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Table 9.2 The important information regarding TLRs and the related SNPs associated with BCa
Chromosomal
position Locus
Family
member Dimerization Position Expression by cell types
Single nucleotide
polymorphism (SNP)
for Bladder Cancers References
4p14 TLR1 TLR2 TLR1-
TLR2,
TLR1-
TLR10
Cell surface Eosinophils,
macrophages,
monocytes, myeloid
DCs, natural killer cells,
neutrophils,
plasmocytoid dendritic
cells,
B cells, endothelial and
epithelial cells
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017;
Saghazadeh and Rezaei
2020; Wang et al. 2020)
4q32 TLR2 TLR2 TLR1-
TLR2,
TLR2-
TLR2,
TLR2-
TLR6,
TLR2-
TLR10
Cell surface Macrophages, mast
cells, monocytes,
myeloid DCs, NK cells,
neutrophils, B and T
cells, endothelial and
epithelial cells
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017;
Saghazadeh and Rezaei
2020; Wang et al. 2020)
4q35 TLR3 TLR3 TLR3-TLR3 Lysosomes,
endoplasmic
reticulum,
endosomes
Myeloid and
plasmacytoid DCs and
NK cells, endothelial
and epithelial cells
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017;
Saghazadeh and Rezaei
2020; Wang et al. 2020)
9q32–33 TLR4 TLR4 TLR4-
TLR4,
TLR4-TLR6
Cell surface/
lysosomes,
endoplasmic
reticulum,
endosomes
Eosinophils,
macrophages, mast
cells, monocytes,
myeloid and
plasmacytoid DCs and
C allele, GC and CC
genotypes of 729GC
and +3725G/C
(rs11536865) and GC
(Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017
;
Pandey et al. 2018;
Saghazadeh and Rezaei
286 P. Behzadi
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neutrophils,
endothelial, epithelial
and smooth muscle
cells
and CC genotypes and
C allele of rs11536889
2020; Shen et al. 2015;
Shen et al. 2013;
Shmuel-Galia et al.
2017; Wang et al. 2020)
1q33.3 TLR5 TLR5 TLR5-TLR5 Cell surface Macrophages,
monocytes, myeloid
and plasmacytoid DCs,
neutrophils and NK
cells, T cells,
endothelial and
epithelial cells
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017;
Saghazadeh and Rezaei
2020; Wang et al. 2020)
4p14 TLR6 TLR2 TLR2-
TLR6,
TLR4-TLR6
Cell surface Macrophages, mast
cells, monocytes,
myeloid and
plasmacytoid DCs,
neutrophils and NK
cells, B cells,
endothelial and
epithelial cells.
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017;
Saghazadeh and Rezaei
2020; Shmuel-Galia
et al. 2017; Wang et al.
2020)
Xp22.3 TLR7 TLR9 TLR7-TLR7 Cell surface/
intracellular
(lysosomes,
endoplasmic
reticulum,
endosomes)
Eosinophils,
macrophages,
monocytes, neutrophils
and plasmacytoid DCs,
B cells, endothelial cells
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Chi et al. 2017;
Dajon et al. 2017;
Saghazadeh and Rezaei
2020; Wang et al. 2020)
Xp22 TLR8 TLR9 TLR8-TLR8 Lysosomes,
endoplasmic
reticulum,
endosomes
Macrophages, mast
cells, monocytes,
myeloid and
plasmacytoid DCs and
neutrophils, T and T
reg
cells, endothelial and
epithelial cells
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017;
Saghazadeh and Rezaei
2020; Wang et al. 2020)
(continued)
9 The Role of Toll-Like Receptor (TLR) Polymorphisms in Urinary Bladder Cancer 287
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Table 9.2 (continued)
Chromosomal
position Locus
Family
member Dimerization Position Expression by cell types
Single nucleotide
polymorphism (SNP)
for Bladder Cancers References
3p21.3 TLR9 TLR9 TLR9-TLR9 Lysosomes,
endoplasmic
reticulum,
endosomes
Eosinophils,
macrophages,
monocytes, myeloid
and plasmacytoid DCs
and neutrophils, B cells,
endothelial and
epithelial cells
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017;
Saghazadeh and Rezaei
2020; Wang et al. 2020)
4p14 TLR10 TLR2 TLR1-
TLR10,
TLR2-
TLR10,
TLR10-
TLR10
Cell surface/
intracellular
Eosinophils,
macrophages,
monocytes, neutrophils
and myeloid and
plasmacytoid DCs), B,
T, and T
reg
cells,
endothelial and
epithelial cells
? (Behzadi and Behzadi
2016; Boozari et al.
