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. 2022 Jul 15;17(7):e0271265. doi: 10.1371/journal.pone.0271265

Association of the PROGINS PgR polymorphism with susceptibility to female reproductive cancer: A meta-analysis of 30 studies

Chen Zhou 1,2, Xiangman Zou 2, Xiaosha Wen 2, Zifen Guo 2,*
Editor: Elda Tagliabue3
PMCID: PMC9286292  PMID: 35839271

Abstract

Aims

The progesterone response of the nuclear progesterone receptor plays an important role in the female reproductive system. Changes in the function of the progesterone receptor gene may increase the risk of reproductive cancer. The present study performed a meta-analysis to examine whether the progesterone receptor gene PROGINS polymorphism was a susceptibility factor for female reproductive cancer.

Materials and methods

We searched the PubMed, Cochrane Library, Web of Science and EMBASE databases for literature on PROGINS polymorphisms and female reproductive cancer published before September 2020. We evaluated the risk using odds ratios [ORs] and 95% confidence intervals via fixed effects models and random-effects models, which were calculated for all five genetic models. We grouped the analyses by race, cancer, and HWE.

Results

Thirty studies comprised of 25405 controls and 19253 female reproductive cancer cases were included in this meta-analysis. We observed that the Alu insertion polymorphism and the V660L polymorphism were significantly associated with female reproductive cancer in the allele and dominant genetic models. The allele genetic model and (Alu-insertion polymorphism: OR = 1.22, 95% CI = 1.02–1.45; V660L polymorphism: OR = 1.02, 95% CI = 1.00–1.13) dominant genetic model (Alu-insertion polymorphism: OR = 1.27, 95% CI = 1.03–1.58; V660L polymorphism: OR = 1.10, 95% CI = 1.011.19) demonstrated a significantly increased risk of female reproductive cancer. A subgroup analysis according to ethnicity found that the Alu insertion was associated with female reproductive cancer incidence in white (Allele model: OR = 1.21, 95% CI = 1.00–1.45; Heterozygous model: OR = 3.44, 95% CI = 1.30–9.09) and Asian (Dominant model: OR = 3.12, 95% CI = 1.25–7.79) populations, but the association disappeared for African and mixed racial groups. However, the V660L polymorphism was significantly associated with female reproductive cancer in the African (Allele model: OR = 2.52, 95% CI = 1.14–5.56; Heterozygous model: OR = 2.83, 95% CI = 1.26–6.35) and mixed racial groups (Dominant model: OR = 1.28, 95% CI = 1.01–1.62). Subgroup analysis by cancer showed that the PROGINS polymorphism increased the risk of cancer in the allele model, dominant mode and heterozygous model, but the confidence interval for this result spanned 1 and was not statistically significant. This sensitivity was verified in studies with HWE greater than 0.5.

Conclusion

Our meta-analysis showed that the progesterone receptor gene Alu insertion and the V660L polymorphism contained in the PROGINS polymorphism were susceptibility factors for female reproductive cancer.

Introduction

Cancer is a major public health problem worldwide. Cancer is a multifactorial disease, and there is a coordinated relationship between genetic and environmental factors [1,2]. Despite extensive research to prevent cancer, cancer cases continue to increase sharply. Data from the American Cancer Society in 2022 predicts 1.9 million new cancer cases in 2022. More than 609,360 Americans die of cancer annually, which is equivalent to greater than 1,700 people dying of cancer daily [3].

Progesterone is a key regulatory factor in the proliferation and differentiation of female reproductive tract cells. Progesterone inhibits the proliferation of reproductive tract cells by excessive estrogen via the progesterone receptor (PgR) [46], and excessive estrogen stimulation increases the risk of female reproductive tract cancer [7]. PgR is a member of the nuclear steroid hormone receptor family and is expressed primarily in female reproductive tissues and the central nervous system. It is encoded by a single gene (Gene ID: 5241) located at 11q22–q23 [8], which encodes two isoforms, PgR-B and PgR-A. The two PgR isoforms with different functions come from different transcriptional promoters. PgR-B (114 KDa) is a transcriptional activator and a mediator of cell proliferation, and PgR-A (94 KDa) is a suppressor of transcription. In vitro studies showed that PgR isoforms exhibited different transcriptional regulatory activities. Robert A. et al. [9] found that selective PgR-A knockout induced endometrial epithelial cell proliferation in mice, which suggests that PgR-A is required to control potential adverse reactions of PgR-B. The expression of PgR-A in PgR-B knockout mice was sufficient and necessary to regulate the antiproliferative response of progesterone and estrogen-induced hyperplasia. Prompt changes in the relative expression of these two isoforms or changes in isoform activity or any other genetic mutations may lead to progesterone receptor alienation. The anti-estrogen proliferation effect of progesterone primarily depends on PgR-B, but the excessive expression of PgR-B causes progesterone-dependent proliferation. Progesterone receptor alienation leads to increased susceptibility to female reproductive cancer.

