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Single Nucleotide Polymorphism in SMAD7 and CHI3L1 and Colorectal Cancer Risk.

1. Colorectal Cancer

Colorectal cancer (CRC) has attracted significant attention as it represents the third most common cancer and fourth cancer in mortality in the world after lung, stomach, and liver cancers [1]. Colorectal cancer accounts for approximately 10% of all new cancer cases, affecting one million people every year throughout the world [2]. The highest incidence rates are mainly found in developed countries, whereas the lowest rates are found in developing countries (Figure 1) [3]. From the genetic standpoint, CRC can be divided into three types: sporadic, familial, and hereditary CRC [4] as shown in Table 1.

The etiology of sporadic CRC is considered to be multifactorial and arises from the interaction between allelic variants in low-penetrant genes and environmental risk factors [5, 6]. Penetrance is the frequency with which the characteristics transmitted by a gene appear in individuals possessing it. A highly penetrant gene almost always expresses its phenotypes regardless of other environmental influence, while low-penetrant genes express its phenotype in the presence of other genetic and/or environmental influence [7]. The genetic contribution of high- and low-penetrant genes to CRC is shown in Figure 2. Risk factors for CRC may be nonmodifiable or modifiable [8] as shown in Table 2.

Vogelstein model, also known as the adenomacarcinoma sequence, is a multistep model [19] that describes the progression of CRC carcinogenesis from a benign adenoma to a malignant carcinoma through a series of well-defined histological stages (Figure 3). The main features of the model include a mutational activation of oncogenes and/or the inactivation of tumor suppressor genes. At least four or five genetic alterations must take place for the formation of malignant tumors. The characteristics of the tumor are dependent upon the accumulation of multiple genetic mutations rather than a certain sequence of mutations of these genes.

Dukes' colorectal cancer staging and Tumors/Nodes/ Metastases (TNM) are the two classification system that are used for the staging of CRC (Table 3). There has been a gradual move from Dukes' to the TNM classification system as TNM was reported to give a more accurate independent description of the primary tumors and its spread [20].

2. Prevention of Colorectal Cancer

Several approaches have been developed to reduce CRC incidence and mortality. Prevention includes primary and secondary strategies. Primary strategy includes dietary changes, increasing physical activity, and the use of nonsteroidal anti-inflammatory drugs (NSAIDs), while the secondary strategy is based on screening tests (Table 4).

Interestingly, dietary factors are responsible for 70% to 90% of CRC. The relatively low CRC rates in the Mediterranean area compared with most Western countries are mostly because the traditional Mediterranean diet is characterized by high consumption of foods of plant origin, relatively low consumption of red meat, and high consumption of olive oil [32]. Therefore, diet modification could potentially help to reduce the incidence of CRC [33, 34]. Examples of some dietary components that lower CRC risk are shown in Table 5.

Early diagnosis of CRC is important to improve outcomes. Fecal occult blood testing (FOBT) or fecal immunochemical test (FIT) is routinely used prior to colonoscopy, and only patients with a positive test result are referred to a specialist. Although these assays are useful screening tools, patient compliance with these stool-based assays tends to be low. Serum-based assays for the early detection of CRC are highly attractive, as they could be integrated into any regular health checkup without the need for additional stool sampling, thereby increasing acceptance among patients [29].

3. Gene Polymorphism

Polymorphism is the occurrence of two or more clearly different morphs or forms of a species in the population. Poly means many; morph means form [48]. The colored flowers of mustard, butterflies, and human ABO blood group system are obvious examples of polymorphisms [49, 50].

Genetic polymorphisms are different forms of the DNA sequence, which may or may not affect biological function depending on its exact nature. Polymorphism arises as a result of mutation. If the frequency of a specific sequence variant reaches 1% or more in the population, it is referred to as polymorphism, and if it is lower than 1%, the allele is typically regarded as mutation [51]. Molecular polymorphism, first demonstrated in Drosophila pseudoobscura, stimulated molecular studies of many other organisms and led to vigorous theoretical debate about the significance of the observed polymorphisms [52, 53].

Single nucleotide polymorphism (SNP) is a variation in a single nucleotide that occurs at a specific position in the genome. Single nucleotide polymorphisms are the most abundant type of genetic variation in the human genome, accounting for more than 90% of all differences between individuals [54]. Single nucleotide maybe changed (substitution), removed (deletion), or added (insertion) to a polynucleotide sequence [54].

Single nucleotide polymorphisms are also thought to be the keys in realizing the concept of personalized medicine as it can affect how humans develop diseases and respond to pathogens, chemicals, drugs, vaccines, and other agents. Single nucleotide polymorphisms underlie the differences in the susceptibility to a wide range of human diseases, for example, a single base mutation in the apolipoprotein E gene is associated with a higher risk for Alzheimer's disease. The severity of illness and the way the body responds to treatments are also manifestations of genetic variations [55, 56].

According to their location in the genome, SNPs are classified into cSNP in the coding region (exons), rSNP in the regulatory region, and iSNP located in the intronic region [54].

Polymorphisms in the coding region are either synonymous or nonsynonymous (Figure 4). Synonymous polymorphisms do not result in a change of amino acid in the protein but still can affect its function in other ways. Silent mutation in the multidrug resistance gene 1, which codes for a cellular membrane pump that expels drugs from the cell, is an example of synonymous polymorphism. It can slow down translation and allow unusual folding of the peptide chain, causing the mutant pump to be less functional [57, 58].

Nonsynonymous polymorphisms, on the other hand, can change the amino acid sequence of the protein and subclassified into missense and nonsense. Missense polymorphism results in different amino acids such as single base change G > T in LMNA gene that results in the replacement of the arginine by the leucine at the protein level, which manifests progeria syndrome [59]. Nonsense polymorphism results in a premature stop codon and usually nonfunctional protein product such as that manifested in cystic fibrosis caused by mutation in the cystic fibrosis transmembrane conductance regulator gene [60].

Promoter polymorphism can cause variations in gene expression as it affects the DNA binding site and alters the affinity of the regulatory protein while intronic region polymorphism may affect gene splicing and messenger RNA degradation [61, 62].

Genotyping technologies typically involve the generation of allele-specific products for SNPs of interest followed by their detection for genotype determination. All current genotyping technologies with only a few exceptions require the polymerase chain reaction (PCR) amplification step. In most technologies, PCR amplification of a desired SNP-containing region is performed initially to introduce specificity and increase the number of molecules for detection following allelic discrimination [63]. Enzymatic cleavage, primer extension, hybridization, and ligation are four popular methods used for allelic discrimination (Table 6).

