Development of a Custom NGS Panel for the Determination of Bladder Cancer Risk

doi:10.21203/rs.3.rs-840773/v1

Backgound

Bladder cancer (BCa) is a heterogeneous disease caused by the interaction between environmental and genetic risk factors. The objective of this study was to design a panel that evaluates the role of some selected variants in BCa susceptibility. We are also interested in studying the interaction between environmental and genetic risk factors.

Methods

The case/controls cohort was composed with 249 BCa cases and 255 controls. The designed Bladder cancer hereditary panel (BCHP) is composed of 139 selected variants. These variants were genotyped by an amplification-based targeted Next-Generation Sequencing (NGS) on the Ion Torrent Proton sequencer (Life Technologies, Ion Torrent technology).

Results

We have found that rs162555, rs2228000, rs10936599, rs710521, rs3752645, rs804276, rs4639, rs4881400 and rs288980 were significantly associated with decreased risk of bladder cancer. However the homozygous genotypes for VPS37C (rs7104333, A/A), MPG (rs1013358, C/C) genes or the heterozygous genotype for ARNT gene (rs1889740, rs2228099, rs2256355, rs2864873), GSTA4 (rs17614751) and APOBR/IL27 (rs17855750) were significantly associated with increased risk of bladder cancer development compared to reference group (OR=2.53, 2.34, 1.99, 2.00, 2.00, 1.47, 1.96 and 2.27 respectively). We have also found that non–smokers patients harboring heterozygous genotypes for ARNT/rs2864873 (A>G), ARNT/ rs1889740 (C>T) or GSTA4/rs17614751 (G to A) were respectively at 2.775, 3.069 and 6.608 –folds increased risk of Bca development compared to non-smokers controls with wild genotypes. Moreover the ARNT CT (rs1889740), ARNT CG (rs2228099), ARNT TC (rs2864873) and GSS GA genotypes were associated with an increased risk of BCa even in absence of professional risk factors. Finally the decision-tree analysis produced a three major BCa class. These three classes were essentially characterized by an intensity of tobacco use more than 20 pack years (PY) and the CYP1A2 (rs762551) genotype.

Conclusions

The determined association between genetic variations in BCa and environmental factors, as well as the effect of studied pathway SNPs in comparison with environmental exposition may provide urologists additional genetic information that may help for clinical assessment and treatment decisions. Nevertheless, the underlying mechanisms through which these genes or SNPs affect the clinical behavior of BCas require further studies.

Molecular Biology

Bladder cancer

NGS

Panel

SNP

tobacco

Tunisia

In this study we determined the effect of studied pathway SNPs in comparison with environmental exposition using Next-Generation Sequencing (NGS). We have found that homozygous minor genotype or heterozygous genotype for rs1889740 C/T, rs2228099 C/G, rs2256355 T/C, rs2864873 A/G in ARNT gene (Aryl hydrocarbon receptor nuclear translocator) were significantly associated to increased risk of bladder cancer even in the absence of tobacco risk factors, or professional risk factors. Finally we noticed the importance of tobacco status and the CYP1A2 (rs762551) genotype in the stratification of Tunisian BCa patients.

Bladder cancer (BCa) is a common malignancy of the urinary tract and the ninth most frequent cancer in the world, affecting nearly 3.4 million people with 430 000 new cases diagnosed in 2012 and 165 000 deaths per year (2% of all the cases)[1]. In the few last years, the incidence of BCa was higher in developed countries and some African countries, with an increase in the aggressiveness of the disease and the mortality rate [2]. According to the Cancer Registry of the north of Tunisia (1999–2003), BCa is the most frequent urological cancer in Tunisia in men and in 2018 it became the second malignant tumor with an age-standardized incidence rates of 17.7 and 2.0 per 100 000 in men in women respectively[3]. In 2018, the number of new BCa cases was 1323 [4]. The mean age at diagnosis is 65.9 years, without sex significant difference. At the time of diagnosis, non-muscle-invasive BCa (NMIBC) represents the majority of BCa whereas muscle-invasive BCa (MIBC) represents around 25% of bladder tumors with a 5-year survival rate ranging from 35–70%. NMIBC is usually associated with a favorable prognosis but it is characterized by a variable rate of recurrence and progression depending on tumor characteristics. MIBC is, however, initially aggressive and given the associated high risk of developing a metastatic disease requires a radical treatment when still localized[5].

BCa is a heterogeneous disease associated with many risk factors. The most known risk factor is tobacco smoking, which accounts for the occurrence of up 50% of BCa [6]. Occupational exposure to chemicals, genetic factors, and other environmental factors such as dietary factors, lifestyle, medical condition, fluid intake, also contribute to BCa carcinogenesis, although the evidence of the role of some of these risk factors is still inconclusive [6, 7]. Most carcinogens undergo activation by Phase I enzymes, mostly through oxidation reactions, and detoxification by Phase II enzymes, which is the case for aromatic and heterocyclic amines, well-known BCa carcinogens present in smoking and occupational exposure [8]. Therefore, early studies evaluated whether candidate genetic variants in such metabolic pathways could modify the risk of BCa induced by the above-mentioned carcinogens. For example, the deletion of xenobiotic metabolism gene "GSTM1 and/or GSTT1" characterized as GSTM1- and GSTT1-null genotypes have been shown to be BCa susceptibility loci in several studies [9, 10]. Moreover, N-acetyltransferase 2 (NAT2) and Glutathione-s-transferase M1 (GSTM1) variants were the first described genes showing a gene-smoking interaction associated with increased risk of BCa[11]. Hypothetically the deficiency in xenobiotic metabolizing pathway could result in the accumulation of somatic mutations which should be corrected by DNA-repair pathways. There are five major important DNA-repair pathways consisting of more than 130 genes: nucleotide excision repair (NER), base excision repair (BER), mismatch repair (MMR), double-strand break repair (DSBR) and transcription-coupled repair (TCR) [12–14]. Among these pathways, NER is the most important DNA repair mechanism responsible for various types of DNA damage consisting of oxidative DNA damage, bulky adducts cross-links, alkylating damage, and thymidine dimmers[15]. Deficient DNA repair capacity is known to be a cancer-predisposing factor. Indeed the presence of some single nucleotide polymorphisms (SNP) in DNA repair genes can impair the function of the repair enzymes, thus reducing DNA Repair Capacity (DRC) and inducing genetic instability [16]. In addition others studies have reported a significant association between variations in gene encoded for cell cycle and/or inflammatory response proteins and bladder development and/or prognosis[17].

All of this reported information highlights the complexity of the mechanisms implicated in the etiology of BCa which warrants further investigation. The goal of this case-control study was to evaluate the implication a selected SNP panel in BCa development of the Tunisian population. We developed an amplification-based targeted Next-Generation Sequencing (NGS) assay to simultaneously genotype 139 polymorphisms in 97 genes, selected according to their eventual implications in the etiology and the prognosis BCa such as those located in genes encoded for enzymes implicated in xenobiotic metabolism, DNA repair, treatment response, and inflammatory reaction process. The design of the panel was done, after consulting published data and available databases (dbSNP, UCSC Genome Browser, and GWAS).

Study population

A case-control study was conducted in the Urology department of Charles Nicolle Hospital in Tunis (Tunisia) and the Laboratory of Protein Engineering and Bioactive Molecules (LIP-MB 11ES24) of the National Institute of Applied Sciences and Technology of Tunis (INSAT), in collaboration with the Genetic Cancer Susceptibility group (GCS group) of the International Agency for Research on Cancer in Lyon (IARC/WHO). Recruitment was carried out after the agreement of the ethics committee of the Charles Nicolle Hospital and approved by an Ethics Committee (IEC Project No. 17–35) and an MTA (MATERIAL TRANSFER AGREEMENT MTA/ 2017 / IMP / GCS)/ 0356) from IARC.

This study was performed on a cohort of 504 cases (249 BCa patients and 255 controls). A total of 255 control cases, randomly selected from healthy volunteer cases enrolled in the Biochemistry Department, were matched to those of the BCa patients group according to the age range (64.28 ± 11.54), sex, and geographic origin. Epidemiological, clinical and anatomopathological data of BCa patients were collected from the medical records of the urology department and the histological reports from the pathology department of the Charles Nicolle Hospital in Tunis (Table 1). Epidemiological data (age, sex, smoking status) and pathological data (grade, stage, histological type, type, and follow-up of treatment) were recorded and made available for the study (Table 1). Histological reviews of the tumors were performed confirmed by a trained pathologist in urological oncology. The BCa tumors of the 249 patients were classified as 45 Specimens of High-Grade (HG) NMIBC, 119 specimens of Low-Grade (LG) NMIBC, and 66 specimens of MIBC.

Table 1: Clinical and Epidemiological characteristics of bladder cancer patients

Clinical and epidemiological parameters	Bladder cancer patients	Controls
Samples sizes Male Female	249 224 (89.96%) 25 (10.04%)	255 196 (76.86%) 59 (23.14%)
Mean Age at diagnosis (years)	68.18 ± 12.80	64.28 ± 11.54
Smoking status
Smokers	199 (79.91%)	138 (54.12%)
Non smokers	27 (10.84%)	117 (45.88%)
ND	23 (9.25%)	0 (00.00%)
Number of pack/years
< 20 PY	31 (15.58%)	70 (50.72%)
≥ 20 PY	168 (84.42%)	68 (49.28%)
Exposure to professional risk factors (farmer, painter, building, chemical factory…)
Not exposed	119 (47.80%)	225 (88.24%)
Exposed	83 (33.33%)	30 (11.76%)
ND	47 (18.87%)	0 (00.00%)
TNM classification
LG NMIBC	119 (47.80%)	-
HG NMIBC	45 (18.07%)	-
MIBC ND	66 (27.50%) 19 (07.63%)	-
ND: Not Determined; PY: Packet per Year; LG: Low Grade; HG: Haut Grade; MIBC: Muscle Invasive Bladder Cancer; NMIBC: Non-Muscle Invasive Bladder Cancer

Biological Samples And Dna Extraction

Peripheral blood samples were collected into tubes with ethylene diamine tetra-acetic acid EDTA (PH 8). Genomic DNA was extracted from leukocytes using a phenol /chloroform procedure. First, the integrity of the genomic DNA was visualized by electrophoresis on a 1% agarose gel stained with ethidium bromide. In a second step, DNA samples were quantified by Nanodrop and Qubit (High Sensitivity HS / Broad Rang BR) and were dried with the speedvac (Eppendorf™ Vacufuge™ Concentrator) to be normalized into 6*96-well plates.

Panel Design

We have selected a panel of 139 polymorphisms from 97 genes. These SNP were selected according to their eventual implications in poor-prognosis BCa such as those affecting the xenobiotic metabolism, DNA repair, treatment response, and inflammatory reaction. The design of the panel was done, after consulting published data and available databases (dbSNP, UCSC Genome Browser, and GWAS).

In a second step, the implication of the SNPs selected in our SNP panel in BCa susceptibility was confirmed by the following tools: Kyoto Encyclopedia of Genes and Genomes (KEGG) available on the website https://www.genome.jp/kegg/pathway.html [18, 19], Panther classification system available on the website (

http://pantherdb.org/tools/gxIdsList.do?list=upload_1&organism=Homo%20sapiens)[20], STRING database available on the website https://string-db.org/ ,AmiGO2[21], Reactome Pathway Database[22] and GWAS [23].In addition, we constructed candidate pathways based on our defined panel consisting of 97 genes. The pathways were defined according to the STRING protein–protein interaction networks. A complete list of the studied variants was summarized in Table 2. Pathways and protein-protein interaction, in which the studied genes were implicated, were presented and described in Fig. 2.

