytokines are a family of proteins that regulate cellular proliferation and differentiation by binding to their specific receptors on target cells. Cytokines are grouped into at least three subfamilies based on structure, cysteine-knot growth factors, tumor necrosis factor, and helical cytokines. FasL was first identified in 1993 by Suda and co-workers [22] and belongs to the TNF family which includes TNF, lymphotoxin, CD30 ligand, 4-1BB ligand, CD40 ligand, CD27 ligand, and TRAIL (Figure 9) [22].
Figure 9 – Schemactic illustration of TNF family members, where FasL belongs [35].
FasL is synthesized as a type II–membrane protein and its extracellular region of about 150 amino acids is well conserved (20–25%) among members of the TNF family, while the length and sequence of the cytoplasmic segments differ significantly [22]. FASL gene is encoded in five exons and spans approximately 8kb on chromosome 1q23 (Figure 10 and 11) [46]. FasL expression is transcriptionaly regulated by NF-kB, NF-AT, early growth response gene-3 (Egr-3) through binding at the 5’ flanking region of the FasL gene (Figure 12) and several other uncharacterized regions in FasL promoter [47, 48].
Figure 10 – Chromosome 1 ideogram showing FASL gene region (1q23) (NCBI Map Viewer, NCBI®)
Figure 11 – FASL gene location at chromosome 10 in q23 region (EntrezGene, NCBI®)
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Figure 12 – FASL gene promoter region showing transcription factors regions [49].
This ligand is predominantly expressed in activated T lymphocytes and NK cells [50, 51] and acts as an effector for CTLs and NK cells to remove cells infected by virus or cancer cells. It is also constitutively expressed in “immune- privileged” sites, such as the eye and testis [52, 53] and is important on T cell control and apoptosis after immune reaction. In the CTL reaction the tumor cell expresses tumor antigens as a complex with MHC. Then the interaction of CTL with these cells activates the CTL through T cell receptor, inducing the FASL gene, and thereafter FasL binds to Fas on target cell, causing apoptosis (Figure 13).
Figure 13 – CTL-mediated killing of target cells. Tumor cells present antigens complexed with MHC. The cytotoxic T cells recognize the antigen and become active, leading to the
Tumor cell
FasL can also occur in a soluble form (sFasL); it can be generated as a posttranslational modification by proteolytic cleavage by matrix metalloproteinases (MMPs) [55, 56]. This form has been detected in normal and malignant cells [57- 59] and maintain apoptotic capacity even after being shed from cell membrane of effector cells [60]. The cytotoxic potential of sFasL is significantly diminished when compared to membrane bound FasL [60]. FasL works locally via cell-cell interactions under physiological conditions and the purpose of shedding FasL is to attenuate the process. The soluble form of human FasL exists as a trimer, suggesting that membrane-bound FasL also has the potential to form a trimeric structure [61].
1.5.3 Fas/FasL activation
Fas, a homotrimeric structure, it must oligomerize to be activated, therefore, dimerization with FasL is not sufficient to activate this receptor. FasL induces trimerization of Fas and the trimerized cytoplasmatic region transduces the signal (Figure 14) [24].
Figure 14 – Illustration evidencing Fas trimerization to bind with FasL [62].
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Fas-mediated apoptosis does not require RNA or protein synthesis [25, 32], and even enucleated cells undergo apoptosis by Fas activation [63]. This suggests that all the components necessary for apoptotic signal transduction are present in growing cells, and that Fas activation triggers this mechanism.
Molecular mechanisms of signaling initiation through Fas are largely unknown. Nevertheless, general aspects of this initiation are known [31]; Fas contains a protein-protein interaction domain in its cytoplasmic region termed the death domain (DD), a characteristic region of the death receptor subfamily of the TNF receptor superfamily [64]. After Fas and FasL binding, Fas becomes competent to form death-inducing signalling complex (DISC), and in this complex the first molecule that is linked to Fas by interaction with DD is Fas-associated death domain contain protein (FADD) [65, 66]. FADD present another protein–
protein interaction domain at its N-terminus, termed death effector domain (DED), which is required for the recruitment of caspases to the DISC and is responsible for downstream signaling transduction [67] (Figure 15).
