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Abstract

Background:

Vascular endothelial growth factor (VEGF) is a crucial regulator of physiological and pathological angiogenesis. Increased VEGF expression has been linked with inappropriate VEGF-induced angiogenesis in various disease pathologies including cancers.

Methodology:

In this case–control study, DNA samples of 319 esophageal squamous cell cancer (ESCC) patients and 354 healthy controls from Punjab, North-West India, were screened for VEGF-417T/C, -172C/A, -165C/T, -160C/T, -152G/A, -141A/C, and -116G/A promoter polymorphisms using Sanger sequencing.

Results:

AA genotype and A allele of both VEGF-152G/A and -116G/A polymorphisms were significantly associated with elevated risk to ESCC in total subjects as well as in female group. CT genotype and T allele of VEGF-165C/T polymorphism were significantly associated with reduced risk for ESCC only in female group. Body mass index-based stratification analysis revealed significant association of AA genotype and A allele of VEGF-152G/A and A allele of VEGF-116G/A polymorphism with an increased risk to ESCC in nonobese patients. Linkage disequilibrium was observed between VEGF-165C/T and VEGF-141A/C (D′ = 0.88, r² = 0.68) and between VEGF-152G/A and VEGF-116G/A (D′ = 0.93, r² = 0.49) polymorphisms. Haplotype T-C-C-C-A-A-A was significantly associated with increased ESCC risk in total subjects as well as in female group.

Conclusion:

From this study, we concluded that VEGF-116 G/A and VEGF-152G/A polymorphisms were significantly associated with increased ESCC risk in total patients as well as in female group, whereas VEGF-165 C/T polymorphism was associated with reduced risk only in female group.

Introduction

Vascular endothelial growth factor (VEGF) is a paradigm of gene regulation as it is regulated at all stages of gene expression, including transcription, messenger RNA (mRNA) stability, and mRNA translation.1,2 The VEGF, a highly conserved homodimeric glycoprotein, is a crucial regulator of physiological and pathological angiogenesis.3 Increased VEGF expression has been linked with inappropriate VEGF-induced angiogenesis in various disease pathologies, including tumor growth and metastasis.4 It has been demonstrated that patients with a low VEGF expression have a better prognosis as compared to those with high expression levels.5,6

VEGF or VEGFA (OMIM 192240) located at 6p21.1 spanning the 14 kb coding region7 is a highly polymorphic gene, and more than 30 single nucleotide polymorphisms (SNPs) have been reported in different parts of this gene.8,9 Functional polymorphisms in the VEGF promoter may influence promoter activity, resulting in differences in VEGF protein production between individuals.9 –11

The role of VEGF-417T/C, -172C/A, -165C/T, -160C/T, -152G/A, -141A/C, and -116G/A promoter polymorphisms has been investigated in different diseases. Till date, there are only few reports on some of these seven polymorphisms in gastrointestinal tract (GIT) cancers. VEGF-116G/A polymorphism has been studied in various GIT cancers, such as oral,12,13 gastric,14 colon,15 colorectal,16 –20 gallbladder,21 and hepatocellular cancer.22,23 VEGF-417T/C and VEGF-152G/A have been studied in colorectal cancer in the Japanese population.16 VEGF-141A/C has been studied in hepatocellular carcinoma in Turkish population.24 The association of A allele of VEGF-141A/C polymorphism with increased risk of papillary thyroid carcinoma has been reported in the Australian population.25 G allele of VEGF-152G/A has been reported to be associated with increased risk of nonsmall cell lung cancer in North Indians.26

Correlation of VEGF promoter polymorphisms with therapy response has been studied in different GIT cancers. A allele of VEGF-116G/A polymorphism has been reported to be associated with severe acute toxicities in 5-fluorouracil/cisplatin-based chemoradiotherapy-treated Japanese esophageal cancer patients.27 GG genotype of VEGF-152G/A and VEGF-116G/A polymorphism wasassociated with shorter progression-free survival inmetastatic colorectal cancer patients.28 In Dutch population, VEGF-116AA genotype was associated withshorter progression-free survival in gastrointestinal stromal tumor patients treated with Imatinib based therapy.29 In metastatic colorectal cancer, GG genotype of VEGF-116 G/A polymorphism was reported with better response rates to chemotherapy and longer progression-free survival.30 Variations in the VEGF could have a promising role in identifying different risk categories among patients receiving anti-angiogenic therapies.

VEGF is a key mediator of continued survival and progression in solid tumors, including esophageal cancer.31 Some studies documented the involvement of VEGF-induced angiogenesis in esophageal adenocarcinoma.32 –36 Over expression of VEGF has been reported to be linked with poor clinical outcomes in patients with advanced esophageal squamous cell carcinoma.37 –41

Genetic polymorphisms might be responsible for interindividual differences in esophageal cancer susceptibility and progression.42 The prognostic significance of VEGF SNPs in esophageal cancer has been reported in Caucasians.43 Till date, there is only one published study among GIT cancers from North India, which reported an increased cancer risk associated with VEGF-116 A allele.21 VEGF promoter polymorphisms have been linked with GIT cancer risk and its development, prognosis, and therapy response; therefore, the aim of this present study was to investigate the role of seven VEGF promoter polymorphisms [-417T/C (rs833062), -172C/A (rs59260042), -165C/T (rs79469752), -160C/T, -152G/A (rs13207351), -141A/C (rs28357093), and -116G/A (rs1570360)] with esophageal squamous cell cancer risk in North-West Indians. To the best of our knowledge, this is the first study on these seven VEGF promoter polymorphisms in esophageal squamous cell cancer.