Silencing or mutation of the PgR gene affects the expression of the progesterone receptor. Six variable sites, four polymorphisms, and five common haploids have been detected in the PgR gene. PROGINS contains the Alu insertion in intron 7 of the PgR gene, which is completely linked to the unbalanced linkage (LD) with rs1042838 (V660L in exon 4) and rs1042839 (H770H in exon 5) [10]. The alleles of Alu-insertion alter transcript levels and may contribute to disease risk [11]. The PROGINS polymorphism of the human progesterone receptor diminishes the response to progesterone [12]. The PROGINS allele was significantly associated with decreased serum progesterone levels in patients with polycystic ovary syndrome (PCOS) [13].

The current study considered PROGINS as a risk modifier for gynecological benign and malignant diseases, which indicated that PROGINS may affect PgR function. Alu insertion of the PROGINS allele was inversely associated with breast cancer risk and ovarian cancer risk in certain races [1416]. However, only two research reports that concluded that PROGINS affected the risk of endometrial cancer [17,18]. The V660L polymorphism is caused by G > T, which causes a valine > leucine substitution in the fourth exon of the PgR gene. No significant association of the PROGINS polymorphism was found in breast or ovarian cancer studies [19,20]. One study on ovarian cancer [21] also failed to find a link, but another study showed that the T allele (leucine) was associated with an increased risk of breast cancer [22]. However, the results of these studies are inconclusive. Therefore, to clarify the role of the PRPGINS PgR polymorphism in female reproductive cancers, we performed a meta-analysis of all eligible case–control studies to derive the overall cancer risk associated with this polymorphism.

Materials and methods

The current study conformed to the checklist for meta-analysis of genetic association studies specified for the PLOS One approach (S1 Table).

Literature search and identification

This meta-analysis adhered to the PRISMA guidelines. PubMed, Cochrane Library, Web of Science and EMBASE were used to perform a comprehensive search of published related documents. The following search keywords were used: “polymorphism, genetic” or “breast cancer” or “ovarian cancer” or “endometrial cancer” or “gynecologic neoplasm” and “PROGINS” or “V660 L” or “rs1042838” or “rs1042839” or “H770H” or “Z49816.1” or “Alu-insertion”. A search strategy was developed (S2). The last search was updated on September 26, 2020.

Inclusion and exclusion criteria

The studies were selected using the following criteria.

The following inclusion criteria were used: (a) case-control or cohort study; (b) assessment of PgR polymorphisms for PROGINS and cancer risk; (c) pathology for diagnosis of cancer patients and confirmation that the control was cancer-free; (d) report odds ratios (ORs) and 95% confidence interval (CIs) values or sufficient data to calculate these values; (e) clearly describe genotyping and statistical methods; (f) participants in the control group were in Hardy-Weinberg Balance (HWE); and (g) no language limitations, regardless of sample size.

The following exclusion criteria were used: (a) case reports, comments, comments, and editorial articles; (b) studies of research progress, severity, treatment response, or survival; (c) when overlapping data from the same case series were included in multiple publications, the most recent or most complete study was selected to perform the meta-analysis, and if no information was available, the study was excluded; and (d) literature with specific requirements for the inclusion of cases or. Any differences in the inclusion of the study were resolved via discussion and subsequent consensus.

Data extraction

Two authors independently extracted the characteristics of the selected study using a standardized protocol, and the third investigator reviewed the results. The following information was extracted from each study: first author, year of publication, study population (country, ethnicity), type of cancer, number of cases and controls, genotype frequencies for cases and controls, and Hardy-Weinberg equilibrium in controls (HWE). We compared key research characteristics, such as location, study time, and authorship, to determine the existence of multiple publications in the same study.

Quality assessment of the studies

We evaluated the quality based on the NOS quality evaluation to determine the quality of the included literature, and low-quality articles with less than 3 points were excluded. Chen Zhou and Xiangman Zou independently performed the literature search and data extraction. Disputes were discussed and resolved by Xiaosha Wen and Zifen Guo.

Statistical analysis

STATA software (version 14.0) was used to synthesize the relevant data, and the odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the relationships between PROGINS gene polymorphisms and female reproductive cancer. Five genetic models were used: T2 vs. T1 (allelic), T1T2+T2T2 vs. T1T1 (dominant), T1T2 vs. T1T1 (heterozygous), T2T2 vs. T1T2+T1T1 (recessive), and T2T2 vs. T1T1 (homozygous). Heterogeneity was evaluated using I2 statistics. When the heterogeneity test found significant heterogeneity (I2 > 50 or P < 0.05), a random-effect model was used. Otherwise, the fixed model was used. When heterogeneity was present in the study, subgroup analysis was performed according to ethnicity, type of disease and HWE of the included cases to examine the sources of heterogeneity. Sensitivity analysis (excluding one study at a time or changing the model) was used to assess the stability of each efficacy index. Begg’s funnel chart and Egger’s test were used to evaluate the publication bias of this study. When P < 0.05, publication bias was present in this study.

Results

Study selection and characteristics

Fig 1 outlines the study selection process in a flowchart following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 189 articles related to PROGINS polymorphism were retrieved using the retrieval method. Among these articles, 139 articles were excluded after review of the abstracts and unrelated literature, and 11 articles were excluded strictly according to the inclusion and exclusion criteria. Ultimately, 30 articles were included in the meta-analysis (Fig 1) [8,18,19,2147]. Of the 30 independent studies, 28 studies included genetic frequency analysis of whites, 2 studies included mixed races, 2 studies included Asians and 2 studies included Africans. The types of diseases included breast cancer, ovarian cancer and endometrial cancer. All samples were taken from humans and genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP), DNA sequencing, TaqMan and other genotyping methods (Table 1). The quality of the studies is shown in Table 2.