4. Genome-Wide Association Study and Colorectal Cancer

Genome-wide association study (GWAS), also known as whole genome association study, is defined as an examination of many common SNPs in different individuals to see if any SNP is associated with a disease. Genome-wide association study compares the DNA of participants having a disease with similar people without the disease. The ultimate goal is to determine genetic risk factors that can be used to make predictions about who is at risk for a disease and to identify their role in disease development for developing new prevention and treatment strategies [68].

The availability of chip-based microarray technology that assay hundreds and thousands of SNPs made genomewide association studies easy to be performed (Table 7). Genome-wide association study identifies a specific location, not complete genes. Many SNPs identified in GWAS are near a protein-coding gene or are within genes that were not previously believed to associate with the disease. So, researchers use data from this type of study to pinpoint genes that may contribute to a person's risk of developing a certain disease [69].

Genome-wide association study is built on the expanding knowledge of the relationships among SNPs generated by the international HapMap project. The HapMap project is an international scientific effort to identify common SNPs among people from different ethnic populations. When several SNPs cluster together on a chromosome, they are inherited as a block known as a haplotype. The HapMap describes haplotypes, including their locations in the genome, and how common they are present in different populations throughout the world [70].

Genome-wide association study is an important tool for discovering genetic variants influencing a disease, but it has important limitations, including their potential for false-positive and false-negative results and for biases related to selection of study participants and genotyping errors [71]. The gold standard for validation of any GWAS is replication in an additional independent sample. Replication studies are performed in an independent set of data drawn from the same population as the GWAS, in an attempt to confirm the effect in the GWAS target population. Once an effect is confirmed in the target population, other populations may be sampled to determine if the SNP has an ethnic-specific effect [72].

It has been recognized that SNPs play an important role in conferring risk of CRC. Genome-wide association studies have reported multiple risk loci associated with risk CRC, some of which are involved in the transforming growth factor-[beta] (TGF-[beta]) signaling pathway [73]. For example, SMAD7 rs4939827 was found to be associated with CRC in two GWASs [74, 75]. The association of SMAD7 rs4939827 with CRC was confirmed by other replication studies [76, 77]. A summary of other SNPs studied as risk factors for CRC is shown in Table 8.

5. Transforming Growth Factor-[beta] Signaling and Its Regulatory Smad7

Mothers against decapentaplegic homolog 7 (Smad7) is a key inhibitor of TGF-[beta] [94, 95]. Smad7 was named after mothers against decapentaplegic (mad), an intermediate of the decapentaplegic signaling pathway in Drosophila melanogaster and sma-gene in Caenorhabditis elegans that has mutant phenotype similar to that observed for the TGF-[beta]like receptor gene [96]. Regulation of TGF-[beta] by Smad7 is crucial to maintain gastrointestinal homeostasis [97]. Smad7 overexpression is commonly found in patients with chronic inflammatory conditions of the colon [98] and may be associated with prognosis in patients with CRC [99]. Loss of Smad/TGF-[beta] signaling interrupts the principal role of TGF-[beta] as a growth inhibitor, allowing unchecked cellular proliferation [100].

In the early 1980s, Roberts and his colleagues isolated two fractions that could induce growth of normal fibroblasts from murine sarcoma cell extracts and were named TGF[alpha] and TGF-[beta] [101, 102]. Transforming growth factor-[beta] is a prototype of a large family of cytokines that includes the TGF-[beta]s, activins, inhibins, and bone morphogenetic proteins (BMPs) [103].

In mammals, TGF-[beta] has 3 isoforms (TGF-[beta]1, TGF[beta]-[beta]2, and TGF-[beta]3), with similar biological properties. The TGF-[beta] isoforms are encoded from genes located on different chromosomes. The TGF-[beta]1 gene is located in chromosome 19q13.1, while TGF-[beta]2 and TGF-[beta]3 genes are located in chromosomes 1q4.1 and 14q24.3, respectively [104].

The isoforms of TGF-[beta]1, TGF-[beta]2, and TGF-[beta]3 are encoded as large precursor, which undergo proteolytic digestion by the endopeptidase furin, yielding two products that assemble into dimers. One is latency-associated peptide (LAP), a dimer from the N-terminal region. The other is mature TGF-[beta], a dimer from the C-terminal portion. A common feature of TGF-[beta] is that its N-terminal portion (LAP) remains noncovalently associated with the mature TGF-[beta] forming a small latent complex [105, 106]. The small latent complex is associated with a large protein termed latent TGF-[beta] binding protein (LTBP) via disulfide bonds forming large latent complex for targeted export to the extracellular matrix (ECM) [107, 108]. For TGF-[beta] to bind its receptors, the latent complex must be removed so that the receptor-binding site in TGF-[beta] is not masked by LAP. Latent TGF-[beta] is cleaved by several factors, including proteases, thrombospondin, reactive oxygen species (ROS), and integrins (Figure 5) [109, 110].

Transforming growth factor-[beta] is a pleiotropic cytokine that has a dual function in cancer development, where it acts as a tumor suppressor in the early stages and a tumor promoter in the late stages [111]. The main actions of TGF-[beta] are summarized in Table 9.

The active TGF-[beta] binds to transforming growth factor-[beta] receptor 2 (TGF-[beta]R2), a serine/threonine kinase receptor, leading to the recruitment and phosphorylation of the TGF-[beta]R1 (Figure 6). The activated TGF-[beta]R1 interacts with and phosphorylates a number of proteins, thereby activating multiple downstream signaling pathways in either a Smad-dependent (canonical) or Smad-independent (noncanonical) signaling pathway (Figure 6) [96].

In the canonical pathway, TGF-[beta]R1 propagates the signal through a family of intracellular signal mediators known as Smads. To date, eight mammalian Smad proteins have been characterized and are grouped into three functional classes: receptor-activated Smads (R-Smads) including Smad1, Smad2, Smad3, Smad5, and Smad8, common mediator Smad (Smad4), and inhibitory Smads (I-Smads) including Smad6 and Smad7. Receptor-activated Smads are retained in the cytoplasm by binding to SARA (Smad anchor for receptor activation). Receptor-activated Smads are released from SARA when they are phosphorylated by the activated TGF-[beta]R1 [130, 131].

Once R-Smads (Smad2/3) are activated through phosphorylation by TGF-[beta]R1, they form an oligomeric complex with Smad4 and translocate into the nucleus, where it modulates the transcription of specific genes. Ability of Smads to target a particular gene and the decision to activate or repress gene transcription are determined by many cofactors that affect the Smad complex [130].

In the noncanonical pathway, TGF-[beta] activates other non-Smad signaling pathways (Table 10). Some of these pathways can regulate Smad activation, but others might induce responses unrelated to Smad [132].

Transforming growth factor-[beta] is strongly implicated in cancer as genetic alterations of some common components of TGF-[beta] pathway (Table 11) that have been identified in human tumors [141].

