HLA-G High-expressor 3’UTR Markers Are Linked to Gastric Cancer Development and Survival

doi:10.21203/rs.3.rs-4437900/v1

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HLA-G High-expressor 3’UTR Markers Are Linked to Gastric Cancer Development and Survival

https://doi.org/10.21203/rs.3.rs-4437900/v1

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Gastric cancer ranks fifth in both world prevalence and lethality, with a 5-year survival of less than 30%. HLA-G, a non-classical class I HLA gene, has emerged as a potential marker for cancer susceptibility and prognosis due to its immunomodulatory properties. Its level of expression is regulated by polymorphisms in the 3’ untranslated region (3’UTR) polymorphisms, which form various combined haplotypes (UTR-1 to -9).

In this study, we examined HLA-G 3’UTR polymorphisms in paired tissue samples from 111 patients with gastric adenocarcinoma and 119 healthy controls. Polymorphism analysis was performed using PCR and Sanger sequencing, followed by statistical analysis using SNPStats software. Survival analysis was conducted using Kaplan-Meier curves and multivariate Cox regression models.

High-expressor HLA-G 3’UTR haplotypes (UTR-1 and UTR-6) were significantly associated with gastric cancer susceptibility, indicating a potential role in tumor immune evasion. Additionally, the 14 base pair insertion/deletion polymorphism (14bp I/D) emerged as a prognostic marker, with D/D genotype carriers showing lower survival rates compared to I/D and I/I genotype carriers.

Our study highlights the clinical relevance of HLA-G polymorphisms in gastric cancer, suggesting their potential as prognostic markers and therapeutic targets. Further elucidation of HLA-G-related pathways could lead to personalized treatment strategies and improved patient outcomes in gastric cancer.

Gastric cancer ranks as the fifth most prevalent cancer worldwide, exhibiting an annual incidence of 11.1 new cases per 100,000 individuals. Furthermore, it stands as the 5th most lethal cancer, with 7.7 deaths per 100,000 individuals annually, underscoring its aggressive nature. The 5-year survival rate for this cancer subtype remains at 29.5%, persisting over the past three decades (1, 2).

HLA-G, a non-classical class I HLA gene, encodes molecules with tolerogenic properties. The HLA-G gene comprises 7 introns and 8 exons, and exon 8 constitutes an untranslated region (3'UTR) with regulatory properties (3). Specific polymorphic sites within the 3'UTR region, such as the 14 base pair (14bp) INS/DEL (I/D), + 3142C/G, and + 3187A/G polymorphisms, influence mRNA stability and HLA-G expression levels. These polymorphisms can give rise to extended haplotypes (denoted as UTR-1 to UTR-7), which either upregulate (UTR-1 or UTR-6) or downregulate (UTR-2 or UTR-5) HLA-G expression (4).

Previous research has documented HLA-G expression in gastric tumors (5). Thus, investigating polymorphisms associated with expression levels, such as those within the 3’UTR of this molecule, could help identify new genetic markers implicated in the risk, severity, or prognosis of this pathology.

In this work, we focused on studying the influence of the aforementioned HLA-G UTR polymorphisms in paired tissue samples (tumoral and non-tumoral) obtained from a cohort of patients with gastric adenocarcinoma. Such an approach will allow us to assess the suitability of HLA-G variants as potential risk markers for gastric adenocarcinoma and elucidate their significance in the prognosis of this type of cancer.

The study was approved by the local ethics committee and carried out in compliance with the ethical guidelines outlined in the Declarations of Helsinki. Prior to the collection of blood samples, all patients provided written informed consent.

A total of 111 patients with gastric cancer were included (see Table 1), alongside a control group of 119 healthy Spanish individuals. Genomic DNA was extracted from paired (tumor and distal) tissues as well as blood samples obtained from patients with gastric cancer using the Nucleon BACC kit (GE Healthcare). DNA extraction from saliva samples collected from controls was performed using the Oragene DNA 500 kit (DNA Genotek) and purified with PrepIT-L2P (DNA Genotek). Quantity and purity of DNA was assessed spectrophotometrically in a Nanodrop-One (Thermo-Scientific).