2019; Dajon et al. 2017;
Mourits et al. 2020;
Saghazadeh and Rezaei
2020; Wang et al. 2020)
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carcinogenicity of epigenetic factors which can be used in BCa diagnostics, thera-
peutics, and prognostics. Hence, this is an effective methodology to determine BCas
development, progression, and prognosis in different stages and grades (Besaratinia
et al. 2013; Jalanko et al. 2020; Tommasi and Besaratinia 2018).
9.4 Urinary Bladder Cancer: Types and Variants
In accordance with present evidences, >90% of BCa cases are categorized as
urothelial carcinomas (UCs) (Guo and Czerniak 2019; Saginala et al. 2020;
Yazbek-Hanna and Jain 2020; Zhu et al. 2020), ~5% of histological variants of
BCa belongs to squamous cell carcinoma (SCC), while adenocarcinoma, neuroen-
docrine tumors, sarcoma, and metastases constitute the minor cases of BCa (in toto
~5% of cases) (Saginala et al. 2020; Sjödahl et al. 2012; Yazbek-Hanna and Jain
2020). The BCas based on clinical and histopathological demonstrations of the
initial invasive tumor on the depth of urinary bladder wall, are divided into
non-muscular (muscle) invasive BCa (NMIBC) and muscular (muscle) invasive
BCa (MIBC) (Jalanko et al. 2020). Seventy percent of BCa cases are belonging to
NMIBC and the left 30% belongs to MIBC cases (Saginala et al. 2020; Tian et al.
2020; Yazbek-H anna and Jain 2020 ). Normally in 50% of patients with NMIBC, the
BCa is recognized as low grade; while the BCa in the majority of patients with
MIBC or metastatic tumors is recognized as high grade (Kamat et al. 2016). The
urinary bladder tumors are morphologically classifi ed into three different groups of
solid, mixed, and papillary types. In major cases, the UCs involve the papillary type
(Kamat et al. 2016 ; LOPEZ 2020). Due to this fact, urothelium encompasses an
inherent plasticity which may lead to occurrence of a wide range of histologic
variants and histologic differentiation in UCs (LOPEZ 2020) (Table 9.3).
According to the eighth edition of American Joint Committee on Cancer (AJCC),
the staging of urinary BCa is represented for urinary bladder nodes, urinary bladde r
tumors, and urinary bladder metastases. In this regard, the represented staging of
BCa for nodes, tum ors, and metastases is, respectively, as follows: N in five levels of
NX, N0, N1, N2, and N3; T in 11 levels of Tx, T0, Ta (NMIBC), Tis (NMIBC), T1
(NMIBC), T2 (MIBC), T2a (MIBC), T2b (MIBC), T3 (MIBC), T3a (MIBC), T3b
(MIBC), T4 (MIBC), T4a (MIBC), and T4b (MIBC); M in four levels of M0, M1,
M1a, and M1b (Cornejo et al. 2020; Ohadian Moghadam and Nowroozi 2019).
In 1973 the World Health Organization (WHO) started to represent grading and
classification system regarding tumors of urinary system. Due to this fact, the
papillary urothelial lesions are classified into three grades of G1, G2, and G3. The
minimal abnormalities of tumors in papillary UCs (no atypia) are shown by G1. The
G2 grade includes a wide range of non-invasive UCs which can be confusing and G3
involves the maximum atypia with maximally constitutional disorders. The G2 grade
has some complications and limitations. In 1998, the WHO/International Society of
Urological Pathology (ISUP) represented a new classi fication involving categories
of papilloma, papillary urothelial neoplasm of low malignant potential (PUNLMP),
low-grade (LG) and high-grade (HG) tumors in association with carcinomas.
