Abstract
Background:
The carcinogenesis process in esophageal cancer (EC), a highly heterogeneous and multifaceted disease, is influenced by both tumor angiogenesis and chronic inflammation pathways. Genetic variants in these pathways may affect the progression and development of EC, ultimately contributing to different susceptibilities to cancer among individuals.
Methods:
In this study, a total of 536 subjects were recruited, including 260 EC patients and 276 healthy individuals. The DNA was isolated from the blood samples of the participants using the standard phenol-chloroform method. The three insertion/deletion (ins/del) polymorphisms (VEGF-2549 18bp I/D, MDM2 40bp I/D, and MCP-1 14bp I/D) were screened using the Direct-polymerase chain reaction (PCR) genotyping method. The role of gene-environment interactions on EC risk was assessed using the Multifactor Dimensionality Reduction (MDR) software (version 3.0.2).
Results:
It was observed that the individuals carrying the II genotype and I allele of the VEGF-2549 18bp I/D polymorphism, as well as the carriers of the ID and DD genotypes and D allele of the MCP-1 14bp I/D polymorphism had a higher risk of developing EC. No association between the MDM2 40bp I/D polymorphism and EC risk was reported in this study. Genotype combination analysis revealed an increased EC risk in the carriers of the II-II-II genotype combination of the VEGF-2549 18bp I/D, MDM2 40bp I/D, and MCP-1 14bp I/D polymorphisms compared to those with other genotype combinations. The gene-environment interaction analysis also indicated a strong interaction between lifestyle factors and genetic polymorphisms in influencing EC risk.
Conclusion:
The present study concluded that the VEGF-2549 18bp I/D and MCP-1 14bp I/D variants were associated with EC risk in the North-west Indians.
Key Words: Esophageal, Cancer, Polymorphism, Angiogenesis, Inflammation, VEGF, MCP-1, MDM2
Introduction
The tumour development is a highly regulated multistep process accompanied by aberrant genetic, epigenetic and environmental changes. These molecular and environmental stresses transform normal healthy cells into rapidly dividing highly heterogeneous malignant cells [1]. Among the various hallmarks of cancer, sustained angiogenesis is recognised as the most important process for metastatic spread and local invasion of the tumour cells. The VEGF protein regulates the process of “angiogenic switch” in the tumour cells and also helps in the formation of new blood vasculature required for controlling the oxygen and nutrient demands of growing tumour cells [2,3]. The rapid hyper-proliferation of the tumour cells creates a severe hypoxic microenvironment [4]. Hypoxia induces the stabilization of the HIF1α protein which further promotes the enhanced transcription of the VEGF mRNA [5,6]. The upregulated VEGF protein interacts with the VEGFR2 receptor and promotes the molecular and biological processes required for tumour angiogenesis [7].
MDM2 and MCP-1 proteins also influence VEGF-induced tumour angiogenesis. MDM2 is an oncogenic protein that regulates hypoxia-dependent VEGF expression. It has been reported that along with cellular stresses, environmental stresses such as hypoxia also stimulate MDM2 overexpression [8]. In hypoxic conditions inside the tumour cells, the MDM2 protein interacts with the 3’ untranslated region (UTR) of the VEGF mRNA, stabilizes the VEGF mRNA, regulates VEGF translation and upregulates its expression [9]. It has been reported that the MDM2 protein also inhibits the production of anti-angiogenic factors, further promoting tumour angiogenesis [10].
It has been documented that chronic inflammation plays a vital role in tumour development and progression [11]. The MCP-1 (CCL2) chemokine, a crucial mediator of chronic inflammation, promotes monocyte recruitment and activation [12], secretes monocyte-mediated proinflammatory signals [13] and influence tumour growth, metastasis and angiogenesis [14]. It has been reported that the secretion of high MCP-1 levels by the tumour cells and tumour-infiltrating monocytes, further increases VEGF expression and promotes angiogenesis [15]. In-vitro studies have also documented a strong correlation between high levels of VEGF and increased MCP-1 mRNA expression in the endothelial cells [16]. It has been reported that the hypoxia-inducible factor-1α (HIF-1α) also plays a role in stimulating VEGF and MCP-1-mediated angiogenesis [15].