Table 2

A comprehensive list of all regions targeted by the Tunisian bladder cancer hereditary panel and Allelic Association (BCHP panel)
CHR	SNP	GENES	VARIATION	Reference variant	Mutated variant	Major allele /Minor allele	Major.allele.freq	Allelic Association
								p-value.log-additive	OR	95% CI
1	rs2020902	CASP9	splice_region_variant,intron_variant	A	G	A/G	82,5	0,873	0,97	0.7–1.35
1	rs2647396	BCL10	intron_variant	C	T	T/C	65,3	0,685	1,05	0.81–1.37
1	rs560018	GSTM4	intron_variant	T	C	T/C	82,8	0,938	0,99	0.72–1.36
1	rs11101992	GSTM5	intron_variant,non_coding_transcript_variant	A	C	A/C	65,9	0,596	1,07	0,83 − 1,39
1	rs4970774	GSTM5	intron_variant,non_coding_transcript_variant	A	C	C/A	50,1	0,754	1,04	0,81 − 1,33
1	rs4970776	GSTM5	intron_variant,non_coding_transcript_variant	T	A	T/A	53,3	0,87	1,02	0,8 − 1,3
1	rs1571858	GSTM3	intron_variant	C	T	C/T	75,9	0,888	1,02	0,76 − 1,37
1	rs15864	EPS8L3	3_prime_UTR_variant	G	C	G/C	81,6	0,947	0,99	0,71 − 1,37
1	rs3136701	CD2	downstream_gene_variant	G	C	C/G	52,8	0,79	0,97	0,76 − 1,23
1	rs1889740	ARNT	intron_variant	C	T	C/T	57,8	0,207	1,17	0,92 − 1,5
1	rs2228099	ARNT	synonymous_variant	C	G	C/G	57,4	0,203	1,18	0,92 − 1,51
1	rs1027699	ARNT	intron_variant	T	C	T/C	64,8	0,937	1,01	0,78 − 1,3
1	rs2256355	ARNT	intron_variant	T	C	T/C	56,7	0,181	1,18	0,92 − 1,52
1	rs2864873	ARNT	intron_variant	A	G	A/G	64,1	0,78	1,04	0,8 − 1,34
1	rs763110	FASLG	upstream_gene_variant	C	T	T/C	58,6	0,998	1	0,78 − 1,28
1	rs228001	ASTN1	intron_variant,non_coding_transcript_variant	C	A	C/A	96	0,937	1,03	0,54 − 1,96
1	rs1800890	IL10	upstream_gene_variant	A	T	A/T	74,9	0,886	0,98	0,74 − 1,3
1	rs2854461	EPHX1	intron_variant	C	A	C/A	73,8	0,223	1,19	0,9 − 1,57
1	rs1051740	EPHX1	missense_variant	T	C	T/C	72,5	0,66	1,06	0,81 − 1,4
1	rs2260863	EPHX1	intron_variant	G	C	C/G	64,9	0,89	1,02	0,8 − 1,3
1	rs1805410	PARP1	intron_variant	T	C	T/C	82,7	0,432	0,88	0,65 − 1,2
2	rs391835	AC012593.1/CCR2	intron_variant,non_coding_transcript_variant	G	A	A/G	53,5	0,93	0,99	0,77 − 1,26
2	rs1056836	CYP1B1/RMDN2	downstream_gene_variant	G	C	C/G	56,1	0,618	1,06	0,84 − 1,34
2	rs162555	CYP1B1	upstream_gene_variant	T	C	T/C	76,1	0,017	0,7	0,52 − 0,94
2	rs3771171	IL18R1	intron_variant	T	C	T/C	80	0,165	0,8	0,59 − 1,1
2	rs11892031	UGT1A10	intron_variant	A	C	A/C	90,6	0,213	0,77	0,51 − 1,17
3	rs2228000	XPC	missense_variant	G	A	G/A	81,5	0,024	0,69	0,5 − 0,96
3	rs1050450	RHOA	downstream_gene_variant	G	A	G/A	74,6	0,953	1,01	0,81 − 1,25
3	rs10936599	ACTRT3	upstream_gene_variant	C	T	C/T	85,2	0,004	0,6	0,42 − 0,85
3	rs710459	MASP1	downstream_gene_variant	G	A	G/A	71,6	0,968	0,99	0,76 − 1,29
3	rs710521	TP63	regulatory_region_variant	T	C	T/C	76,7	0,035	0,73	0,54 − 0,98
4	rs798766	TACC3	intron_variant	T	C	C/T	69,7	0,836	0,98	0,77 − 1,24
4	rs4073	IL8	upstream_gene_variant	A	T	A/T	55,3	0,83	0,97	0,77 − 1,23
4	rs2227306	IL8	intron_variant	C	T	C/T	68,5	0,428	0,9	0,7 − 1,16
4	rs3804099	TLR2	synonymous_variant	T	C	T/C	53	0,259	0,87	0,68 − 1,11
4	rs3087455	CASP3	intron_variant	T	G	T/G	65	0,4	0,9	0,69 − 1,16
5	rs34847072	AHRR	3_prime_UTR_variant	G	C	G/C	82,9	0,106	0,77	0,56 − 1,06
5	rs401681	TERT/CLPTM1L	intron_variant	C	T	T/C	53,8	0,415	0,9	0,69 − 1,16
5	rs2070874	IL4	5_prime_UTR_variant	C	T	C/T	80,9	0,455	1,13	0,82 − 1,55
6	rs4510656	CDKAL1	intron_variant	C	A	C/A	61,9	0,103	0,81	0,63 − 1,04
6	rs451774	GPX5	3_prime_UTR_variant	A	G	A/G	60,5	0,377	0,89	0,68 − 1,15
6	rs8193036	IL17A	upstream_gene_variant	C	T	T/C	74,3	0,9	0,98	0,76 − 1,27
6	rs2275913	IL17A	upstream_gene_variant	G	A	G/A	79,8	0,207	1,21	0,9 − 1,64
6	rs2180314	GSTA2	missense_variant	C	G	G/C	54,9	0,398	0,9	0,7 − 1,15
6	rs2144698	GSTA2	intron_variant	T	G	G/T	79,5	0,679	1,06	0,79 − 1,43
6	rs17614751	GSTA4	downstream_gene_variant	G	A	G/A	95,4	0,029	2,14	1,14 − 3,99
6	rs367836	GSTA4	downstream_gene_variant	G	T	T/G	59,7	0,764	1,04	0,81 − 1,32
6	rs150126	MAP3K7	intron_variant	C	T	T/C	74,9	0,999	1	0,76 − 1,31
6	rs4880	SOD2	missense_variant	A	G	A/G	53	0,406	1,11	0,87 − 1,4
7	rs1062492	SNX8	downstream_gene_variant	C	T	C/T	79,8	0,234	0,83	0,62 − 1,13
7	rs2017000	EGFR	intron_variant	A	G	A/G	74,5	0,139	0,82	0,63 − 1,07
7	rs1140475	EGFR	synonymous_variant	T	C	C/T	92,3	0,59	1,12	0,73 − 1,73
7	rs2293347	EGFR	synonymous_variant	C	T	C/T	96	0,698	1,13	0,61 − 2,09
7	rs1045642	ABCB1	synonymous_variant	A	G	G/A	69,1	0,12	1,24	0,95 − 1,62
7	rs1858923	ABCB1	intron_variant	A	G	A/G	61,8	0,611	1,07	0,82 − 1,39
7	rs2740574	CYP3A4	upstream_gene_variant	C	T	T/C	79,4	0,129	0,79	0,58 − 1,07
7	rs11773597	CYP3A4	upstream_gene_variant	G	C	G/C	92,3	0,247	1,28	0,81 − 2,04
7	rs3752645	PRKAR2B	intron_variant	G	A	G/A	90,9	0,023	0,6	0,39 − 0,94
8	rs804276	NEIL2	upstream_gene_variant	G	A	G/A	67,4	0,03	0,75	0,58 − 0,97
8	rs8191604	NEIL2	intron_variant	T	G	T/G	69,3	0,409	1,11	0,86 − 1,44
8	rs1874546	NEIL2	intron_variant	C	G	C/G	85,2	0,769	0,95	0,66 − 1,35
8	rs4639	NEIL2	3_prime_UTR_variant	A	G	A/G	65,4	0,009	0,72	0,56 − 0,92
8	rs1961456	NAT2	intron_variant	A	G	A/G	76,8	0,952	1,01	0,75 − 1,36
8	rs1799929	NAT2	synonymous_variant	C	T	C/T	54,3	0,374	1,12	0,88 − 1,42
8	rs1799930	NAT2	missense_variant	G	A	G/A	70,9	0,17	0,82	0,63 − 1,09
8	rs1799931	NAT2	missense_variant	G	A	G/A	97,3	0,814	1,09	0,54 − 2,19
8	rs12674710	NAT2	downstream_gene_variant	A	C	A/C	89,8	0,538	0,88	0,58 − 1,33
8	rs1495741	NAT2	regulatory_region_variant	G	A	A/G	79,6	0,509	1,11	0,82 − 1,51
8	rs13278062	TNFRSF10A	upstream_gene_variant	G	T	G/T	55,7	0,633	0,94	0,74 − 1,2
8	rs1126452	EPHX2	synonymous_variant	A	C	A/C	69,9	0,325	1,14	0,88 − 1,49
8	rs3136717	POLB	intron_variant	C	T	T/C	71,6	0,439	1,11	0,85 − 1,45
8	rs17226566	LY96	intron_variant	T	C	T/C	84,3	0,611	0,92	0,66 − 1,27
8	rs9642880	CASC11	intron_variant,non_coding_transcript_variant	G	T	T/G	50,3	0,405	1,11	0,87 − 1,43
8	rs2294008	PSCA	5_prime_UTR_variant	C	T	T/C	54,4	0,426	0,9	0,7 − 1,16
10	rs1937845	AKR1C3	5_prime_UTR_variant	A	G	G/A	52,8	0,886	0,98	0,77 − 1,25
10	rs3763676	AKR1C3	5_prime_UTR_variant	A	G	A/G	72	0,289	1,16	0,88 − 1,52
10	rs12529	AKR1C3	missense_variant	C	G	G/C	52,8	0,886	0,98	0,77 − 1,25
10	rs1937843	AKR1C3	intron_variant	A	G	A/G	72	0,289	1,16	0,88 − 1,52
10	rs4881400	AKR1C3	intron_variant	T	G	T/G	76,5	0,029	0,73	0,55 − 0,97
10	rs12775701	AKR1C3	intron_variant	A	G	G/A	59,3	0,665	1,06	0,83 − 1,35
10	rs2475377	CYP2C9	intergenic_variant	C	T	C/T	87,3	0,283	1,22	0,85 − 1,76
10	rs9332197	CYP2C9	intron_variant	T	C	T/C	98,2	0,132	2,1	0,78 − 5,69
10	rs12357751	BLNK	intron_variant	C	T	C/T	73,5	0,66	1,06	0,81 − 1,41
10	rs3789928	BLNK	intron_variant	G	C	G/C	52,8	0,057	0,79	0,61 − 1,01
10	rs2031920	CYP2E1	upstream_gene_variant	C	T	C/T	97,9	0,249	1,34	0,58 − 3,13
10	rs915908	CYP2E1	intron_variant	G	A	G/A	84,5	0,869	1,03	0,73 − 1,46
11	rs7104333	VPS37C	downstream_gene_variant	G	A	G/A	52,5	0	1,58	1,24 − 2,02
11	rs625978	GSTP1	regulatory_region_variant	C	T	C/T	61,5	0,73	0,96	0,74 − 1,23
11	rs1695	GSTP1	missense_variant	A	G	A/G	62,5	0,376	0,89	0,69 − 1,15
12	rs3213427	CD4	3_prime_UTR_variant	T	C	T/C	64,2	0,761	0,96	0,75 − 1,24
12	rs11046349	AICDA	3_prime_UTR_variant	T	G/A	T/G	73,6	0,283	1,16	0,88 − 1,54
12	rs10878176	TBK1	intron_variant	G	C	G/C	71,9	0,807	0,97	0,74 − 1,26
12	rs1866074	TDG	intron_variant	A	G	A/G	59,4	0,247	0,86	0,67 − 1,11
12	rs3890995	UNG	upstream_gene_variant	T	C	T/C	81,4	0,796	1,04	0,76 − 1,43
12	rs4765621	SCARB1	intron_variant	C	T	C/T	51,6	0,155	0,83	0,65 − 1,07
13	rs1050112	PARP4	missense_variant	G	T	G/T	50,6	0,164	0,85	0,68 − 1,07
13	rs13428	PARP4	missense_variant	C	G	C/G	58,8	0,131	0,85	0,69 − 1,05
13	rs17655	ERCC5	missense_variant	G	C	G/C	67,7	0,887	0,98	0,75 − 1,28
14	rs2228026	TEP1	synonymous_variant	A	G	A/G	94,4	0,475	0,83	0,49 − 1,4
14	rs1130409	OSGEP	upstream_gene_variant	T	G	T/G	53,8	0,978	1	0,79 − 1,26
14	rs696	NFKBIA	3_prime_UTR_variant	C	T	C/T	52,5	0,236	1,16	0,91 − 1,49
14	rs10133290	CHURC1	downstream_gene_variant	A	C	A/C	72,7	0,797	0,96	0,74 − 1,27
14	rs7101	FOS	5_prime_UTR_variant	C	T	T/C	81,8	0,698	0,94	0,69 − 1,29
14	rs861539	KLC1	intron_variant	G	A	G/A	60,8	0,985	1	0,78 − 1,27
15	rs1048943	CYP1A1	missense_variant	T	C	T/C	96,7	0,587	0,86	0,44 − 1,68
15	rs2472299	CYP1A1	intergenic_variant	A	G	G/A	58,6	0,601	0,93	0,72 − 1,21
15	rs762551	CYP1A2	intron_variant	C	A	A/C	57,6	0,901	0,98	0,76 − 1,27
15	rs976072	POLG	downstream_gene_variant	A	G	A/G	71,1	0,393	1,12	0,86 − 1,47
16	rs1013358	MPG	intron_variant	C	T	T/C	68,1	0,01	1,4	1,08 − 1,81
16	rs1799801	ERCC4	synonymous_variant	T	C	T/C	67,7	0,044	1,31	1,01–1,71
16	rs17855750	APOBR/IL27	downstream_gene_variant	A	C	A/C	96,1	0,021	2,37	1,18 − 4,74
16	rs153109	IL27	upstream_gene_variant	T	C	T/C	75,6	0,632	1,07	0,81 − 1,4
16	rs1800566	NQO1	missense_variant	G	A	G/A	73,8	0,507	1,1	0,83 − 1,46
16	rs689452	NQO1	intron_variant	C	G	G/C	86,1	0,61	1,1	0,77 − 1,56
16	rs899729	IL17C	upstream_gene_variant	C	A	C/A	67,3	0,598	1,07	0,83 − 1,39
17	rs4791489	MAP2K4	downstream_gene_variant	C	T	C/T	74,7	0,251	0,85	0,64 − 1,12
17	rs4796030	LIG3	3_prime_UTR_variant	A	C	C/A	52,6	0,525	0,92	0,73 − 1,18
17	rs2333227	MPO	upstream_gene_variant	C	T	C/T	68,7	0,275	0,86	0,66 − 1,12
17	rs7209435	MAP3K3	intron_variant	T	C	T/C	64,5	0,09	0,8	0,62 − 1,04
17	rs11655650	BIRC5	intron_variant	C	T	C/T	56,9	0,485	1,09	0,85 − 1,39
18	rs288980	ROCK1	intron_variant	T	C	C/T	71,4	0,03	0,75	0,57 − 0,97
18	rs10775480	SLC14A1	intron_variant	T	C	C/T	61	0,363	1,13	0,87 − 1,46
18	rs10853535	SLC14A1	intron_variant	C	T	T/C	61,3	0,479	1,1	0,85 − 1,43
18	rs723279	SOCS6	intron_variant	G	A	G/A	69,1	0,963	1,01	0,77 − 1,31
19	rs3746162	SBNO2	intron_variant	C	T	C/T	77,5	0,392	1,13	0,85 − 1,51
19	rs5498	ICAM5	upstream_gene_variant	A	G	A/G	62,8	0,664	0,94	0,73 − 1,23
19	rs25487	XRCC1	missense_variant	T	C	C/T	56,7	0,969	1	0,83 − 1,2
19	rs1799782	XRCC1	missense_variant	G	A	G/A	94,3	0,765	0,93	0,56 − 1,53
19	rs13181	ERCC2	downstream_gene_variant	T	G	T/G	65,9	0,092	0,8	0,62 − 1,04
20	rs7265992	GSS	intron_variant	G	A	G/A	90,4	0,148	0,74	0,49 − 1,12
20	rs6088662	GSS	upstream_gene_variant	T	G	T/G	69,9	0,091	0,8	0,61 − 1,04
20	rs7260770	GSS	intergenic_variant	G	A	G/A	88,6	0,046	1,48	1–2,19
21	rs2173962	AP000253.1	downstream_gene_variant	T	C	T/C	96,6	0,943	1,03	0,51 − 2,06
21	rs2839488	TFF1	intron_variant	G	C	G/C	50,4	0,904	1,02	0,8 − 1,29
22	rs4633	COMT	synonymous_variant,NMD_transcript_variant	C	T	C/T	57,9	0,152	0,84	0,65 − 1,07
22	rs4680	COMT	missense_variant,NMD_transcript_variant	G	A	G/A	58	0,081	0,8	0,63 − 1,03
22	rs1006771	DDTL	3_prime_UTR_variant	G	T	T/G	74,3	0,177	1,22	0,91 − 1,64
22	rs1014971	GSTT2	regulatory_region_variant	C	T	T/C	69,1	0,526	0,92	0,7 − 1,2
22	rs5751222	CYP2D6	downstream_gene_variant	T	A	T/A	87,7	0,823	0,96	0,68 − 1,36
Chr: Chromosome; SNP: Single Nucleotide Polymorphism ; P: P value for Fisher Test; OR: Odds ratio; 95% CI: Confidence Interval