9 The Role of Toll-Like Receptor (TLR) Polymorphisms in Urinary Bladder Cancer 289
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Interestingly, the mentioned 1998 grading system was reused in WHO 2004 and
2016 classifications too. The WHO classifications for non-invasive and invasive
urothelial tumors are shown in Table 9.3. Moreover, the classifications of UCs
Table 9.3 The fourth edition of the WHO classification of non-invasive urothelial lesions and
invasive urothelial tumors
Non-invasive urothelial
lesions Invasive urothelial tumors References
Urothelial carcinoma in
situ (CIS)
Infiltrating urothelial carcinoma
with divergent differentiation (e.g.,
glandular, squamous, and
trophoblastic differentiations)
(Humphrey et al. 2016;
Lopez-Beltran et al. 2019;
Wang and McKenney 2019)
Papillary urothelial
carcinoma, low grade
Nested including large nested
Papillary urothelial
carcinoma, high grade
Microcystic
Papillary urothelial
neoplasm of low
malignant potential
(PUNLMP)
Micropapillary
Urothelial papilloma Lymphoepithelioma-like
Inverted urothelial
papilloma
Plasmocytoid/signet ring cell/
diffuse
Urothelial proliferation
of uncertain malignant
potential (hyperplasia)
Sarcomatoid
Urothelial dysplasia Giant cell
Poorly differentiated
Lipid rich
Clear cell (glycogen rich cell)
Tumors of maüllerian type
Tumors arising in a bladder
diverticulum
Fig. 9.1 The grading systems of UC done by the WHO in the years of 1973 (involving grades 1–3)
and 2016 (involving grades 1–2). The PUNLMP depicts papillary urothelial neoplasms of low
malignant potential. The low- and high-grades imply NILGC and NIHGC which, respectively,
depict: non-invasive low-grade papillary UC and non-invasive high-grade papillary UC
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achieved by WHO in 1973 and 2016 are compared in Fig. 9.1 (Compérat et al. 2019;
Humphrey et al. 2016; Kamat et al. 2016; Wang and McKenney 2019).
9.5 Urinary Bladder Cancer: Classification and Grading
As BCa is a heterogeneous cancer with different pathological and molecular
parameters, a number of classification systems have been represented which involve
traditional and molecular subtyping systems. The BCa traditional classification
system usually involves pathological items. As we know, the pathological gradi ng
and staging and the BCa progression and recurrence are versatile in different
patients. Besides, all the risks in association with the all types of BCas including
MIBCs and NMIBCs are not predictable by traditional system. In this regard, the
recurrency and progression risks may be predictable for NMIBCs but not for
MIBCs. These parameters determine how the patients’ should be monitored and
treated; while the pathological and biological reactions differ from person-to-person.
Traditional system is supported by the European Organisation for Research and
Treatment of Cancer (EORTC) (http://www.eortc.be/tools/bladdercalculator/default.
htm). It is important to know that, the pathological characteristics do not reveal the
genetical and molecular properties. By the advanced technologies of sequencing and
omics (such as epigenomics, genomics, metabolomics, proteomics, transcriptomics,
etc.) the accuracy rate of BCa diagnosis and treatment has been raised up (Loras et al.
2019; Sylvester et al. 2006; Zhu et al. 2020). Therefore, since the year of 2012
different molecular subtyping systems have been conducted by scientists to have
accurate and effective results in association with diagnosing and treatment of BCa
cases (Zhu et al. 2020). Due to this fact, in 2012 Sjödahl et al. from Lund University,
Sweden, performed a study based on gene expression profiles belonging to tumor
cases of patients with BCa. The gene expression profiles involve cell adhesion genes,
cell cycle genes, cytokeratins, and receptor tyrosine kinases genes. In this regard,
five determined molecular subtypes of urothelial cell carcinoma including
genomically unstable, infiltrated class of tumors, SCC-like, urobasal A and urobasal
B were defined (Table 9.4). The molecular subtyping system done by Sjödahl et al. is
known as an early subtyping which includes both types of MIBC and NMIBC
(Sjödahl et al. 2012; Zhu et al. 2020).