Esophageal cancer (EC) is a highly heterogeneous tumour, characterized by its aggressive nature and poor survival. Previous studies have documented the relationship between VEGF, MCP-1 and MDM2 overexpression with lymph node metastasis, tumour invasion, distant metastasis, and poor prognosis in EC [17-20]. Since hypoxia has been reported as a major regulator of VEGF, MDM2 and MCP-1 expression, the interplay between these proteins might play an important role in EC development.
Genetic variability is responsible for inter-individual variation in predisposition towards different cancers. Among the various forms of genetic variability, small ins/del (I/D) polymorphisms represent humans’ most common form of genetic variation [21]. It has been reported that I/D polymorphisms impact key biological processes in humans and are also implicated in the pathogenesis of several diseases. Functional I/D polymorphisms are known to influence gene function [22]. It has been documented that the I/D polymorphisms located in the promoter region affect gene expression variability among humans. The two important I/D polymorphisms located in the promoter region are VEGF-2549 18bpI/D (rs35569394) and MDM2 40bpI/D (rs3730485) polymorphism. The VEGF-2549I/D polymorphism is an 18bp I/D polymorphism located at -2549 upstream of the VEGF promoter. It has been reported that the VEGF-2549 18bp I/D polymorphism influences the VEGF promoter activity as well as VEGF protein production [23,24]. The MDM2 40bpI/D polymorphism is a 40bp I/D polymorphism, situated at the -1518 position upstream of the constitutive P1 promoter [25, 26] of the gene. Association of MDM2 40bp I/D polymorphism with altered transcriptional activity been previously reported in in-vitro analysis [27]. The role of VEGF-254918bp I/D polymorphism in influencing cancer susceptibility has been studied in various gastrointestinal tract (GIT) cancers including esophageal [28], gastric [29], hepatocellular [30], gall bladder [31] and colorectal cancer [32]. The MDM2 40bp I/D polymorphism has been studied in GIT cancers including esophageal [33-35], gastric [33, 36], hepatocellular [37], colon [38] and colorectal [36] cancer.
The MCP-1 14bp I/D polymorphism is a 14bp I/D polymorphism (rs3917887) present in intron 1 (int1del554-567) of the MCP-1 [39]. Polymorphisms located in the intronic regions of the gene might also affect gene expression levels by affecting the splicing process [40]. Till now, the relationship between MCP-1 14bp I/D polymorphism and cancer susceptibility has been reported from India in the prostate [41] and bladder cancer patients [42].
The process of angiogenesis and inflammation, both play a crucial role in EC development. The variants in the genes involved in these pathways might deregulate cellular homeostasis, and promote tumour development and progression. Therefore, the present study aims to study the role of three I/D polymorphisms (VEGF-2549 18bpI/D, MDM2 40bpI/D and MCP-1 14bp I/D) in influencing EC risk in patients from Punjab, North-West India. The present study is the first reported study to evaluate the combined role of three I/D polymorphisms of MCP-1, VEGF and MDM2 in EC in North-West Indians.
Materials and Methods
Study Type, Sample Collection and DNA Extraction
From January 2021 to December 2023, two hundred and sixty clinically and histologically confirmed EC patients who were referred at Sri Guru Ram Das Institute of Medical Sciences, Amritsar, Punjab, India were recruited in this study. The included patients were sporadic cancer patients who had not received any medical treatment, were not on blood transfusion and were not suffering from any other chronic disease. At the same time, 276 healthy cancer-free controls were recruited in this study. The inclusion criteria for the controls were age, gender, habitat and ethnicity-matched unrelated healthy individuals, free from any chronic disease and not having any family history of any cancer. All the study participants belonged to the Amritsar district of Punjab state or its surrounding areas. The study was constructed following Helsinki Declaration guidelines and the institutional ethics committee of Guru Nanak Dev University, Amritsar approved the study protocol. Before collecting the blood samples, written consent was obtained from all the study participants. The demographic and the clinical details of each study participant were recorded on the pre-designed proforma. In a sterilized EDTA-coated vial, 5ml venous blood sample was collected from each study participant by the trained personnel using sterilized disposable syringes. The collected blood samples were transferred to the laboratory and were stored at -20°C till further use. Isolation of the genomic DNA from the peripheral blood samples was done using the standard phenol-chloroform method [43]. The quality and quality of the DNA samples were checked on 1% agarose gel.