Figure 15 - Apoptosis signaling by Fas/FasL system, DISC formation. DD, death domain;
DED, death effector domain; FADD, Fas-associated death domain contain protein [33].
Caspases are cysteine proteases that cleave substrates at aspartic acid residues and are synthesized as relatively inactive zymogens called pro-caspases [68]. These proteases are responsible for apoptosis, in which several of them are involved in both initiation and execution of the apoptotic program. The effector caspases (including caspases 3, 7, and 6) are responsible for most of the proteins cleavage, which induces the major morphological changes observed during apoptosis. Initiation caspases are the first to be activated in response to a pro- apoptotic stimulus and begin a cascade of increasing caspase activity through cleavage and activation of effector caspases [68].
Caspase-8 is the main initiator in Fas signalling, which is recruited into DISC upon binding of FADD. It carries two DED at the N-terminal region that will bind to FADD. Therefore, the high local concentration of caspase-8 is believed to lead to its autoproteolytic cleavage and activation [69].
Apoptosis downstream of DISC usually proceeds independently of mitochondria influence. Cells presenting DISC-activated caspase-8 that will lead to the rapid activation of caspase-3 and cell death, are known as type I cells. In some cells, however, DISC formation following Fas stimulation is strongly reduced (type II cells). In these cells, mitochondria plays an essential role as signal amplifiers (Figure 16) [70]. This mitochondrial or ‘intrinsic’ apoptosis pathway is activated by caspase-8-mediated cleavage of the Bcl-2 family member, Bid. Truncated Bid translocates to the mitochondria, where it can induce both the oligomerization of pro-apoptotic Bax and/or Bak in the membrane and the release of pro-apoptotic molecules, including cytochrome c, from the mitochondrial intermembrane space.
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Cytochrome c can then associate with the scaffolding protein Apaf-1, dATP and pro-caspase-9 to form a high-molecular mass complex called the apoptosome, which activates pro-caspase-9 and then caspase-3, resulting in cell death [31].
Figure 16 - Apoptosis signalling via the Fas receptor: the pathways of type I and type II cells [71].
In addition to the morphological changes of cells and their nuclei, apoptosis is characterized by the degradation of chromosomal DNA into nucleosomal units.
Fas activation also causes chromosomal DNA rapid degradation, and is dependent on the activation of caspases. Biochemical analysis of this step indicated that there is a specific DNase (CAD, caspase-activated DNase) that is activated during apoptosis [72]. CAD, a protein of about 40 kDa with a putative nuclear localization signal at the C terminus, is ubiquitously expressed in various tissues (44). In growing cells, CAD is complexed with its inhibitor, ICAD (inhibitor of CAD), a protein of about 45 kDa [73, 74]. Caspases 3 and 7 can cleave ICAD at two positions (amino acids 117 and 224), inactivating the CAD-binding and inhibitory activity of ICAD [74, 75]. CAD, thus released from ICAD, cleaves the chromosomal DNA (Figure 17).
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Figure 17 - Apoptotic signal transduction induced by Fas ligand. Evidencing activated caspase 3 that cleave ICAD and releases a specific DNase (CAD), which causes degradation of chromosomal DNA.
After cell death by apoptosis, it is phagocyted by neighbouring macrophages and neutrophils. Apoptosis is intended to remove virally infected or cancerous cells that may carry damage to DNA. If apoptotic cells carrying intact DNA were phagocyted, the damaged or viral DNA might also be transferred to the phagocytic cells, and might transform them. The cleavage of chromosomal DNA during apoptosis may be a mechanism for avoiding this outcome [76].
1.5.4 Fas/FasL pathway and cancer
The Fas/FasL pathway is a complicated process under multiple internal and external influences. Abnormalities and functional inactivation in this pathway may contribute to tumor development and progression.
The most basic requirement for normal functioning of the death receptor pathways is that the receptor is expressed on the tumor cell surface to allow receptor-ligand interaction. A decrease or loss of Fas expression has been implicated in tumor progression in several cancers [77, 78]. Furthermore, loss of Fas and gain of FasL expression may vary as a function of the degree of dedifferentiation in malignant cells [79]. Therefore, correlation between the degree of malignant progression and levels of FasL expression support this molecule has a probable diagnostic and prognostic marker in some tumors [80-82].
most common epigenetic modification, occurs when a methyl group is added to a cytosine in CpG dinucleotides. DNA hypermethylation, that is methylation in normally unmethylated gene sequences at promoter regions of certain genes, may silence gene transcription and, thereby, act as a carcinogenic event. FAS methylation status has been investigated in some tumor types, including prostate cancer, and associated with Fas expression downregulation [83, 84].