In 2014, three groups of molecular subtypes regarding MIBC including UNC
(Damrauer et al. 2014), MDA (Choi et al. 2014), and TCGA (Cancer Genome Atlas
Research Network 2014) were represented, separately (Zhu et al. 2020). The UNC
subtyping system is based on high-grade BCa of MIBC . In this regard, the related
subtypes are divided into two groups of basal-like and luminal (Table 9.4)
(Damrauer et al. 2014; Zhu et al. 2020). The MD Anderson as another molecular
subtyping system (based on whole genome mRNA expression pro filing) for MIBC
was achieved in the MD Anderson Cancer center by a scientific group in 2014 (Choi
et al. 2014; Zhu et al. 2020). Throughout this methodology, three subtypes including
basal, luminal, and p53-like were recognized for MIBC subtyping system
(Table 9.4) (Choi et al. 2014; Zhu et al. 2020).
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Table 9.4 A comparison between the main BCas molecular subtyping systems from 2012
Subtyping
system
Target
BCas criterion Molecular subtypes References
Lund 2012 Early BC
subtyping
for MIBC
and
NMIBC
Gene
expression
profiles
belonging to
tumor cases of
patients with
BCa
Urobasal
A
Genomically
unstable
Infiltrated
class of
tumors
Urobasal
B
SCC-like (Sjödahl
et al. 2012;
Zhu et al.
2020)
UNC 2014
(University of
North Carolina)
High-
grade
MIBC
Expression of
gene set
predictor of
BASE47
Luminal Basal-like (Damrauer
et al. 2014;
Zhu et al.
2020)
MDA 2014
(MD Anderson)
MIBC Whole genome
mRNA
expression
profiling
Luminal p53-like Basal (Choi et al.
2014; Zhu
et al. 2020)
TCGA 2014
(The Cancer
Genome Atlas)
MIBC Genetic
expression
signature
Cluster I
(luminal)
Cluster II
(luminal-
infiltrated)
Cluster III
(basal-
squamous)
Cluster
IV
(basal)
(Cancer
Genome
Atlas
Research
Network
2014; Zhu
et al. 2020)
TCGA 2017
(The Cancer
Genome Atlas)
Luminal Luminal-
infiltrated
Basal-
squamous
Neural Luminal-
papillary
(Robertson
et al. 2017;
Zhu et al.
2020)
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UROMOL
2016
NMIBC Transcriptome
sequencing
analysis
Class 1 Class 3 Class 2 (Hedegaard
et al. 2016;
Zhu et al.
2020)
GSC 2017
(Genomic
subtyping
classifier)
MIBC Gene
expression
Claudin-
low
Basal Luminal-
infiltrated
Luminal (Seiler et al.
2017; Zhu
et al. 2020)
EAU 2018
(European
Association of
Urology)
guideline
High-risk
NMIBCs
Gene
expression
Good Moderate Poor (van Kessel
et al. 2018;
Zhu et al.
2020)
BOLD 2018
(BLCA
(Bladder
Cancer)
Subtypes Of
Large meta-
cohort
Database)
MIBC and
NMIBC
Gene
expression and
transcriptome
Neural-
like
Luminal-like Papillary-
like
HER2-
like
Squamous-
cell
carcinoma-
like
Mesenchymal-
like
(Tan et al.
2019; Zhu
et al. 2020)
NAC 2018
(NeoAdjuvant
Chemotherapy)
MIBC Gene
expression
CC1-
basal
CC2-luminal CC3-
immune
CC4-
scar-like
(Seiler et al.