Fig 1. Flowchart showing the meta-analysis literature screening process.

Fig 1

Table 1. Characteristics of the studies included in the meta-analysis.

Study Country Ethnicity Cancer Detection method Sample size
(case/control)
Genotype frequency Allele frequency
case controls Case (%) Control (%)
Alu insertion T1T1 T1T2 T2T2 T1T1 T1T2 T2T2 T1 T2 T1 T2
Albalawi, I. A Saudi Arabia Asian BC PCR–RFLP 100/100 81 18 1 93 6 1 10 90 4 96
Donaldson, C J USA white BC PCR–RFLP 23/60 17 5 1 41 16 3 84.4 15.2 81.3 18.3
Donaldson, C J -2 USA African BC PCR–RFLP 61/81 56 5 0 73 8 0 95.9 4.1 95.1 4.9
Govindan, S India white BC PCR–RFLP 157/108 134 23 0 102 6 0 92.7 7.3 97.2 2.8
Junqueira, M. G Brazil white EC PCR–RFLP 282/121 221 61 0 100 18 3 89.2 10.8 90.1 9.9
Lancaster, J. M -2 USA white BC PCR–RFLP 68/101 55 12 1 79 18 4 89.7 10.3 87.1 12.9
Lancaster, J. M USA white OC PCR–RFLP 309/397 219 80 10 285 95 17 83.8 16.2 83.8 16.2
Leite, D.B Brazil white OC PCR–RFLP 80/282 57 12 11 221 61 0 78.8 21.2 89.2 10.8
Manolitsas, T. P UK white BC PCR–RFLP 292/220 229 61 2 162 54 4 88.9 11.1 85.9 14.1
Manolitsas, T. P -2 UK white OC PCR 231/220 173 52 6 162 54 4 86.1 13.9 85.9 14.1
McKenna, N. J Ireland white OC S-blot 41/83 26 15 0 58 21 4 81.7 18.3 82.5 17.5
McKenna, N. J-2 Germany white OC S-blot 26/101 17 8 1 88 12 1 80.8 19.2 93.1 6.9
Patricia, G. A Mexico white BC PCR 481/209 360 103 18 176 33 0 85.6 14.4 92.1 7.9
Runnebaum, I. B USA white OC PCR 167/496 101 60 6 328 153 15 78.4 21.6 81.6 18.4
Surekha, S India white BC PCR 250/249 241 7 2 242 7 0 97.8 2.2 98.6 1.4
V660L GG GT TT GG GT TT G T G T
Gabriel, C. A USA white BC TaqMan 346/357 236 101 9 255 92 10 82.8 17.2 84.3 15.7
Gabriel, C. A -2 USA African BC TaqMan 86/327 75 11 0 309 16 2 93.6 6.4 96.9 3.1
Clendenen, T Mix white BC TaqMan 658/1099 846 288 26 1516 523 54 85.5 14.5 84.9 15.1
Fabjani, G Austria white BC DNA 155/106 119 32 4 78 28 0 87.1 12.9 86.8 13.2
Fernandez, L.P Spain white BC TaqMan 550/564 354 153 24 375 154 15 81.1 18.9 83.1 16.9
Johnatty, S.E Australia white BC PCR–RFLP 1444/583 1017 380 47 409 160 14 83.6 16.4 83.9 16.1
Lee, E USA MIX EC TaqMan 198/1077 170 25 3 954 114 9 92.2 7.8 93.9 6.1
Lee, E -2 USA white EC TaqMan 379/836 259 109 11 615 199 22 86 14 90.2 9.8
Lundin, E MIX white EC TaqMan 391/705 281 96 14 540 147 18 84.1 15.9 87 13
O’Mara, T. A Singapore Asian EC TaqMan 528/1538 414 151 17 1147 361 30 84.1 15.9 86.3 13.7
O’Mara, T. A -2 UK white EC TaqMan 1086/1591 765 294 27 1123 434 34 84 16 84.2 15.8
O’Mara, T. A -3 Australia white EC TaqMan 1220/1354 867 323 30 933 383 38 84.3 15.7 83.1 16.9
Pearce, C. L USA white OC DNA 267/397 173 82 12 279 111 6 80.1 19.9 84.5 15.5
Pearce, C. L-2 USA white BC DNA 1715/2505 1400 252 15 2025 363 37 91.5 8.5 91 9
Pooley, K. A Englishman white BC TaqMan 2345/2281 1302 517 42 1461 513 39 83.9 16.1 85.3 14.7
Romano, A Netherlands white BC PCR–RFLP 167/31 123 41 3 22 7 2 85.9 14.1 82.3 17.7
Romano, A German white BC PCR–RFLP 545/443 399 133 14 347 87 9 85.4 14.6 88.1 11.9
Romano, A -2 German white OC PCR–RFLP 67/443 42 24 1 347 87 9 80.6 19.4 88.1 11.9
Spurdle, A. B Australia white OC PCR–RFLP 551/298 395 144 12 203 90 5 84.8 15.2 83.2 16.8
Terry, K. L USA white OC TaqMan 895/939 648 223 25 612 298 29 84.9 15.1 81 19
De vivo, I USA white BC TaqMan 1252/1660 869 348 35 1186 434 40 83.3 16.7 84.5 15.5
Tong, D Austrian white OC DNA 226/194 167 50 9 141 52 1 85 15 86.1 13.9
Quaye, L UK/USA white OC TaqMan 1424/2408 1005 377 42 1819 526 63 83.8 16.2 86.5 13.5
Ghali, R. M Tunisia white BC TaqMan 183/216 127 50 6 172 37 7 83.1 16.9 88.2 11.8