Materials and Methods

Selection of study participants and collection of blood samples

We conducted a case–control study on 673 subjects (319 esophageal squamous cell cancer (ESCC) patients and 354 controls). The design of this study was approved by the institutional ethics committee of Guru Nanak Dev University, Amritsar. All methods were carried out in accordance with relevant guidelines and regulations (IRB approval No. 1610/HG, dated May 9, 2023). Clinically confirmed ESCC patients were recruited from Sri Guru Ram Das Institute of Medical Sciences and Research, Vallah, Amritsar, Punjab (India). The control group consisted of 354 unrelated healthy, age-, gender-, and geography-matched individuals. The demographic and clinical characteristics of ESCC patients and controls were recorded on proforma. All the patients and controls gave a written informed consent to participate in this study. Five milliliter venous blood sample was collected from each subject in an ethylene diamine tetra-acetic acid (EDTA)-coated vial and was stored at −20 °C for subsequent DNA extraction. Genomic DNA was extracted from each blood sample using the standard method.44

Genotyping of VEGF promoter polymorphisms

The promoter region of VEGF (Fig.1) harboring sevenpolymorphisms [-417T/C (rs833062), -172C/A (rs59260042), -165C/T (rs79469752), -160C/T, -152G/A (rs13207351), -141A/C (rs28357093), and -116G/A (rs1570360)] was amplified using published primer sequences.45 The polymerase-chain reaction (PCR) reaction of 25 µl contained 100 ng of genomic DNA, 1X Taq buffer, 0.5 µl dNTPs mix, 10 pmol of forward and reverse primers, 1X Q-solution, and 0.6U Taq polymerase (Qiagen, Germany). Amplification conditions consisted of initial denaturation at 95 °C for 5 min, followed by 35 cycles with denaturation at 95 °C for 45 s, annealing at 62 °C for 30 s, extension at 72 °C for 45 s, and final extension at 72 °C for 10 min. The purified PCR products of 486bp were sequenced using the Big Dye terminator kit (version 3.1). Sequencing data were analyzed using Chromas v1.45 (Technelysium Pty Ltd., Queensland, Australia) software.

FIG. 1.

Diagram showing locations of analyzed VEGF promoter polymorphisms.

Statistical analysis

Deviation of genotype frequencies from Hardy–Weinberg equilibrium was assessed using chi square test. Odds ratio (OR) and its 95% confidence interval (CI) were used to find the association of genotypes and alleles of VEGF polymorphisms with ESCC risk. The age, gender, diet, smoking status, and alcohol consumption were selected as adjustment variables. Data analysis was carried out using online SNPstats software.46 Online SHEsis software was used to calculate Lewontin’s standardized disequilibrium coefficient (D′) and correlation coefficient (r²).47 The value of p < 0.05 was considered statistically significant.

Results

Characteristics of the ESCC patients and healthy controls

In this case–control study, a total of 673 subjects (319 ESCC patients and 354 unrelated healthy controls) from the Punjab state, North-West India, were screened (Table1). The mean age of patients and controls was 56.59 ± 13.02 and 56.01 ± 12.23 years, respectively. In 62.07% of patients, cancer was diagnosed after the age of 50 years. The number of female patients was higher as compared to male patients. Of the 319 ESCC patients, 12.56% had stage I, 44.72% had stage II, 25.63% had stage III, and 9.05% had stage IV tumor. Cancer stage was unknown in 8.04% patients.

Table1.

Baseline characteristics of ESCC patients and healthy controls

	Patients		Controls
Characteristics	n	Percent	n	Percent
No. of subjects	319		354
Gender
Males	134	42.01	154	43.50
Females	185	57.99	200	56.50
Age
≤50 years	121	37.93	199	56.21
>50 years	198	62.07	155	43.79
Mean age (years)
Total	56.59 ± 13.02		56.01 ± 12.23
Males	58.13 ± 13.73		58.27 ± 13.03
Females	55.48 ± 12.39		55.05 ± 12.92
Habitat
Rural	252	79.00	260	73.44
Urban	55	17.24	79	22.32
Suburban	12	3.76	15	4.24
Habits
Diet
Vegetarian	167	52.35	216	61.02
Nonvegetarian	152	47.65	138	38.98
Alcohol intake
Yes	82	25.71	70	19.77
No	237	74.29	284	80.23
Smoking
Yes	40	12.54	10	2.82
No	279	87.46	344	97.18
Nonsmokers
Males	96	34.41	146	42.44
Females	183	65.59	198	57.56
Smokers
Males	38	95.0	8	80.0
Females	2	5.0	2	20.0
Menstrual status
Premenopausal	34	18.38	82	41.0
Post-menopausal	151	81.62	118	59.0

ESCC: esophageal squamous cell cancer.

Association of VEGF promoter polymorphisms with ESCC risk in total patients

The DNA samples of 319 ESCC patients and 354 controls were screened for VEGF-417T/C, -172C/A, -165C/T, -160C/T, -152G/A, -141A/C, and -116G/A VEGF promoter polymorphisms using Sanger sequencing. We observed 2bp ins/del in seven esophageal cancer patients and in one healthy control. The genotypes distributions of VEGF-116 G/A and VEGF-152G/A polymorphisms were in agreement with Hardy–Weinberg equilibrium in controls (p > 0.05). Comparative genotype and allele frequencies of VEGF promoter polymorphisms between ESCC patients and controls have been detailed in Table2. The frequency of AA genotype and A allele of VEGF-152G/A andVEGF-116G/A polymorphisms was higher in ESCC patients as compared to controls. Individuals with VEGF-152AA genotype (OR = 1.78, 95% CI, 1.12–2.82; p = 0.04) and A allele (OR = 1.30, 95% CI, 1.05–1.62; p = 0.02) showed significantly increased risk to esophageal cancer in total subjects. Genetic model analysis of VEGF-152G/A polymorphism revealed significantly increased cancer risk under codominant (p = 0.04), recessive (p = 0.02), and log additive (p = 0.02) genetic models (Table3).

