Molecular pathogenesis of gallbladder cancer: An update

Mutat Res Fund Mol Mech Mutagen 816-818 (2019) 111674

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Review

Molecular pathogenesis of gallbladder cancer: An update Shravan Kumar Mishra, Niraj Kumari , Narendra Krishnani ⁎

T

Department of Pathology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, 226014, India

ARTICLE INFO

ABSTRACT

Keywords: Gallbladder cancer Mutation KRAS BRAF

Gallbladder carcinoma (GBC) is the most aggressive gastrointestinal malignancy throughout the world, with wide geographical variance. It is the subtype of biliary tract malignancy that has the poorest prognosis and lower survival among all biliary tract malignancies. Various factors are associated with GBC pathogenesis such as environmental, microbial, metabolic and molecular. Chronic inflammation of gallbladder due to presence of gallstone or microbial infection (eg. Salmonella or H. pylori) results in sustained production of inflammatory mediators in the tissue microenvironment, which can cause genomic changes linked to carcinogenesis. Genetic alterations are one of the major factors, associated with aggressiveness and prognosis. Researches have been done to explore suitable biomarker for early diagnosis and identify altered molecular pathways to develop appropriate biomarkers for early diagnosis, therapy and predicting prognosis. Different agents for targeted therapy against actionable mutations of molecules like EGFR, VEGF, mTOR, HER2, PDL-1, PD-1, MET, PI3K, Ncadherin, VEGFR, MEK1 and MEK2 are being tried. Despite these advancements, there is dismal improvement in the survival of GBC patients. Genetic aberrations other than actionable mutations and epigenetic modification including aberrant expressions of micro-RNAs, are also being studied both as diagnostic biomarker and therapeutic targets. Complex pathogenesis of GBC still needs to be unfolded. In this review we focus on the molecular pathogenesis of GBC elucidated till date along with future directions that can be explored to achieve better management of GBC patients.

1. Background Gallbladder Cancer (GBC) is the fifth most common gastrointestinal malignancy worldwide, often presenting at advanced stage, associated with extremely poor prognosis [1]. GBC is most common in India with an incidence of 9/100,000 and 1/100,000 in north-eastern and southern part of India respectively. It is most prevalent in northern and eastern parts of India such as Uttar Pradesh, Bihar, Orissa, West Bengal and Assam [2]. The other countries where GBC has high incidence are Chile (16–27/100,000), Poland (14/100,000), South Pakistan (11/ 100,000) and Japan (7/100,000), whereas, it is less common in United States (1.5/100,000) [3]. GBC is the most aggressive malignancy of biliary tract having a mean survival of 24.6 months [4,5]. Various risk factors associated with GBC include presence of gallstones of size > 3 cm [6], genetic and epigenetic alterations, aberrant expression of micro-RNAs and altered signaling pathways [7]. Gallstone (GS) formation is basically induced by calcium and magnesium and an NMR study showed significantly elevated level of these metals in GBC patients [8]. Genetic aberrations are being widely explored in GBC to

search for diagnostic, prognostic and predictive biomarkers. Despite advancements in GBC research, not much success has been achieved in improving the survival of these patients. This review focuses mainly on genetic changes in GBC patients discovered till date, with some future directions in identifying diagnostic, therapeutic and prognostic markers in GBC. 1.1. Mutations in oncogenes in GBC Genetic mutations can be either germline or somatic involving proto-oncogenes [9–20], tumor suppressor genes [21–25] and cell cycle and growth factors with their upstream and downstream signaling pathways like mitogen-activated protein kinase and phosphoinositide3kinase [12,16,18,20,25–29] which are involved in cell proliferation, differentiation and programmed cell death [30–32]. Somatic mutations identified in some cancers have transformed dramatically the management of cancers such as in lung and colorectal cancers [33–35]. Fan et al [36] reported ALK, EGFR and KRAS mutations in lung cancer whereas, Lovly et al [37] found BRAF, KIT and NRAS mutations in

Abbreviations: EGFR, epidermal growth factor receptor; VEGF, vascular endothelial growth factor; mTOR, mechanistic target of rapamycin; HER2, human epidermal growth factor receptor 2; PDL1, programmed death ligand 1; MET, mesenchymal epithelial transition; PI3K, phosphatidylinositol-4,5-bisphosphate 3-kinase ⁎ Corresponding author. E-mail addresses: [email protected] (S.K. Mishra), [email protected] (N. Kumari), [email protected] (N. Krishnani). https://doi.org/10.1016/j.mrfmmm.2019.111674 Received 14 February 2019; Received in revised form 17 June 2019; Accepted 24 June 2019 Available online 06 July 2019 0027-5107/ © 2019 Elsevier B.V. All rights reserved.

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melanoma as molecular biomarkers for predicting drug response. Besides their role as diagnostic marker, these mutations also act as candidates for targeted therapy. However, in GBC it is still challenging to identify such marker due their genetic heterogeneity. Different mutations in oncogenes, tumor suppressor genes and growth factors in GBC are shown in Table 1.