Snp Genotyping

SNP genotyping was performed by NGS on the Ion Torrent Proton sequencer (Life Technologies, Ion Torrent technology). The GeneRead DNAseq Panel PCR Kit V2 (Qiagen) was used for the amplification of the targeted SNPs. The Gene Readprimers provided in different three pools. The samples were all re-quantified by Picogreen (using Fluoroscan) and normalized to 5ng/ul and 20 ng of each sample was plated into 3 daughter plates for the analysis of each group of primers. A validated in-house protocol was used to perform multiplex PCRs in 10 µL reaction volumes, containing 20 ng DNA, 60 nM of each primer pool and 0.73 µL of HotStarTaq enzyme. Amplification was carried out in a 96-well format plates using the standard conditions recommended by Qiagen: 15 min at 95°C and 22 cycles of 15 s at 95°C and 4 min at 60°C and 10 min at 72°C. Amplification products from the same sample were pooled purified using paramagnetic Serapure beads at 1.8X and quantified with the Qubit DNA high-sensitivity assay kit (Invitrogen Corporation). Barcoded libraries were prepared from 10ul of purified products and as previously described [24]. For template preparation, the barcoded libraries were pooled in equimolar concentrations and 7 µL of 100 pM was subsequently used for emulsion PCR (emPCR) using the Ion Torrent Template Ion PI Hi-Q OT2 200 kit on the Ion OneTouch2 Instrument (Thermo Fisher Scientific). The sequencing reaction was performed on an Ion Proton System using Life Technologies' Ion PI™ Chip Kit v3 and Ion PI™ Hi-Q™ Sequencing 200 Kit (Thermoscience Fisher Scientific) (Fig. 3).

Bioinformatics Analyses

Primary analyses were done using the Torrent_Suite 5.6.0 and included signal processing, base calling, reads alignment to the human genome reference 19 (Genome Reference Consortium GRCh37), quality control of mapping and coverage analysis, and variant calling. Subsequently, a list of detected sequence variants, including SNPs and small insertions/deletions, was imported into (Thermo Fisher Scientific) for annotation. The GeneRead data analysis workflow runs the GATK Variant Annotator program using the TVC output to populate the INFO field in the VCF file with the parameters necessary for downstream filtering. The INFO field of the GATK Unified Genotyper output already contains all the necessary parameters. Alignments were visually verified with the Integrative Genomics Viewer (IGV) v2.3. A combination of SnpEff v4.3, SnpSift v4.3 were used for annotation and filtration, and PLINK and in-house algorithms (R packages …) were used for analysis. QC filtered variants were then merged, annotated, and filtered using various databases including, ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/), HGMD (http://www.hgmd.cf.ac.uk/ac/index.php), and dbSNP (https://www.ncbi.nlm.nih.gov/snp/).

All assays were performed using DNA samples from a total of 544 cases and controls and duplicated samples for quality control. Only 40 samples (40/544; 7.35%) failed the library preparation and were excluded from the analysis. In this series, two runs led to 75% and 88% ISP loading and to the generation of total bases of 4.33 and 11.4 Gigabases for total bases of 33, 329, 31 and 84,548,378 respectively, 99% of which aligned to the reference genome (Hg19) (Fig. 4). This analysis provided high analytical sensitivity and allowed detecting SNPs. Using this approach, we have generated molecular profiles of a large number of individuals and identified specific BCa variations.