Table2.

The relationship between VEGFA promoter polymorphisms and susceptibility to esophageal squamous cell carcinoma

	Total				Females				Males
Variant	Patients, N = 319n (percent)	Controls, N = 354n (percent)	AOR (95 percent CI)	p value*	Patients, N = 185n (percent)	Controls, N = 200n (percent)	AOR (95 percent CI)	p value†	Patients, N = 134n (percent)	Controls, N = 154n (percent)	AOR (95 percent CI)	p value†
-417T/C(rs833062)
Genotype
TT	304 (95.3)	335 (94.6)	Reference		177 (95.7)	190 (95.0)	Reference		127 (94.8)	145 (94.2)	Reference
TC	15 (4.7)	18 (5.1)	0.99 (0.48–2.02)	0.49	8 (4.3)	9 (4.5)	0.95 (0.36–2.53)	0.52	7 (5.2)	9 (5.8)	1.04 (0.35–3.05)	0.95
CC	–	1 (0.3)	–	–	–	1 (0.5)	–	–	–	–	–	–
Allele
T	623 (97.6)	688 (97.2)	Reference		362 (97.8)	389 (97.3)	Reference		261 (97.4)	299 (97.0)	Reference
C	15 (2.4)	20 (2.8)	0.83 (0.42–1.63)	0.59	8 (2.2)	11 (2.7)	0.78 (0.31–1.96)	0.60	7 (2.6)	9 (3.0)	0.89 (0.33–2.43)	0.82
-172C/A (rs59260042)
Genotype
CC	312 (100.0)	353 (100.0)	–	–	181 (100.0)	200 (100.0)	–	–	131 (100.0)	153 (100.0)	–	–
CA	–	–	–	–	–	–	–	–	–	–	–	–
AA	–	–	–	–	–	–	–	–	–	–	–	–
Allele
C	624 (100.0)	706 (100.0)	–	–	362 (100.0)	400 (100.0)	–	–	262 (100.0)	306 (100.0)	–	–
A	–	–	–	–	–	–	–	–	–	–	–	–
-165C/T (rs79469752)
Genotype
CC	287 (92.0)	315 (89.2)	Reference		168 (92.8)	171 (85.5)	Reference		119 (90.8)	144 (94.1)	Reference
CT	25 (8.0)	38 (10.8)	0.62 (0.35–1.07)	0.08	13 (7.2)	29 (14.5)	0.46 (0.23–0.93)	0.03	12 (9.2)	9 (5.9)	1.41 (0.54–3.70)	0.48
TT	–	–	–	–	–	–	–	–
Allele
C	599 (96.00)	668 (94.6)	Reference		349 (96.4)	371 (92.8)	Reference		250 (95.4)	297 (97.1)	Reference
T	25 (4.00)	38 (5.4)	0.74 (0.44–1.23)	0.24	13 (3.6)	29 (7.2)	0.48 (0.24–0.93)	0.03	12 (4.6)	9 (2.9)	1.58 (0.66–3.82)	0.31
-160C/T
Genotype
CC	302 (96.8)	346 (98.0)	Reference		177 (97.8)	197 (98.5)	Reference		125 (95.4)	149 (97.4)	Reference
CT	10 (3.2)	7 (2.0)	1.58 (0.58–4.33)	0.37	4 (2.2)	3 (1.5)	–	–	6 (4.6)	4 (2.6)	–	–
TT	–	–	–	–	–	–	–		–	–	–	–
Allele
C	614 (98.4)	699 (99.0)	Reference		358 (98.9)	397 (99.3)	Reference		256 (97.7)	302 (98.7)	Reference
T	10 (1.6)	7 (1.0)	1.63 (0.62–4.30)	0.33	4 (1.1)	3 (0.7)	–	–	6 (2.3)	4 (1.3)	–	–
-152G/A (rs13207351)
Genotype
GG	89 (28.5)	121 (34.3)	Reference		49 (27.1)	72 (36.0)	Reference		40 (30.5)	49 (32.0)	Reference
GA	154 (49.4)	179 (50.7)	1.17 (0.83–1.66)	0.38	87 (48.0)	103 (51.5)	1.24 (0.78–1.97)	0.36	67 (51.2)	76 (49.7)	1.08 (0.63–1.84)	0.78
AA	69 (22.1)	53 (15.0)	1.78 (1.12–2.82)	0.04	45 (24.9)	25 (12.5)	2.63 (1.43–4.84)	0.005	24 (18.3)	28 (18.3)	0.98 (0.47–2.04)	0.96
Allele
G	332 (53.2)	421 (59.6)	Reference		185 (51.1)	247 (61.8)	Reference		147 (56.1)	174 (56.9)	Reference
A	292 (46.8)	285 (40.4)	1.30 (1.05–1.62)	0.02	177 (48.9)	153 (38.2)	1.54 (1.16–2.06)	0.003	115 (43.9)	132 (43.1)	1.03 (0.74–1.44)	0.86
-141A/C (rs28357093)
Genotype
AA	282 (90.4)	312 (88.4)	Reference		165 (91.2)	171 (85.5)	Reference		117 (89.3)	141 (92.2)	Reference
AC	30 (9.6)	41 (11.6)	0.71 (0.42–1.19)	0.19	16 (8.8)	29 (14.5)	0.58 (0.30–1.13)	0.1	14 (10.7)	12 (7.8)	1.22 (0.51–2.92)	0.65
CC	–	–	–	–	–	–	–	–	–	–	–	–
Allele
A	594 (95.2)	665 (94.2)	Reference		346 (95.6)	371 (92.8)	Reference		248 (94.7)	294 (96.1)	Reference
C	30 (4.8)	41 (5.8)	0.82 (0.51–1.33)	0.42	16 (4.4)	29 (7.2)	0.59 (0.32–1.11)	0.10	14 (5.3)	12 (3.9)	1.38 (0.63–3.05)	0.42
-116G/A (rs1570360)
Genotype
GG	139 (44.5)	187 (53.0)	Reference		83 (45.9)	109 (54.5)	Reference		56 (42.8)	78 (51.0)	Reference
GA	130 (41.7)	145 (41.1)	1.21 (0.87–1.67)	0.26	70 (38.7)	79 (39.5)	1.16 (0.76–1.79)	0.49	60 (45.8)	66 (43.1)	1.27 (0.78–2.07)	0.35
AA	43 (13.8)	21 (5.9)	2.71 (1.52–4.83)	0.002	28 (15.4)	12 (6.0)	3.04 (1.46–6.36)	0.008	15 (11.4)	9 (5.9)	1.89 (0.72–4.95)	0.29
Allele
G	408 (65.4)	519 (73.5)	Reference		236 (65.2)	297 (74.3)	Reference		172 (65.7)	222 (72.5)	Reference
A	216 (34.6)	187 (26.5)	1.47 (1.16–1.86)	0.001	126 (34.8)	103 (25.7)	1.54 (1.13–2.10)	0.007	90 (34.3)	84 (27.5)	1.38 (0.96–1.97)	0.08