Table 1

Demographic and clinical characteristics of patients.
	Patient characteristics
	Total N. (%)	Patients
	Total N. (%)	N	Range, %
Age (y)	Median (range)	70	(33–89)
Sex, N. (%)	Male	66	(60.6%)
	Female	43	(55.4%)
	NA	1
Stage, N. (%)	I	24	(22.0%)
	II	39	(36.0%)
	III	23	(21.0%)
	IV	23	(21.0%)
	NA	2
Treatment a, N. (%)	Surgery	111	(100%)
Treatment a, N. (%)	Chemotherapy	111	(100%)
Localization, N. (%)	Fundus	14	(13.6%)
	Antrum	37	(35.9%)
	Body	34	(33.0%)
	Difuse	6	(5.8%)
	Cardia	4	(3.9%)
	Gastric Bypass	7	(6.8%)
	NA	8
Type, N. (%)	Intestinal	51	(52.7%)
	Non-intestinal	52	(47.3%)
	NA	8
Overall survival, N. (%)	< 5 y	60	(58.3%)
	> 5 y	43	(41.7%)
	NA	8

HLA-G polymorphism analysis was performed using PCR (see Table 2). The 14bp polymorphism was analyzed by band size discrimination (6) and the remaining UTR SNPs were analyzed by Sanger sequencing. Primers and PCR conditions are detailed in Table 2.

Table 2

Primers and PCR programs employed in this study.
Polymorphism	Primers		PCR conditions
	Forward	Reverse	Denaturalization		Annealing	Elongation
14bp INS/DEL (30 cycles)	5’-GTGATGGGCTGTTTAAAGTGTCACC − 3’	5’-GGAAGGA ATGCAGTTC AGCATGA − 3’	94°C		64°C	72°C
			2 min	30 sec	60 sec	60 sec	10 min
UTR SNPs (32 cycles)	5’-CATGCTG AACTGCAT TCCTTCC − 3’	5’-CTGGTGG GACAAGGT TCTACTG − 3’	94°C		65.5°C	72°C
			5 min	30 sec	30 sec	60 sec	5 min

The PCR or PCR-RFLP data of the studied polymorphisms were analyzed using the software SNPStats. This software allows the evaluation of Hardy-Weinberg Equilibrium (exact test), chi-square test, odds ratio (OR) estimation for the association between polymorphisms, the analysis of linkage disequilibrium using the D statistic and correlation coefficient, and haplotype analysis employing the EM algorithm (7, 8).

Kaplan-Meier method was used to estimate the 5-year survival function of patients with gastric cancer considering various genetic factors (GraphPad Prism 8.0 software). Multivariate Cox regression models were used to simultaneously assess the effect of genetic factors along with other variables such as comorbidities, clinical features and demographic characteristics on 5-year survival of patients (software R). In all Cox regression fits, both individual and global Schoenfeld test indicated that no covariate in the model nor the model as a whole violate the Proportional Hazard assumption, meaning that the hazard ratio stays constant over time (9).

P-values below 0.05 were considered statistically significant. When required, the Holm-Bonferroni (HB) sequential correction method for multiple testing was applied to the statistical analyses. This method compares the k-ranked p-value to the nominal significance level (0.05) divided by (n-k + 1), where in this case n = 2 (the number of polymorphisms) and k = 1 and 2.

1. Hardy-Weinberg equilibrium and linkage disequilibrium

The analysis showed that UTR polymorphisms were in Hardy-Weinberg equilibrium (not shown). Additionally, genetic distance analysis demonstrated that the polymorphisms were in linkage disequilibrium (Fig. 1), suggesting that these variants form combined haplotypes, as described in previous works. We then proceeded to analyze the distribution of these haplotypes in our study population.

2. UTR-1 and 6 haplotypes are increased in patients with gastric cancer

The analysis of the 9 polymorphisms forming the HLA-G 3’UTR haplotypes showed an elevated frequency of UTR-1 and UTR-6, which are associated with increased HLA-G expression. Specifically, UTR-1 showed an odds ratio (OR) of 2.42 (1.12–5.21 95% CI, p-value = 0.025) and UTR-6 an OR of 3.02 (1.03–8.90 95% CI, p-value = 0.046), with frequencies of 32.1% and 6.9%, respectively, compared to the control group (25.5% and 4.6%, respectively) (Table 3).

Table 3

HLA-G 3’-UTR haplotype frequencies estimation and distribution. UTR 1 and 6 are overrepresented in patients with gastric cáncer.
3'UTR Haplotypes analysis
UTR	14bp	+ 3092 G > T	+ 3107 C > G	+ 3111 G > A	+ 3121 T > C	+ 3142 C > G	+ 3187 A > G	+ 3196 C > G	+ 3227 G > A	Control	Gastric Cancer	Mean Freq.	OR (95% CI)	P-value
5	I	G	C	G	T	G	A	C	G	0.116	0.069	0.094	1.00	---
1	D	G	C	G	T	C	G	C	G	0.254	0.321	0.284	2.42 (1.12–5.21)	0.025
2	I	G	C	G	T	G	A	G	G	0.254	0.235	0.245	1.82 (0.84–3.93)	0.131
3	D	G	C	G	T	G	A	C	G	0.149	0.135	0.142	1.75 (0.75–4.09)	0.195
4	D	G	C	G	T	C	A	C	G	0.126	0.131	0.128	2.11 (0.85–5.24)	0.107
6	D	G	C	G	T	C	A	C	A	0.046	0.069	0.060	3.02 (1.03–8.90)	0.046
rare	*	*	*	*	*	*	*	*	*	0.020	0	0.047	1.62 (0.51–5.12)	0.409

This data provides evidence of the role of the 3’UTR region polymorphisms of the HLA-G gene in gastric cancer susceptibility.