Among the 139 retained SNP (Table 2) nine minor alleles were significantly inversely associated with bladder cancer development [rs162555 (CYP1B1*C), rs2228000 (XPC*A), rs10936599 (ACTRT3*T), rs710521 (TP63*C), rs3752645 (PRKAR2B*A), rs804276 and rs4639 (NEIL2*A and NEIL2*G), rs4881400 (AKR1C3*G) and rs288980 (ROCK1*T)]. When we used the co-dominant model (the reference group is composed of subjects with homozygous genotype for major allele) we also found a statistically significant inverse association for heterozygous genotypes of ACTRT3 (rs10936599), TP63 (rs710521), CYP3A4 (rs2740574), BLNK (rs3789928) and COMT (rs4680) (OR1 = 0.51, 0.62, 0.61, 0.55, and 0.66 respectively) or homozygous genotypes of CYP1B1 (rs162555), XPC (rs2228000), NEIL2 (rs4639), NAT2 (rs1799930), AKR1C3 (rs4881400) and ROCK1 (rs288980) (OR2 = 0.36, 0.12, 0.49, 0.38, 0.4 and 0.42 respectively) (Table 3). However six minor alleles in six genes were significantly associated with increased risk of bladder cancer development: MPG (rs1013358 T > C), GSTA4 (rs17614751 G > A); GSS (rs7260770 G > A); VPS37C/CD5 (rs7104333 G > A); APOBR/IL27 (rs17855750 A > C); and ERCC4 (rs1799801 T > C). These aggravating effects were attributed to homozygous genotypes for VPS37C (rs7104333, A/A) or MPG (rs1013358, C/C) genes (OR2 = 2.53 and 2.34 respectively) or to the heterozygous genotype for ARNT gene (rs1889740, rs2228099, rs2256355, rs2864873), GSTA4 (rs17614751) and APOBR/IL27 (rs17855750) with OR1 respectively estimated at 1.99, 2.00, 2.00, 1.47, 1.96 and 2.27 compared to reference group. When comparing the distribution of these unfavorable genotypes according to exposition to environmental risk factors (Tables 4 and 5), we have found that non–smokers patients harboring heterozygous genotypes for ARNT/rs2864873 A > G, ARNT/ rs1889740 (C > T) or GSTA4/rs17614751 (G to A) were respectively at 2.775, 3.069 and 6.608 –folds increased risk of Bca development compared to non-smokers controls with wild genotypes. When we analyzed genotypic distribution in heavy smokers (BCa and Controls smoking more than 20PY) we found that smoker’s patients harboring ARNT CT (rs1889740), ARNT CG (rs2228099), ARNT TC (rs2864873) or ROCK1 TC genotypes were respectively associated with 2.690, 2.864, 2.779 and 3.00 fold-increased risk of BCa. In the other hand we have found that ARNT CT (rs1889740), ARNT CG (rs2228099), ARNT TC (rs2864873) and GSS GA genotypes were associated with an increased risk of BCa even in absence of professional risk factors (comparison of Non-exposed patients to Non-exposed controls). However when we compare genotypic distribution of unfavorable genotypes in exposed patients and controls according to professional risk factor, we observed that ARNT TT (rs1889740), ARNT GG (rs2228099), ARNT CC (rs2864873), ROCK1 CC/CT genotypes were respectively associated with 12.000, 12.666, 12.666, 3.976, 3.960 fold-increased risk of BCa development.

Table 3

Comparison of genotypic distribution between case and control groups
					Dominant model (DM)				Recessive model (RM)					Co-dominant model (CM)
Gene	SNP	Raisonnement/	Alleles	MjAF	p-value	OR	(95% CI)		p-value	OR	(95% CI)		p-value ¥	OR_CD1	*(95% CI)1**		OR _CD2	*(95% CI)2**
ARNT	rs1889740	T	C > T	C	0,00	1,7	1,17	2,48	0,26	0,77	0,49	1,21	0,00	1,99	1,34	2,96	1,15	0,69	1,91
ARNT	rs2228099	G	C > G	C	0,00	1,72	1,18	2,5	0,26	0,77	0,49	1,21	0,00	2	1,34	2,98	1,16	0,69	1,94
ARNT	rs2256355	C	T > C	T	0,00	1,73	1,19	2,53	0,31	0,8	0,51	1,24	0,00	2	1,34	2,99	1,2	0,72	2
ARNT	rs2864873	G	A > G	A	0,16	1,29	0,9	1,84	0,14	0,68	0,41	1,14	0,05	1,47	1,01	2,14	0,83	0,48	1,45
CYP1B1	rs162555	C	T > C	T	0,06	0,72	0,5	1,02	0,02	0,39	0,17	0,9	0,03	0,79	0,55	1,14	0,36	0,15	0,83
XPC	rs2228000	A	G > A	G	0,19	0,78	0,54	1,13	0,00	0,12	0,03	0,53	0,00	0,92	0,62	1,35	0,12	0,03	0,52
ACTRT3	rs10936599	T	C > T	C	0,00	0,52	0,35	0,79	0,62	0,76	0,26	2,23	0,01	0,51	0,34	0,78	0,65	0,22	1,9
TP63	rs710521	C	T > C	T	0,01	0,64	0,44	0,91	0,89	0,95	0,44	2,06	0,04	0,62	0,42	0,89	0,79	0,36	1,74
GSTA4	rs17614751	A	G > A	G	0,02	2,11	1,1	4,04	0,24	NA	0	NA	0,03	1,96	1,02	3,79	NA	0	NA
CYP3A4	rs2740574	C	C > T	T/C	0,03	0,67	0,46	0,96	0,35	1,51	0,63	3,59	0,02	0,61	0,42	0,89	1,27	0,53	3,06
NEIL2	rs804276	A	G > A	G	0,03	0,67	0,47	0,96	0,25	0,73	0,42	1,26	0,08	0,69	0,48	1	0,61	0,34	1,08
NEIL2	rs4639	G	A > G	A	0,03	0,68	0,48	0,97	0,03	0,56	0,33	0,94	0,03	0,76	0,52	1,11	0,49	0,28	0,85
NAT2	rs1799930	A	G > A	G	0,86	0,97	0,68	1,37	0,00	0,36	0,18	0,74	0,01	1,14	0,79	1,64	0,38	0,18	0,8
AKR1C3	rs4881400	G	T > G	T	0,11	0,75	0,52	1,07	0,02	0,42	0,2	0,91	0,05	0,84	0,58	1,22	0,4	0,18	0,86
BLNK	rs3789928	C	G > C	G	0,01	0,58	0,39	0,86	0,78	0,94	0,62	1,43	0,02	0,55	0,36	0,84	0,64	0,39	1,06
VPS37C	rs7104333	A	G > A	G	0,01	1,73	1,17	2,55	0,00	2,03	1,34	3,09	0,00	1,42	0,94	2,16	2,53	1,54	4,13
MPG	rs1013358	C	C > T	T/C	0,09	1,36	0,95	1,92	0,00	2,2	1,26	3,84	0,01	1,15	0,79	1,68	2,34	1,31	4,19
ERCC4	rs1799801	C	T > C	T	0,15	1,3	0,91	1,84	0,05	1,8	1	3,22	0,09	1,18	0,81	1,71	1,95	1,05	3,59
APOBR	rs17855750	C	A > C	A	0,01	2,36	1,16	4,79	0,49	NA	0	NA	0,02	2,27	1,11	4,63	NA	0	NA
ROCK1	rs288980	T	T > C	C /T	0,21	0,8	0,56	1,13	0,01	0,43	0,23	0,8	0,02	0,94	0,65	1,37	0,42	0,22	0,8
GSS	rs7260770	A	G > A	G	0,03	1,62	1,05	2,5	0,97	1,02	0,25	4,14	0,08	1,67	1,07	2,62	1,13	0,28	4,6
COMT	rs4633	T	C > T	C	0,03	0,67	0,46	0,96	0,99	1	0,64	1,57	0,07	0,63	0,42	0,93	0,77	0,47	1,27
COMT	rs4680	A	G > A	G	0,01	0,63	0,44	0,92	0,83	0,95	0,61	1,49	0,04	0,6	0,41	0,89	0,71	0,43	1,18
P: P value; OR: Odds ratio; 95% CI: Confidence Interval, OR_CD1: Heterozygous genotype VS Homozygous Wild genotype; OR_CD2: Mutant homozygous genotype VS Homozygous wild genotype; p-value ¥: P value for co-dominant model