6. Inhibitory Smad (I-Smad, Smad7)

Mothers against decapentaplegic homolog 7 (Smad7) belongs to the third type of Smads, the I-Smads that also include Smad6. The structure of the Smads is characterized by two conserved regions known as the amino terminal (Nterminal) Mad homology domain-1 (MH1) and C-terminal Mad homology domain-2 (MH2), which are joined by a short poorly conserved linker region. The MH1 domain is highly conserved among the R-Smads and the Co-Smad, whereas the I-Smads lack a MH1. The MH2 domain is conserved among all of the Smad proteins but I-Smads lack SXSS motif, which is needed for phosphorylation following TGF-[beta]R1 activation (Figure 7). Thus, I-Smads are not phosphorylated upon binding of TGF-[beta] to its receptors. The L3 loop in the MH2 domain of the R-Smads is a specific binding site for the TGF-[beta]R1 [95, 156].

Smad7 antagonizes TGF-[beta] signaling through multiple mechanisms, both in the cytoplasm and the nucleus (Figure 8). Smad7 antagonizes TGF-[beta] in the cytoplasm through the formation of a stable complex with TGF-[beta]R1, leading to inhibition of R-Smad phosphorylation. Smad7 can recruit E3 ubiquitin ligases that induce the degradation of activated TGF-[beta]R1 complexes [156,157]. Also, Smad7forms a heteromeric complex with R-Smads through the MH2 domain and hence interferes with R-Smad (Smad2/3)-Smad4 oligomerization in a competitive manner. Additionally, Smad7 can bind to DNA disrupting the formation of functional Smad-DNA complexes [158, 159].

Inhibitory Smads can mediate the cross talking of TGF-[beta] with other signaling pathways. Various extracellular stimuli such as interferon-[gamma] (IFN-[gamma]) can induce Smad7 expression to exert opposite effects on diverse cellular functions modulated by TGF-[beta] [161]. In addition, Smad7 was found to be a key regulator of Wnt/[beta]-catenin pathway that is responsible for the TGF-[beta]-induced apoptosis and survival in various cell types [162].

There is a controversy regarding the role of Smad7 in tumor development depending on the type of the tumor. High Smad7 expression was reported to be correlated with the clinical prognosis of patients with colorectal, pancreatic, liver, and prostate cancer. In contrast, a protective role of high Smad7 expression was reported in other tumors [163]. Boulay et al. [164] found that CRC patients with deletion of Smad7 had a favorable clinical outcome compared with patients with Smad7 expression. Additionally, Smad7 was found to act as a scaffold protein to facilitate TGF-[beta]-induced activation of p38 and subsequent apoptosis in prostate cancer cells [162].

Even in the same tumor, the function of Smad7 can switch from tumor suppressive to tumor promoting depending on the tumor stage (i.e., early versus advanced). These apparently contradictory functions are in harmony with the opposite roles of TGF-[beta] signaling pathway in the early versus advanced tumor stages and the interaction of Smad7 with a vast array of functionally heterogeneous molecules that may be differently expressed during the carcinogenic process [160].

The overexpression of Smad7 in CRC cell was reported to enhance cell growth and inhibit apoptosis through a mechanism dependent on suppression of TGF-[beta] signaling [100]. In addition, Smad7-deficient CRC cells were reported to enhance the accumulation of CRC cells in S phase of cell cycle and cell death through a pathway independent on TGF-[beta] [165]. Genetic variants in SMAD7 gene have been extensively studied in CRC patients (Table 12).

7. Chitinase 3 Like 1/YKL-40

YKL-40 is a mammalian member of the chitinase protein family. YKL-40 is a 40 kDa heparin- and chitin-binding glycoprotein. The human protein was named YKL-40 based on its three N-terminal amino acids tyrosine (Y), lysine (K), and leucine (L) and its 40kDa molecular mass [178]. This protein has several names, YKL-40 [178], human cartilage glycoprotein-39 (HC-gp39) [179], 38kDa heparin-binding glycoprotein (Gp38k) [180], chondrex [181], and 40kDa mammary gland protein (MGP-40) [182].

In a search of new bone proteins, the glycoprotein YKL40 was identified in 1989 to be secreted in vitro by the human osteosarcoma cell line MG63. The protein was later found to be secreted by differentiated smooth muscle cells, macrophages, human synovial cells, and nonlactating mammary gland [178,181,182]. In 1997, the chitinase 3 like 1 (CHI3L1) gene encoding for YKL-40 was isolated. It is assigned to chromosome 1q31-q32 and consists of 10 exons and spans about 8 kilobases of genomic DNA [178, 183].

Based on amino acid sequence, it was found that YKL40 belongs to the glycosyl hydrolase family 18 that hydrolyses the glycosidic bond between two or more carbohydrates or between a carbohydrate and a noncarbohydrate moiety. Based on sequence similarity, there are more than 100 different families of glycosyl hydrolases [184-186].

Chitin, a polymer of N-acetyl glucosamine, is the second most abundant polysaccharide in nature, following cellulose. It is found in the walls of fungi, the exoskeleton of crabs, shrimp and insects, and the micro filarial sheath of parasitic nematodes [187]. Chitin accumulation is regulated by the balance of chitin synthase-mediated biosynthesis and degradation by chitinases. Although YKL-40 contains highly conserved chitin-binding domains, it functionally lacks chitinase activity due to the mutation of catalytic glutamic acid into leucine [183].

Several types of solid tumors can express YKL-40 such as osteosarcoma [178], CRC [188], thyroid carcinoma [189], breast [190], ovarian [191], lung [192], pancreatic cancer [193], glioblastoma [194-196], and cholangiocarcinoma [197].

There are several synergistic and antagonistic factors that modulate the regulatory functions of YKL-40 (Figure 9) in both normal and pathological conditions [198].

8. CHI3L1/YKL-40 Targets and Actions

Although the biological function of YKL-40 is not fully understood, the pattern of its expression suggests function in remodeling or degradation of ECM. The diverse roles of YKL-40 in cell proliferation, differentiation, survival, inflammation, and tissue remodeling have been suggested [199]. Aberrant expression of YKL-40 is associated with the pathogenesis of an array of human diseases (Figure 10).

Elevated serum YKL-40 levels were reported to be associated with a wide range of inflammatory diseases (Table 13). More than 75% of patients with streptococcus pneumoniae bacteremia had elevated serum levels of YKL-40 compared with age-matched healthy subjects. Treatment of these patients with antibiotics resulted in reaching serum YKL-40 normal level within few days in most patients before the serum C-reactive protein (CRP) reach the normal level [200].