PCC, population-based case–control study, HCC, hospital-based case–control study, PCR–RFLP PCR-restriction fragment length polymorphism, BC, Breast cancer, EC, Endometrial cancer, OC, Ovarian cancer, DNA, DNA sequencing, S-blot, Southern blot.

Table 2. Article quality evaluation.

Study Adequate case definition Definition of controls Comparability HWE>0.05 PCC PMH (Past Medical History) Unified detection method Article quality
Alu insertion
Albalawi 2020 [47] 1 1 1 0 0 1 1 5
Donaldson 2002 [28] 1 1 1 1 0 0 1 5
Govindan, S 2007 [34] 1 1 1 1 0 0 1 5
Junqueira, M.G 2007 [18] 1 1 1 1 0 1 1 6
Lancaster 1998 [25] 1 0 0 0 0 0 1 2
Lancaster, J.M 2003 [30] 1 1 1 0 1 1 1 6
Leite, D.B. 2008 [37] 1 1 1 0 0 1 1 5
Manolitsas TP 1997 [24] 1 0 1 1 1 0 1 5
McKenna 1995 [23] 0 0 1 1 0 0 1 3
Patricia Gallegos-Arreola, M 2015 [15] 1 1 1 1 1 1 1 7
Runnebaum, I.B 2001 [26] 1 1 1 1 1 1 1 7
Surekha 2009 [39] 1 1 1 1 1 1 1 7
V660L
Gabriel, C. A.2013 [44] 1 1 1 1 0 1 1 6
Clendenen, T 2013 [43] 1 1 1 1 1 1 1 7
Fabjani, G 2002 [29] 1 1 1 1 1 1 1 7
Fernandez, L.P 2006 [31] 1 1 1 1 0 1 1 6
Johnatty, S.E 2008 [36] 1 1 1 1 1 1 1 7
Lee, E 2010 [40] 1 1 1 0 1 1 1 6
Lundin, E 2012 [42] 1 1 1 0 1 1 1 6
O’Mara, T.A 2011 [41] 1 1 1 1 1 1 1 7
Pearce, C.L. 2005 [22] 1 1 1 1 1 0 1 6
Pooley, K.A 2006 [32] 1 1 1 1 1 0 1 6
Romano A 2007 [12] 1 1 1 1 1 1 1 7
Romano, A 2006 [33] 1 1 1 1 1 0 1 6
Spurdle 2001 [21] 1 1 1 1 1 1 1 7
Terry, K.L. 2005 [8] 1 1 1 1 1 1 1 7
De vivo 2004 [19] 1 1 1 1 1 0 1 6
Tong, D. 2001 [27] 1 1 1 1 1 0 1 6
Quaye 2009 [38] 1 1 1 0 1 1 1 6
Ghali RM 2020 [46] 1 1 1 0 0 1 1 5

low quality, <3; Medium quality,3–4; high quality, ≥5.

Alu-insertion polymorphism and the risk of female reproductive cancer

We counted the Alu-insertion locus and the susceptibility to female reproductive cancer in the five models of allele genetic model (T2 vs. T1), homozygous genetic model (T2T2 vs. T1T2), heterozygous genetic model (T1T2 vs. T1T1), dominant genetic model (T1T2+T2T2 vs. T1T1) and recessive genetic models (T2T2 vs. T1T2+T1T1) (Table 3). The meta-analysis showed a significant association between Alu-insertion polymorphisms and the risk of female reproductive cancer in the allele genetic model (OR = 1.22 95% CI = 1.02–1.45), the dominant genetic model (OR = 1.27 95% CI = 1.03–1.58), and the heterozygote genetic model (OR = 1.19 95% CI = 1.03–1.38) (Figs 2 and 3). A significant association was found in the allele genetic model of the white group (OR = 1.21 95% CI = 1.00–1.45) (Table 4).

Table 3. Meta-analysis of the association between the PROGINS polymorphism and female reproductive cancer susceptibility.

Polymorphism Genetic model Case/Control Test of association Heterogeneity Publication bias
OR(95%CI) P I2(%) PHet Model Egger‘s test p value Begg’s
test p value
Alu insertion T2 vs. T1 2568/2828 1.22[1.02,1.45] 0.027 * 21.3 0.218 F 0.373 0.168
T2T2+T1T2 vs.T1T1 2568/2828 1.27[1.03,1.58] 0.023* 43 0.035 R 0.373 0.201
T2T2 vs.T1T2+T1T1 2568/2828 1.18[0.55,2.55] 0.670 52.1 0.015 R 0.360 0.469
T2T2 vs.T1T1 2046/2322 1.23[0.57,2.65] 0.605 52.2 0.014 R 0.428 0.455
T1T2 vs.T1T1 2509/2772 1.19[1.03,1.38] 0.019* 39 0.058 F 0.428 0.263
V660L L vs. V 16685/22577 1.07[1.00,1.13] 0.031* 15 0.253 F 0.130 0.081
LL+VL vs. VV 16685/22577 1.10[1.01,1.19] 0.027* 60.1 0.000 R 0.503 0.265
LL vs. VL+VV 16685/22577 1.13[0.99,1.29] 0.075 0 0.476 F 0.413 0.244
LL vs. VV 12481/17361 1.07[0.93,1.23] 0.325 5 0.392 F 0.673 0.219
VL vs. VV 16257/22084 1.09[1.00,1.18] 0.056 60.7 0.000 R 0.385 0.204

F: Fixed model, R: Random model.