3. Patients with the 14bp D/D polymorphism show lower survival rate

Survival curve analysis showed that the 14bp polymorphism was the only one implicated in the survival of patients with gastric cancer.

Specifically, patients with the 14bp D/D genotype exhibited a lower survival rate (p = 0.023, survival below 25%), compared to 14bp I/D and 14bp I/I patients combined (survival above 50%) (Fig. 2A).

Moreover, the corresponding Cox regression model along with TNM staging, showed that the hazard ratio estimate of D/D vs. I/D + I/I is 2.7 (95% CI 1.17–6.3, p-value = 0.021) (Fig. 2B)

In recent years, significant interest has been directed towards the interplay between HLA-G, immunoediting, and cancer (10, 11, 12). Indeed, the HLA-G-mediated signaling pathway is currently acknowledged as a novel therapeutic immune checkpoint, alongside other firmly established checkpoints (13).

This study shows that individuals harboring genetic markers in the 3’-UTR region associated with elevated HLA-G expression are more susceptible to developing gastric cancer. In our cohort, we observed a heightened frequency of 3’-UTRs inducing high HLA-G high expression (namely UTR-1 and UTR-6,) among patients with gastric cancer,

The UTR-1 and 6 haplotypes displayed an increased frequency in patients with gastric cancer. These haplotypes encompass variants known to increase HLA-G levels (4), thereby fostering an HLA-G mediated immunosuppressive microenvironment, as proposed in our initial hypothesis.

Several authors have identified mechanisms that regulate HLA-G expression probably related to the 3’ UTR variants. For instance, the 14bp I/D is associated with mRNA stability (14), while + 3142 G/C and + 3187 G/A (located in an AU-rich element, ARE) may participate in miRNA-mediated post-transcriptional regulation (15) or in mRNA degradation (16), respectively. Additionally, other SNPs (namely + 3001 C/T, + 3003 T/C, + 3010 G/C, + 3027 C/A, + 3035 C/T and + 3196 C/G), have been proposed as miRNA targets, suggesting a potential role in post-transcriptional regulation of HLA-G (17).

Elevated HLA-G levels have been linked to numerous physiological (18) and pathological conditions, such as cancer, while lower levels are associated with autoimmune and inflammatory diseases (19), in line with the results described herein.

These findings underscore HLA-G as a promising target for potential therapeutic interventions. Strategies such as miRNA-mediated downregulation of HLA-G expression or inhibition of its interaction with its cognate receptors, akin to current PD-1/PD-L1 immunotherapies, hold promise for stimulating immune responses against the tumor.

Furthermore, exploring the functional implications of these HLA-G polymorphisms and their relationship with disease susceptibility and progression could shed light on the association between HLA-G markers and pathological conditions.

Other works and meta-analysis described an association of HLA-G 3’UTR haplotypes to the development and severity of different malignancies, such as breast and colorectal cancer, were 14bp Del/Del and + 3142 C/C, both forming UTR-1 and UTR6 haplotypes, showed association to risk of developing both cancers (20, 21). Moreover, other authors showed an association of HLA-G levels of expression and the 14bp polymorphism in gynecologic cancers (22), and, in the same vein of thinking, loss of miR-152 increases HLA-G expression in vitro (23), mimicking the effect of + 3142 polymorphisms, as miR-152 is not able to bind + 3142 C/C.

All these findings not only support the results of our work, but also provide a functional explanation for them, as it seems clear that there is a link between variants in the 3'UTR of HLA-G and the expression levels of this protein and, consequently, with the risk of developing tumors of epithelial origin.

This work has some limitations. First, it is focused on genetic variants with a known effect on HLA-G expression. However, further studies in a large cohort of patients may enable to link this polymorphisms and UTR haplotypes with data of protein in sera and tissue of patients, thus comparing the actual effect of these variants in the level of expression of HLA-G. Although it is an interesting point, several factors can modify HLA-G levels of expression that diverge from the regulation of classic class I HLA molecules (24), such as inflammation and cellular stress (23, 25), making it difficult to link the effect of genetic variants with HLA-G expression in the context of an evolving pathology like cancer.