AOR: adjusted odds ratio; CI: confidence interval.

Adjusted for age, gender, diet, smoking status, and alcohol consumption.

†

Adjusted for age, diet, smoking status, and alcohol consumption; statistically significant p values are displayed in bold.

Table3.

Association of VEGF-152G/A and VEGF -116G/A promoter polymorphisms with ESCC risk under different genetic models

	Total				Females				Males
Genetic model	Patients, n (percent)	Controls, n (percent)	AOR (95 percent CI)	p value*	Patients, n (percent)	Controls, n (percent)	AOR (95 percent CI)	p value†	Patients, n (percent)	Controls n (percent)	AOR (95 percent CI)	p value†
VEGF-152G/A
Codominant
GG	89 (28.5)	121 (34.3)	Reference		49 (27.1)	72 (36.0)	Reference		40 (30.5)	49 (32.0)	Reference
GA	154 (49.4)	179 (50.7)	1.17 (0.83–1.66)	0.38	87 (48.0)	103 (51.5)	1.24 (0.78–1.97)	0.36	67 (51.2)	76 (49.7)	1.08 (0.63–1.84)	0.78
AA	69 (22.1)	53 (15.0)	1.78 (1.12–2.82)	0.04	45 (24.9)	25 (12.5)	2.63 (1.43–4.84)	0.005	24 (18.3)	28 (18.3)	0.98 (0.47–2.04)	0.96
Dominant
GG	89 (28.5)	121 (34.3)	Reference		49 (27.1)	72 (36.0)	Reference		40 (30.5)	49 (32.0)	Reference
GA+AA	223 (71.5)	232 (65.7)	1.29 (0.92–1.80)	0.14	132 (72.9)	128 (64.0)	1.50 (0.97–2.33)	0.07	91 (69.5)	104 (68.0)	1.04 (0.61–1.78)	0.88
Recessive
GG+GA	243 (77.9)	300 (85.0)	Reference		136 (75.1)	175 (87.5)	Reference		107 (81.7)	125 (81.7)	Reference
AA	69 (22.1)	53 (15.0)	1.64 (1.09–2.45)	0.02	45 (24.9)	25 (12.5)	2.32 (1.35–3.98)	0.002	24 (18.3)	28 (18.3)	0.94 (0.50–1.80)	0.86
Over dominant
GG+AA	158 (50.6)	174 (49.3)	Reference		94 (51.9)	97 (48.5)	Reference		64 (48.8)	77 (50.3)	Reference
GA	154 (49.4)	179 (50.7)	0.92 (0.68–1.26)	0.62	87 (48.1)	103 (51.5)	0.86 (0.58–1.29)	0.48	67 (51.2)	76 (49.7)	1.07 (0.65–1.77)	0.78
Log additive	–	–	1.31 (1.04–1.64)	0.02	–	–	1.56 (1.16–2.10)	0.003	–	–	1.00 (0.70–1.43)	1
VEGF-116G/A
Codominant
GG	139 (44.5)	187 (53.0)	Reference		83 (45.9)	109 (54.5)	Reference		56 (42.8)	78 (51.0)	Reference
GA	130 (41.7)	145 (41.1)	1.21 (0.87–1.67)	0.26	70 (38.7)	79 (39.5)	1.16 (0.76–1.79)	0.49	60 (45.8)	66 (43.1)	1.27 (0.78–2.07)	0.35
AA	43 (13.8)	21 (5.9)	2.71 (1.52–4.83)	0.002	28 (15.4)	12 (6.0)	3.04 (1.46–6.36)	0.008	15 (11.4)	9 (5.9)	1.89 (0.72–4.95)	0.29
Dominant
GG	139 (44.5)	187 (53.0)	Reference		83 (45.9)	109 (54.5)	Reference		56 (42.8)	78 (51.0)	Reference
GA+AA	173 (55.5)	166 (47.0)	1.44 (1.05–1.97)	0.02	98 (54.1)	91 (45.5)	1.39 (0.92–2.08)	0.11	75 (57.2)	75 (49.0))	1.44 (0.87–2.38)	0.15
Recessive
GG+GA	269 (86.2)	332 (94.0)	Reference		153 (84.6)	188 (94.0)	Reference		116 (88.5)	144 (94.1)	Reference
AA	43 (13.8)	21 (6.0)	2.45 (1.40–4.27)	0.001	28 (15.4)	12 (6.0)	2.87 (1.41–5.85)	0.002	15 (11.4)	9 (5.9)	1.62 (0.64–4.09)	0.31
Over dominant
GG+AA	182 (58.3)	208 (58.9)	Reference		111 (61.3)	121 (60.5)	Reference		71 (54.2)	87 (56.9)	Reference
GA	130 (41.7)	145 (41.1)	1.07 (0.78–1.46)	0.69	70 (38.7)	79 (39.5)	0.94 (0.62–1.43)	0.79	60 (45.8)	66 (43.1)	1.25 (0.76–2.07)	0.38
Log additive	–	–	1.48 (1.16–1.88)	0.001	–	–	1.49 (1.10–2.02)	0.01	–	–	1.37 (0.92–2.05)	0.12