Biologically, YKL-40 was found to activate a wide range of inflammatory responses. An inflammatory stimulus can trigger the secretion of a variety of cytokines that in turn may regulate YKL-40 (Figure 11). Increased YKL-40 was reported to regulate chronic inflammatory responses like asthma, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and arthritis. Inhibition of YKL-40 by utilizing anti-CHI3L1 antibody may be a useful therapeutic strategy to control/reduce the effect of inflammatory diseases [198].

Over the past three decades, a considerable attention has been focused on the potential role of YKL-40 in the development of a variety of human cancers. Serum levels of YKL-40 (Table 14) were independent of serum carcinoembryonic antigen (CEA) in CRC [188], serum cancer antigen 125 (CA-125) in ovarian cancer [191], serum human epidermal growth factor receptor 2 (HER-2) in metastatic breast cancer [190], serum lactate dehydrogenase (LDH) in small cell lung cancer [192], and serum prostate-specific antigen (PSA) in metastatic prostate cancer [208]. Therefore, it may be of value to include serum YKL-40 as a biomarker for screening of cancer together with a panel of other tumor markers as it can reflect other aspects of tumor growth and metastasis than the routine tumor markers [201].

Macrophages and neutrophils in tumor microenvironment or tumor cells were found to secrete YKL-40 into extracellular space, which can enhance tumor initiation, proliferation, angiogenesis, and metastasis (Figure 12).

The ability of YKL-40 to induce cytokine secretion, proliferation, and migration of target cells suggests the existence of their receptors on the cell surface. However, receptors interacting with YKL-40 are incompletely characterized, and only limited information is available about YKL-40-induced signaling pathways. There are evidences to strengthen a hypothesis that a cross talk between adjacent membrane-anchored receptors plays a key role in transmitting "outside-in" signaling to the cells, leading to a diverse array of intracellular signaling [213, 214].

YKL-40 possesses heparin-binding affinity, which enables it to specifically bind heparan sulfate (HS) fragments [215]. Syndecans are transmembrane molecules with cytoplasmic domains that can interact with a number of regulators [216]. Syndecan-1 is the major source of cell surface HS. There is compelling evidence demonstrating that syndecan1 can act as a matrix coreceptor with adjacent membrane-bound receptors such as integrins to mediate cell adhesion and/or spreading [217]. It was found that YKL-40 could induce the coupling of syndecan-1 and [alpha]v[beta]3 integrin (Figure 13), resulting in phosphorylation of focal adhesion kinase (FAK) and activation of downstream ERK1/2 signaling pathway, which enhance vascular endothelial growth factor (VEGF) expression in tumor cells, angiogenesis, and tumor growth [214]. Additionally, ERK1/2 and JNK signaling pathways were reported to upregulate proinflammatory mediators such as C-chemokine ligand 2 (CCL2), chemokine CX motif ligand 2 (CXCL2), and MMP-9; all of which contribute to tumor growth and metastasis [218].

Another VEGF-independent pathway was reported to mediate angiogenic activity ofYKL-40, as an anti-VEGF neutralizing antibody failed to impede YKL-40-induced migration [219]. Therefore, targeting both YKL-40 and VEGF could be an efficient course of therapy along with radiotherapy for eventual eradication of deadly diseases.

Furthermore, YKL-40 was demonstrated to stimulate TGF-[beta]1 production in malignant cells via interleukin-13 receptor [alpha]2- (IL-13R[alpha]2-) dependent mechanism (Figure 14). The binding of YKL-40 to IL-13R[alpha]2 results in the activation of MAPK, AKT, and Wnt/[beta]-catenin which play an important role in inhibiting apoptosis and interleukin-1[beta] (IL-1[beta]) production thereby acting as a potential cancer promoter [220].

Recently, Low et al. [221] showed that YKL-40 can also bind surface receptor for advanced glycation end product (RAGE), which is involved in tumor cell proliferation, migration, and survival through [beta]-catenin- and nuclear factor kappa-B- (NF-[kappa]B-) associated signaling pathways [221,222].

Most of the ongoing researches have been carried out on SNP rs4950928 in the promoter region of CHI3L1 gene as it was found to be associated with the serum/plasma YKL-40 levels [223, 224] and diseases such as asthma, bronchial hyperresponsiveness [207], and the severity of hepatitis C virus-induced liver fibrosis [225]. Some of the association studies of CHI3L1 SNPs with different diseases are shown in Table 15.

Conflicts of Interest

The authors declare that they have no conflict of interest.


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Amal Ahmed Abd El-Fattah, (1) Nermin Abdel Hamid Sadik, (1) Olfat Gamil Shaker, (2) and Amal Mohamed Kamal [ID] (1)

(1) Biochemistry Department, Faculty of Pharmacy, Cairo University, Kasr El-Einy Street, Cairo, Egypt

(2) Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Cairo University, Cairo, Egypt

Correspondence should be addressed to Amal Mohamed Kamal;

Received 17 May 2018; Revised 1 August 2018; Accepted 16 August 2018; Published 25 October 2018

Academic Editor: Vinod K. Mishra

Caption: Figure 2: Genetic contribution to CRC.

Caption: Figure 3: The colorectal adenoma-carcinoma sequence (Vogelstein model). Progression from normal epithelium through adenoma to CRC is characterized by accumulated abnormalities of multiple genes.

Caption: Figure 4: Genetic polymorphism in the coding region (

Caption: Figure 5: The sequential steps in the synthesis and secretion of active TGF-[beta].

Caption: Figure 6: Canonical and noncanonical pathways of TGF-[beta].

Caption: Figure 7: Gene constructions of SMADs

Caption: Figure 8: Smad7 antagonizes TGF-[beta] signaling in the cytoplasm and the nucleus, respectively [160].

Caption: Figure 9: Several synergistic and antagonistic factors modulate the regulatory functions of YKL-40. EGFR: epidermal growth factor receptor; SAPK: stress-activated protein kinases; MCP-1: monocyte chemoattractant protein-1.

Caption: Figure 10: YKL-40 regulates the pathogenesis of cancer and inflammatory disorders [198].

Caption: Figure 11: Role of inflammatory cytokines in YKL-40-mediated allergy and inflammation.

Caption: Figure 12: YKL-40 supports tumor progression.

Caption: Figure 13: Involvement of YKL-40 in pathways pertaining to cell proliferation, survival, differentiation, and tumorigenesis.

Caption: Figure 14: YKL-40 function through IL-13R[alpha]2-dependent mechanism.
Table 1: Genetic classification of CRC

Sporadic CRC           Familial CRC              Hereditary CRC

Occurs entirely by     Occurs when there         When people
chance throughout      are two or more           inherit a high
life without any       family members            penetrant gene
previous family        with a history            mutation from
history                of CRC                    either of their
                       No specific inherited
                       gene mutation has
                       been identified to
                       explain the cancer yet.