2019; Zhu
et al. 2020)
9 The Role of Toll-Like Receptor (TLR) Polymorphisms in Urinary Bladder Cancer 293
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The Cancer Genome Atlas (TCGA) subtyping system was performed in 2014 for
the first time and was supported by two US research centers of The National Cancer
Institute (TNCI) and The National Human Genome Institute (TNHGI). By the
TCGA—version 2014—four MIBCs molecular subtypes including Cluster I, Clus-
ter II, Cluster III, and Cluster IV were detected (Table 9.4) (Cancer Genome Atlas
Research Network 2014; Zhu et al. 2020 ). Again, the TCGA subtyping system was
performed in 2017 as a multiple TCGA analytical platform. The TCGA—version
2017—identified five molecular subtypes including luminal, luminal-infiltrated,
basal-squamous, luminal-papillary, and neuronal (Table 9.4) (Robertson et al. 2017).
UROMOL 2016 is an NMIBC subtyping system with three molecular subtypes of
Class 1, Class 3, and Class 2 (Table 9.4). The UROMOL subtyping system is based
on a transcriptome sequencing analysis which targets a huge number of genes which
are involved in different biological processes. Hence, the Class 1 involves
LG-tumors, Class 3 includes tumors with phenotypic characteristics like CIS, and
Class 2 represents the HG-malignant tumors (Hedegaard et al. 2016; Zhu et al.
2020).
The single-sample genomic subtyping classifier (GSC) is another molecular
subtyping system for MIBC with four target subtypes of basal, claudin-low, luminal,
and luminal-infiltrated which was performed in 2017 (Table 9.4). The GSC
subtyping system was invented to predict the prognosis and response to neoadjuvant
cisplatin-based chemotherapy (NAC) based on gene expression (Seiler et al. 2017;
Zhu et al. 2020).
Another NMBIC subtyping system is European Associa tion of Urology (EAU)
guideline for NMIBC which was achieved by Van Kessel et al. This subtyping
system targets EAU high-risk NMIBCs and a reclassification was done for the
related molecular subtypes including good, moderate, and poor (Table 9.4) (van
Kessel et al. 2018; Zhu et al. 2020).
The BOLD subtyping system which involves both of MIBC and NMIBC was
performed by Tan et al. to present the related molecular subtypes based on
transcriptomic properties and gene expression. Six subtypes of HER2-like, lumi-
nal-like, neural-like, papillary-like, mesenchymal-like (MES-like), and squamous
cell carcinoma-like (SCC-like) were recognized (Table 9.4) (Tan et al. 2019 ; Zhu
et al. 2020).
Seiler et al. run a subtyping system based on adjuvant chemotherapy with four
molecular subtypes of CC1-basal, CC2-luminal, CC3-immune, and CC4-scar-like
(Table 9.4) (Seiler et al. 2019). The gene profiling of NMIBC and MIBC is shown in
Table 9.4.
9.6 Toll-Like Receptors and Signaling Pathways
TLRs—the magic molecules of type I transmembrane glycoprotein pertain to the
largest pathogen recognition receptors (PRRs) family which have pivotal role in
immunity, pathology, and physiology (Fig. 9.2). The TLR molecules bind to three
types of ligands involving exterior molecules of pathogen-associated molecular
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patterns (PAMPs), exterior synthetic molecules of xenobiotic-associated molecular
patterns (XAMPs), and interior molecules of damage/danger-associated molecular
patterns (DAMPs) (Angrini et al. 2020; Behzadi and Behzadi 2016; Behzadi 2020;
Javaid and Choi 2020; Pradere et al. 2014; Saghazadeh and Rezaei 2020; Wang et al.
2020).
There are 13 recognized TLRs up to now. Humans encompass TLRs 1–10 and
mice possess TLRs 1–9and11–13. Indeed, there are 10 and 12 functional types of
TLRs in human and mouse immune systems, respectively. However, the TLRs of
11, 12, and 13 are protein products of TLR11, TLR12, and TLR13 pseudogenes in
mouse (Angrini et al. 2020; Behzadi and Behzadi 2016; Dajon et al. 2017;
Saghazadeh and Rezaei 2020).
Fig. 9.2 Tumor biology diagram, the increase or decrease of TLRs may lead to turning-on or
turning-off the anti-tumoral activities or tumorigenesis; the double-edged sword characteristics
of TLRs
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