Genotyping of Polymorphisms
Genotyping of VEGF-254918bpI/D (rs35569394), MDM2 40bpI/D (rs3730485) and MCP-1 14bpI/D (rs3917887) polymorphisms was done using the Direct-PCR technique. The targeted region of the studied polymorphisms was amplified using previously published primer sequences [44-46]. The PCR amplification was carried out using 1 µl of 10X Taq buffer with 15mM MgCl2, 0.4 µl of dNTP’s mix, 0.4µl of forward and reverse primer (10pmoles/microlitre), 0.9 U of Taq polymerase and 50ng DNA in a 10 µl reaction volume.
The amplification was carried out in T100 thermal cycler (Biorad) at initial denaturation 95°C for 5 minutes, followed by 35 cycles of denaturation at 95°C for 45 seconds, annealing for VEGF-254918bpI/D, MDM2 40bpI/D, and MCP-114bpI/D polymorphisms were 55°C, 58°C and 56°C respectively and extension at 72°C for 45 seconds and final extension at 72°C for 10 minutes. The PCR products were separated on 2.6% agarose gel and visualized under the UV transilluminator. Genotyping was performed based on the amplicon sizes: VEGF-2549 18bp I/D (I allele-229 bp; D allele-211bp), MDM2 40bpI/D (I allele-287bp; D allele-247bp) and MCP-114bpI/D (I allele-195bp; D allele-181 bp). The 10% of the results were validated by Sanger sequencing and 100% concordance was observed (Figure 1).
Figure 1.
The Gel Photograph and Electropherograms Showing Different Genotypes of VEGF -2549 18bp I/D (A), MDM2 40bp I/D (B) and MCP-1 14bp I/D (C) Polymorphisms
Statistical analysis
The deviation from the Hardy-Weinberg equilibrium (HWE) in control subjects was calculated using the Chi-square test. A p-value of >0.05 was considered statistically significant. The association between the polymorphisms and EC risk was studied by calculating the Odds ratio (OR) and its 95% Confidence Intervals (CI) using the MedCalc software. The genetic model analysis was performed using the online SNPstats software [47]. The results were considered significant if the p-value was less than 0.05.
The Multifactor dimensionality reduction (MDR) (version 3.0.2) software was used to study the overall impact of various interactions between the studied polymorphisms and confounding factors like gender, smoking status, diet and alcohol consumption on EC risk. The model with the maximum testing accuracy, training accuracy and cross-validation consistency was considered the best-studied model compared with other tested SNP models. The synergistic role of the polymorphisms and various confounding factors was examined by the construction of a circle graph based on the interaction entropy model.
Results
Demographic and Clinical Characteristics of the Study Participants
The present case-control study enrolled 260 sporadic EC patients (119 males and 141 females) and 276 healthy age and gender-matched subjects (134 males and 142 females). The mean age of the patients and controls were 56.58±13.24 and 54.03±15.59 years respectively. Of all the patients, 62.3% were older than 50 years. The majority of the EC patients (77.7%) lived in the rural areas of Punjab. There was a higher frequency of vegetarians as compared to non-vegetarians in both EC patients and controls. The frequency of smokers was higher in males EC patients than the male controls. Among patients, majority of the males were farmers, involved in agriculture-related activities or were labourers, whereas females were mostly housewives. Among 141 EC females, 79.4% were postmenopausal whereas 20.6% were pre-menopausal. In this study, squamous cell carcinoma was the most common histological subtype (88.1%), with the majority of the patients having stage II tumours (38.1%). The demographic and clinical characteristics of the study participants have been mentioned in Supplementary Table 1.
Association of VEGF-254918bpI/D Polymorphism with EC Risk
The genotype distribution of the VEGF-254918bp I/D polymorphism was in agreement with HWE in the control group (p=0.09). In the total subjects, it was observed that the individuals carrying the II genotype (OR=1.73, 95%CI=1.03-2.91; p=0.04) and I allele (OR=1.28, 95%CI=1.00-1.62; p=0.04) of VEGF-2549 18bpI/D polymorphism were more susceptible to EC development (Table 1). The genetic model analysis also revealed a higher predisposition toward EC development under the log-additive genetic model (OR=1.31, 95%CI=1.02-1.69; p=0.04) of VEGF-2549 18bp I/D polymorphism (Supplementary Table 2).
Table 1.