-60%-80%               -15%-30%                  -5%

Table 2: Risk factors of CRC.


(i) Age: the incidence of CRC diagnosis increases after the age of
40 and rises sharply after age 50, but there is an increase in the
young-onset rate due to the adoption of a Westernized lifestyle and
diet [9]

(ii) Family history of CRC (especially a first-degree relative
diagnosed at age 49 or younger) [10]

(iii) Hereditary predisposition

(a) Hereditary nonpolyposis colorectal cancer (HNPCC, Lynch syndrome)

(b) Familial adenomatous polyposis (FAP) [4, 9]

(iv) Inflammatory bowel disease (IBD): chronic inflammation is
assumed to underlie the cause of colitis-associated cancer, which
is associated with oxidative stress-induced DNA damage resulting in
the activation of procarcinogenic genes and silencing of
tumor-suppressor pathways [11]

(v) Adenomatous polyp: polyps are abnormal growths of the large
intestine lining that protrude into the intestinal lumen. Polyps
greater than one centimeter in diameter are associated with a
greater risk of cancer [12]


(i) Diets: Western diet rich in red meat, refined grains, desserts,
and low in fiber was reported to be associated with
increased CRC risk [10, 13, 14]

(ii) Cigarette smoking: carcinogens as aromatic amines,
nitrosamines, and polycyclic aromatic hydrocarbons in tobacco smoke
produce metabolites that can react with DNA or other macromolecules
to form DNA adducts inducing genetic mutations [15]

(iii) Obesity: obese women have higher risk of CRC than obese men
due to higher abdominal visceral adipose tissue volume
[16, 17]

(iv) High alcohol consumption (>2 glasses per day): ethanol
increases the activation of various procarcinogens present in
tobacco smoke, diets, and industrial chemicals to carcinogens
through the induction of CYP2E1 [18]

Table 3: Staging and survival of CRC.

Dukes'     TNM staging     Description                      Survival
staging                                                     (%)

           Stage 0         Carcinoma in situ

A          Stage I         No nodal involvement, no         90-100%
                           metastasis, tumor invades
                           submucosa ([T.sub.1]
                           [N.sub.0], [M.sub.0]), tumor
                           invades muscularis ([T.sub.2],
                           [N.sub.0], [M.sub.0])

B          Stage II        No nodal involvement, no         75-85%
                           metastasis, tumor invades
                           subserosa ([T.sub.3],
                           [N.sub.0], [M.sub.0]), invade
                           other organ ([T.sub.4],
                           [N.sub.0], [M.sub.0])

C          Stage III       Regional lymph nodes involved    30-40%
                           (any [T.sub.4], [N.sub.1]

D          Stage IV        Distant metastasis (any T, any   <5%
                           N, [M.sub.1])

Table 4: Primary and secondary prevention strategies of CRC.

(i) Diet. A diet high in vegetables, fruits, dairy products,

olive oil, fish, and whole grains and low in red and processed
meats has been shown to lower CRC risk [21-23].

(ii) Physical Activity. Physically active individuals have 24%
lower risk of CRC development than those who have a
sedentary lifestyle.

Physical activity promotes the production of interleukin-6
(IL-6) and decreases the expression of inducible nitric oxide
synthase (iNOS) and tumor necrosis factor-alpha (TNF-[alpha])
in plasma and colon, leading to enhanced immunity [24, 25].
(iii) NSAIDs. They reduce the risk of CRC by blocking

cyclooxygenase (COX) enzymes, so inhibit prostaglandin
production, which are known to promote tumor
angiogenesis and cell proliferation [26].


(i) Fecal Tests. Fecal occult blood test (FOBT) and fecal
immunochemical test (FIT) detect hidden blood in the stool,
while fecal DNA test detects DNA in the stool [27-29].

(ii) Flexible Sigmoidoscopy. It is performed using an endoscope
that allows the examination of the surface up to 60 cm from the
anal verge (rectum, sigmoid colon, and part of the descending
colon). It is done after colon lavage using enema or
administering laxatives without the need of sedation [30].

(iii) Colonoscopy. It is performed using an endoscope, which allows
an examination of the entire colon surface. It must be done
under intravenous sedation and requires being on a low-residue
diet, colon lavage using laxatives, and drinking plenty
of water the day before the test [31].

Table 5: Examples of some dietary components that decrease risk of

Fiber        (i) A high-fiber diet has a protective effect from
             CRC as it decreases transit time through the
             gastrointestinal tract, dilutes colonic contents,
             and enhances bacterial fermentation. This can
             increase the production of short-chain fatty acids
             that interfere with numerous regulators of the
             cell cycle, proliferation, and apoptosis such as
             [beta]-catenin, p53, and caspase 3 genes [35, 36]

             (ii) Corn, beans, avocado, brown rice, lentils,
             pear, artichoke, carrots, oatmeal, broccoli, and
             apples are examples of diet rich in fiber [37]

Fish oil     (i) Fish oil rich in omega-3 fatty acids may
             inhibit the promotion and progression of cancer
             through suppression of arachidonic acid-derived
             eicosanoid biosynthesis, which results in altered
             immune response to cancer and modulation of
             inflammation, cell proliferation, apoptosis,
             metastasis, and angiogenesis [38]

             (ii) It also influences transcription factor
             activity, gene expression, and signal
             transduction, which leads to changes in
             metabolism, cell growth, and differentiation

Olive oil    (i) Olive oil reduces deoxycholic acid in the
             human colon and rectum

             (ii) Deoxycholic acid was found to reduce diamine
             oxidase, a main enzyme for the metabolism of
             ingested histamine and control of mucosal
             proliferation in the ileal and the colonic mucosa

Folate       (i) Folate acts as donors of methyl groups in the
             biosynthesis of nucleotide precursors used for
             DNA synthesis and methylation of DNA, RNA,
             and protein and participates in the maintenance
             of genomic stability [42, 43]

             (ii) Spinach, broccoli, strawberries, raspberries,
             beans, peas, lettuce, lentils, and celery are
             examples of diet rich in folate [37]

Calcium      (i) Calcium can suppress epithelial cell
             proliferation in the colon by binding to bile
             acids and ionized fatty acids [44]

             (ii) Calcium can act directly by reducing
             proliferation, stimulating differentiation, and
             inducing apoptosis via upregulation of p21 and
             Bcl-2 in the colonic mucosa [44-47]

Table 6: Methods of allelic discrimination used in SNP genotyping

Enzymatic       Enzymatic cleavage is based on the ability of
cleavage        certain classes of enzymes to cleave DNA by
                recognition of specific sequences and structures.
                Such enzymes can be used for discrimination
                between alleles when SNP sites are located in an
                enzyme recognition sequence and allelic
                differences affect recognition. For example,
                restriction fragment length polymorphism (RFLP) is
                based on genotyping a SNP located in a restriction
                enzyme site using PCR product containing the SNP
                that is incubated with corresponding restriction
                enzyme. The reaction product is run on a gel, and
                SNP genotype is easily determined from the product
                sizes [64].