Fig 2. Forest plot of overall cancer risk associated with Alu-insertion PgR polymorphism (T2 vs. T1 and T2T2+T1T2vs.T1T1).

Fig 2

Fig 3. Forest plot of overall cancer risk associated with V660L PgR polymorphism (L vs. V and LL+VL vs. VV).

Fig 3

Table 4. Pooled odds ratios (ORs) in subgroups.

SNP/subgroups No. of study Allele model Dominant model Recessive model Homozygous model Heterozygous model
OR 95%CI P OR 95%CI P OR 95%CI P OR 95%CI P OR 95%CI P
Alu insertion
OC 5 1.20 0.95–1.51 0.125 1.23 0.96–1.56 0.100 1.59 0.56–4.49 0.382 1.67 0.60–4.69 0.330 1.13 0.93–1.37 0.232
BC 7 1.28 0.95–1.72 0.101 1.30 0.86–1.97 0.219 1.14 0.32–4.04 0.836 1.17 0.33–4.29 0.818 1.23 0.97–1.55 0.086
EC 1 1.08 0.53–2.19 0.828 1.31 0.76–2.28 0.170 0.06 0.00–1.17 0.063 0.06 0.00–1.27 0.071 1.53 0.86–2.73 0.146
white 9 1.21 1.00–1.45 0.046* 1.23 0.99–1.54 0.066 1.40 0.62–3.14 0.413 1.44 0.84–3.28 0.377 1.14 0.98–1.33 0.099
Asian 1 2.67 0.81–8.81 0.108 3.12 1.25–7.79 0.015* 1.00 0.06–16.21 1 1.15 0.07–18.65 0.923 3.44 1.30–9.09 0.013*
African 1 1.00 0.21–4.62 0.996 0.81 0.25–2.63 0.731 —— —— —— —— —— —— 0.81 0.25–2.63 0.731
Mix 1 1.08 0.53–2.19 0.828 1.31 0.75–2.28 0.329 0.06 0.00–1.17 0.063 0.06 0.00–1.27 0.071 1.53 0.86–2.73 0.019
HWE > 0.05 8 1.21 0.98–1.50 0.076 1.27 0.98–1.65 0.066 0.85 0.38–1.91 0.043 1.12 0.48–2.61 0.797 1.22 1.02–1.45 0.026
HWE < 0.05 4 1.23 0.90–1.68 0.188 1.30 0.85–1.98 0.230 1.85 0.22–15.66 0.004 1.88 0.23–15.50 0.556 1.13 0.86–1.48 0.379
V660L
OC 6 1.06 0.94–1.20 0.334 1.09 0.82–1.45 0.566 1.24 0.94–1.64 0.126 1.19 0.89–1.59 0.230 1.05 0.78–1.43 0.733
BC 10 1.06 0.98–1.15 0.139 1.09 1.00–1.19 0.052 1.07 0.88–1.29 0.518 1.00 0.82–1.22 0.979 1.09 0.99–1.20 0.064
EC 3 1.07 0.96–1.20 0.215 1.10 0.97–1.26 0.137 1.16 0.90–1.50 0.256 1.11 0.85–1.44 0.461 1.09 0.96–1.23 0.195
white 17 1.06 0.99–1.12 0.081 1.07 0.98–1.17 0.134 1.10 0.95–1.27 0.189 1.06 0.91–1.22 0.471 1.06 0.97–1.16 0.209
Asian 1 1.20 0.92–1.56 0.186 1.19 0.96–1.47 0.109 1.51 0.83–2.76 0.179 1.35 0.73–2.53 0.341 1.16 0.93–1.45 0.190
African 1 2.38 0.84–6.74 0.103 2.52 1.14–5.56 0.022* 0.75 0.04–15.82 0.855 0.29 0.02–6.55 0.434 2.83 1.26–6.35 0.012*
Mix 2 1.35 0.76–2.38 0.305 1.28 1.01–1.62 0.041* 1.49 0.80–2.79 0.212 1.23 0.65–2.42 0.499 1.25 0.97–1.60 0.081
HWE > 0.05 15 1.04 0.97–1.11 0.229 1.03 0.93–1.14 0.003 1.17 1.00–1.37 0.46 1.15 0.98–1.35 0.084 1.03 0.95–1.13 0.452
HWE < 0.05 6 1.16 1.02–1.31 0.020 1.34 1.10–1.64 0.003 1.01 0.76–1.29 0.975 0.85 0.64–1.14 0.277 1.29 1.06–1.57 0.009

Val 660 Leu polymorphism and the risk of female reproductive cancer

A total of 16685 cancer patients and 22577 healthy women in 18 studies were used to assess the relationship between the V660 locus and female reproductive cancer risk using the allele genetic model (L vs. V), homozygous genetic model (LL vs. VV), heterozygous genetic model (VL vs. VV), dominant genetic model (VL+LL vs. VV) and recessive genetic models (LL vs. VL+VV). The V660L mutation increased the risk of female reproductive cancer in the allele genetic model (OR = 1.02 95% CI = 1.00–1.13) and dominant genetic model (OR = 1.10 95% CI = 1.01–1.19). The heterozygote genetic model confirmed (OR = 1.09 95% CI = 1.00–1.18) that the V660L mutation increased the risk of female reproductive cancer (Fig 3 and Table 3).