1.2. Tumor suppressor (TP53) gene mutation TP53 is a member of tumor suppressor genes and regulates cell cycle arrest, apoptosis, gene transcription etc. The alterations in TP53 gene and its association with GBC has been reported in many studies commonly in exons 5, 6, 7, 8 and 9 in GBC patients. Javle et al [49] reported 59% and Roa et al [70] reported 52% TP53 mutations in GBC. They found frequent mutations in exons 5 and 6 compared to exons 7, 8 and 9 [70]. Vidaurre et al [62] found 33.3% TP53 mutations with G:C to A:T transition being frequent substitution in Peruvian GBC patients. In addition to these, they found frequent mutations in exons 7 and 8 compared to exons 5 and 6 of TP53. TP53 mutations in Peruvian GBC patients were similar to that reported from Bolivia (50%), Hungary (33.3%), Chile (55.0%), and Japan (50.0%) as reported by Asai et al [71], Nagahashi et al [72] and Yokoyama et al [48]). Li et al [59] and Li et al [44] from China reported 50 and 47% TP53 mutation in GBC respectively whereas, Saetta et al [16] from Greece and Kim et al [25] from South Korea reported 18% and 33% TP53 mutation respectively. Similar to the high frequency of TP53 mutation in GBC patients of America, Europe and Asia, Iyer et al [68] from western India reported 35% TP53 mutations, however, Kumari et al [40], Nigam et al [73] and Yadav et al [67]) from north and north-eastern parts of India found 8%, 9% and 18% TP53 mutations in GBC respectively.

1.1.1. KRAS KRAS gene encodes KRAS protein, which takes part in RAS/MAPK signaling pathway and PIK3CA pathway. The KRAS protein has GTPase activity that plays crucial role in regulation of signals through various signaling pathways. The data from western countries showed lower incidence of KRAS mutations ranging from 0 to 10% [38,39], however, it is much more variable in eastern countries ranging from 2 to 59%. KRAS codon 12 and 13 mutations vary between 2–80% in GBC in different studies [40–53,25,54–56,14,57,58]. Li et al [59] reported 7.1% mutation in codon 61 of KRAS. Sabato et al [60] from Brazil and Pramanik et al [61] found mutation in codons 55 and 25 of KRAS with a frequency of 33% and 53% respectively. G to A is the commonest substitution found in codon 12 of KRAS [25,12]. Studies from America have reported KRAS mutation frequency ranging from 0 to 33% [29,62,63,45,47,49,64,55,60,38]. Saetta et al [16] from Greece has shown 25% KRAS mutation in GBC whereas Rashid et al [12], Li et al [44] and Li et al [59] from China have reported lower frequency of KRAS mutation of 3%, 7.8% and 7.1% respectively. Similarly studies from Japan (Shigematsu et al [41], Yokoyama et al [48], Noguchi et al [52], Shibata et al [53] and Hanada et al [14]) have also reported variable mutation frequency in KRAS ranging from 2 to 38%. Kim et al [25] reported 20% KRAS mutations in Korea. Huang et al [42] and Chang et al [51] from Taiwan reported 3.3 and 11.4% KRAS mutation respectively. KRAS mutation frequency has been reported in the range of 2–41% in India [40,57]. Singh et al [56] and Sharma et al [54] found association of KRAS mutation with advanced stage of GBC.

1.3. Epigenetic modification inGBC Epigenetic modification is a well-defined mechanism in gene expression either via transcriptional repression or activation [79,80] which cause modification of DNA (methylation) and histones (acetylation, methylation and phosphorylation). RNA interference has been discovered as a new epigenetic mechanism, which is involved in posttranscriptional silencing [81]. DNA methylation is the most frequently studied epigenetic mechanism, involved in various biological processes occurring at 5′ end of cytosine in cytosine-guanine dinucleotide (CpG) [80–82]. CpG islands accounts for 15% of human genome [79] and approximately 60% of human CpG islands are located in promoter region. Generally, the cytosine rings of these CpG islands are unmethylated [83]. Various tumors are associated with hypermethylation of CpG islands which are found in demethylated regulatory regions. Most of the tumor suppressor genes are silenced by DNA methylation in their demethylated regulatory regions [84–89]. However, in normal cells, genes showing oncogenic properties are silenced via methylation of their promoter regions which can reactivate in cancer cells by loss of methylation [90]. Various studies reported hypermethylation and hypomethylation of tumor suppressor genes and oncogenes in GBC. Furthermore, similar to the variation in mutation frequency with geographical origin, methylation frequency also varies in different geographical regions. Variable methylation frequencies of different genes such as PTEN, APC, P16, CDH1, CDH13, FHIT, SEMA3B and MLH1 have been reported. Garcia et al [85] from Chile investigated the frequency of epigenetic mechanism of 14 genes through methylation specific PCR, out of which 4 (DAPK1, DLC1, TIMP3, RARβ1) showed increase in methylation status throughout the disease progression from chronic cholecystitis to advanced GBC, ranging from 60%, 39%, 39%, and 43% respectively. They found DLC1 methylation to be significantly associated with poor prognosis, however, methylation of MGMT correlated with better prognosis and survival. Kagohara et al [91] from Chile evaluated promoter methylation through quantitative methylation specific PCR and found methylation of APC, CDKN2A, ESR1, MCAM, MGMT, PGP9.5, RARβ and SSBP2 to be 32%, 26%, 42%, 37%, 29%, 21%, 37% and 53% in GBC respectively. Roa et al [92] from Chile found 60% methylation of CDH1 gene, 20% methylation of CDKN2A, 32% each of FHIT and APC and 4% of MLH1 in GBC. Roa et al [93] evaluated methylation of promoter region of CDKN2A (p16), MLH1, APC, FHIT, and CDH1 (E-cadherin) genes, and observed 5%, 20%, 30%, 40% and 65% methylation in promoter region of MLH1, CDKN2A,