Primer          In a typical primer extension reaction, a primer
extension       is designed to anneal with its 3\ end adjacent to
                a SNP site and extended with nucleotides by
                polymerase enzyme. The identity of the extended
                base is determined either by fluorescence or mass
                to reveal SNP genotype, for example, the PinPoint
                assay, MassEXTEND tm, SPC-SBE, and GOODassay
                primer extension-based methods, where SNP-specific
                primers are simultaneously extended with
                various nucleotides using PCR products as a
                template [65].

Hybridization   Hybridization approaches use differences in the
                thermal stability of double-stranded DNA to
                distinguish between perfectly matched and
                mismatched target-probe. For example, the TaqMan[R]
                genotyping assay combines hybridization and 5                nuclease activity of polymerase coupled with
                fluorescence detection. The allele-specific probes
                carry a fluorescent dye at one end (reporter) and
                a nonfluorescent dye at the other end (quencher).
                The intact probes show no fluorescence owing to
                the close proximity between the reporter and
                quencher dyes. During PCR primer extension, the
                enzyme only cleaves the hybridized probe that is
                perfectly matched, freeing the reporter dye from
                the quencher. The reporter dye generates a
                fluorescent signal, whereas the mismatched probe
                remains intact and shows no fluorescence [66].

Ligation        Ligation approach employs specificity of ligase
                enzymes. When two oligonucleotides hybridize to
                single-stranded template DNA with perfect
                complementarity, adjacent to each other, ligase
                enzymes join them to form a single
                oligonucleotide. Three oligonucleotide probes are
                used in traditional ligation assays, 2 of which
                are allele-specific and bind to the template at
                the SNP site. The third probe is common and binds
                to the template adjacent to the SNP immediately
                next to the allele-specific probe. For example,
                combinatorial fluorescence energy transfer tags
                are composed of fluorescent dyes that can transfer
                energy when they are in close proximity. Tags with
                different fluorescence signatures can be created
                using a limited number of dyes by varying the
                number of dyes used and spacing between the dyes

Table 7: Some of the published GWASs on CRC (100).

Reference    Gene or region          Population          Sample size
 SNP (rs)                                                 for stage

rs4939827      18q21 SMAD7        First stage: UK         940 cases/
                                  Second stage: UK       965 controls

rs6983267         8q24            First stage: UK         930 cases/
                                  Second stage: UK       960 controls

rs10505477        8q24          First stage: Canada      1257 cases/
                                                        1336 controls
rs719725          9p24         Other stages: Canada,
                                  US, and Scotland

rs4779584      15q13 CRAC1        First stage: UK         730 cases/
                                  Second stage: UK       960 controls

rs4939827      18q21 SMAD7     First stage: Scotland

rs7014346         8q24           Second stage and         98 cases/
                               replication: Canada,     1002 controls
rs3802842         11q23         UK, Israel, Japan,
                                       and EU

rs4444235     14q22.2 BMP4        First stage: UK

rs9929218     16q22.1 CDH1                               6780 cases/
                                                        6843 controls
rs10411210     19q13 RHPN2       Replication: EU,
rs961253         20p12.3

Reference     Sample size for     Genotyping platform      Study
 SNP (rs)    subsequent stages       (Nb. of SNPs)       reference

rs4939827       7473 cases/       Asymetrix (550,163)      (101)
               5984 controls

rs6983267       7334 cases/        Illumina (547,647)      (102)
               5246 controls

rs10505477      4024 cases/          Illumina and          (103)
               4042 controls      Affymetrix (99,632)

rs4779584       4500 cases/        Illumina (547,647)      (104)
               3860 controls


rs7014346       16476 cases/       Illumina (541,628)      (105)
               15351 controls


rs9929218       13406 cases/       Multiple (38,710)       (106)
               14012 controls


Table 8: Gene polymorphisms associated with CRC.

Gene                     Reference     Effect on CRC
                         SNP (rs)
                                       A promoter polymorphism due to
Matrix                   rs34016235    a C to T substitution results
metalloproteinases-9                   in the loss of the binding
(MMP 9)                                site of a nuclear protein to
                                       this region of the MMP 9 gene
                                       promoter. The polymorphism is
                                       associated with lymph node
                                       metastasis of CRC.

COX-2                    rs20417       The C allele has lower
                                       promoter activity than the G
                                       allele, and GG genotype in
                                       smokers is associated with a
                                       significant increase in the
                                       risk of CRC compared to

Vitamin D receptor       rs1544410     Polymorphism of the vitamin D
                                       receptor gene to be associated
                                       with an increased risk of
                                       colon cancer.

Bone morphogenetic       rs4444235     The rs4444235 increases risk
protein 4 (BMP 4)                      of CRC development through its
                                       cis-acting regulatory
                                       influence on BMP4 expression.

Phospholipase A2         rs9657930     Polymorphisms in the
                                       phospholipase A2 gene is
                                       associated with the risk of
                                       the rectal cancer.

Colorectal adenoma       rs4779584     The rs4779584 polymorphism is
and carcinoma 1                        associated with increased risk
                                       of CRC among Caucasian not
                                       Asian populations.

Eukaryotic translation   rs16892766    The rs16892766 polymorphism is
initiation factor 3                    associated with increased risk
                                       of CRC but not adenoma among

Cadherin-1               rs9929218     The minor allele of rs9929218
                                       has reduced E-cadherin
                                       expression and resulted in
                                       worsening the survival of CRC

                                       The rs2234767 contributes to
FAS                      rs2234767     an increased risk of CRC by
                                       altering recruitment of SP1/
                                       STAT1 complex to the FAS
                                       promoter for transcriptional

Maternally               rs7158663     The rs7158663 changes the
expressed gene 3                       folding structures of
                                       maternally expressed gene 3;
                                       therefore, it contributes to
                                       genetic susceptibility of CRC.

Fc-g receptor gene       rs1801274     The rs1801274 changes the
                                       amino acid from histidine (H)
                                       to arginine. CRC patients with
                                       Fc/g receptor H/H genotype
                                       have better survival.

SPSB2 gene               rs11064437    The rs11064437 contributes to
                                       an increased risk of CRC by
                                       disrupting the splicing and
                                       introduction of a
                                       transcriptional isoform with a
                                       shortened untranslated region
                                       of SPSB2 gene.