AOR: adjusted odds ratio; CI: confidence interval; ESCC: esophageal squamous cell cancer.

Adjusted for age, gender, diet, smoking status and alcohol consumption;

†

Adjusted for age, diet, smoking status, and alcohol consumption; statistically significant p values are displayed in bold.

VEGF-116AA genotype (OR = 2.71, 95% CI, 1.52–4.83; p = 0.002) and A allele (OR = 1.47, 95% CI, 1.16–1.86; p = 0.001) were significantly associated with increased risk for esophageal cancer (Table2). Genetic model analysis of VEGF-116G/A polymorphism showed significantly increased cancer risk under codominant (p= 0.002), dominant (p = 0.02), recessive (p = 0.001), and log additive (p = 0.001) model (Table3). No significant association was found between VEGF-417T/C, VEGF-172C/A, VEGF-165C/T, VEGF-160C/T, and VEGF-141A/C polymorphisms and esophageal cancer risk in the studied population (p > 0.05).

Gender wise stratification of VEGF promoter polymorphisms and ESCC risk

Stratification of data of VEGF polymorphisms showed a gender-specific association (Table2). In the female group, individuals carrying VEGF-152AA genotype (p = 0.005) and A allele (p = 0.003) had significantly increased risk of esophageal cancer. Similarly, female patients with VEGF-116 AA genotype (p = 0.008) and A allele (p = 0.007) showed increased risk of esophageal cancer. CT genotype (p = 0.03) and T allele (p = 0.03) of VEGF-165C/T polymorphism were significantly associated with reduced risk for esophageal cancer in the female group. Genetic model analysis revealed an association of VEGF-152G/A polymorphism with increased risk under codominant (p = 0.005), recessive (p = 0.002), and log additive model (p = 0.003) in the female group (Table3). VEGF-116G/A polymorphism was also associated with increased risk of esophageal cancer under codominant (p = 0.008), recessive (p = 0.002), and log additive model (p = 0.01) in the female group (Table3).

Age wise stratification of VEGF promoter polymorphisms and ESCC risk

We investigated the association of VEGF polymorphisms with the age at diagnosis of the patients and found that A allele (p = 0.04) of VEGF-116G/A polymorphism was significantly associated with increased risk of esophageal cancer in patients having age at diagnosis more than 50 years as compared to patients having age at diagnosis less than 50 years (Supplementary Table 1).

Stratification of the data based on body mass index

It was observed that the AA genotype (p = 0.007) and Aallele (p = 0.01) of VEGF-152G/A and A allele (p = 0.006) of VEGF-116G/A polymorphism were significantly associated with increased risk to esophageal cancer in nonobese patients (Supplementary Table 2). We observed a significant association of VEGF-152G/A polymorphism with increased risk to esophageal cancer under the codominant (p = 0.007), recessive (p = 0.002), and log additive (p = 0.012) models, whereas VEGF-116G/A polymorphism was associated with increased risk to esophageal cancer under the log additive model (p = 0.006) in nonobese patients (Supplementary Table 3).

Genotype combinations of VEGF promoter polymorphisms and ESCC risk

We compared the different genotype combinations of studied polymorphisms and found that TT-AA (p = 0.03) genotype combination of VEGF-417T/C and VEGF-152G/A, TT-AA (p = 0.002) of VEGF-417T/C and VEGF-116G/A, CC-AA (p = 0.02) of VEGF-165C/T and VEGF-152G/A, CC-AA (p = 0.0006) of VEGF-165C/T and VEGF-116G/A, CC-AA (p = 0.02) of VEGF-160C/T and VEGF-152G/A, CC-AA (p = 0.0005) of VEGF-160C/T and VEGF-116G/A, AA-AA (p = 0.02) of VEGF-152G/A and VEGF-141A/C, AA-AA (p= 0.002) of VEGF-152G/A and VEGF-116G/A, and AA-AA (p = 0.0007) of VEGF-141A/C and VEGF-116G/A polymorphisms were significantly associated with increased risk to esophageal cancer (Supplementary Table 4).

