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

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) [4-6], 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 [14-16]. 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) [8,18,19,21-47]. 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.

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’stest 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 3

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

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.

(DOCX)

Click here for additional data file.

(XLSX)

Click here for additional data file.

10 Feb 2022

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Elda Tagliabue

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please include your tables as part of your main manuscript and remove the individual files. Please note that supplementary tables (should remain/ be uploaded) as separate "supporting information" files

3. Please note that according to our submission guidelines (http://journals.plos.org/plosone/s/submission-guidelines), outmoded terms and potentially stigmatizing labels should be changed to more current, acceptable terminology. For example: “Caucasian” should be changed to “white” or “of [Western] European descent” (as appropriate).

4. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Whilst you may use any professional scientific editing service of your choice, PLOS has partnered with both American Journal Experts (AJE) and Editage to provide discounted services to PLOS authors. Both organizations have experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. To take advantage of our partnership with AJE, visit the AJE website (http://aje.com/go/plos) for a 15% discount off AJE services. To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services.  If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free.

Upon resubmission, please provide the following:

The name of the colleague or the details of the professional service that edited your manuscript

A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)

A clean copy of the edited manuscript (uploaded as the new *manuscript* file)”"

5. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

This study is partially funded by the Natural Science Foundation of Hunan Province (No.2018JJ2350) and the key project of Education Department of Hunan Province (No.19A419).

Please provide an amended statement that declares *all* the funding or sources of support (whether external or internal to your organization) received during this study, as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now.  Please also include the statement “There was no additional external funding received for this study.” in your updated Funding Statement.

Please include your amended Funding Statement within your cover letter. We will change the online submission form on your behalf.

6. Thank you for stating the following in the Acknowledgments/ Funding Section of your manuscript:

This study is partially funded by the Natural Science Foundation of Hunan Province (No.2018JJ2350) and the key project of Education Department of Hunan Province (No.19A419).

We note that you have provided additional information within the Acknowledgements Section that is not currently declared in your Funding Statement. Please note that funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

NO - Include this sentence at the end of your statement: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

7. Please amend your list of authors on the manuscript to ensure that each author is linked to an affiliation. Authors’ affiliations should reflect the institution where the work was done (if authors moved subsequently, you can also list the new affiliation stating “current affiliation:….” as necessary).

8. Please amend either the abstract on the online submission form (via Edit Submission) or the abstract in the manuscript so that they are identical.

9. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please move it to the Methods section and delete it from any other section. Please ensure that your ethics statement is included in your manuscript, as the ethics statement entered into the online submission form will not be published alongside your manuscript.

10. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

11. We note that this manuscript is a systematic review or meta-analysis; our author guidelines therefore require that you use PRISMA guidance to help improve reporting quality of this type of study. Please upload copies of the completed PRISMA checklist as Supporting Information with a file name “PRISMA checklist”.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

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.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: Comments PLOS ONE.doc

Click here for additional data file.

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.

Submitted filename: Response to Reviewers.doc

Click here for additional data file.

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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.

Kind regards,

Elda Tagliabue

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

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.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Elda Tagliabue

Academic Editor

PLOS ONE