TPP1                     rs149418249   Prevents TPP1-TIN2
                                       interaction, shortening the
                                       telomere length, and as a
                                       consequence, enhances cell

SLC22A5                  rs27437       The G allele decreases the
                                       expression of SLC22A5 via
                                       influencing the TF-binding
                                       upstream of the gene, leading
                                       to higher CRC risk.

KBTBD11                  rs11777210    C allele allows binding of
                                       MYC, a potent oncogene,
                                       preventing the expression of
                                       KBTBD11, a potent tumor

miR-17-92                rs9588884     The G allele lowers the CRC
cluster                                risk by decreasing
                                       transcriptional activity and
                                       consequently lowering levels
                                       of miR-20a.

Gene                     Reference

Matrix                   [78]
(MMP 9)


Vitamin D receptor       [80]

Bone morphogenetic       [81]
protein 4 (BMP 4)

Phospholipase A2         [82]

Colorectal adenoma       [83]
and carcinoma 1

Eukaryotic translation   [84]
initiation factor 3

Cadherin-1               [85]

FAS                      [86]

Maternally               [87]
expressed gene 3

Fc-g receptor gene       [88]

SPSB2 gene               [89]

TPP1                     [90]

SLC22A5                  [91]

KBTBD11                  [92]

miR-17-92                [93]

Table 9: The role of TGF-[beta] in various cell processes.

Cytostasis                (i) TGF-[beta] can activate cytostatic gene
                          responses at any point in the cell cycle
                          phases G1, S, or G2 [112]

                          (ii) TGF-[beta] induces activation of the
                          cyclin-dependent kinase (CDK) inhibitors
                          [113-115] and repression of the growth-
                          promoting transcription factors c-MYC and
                          inhibitors of differentiation (ID1, ID2, and
                          ID3) [116].

                          TGF-[beta] induces apoptosis through

                          (i) upregulation of SH2-domain-containing
Apoptosis                 inositol-5-phosphatase expression, which
                          inhibits signaling via the survival protein
                          kinase AKT [117]

                          (ii) induction of TGF-[beta]-inducible early-
                          response gene, which induces the generation
                          of ROS and the loss of the mitochondrial
                          membrane potential preceding the apoptotic
                          death [118, 119]

                          (iii) induction of death-associated protein
                          kinase [117]

                          For immune suppression, TGF-[beta] plays a
                          critical role through

Immunity                  (i) blocking antigen-presenting cells such as
                          dendritic cells, which acquire the ability to
                          effectively stimulate T cells during an
                          immune response [120]

                          (ii) decreasing the activity of natural
                          killer cells and neutrophils [121]

                          (i) TGF-[beta] induces the expression of
Angiogenesis              matrix metalloproteinases (MMPs) on both
                          endothelial cells and tumor cells, allowing
                          the release of the endothelial cells from the
                          basement membrane [122]

                          (ii) TGF-[beta] can also induce the
                          expression of angiogenic factors such as
                          vascular endothelial growth factor (VEGF) and
                          connective-tissue growth factor (CTGF) in
                          epithelial cells and fibroblasts [123, 124]

                          The migratory ability of epithelial cells
                          relies on loss of cell-cell contacts, a
                          process that is commonly referred to as the
                          EMT. It is marked by the loss of E-cadherin
                          and the expression of mesenchymal proteins
                          such as vimentin and N-cadherin [125].

Epithelial-mesenchymal    (i) TGF-[beta] was reported to destabilize
transition (EMT)          the E-cadherin adhesion complex resulting in
                          its loss in pancreatic cancer [126].
                          Alternatively, in epithelial cell lines, TGF-
                          [beta] can deacetylate the E-cadherin
                          promoter, thus repressing its transcription

                          (ii) TGF-[beta] was found to upregulate
                          vimentin in prostate cancer [128]

                          (iii) TGF-[beta] upregulates MMPs to promote
                          invasion through proteolytic degradation and
                          remodeling of the ECM [129]

Table 10: TGF-[beta]-induced non-Smad signaling pathways.

c-Jun N-terminal       (i) TGF-[beta] can rapidly activate JNK and
kinases (JNK)/p38      p38 through MAPK kinases (MKK4, MKK 3-6) in
activation             various cell lines [133,134]. Activation of
                       JNK-P38 plays a role in TGF-[beta]-induced
                       apoptosis and in TGF-[beta]-induced EMT

Extracellular          (i) TGF-[beta] was found to activate the
signal-regulated       mitogen-activated protein kinase (MAPK)-
kinase (ERK)           extracellular signal-regulated kinase (ERK)
activation             pathway which are important for TGF-[beta]
                       mediated EMT [125, 136].

Phosphoinositide       (i) TGF-[beta] was reported to rapidly
3-kinase (PI3-K)/      activate phosphoinositide 3-kinase (PI3-K) as
AKT activation         indicated by the phosphorylation of its
                       downstream effector Akt [137] (ii) Although
                       the PI3-K-Akt pathway is a non-Smad pathway
                       contributing to TGF-[beta]-induced EMT, it
                       can antagonize Smad-induced apoptosis and
                       growth inhibition [138]

Rho-like GTPases       (i) The Rho-like GTPases, such as Ras homolog
                       gene family, member A (RhoA) plays an
                       important role in controlling dynamic
                       cytoskeletal organization, cell motility, and
                       gene expression and is a key player in TGF-
                       [beta]-induced EMT [139]

                       (ii) TGF-[beta] regulates RhoA activity in
                       two different modes as it induces a rapid
                       activation of RhoA during the early phase of
                       stimulation and then downregulates the level
                       of RhoA protein at later stages, both of
                       these modes of regulation appear to be
                       essential for TGF-[beta]-induced EMT [140]

Table 11: Alterations of some components of TGF-# pathway in
human tumors.

TGF-[beta]R2           (i) The TGF-[beta]R2 gene has been mapped to
                       chromosome 3p, a chromosome in which mutation
                       was observed in small cell lung carcinoma
                       (SCLC), non-small-cell lung carcinoma
                       (NSCLC), CRCs, and ovarian and breast cancers
                       [142-144] (ii) Besides mutations in the
                       coding region of TGF-[beta]R2, loss of
                       expression of TGF-[beta]R2 in NSCLCs, bladder
                       cancer, and breast cancer were reported

TGF-[beta]R1           (i) The TGF-[beta]R1 gene has been mapped to
                       chromosome 9q (ii) Mutation in TGF-[beta]
                       gene was reported in ovarian cancer, head and
                       neck squamous cell carcinomas (HNSCC), and
                       breast cancer [148-150] (iii) Homozygous
                       deletion of TGF-[beta]R1 was also identified
                       in pancreatic and biliary adenocarcinomas

SMAD3                  (i) The gene for SMAD3 is located in
                       chromosome 15q21-q22 (ii) The rate of
                       mutation in the SMAD3 gene is rare, and there
                       are only few examples of such defects in
                       Smad3 expression that was found in some
                       gastric cancer and leukemia [152, 153]

SMAD2/SMAD4            (i) Chromosome 18q has genes encodes for
and SMAD7              SMAD2, SMAD4, and SMAD7 (ii) Mutation in
                       chromosome 18q was found in about 30% of
                       neuroblastoma, breast, prostate, and cervical
                       cancers and even more frequently in HNSCC
                       (40%), NSCLC (56%), colon cancer (60%),
                       gastric cancer (61%), and 90% of pancreatic
                       tumors [154, 155]

Table 12: Association studies of SNPs in SMAD7 gene and CRC.