Linkage disequilibrium and haplotype analysis

Linkage disequilibrium (LD) analysis of VEGF promoter polymorphisms revealed a LD between VEGF-165C/T and VEGF-141A/C (D′ = 0.88, r²= 0.68) and between VEGF-152G/A and VEGF-116G/A (D′ = 0.93, r² = 0.49) polymorphisms (Fig.2). Haplotype analysis was carried out to evaluate the combined effect of VEGF promoter polymorphisms on ESCC risk. T-C-C-C-G-A-G was the most common haplotype in the present study with the frequencies of 45.6% in ESCC patients and 49.5% in healthy controls. Haplotype T-C-C-C-A-A-A was significantly associated with increased ESCC risk in total subjects (p = 0.01) as well as in female group (p = 0.02) (Table4). No significant association between other VEGF haplotypes and ESCC risk was observed.

FIG. 2.

Linkage disequilibrium pattern for VEGF promoter polymorphisms in ESCC patients based on (A) D′ and (B) r²; SNP1: VEGF-417T/C, SNP2: VEGF-172C/A, SNP3: VEGF-165C/T, SNP4: VEGF-160C/T, SNP5: -152G/A, SNP6: VEGF-141A/C and SNP7: VEGF-116G/A.

Table4.

VEGF haplotypes and ESCC risk

Haplotype*	Patients (frequency)	Controls (frequency)	AOR (95 percent CI)	p value
Total
T-C-C-C-G-A-G	0.456	0.495	Reference
T-C-C-C-A-A-A	0.322	0.258	1.40 (1.07–1.82)	0.01 †
T-C-C-C-A-A-G	0.121	0.138	0.98 (0.69–1.40)	0.93
T-C-T-C-G-C-G	0.028	0.047	0.60 (0.30–1.18)	0.14
C-C-C-C-G-A-G	0.017	0.028	0.79 (0.37–1.71)	0.55
T-C-C-C-G-A-A	0.015	0.007	1.91 (0.51–7.16)	0.34
Female
T-C-C-C-G-A-G	0.446	0.517	Reference
T-C-C-C-A-A-A	0.326	0.246	1.52 (1.08–2.13)	0.02 ‡
T-C-C-C-A-A-G	0.140	0.116	1.47 (0.91–2.36)	0.12
T-C-T-C-G-C-G	0.022	0.054	0.45 (0.17–1.22)	0.12
C-C-C-C-G-A-G	0.013	0.028	0.67 (0.23–1.97)	0.47
T-C-T-C-A-C-G	0.009	0.013	0.98 (0.13–7.32)	0.98
T-C-C-C-G-A-A	0.016	0.009	1.84 (0.42–8.05)	0.42
Male
T-C-C-C-G-A-G	0.467	0.487	Reference
T-C-C-C-A-A-A	0.323	0.271	1.33 (0.86–2.05)	0.21‡
T-C-C-C-A-A-G	0.092	0.151	0.66 (0.37–1.19)	0.17
T-C-T-C-G-C-G	0.036	0.023	1.46 (0.47–4.51)	0.52
C-C-C-C-G-A-G	0.020	0.028	1.08 (0.35–3.35)	0.90
T-C-C-C-G-C-G	0.009	0.017	1.01 (0.23–4.47)	0.99

AOR: adjusted odds ratio; CI: confidence interval; ESCC: esophageal squamous cell cancer.

In the order of VEGF-417T/C,-172C/A,-165C/T,-160C/T,-152G/A,-141A/C,-116G/A.

†

Adjusted for age, gender, diet, smoking status and alcohol consumption.

‡

Adjusted for age, diet, smoking status and alcohol consumption statistically significant p values are displayed in bold.

Discussion

In the present case–control study, we investigated whether VEGF-417T/C, -172C/A, -165C/T, -160C/T, -152G/A, -141A/C, and -116G/A promoter polymorphisms are associated with ESCC risk in the North-West Indians. Till now, there is no published study on these seven polymorphisms in esophageal squamous cell cancer. There are very limited studies in different ethnic groups reporting the association of these seven VEGF promoter polymorphisms with GIT cancers (Supplementary Table 5). Till date, there are only three Indian studies on the investigated VEGF promoter polymorphisms (Table5).

Table5.

Key findings of VEGF promoter polymorphisms in ESCC, breast, gall bladder, and nonsmall cell lung cancer patients in North Indians

Polymorphism	ESCC (present study)	Breast cancer48	Gall bladder cancer21	Nonsmall cell lung cancer26
VEGF-417T/C	No association	No association	–	–
VEGF-172C/A	No association	No association	–	–
VEGF-165C/T	↓ risk with CT genotype and T allele in female group	↓ risk with CT genotype and T allele	–	–
VEGF-160C/T	No association	No association	–	–
VEGF-152G/A	↑ risk with AA genotype and A allele in total subjects as well as in female group	↑ risk with AA genotype and A allele	–	↑ risk with G allele
VEGF-141A/C	No association	↓ risk with AC genotype and C allele	–	–
VEGF-116G/A	↑ risk with AA genotype and A allele in total subjects as well as in female group	↑ risk with AA genotype and A allele	↑ risk with A allele	–
Linkage disequilibrium	-165C/T and -141A/C (D′ = 0.88, r² = 0.68); -152G/A and -116G/A (D′ = 0.93, r² = 0.49)	-165C/T and -141A/C polymorphisms (D′ = 1, r² = 0.7071)	–	–

ESCC: esophageal squamous cell cancer.