Association of VEGF-254918bpI/D, MDM2 40bp I/D and MCP-1 14bpI/D Polymorphism with EC Risk
| Total =536 | Females=283 | Males=253 | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Genotype/Allele | Patients | Controls | OR(95%CI) | p-value | Patients | Controls | OR(95%CI) | p-value | Patients | Controls | OR(95%CI) | p-value |
| n (%) | n (%) | n (%) | n (%) | n (%) | n (%) | |||||||
| VEGF-254918bp I/D (rs35569394) | ||||||||||||
| DD | 65 (25.0) | 87 (31.5) | Reference | 31 (22.0) | 41 (28.9) | Reference | 34 (28.6) | 46 (34.3) | Reference | |||
| ID | 142 (54.6) | 148 (53.6) | 1.28(0.86-1.91) | 0.21 | 78 (55.3) | 82 (57.8) | 1.25 (0.72-2.20) | 0.42 | 64 (53.8) | 66 (49.2) | 1.32 (0.75-2.30) | 0.34 |
| II | 53 (20.4) | 41 (14.9) | 1.73(1.03-2.91) | 0.04 | 32 (22.7) | 19 (13.4) | 2.23 (1.07-4.64) | 0.03 | 21 (17.6) | 22 (16.4) | 1.29 (0.61-2.71) | 0.5 |
| D | 272 (52.3) | 322 (58.3) | Reference | 140 (49.6) | 164 (57.7) | Reference | 132 (55.5) | 158 (59.0) | Reference | |||
| I | 248 (47.7) | 230 (41.7) | 1.28(1.00-1.62) | 0.04 | 142 (50.4) | 120 (42.3) | 1.39 (0.99-1.94) | 0.05 | 106 (44.5) | 110 (41.0) | 1.15 (0.81-1.64) | 0.43 |
| MDM2 40bpI/D (rs3730485) | ||||||||||||
| II | 155 (59.6) | 160 (58.0) | Reference | 87 (61.7) | 82 (57.8) | Reference | 68 (57.1) | 78 (58.2) | Reference | |||
| ID | 92 (35.4) | 104 (37.7) | 0.91(0.64-1.30) | 0.62 | 49 (34.8) | 51 (35.9) | 0.91 (0.55-1.49) | 0.69 | 43 (36.1) | 53 (39.5) | 0.93 (0.55-1.56) | 0.78 |
| DD | 13 (5.0) | 12 (4.3) | 1.12(0.49-2.53) | 0.79 | 5 (3.5) | 9 (6.3) | 0.52 (0.17-1.63) | 0.26 | 8 (6.7) | 3 (2.2) | - | |
| I | 402 (77.3) | 424 (76.8) | Reference | 223 (79.1) | 215 (75.7) | Reference | 179 (75.2) | 209 (78.0) | Reference | |||
| D | 118 (22.7) | 128 (23.2) | 0.97(0.73-1.29) | 0.85 | 59 (20.9) | 69 (24.3) | 0.82 (0.55-1.22) | 0.34 | 59 (24.8) | 59 (22.0) | 1.17 (0.77-1.76) | 0.46 |
| MCP1 14bp I/D(rs3917887) | ||||||||||||
| II | 117 (45.0) | 157 (56.9) | Reference | 65 (46.1) | 85 (59.9) | Reference | 52 (43.7) | 72 (53.7) | Reference | |||
| ID | 118 (45.4) | 105 (38.0) | 1.51(1.06-2.15) | 0.02 | 66 (46.8) | 48 (33.8) | 1.80 (1.10-2.94) | 0.02 | 52 (43.7) | 57 (42.5) | 1.26 (0.75-2.12) | 0.37 |
| DD | 25 (9.6) | 14 (5.1) | 2.40(1.19-4.81) | 0.01 | 10 (7.1) | 9 (6.3) | 1.45 (0.56-3.78) | 0.44 | 15 (12.6) | 5 (30.6) | 4.15 (1.42-12.14) | 0.009 |
| I | 352 (67.7) | 419 (75.9) | Reference | 196 (69.5) | 218 (76.8) | Reference | 156 (65.5) | 201 (75.0) | Reference | |||
| D | 168 (32.3) | 133 (24.1) | 1.50(1.15-1.97) | 0.003 | 86 (30.5) | 66 (23.2) | 1.45 (0.99-2.11) | 0.05 | 82 (34.5) | 67 (25.0) | 1.58 (1.07-2.32) | 0.02 |
OR, Odds Ratio; CI,Confidence Interval; p, probability value; significant p values are displayed in bold
The data was stratified based on the gender and female-specific association was observed. The II genotype (OR=2.23, 95%CI=1.07-4.64; p=0.03) was associated with a higher risk of EC in females subjects only (Table 1). The VEGF-2549 18bp I/D polymorphism was associated with higher EC risk under the recessive (p=0.04) and log-additive (p=0.04) genetic model in female group (Supplementary Table 2). No genotype was associated with EC risk in male group (p>0.05) (Table 1 and Supplementary Table 2). Age-wise stratification analysis also did not reveal any association between VEGF-2549 18bp I/D polymorphism and EC risk (Supplementary Table 3).