Population          Reference    Location    Association    Reference
                     SNP (rs)
                                              In women:
African American    rs4939827    Intron 3        yes          [166]
and Caucasian       rs4464148    Intron 3        Yes
                    rs12953717   Intron 3        Yes
Caucasian           rs4939827    Intron 3        Yes          [167]
                    rs4464148    Intron 3         No
Swedish             rs4939827    Intron 3        Yes          [168]
European            rs4464148    Intron 3        Yes          [169]
                    rs4939827    Intron 3         No
                    rs4939827    Intron 3         No
Chinese             rs12953717   Intron 3        Yes          [170]
                    rs4464148    Intron 3         No
African American    rs4939827    Intron 3        Yes          [171]
Chinese             rs4939827    Intron 3        Yes           [76]
                                                CRC vs
                                             control: no
Romanian            rs4939827    Intron 3     Rectal vs       [172]
                                             cancer: yes
Caucasian           rs4939827    Intron 3        Yes          [173]
Croatian            rs4939827    Intron 3        Yes           [77]
Italian             rs4939827    Intron 3        Yes          [174]
Korean              rs4939827    Intron 3        Yes          [175]
Spanish             rs4939827    Intron 3        Yes          [176]
French              rs4939827    Intron 3        Yes          [177]
                    rs58920878   Intron 3        Yes

Table 13: Serum YKL-40 levels (ng/ml) in patients with
inflammation, tissue remodeling, or fibrosis [201].

Disease                     Median serum     Reference
                            YKL-40 (ng/l)
Viral hepatitis                   83
Noncirrhotic fibrosis            158           [202]
Posthepatitis cirrhosis          204
Rheumatoid arthritis             110           [203]
Streptococcus pneumoniae         342           [200]
Osteoarthritis                   112           [204]
UC, severe                        59
CD, severe                        59           [205]
Pulmonary sarcoidosis            201           [206]
Asthma                            92           [207]

Table 14: Serum YKL-40 levels (ng/ml) in patients with localized or
advanced cancer [201].

Disease                       Median serum         Reference
                              YKL-40 (ng/l)
Metastatic breast cancer      80                   [209]
CRC                           160                  [210]
Glioblastoma multiforme       130                  [195]
Lower grade gliomas           101
Primary breast cancer         57                   [211]
Small cell lung cancer        82
Local disease                 71                   [192]
Extensive disease             101
Metastatic prostate cancer    112                  [208]
Ovarian cancer, all stages    94
Ovarian cancer, stage III     168                  [212]
Ovarian cancer, relapse       94

Table 15: Association of some CHI3L1 SNPs with diseases.

Disease                           Population       Reference
                                                    SNP (rs)

Sarcoidosis                       Caucasian        rs10399931
Schizophrenia                     Caucasian        rs10399805
Liver fibrosis                    Caucasian        rs4950928
Glioblastoma                      Caucasian        rs4950928
Asthma and atopy                    Danish         rs4950928
Rheumatoid arthritis                Danish         rs10399931
Coronary heart disease             Chinese         rs10399931
Schizophrenia                      Japanese        rs4950928
Atrial fibrillation                 Danish         rs4950928
Asthma                        African Americans    rs4950928
Cervical cancer                   Taiwanese        rs10399805
Asthma                            Taiwanese        rs1538372
Atherosclerosis                   Taiwanese        rs10399931
Asthma                              Indian         rs4950928
Non-Hodgkin's lymphoma              Danish         rs4950928
Asthma                             Swedish         rs4950928
Venous thromboembolism              Danish         rs4950928
Coronary artery disease           Taiwanese        rs4950928

Disease                         Location      Association    Reference

Sarcoidosis                     Promoter           No          [226]
Schizophrenia                   Promoter          Yes          [163]
Liver fibrosis                  Promoter          Yes          [225]
Glioblastoma                    Promoter           No          [227]
Asthma and atopy                Promoter          Yes          [228]
                                Promoter           No
                                Promoter           No
Rheumatoid arthritis            Promoter           No          [229]
                                 Exon 5            No
Coronary heart disease          Promoter           No          [230]
Schizophrenia                   Promoter          Yes          [231]
Atrial fibrillation             Promoter           No          [232]
Asthma                          Promoter          Yes          [233]
Cervical cancer                 Promoter          Yes          [234]
                                Promoter           No
                                Promoter          Yes
Asthma                        Intron2/exon3       Yes          [235]
Atherosclerosis                 Promoter           No          [236]
Asthma                          Promoter           No          [237]
Non-Hodgkin's lymphoma          Promoter          Yes          [238]
Asthma                          Promoter           No          [239]
Venous thromboembolism          Promoter           No          [240]
Coronary artery disease         Promoter          Yes          [241]

Figure 1: Age-standardized CRC incidence rate
by sex and world area, GLOBOCAN 2012.

                              Males   Females

Australia/ New Zealand        44.8    32.2
Southern Europe               39.5    24.1
Western Europe                39.1    24.9
Northern Europe               36.5    25.3
Central and Eastern Europe    34.5    21.7
Northern America              30.1    22.7
Eastern Asia                  22.4    14.6
Micronesia/Polynesia          18.5    11.8
Western Asia                  17.6    12.4
South America                 17.1    14.6
Carribean                     16.3    16.6
South-Eastern Asia            15.2    10.2
Southern Africa               14.2    8.7
Melanesia                     11.1    6.9
Central America               8.8     7.1
Northern Africa               8.5     I6.9
Eastern Africa                7.1     6.1
South-Central Asia            7       5.2
Middle Africa                 4.7     4.8
Western Africa                4.5     3.8

Age-standardized rate per 100,000

Note: Table made with bar graph.
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Author:Fattah, Amal Ahmed Abd El-; Sadik, Nermin Abdel Hamid; Shaker, Olfat Gamil; Kamal, Amal Mohamed
Publication:Mediators of Inflammation
Date:Jan 1, 2018
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