1.1.2. BRAF BRAF gene encodes a protein, which is a part of MAPKinase signaling pathway and controls several important cell functions. The data worldwide shows that BRAF mutation rates are highly controversial, ranging from 0 - 33%. Studies from West by Goldenberg et al [17], Zauber et al [47], Rish et al [45], Javle et al [49] and Ross et al [64] have reported very low incidence of BRAF mutation ranging between 0 - 1% in GBC. Goeppert et al [65] and Mallika et al [66], from Germany did not find V600E mutation of BRAF in GBC patients, however, Saetta et al [16] from Greece showed high incidence of BRAF V599E mutation (33.0%). Shigmatsu et al [41] 2006 from Japan reported absence of BRAF mutation in GBC. Studies from China have reported 0 - 6% mutation in BRAF [59,44], however, from India Kumari et al [40], Yadav et al [67] and Iyer et al. [68]) did not find any BRAF mutation in GBC. 1.1.3. PIK3CA Phosphatidylinositol 3-kinase protein is composed of regulatory subunit (85 kDa) and a catalytic subunit (110 kDa) that activates signaling cascade involved in various process like cell growth, survival etc. Exon 9 and 20 of PIK3CA are the most frequently mutated exons with variable frequency [69,63] that include E542 K, E545 K, E545 G and H1047R, H1047 L point mutations. Mutation of PIK3CA has been reported by different groups ranging from 0 to 16.6%. Sabato et al [60] from Brazil did not find any PIK3CA mutation in GBC, however, studies from USA reported 12.5% [29], and Chile reported 16.6% [63] PIK3CA mutations in GBC. Yokoyama et al [48] did not find PIK3CA mutation however; Noguchi et al [52] from Japan reported 21.4% PIK3CA mutations in GBC. Reiner et al [20] from Switzerland reported 4.0% PIK3CA mutation. Kumari et al [40] and Sharma et al [54] reported 4.0% and 20.6% PIK3CA mutation in Indian GBC cases. 2

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Table 1 Mutation Frequency of genes susceptible for GBC development in different population. Gene

Description

Frequency

Method

KRAS

Proto-oncogene, GTPase

11.0%

Comprehensive genomic profiling Mass spectrometric genotyping Sequencing

0.0% 8.0% 11.0% 7.0% 5.2% 0.0% 7.0% 3.3% 11.4% 33% 3.0% 7.8% 25.0%

BRAF

Proto-oncogene, Serine-threonine kinase

14.3% 2.0% 15.3% 9.0% 38.4% 20.0% 23.5% 2.0% 38.0% 41.0% 1.0% 1.0% 0.0% 0.0% 6.0% 0.0 0.0% 0.0% 5.90% 0.0% 0.0% 33.0%

PIK3CA

Phosphatidylinositol- 4,5-Bisphosphate-3kinasecatalytic subunit alpha

EGFR

Epidermalgrowth factorreceptor

N-RAS

NRASProto- oncogene,GTPase

ERBB2

Erb-B2Receptor Tyrosine Kinase2

ERBB3

Erb-B2Receptor Tyrosine Kinase3

TP53

Tumoursuppressor gene

CTNNB1

Catenin beta1

CDKN2A

Cyclindependent kinase 2alpha

AA Change

Mutector assay Sequinom massarray Sequencing Next generation Sequencing Sequencing Sequencing Sequencing Sequencing Targeted NGS PCR-SSCP& Sequencing Sequencing Sequencing Sequencing Sequencing RFLP PCR-SSCP Sequencing Sequenom MassArray RFLP Comprehensive genomic profiling Comprehensive genomic profiling Sequencing Sequencing Sequencing Mutector assay