Association of MDM2 40bpI/D Polymorphism with EC Risk
The genotype distribution of the MDM2 40bpI/D polymorphism was in agreement with HWE in the control group (p=0.34). There was no association of MDM2 40bp I/D polymorphism with EC risk in the total, males and females subjects (Table 1 and Supplementary Table 2). The data was further stratified based on the age of the EC patients and no association was observed (p>0.05) (Supplementary Table 3).
Association of MCP-1 14bpI/D Polymorphism with EC Risk
The genotype distribution of MCP-1 14bpI/D polymorphism was in agreement with the HWE in the control group (p=0.51). In the total subjects, the carriers of the ID (OR=1.51, 95%CI=1.06-2.15; p=0.02), DD genotype (OR=2.40, 95%CI=1.19-4.81; p=0.01) and D allele (OR=1.50, 95%CI=1.15-1.97; p=0.003) were more susceptible towards EC development (Table 1). Genetic model analysis revealed a significantly higher EC risk under dominant (p=0.006), recessive (p=0.04) and log-additive model (p=0.002) (Supplementary Table 2).
In female group, increased EC risk was observed with the ID genotype (OR=1.80, 95%CI=1.10-2.94; p=0.02) (Table 1). The MCP-1 14bp I/D polymorphism was associated with higher EC risk in females under the dominant (p=0.02), overdominant (p=0.03) and log-additive genetic model (p=0.04) (Supplementary Table 2).
In males, carriers of the DD genotype (OR=4.15, 95%CI=1.42-12.14; p=0.009) and D allele (OR=1.58, 95%CI=1.07-2.32; p=0.02) were more susceptible towards EC development (Table 1). Genetic model analysis revealed an increased EC risk under the recessive (p=0.008) and log-additive genetic model (p=0.02) (Supplementary Table 2). The genotype data was stratified based on the age at diagnosis of EC patients and no association was observed (p>0.05) (Supplementary Table 3).
Interaction Analysis
To study the combined impact of VEGF-2549 18bp I/D, MDM2 40bp I/D and MCP-1 14bp I/D polymorphisms on EC risk, different genotype combinations were prepared. It was observed that the carriers of II-II-II genotype combination of the VEGF-2549 18bpI/D, MDM2 40bp I/D and MCP-1 14bp I/D polymorphisms had a three-fold higher risk of EC (OR=3.04, 95%CI=1.12-8.27; p=0.03) as compared to the carriers of the other genotype combinations (Table 2).
Table 2.
Genotype Combinations of VEGF-2549 18bpI/D, MDM2 40bp I/D and MCP-1 14bp I/D Polymorphisms and EC Risk
| Genotype Combination | Patients n | Controls n | OR (95%CI) | p-value |
|---|---|---|---|---|
| VEGF-2549 18bpI/D-MDM2 40bpI/D-MCP1 14bpI/D | ||||
| DD-II-II | 15 | 24 | Reference | |
| DD-ID-ID | 10 | 12 | 1.33 (0.46-3.84) | 0.59 |
| DD-ID-II | 11 | 25 | 0.70 (0.27-1.84) | 0.47 |
| DD-II-ID | 20 | 14 | 2.29 (0.89-5.85) | 0.08 |
| ID-ID-ID | 22 | 23 | 1.53 (0.64-3.65) | 0.34 |
| ID-ID-II | 25 | 22 | 1.82 (0.77-4.31) | 0.17 |
| ID-II-DD | 9 | 5 | 2.88 (0.81-10.25) | 0.1 |
| ID-II-ID | 38 | 32 | 1.90 (0.86-4.22) | 0.12 |
| ID-II-II | 33 | 62 | 0.85 (0.39-1.84) | 0.68 |
| II-ID-ID | 6 | 9 | 1.07 (0.32-3.61) | 0.92 |
| II-ID-II | 12 | 10 | 1.92 (0.67-5.53) | 0.23 |
| II-II-ID | 14 | 9 | 2.49(0.86-7.16) | 0.09 |
| II-II-II | 19 | 10 | 3.04 (1.12-8.27) | 0.03 |
OR, Odds Ratio; CI, Confidence Interval; significant p-values are displayed in bold
Gene-Environment Interactions
The interaction between the VEGF-2549 18bpI/D, MDM2 40bp I/D and MCP-1 14bp I/D polymorphisms and confounding factors including gender, diet, alcohol and smoking in determining EC risk was studied. It was observed that the training balance accuracy was highest in the seven-locus model (VEGF-2549 18bpI/D, MDM2 40bpI/D, MCP 14bp I/D, gender, diet, alcohol, smoking). The testing balance accuracy was highest in the six-locus model (VEGF-2549 18bpI/D, MDM2 40bp I/D, MCP-1 14bp I/D, gender, diet and smoking), suggesting that this model was the best-predicted model for studying the interaction between polymorphisms and lifestyle factors on EC risk and development. All the studied models were statistically significant (p<0.05) (Table 3).