One of the mechanisms contributing to malignant cells resistance to FasL- mediated apoptosis involves mutations of the FAS gene, in which exon 9 has been identified as a mutational hotspot in various tumor types (Figure 18), including prostatic tumors [85-88].
Figure 18 - Germline and somatic mutations of the FAS gene are related to malignancy.
Structure of FAS gene, showing point mutations on exon 9, a hotspot in solid tumors. Point mutations are depicted by vertical lines within the respective exons; arrowhead point mutations generating a stop codon or frameshift. In exon 9, the positions of the point mutations are not to scale, as for some nucleotide positions multiple mutations were encountered [79].
Other mechanisms that can help cancer cells to evade cytotoxic T cell attack are solube decoy receptors. These receptors are thought to be released from the tumors and to act as competitive inhibitors for membrane bound receptors, effectively shielding the tumor from attack. sFas is one of these soluble
Mutations at the FAS gene
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decoys and increased sFas levels, which have been detected in the serum of patients with various types of cancer including bladder and prostate cancer, may possibly act as a prognostic indicator of poor outcome in these diseases [41, 43, 89]. Another decoy receptor for FasL is DcR3, which is also a member of the TNF receptor family with no transmembrane domain and is secreted from the cells. This protein binds FasL as efficiently as the authentic Fas receptor, and seems to neutralize the action of FasL. The DcR3 gene is located at human chromosome 20q13 and is significantly amplified in 50% of primary lung and colon tumors [90]
and overexpressed in various types of cancer [91-94], supporting the neutralization of FasL hypothesis (Figure 19)
Figure 19 – Schematic representation of Fas-mediated apoptosis and the role of soluble decoys [95].
Since activated T lymphocytes, particularly tumor-infiltrating lymphocytes (TILs), are sensitive to Fas-induced apoptosis, FasL expression is involved in
100]. This might protect the tumor cells against FasL-induced apoptosis while at the same time any activated T-cell presenting Fas on its surface, and attacking the tumor, would be killed (Figure 20). The same mechanism is used to establish
“immune-privilege” and could explain why cancer patients' immune system fail to eliminate the tumor [71].
Figure 20 - The Fas counterattack. Following recognition of tumor antigens bound to major histocompatibility complex (MHC) molecules on the surface of tumor cells, T cells upregulate FasL expression. Cancer cells are frequently resistant to Fas-mediated apoptosis, resulting in insensitivity of the tumor cells towards T cell-expressed FasL and tumor survival. By contrast, many cancers express FasL and can therefore counterattack and eliminate Fas-sensitive tumor- infiltrating T cells. Ag, antigen; TCR, T cell receptor [71].
1.5.5 FAS and FASL genes polymorphisms
The first study to find genetic polymorphisms in the promotor region of FAS gene was performed by Huang and co-workers [101]. Two polymorphisms were identified, and one of them is a substitution of adenine (A) to guanine (G) at locus - 670 (FAS–670A/G) [101]. This functional polymorphism is located at the enhancer region and abolishes the binding site of nuclear transcription element GAS [101]
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and decreases the binding ability to a GAS-binding protein, STAT1, thus diminishing the promoter activity and decreasing FAS-gene expression [102]. The other polymorphism G (to A substitution) was found at position -1377 of the promoter silencer region (FAS–1377G/A) and it alters the transcription factor SP-1 binding site and thus, the binding of SP-1 is less efficient [103].
The promoter region of FASL also has a functional SNP, reported by Wu and colleagues [49]. A thymine (T) to cytosine (C) transition at position -844 (FASL–844T/C) which is located in a binding motif for another transcription factor, the CAAT/enhancer-binding protein β [49]. In the same study it was shown that a higher basal expression of FasL was significantly associated with –844 C allele compared with –844 T allele [49].