35.7% 9.1% 18.0% 8.0% 9.0% 4.8% 4.0% 41.0%

RFLP Ultradeep Sequencing Sequenom Mass Array Sequencing Sequencing Sequenom Mass Array Sequencing

16.6% 0.0% 4.0% 20.6% 4.0% 9.0% 20.6% 6.3% 8.8% 7.0% 16.0% 8.0% 11.8% 27.0% 52.0% 25.0%

Codon 12 &13 G12D& G13D

Codon12 & 13 Ile55Thr Gly12Asp Gly12Arg, Gly12Val, Gly13Asp G12R, G12D & G13D G12 V, G12D & G12S Codon 12 Gly12Asp G12QG12D Q61L Gly12Ser Codon 12 Codon12

Targeted Sequencing Wholeexome sequencing Sequencing PCR-SSCP& Sequencing Mass spectrometric genotyping Sequencing Sequencing Sequencing Sequencing SequenomMass Array Sequencing Sequencing Mass spectrometric genotyping Sequencing Whole-exome sequencing Next generation Sequencing Whole-exome sequencing Whole-exome sequencing Whole-exome sequencing Sequencing PCR-SSCP& Sequencing PCR-SSCP

12.5%

Gly12Asp

Val599Glu

Population

Reference

USA

[49]

USA

[29]

USA USA USA Chile Peru Toronto& HongKong

[47] [50] [45] [43] [62] [46]

Taiwan Taiwan Brazil China China

[42] [51] [60] [12] [44]

Greece

[16]

Japan Japan Japan Japan Japan Korea India India India India USA

[52] [41] [53] [48] [14] [25] [69] [40] [56] [57] [50]

USA

[49]

USA USA USA Stanford& Washington Japan China China Brazil Germany Greece

[47] [17] [74] [45] [41] [59] [44] [60] [65] [16]

E545 K, E542K

USA

[29]

E542 K, E545 K, E545 G, H1047R, H1047L

Chile Brazil Switzerland Indian Indian Italy Indian USA

[63] [60] [20] [69] [40] [75] [69] [29]

G12C, G12V S310 F S310Y S310F

Indian China

[69] [76] [49]

V104 L V104M

China

[76]

China Chile Greece

[76] [70] [16]

Korea

[25]

Indian Indian Indian China Japan Indian Brazil

[73] [67] [40] [12] [77] [40] [60]

E542K H1047R, H1047L H1047R, E545K T790M G12D

Arg248Trp, Arg248Gln, Arg282Trp, Gln285Asp Arg249Ser Arg175His,Arg273Cys, Asp281Gly

Ala127Ser, Ala148Thr,W15X

(continued on next page) 3

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Table 1 (continued) Gene

Description

Frequency

Method

AA Change

IDH2 IDH1 SMAD4 KMT2C

Isocitrate dehydrogenase2 Isocitrate dehydrogenase 1 SMADFamily member 4 Lysinemethyl transferase 2C

11.8% 7.0% 11.0% 11.0%

Sequencing Sequenom Mass Array Whole-exome sequencing Whole-exome sequencing

R140Q

FHIT, APC, and CDH1. Takahashi et al [94] from Santiago, investigated methylation profile of 24 known or suspected tumor suppressor genes, out of which 10 genes had high frequencies of aberrant methylation. They detected 8 genes (3-OST2 (72%), CDH13 (44%), CDH1 (38%), RUNX3 (32%), APC (30%), RIZ1 (26%), P16INK4A (24%), and HPP1 (20%) with significantly high methylation frequency in GBC as compared to chronic cholecystitis. House et al [95] from United States and Chile, studied methylation pattern of six candidate tumor suppressor genes in GBC, chronic cholecystitis and normal gallbladder control. They found that p16 (56%), p73 (28%), APC (27%), and hMLH1 (14%) were frequently methylated in GBC. The methylation frequencies of APC and p73 genes were significantly different among USA and Chile. APC methylation was found in 42% cases in USA but in only 14% Chilean cases, however, p73 methylation was common in Chilean cases as compared to USA. Klump et al [87] from Germany studied the potential diagnostic role of promoter methylation of p16INK4a and p14ARF in GBC and found high frequencies of promoter methylation of p16INK4a (60%) and p14ARF (40%). Tadokoroet al [88] and Tozawaet al [96] from Japan reported 22% and 73% methylation of p16 gene. Tozawaet al [96] and Koga et al [97] showed 11% and 41% CDH1 methylation in GBC. Ali et al [98] reported 48% PTEN hypermethylation in Indian GBC patients. Tekcham et al [99] investigated the methylation pattern of APC promoter region of exon 1 and 2 and found 96% methylation of promoter of APC exon 1 in GBC. They found down-regulation of exon 1 in grade II and grade III GBC, however exon 2 was normally expressed. These findings suggest the role of epigenetic silencing of APC in advanced GBC. The methylation frequency in different genes are shown in Table 2.