The subgroup analysis found a significant association under the dominant genetic model (OR = 1.21 95% CI = 1.00–1.45) of the breast cancer group (Table 4).

Publication bias

Begg’s and Egger’s analyses showed that no publication bias in the Alu insertion or V660L (Table 3).

Sensitivity and heterogeneity

A sensitivity analysis was performed to determine whether changes in the inclusion criteria for meta-analysis affected the final results. The author deleted individual studies involved in each meta-analysis to reflect the impact of a single dataset on the merged ORs. Most of the corresponding merged ORs did not change substantially (data not shown). We also changed the effect model to test the impact on the results, and no substantial changes were found on the combined OR, which showed that our results were statistically robust. I2 statistics were used to test the heterogeneity (Table 3), and no heterogeneity was observed in any of the genetic models.

Discussion

Current evidence indicates that progesterone plays a vital role in regulating female reproduction. The physiological role of progesterone is mediated by the progesterone receptor (PgR), which includes a total of 8 exons and 7 introns [48]. PgR-A and PgR-B are the two subtypes of PgR. The co-expression levels in most normal progesterone-targeted cells are similar. The balance between subtypes regulates the expression of many other genes. Abnormal expression of PgR-A or PgR-B causes a significant change in the ratio between subtypes, which leads to changes in the transmission of progesterone information, and these changes affect physiological functions and trigger a series of serious physiological consequences. The Alu insertion together with V660L and H770H is called PROGINS, which is an important polymorphism of the PgR gene. The Alu insertion affects the binding properties of receptors and hormones and induces amino acid changes, which cause female reproductive cancer.

Our meta-analysis included 30 studies with 25405 controls and 19253 female reproductive cancer cases. These studies examined the relationship between PgR gene PROGINS polymorphisms (Alu insertion and V660L) and female reproductive tract cancer. Our meta-analysis results demonstrated a significant association between PROGINS and female reproductive cancer, and PROGINS mutations increased the risk of female reproductive cancer. We also performed a sensitivity analysis to test the validity of the results, and the results of the meta-analysis were stable. The association between PgR mutations and female reproductive cancer varies between races. The meta-analysis of the dominant genetic model of the Alu-insertion polymorphism showed that women with T2 mutations had a significantly higher risk of developing female reproductive tract cancer than women with T1T1 genotypes in the general population. There was a significant association between Alu insertion and female reproductive cancer in whites (OR = 1.25, 95% CI = 1.01–1.56), but this association disappeared in Asians and Africans. The difference in correlation may be caused by several factors. First, the frequency of Alu insertion is different due to different ethnic groups, different ethnic groups of genetic backgrounds, different lifestyles, and different environmental factors. Second, there are few reports of the locus in Asians and Africans.

Although some studies showed linkage disequilibrium reactions between Alu insertions and V660L, V660L cannot replace Alu insertions in the analysis of genetic polymorphisms based on these meta-analysis data. The disease correlation between the two polymorphisms was different between ethnicities. Alu insertion was associated with female reproductive cancer incidence in white (Allele model: OR = 1.21, 95% CI = 1.00–1.45; Heterozygous model: OR = 3.44, 95% CI = 1.30–9.09) and Asian populations (Dominant model: OR = 3.12, 95% CI = 1.25–7.79), but the association disappeared for African and mixed racial groups.

Our results showed a significant relationship between V660L and the susceptibility to female reproductive cancer in the allele genetic model, dominant genetic model and heterozygous genetic model.

However, our research has some potential limitations. First, studies that met the inclusion criteria or were unpublished may have been missed. Second, although the control group was primarily selected from healthy people, some people did not mention their physiological status or whether they had benign disease. Finally, 26 studies included whites in the ethnic subgroup analysis, but few studies included Asians and Africans. Therefore, the differences in the associations between different ethnic subgroups should be carefully interpreted. In conclusion, although there are limitations, the results in this article provide significant evidence that PROGINS increases the risk of female reproductive cancer.

Supporting information

S1 Checklist

(DOCX)

S1 Table

(XLSX)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This study was funded by the Research Fund Project of the Education Bureau of Hunan Province, China (Grant No.19A419) with a grant of CNY 80,000. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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10 Feb 2022

PONE-D-21-14829Association of PROGINS PgR Polymorphism with susceptibility to female reproductive cancer: A meta-analysis based on 30 studiesPLOS ONE

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Reviewer #1: Yes

Reviewer #2: No

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5. Review Comments to the Author

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Reviewer #1: This study is a meta-analysis of the association between PgR gene polymorphisms and female reproductive cancer. This is a very interesting study, but I would like to point out the following points.