Polymorphisms in the promoter region of FAS and FASL genes alter the transcriptional activity of these genes, which may impact significantly in the Fas/FasL pathway, and they are associated with a higher cancer risk in various models [103-109]. However, to the best of our knowledge, there are no studies regarding the association of any of these genes in prostate cancer, where these is sufficient amount of evidence to support biological plausibility for its influence in prostate cancer development.
1.6 Prostate Cancer
1.6.1 Incidence and mortality
Prostate cancer is one of the most commonly diagnosed neoplasias and a leading cause of death by cancer in men, worldwide [1]. Conversely, incidence and mortality rates vary according to geographic location (Figure 21). There are low incidence rates in countries such as Japan and China (12.6 and 1.6 per 100 000 habitants, respectively), which are lower than those found in Western countries (e.g. in 2002 at Northen America, prostate cancer incidence was 119.9/100 000) [1]. African Americans present a 70% higher incidence of prostate cancer when compared with Caucasian Americans. However, black individuals’
incidence in Africa is 4 times lower than in the USA [1, 110].
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Figure 21 - Age-standardised incidence and mortality rates for prostate cancer in the world at year 2002 [1].
In 2002, Western and Northern European countries had the highest incidence rates of prostate cancer in Europe (approximately 61.6 and 57.4 per 100 000 habitants, respectively). Eastern European countries present the lowest incidence rates, 17.3 per 100 000 habitants [111, 112]. The 2006 estimates for European prostate cancer incidence are similar to 2002, and are evidenced in Figure 22.
Figure 22 – Age-standardised (European) incidence and mortality rates for prostate cancer in EU countries, 2006 estimates [113].
In Portugal, prostate cancer incidence in the year 2006 was 101.2 per 100 000 habitants [112]. In the North region it was observed an incidence rates of 75.6 per 100 000 in the year 2000 [114].
Similarly to incidence rates, there are differences in mortality among geographic regions and demographic ethnic groups. The highest mortality rate was found in the Caribbean region (28.0 per 100 000), while Northen America have a 15.8 per 100 000 habitants mortality rate due to prostate cancer that is similar to Southern Europe [1] (Figure 21). In Portugal, prostate cancer is the second leading cause of death from cancer and is responsible for 12% of all cancer related deaths [3].
1.6.2 Risk factors
Despite prostate cancer high incidence and morbidity, its aetiology remains obscure. Advanced age, race, and familial history are well established risk factors [115]. Other putative risk factors, including androgens, diet, physical activity, sexual factors, inflammation, and obesity, have all been implicated albeit their roles in prostate cancer aetio-pathology remain controversial.
Age is a major risk factor for prostate cancer and there are studies estimating that 30% of men older than 50 years have the disease and that prevalence increases from 12% in 40 years old men to 43% in those with 80 years old [115]. Conversely, studies revealed that higher circulating levels of testosterone might explain the differences in incidence between African Americans and Caucasians, tumor aggressiveness and mortality from prostate cancer [115, 116].
The role of environment, diet and social habits have been subject of several studies, and it was observed that individuals migration from countries with low prostate cancer incidence and mortality rates into countries with higher rates,
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increases risk for prostate cancer. As an example, although native Japanese have a low risk for prostate cancer, after immigration Japanese Americans have the same or higher incidence than native Americans [115, 117, 118].
Another postulated cause for increased cancer risk is the ingestion of saturated fat [119]. Albeit several studies support a role for fat-rich diets in prostate cancer pathogenesis, the relevance of such an association is still controversial [115, 119, 120].
Familial history is an important risk factor for developing prostate cancer [121]. Men with first degree relatives with prostate cancer have a 2-fold higher risk for being diagnosed with prostate cancer. Nevertheless, only a reduced percent of prostate cancer (10%) are due to hereditary transmission, and a great majority of cases are sporadic [121].
Although many known environmental, genetic and biological risk factors have been uncovered, worldwide differences in incidence are due to unshared access to prostate cancer screening in some populations or ethnic groups.
However, prostate cancer screening seems unlikely to explain the nearly 60-fold difference in prostate cancer risk between high- and low-risk populations [115], suggesting that other factors, such as host genetic profile, might influence susceptibility and prostate cancer course [122-129].
1.6.3 Early Diagnosis
Prostate cancer screening in men after 40-45 years old includes at least
biopsy. Definite diagnosis includes histological documentation of malignant transformation in prostatic tissue from biopsy specimens.