Moreover, HLA-G gene is in a high linkage disequilibrium with other class I genes, as all of them are located in the same chromosome. For instance, the HLA-A locus is surrounded by HLA class Ib genes: HLA-E, HLA-H, HLA-G and HLA-F (26), meaning that the association of genetic variants to a certain phenotype may be mediated by other genes in that haplotype.

Finally, although several authors described the effect of HLA-G in the immune system (27, 28), functional analysis may enlight the actual immunomodulatory properties of this molecule in the context of gastric cancer. In our group, we already described the expression of HLA-G in gastric tumors (6, Supplementary Material), and a closer look to the in vivo effect of the immunomodulatory properties of HLA-G in the tumor microenvironment should address the importance of this molecule in the evolution and possible therapies of this pathology.

ETHICS STATEMENT

The studies involving human participants were reviewed and approved by Comité ético de investigación clínica, Hospital Clínico San Carlos, Madrid, Spain. The patients/participants provided their written informed consent to participate in this study.

The study was performed in accordance with the ethical standards as laid down in the Declarations of Helsinki and approved by the local ethics committee. Written informed consent was obtained from all subjects.

ACKNOWLEDGEMENTS

We thank Prof. E. D. Carosella (Saint Louis Hospital, Paris, France) for scientific support.

CONFLICT OF INTEREST STATEMENT

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

FUNDING

This work was supported by grants from Instituto de Salud Carlos III (PI18/00626 and PI18/00721), with funds from the European Union (Fondo Europeo de Desarrollo Regional FEDER) and PR3/23 30834

AUTHORSHIP

CV-Y and IJ: manuscript writing, investigation, and analysis. IJ: design, analysis, and supervision. MM-A: investigation support and validation. EM-L: analysis. AG-C, AL-G, IL, and RG: patient follow-up, sample and data collection. AA-V: critical review, project administration, and funding acquisition. JM-V: manuscript writing and revision, supervision, project administration, and funding acquisition. All authors contributed to the article and approved the submitted version.