In this study, we found that VEGF-116 AA genotype (p = 0.002) and A allele (p = 0.001) were significantly associated with an increased risk of ESCC. The A allele of VEGF-116 G/A polymorphism has been reported to be associated with lower VEGF plasma levels as compared to the G allele.8,49 The findings of the present study are consistent with reports on some GIT cancers (Supplementary Table 5). VEGF-116 A allele has been reported to be associated with an increased risk for colorectal cancer in Korean males19 and with gall bladder cancer in the North Indians.21 Contrary to our results, the A allele of VEGF-116 G/A polymorphism was associated with a decreased risk to hepatocellular cancer in Chinese patients.23 The AA genotype was associated with larger tumor size and invasive characteristics in the Korean hepatocellular carcinoma patients50 and an increased risk of death in the Chinese hepatocellular carcinoma patients.51 No significant association was observed between VEGF-116G/A polymorphism and oral cancer in Caucasians,12 gastric cancer in Greek,14 colon cancer in Caucasians,15 colorectal cancer in Koreans,20 Greeks,17 and Swedish,18 and hepatocellular cancer in Chinese22 subjects.

Similarly, VEGF-152 AA genotype (p = 0.04) and A allele (p = 0.02) were significantly associated with increased esophageal cancer risk in the present study. There are very few studies reporting the association of VEGF-152G/A polymorphism with cancer. The association of VEGF-152GA and AA genotypes with higher VEGF mRNA levels has been reported in Japanese colorectal cancer patients.16 AA genotype of VEGF-152G/A polymorphism was associated with larger tumor size and poor overall survival in Korean hepatocellular patients.50

We did not observe any significant association of VEGF-417T/C, -172C/A, -165C/T, -160C/T, and -141A/C polymorphisms with ESCC. No association of VEGF-417T/C polymorphism with risk to colorectal cancer was observed in the Japanese patients.16 It has been predicted that VEGF-172A allele abolished the binding site of Sp1 transcription factor and created the binding of GATA-1 and GATA-2 transcription factors.48 Sp1 is a zinc finger transcription factor that binds to variety of gene promoters containing GC-rich motifs52 and has also been implicated in apoptosis.53 In the mouse model, it has been demonstrated that the GATA family members help in regulation of gene expression in hematopoietic cells.54 Hematopoietic cells are involved in tumor angiogenesis and regulate the angiogenic switch during tumorigenesis.55 No significant risk association of VEGF-141 A/C was reported in the present study. VEGF-141 A/C polymorphism was not associated with hepatocellular carcinoma in Turkish patients.24 The association of VEGF-141 A allele with increased risk to papillary thyroid carcinoma has been documented in Australian females.25 Our results on VEGF-417T/C, -172C/A, -165C/T, -160C/T, -152G/A, and -141A/C polymorphisms are concordant with other studies on other diseases apart from cancers (Table6).

Table6.

Published studies on the association of VEGF-417T/C, -172C/A, -165C/T, -160C/T, -152G/A, and -141A/C promoter polymorphisms with different diseases

Disease	Polymorphism	Population/ethnicity	Key findings	Reference
Age-related macular degeneration	-417T/C, -172C/A, -165C/T, -160C/T, -152G/A, -141A/C	European	No association	56
End stage renal disease	-417T/C, -152G/A	Japanese	No association	57
Diabetic retinopathy in Type 1 or Type 2 diabetes	-417T/C, -172C/A, -165C/T, -141A/C	European	No association	45
	-160C/T		↑ risk with CC genotype and C allele in proliferative diabetic retinopathy
	-152G/A		↑ risk with AA genotype and A allele in proliferative diabetic retinopathy
Diabetic retinopathy	-165C/T	Egyptian	No association	58
	-152G/A		↑ risk with GA genotype in nonproliferative diabetic retinopathy
Retinopathy of prematurity (ROP)	-165C/T	Chinese	↓ risk with TT+CT genotype in ROP regressive and ROP severe group	59
	-141A/C		No association
Coronary chronic total occlusions	-165C/T, -152G/A	Caucasian	No association	60
Psoriasis	-160C/T	Italian Caucasian	No association	61
	-152G/A		↑ risk with AA genotype
Diabetic retinopathy in Type 2 diabetes	-152G/A	Japanese	No association	62
	-152G/A	Chinese	↑ risk with A allele	63
	-152G/A	Chinese	↑ risk with AA genotype	64
	-152G/A	Pakistani	↑ risk with G allele in nonproliferative diabetic retinopathy	65
	-152G/A	South Indian	No association	66
Type 1 diabetes	-152G/A	Italian	↑ risk with AA genotype	67
	-152G/A	Finnish	↓ risk with GG genotype
Hypertension-related chronic kidney disease	-152G/A	Polish	No association	68
Essential hypertension	-152G/A	Italian	↓ risk with A allele	69
Steroid sensitive nephrotic syndrome	-141A/C	European	No association	70

In this study, a significant association of VEGF-152AA genotype (p = 0.005) and A allele (p = 0.003) and VEGF-116 AA genotype (p = 0.008) and A allele (p= 0.007) with increased risk of esophageal cancer was reported in the female subjects. CT genotype (p = 0.03) and T allele (p = 0.03) of VEGF-165C/T polymorphism were significantly associated with reduced risk for esophageal cancer in the female group. Similarly, we reported the association of AA genotype and A allele of VEGF-152G/A polymorphism and AA genotype and A allele of VEGF-116G/A polymorphism with increased risk of breast cancer, whereas CT genotype and T allele of VEGF-165 C/T polymorphism were associated with decreased risk of breast cancer in our previous study (Table5). Higher serum VEGF levels were reported in females as compared to the males in the Greek population.71 High estrogen levels in the female subjects might influence higher VEGF protein production, thus enhanced angiogenesis in the females.72,73