Population

Reference Indian USA China China

[69] [78] [76] [76]

pathophysiology of tumor (Table 4). 1.6. Copy number variations (CNV) CNV results from genetic rearrangement like deletion or duplication of genetic material. Rearrangement of a stretch of megabases (Mbs) to a few kilobases (Kbs) of nucleotide sequence in genome including promoter or coding regions consequently results in development of disease phenotype. Various groups have reported the association of CNV with the pathogenesis of different cancers [124–127] (Table 5). Sharma et al [54] found significant deletions (4q35.1) and amplifications (20p12.1, 12q14.2 and 12q14.3) of chromosome in 13 of 18 GBC patients suggesting their role in GBC pathogenesis [54] 1.7. Micro-RNAs inGBC MicroRNAs (miRNAs) are 17–25 nucleotide long noncoding RNA act as regulators of gene expression [139,140]. Till date a large number of miRNAs have been identified which are involved in regulation of various biological, developmental and physiological process [141–143]. They can act as either tumor suppressors or oncogene. Oncogenic miRNAs act directly on transcript of gene having apoptotic and anti-proliferative roles [144]. In addition, tumor-suppressor miRNAs down regulate the expression of genes involved in cell proliferation and differentiation [145]. Many studies have found association of altered miRNAs expression with cancer progression [146–148] including GBC [149]. Oncogenic miRNAs in GBC (miR-155, miR-20a, miR-182) are up regulated and associated with their aggressive biologics like cell migration, metastasis, vascular invasion and poor prognosis [150–152]. However, tumor suppressive miRNA in GBC (mir-34a, miR-335, miR-135-5p, miR-26a,miR-1, miR-145 and mir-146b-5p) are down regulated and associated with aggressive tumor behavior [153–156] (Table 6).

1.4. Microsatellite instability in GBC Microsatellite instability (MSI) is an alteration in the number of sequence repeats of microsatellite markers, caused by insertion or deletion of repeat units [103]. The DNA mismatch repair (MMR) complex repairs the unstable microsatellite. The deficiency of DNA MMR complex results in microsatellite instability. The different MMR proteins include hMLH1 (human MutL Homologue 1) hMSH2 (human MutS homologue 2), hMSH3 (human MutS homologue 3) and hMSH6 (human MutS homologue 6) that bind to DNA and repair the mismatched sequence [104] [105]. MSI can alter the tumor biology through the inactivation of several genes. The role of MSI has been studied in various cancer types [106–110] and found to be associated with pathogenesis and prognosis of GBC (Table 3) [111]. Mishra et al [112] reported MSI-H of markers (D13S317, FES/FPS and F13A01) in 10% of GBC patients. High MSI in E-cadherin (CDH1) (67%) [113], and FHIT (17.5%) has been reported from India [114].

1.8. Immune check points in GBC pathogenesis Tumor cells express the programmed death ligand-1 (PDL-1), which binds and inhibits the function of programmed death-1 (PD-1) present on T lymphocytes. It is associated with aggressive biology of the tumor and prognosis of various cancers [164–166]. Mutations of ERBB2/3 has shown up regulated PD-L1 expression in GBC cells, activating PI3K/ AKT signaling pathway leading to the inhibition of normal T-cell mediated cytotoxicity in-vitro contributing to growth and progression of GBC in vivo. ERBB2/3 mutations serve as useful biomarkers in identifying GBC patients sensitive for ERBB2/3 inhibitors or PD-L1 monoclonal antibody which reverses its immunosuppressive effect [76]. Our institute is a tertiary care centre with high volume of GBC resections. The authors have studied mutation profile, microsatellite instability, loss of heterozygosity, copy number variations, and metabolic profile of GBC (Tables 1–5) to find biomarkers for early diagnosis of GBC and explore actionable targets for therapy which may improve the prognosis and survival in GBC patients.

1.5. Loss of Heterozygosity (LOH) in GBC Loss of Heterozygosity (LOH) is one of the most common genetic abnormalities in genome of cancer. There are various mechanisms which can result LOH such as deletion of an allele, duplication of a chromosome or chromosomal region and contemporaneous loss of another allele. LOH has been reported in various chromosomal regions in GBC [117], including 2p, 3p, 5q, 7q, 8p, 9p, 17p and 22q [118–120]. Furthermore, GBC shows allelic loss in various regions of known and putative tumor suppressor genes which are involved in the

2. Current approaches for management of GBC Surgical resection is one of the major therapeutic cures of GBC 4

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Table 2 Frequency of Epigenetically altered gene in GBC patients. Gene PTEN CDO1 WIF-1 APC

Full Name

Function

Frequency

Population

Method

Reference

48% 47(47/99) 72% 96% 32% 35 (8/23) 32 (8/25) 40 (8/20) 30 (15/50) 26 (14/54) 26 (5/19)