Major comments

1. Most of the papers that authors adopted for this meta-analysis are on cancers that occur in specific organs (breast, endometrial, and ovarian cancer) and gene polymorphisms in PgR. Does the role of PgR play a similar role in each of these organs? Is it justified to perform a meta-analysis together with female reproductive cancer without considering organ specificity?  For example, past epidemiological studies have shown that hormone replacement therapy, including progesterone, has different effects on breast and endometrial cancer risks.

2. From the viewpoint of Comment 1, the interpretation of the results of this study, which examined the relationship between female reproductive cancer and gene polymorphisms in PgR, is difficult to interpret and seems to have low clinical significance.  I think it is more clinically significant to focus on organ-specific meta-analysis and discuss whether there are any differences.

Minor moment

3. Abstract

In the Material and Method section, it is said that the analysis was performed for the race, cancer, and HWE groups, but the in section of Result, the description of the analysis result is only for race.

4. Figure 1

Check if the numbers in the study consort are correct.  The total number of excluded studies and the number of non-excluded studies do not match.

Reviewer #2: Detailed comments for the author's consideration

Review of the paper by �Chen Zhou, Xiangman Zou, Xiaosha Wen, Zifen Guo entitled: “Association of PROGINS PgR Polymorphism with susceptibility to female reproductive cancer: A metaanalysis based on 30 studies” The work presented is interesting in terms of demonstrating the association of PROGINS PgR Polymorphism with susceptibility to female reproductive cancer. The manuscript is well written and results are well described with proper statistics. The language is appropriate, technical and easy to read. However, I have some minor recommendations

Comment 1: The highlights of the manuscript should be written properly with more conclusive meaning.

Comment 2: The first sentence of the abstract is not properly written. It should be rewritten with proper meaning.

Comment 3: The first para of introduction section has 2020 data. Update the para with 2021/22 epidemological and incidence data.

Comment 4: In second para of introduction section there are some sentences related to estrogen which creates confusion. Remove the estrogen related sentences or If not rewrite the sentence with proper meaning. Additionally, in second para “vitro” should be replaced with “invitro”

Comment 5: Add some lines about PROGINS and its functions in para 3 of introduction section.

Comment 6: There are various spelling and grammatical mistakes such as “conformed” in materials and methods section. Kindly go through the whole manuscript to edit grammatical mistakes.

Comment 7: Manuscript contains old and outdated references, replace them with latest and updated references wherever possible.

**********

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Reviewer #1: No

Reviewer #2: No

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Attachment

Submitted filename: Comments PLOS ONE.doc

PLoS One. 2022 Jul 15;17(7):e0271265. doi: 10.1371/journal.pone.0271265.r002

Author response to Decision Letter 0


11 May 2022

Dear the editor and reviewers:

Thank you very much for giving us an opportunity to revise our manuscript (PONE-D-21-14829) titled Association of PROGINS PgR Polymorphism with susceptibility to female reproductive cancer: A meta-analysis based on 30 studies. We appreciate the positive and constructive comments and suggestions from the editor and reviewers, which significantly improved the quality of our manuscript. We have carefully revised the manuscript accordingly with all changes shown in red in the paper. Please see the detailed responses below.

Reviewers 1' Comments to Author

This study is a meta-analysis of the association between PgR gene polymorphisms and female reproductive cancer. This is a very interesting study, but I would like to point out the following points.

Comment 1: Most of the papers that authors adopted for this meta-analysis are on cancers that occur in specific organs (breast, endometrial, and ovarian cancer) and gene polymorphisms in PgR. Does the role of PgR play a similar role in each of these organs? Is it justified to perform a meta-analysis together with female reproductive cancer without considering organ specificity? For example, past epidemiological studies have shown that hormone replacement therapy, including progesterone, has different effects on breast and endometrial cancer risks.

RESPONSE: Thank you very much for your constructive suggestions. Progesterone and progesterone receptors (PgR) are essential for the development and cyclical regulation of hormone-responsive tissues including the breast and reproductive tract. We think it is reasonable to conduct a Meta-analysis on female reproductive cancers. Human is an organic whole, and the regulation of genes by genetic polymorphisms is holistic. As a steroid hormone, the effects of progesterone exerts on the female reproductive system are complicated.

The main subtypes of PgR are PgR-A and PgR-B mediating the main progesterone responses, but the roles of PgR-A and Pgr-B in different organs are not the same. PgR-A is essential for ovarian normal function in ovarian cancer, while its expression is decreased or lost in ovarian cancer. PgR-B has the functions of anti-proliferation (such as anti-aging and anti-apoptosis), playing a dominant role in ovarian cancer. In breast cancer, PgR has been shown to rapidly activate the Src/p21Ras/Erk, PI3K/Akt, and JAK/STAT pathways that contribute to the proliferative effect of progesterone in breast cancer cells, but unliganded PgR has been shown to suppress growth and inflammatory responses in breast cancer cells. The PgR status of endometrial tumors has been controversial. One of the previous studies showed the predominance of PgR-B in advanced endometrial tumors, but another study noted the loss of both subtypes in advanced endometrial cancers; additionally, a third study showed that only PgR-A was expressed in poorly differentiated endometrial cancer cell lines. At present, the imbalance between the expression of PgR-A and PgR-B is one of the pathogenesis of endometrial cancer.