Body mass index (BMI)-based stratification analysis revealed significant association of AA genotype (p = 0.007) and A allele (p = 0.01) of VEGF-152G/A and A allele (p = 0.006) of VEGF-116G/A polymorphism with an increased risk to esophageal cancer in nonobese patients (Supplementary Table 2). A study from Spain reported elevated VEGF plasma level in obese patients.74 Increased VEGF protein levels have also been reported in postmenopausal obese mice.75 It has been reported that fat cells in the obese or overweight individuals affect angiogenesis response in individuals.76

A LD was observed between VEGF-165C/T and VEGF-141A/C (D′ = 0.88, r² = 0.68) and between VEGF-152G/A and VEGF-116G/A (D′ = 0.93, r² = 0.49) polymorphisms in the present study. Strong LD between VEGF-165C/T and -141A/C polymorphisms (D′ = 1.0, r² = 0.70) has been reported in our previous study on breast cancer patients from the same population (Table5). Haplotype analysis is a better approach for the prediction of disease risk as compared to single/double or the triple polymorphism approach. In the present study, T-C-C-C-A-A-A haplotype of VEGF-417T/C, -172C/A, -165C/T, -160C/T, -152G/A, -141A/C, and -116G/A polymorphisms was significantly associated with increased ESCC risk in the total patients (p = 0.01) as well as in the female group 6 (p = 0.02). The association of VEGF-2578C/-165C/-152G/-141A/-116G/-634C/-7C/+936C haplotype with smaller tumor size has been reported in Korean hepatocellular carcinoma patients.50 Apart from cancers, significant association ofhaplotype T-T-C-C-C-G-A-A-C of VEGF-460T/C, -417T/C, -172C/A, -165T/C, -160C/T, -152G/A, -141A/C, -116G/A, and +405G/C polymorphisms with increased susceptibility to develop age-related macular degeneration has been reported in Europeans.56 In other study, haplotype C-T-C-C-C-A-A-A-C of VEGF-460T/C, -417T/C, -172C/A, -165T/C, -160C/T, -152G/A, -141A/C, -116G/A, and +405G/C was significantly associated with Type 1 or 2 diabetes with proliferative diabetic retinopathy, whereas haplotype C-T-C-C-C-A-A-G-G was significantly associated with Type 1 or 2 diabetes without retinopathy in Europeans.45

Till date, nine genome-wide association studies have been conducted in ESCC and identified several disease susceptibility loci on different chromosomes (Supplementary Table 6). The association of PLCE1 variants with increased risk of ESCC has been reported in three studies.77 –79 It has been reported that PLCE1 regulates angiogenesis and proliferation in ESCC via NF-κB signaling pathway.80 About 79% of the patients in the present study belong to rural areas and were involved in agricultural activities with self-reported exposure to agricultural chemicals and pesticides. Pesticide exposure has been linked to an increased risk to EC in various studies.81 –83 Pesticide exposure has also been shown to stimulate angiogenesis in invitro and invivo studies.84,85 In the present study, 62.07% of the ESCC patients were more than 50 years old. It has been documented that age-associated changes in the cellular microenvironment are required for the proliferation of transformed cells leading to malignancy.86

The correlation of VEGF-417T/C, -165C/T, -152G/A, -141A/C, and -116G/A promoter polymorphisms with response to different therapy regimens has been studied in GIT cancers (Supplementary Table 7). The treatment response or treatment failure among different population groups depends upon the presence of particular variant of VEGF polymorphisms. Identification of correlation between VEGF polymorphisms and their haplotypes with particular therapy may be helpful in better selection of patients for treatment.

Conclusions

This study findings concluded that VEGF-116 G/A and VEGF-152G/A polymorphisms were significantly associated with increased ESCC risk in total patients as well as in the female group, whereas VEGF-165 C/T polymorphism was associated with reduced risk only in the female group.

Authorship Contribution Statement: K.G. and V.S. designed the study. D.M. and K.G. performed the experiments. D.M. and K.G. analyzed the data and prepared the manuscript. M.S. and M.S.U. performed clinical diagnosis of patients and also helped in collection of blood samples of patients. All authors read and approved the manuscript.

Authors’ Disclosure Statement: All authors declare that they have no competing interests.

Funding Statement: This study was financially supported by the MHRD grant under RUSA 2.0 scheme.

Footnotes

Acknowledgments

We are thankful to the study subjects who participated in this study. A part of data has been presented in the conference, and abstract has been published in Annals of Oncology 34: S143. DOI: .

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Supplementary Material

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Association of Vascular Endothelial Growth Factor Gene Polymorphisms with Esophageal Squamous Cell Cancer Risk in North-West Indians: A Case–Control Study

Abstract

Abstract

Background:

Methodology:

Results:

Conclusion:

Introduction

Materials and Methods

Selection of study participants and collection of blood samples

Genotyping of VEGF promoter polymorphisms

Statistical analysis

Results

Characteristics of the ESCC patients and healthy controls

Association of VEGF promoter polymorphisms with ESCC risk in total patients

Gender wise stratification of VEGF promoter polymorphisms and ESCC risk

Age wise stratification of VEGF promoter polymorphisms and ESCC risk

Stratification of the data based on body mass index

Genotype combinations of VEGF promoter polymorphisms and ESCC risk

Linkage disequilibrium and haplotype analysis

Discussion

Conclusions

Footnotes

Acknowledgments

References

Supplementary Material