Table 4

Comparison of genotypes distribution of significant unfavorable SNP from “Tunisian BCHP” panel in bladder cancer patients according to tobacco status
	Genotypes	Controls				Bladder cancer				Bladder cancer (NE) Vs Controls (NE)		Bladder cancer (E) Vs Controls (E)		Bladder cancer (E) Vs Controls (NE)		BC ≥ 20PY VS Controls ≥ 20PY		BC ≥ 20PY VS Controls NE
Gene/Variant	Genotypes	Controls				Bladder cancer
		NE	< 20PY	≥ 20PY	E	NE	< 20PY	≥ 20PY	E	p	OR (95% CI)	p	OR (95% CI)	P	OR (95% CI)	P	OR (95% CI)	P	OR (95% CI)
ARNT rs1889740 C > T
	CC	44	24	34	58	5	8	50	58	,	1*	,	1*	,	1*	,	1*	,	1*
	CT	43	35	23	58	15	19	91	110	0.044	3.069 (1.026–9.184)	0.009	1.896(1.169–3.075)	0.013	1.940(1.145–3.287)	0.002	2.690(1.430–5.060)	0.025	1.862(1.081–3.207)
	TT	30	11	11	22	7	4	27	31	0.254	2.053(0.595–7.080)	0.305	1.409(0.730–2.716)	0.453	0.783(0.414–1.481)	0.223	1.669(0.731–3.810)	0.488	0.792(0.409–1.531)
ARNT rs2228099 C > G
	CC	43	23	34	57	5	8	48	56	,	1*	,	1*	,	1*	,	1*	,	1*
	CG	44	36	23	59	15	19	93	112	0.054	2.931(0.979–8.771)	0.007	1.932(1.189–3.138)	0.013	1.954(1.151–3.316)	0.001	2.864( 1.520–5.396)	0.021	1.893(1.096–3.268)
	GG	30	11	11	22	7	4	27	31	0.270	2.006(0.581–6.925)	0.283	1.434(0.741–2.772)	0.478	0.793(0.418–1.505)	0.190	1.738(0.760–3.976)	0.524	0.806( 0.415–1.564)
ARNT rs2256355 T > C
	TT	30	22	33	55	5	8	46	54	,	1*	,	1*	,	1*	,	1*	,	1*
	TC	44	36	24	60	15	19	93	112	0.207	2.045(0.671–6.228)	0.010	1.901(1.165-3.100)	0.230	1.414(0.802–2.491)	0.001	2.779(1.475–5.237)	0.280	1.378( 0.769–2.470)
	CC	43	12	11	23	7	4	29	33	0.970	0.976(0.283–3.371)	0.253	1.461(0.761–2.803)	0.008	0.426(0.225–0.805)	0.130	1.891(0.828–4.318)	0.014	0.439(0.227–0.849)
ARNT rs2864873 A > G
	AA	51	26	37	63	7	10	71	81	,	1*	,	1*	,	1*	,	1*	,	1*
	AG	42	36	23	59	16	17	79	96	0.040	2.775(1.044–7.377)	0.317	1.265(0.797–2.008)	0.157	1.439(0.869–2.382)	0.061	1.790(0.971–3.298)	0.255	1.351(0.803–2.270)
	GG	24	8	8	16	4	4	18	22	0.773	1.214(0.324–4.549)	0.855	1.069(0.5189 to 2.204)	0.111	0.577(0.293–1.135)	0.735	1.172(0.466–2.950)	0.087	0.538(0.265–1.094)
CYP1B1 rs162555 (T to C)
	TT	63	38	36	74	18	16	106	122	,	1*	,	1*	,	1*	,	1*	,	1*
	TC	47	24	27	51	7	12	60	72	0.179	0.521 (50.201–1.349)	0.509	0.856 ( 0.540–1.357)	0.335	0.791 (0.491–1.274)	0.350	0.754 (0.417–1.362)	0.272	0.758 (0.4635 to 1.242)
	CC	7	8	5	13	2	3	2	5	1.000	1,000 (0.190–5.240)	0.007	0.233 (0.079–0.680)	0.099	0.368 ( 0.112–1.209)	0.020	0.135 (0.025–0.731)	0.030	0.169 (0.0342 to 0.842)
XPC rs2228000 (G to A)
	GG	72	43	42	85	22	20	114	134	,	1*	,	1*	,	1*	,	1*
	GA	37	19	20	39	5	11	52	63	0.127	0.442 (0.154–1.262)	0.921	1.024 ( 0.632–1.661)	0.725	0.914 (0.5567 to 1.503)	0.892	0.957 ( 0.5125 to 1.790)	0.649	0.887 (0.5306 to 1.484)
	AA	2	8	6	14	0	0	2	2	0.779	0.644 (0.029–13.924)	0.001	0.090 (0.020–0.408)	0.538	0.537 ( 0.074–3.894)	0.012	0.122 (0.023–0.632)	0.649	0.631 (0.0870 to 4.583)
TP63, P3H2 rs710521 T/C
	TT	55	46	35	81	16	23	107	130	,	1*	,	1*	,	1*	,	1*
	TC	56	21	28	49	9	7	53	60	0.195	0.552 (0.225–1.355)	0.257	0.763 (0.477–1.218)	0.001	0.453 (0.280–0.733)	0.115	0.619 (0.341–1.123)	0.004	0.486 (0.2960 to 0.799)
	CC	6	3	5	8	2	1	8	9	0.874	1.145 (0.210–6.237)	0.482	0.701 (0.259–1.890)	0.409	0.634 (0.215–1.868)	0.282	0.523 (0.160–1.704)	0.503	0.685 (0.2265 to 2.074)
ACTRT3/MYNN rs10936599 (C to T)
	CC	76	51	44	95	18	24	135	159	,	1*	,	1*	,	1*	,	1*
	CT	39	18	19	37	9	5	29	34	0.9543	0.974 (0.400-2.369)	0.026	0.549 ( 0.323–0.933)	0.001	0.416 ( 0.244–0.711)	0.041	0.497 (0.254–0.973)	0.002	0.418 (0.2399 to 0.730)
	TT	2	1	5	6	0	2	4	6	0.903	0.827 (0.038–17.969)	0.384	0.597 (0.187–1.905)	0.663	1.434 (0.282–7.271)	0.052	0.260 (0.067–1.014)	0.892	1.125 (0.2015 to 6.291)
GSTA4 rs17614751(G to A)
	GG	114	63	63	126	23	31	168	199	,	1*	,	1*	,	1*	,	1*
	GA	3	7	5	12	4	1	17	18	0.017	6.608 (1.385–31.530)	0.894	0.949 (0.442–2.038)	0.051	3.437 ( 0.990-11.922)	0.646	1.275 (0.451–3.601)	0.034	3.845 (1.1014 to 13.424)
	AA	0	0	0	0	0	0	2	2	0.431	4.872 (0.094-251.797)	0.457	3.170 ( 0.151–66.582)	0.497	2.869 (0.136–60.298)	0.683	1.884 ( 0.089–9.791)	0.431	3.397 (0.1616 to 71.433)
CYP3A4 rs2740574 C > T
	CC	5	3	1	4	3	3	5	8	,	1*	,	1*	,	1*	,	1*	,	1*
	CT	46	23	28	51	2	8	50	58	0.010	0.072(0.009–0.542)	0.379	0.568(0.161-2.000)	0.693	0.788(0.241-.571)	0.358	0.357(0.039–3.211)	0.900	1.087(0.295–3.999)
	TT	66	44	39	83	22	20	113	133	0.445	0.555(0.122–2.516)	0.724	0.801(0.233–2.744)	0.695	1.259(0.396-4.000)	0.623	0.579(0.065–5.114)	0.408	1.712(0.477–6.134)
PRKAR2B rs3752645 (G to A)
	GG	88	57	58	115	22	25	149	174	,	1*	,	1*	,	1*	,	1*
	GA	26	10	10	20	5	6	19	25	0.629	0.769 ( 0.265–2.231)	0.554	0.826 ( 0.438–1.556)	0.019	0.486 ( 0.265–0.891)	0.472	0.739 (0.324–1.685)	0.011	0.431 (0.2259 to 0.824)
	AA	2	3	0	3	0	0	0	0	0.878	0.786 (0.036–16.971)	0.119	0.094 (0.004–1.847)	0.141	0.101 ( 0.004–2.135)	0.640	0.391 (0.007–19.952)	0.170	0.118 (0.0056 to 2.494)
NEIL2 rs804276 G/A
	GG	39	37	30	67	18	17	82	99	,	1*	,	1*	,	1*	,	1*	,	1*
	GA	59	25	31	56	7	12	67	79	0.005	0.257 (0.098–0.672)	0.844	0.954 ( 0.601–1.515)	0.012	0.527 ( 0.319–0.870)	0.440	0.790 (0.435–1.436)	0.019	0.540( 0.321–0.906)
	AA	19	8	7	15	2	2	19	21	0.063	0.228 ( 0.047–1.085)	0.885	0.947 (0.455–1.969)	0.024	0.435 ( 0.211–0.897)	0.988	0.993 (0.379–2.599)	0.049	0.475( 0.226–0.998)
NEIL2 rs4639 A/G
	AA	37	36	29	65	16	15	82	97	,	1*	,	1*	,	1*	,	1*	,	1*
	AG	58	23	28	51	8	13	68	81	0.017	0.319 (0.124–0.819)	0.795	1.064 (0.664–1.703)	0.014	0.532 ( 0.320–0.884)	0.625	0.858 (0.4663 to 1.581)	0.017	0.529(0.313–0.892)
	GG	22	11	11	22	3	3	18	21	0.091	0.315 (0.082–1.205)	0.194	0.639 ( 0.325–1.256)	0.005	0.364 (0.179–0.739)	0.213	0.578 (0.244–1.369)	0.007	0.369(0.177–0.769)
NAT2 rs1799930 G > A
	GG	56	38	32	70	11	19	83	102	,	1*	,	1*	,	1*	,	1*	,	1*
	GA	46	26	28	54	14	10	78	88	0.329	1.549(0.642–3.738)	0.630	1.118(0.709–1.763)	0.842	1.050(0.647–1.702)	0.813	1.074( 0.593–1.945)	0.596	1.144(0.695–1.881)
	AA	15	6	8	14	2	2	7	9	0.637	0.678(0.135–3.398)	0.071	0.441(0.181–1.075)	0.014	0.329(0.135-0.800)	0.051	0.337(0.113–1.006)	0.018	0.314(0.120–0.821)
AKR1C3 rs4881400 T > G
	TT	63	37	43	80	18	22	101	123	,	1*	,	1*	,	1*	,	1*	,	1*
	TG	41	28	20	48	7	9	61	70	0.291	0.597(0.229–1.556)	0.822	0.948(0.597–1.506)	0.592	0.874(0.535–1.428)	0.407	1.298(0.699–2.410)	0.772	0.928(0.559–1.538)
	GG	13	5	5	10	2	0	6	6	0.442	0.538(0.111–2.609)	0.079	0.390(0.136–1.115)	0.005	0.236(0.085–0.651)	0.288	0.510(0.147–1.764)	0.016	0.287(0.104–0.796)
BLNK rs3789928 G/C
	GG	24	18	16	34	8	11	55	66	,	1*	,	1*	,	1*	,	1*	,	1*
	GC	59	37	42	79	17	13	70	83	0.767	0.864 (0.329–2.269)	0.019	0.541 (0.323–0.906)	0.022	0.511(0.288–0.908)	0.035	0.484 (0.246–0.952)	0.029	0.517(0.286–0.935)
	CC	36	15	10	25	2	7	43	50	0.031	0.166 (0.032–0.853)	0.926	1.030 ( 0.546–1.941)	0.034	0.505 ( 0.267–0.952)	0.620	1.250 ( 0.516–3.031)	0.050	0.521(0.271–1.001)
VPS37C/CD5 rs7104333 G > A
	GG	18	14	14	28	10	11	53	64	,	1*	,	1*	,	1*	,	1*	,	1*
	GA	53	32	35	67	11	14	76	90	0.055	0.373(0.136–1.025)	0.056	0.587(0.340–1.013)	0.020	0.477(0.256–0.890)	0.126	0.573(0.281–1.169)	0.027	0.487(0.256–0.923)
	AA	46	24	19	43	6	6	49	45	0.013	0.234(0.074–0.741)	0.012	0.457(0.248–0.842)	0.000	0.275(0.141–0.535)	0.342	0.681(0.308–1.504)	0.002	0.361(0.185–0.706)
MPG rs1013358 C/T
	CC	10	5	6	11	5	4	25	29	,	1*	,	1*	,	1*	,	1*	,	1*
	CT	39	34	29	62	8	13	68	81	0.184	0.410(0.110–1.529)	0.073	0.495(0.229–1.069)	0.421	0.716(0.317–1.616)	0.255	0.562(0.208–1.5167)	0.396	0.697(0.303–1.603)
	TT	68	31	34	65	14	14	75	89	0.153	0.411(0.121–1.391)	0.092	0.519(0.241–1.115)	0.047	0.451(0.205–0.989)	0.202	0.529(0.198–1.409)	0.045	0.441(0.197–0.985)
ERCC4 rs1799801 T/C
	TT	58	33	34	67	10	15	70	85	,	1*	,	1*	,	1*	,	1*
	TC	52	29	29	58	13	16	71	87	0.421	1.450 (0.586–3.585)	0.4768	1.182 (0.745–1.875)	0.587	1.141 ( 0.707–1.843)	0.568	1.189 (0.655–2.156)	0.628	1.131 (0.6868 to 1.863)
	CC	7	8	5	13	4	0	27	27	0.093	3.314 (0.817–13.438)	0.188	1.637 ( 0.784–3.414)	0.034	2.631 (1.074–6.446)	0.068	2.622 (0.928–7.409)	0.011	3.195 (1.2978 to 7.870)
APOBR rs17855750 A/C
	AA	111	67	65	132	26	27	151	178	,	1*	,	1*	,	1*	,	1*
	AC	6	3	3	6	1	4	16	20	0.757	0.711(0.082–6.167)	0.059	2.471 ( 0.965–6.326)	0.128	2.078 ( 0.809–5.335)	0.198	2.295 (0.646–8.150)	0.173	1.960 (0.7433 to 5.169)
	CC	0	0	0	0	0	0	1	1	0.475	4.207 ( 0.081-216.956)	0.624	2.226 ( 0.090–55.100)	0.701	1.873 (0.075–46.406)	0.874	1.297 (0.052–32.260)	0.628	2.207 (0.0891 to 54.710)
ROCK1 rs288980 T/C
	TT	13	8	14	22	0	1	14	15	,	1*	,	1*	,	1*	,	1*	,	1*
	TC	42	28	22	50	12	10	66	76	0.160	7.941(0.440-143.219)	0.035	2.229(1.056–4.705)	0.289	1.568(0.681–3.606)	0.014	3.00(1.239–7.26)	0.382	1.459(0.624–3.408)
	CC	62	34	32	66	15	20	88	108	0.195	6.696(0.377-118.925)	0.017	2.400(1.163–4.951)	0.316	1.509(0.674–3.379)	0.018	2.750(1.182–6.396)	0.510	1.318( 0.579-.998)
GSS rs7260770 G/A
	GG	94	61	56	117	17	24	129	153	,	1*	,	1*	,	1*	,	1*	,	1*
	GA	20	9	11	20	9	7	36	43	0.057	2.488 (0.970–6.377)	0.094	1.644 (0.918–2.943)	0.354	1.320 (0.732–2.381)	0.355	1.420 (0.674–2.991)	0.381	1.311 (0.7142 to 2.408)
	AA	3	0	1	1	1	0	3	3	0.605	1.843 (0.180-18.781)	0.474	2.294 ( 0.235–22.338)	0.555	0.614 ( 0.121–3.107)	0.820	1.302 (0.132–12.794)	0.702	0.728 (0.1439 to 3.690)
COMT rs4633 C > T
	CC	38	19	19	38	8	9	75	84	,	1*	,	1*	,	1*	,	1*	,	1*
	CT	60	35	35	70	14	15	62	77	0.833	1.108(0.424–2.891)	0.006	0.497(0.301–0.821)	0.036	0.580(0.348-.967)	0.016	0.448(0.233–0.861)	0.016	0.523(0.308–0.887)
	TT	18	16	14	30	5	7	31	38	0.663	1.319(0.377–4.606)	0.075	0.573(0.310–1.057)	0.894	0.955(0.484–1.883)	0.160	0.561(0.250–1.257)	0.702	0.872(0.433–1.756)
COMT rs4680 G > A
	GG	38	20	18	38	9	10	75	85	,	1*	,	1*	,	1*	,	1*	,	1*
	GA	62	33	35	68	14	13	63	76	0.919	0.953(0.376–2.415)	0.006	0.499(0.302–0.826)	0.020	0.548(0.329–0.911)	0.012	0.432(0.223–0.835)	0.013	0.514(0.304–0.870)
	AA	17	17	15	32	4	8	30	38	0.992	0.993(0.268–3.679)	0.040	0.530(0.289–0.973)	0.998	0.999(0.502–1.988)	0.074	0.480(0.214–1.074)	0.757	0.894(0.438–1.821)
P: P value; OR: Odds ratio; 95% CI: Confidence Interval; NE: Non Smoker; E: Smoker