India Japan china India Chile Chile Chile Chile Chile Chile, USA Chile

MSP Q-MSP MSP MSP Q-MSP MSP MSP MSP MSP Nested, MSP Q-MSP

[98] [100] [101] [99] [91] [85] [92] [93] [94] [95] [91]

26 (6/23) 20 (5/25) 73 (37/51) 20 (4/20) 15 (8/54) 24 (12/50 24 (9/38) 22 (2/9) 60 (3/5) 56 (30/54) 42 (8/19) 37 (7/19) 29 (2/7) 30 (7/23) 13 (7/54) 21 (4/19) 37 (7/19) 44 (10/23) 14 (7/50) 4 (2/54) 53 (10/19) 17 (4/23) 4 (1/25) 4 (2/50) 5 (1/20) 0 (0/9) 13 (7/54) 65 (15/23) 60 (13/20) 65 (13/20) 41 (9/22) 38 (19/50) 11 (1/9) 70 (16/23) 44 (22/50) 57 (13/23) 32 (8/25) 66 (33/50) 30 (6/20) 61 (14/23)

Chile Chile Japan Chile China Chile Chile Japan Germany Chile, USA Chile Chile Chile Chile Chile, USA Chile Chile Chile Chile Chile, USA Chile Chile Chile Chile Chile Japan Chile, USA Chile Chile Chile Japan Chile Japan Chile Chile Chile Chile Chile Chile Chile

MSP MSP MSP MSP MSP MSP MSP MSP MSP Nested MSP Q-MSP Q-MSP Q-MSP MSP Nested MSP Q-MSP Q-MSP MSP MSP Nested MSP Q-MSP MSP MSP MSP MSP MSP Nested MSP MSP MSP MSP Nested MSP MSP MSP MSP MSP MSP MSP MSP MSP MSP

[85] [92] [88] [93] [22] [94] [102] [96] [87] [95] [91] [91] [91] [85] [95] [91] [91] [85] [94] [95] [91] [85] [92] [86] [93] [96] [95] [85] [92] [93] [97] [94] [96] [85] [94] [85] [92] [86] [93] [85]

8 (4/50) 22 (2/9) 26 (13/50) 39 (9/23)

Chile Japan Chile Chile

MSP MSP MSP MSP

[94] [96] [86] [85]

Adenomatous polyposis coli

Cellmigration, adhesion and apoptosis

Cyclin-dependent kinase inhibitor 2A

Cellcycle regulation

O-6- Methyl guanineDNA methyl transferase

Methyl transferase

Retinoic acid receptor, beta

Encodes retinoic acid receptorbeta (mediates cellular signaling)

Human homologs of the MutLgeneof bacteria

Mismatch repair

CDH1

Cadherin 1, type 1, E-cadherin (epithelial)

Tissue invasion (cell-cell adhesion)

CDH13

Cadherin 13, H- cadherin (heart) Fragile histidine triad gene

Tissue invasion (cell-cell adhesion) Regulation of DNA replication and apoptosis

Death-associated protein kinase 1

Serine-threonine kinase

BLU TIMP3

Zincfinger Metallo peptidase inhibitor 3

SEMA3B

Sema domain, immunoglobulin domain (Ig), shortbasic domain, secreted, (semaphorin)3B Human homolog of Drosophila Round about (ROBO1)

Cell-cycle regulation Degradationof the extracellular matrix Inductionof apoptosis

92 (46/50)

Chile

MSP

[86]

Cell migration and metastasis

22 (11/50)

Chile

MSP

[86]

P16

ESR1 MCAM MGMT PGP9.5 RARβ

SBPP2 MLH1

FHIT

DAPK1

DUTT1

patients with stage I, II and III. Patients with stage IV GBC are unresectable because of lymphatic metastases, peritoneal implants, or invasion of major vessels. Fluoropyrimidine-based chemo-radiotherapy or gemcitabine chemotherapy (CT) alone are generally considered in patients with adequate performance status and intact organ function as adjuvant treatment for unresectable, recurrent, or metastatic diseases [167,168].

2.1. Targeted therapy GBC is one of the subtypes of billiary tract cancer. Unfortunately, large number of the patients with GBC present in advanced stage of disease, when systemic chemotherapy is the only option for treatment of those patients. Now a days next-generation sequencing has produced detailed information about the genetic landscape in GBC similar to other cancers, which has led to the discovery of various actionable mutations [169]. Biomarker driven clinical trial studies have evaluated 5

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Table 3 High Frequency micro satellite instability (MSI-H) in GBC patient of different population. MSI markers

BAT26, BAT25, D2S123, D5S346, D17S250, BAT40, D3S1067, D3S1286, D3S1262, D3S1478, D12S1638, D12S347, D16S265 D2S123, D3S1067, D3S1265, D5S107, D5S346, TP53, D17S578, D17S787, D18S34, Mfd41 BAT25 6FAM (BAT-25, D2S123), VIC (BAT-26, D17S250), or NED (D5S346) D16S421 (16q21.1), D16S496 (16q21.1), D16S503 (16q13), D16S512 (16q21–22), D16S2624 (16q21-22), D16S3021 (16q22–23) D3S1217,D3S1300,D3S1313, D3S1600,D3S2757 D13S317, FES/FPS, F13A01