WHO Cancer Today: Data Visualization Tools for Exploring the Global Cancer Burden in 2020. https://gco.iarc.fr/today/home
Sung H, Ferlay J, Siegel RL et al (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 71(3):209–249. https://doi.org/10.3322/caac.21660
Arnaiz-Villena A, Juarez I, Suarez-Trujillo F et al (2020) HLA-G: Function, Polymorphisms and Pathology. Int J Immunogenet 48(2):172–192. https://doi.org/10.1111/iji.12513
Donadi E, Castelli E, Arnaiz-Villena A et al (2011) Implications of the Polymorphism of HLA-G on its Function, Regulation, Evolution and Disease Association. Cell Mol Life Sci 68:369–395. https://doi.org/10.1007/s00018-010-0580-7
Murdaca G, Calamaro P, Lantieri F et al (2018) HLA-G Expression in Gastric Carcinoma: Clinicopathological Correlations and Prognostic Impact. Virchows Arch 473:425–433. https://doi.org/10.1007/s00428-018-2379-0
Vaquero-Yuste C, Juarez I, Molina-Alejandre M et al (2021) HLA-G 3'UTR Polymorphisms Are Linked to Susceptibility and Survival in Spanish Gastric Adenocarcinoma Patients. Front Immunol 12:698438. https://doi.org/10.3389/fimmu.2021.698438
Iniesta R, Guinó E, Moreno V (2005) Análisis Estadístico De Polimorfismos Genéticos En Estudios Epidemiológicos. Gac Sanit 19:333–341. https://doi.org/10.1157/13078029
Solé X, Guinó E, Valls J et al (2006) SNPStats: A Web Tool for the Analysis of Association Studies. Bioinformatics 22:1928–1929. https://doi.org/10.1093/bioinformatics/btl268
Schoenfeld D (1980) Chi-Squared Goodness-Of-Fit Tests for the Proportional Hazards Regression Model. Biometrika 67:145–153. https://doi.org/10.2307/2335327
Lázaro-Sánchez AD, Salces-Ortiz P, Velásquez LI et al (2020) HLA-G as a New Tumor Biomarker: Detection of Soluble Isoforms of HLA-G in the Serum and Saliva of Patients With Colorectal Cancer. Clin Transl Oncol 22:1166–1171. https://doi.org/10.1007/s12094-019-02244-2
Dardano A, Rizzo R, Polini A et al (2012) Soluble Human Leukocyte Antigen-G and Its Insertion/Deletion Polymorphism in Papillary Thyroid Carcinoma: Novel Potential Biomarkers of Disease? J Clin Endocrinol Metab 97:4080–4086. https://doi.org/10.1210/jc.2012-2231
Arnaiz-Villena A, Dimitroski K, Pacho A et al (2001) HLA Genes in Macedonians and the Sub-Saharan Origin of the Greeks. Tissue Antigens 57:118–127. https://doi.org/10.1034/j.1399-0039.2001.057002118.x
Lin A, Yan W (2018) Heterogeneity of HLA-G Expression in Cancers: Facing the Challenges. Front Immunol 9:2164. https://doi.org/10.3389/fimmu.2018.02164
Rousseau P, Le Discorde M, Mouillot G et al (2003) The 14 bp deletion-insertion polymorphism in the 3′ UT region of the HLA-G gene influences HLA-G mRNA stability. Hum Immunol 64(11):1005–1010
Tan Z, Randall G, Fan J et al (2007) Allele-specific targeting of microRNAs to HLA-G and risk of asthma. Am J Hum Genet 81(4):829–834. https://doi.org/10.1086/521200
Yie SM, Li LH, Xiao R et al (2008) A single base-pair mutation in the 3'-untranslated region of HLA-G mRNA is associated with pre-eclampsia. Mol Hum Reprod 14(11):649–653. https://doi.org/10.1093/molehr/gan059
Castelli EC, Moreau P, Oya e Chiromatzo A et al (2009) In silico analysis of microRNAS targeting the HLA-G 3' untranslated region alleles and haplotypes. Hum Immunol 70(12):1020–1025. https://doi.org/10.1016/j.humimm.2009.07.028
Barbaro G, Inversetti A, Cristodoro M et al (2023) HLA-G and Recurrent Pregnancy Loss. Int J Mol Sci 24(3):2557. https://doi.org/10.3390/ijms24032557
Martín-Villa JM, Vaquero-Yuste C, Molina-Alejandre M et al (2022) HLA-G: Too Much or Too Little? Role in Cancer and Autoimmune Disease. Front Immunol 13:796054. https://doi.org/10.3389/fimmu.2022.796054
Tizaoui K, Jalouli M, Ouzari HI et al (2022) 3'UTR-HLA-G polymorphisms and circulating sHLA-G are associated with breast cancer: Evidence from a meta-analysis. Immunol Lett 248:78–89. https://doi.org/10.1016/j.imlet.2022.06.010
Dhouioui S, Laaribi AB, Boujelbene N et al (2022) Association of HLA-G 3'UTR polymorphisms and haplotypes with colorectal cancer susceptibility and prognosis. Hum Immunol 83(1):39–46. https://doi.org/10.1016/j.humimm.2021.10.003
Tizaoui K, Jalouli M, Boujelbene N et al (2022) The relationship of 3'UTR HLA-G14-bp insertion/deletion and + 3142 C/G polymorphisms and soluble HLA-G expression with gynecological cancers: An updated meta-analysis. Immun Inflamm Dis 10(7):e645. https://doi.org/10.1002/iid3.645
Song B, Guan Z, Liu F et al (2015) Long non-coding RNA HOTAIR promotes HLA-G expression via inhibiting miR-152 in gastric cancer cells. Biochem Biophys Res Commun 464(3):807–813. https://doi.org/10.1016/j.bbrc.2015.07.040
Castelli EC, Veiga-Castelli LC, Yaghi L et al (2014) Transcriptional and posttranscriptional regulations of the HLA-G gene. J Immunol Res 2014:734068. https://doi.org/10.1155/2014/734068
Morandi F, Fainardi E, Rizzo R et al (2014) The role of HLA-class Ib molecules in immune-related diseases, tumors, and infections. J Immunol Res 2014:231618. https://doi.org/10.1155/2014/231618
Carlini F, Ferreira V, Buhler S et al (2016) Association of HLA-A and Non-Classical HLA Class I Alleles. PLoS ONE 11(10):e0163570. https://doi.org/10.1371/journal.pone.0163570
Carosella ED, Favier B, Rouas-Freiss N et al (2008) Beyond the increasing complexity of the immunomodulatory HLA-G molecule. Blood 111(10):4862–4870. https://doi.org/10.1182/blood-2007-12-127662
LeMaoult J, Krawice-Radanne I, Dausset J et al (2004) HLA-G1-expressing antigen-presenting cells induce immunosuppressive CD4 + T cells. Proc Natl Acad Sci U S A 101(18):7064–7069. https://doi.org/10.1073/pnas.0401922101

No competing interests reported.

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HLA-G High-expressor 3’UTR Markers Are Linked to Gastric Cancer Development and Survival

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