Table 3.
Gene-Environment Interaction Model
| Model | Training balanced Accuracy | Testing balance Accuracy | Cross-validation consistency | OR (95%CI) | p-value |
|---|---|---|---|---|---|
| MCPI/D | 0.5599 | 0.5468 | 9/10 | 1.61 (1.14-2.27) | 0.006 |
| MCPI/D, Smoking | 0.5857 | 0.5396 | 5/10 | 1.97 (1.40-2.78) | 0.0001 |
| Gender, Diet, Smoking | 0.6204 | 0.574 | 7/10 | 2.99 (2.05-4.36) | <0.0001 |
| VEGF-2549I/D,MDM2I/D,MCPI/D, Diet | 0.6539 | 0.5451 | 8/10 | 3.37 (2.36-4.80) | <0.0001 |
| VEGF-2549I/D,MDM2I/D,MCPI/D, Gender, Diet | 0.705 | 0.5759 | 10/10 | 5.41 (3.74-7.83) | <0.0001 |
| VEGF-2549I/D,MDM2I/D,MCPI/D, Gender, Diet, Smoking | 0.74 | 0.606 | 10/10 | 7.69 (5.24-11.30) | <0.0001 |
| VEGF-2549I/D,MDM2I/D,MCPI/D, Gender, Diet, Alcohol, Smoking | 0.7498 | 0.6052 | 10/10 | 8.5 (5.76-12.54) | <0.0001 |
OR, Odds Ratio; CI, Confidence Interval; significant p-values are displayed in bold
The circle graph was constructed and it showed that the MCP-1 14bp I/D polymorphism had the highest entropy (1.25%), contributing the maximum to the development of EC. Also, the interaction entropy model suggested a moderate interaction between the VEGF-2549 18bpI/D and MDM2 40bp I/D polymorphism in determining the EC risk (0.56%) (Figure 2).
Figure 2.
The Circle Graph Depicting the Interaction Entropy Model of EC Patients and Controls, The Degree of Interaction Represented by Different Colours: orange (moderate interaction), green (weak interaction), blue (redundancy), gold (midway interaction between synergy and redundancy
Discussion
The tumour-induced angiogenesis and chronic inflammation play a key role in EC development. In EC, angiogenesis is a prerequisite for the invasion and metastatic growth of the tumour [48]. Esophageal injury caused by environmental exposures induces chronic inflammation in esophageal tissues [49]. This esophageal damage further induces DNA damage and creates genomic instability in the esophageal tissues [50]. Chronic inflammation has been known to promote hypoxic conditions inside the tumour and further influences tumour growth, development and angiogenesis [51]. Genetic variants in the multiple low penetrant susceptibility genes and environmental risk factors influence the development of cancers. Variants in the genes involved in the angiogenesis and chronic inflammation pathways might impact the inter-individual variability in cancer development and progression.
In the present study, it was observed that the II genotype and I allele of VEGF-2549 18bp I/D polymorphism and ID, DD genotype and D allele of MCP-1 14bpI/D polymorphism were associated with a higher risk of EC, whereas MDM2 40bp I/D polymorphism was not associated with risk of EC in the studied population. In-vitro functional analysis has reported a correlation between the II genotype of VEGF-2549I/D polymorphism with enhanced VEGF production [24, 52]. The D allele of the MDM2 40bp I/D polymorphism has also been associated with reduced MDM2 expression in cell lines [27]. The role of MCP-1 14bp I/D intronic polymorphism on the transcriptional activity of the gene has been reported in earlier study [53]. In-vitro study has reported that MCP-1 -362C/int1del554-567 Del combination was associated with low MCP-1 expression [54]. The genetic variability in the VEGF, MDM2 and MCP-1 genes might affect the regular cellular functions and foster inter-individual susceptibility to EC development.