Genes

Method

Frequency

Population

References

MSH2/MSH6 MLH1/ PMS2 –

IHC

7.8%

Boston (USA)

[111]

PCR

10.0%

Temuco, Chile

[115]

– – E-Cadherin (CDH1)

PCR PCR PCR

41.0% 42.1% 67.0%

Japan Japan India

[116] [72] [113]

FHIT

PCR PCR

17.5% 10.0%

India India

[114] [112]

Table 4 LOH at various chromosomal regions of various genes in GBC patients of different populations. S.No.

Loss of Heterozygosity (LOH)

Gene associated with LOH region

Population

Reference

1

> 60% Frequency: 3p, 6q, 7q, 8p, 9p, 9q, 11q, 12q, 17p, 18q, 19p, 22q, and Xq Tumour suppressor gene region: 1p34-36, 3q13, 4p16, 6q21, 7q32,7q36,9q22-31, 9q34, 11q13-14, 12q21-23, 18q12, 19p1213, 21q11-20, Xp11, and Xq34 > 88% Frequency: 3p (3p22-24, 3p21.3, 3p14.2, 3p12), 8p (8p23,8p22,8p21) 9q (9q31, 9q3133, 9q34.2- 34.3), and 22q (22q11.2, 22qq12.2-q12.3)

3p14-21, 5q11-23 (APC), 8p22-23,9p21-22 (p16Ink4/CDKN2), 13q1314, 17p11-13 (p53), and 18q22-23 (DCC, DPC4) 3p22-24 (RARβ), 3p14.2 (FHIT),8p22 (FEZ1/LZTS1), 9q32-33 (DBCCR1), 22q12.2q12.3 (NF2) Deletion on chromosome: 14q22 (CDKassociated phosphatase)

Chile

[117]

Chile

[121]

Japan

[122]

DUTT1, FHIT, APC, p16, FCMD, RB1, p53, and DCC

India

[123]

2 3

4

> 50% Frequency: 2p, 4p, 4q, 8q, 9q, 10p, 14p, 14q, 16p, 19p, 21pXp, Chromosome with highest deletion region: 2p24 (100%), 14q22 (75%) and 21q22 (75%) 3p12, 3p14.2, 5q21, 9p21, 9q, 13q, 17p13, and 18q

Table 5 Copy Number Variation (CNV) in various cancer types. Chromosomal region

Genes

Tissue

References

20p12.1,12q14.2, 12q14.3,4q35.1

MACROD2,RASSF3,HMGA2, RPSAP52,ENPP6,IRF2,CASP3, CCDC111,PRIMPL,MLF1IP,CENP U,ACSL1,ACSL1,SLED1 NBPF – PIK3CA, TNK2, APC, IRX1, MET, EGFR, c-MYC, HER2, TP53, AURKA, C20orf11

GBC

[54]

Neuroblastoma Breast Cancer Gastric cancer

[124] [125] [128–138]

EGFR

Non–Small-Cell Lung Cancer

[127]

1q21.1 chromosome 8 3q26.3, 3q29, 5q21-q22,5p15.33, 7q21,7p12,8q24.1,17q21, 17p13.1, 20q13, 20q13.33 7p12

various novel agents in phase I and II trials. Epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor that regulates cell proliferation, survival, angiogenesis and invasion through the MAPK pathway and PI3K/AKT pathway [170]. Agents used in targeted therapy either prevent ligand binding and activation of these receptors or competitively bind with tyrosine kinase domain (ATP binding domain). Erlotinib in phase II clinical trial has shown promising results in patients with biliary tract cancer [171]. Another phase II clinical trial suggested efficacy of cetuximab followed by gemcitabine plus oxaliplatin on patients of advanced GBC and cholangiocarcinoma [172–175]. Vascular endothelial growth factor (VEGF) has been correlated with aggressiveness of GBC. A multicentric phase II trial showed promising results of bevacizumab and sorafenib which acts on VEGF in metastatic GBC patients [176,177]. HER2 (ERBB2) mediates its signaling via the MAPK and PI3K pathways. Lepatinib has been studied in phase II as a dual HER2 and EGFR inhibitor for patients of advanced biliary tract cance [178]. PI3K/mTOR is signaling is crucial for cell growth and survival. Activation mutation of PIK3CA has been found in GBC and everolimus has been used against mTOR as first line in patients with metastatic disease [179]. The associations of MEK pathway signaling cascade mutations with GBC pathogenesis has also been reported. Selumitinib is a MEK inhibitor which has been used in phase II