PSA discovery has given a great impulse to prostate cancer early detection programs [130], and dramatically changed the way prostate cancer is followed and diagnosed and emerged as an useful diagnostic tool for early detection and prostate cancer screening. PSA, which is released in serum by both benign and malignant prostate tissue, is organ specific but not cancer specific, since several non cancer conditions may elevate serum PSA. Men with suspected prostate cancer due to elevated PSA are more prone to be diagnosed at an initial stage of disease. Individuals with localized tumors at time of diagnosis were found to have a prolonged survival when compared with higher stages tumors [130-132].
1.6.4 Diagnostic, Grade and Stage
The adenocarcinoma is the most common type of prostate malignant tumor, corresponding to 95% of prostate cancer. Biological behaviour of prostate cancer varies greatly and complete characterization includes size (tumor volume), grade, local extension (extracapsular invasion) and distant metastasis. Tumor volume is important to predict patients overall survival, but is difficult to evaluate accurately before surgery.
The Gleason grading system for prostatic carcinoma is the dominant method around the world in research and in routine Pathology practice. This system is based entirely on the extent of glandular differentiation and the pattern of growth of the tumor in the prostatic stroma [133, 134]. High score tumors are more aggressive and often metastasize.
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Tumor staging describe tumor extent at a given point in time. Tumor extent is considered to predict natural course of disease and, thereby, have decisive influence in therapeutic decisions. The TNM classification (T - primary tumor, N - lymph node status, and M - distant metastasis) is widely used to stage disease status in prostate cancer patients. It is a useful tool for predicting prognosis and to plan and evaluate treatment.
2. OBJECTIVES
2.1 General Objectives
Evaluate the influence of FAS–670A/G and FASL–844T/C polymorphisms in individual susceptibility and development of prostate cancer.
2.2 Specif Aims
Analyse FAS and FASL polymorphisms genotypes frequencies in prostate cancer patients and control individuals.
Evaluate the association between FAS and FASL polymorphisms genotypes and patients clinical characteristics.
Analyze gene-gene interaction within FAS–670 and FASL–844 polymorphisms.
Compare genotype frequencies of FAS and FASL polymorphisms between Portuguese and other reported studies in different populations.
3. MATERIALS & METHODS
3.1 Study population (Cases and controls)
The studied population included DNA samples from 936 male individuals.
From these, 674 were consecutive prostate cancer patients and 262 constituted the control group composed by healthy donors recruited from the Institute’s blood donors’ bank, with no evidence of prostatic disease or other oncologic malignancy.
The controls mean age was 41.2 years (standard error, SE, 0.724) and the median 42.0 years. All samples were obtained with the informed consent of the participants before their inclusion in the study, according to the declaration of Helsinki.
3.1.1 Prostate cancer patients
DNA samples from 657 individuals with prostate cancer diagnosed at Instituto Português de Oncologia (Porto) and Centro Hospitalar de Lisboa Central were included in this study. The mean age for cases was 67.4 years (SE 0.307) and the median 67.0 years. A total of 624 prostate cancer cases were considered with complete data for statistical analysis, from which 370 cases had localized prostate disease and 254 cases had advanced disease (invasion and extension beyond the capsule and/or to the adjacent tissue, or involving regional lymph nodes or distant metastatic sites). Clinical characteristics including Gleason grade, tumor stage and age at diagnosis were obtained from medical records. Patients’
clinical characteristics are summarized in Table 1.
TABLE 1. Patients clinical characteristics FAS–670 Frequency %
PSA
< 10 290 48.8
> 10 304 51.2
Total 594 100
Gleason grade
< 7 274 48.6
≥ 7 295 51.4
Total 574 100
Disease Status
Localized 370 59.3
Advanced 254 40.7
Total 624 100
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3.2 DNA extraction
Blood samples were collected using a standard technique to EDTA containing tubes. Genomic DNA was extracted from peripheral blood leukocytes by an adapted salting-out method, according to a previously reported protocol [135].
First, a hypotonic solution (AKE – Appendix I) was added to whole blood samples to promote erythrocyte lysis and it was incubated for 30min at 4ºC. Then, it was centrifuged at 2500rpm for 10min, the supernatant was removed and the pellet ressuspended in AKE solution. After repeating the centrifugation step, the supernatant was despised and the pellet re-suspended in PBS (Appendix I), followed by another centrifugation at 2500rpm for 10min.