Table 5

Comparison of genotypes distribution of significant unfavorable SNP from “Tunisian BCHP” panel in bladder cancer patients according to professional risk factors
		Controls		Bladder cancer		Bladder cancer (NE) Vs Controls (NE)		Bladder cancer (E) Vs Controls (E)		Bladder cancer (E) Vs Controls (NE)
Gene/Variant	Genotypes	Non Exposed (NE)	Exposed	Non Exposed (NE)	Exposed	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)
		Non Exposed (NE)	(E)	Non Exposed (NE)	(E)	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)
ARNT rs1889740 C > T
	CC	90	12	36	19	-	1*	-	1*	-	1*
	CT	84	17	65	45	0.010	1.934(1.168–3.203)	0.269	1.671(0.670–4.166)	0.002	2.537(1.374–4.685)
	TT	51	1	18	19	0.710	0.882(0.455–1.710)	0.022	12.000(1.416-101.672)	0.123	1.764( 0.856–3.635)
ARNT rs2228099 C > G
	CC	88	12	35	18	-	1*	-	1*	-	1*
	CG	86	17	66	46	0.010	1.929(1.163–3.201)	0.207	1.803(0.720–4.518)	0.002	2.615(1.405–4.864)
	GG	51	1	18	19	0.724	0.887(0.456–1.725)	0.020	12.666(1.491-107.602)	0.108	1.821(0.876–3.783)
ARNT rs2256355 T > C
	TT	86	12	34	18	-	1*	-	1*	-	1*
	TC	87	17	65	46	0.014	1.889(1.133–3.149)	0.207	1.803(0.720–4.518)	0.003	2.526(1.357–4.701)
	CC	52	1	20	19	0.933	0.972(0.507–1.865)	0.020	12.666(1.491-107.602)	0.135	1.745(0.840–3.625)
ARNT rs2864873 A > G
	AA	101	13	43	33	-	1*	-	1*	-	1*
	AG	85	16	62	39	0.029	1.713(1.055–2.780)	0.926	0.960(0.403–2.283)	0.222	1.404(0.813–2.424)
	GG	39	1	14	11	0.636	0.843(0.415–1.710)	0.180	4.333(0.507–37.030)	0.710	0.863(0.397–1.875)
CYP1B1 rs162555 (T to C)
	TT	120	17	72	58	-	1*	-	1*	-	1*
	TC	89	9	42	25	0.315	0.786 (0.4920-.257)	0.666	0.814 (0.3199–2.072)	0.050	0.581 (0.337-1.000)
	CC	16	4	5	0	0.221	0.183–1.482	0.024	0.033 (0.0017–0.648)	0.054	0.062 (0.003–1.058)
XPC rs2228000 (G to A)
	GG	146	17	79	58	-	1*	-	1*	-	1*
	GA	68	8	39	25	0.811	1.059 (0.6562–1.712)	0.858	0.915 (0.349–2.397)	0.782	0.925 (0.533–1.604)
	AA	11	5	1	0	0.090	0.168 (0.021–1.325	0.016	0.027 (0.001–0.516)	0.126	0.108 (0.0063–1.877)
TP63, P3H2 rs710521 T/C
	TT	124	12	78	53	,	1*	,	1*	-	1*
	TC	89	16	36	26	0.071	0.643 (0.3980–1.038)	0.026	0.367 (0.152–0.890)	0.169	0.683 (0.397–1.175)
	CC	12	2	5	4	0.455	0.662 (0.2247–1.952)	0.390	0.452 (0.074–2.765)	0.678	0.779 ( 0.2405–2.529)
ACTRT3/MYNN rs10936599 (C to T)
	CC	150	21	95	65	,	1*	,	1*	-	1*
	CT	70	6	21	16	0.007	0.473 (0.2730–0.822)	0.782	0.861 (0.298–2.485)	0.041	0.527 ( 0.284–0.976)
	TT	5	3	3	2	0.941	0.947 ( 0.2213–4.056)	0.104	0.215 (0.033–1.377)	0.925	0.923 (0.174–4.881)
GSTA4 rs17614751(G to A)
	GG	213	27	107	77	,	1*	,	1*	-	1*
	GA	12	3	11	6	0.165	1.824 (0.779–4.271)	0.632	0.701 (0.163-3.000)	0.530	1.383 (0.501–3.813)
	AA	0	0	1	0	0.275	5.958 (0.240-147.496)	0.606	0.354 (0.006–18.319)	0.613	2.754 (0.054-140.045)
CYP3A4 rs2740574 C > T
	CC	8	1	5	3	-	1*	-	1*	-	1*
	CT	85	12	29	21	0.320	0.545(0.165–1.802)	0.656	0.583(0.054–6.251)	0.561	0.658(0.160–2.699)
	TT	132	17	85	59	0.959	1.030(0.326–3.254)	0.902	1.156(0.112–11.850)	0.800	1.191(0.305–4.653)
PRKAR2B rs3752645 (G to A)
	GG	178	25	101	75	,	1*	,	1*	-	1*
	GA	43	4	18	8	0.322	0.737 (0.4041–1.346)	0.535	0.666 (0.184–2.404)	0.045	0.441 (0.198–0.984)
	AA	4	1	0	0	0.275	0.195 (0.010–3.666)	0.185	0.112 (0.004–2.851)	0.371	0.262 (0.014–4.940)
NEIL2 rs804276 G/A
	GG	93	13	64	39	,	1*	,	1*	-	1*
	GA	100	15	45	37	0.079	0.653 (0.406–1.050)	0.658	0.822 (0.345–1.959)	0.644	0.882 (0.518-1.500)
	AA	32	2	10	7	0.046	0.454 (0.208–0.988)	0.858	1.166 (0.214–6.336)	0.156	0.521 (0.212–1.282)
NEIL2 rs4639 A/G
	AA	90	12	60	42	,	1*	,	1*	-	1*
	AG	94	15	48	34	0.273	0.766 ( 0.475–1.234)	0.335	0.647 (0.267–1.566)	0.352	0.775 (0.453–1.325)
	GG	41	3	11	7	0.016	0.402 (0.191–0.844)	0.595	0.666 (0.149–2.978)	0.025	0.365 ( 0.151–0.883)
NAT2 rs1799930 G > A
	GG	111	15	56	42	-	1*	-	1*	-	1*
	GA	89	11	57	39	0.311	1.269(0.799–2.015)	0.603	1.2662( 0.519–3.089)	0.578	1.158(0.690–1.943)
	AA	25	4	6	2	0.124	0.475(0.184–1.226)	0.060	0.178(0.029–1.076)	0.040	0.211(0.048–0.932)
AKR1C3 rs4881400 T > G
	TT	121	22	68	58	-	1*	-	1*	-	1*
	TG	85	4	45	23	0.802	0.942(0.590–1.503)	0.191	2.181( 0.677–7.025)	0.044	0.564(0.323–0.985)
	GG	19	4	6	2	0.241	0.561(0.214–1.474)	0.065	0.189(0.032–1.110)	0.046	0.219(0.049–0.974)
BLNK rs3789928 G/C
	GG	50	8	39	30	,	1*	,	1*	-	1*
	GC	119	19	56	32	0.059	0.603 (0.356–1.020)	0.103	0.449 (0.171–1.178)	0.008	0.448 (0.246–0.814)
	CC	56	3	24	21	0.064	0.549 (0.291–1.037)	0.395	1.866 (0.442–7.873)	0.172	0.625 (0.318–1.228)
VPS37C/CD5 rs7104333 G > A
	GG	40	6	41	21	-	1*	-	1*	-	1*
	GA	105	15	48	45	0.004	0.446(0.256–0.775)	0.779	0.857(0.291–2.522)	0.529	0.816(0.433–1.537)
	AA	80	9	30	17	0.001	0.365(0.199–0.669)	0.319	0.539(0.160–1.818)	0.017	0.404(0.192–0.851)
MPG rs1013358 C/T
	CC	17	4	19	14	,	1*	,	1*	-	1*
	CT	84	17	41	36	0.031	0.436(0.205–0.927)	0.431	0.605(0.173–2.116)	0.113	0.520(0.232–1.167)
	TT	124	9	59	33	0.020	0.425(0.206–0.878)	0.945	1.047(0.276–3.974)	0.005	0.323(0.144–0.722)
ERCC4 rs1799801 T/C
	TT	109	16	51	34	,	1*	,	1*	-	1*
	TC	97	13	55	35	0.422	1.211 (0.7581 to 1.937)	0.594	1.267 (0.5304 to 3.026)	0.600	1.156 (0.670–1.996)
	CC	19	1	13	14	0.339	1.462 (0.670–3.189)	0.080	6.588 (0.795–54.560)	0.033	2.362 (1.071–5.207)
APOBR rs17855750 A/C
	AA	214	29	105	76	,	1*	,	1*	-	1*
	AC	11	1	14	6	0.023	2.593 (1.138–5.910)	0.452	2.289(0.264–19.849)	0.413	1.535(0.549–4.296)
	CC	0	0	0	1	0.723	2.033 (0.040-103.184)	0.929	1.156(0.045–29.208)	0.193	8.411(0.339-208.705)
ROCK1 rs288980 T/C
	TT	28	7	9	4	,	1*	,	1*	-	1*
	TC	88	4	43	36	0.325	1.520(0.659–3.503)	0.020	3.976 (1.239–12.756)	0.064	2.863(0.937–8.751)
	CC	109	19	67	43	0.116	1.912(0.850–4.300)	0.044	3.960 (1.035–15.154)	0.071	2.761(0.914–8.341)
GSS rs7260770 G/A
	GG	186	25	89	60	,	1*	,	1*	,	1*
	GA	35	5	28	23	0.070	1.671 (0.957–2.919)	0.235	1.916 (0.654–5.609)	0.020	2.037 (1.116–3.716)
	AA	4	0	2	0	0.960	1.044 (0.187–5.812)	0.667	0.421 (0.008–21.829)	0.474	0.342 (0.018–6.454)
COMT rs4633 C > T
	CC	71	6	43	35	-	1*	-	1*	-	1*
	CT	109	21	52	31	0.352	0.787(0.476–1.302)	0.008	0.253( 0.090–0.707)	0.057	0.576(0.326–1.018)
	TT	45	3	24	17	0.689	0.880(0.472–1.642)	0.969	0.971(0.216–4.363)	0.449	0.766(0.384–1.526)
COMT rs4680 G > A
	GG	69	7	45	35	-	1*	-	1*	-	1*
	GA	111	19	50	31	0.1489	0.690(0.417–1.141)	0.027	0.326( 0.121–0.880)	0.039	0.550(0.311–0.972)
	AA	45	4	24	17	0.525	0.817(0.439–1.522)	0.814	0.850(0.218–3.306)	0.402	0.744(0.373–1.485)
P: P value for Fisher Test; OR: Odds ratio; 95% CI: Confidence Interval; NE: Non Exposed; E: Exposed