clinical trial study against advanced biliary tract cancer patients [180]. 2.2. Immunotherapy Tumor evasion of the immune system is frequently mediated by cytotoxic T-lymphocytes associated antigen 4 (CTLA4) or the interaction between programmed cell death 1 (also known as PD1) and its ligand (also known as PDL1) [181]. It will be important to investigate the potential of blocking these immunosuppressive pathways with monoclonal antibodies in conjunction with the currently used immunotherapeutic approaches in biliary tract cancer. The anti-CTLA4 antibody, Ipilimumab has shown great promise in melanoma [182], but it has not yet been studied in biliary tract cancer (Table 7). 3. Conclusions Despite the advance researches in GBC, the knowledge about candidate markers useful in diagnosis and therapy still remains limited, as knowedge about genetic mutations and related altered pathways still remain unclear. Epigenetic studies have shown variety of genes to be epigenetically modified in GBC, but there is lack of sufficient knowledge about the exact role of these modifications in GBC. MiRNAs have 6

Mutat Res Fund Mol Mech Mutagen 816-818 (2019) 111674

S.K. Mishra, et al.

Table 6 Aberrant expression of micro-RNAs in GBC patients. mi RNAs

Expression level

Target

Function

Role

References

miR-29c-5p

Down

CPEB4

TSG

[157]

miR-125b

Down

–

TSG

[158]

mir-218-5p Mir-146b-5p

Down Down

BMI-1 EGFR

TSG TSG

[159] [156]

mir-130a mir-26a mir-34a hsa-mir-135a-5p mir-133a/b, mir-143-3p/5p, mir- 991-5p, mir125b-5p, mir-29c-3p, mir-195-5p, mir-139- 5p, mir29c-5p, mir-1005p, mir-148a-3p, mir-376c, mir- 187-3p, mir365a-3p, mir29b-3p, mir-497-5p, mir-654-3p, mir-411-5p, mir-125a5p, mir-26a-5p, mir-101-3p, mir- 495, mir381-3p, mir154-5p,mir-99a-3p,mir-328, mir-299-5p,mir30e-3p, mir-29b-2-5p, mir-379-5p, mir140-5p, mir-24-1-5p, mir- 101-5p mir-145-3p/5p

Down Down Down Down Down

– HMGA2 PNUTS VLDLR –

Lymph node metastasis, overall survival, disease free survival and MAPK pathway activation Tumor differentiation, lymph metastasis, tumor invasion and poor survival Cell proliferation,Invasion Apoptosis,G1phase Arrest. Cell proliferation, Invasion Cell proliferation Cell proliferation Poor prognosis Cell proliferation.

TSG TSG TSG TSG TSG

[160] [161] [154] [139] [162]

mir-1 mir-182 mir-155

Down UP UP

VEGF-A, AXL CADM1

mir-20a let-7a, mir-200b, mir-143, mir- 31, mir-335, mir551 mir-21, mir-370, mir-187, mir- 122, mir-202 mir-106a, mir-96 mir-223 mir- 27a mir-17 mir15b mir142-5p mir-142-3p mir-21 mir-665 mir-714 mir-763 mir- 466f-3p mir-145 mir-193 mir-467e mir-143 mir-881 mir- 720 mir-706 -mir-122 mir-378 mir-335

UP Down

Down

OG

[152] [150]

SMAD-7 –

Cell growth, cell viability, apoptosis Cell growth, cell viability, apoptosis Cell migration, Invasion, Metastasis Cell proliferation, Invasion, Lymph node metastasis, invasion, poor prognosis EMT,metastasisWorse overall survival mir-187, mir-143, mir- 202 were associated with metastasis, TNM

OG –

[151] [163]

UP UP

– –

–

–

[155]

Down

–

–

–

Down

–

Histologicgrade,stage, metastasis, poor survival

–

discovery of many novel actionable mutations in GBC patients, which might help to shift the management towards personalized therapy. Further, exploration of complete genetic profile in different ethnic groups and at different clinical stages may provide a complete picture of the disease process and open new options for developing biomarkers to be useful for early diagnosis as well as targeted therapy in GBC. The immune checkpoint inhibitors have opened a new arena in the field of targeted therapy and we hope to see its effects on survival benefit in future.

Table 7 Therapeutic agents against novel targets and their phase of trial. Therapeutic Agents

Target

Phase of clinical trial

References

Erlotinib, Cetuximab, Oxaliplatin, Panitumumab Bevacizumab Sorafinib Everolimus Lepatinib Trastuzumab Afatinib Selumitinib

EGFR

II

[171–175]

VEGF

II

[176,177]

mTOR HER2

II II

[179] [178]

MEK1, MEK2

II

[180]

[153]

Financial disclosure None to declare. References

also shown aberrant expression profile in GBC, however no specific miRNA alteration has been related to any specific cancer and moreover there is a great overlap between different miRNAs and target cancers.

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