A pellet of nucleated cells was obtained after removal of the supernatant and it was added 4ml of Cell Lysis Solution (Gentra Systems), in order to promote leucocyte lysis. Then, 1ml of Protein Precipitation Solution (Gentra Systems) was added to the cell lysate, in order to provoke protein precipitation (salting out) which should form a white pellet. An equal volume of 100% Isopropanol was added to the supernatant (which contains the DNA) and the solution was mixed by inverting gently 50 times. The DNA condensed in the solution was removed to a microcentrifuge tube containing 0.5ml of 70% Ethanol for 24h.
After this period, the DNA was removed to a safe-lock 1.5ml microcentrifuge tube and let it air dry. When it was dried the DNA was hydrated in bidistilled water and stored at 4ºC.
3.3 DNA amplification
The FAS and FASL gene fragments were amplified using polymerase chain reaction (PCR) technique.
3.3.1 FAS–670A/G polymorphism
The primers used in the amplification of FAS gene promoter region, in order to obtain a 193 bp fragment were: FAS-F (forward): 5’-ATA GCT GGG GCT ATG CGA TT-3’ and FAS-R (reverse): 5’-CAT TTG ACT GGG CTG TCC AT-3’
(Metabion, Martinsried, Deutschland). PCR reaction mixture was prepared as follows: 100 ng of genomic DNA was added to 0.5 mM of each primer, 0.2 mM of each deoxyribonucleotide triphosphate (dNTP) (Fermentas, Vilnius, Lithuania), 2.0 mM MgCl2, 1X Taq buffer and 1U of Taq DNA polymerase (Promega, Madison, WI) to a final volume of 50 µl. The amplification conditions were 95ºC during 5 min for the initial denaturation step, followed by 35 cycles of denaturation at 94ºC (1 min), annealing at 55ºC (45 s) and extension at 72ºC (1 min). The final extension step consisted of 5 min at 72ºC. As a negative control, PCR mix without DNA sample was used to ensure the contamination-free PCR product.
3.3.2 FASL–844T/C polymorphism
The primers used in the amplification of FASL gene promoter region, in order to obtain a 401 bp fragment were: FASL-F (forward): 5’- CAG CTA CTC GGA GGC CAA G -3’ and FASL-R (reverse): 5’- GCT CTG AGG GGA GAG ACC
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AT-3’ (Metabion, Martinsried, Deutschland). PCR reaction mixture was prepared as follows: 100 ng of genomic DNA was added to 0.5 mM of each primer, 0.2 mM of each dNTP (Fermentas, Vilnius, Lithuania), 3.0 mM MgCl2, 1X Taq buffer and 1U of Taq DNA polymerase (Promega, Madison, WI) to a final volume of 50 µl.
The amplification conditions were 95ºC during 5 min for the initial denaturation step, followed by 35 cycles of denaturation at 94ºC (1 min), annealing at 62ºC (45 s) and extension at 72ºC (1 min). The final extension step consisted of 5 min at 72ºC. As a negative control, PCR mix without DNA sample was used to ensure the contamination-free PCR product.
3.3.3 Identification of the obtained fragments
For amplification confirmation of the DNA fragments from FAS and FASL, 15µl of PCR product were analysed by electrophoresis in a 1.5% (w/v) agarose gel and stained with ethidium bromide. Samples were applied into wells of the gel.
Gels visualization was carried out using an ultra-violet (UV) light in Image Master VDS (Pharmacia Biotech) (Figure 23A and 23B)
A
Figure 23 – Fragments identification in agarose gels. A: FAS–670A/G, Amplification in all samples shown, except for sample at lane 3; B: FASL–844T/C, Amplification in all samples shown.
B
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3.4 Polymorphisms analysis
The studied polymorphisms were analysed using Restriction Fragment Length Polymorphism (RFLP) technique.