Several case-control studies in different ethnic populations have evaluated the role of VEGF-2549I/D polymorphism with EC susceptibility with inconsistent results. The DD genotype and D allele of VEGF-2549 18bp I/D polymorphism has been associated with higher EC risk in the total subjects as well as in female group [28]. Apart from EC, the association of VEGF-2549 18bp I/D polymorphism with the risk of other GIT cancers have been studied in different populations. The ID, II genotypes and I allele were associated with higher gastric cancer risk in the South-Indians [29]. The VEGF-2549I/D polymorphism was not associated with gall bladder cancer risk in North Indians [31], hepatocellular cancer risk in Han Chinese [30] and colorectal cancer risk in the Swedish population [32]
Similar to our results, no association of MDM2 40bp I/D polymorphism has been reported with EC risk in the Chinese population [33-35]. The ID and DD genotypes were associated with lower gastric cancer risk [33] and higher hepatocellular cancer risk [37] in the Chinese population. The II genotype was only associated with lower gastric cancer risk [36] but not with colorectal cancer risk in Brazilians [36]. The association of the D allele with an increased risk of colon cancer has been reported in the Norwegian population [38].
In our study, ID, DD genotype and D allele of MCP-1 14bp I/D polymorphism were associated with elevated EC risk in North- Indians. The ID genotype and combined ID+DD genotypes were associated with a higher risk of prostate [41] and bladder cancer [42] in the North Indians. Interaction analysis revealed that the II-II-II genotype combinations of the VEGF-2549 18bp I/D, MDM2 40bp I/D and MCP-1 14bp I/D were associated with higher EC risk. Although MDM2 alone was not associated with EC risk in the overall analysis, the interaction analysis suggested that MDM2 I/D polymorphisms might influence EC development in interaction with other polymorphisms. Gene-environment interaction analysis revealed the importance of lifestyle factors in the development of EC. It was revealed in our study that lifestyle factors exhibited strong interactions with other genetic factors in determining EC risk. This is evidenced in a study by Zhai et al. which reported the role of VEGF-460T/C polymorphism in influencing EC risk based on the smoking status of the study participants [55].
The variants in these genes affect the clinical response and prognosis of the cancer patients. It has been reported that the DD genotype of VEGF-2549 18bp I/D polymorphism has been linked with complete or partial response to chemotherapy in the Chinese EC patients [28] and associated with better treatment response and longer progression free survival in colorectal Caucasian patients [56]. The association of MDM2 40bp I/D polymorphism with clinical features and therapy response was studied in Sudanese chronic lymphocytic leukemia patients, but no association was reported [57]. Every cancer patient responds differently to cancer treatment, therefore the variants in these genes could help in early selection of the patients more likely to benefit from a particular treatment plan.
In conclusions, the main limitation of the present case-control study was its limited sample size. Stratification analysis could not be performed because of the limited data on the confounding factors. The present study did not evaluate the functional role of the polymorphisms in influencing EC risk. Understanding the role of other functional polymorphisms in the studied genes will be beneficial in studying the pathology behind EC development and in designing individualized treatment therapies for the EC patients. As India is home to several ethnic groups and different socioeconomic traditions, the impact of the studied polymorphisms on EC risk must be validated in other ethnic groups as well to provide nationwide-based findings.
Author Contribution Statement
KG and VS designed the study. DM performed the experiments. DM and KG analyzed the data and prepared the manuscript. MS and MSU did clinical diagnosis of patients and also helped in collection of blood samples of patients. All authors read and approved the manuscript.
Acknowledgements
We thank the study participants for taking part in the present study.
Ethical Clearance
This work was approved by Institutional Ethics Committee of Guru Nanak Dev University, Amritsar and some part of this work is a part of Ph.D thesis.
Availability of data and materials
All data relevant to this study has been included in the manuscript or uploaded as supplementary information
Conflict of interest
The authors declare that they have no conflict of interest
Supplementary information
References
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