Finally the decision-tree analysis produced a three major BCa class. All of these classes were characterized by an intensity of tobacco use ≥ 20 pack years (PY) and subdivided according to the genotype of the CYP1A2 C > A variation (rs762551). The first class (58/249) is defined by the presence of CYP1A2 CC or CYP1A2 CA genotype and also defined by others 8 variations: ARNT C > G (rs2228099), CYP1B1 T > C (rs162555), SOD1 T > C (rs2173962), ROCK1 T > C (rs288980), IL10 A > T (rs1800890), LY96 T > C (rs17226566), AICDA T > G (rs11046349) and MAP2K4 C > T (rs4791489). The second class of BCa group (31/249) is only defined by the intensity of tobacco use ≥ 20PY and the inheritance of the homozygous genotype for rs762551 in CYP1A2 (CYPA2 A/A), XPC GG or AG genotype (rs2228000, G > A), and MAP2K4 CC or CT genotype (rs4791489, C > T). The third class (25/249) of BCa patients was defined by rs762551 (CYP1A2 C/A or C/C genotype) and 6 other variables (ARNT rs2228099 C > G, MPO rs2333227 C > T, LY96 rs17226566 T > C, CCR2 rs391835 G > A; APOBEC3 rs1014971 C > T and CASP3 rs3087455 T > G) (Fig. 5).

As all complex diseases, BCa isn't one SNP/gene disorder. Rather, many SNPs with small effects may result in the impairment of key pathways involved in their pathophysiology. The identification of such SNP-signatures represents an analytical challenge requiring the appliance of novel comprehensive statistical approaches. To our knowledge, this is the first study on BCa in Tunisian population analyzing a large number of SNPs with NGS technique. Indeed, in this study, we report the development and validation of the targeted amplification-based NGS panel analyzed on the Ion Torrent Proton Platform. This panel is named BCHP (BCa Heredity Panel) and used for detecting clinically useful genetic variations associated with the development of BCa in a total of 249 patients and 255 controls. After filtration the BCHP was composed of 139 SNPs in 97 genes. These SNPs are located in many different regions: introns sites (BCL10, GSTM4, GSTM3...), regulatory region (TP63, NAT2, GSTP1, GSTP2), up and downstream regulation genes sequences (GSTA4, NAT2 APOBR/IL27, CYP2D6…), splicing sites (CASP9)…. The encoded enzymes modulate biological processes (xenobiotic metabolic process, cellular response to xenobiotic stimulus, Base-excision repair, immunology response...) and/or affect molecular function (Damaged DNA binding, Enzyme model we found statistically significant association between some genotypes and risk of bladder cancer development. These associations were reported for gene encoding for enzymes implicated in xenobioitic and drug metabolisms [CYP1B1 (rs162555), NAT2 (rs1799930), CYP3A4 (rs2740574), COMT (rs4680), AKR1C3 (rs4881400), PRKAR2B (rs3752645), ARNT (rs1889740, rs2228099, rs2864873), GSS (rs7260770), GSTA4 (rs17614751)], or in DNA repair pathway [NEIL2 (rs4639), XPC (rs2228000), MPG (rs1013358), ERCC4/XPF (rs1799801)] or in other molecular functions such as cell proliferation, immunology response.

Xenobiotic metabolism pathway

In this study, we have found that CYP1B1 C/C (rs162555), NAT2 A/A (rs1799930), AKR1C3 G/G (rs4881400) genotypes and heterozygous genotypes for CYP3A4 (rs2740574), COMT (rs4680) and PRKAR2B (rs3752645) were associated with a decreased risk of BCa development compared to reference group. CYP1B1 encodes for the CYP1B1 enzyme which is implicated in the NADPH-dependent electron transport and xenobiotic oxidation [25]. Nevertheless, no previous study has presented conclusive results for an association between CYP1B1 rs162555 and BCa development. The CYP3A4 (Cytochrome P450 3A4) enzyme encoded by the CYP3A4 gene is expressed in adult human liver and it is responsible for the oxidative metabolism of many clinically used drugs. The CYP3A4*1B variant (rs2740574 C to T) is associated with the reduction of the expression of the activity of CYP3A4 enzyme which could explain its effect on the development of BCa [26]. These results were supported by others studies which reported a significant protective effect of homozygous wild genotype in other cancer types such as prostate cancer, breast cancer, leukemia, gastric cancer, colorectal cancer, and ovarian cancer [27].

The N-acetyltransferase 2 (NAT2) gene encodes for an important phase II xenobiotic-metabolizing enzyme frequently present in liver and intestinal mucosa. It catalyzes the reaction of aromatic and heterocyclic amine carcinogens via O-acetylation and N-acetylation [28–30]. In our case–control study we have found an inverse association between NAT2 A/A genotype (rs1799930) and BCa development. This result concord with those of Lei Quan who reported that NAT2 A/A carriers (rs1799930) were at 50% decreased risk of bladder cancer development compared to rapid acetylator[31]. Catechol-O-methyltransferase (COMT) encodes a phase II enzyme mainly liable for the degradation of catecholamines, like dopamine and noradrenalinev [32]. It catalyzes the O-methylation of 2-hydroxyestradiol to yield 2-ME2 [32]. Additionally, it is involved within the inactivation of potential carcinogenic compounds that produce inflammation and catechol estrogens and thus might protect DNA from oxidative damage. Rs4680 (Ex4-12 G > A, or val158met) is the most studied COMT single nucleotide polymorphism (SNP). In our cohort we explain the significant inverse association of heterozygous genotype against BCa development by the modification of enzyme activity associated to this genotype. Indeed it has been reported that valine (val) variant enzyme is 3–4 times more active than the methionine (met) variant [33, 34]. Moreover we observed that PRKAR2B A/A genotype (rs3752645) is inversely correlated with BCa risk. The rs3752645 G/A SNP lies within the PRKAR2B gene, which encodes a regulatory subunit for cyclic adenosine 3′, 5′-monophosphate kinase. Our result confirms previous findings of a GWAS study where the authors showed that the rs3752645 SNP had a strong inverse association with BCa risk [35].

In contrast we have found that homozygous minor genotype or heterozygous genotype for rs1889740 C/T, rs2228099 C/G, rs2256355 T/C, rs2864873 A/G in ARNT gene (Aryl hydrocarbon receptor nuclear translocator) were significantly associated to increased risk of bladder cancer. These SNPs are described for the first time in association with increased risk of BCa development. ARNT gene encodes a protein that binds to ligand-bound aryl hydrocarbon receptor and promotes the expression of genes involved in xenobiotic metabolism [36]. We also found that the inheritance of rare homozygous genotype of GSS (rs7260770) is associated with an increased risk of BCa which confirms findings reported in other studies [37]. These findings may be explained by the functional impact of this variant on the enzyme activity. Indeed it has been reported that GSS deficiency resulted in decreased GSH levels and caused dramatic metabolic consequences. However, the role of GSS in cancers has not been studied in details. Finally we showed that GSTA4 G/A genotype (rs17614751) was associated with an increased risk of BCa in our population. This result could be explained by the perturbation of enzyme activity or expression (the rs17614751 SNP is a downstream gene variant). Moreover, it has been reported that the deregulation of GSTA4 enzyme activity was implicated in cell proliferation in nasopharyngeal carcinoma, breast cancer, and liver cancer cells [38].

DNA repair pathway

When considering the DNA repair pathway we have found that the minor alleles of the rs4639 and rs2228000 SNPs in NEIL2 and XPC genes respectively were associated with a decreased risk of BCa development compared to reference groups carrying major alleles. However the minor alleles observed in the studied population for the rs1013358 and rs1799801 SNPs in respectively MPG and ERCC4/ XPF genes increased the risk of bladder cancer.

The NEIL2 (Nei-like DNA glycosylase 2) gene encodes for an enzyme implicated in the first step of the base excision repair (BER) mechanism which consists of cleaving oxidatively damaged bases and introducing a DNA strand break via the associated lyase reaction [39]. The rs4639, is located on 3′UTR of NEIL2[40]. In our study, we found that NEIL2 G/G genotype for rs4639 was associated with 0, 49-fold decreased risk of BCa. This inverse association could be explained by the fact that the minor allele interacts with some specific miRNA, which activates the BER pathway [41]. Moreover, we have found that rs4639 and rs804276 in NEIL2 gene were in linkage disequilibrium (p-value = 0.03). Beside NEIL2, we found that XPC AA genotype (rs2228000) was associated with a decreased risk of BCa compared to reference group. The XPC gene is located on 3p25 and encodes for an enzyme involved in global genome repair. This enzyme represents the earliest damage detector by initiating the NER pathway and eliminating the DNA damages induced by chemical and environmental exposures such as aromatic amines and UV light [42]. Our result confirms the study of Zhu Y. et al. which demonstrates a significant association between the presence of XPC rs2228000 AA genotype and a decreased risk of BCa [43]. However, the recent study of Dai Y. et al. suggests that XPC AA genotype may be linked to an increased risk of bladder and breast cancer [44]. These conflicting results and differences in risk associations may be explained by the different etiology and mechanisms of BCa in study populations with different ethnic backgrounds [15].

On the other hand, ERCC4/XPF and MPG enzymes represent the headmaster in DNA metabolic process, DNA repair, and cellular response to DNA damage stimulus. ERCC4 (16p13.12) is a NER gene that plays a key role in DNA repair that protects against genetic instability and carcinogenesis [45]. The ERCC4-rs1799801 is a synonymous variation (Ser835Ser). A significant association between the ERCC4-rs1799801 polymorphisms and increased risk of Bca in Tunisian population could be explained by the effect of this variation on the enzyme activity. Indeed a previously genotype-phenotype correlation analysis indicated that the ERCC4-rs1799801 rare homozygous C/C genotype carriers had an increased trend of ERCC4 expression levels [46]. In contradiction with our results, the meta-analysis of Shi T.Y. et al. also did not provide statistical evidence for an association between ERCC4 gene and the overall risk of several human cancers, they also report that stratification analysis showed an inverse correlation with cancer in Caucasians [47]. These conflicting results could be explained by a difference in both ethnic origins of patients and exposure to environmental risk factors. MPG, a BER gene, also plays an important role in DNA repair.