3.4.1 Digestion of FAS–670A/G polymorphism
Reaction products (15 µl) were digested with 1U of Bme1390I restriction endonuclease (Fermentas, Vilnius, Lithuania) during 4 h at 37ºC. After digestion the product was visualized in a 3% (w/v) agarose gel stained with ethidium bromide. An uncut band of 193 bp corresponded to the homozygous –670 AA genotype, the 136 and 57 bp fragments indicated the polymorphic homozygous – 670 GG genotype. The three fragments (193, 136 and 57 bp) indicated the heterozygous –670 AG genotype (Figure 24). A second PCR-RFLP analysis was carried out in 10% of all samples to confirm the genotype results.
Figure 24 – FAS–670A/G polymorphism genotyping (AA: 193 pb; TC: 193+136+57 pb; CC:
3.4.2 Digestion of FASL– 844T/C polymorphim
Reaction products (15 µl) were digested with 0.5U of BseMI restriction endonuclease (Fermentas, Vilnius, Lithuania) during 6 h at 56ºC. After digestion the product was visualized in 3% (w/v) agarose gel stained with ethidium bromide.
An uncut band of 401 bp corresponded to the homozygous –844 TT genotype, the 233 and 168 bp fragments indicated the polymorphic homozygous –844 CC genotype. The three fragments (401, 233 and 168 bp) indicated the heterozygous –844 TC genotype (Figure 25). Again, a second PCR-RFLP analysis was carried out in 10% of all samples to confirm the genotype results.
Figure 25 – FASL–844T/C polymorphism genotyping (TT: 401 bp; TC: 401+233+168 bp;
CC: 233+168 bp)
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3.5 Statistical analysis
Data analysis was carried out using the computer software Statistical Package for Social Sciences — SPSS for Windows (version 15.0) and Epi Info (version 6.04a).
The cases were analyzed according to age at diagnosis, serum prostate- specific antigen (PSA) level, Gleason grade and disease status (advanced vs localized). Statistical differences between mean values of groups were evaluated using the unpaired Student’s t-test or the analysis of variance test. Odds ratio (OR) and 95% confidence interval (CI) were calculated as a measure of association between FAS and FASL genotypes and prostate cancer risk. Chi-square test was used in categorical variables comparison and the obtained p value was considered statistically significant under 0.05. The Hardy – Weinberg equilibrium was tested by Pearson goodness fit test to compare the observed vs the expected genotype frequencies.
4. RESULTS
4.1 Genotypic frequencies for FAS–670A/G and FASL– 844T/C polymorphisms
The frequencies of all analysed polymorphisms in prostate cancer cases and controls are shown in Table 2. The most common genotype for FAS–670 was AG, both in cases (54.6%) and controls (52.6%). The homozygous genotypes were less frequent in cases (30.4% AA and 14.9% GG) than in controls (27.1% AA and 20.2% GG). For FASL–844 the heterozygous genotype was most frequent in the two analysed groups (59.0% in cases and 54.4% in controls), being less common the TT genotype (14.6% in cases and 13.9% in controls) and CC genotype (26.4% in cases and 31.7% in controls). No statistically significant differences were found between genotype frequencies in prostate cancer patients and healthy individuals.
TABLE 2. Prevalence and OR of FAS–670 and FASL–844 Genotypes Among Prostate Cancer Patients and Controls
Controls Cases
SNPs
Alleles/
Genotypes
Nº % Nº % OR 95% CI p*
FAS–670 A 264 53.4 759 57.8 1.00 Referent
G 230 46.6 555 42.2 0.84 0.68-1.04 0.099 AA 67 27.1 200 30.4 1.00 Referent
AG 130 52.6 359 54.6 0.93 0.65-1.32 0.655 GG 50 20.2 98 14.9 0.66 0.41-1.04 0.059 G carriers 180 72.8 394 69.5 0.78 0.55-1.09 0.128 FASL–844 T 207 41.1 532 44.1 1.0 Referent
C 297 58.9 674 55.9 0.88 0.71-1.10 0.247
TT 35 13.9 88 14.6 1.0 Referent
TC 137 54.4 356 59.0 1.03 0.65-1.64 0.883 CC 80 31.7 159 26.4 0.79 0.48-1.30 0.332
The expected genotype distributions for FAS–670A/G and FASL–844T/C under Hardy – Weinberg equilibrium were derived for both patients and controls, and they were compared with the observed distributions. This strategy confirmed that the observed distributions were consistent with the Hardy – Weinberg equilibrium (P>0.05).