Comment 2:From the viewpoint of Comment 1, the interpretation of the results of this study, which examined the relationship between female reproductive cancer and gene polymorphisms in PgR, is difficult to interpret and seems to have low clinical significance. I think it is more clinically significant to focus on organ-specific meta-analysis and discuss whether there are any differences.

RESPONSE: Thank you very much for the good advice. As to the data presented in this paper, the risk propensity for female reproductive cancers is the same as that for ovarian, breast, and endometrial cancers. The data in table 4 suggest that PROGINS gene polymorphisms may be associated with a slightly increased risk of ovarian, breast, and endometrial cancers.

Comment 3: Abstract,In the Material and Method section, it is said that the analysis was performed for the race, cancer, and HWE groups, but the in section of Result, the description of the analysis result is only for race.

RESPONSE: Thank you very much for the good advice. We added the analysis results of cancer and HWE groups to the Abstract.

Abstract: Subgroup analysis by cancer, PROGINS polymorphism increase the risk of cancer in the Allele model, Dominant mode and Heterozygous model, but the confidence interval for this result spanned 1 and was not statistically significant. At the same time, this sensitivity was also verified in studies with HWE greater than 0.5.

Comment 4: Figure 1,Check if the numbers in the study consort are correct.  The total number of excluded studies and the number of non-excluded studies do not match.

RESPONSE: Thank you very much for the good advice. We verified the data in Figure 1 and corrected this error.

Fig 1. Flowchart showing the meta-analysis literature screening process

Reviewers 2' Comments to Author:

The work presented is interesting in terms of demonstrating the association of PROGINS PgR Polymorphism with susceptibility to female reproductive cancer. The manuscript is well written and results are well described with proper statistics. The language is appropriate, technical and easy to read. However, I have some minor recommendations.

Comment 1: The highlights of the manuscript should be written properly with more conclusive meaning.

RESPONSE: Thank you very much for the good advice. We have refined the highlights.

Highlights

Alu insertion may be a susceptible factor for reproductive cancer in white and Asian populations, and the V660L polymorphism may be a susceptible factor for female reproductive cancer in African populations.

Comment 2: The first sentence of the abstract is not properly written. It should be rewritten with proper meaning.

RESPONSE: Thank you very much for the good advice. We rewrote this sentence.

Aims: The progesterone response of the nuclear progesterone receptor plays an important role in the female reproductive system.

Comment 3: The first para of introduction section has 2020 data. Update the para with 2021/22 epidemological and incidence data.

RESPONSE: Thank you very much for the good advice. We have updated the latest epidemiological data for 2022.

Despite extensive research to prevent cancer, cancer cases continue to increase sharply. Data from the American Cancer Society in 2022 predicts 1.9 million new cancer cases in 2022. More than 609,360 Americans die of cancer annually, which is equivalent to greater than 1,700 people dying of cancer daily [3].

Comment 4: In second para of introduction section there are some sentences related to estrogen which creates confusion. Remove the estrogen related sentences or If not rewrite the sentence with proper meaning. Additionally, in second para “vitro” should be replaced with “invitro”.

RESPONSE: Thank you very much for the good advice. We rewrote the sentence to clarify it and replaced the word.

Progesterone inhibits the proliferation of reproductive tract cells by excessive estrogen via the progesterone receptor (PgR) [4-6], and excessive estrogen stimulation increases the risk of female reproductive tract cancer [7].

Comment 5: Add some lines about PROGINS and its functions in para 3 of introduction section.

RESPONSE: Thank you very much for the good advice. We added the functions of PROGINS to the Introduction.

The PROGINS polymorphism of the human progesterone receptor diminishes the response to progesterone [12]. The PROGINS allele was significantly associated with decreased serum progesterone levels in patients with polycystic ovary syndrome (PCOS) [13].

Comment 6: There are various spelling and grammatical mistakes such as “conformed” in materials and methods section. Kindly go through the whole manuscript to edit grammatical mistakes.

RESPONSE: Thank you very much for the good advice. We carefully revised the sentences in the article, and we have updated and revised our manuscript through the language editing service from AJE (Verification Code: 0283-9E24-1846-6C24-A673). Certificate of language editing as follows:

Comment 7: Manuscript contains old and outdated references, replace them with latest and updated references wherever possible.

RESPONSE: Thank you very much for the good advice. We updated the current references, but the references the data extracted from could not be replaced.

Attachment

Submitted filename: Response to Reviewers.doc

Decision Letter 1

Elda Tagliabue

28 Jun 2022

Association of the PROGINS PgR polymorphism with susceptibility tofemale reproductive cancer: A meta-analysis of 30 studies

PONE-D-21-14829R1

Dear Dr. Guo,

After a careful assessment of the revised version of the manuscript by the Editor, we’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Elda Tagliabue

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Elda Tagliabue

7 Jul 2022

PONE-D-21-14829R1

Association of the PROGINS PgR polymorphism with susceptibility to female reproductive cancer: A meta-analysis of 30 studies

Dear Dr. Guo:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

Dr. Elda Tagliabue

Academic Editor

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Associated Data

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    Submitted filename: Response to Reviewers.doc

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