Others cellular pathway

In addition to xenobiotic metabolic pathway and DNA repair process we are interested in this study to investigate the impact of others variations in gene implicated in cell proliferation pathway and immunology response in the etiology of BCa. Among the analyzed variations in this panel we have found that APOBR/IL27 A/C genotype (rs17855750) was associated with 2.27 fold-increased risk of BCa. The APOBR (Apolipoprotein B Receptor)/ IL27 (Interleukin 27) encodes for a protein that has been recognized as a pleiotropic cytokine with both pro- and anti-inflammatory properties [48]. This significant association could be explained by the implication of encoded enzyme in the inflammatory process. In the same context, Zhou B. et al. showed a significant association between IL-27 gene polymorphisms and IL-27plasma level and reported that rs17855750 GG (CC) genotype was associated with increased risk for muscle invasive bladder carcinoma. Moreover we found that rs7104333 in CD5/VPS37C gene. The Vacuolar protein sorting-associated protein 37C (VPS37C) is a Component of the ESCRT-I complex, and a regulator of vesicular trafficking process. This protein may be involved in cell growth and differentiation and it is known as a negative regulator of T- and B-cell receptor signaling. Its expression has been shown to be implicated in T lymphocytes tolerance toward tumor cells [49]. In contrast we have found that genetic variations in BLNK (rs3789928), TP63 (rs710521), ROCK1 (rs288980) and ACTRT3/MYNN (rs10936599) were associated with a decreased risk of bladder cancer. BLNK gene encodes for a cytoplasmic linker or adaptor protein that plays a critical role in B cell development [50]. It plays an important role in the pro-B cell to pre-B cell transition and B-cell apoptosis via BCR signaling pathway and reported to have a tumor-suppressive function in various hematologic malignancies [51]. Moreover the Human Protein Atlas consortium showed that high expression of BLNK had a favorable prognosis value in urothelial cancer [52]. TP63 (3q27-28) has a homolog sequence to TP53 (tumor suppressor) and TP73[53]. This gene encodes for an enzyme implicated in the control of cell cycle and plays an important role in apoptosis. Abnormal expression of TP63 is associated with a loss of urothelial differentiation [54]. In our study the TP63 T/C genotype (rs710521) was reported to be inversely associated with BCa (p-value = 0.035 and an OR = 0.62; CI95% 0.42–0.89). Our results seem to agree with those of Kimeney L. et al. and Lehmann M.-L et al. who confirmed that this variant plays a role in decreasing the risk of BCa in European patients [55, 56]. We have also found that ROCK1 TT genotype (rs288980) was associated with 0.75 fold-decreased risk of BCa. ROCK1 enzyme is a necessary effector kinase downstream of Rho GTPases, a very important pathway involved in cell migration and has been identified as a possible therapeutic target [57]. The Cancer Genome Project identified three non-synonymous mutations within the ROCK1 gene [58] but the effect of these variations in protein activity or expression was not more elucidated. Finally ACTRT3/ MYNN (Actin Related Protein T3; 3q26.2) gene is poorly described in the literature. The minor T allele of rs10936599 in ACTRT3/ MYNN has been described in the Genome-wide association study conducted by Figueroa J. et al. in 2014, to be highly associated with decreased risk of BCa [59], which was confirmed by Wang M. et al. [60]. However, the effect of rs10936599 polymorphism on the MYNN activity is not well known and more biological functional studies are needed to draw more concise conclusions regarding the underlying molecular mechanism of this variation.

Interaction between genetic and environmental risk factors

When we compare the distribution of unfavorable genotypes [GSS G/A (rs7260770), ARNT A/G (rs2864873), ARNT C/T (rs1889740) ARNT C/G (rs2228099), ARNT T/C (rs2256355), GSTA4 G/A (rs17614751), ERCC4 C/C (rs1799801), MPG C/C (rs1013358), VPS37C A/A (rs7104333), APOBR/IL27 A/C (rs17855750)] between exposed bladder cancer cases and controls according to environmental risk factors we found that ARNT C/T (rs1889740), ARNT A/G (rs2864873) and GSTA4 G/A (rs17614751) genotypes were associated with an increased risk of BCa even in the absence of tobacco risk factors, or professional risk factors. Moreover when we compared exposed cases to exposed controls, we have not found a significant additive effect between the majority of unfavorable genotypes and exposure to environmental risk factors (smokers’ ≥ 20PY or exposed to professional risk factors). The absence of significant additive effect between the majority of unfavorable genotypes and BCa risk could be explained by the fact that the targeted SNPs encoding enzymes were not directly implicated in the metabolism of xenobiotics. For example, the proinflammatory role of APOBR/IL27 enzyme could explain the role of rs17855750 in BCa development independently to exposition to environmental risk factors. However this additive effect reached more than 12 fold-increased risk of BCa development for ARNT rs1889740 T/T, ARNT rs2228099 G/G and ARNT rs2256355 C/C genotypes in subjects exposed to professional risk factors. This association may be explained by the fact that ARNT gene encodes a protein thats binds to ligand-bound aryl hydrocarbon receptor and promotes the expression of genes involved in xenobiotic metabolism [36]. Whether this association is caused by specific bladder carcinogens present in the work environment warrants further investigations. To conclude our analysis, a decision tree was implemented to create a disease prediction model. This tree has allowed us to define the risk groups most genetically likely to develop BCa. According to the established decision tree, we note the importance of both smoking status (≥ 20PY) and the genotype of CYP1A2 (rs762551) in the development of BCa. The decision-tree analysis produced a three major BCa class. The first major class (58/249) is defined by the presence of CYP1A2 CC or CYP1A2 CA genotype and also defined by others 8 variations: ARNT C > G (rs2228099), CYP1B1 T > C (rs162555), SOD1 T > C (rs2173962), ROCK1 T > C (rs288980), IL10 A > T (rs1800890), LY96 T > C (rs17226566), AICDA T > G (rs11046349) and MAP2K4 C > T (rs4791489). The second major class of BCa group (31/249) is only defined by the intensity of tobacco use ≥ 20PY and the inheritance of the homozygous genotype for rs762551 in CYP1A2 (CYP1A2 A/A), XPC GG or AG genotype (rs2228000, G > A), and MAP2K4 CC or CT genotype (rs4791489, C > T). This decision tree confirms the crucial role of tobacco consumption in the etiology of BCa. Indeed BCa is considered as a smoking-related cancer [61]. This risk was attributed to many compounds of tobacco such as 4-Aminobiphenyl, 3-Amino-1,4-dimethyl-5H-pyrido [4,3-b] indole (Trp-P-1), Toluene, Benzo[a]pyrene, Benzene… [62]. In the other hand CYP1A2 is an enzyme responsible for the metabolism of caffeine and some tobacco compounds. Rs762551 variation in CYP1A2 gene encodes for the CYP1A2*1F allele. The baseline activity of the enzyme is similar in CYP1A2*1F allele carriers and non-carriers. Moreover it has been reported that he presence of rs762551 (A) codes for the "high inducibility" form the CYP1A2 enzyme, characterized by higher enzyme activity in the presence of an inducer such as smoking or heavy coffee consumption[63]. To explain our result we have reanalyzed the CYP1A2 C > A genotype distribution between cases and controls and according to tobacco status. As result we have found that the inheritance of CYP1A2 (CC) or CYP1 A2 (CA) genotype were respectively associated with 6.89 and 9.04 –fold increased risk of BCa in only heavy smokers patients (≥ 20PY) compared to heavy smokers controls. However we have not data about coffee consumption.

We have conducted the first study in Tunisian population to evaluate systematically the association between genetic variations in BCa and environmental factors. We also determined the effect of studied pathway SNPs in comparison with environmental exposition. Once validated, these findings may provide urologists additional genetic information that may help for clinical assessment and treatment decisions. Nevertheless, the underlying mechanisms through which these genes or SNPs affect the clinical behavior of BCas require further studies. Future investigations in our populations and detailed functional characterization are needed to establish predictive or prognostic markers for BCa.

ACTRT3

Actin Related Protein T3; 3q26.2

APOBR

Apolipoprotein B Receptor

ARNT

Aryl hydrocarbon receptor nuclear translocator

BCa

Bladder cancer

BER

base excision repair

BLNK

B cell linker

COMT

Catechol-O-methyltransferase

CYP1B1

cytochrome P450 family 1 subfamily B member 1

CYP3A4

Cytochrome P450 3A4

dbSNP

database of single nucleotide polymorphisms

DNA

deoxyribonucleic acid

DRC

DNA Repair Capacity

DSBR

double-strand break repair

EDTA

ethylene diamine tetra-acetic acid

ERCC4

Excision Repair Cross-Complementation group 4

GSTM1

Glutathione-s-transferase M1

GWAS

Genome-Wide Association Study

GSS

Glutathione Synthase

GSTA4

Glutathione S-transferase Alpha 4

HG

High-Grade

IARC

International Agency for Research on Cancer

IL27

Interleukin 27

KEGG

Kyoto Encyclopedia of Genes and Genomes

LG

Low-Grade

MIBC

muscle-invasive BCa

MMR

mismatch repair

MPG

N-methylpurine DNA glycosylase

NEIL2

Nei-like DNA glycosylase 2

NAT2

N-acetyltransferase 2

NER

nucleotide excision repair

NGS

Next-Generation Sequencing

NMIBC

non-muscle-invasive BCa

PRKAR2B

Protein Kinase cAMP-dependent type II regulatory subunit beta

ROCK1

Rho associated coiled-coil containing protein kinase 1

SNP

nucleotide polymorphisms

TCR

transcription-coupled repair

TP63

Tumor Protein p63

VPS37C

vacuolar protein sorting-associated protein 37C

WHO

World Health Organization

XPC

Xeroderma Pigmentosum, Complementation group C

XPF

excision repair cross-complementing rodent repair deficiency, complementation group 4

Ethics approval and consent to participate

- This trial protocol and recruitment were approved and carried out after the agreement of the ethics committee of the Charles Nicolle Hospital and approved by an Ethics Committee (IEC Project No. 17-35) and an MTA (MATERIAL TRANSFER AGREEMENT MTA/ 2017 / IMP / GCS)/ 0356) from IARC.

-Informed consent was obtained from all participants (in both languages: Arabic/French) prior to enrollment and participation in this study..

- All samples are coded and no patient names appear in the study. All data whether clinical or personal remains anonymous and secret.

Consent for publication

Not applicable. This study did not use identifying images and any clinical and personal details despite written informed consent for publication of their clinical details and/or clinical

Availability of data and material

The dataset is available upon reasonable request to the corresponding author

Competing interests

The authors declare that they have no competing interests

Funding

“No funding was obtained for this study”

Authors' contributions

IH: Collecting clinical samples and data, designed the panel, molecular analysis, drafted the manuscript and bioinformatics analyzes. SB, HD and FH: Help in Bioinformatics and statistical analyzes. GD and CV: Technical assistance for NGS analyzes. HA: Clinical characterization of the studied population. SZ, ZN and MA: help in collecting samples. MC and JM: designed the study and revised the manuscript. FL: drafted and revised the manuscript. SO: designed the study, performed the statistical analysis and drafted and revised the manuscript. All authors read and approved the final version of the manuscript.

Acknowledgements

The authors thank all patients for participating in this study. We greatly thank also the Urology department, Charles Nicolle hospital, Tunis, Tunisia, Biochemistry Department, Charles Nicolle Hospital, Tunis and the International Agency for Research on Cancer IARC ; Lyon. France.

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SupplementaryFile.docx

Development of a Custom NGS Panel for the Determination of Bladder Cancer Risk

Status:

Version 1

Abstract

Figures

Highlight

Background

Methods

Study population

Biological Samples And Dna Extraction

Panel Design

Snp Genotyping

Bioinformatics Analyses

Results

Discussion

Xenobiotic metabolism pathway

DNA repair pathway

Others cellular pathway

Interaction between genetic and environmental risk factors

Conclusion

Abbreviations

Declarations

References

Supplementary Files

Status:

Version 1