Associations of PD-1 and PD-L1 gene polymorphisms with cancer risk: a meta-analysis based on 50 studies

Results

Literature search and screening

The systematic search initially yielded 10081 potentially relevant articles through PubMed (n = 3488), Embase (n = 7504), and Cochrane Library (n = 1135) databases, and 4 additional records [31–34] were retrieved from other sources. After the elimination of 4325 duplicate references, 7804 additional publications were removed by screening the abstract and title. Of these, 6383 articles were reviews, meta-analysis, editorials, letters, and conference abstracts, while 983 articles were involved in animal or vitro studies. After careful review of the full texts, 388 studies were further excluded due to the following reasons: 229 studies focused on other SNPs of PD1/PD-L1, 116 studies were not related to cancer and 43 studies lacked of available data. Finally, 50 eligible publications were qualified for this meta-analysis [13, 26, 31–78]. The flow diagram showed the detailed literature search and selection process in Figure 1.

Figure 1. Flow chart of search strategy and study selection.

Characteristics and quality of studies

A total of 50 eligible articles embodying 122 studies were enrolled in the present analysis, which included 25 studies for PD-1.5, 17 studies for PD-1.9, 13 studies for PD-1.3, 15 studies for PD-1.1, 8 studies for rs7421861, 12 studies for PD-L1 rs4143815, 13 studies for PD-1.6, 9 studies for rs2890658, 3 studies for rs10815225, 3 studies for rs17718883, and 4 studies for rs2297136. Among these studies, twenty-six studies were conducted in China, thirteen in Iran, three in Turkey, two in Poland, two in Japan, one in Sweden, one in Czech, one in Brazil, and one in Saudi Arabian. Five studies were from Caucasian population, and forty-five studies were from Asian population. The control group of 19 studies were based on population, and 31 studies on hospital. Twenty-three reported gastrointestinal neoplasms including esophageal cancer (EC), gastric cancer (GC), hepatocellular carcinoma (HCC), and colorectal cancer (CRC). Ten studies investigated cervical cancer (CC), breast cancer (BC) and ovarian cancer (OC), six covered non-small cell lung cancer (NSCLC), and eleven studies involved other types of cancer, such as TC (thyroid cancer), Brain tumor, Melanoma, HNSCC (head and neck squamous cell carcinoma), Myeloma, BCC (basal cell carcinoma), Leukemia, RCC (renal cell carcinoma), AML (acute myelocytic leukemia) and UCC (urothelial cell carcinoma). Detailed characteristics of these studies are illustrated in Table 1 and Supplementary Table 1. All articles are of high quality because of the Newcastle-Ottawa Scale (NOS) score no less than 6 in Supplementary Table 2.

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

Author	Year	Country	Ethnicity	Type of cancer	Sample size case/control	Genotyping methods	Source of control	NOS
Emma L [26]	2010	Sweden	Caucasian	CC	1306/811	PCR-RFLP	PB	7
Haghshenas [35]	2011	Iran	Asian	BC	443/328	PCR-RFLP	PB	8
Hua Z [36]	2011	Chian	Asian	BC	490/ 512	PCR-RFLP	PB	8
Bayram S [37]	2012	Turkey	Asian	HCC	236/236	PCR–RFLP	HB	7
Mojtahedi Z [38]	2012	Iran	Asian	CRC	200/200	PCR–RFLP	PB	7
Li [39]	2013	China	Asian	HCC	271/318	TIANamp	PB	8
Yousefi AR [40]	2013	Iran	Asian	CRC	80/100	PCR-RFLP	HB	6
Savabkar S [41]	2013	Iran	Asian	GC	122/166	PCR–RFLP	HB	7
Wang WP [42]	2013	China	Asian	GC	205/393	Sequencing	HB	6
Chen YB [43]	2014	China	Asian	NSCLC	293/293	PCR-RFLP	HB	7
Qiu H [44]	2014	China	Asian	EC	629/686	PCR-LDR	HB	7
Yin L [45]	2014	China	Asian	NSCLC	324/330	PCR	PB	8
Cheng SS [46]	2015	China	Asian	NSCLC	288/300	PCR-RFLP	HB	6
Ge J [47]	2015	China	Asian	CRC	596/620	TaqMan	HB	7
Ma Y [48]	2015	China	Asian	NSCLC	528/600	PCR-RFLP	PB	9
Tang WF [49]	2015	China	Asian	EC	330/608	PCR-LDR	HB	7
Li XF [50]	2016	China	Asian	CC	256/250	PCR-RFLP	PB	8
Ren HT [51]	2016	China	Asian	BC	560/583	MassARRAY	PB	8
Haghshenas [52]	2016	Iran	Asian	TC	105/160	PCR-RFLP	PB	8
Zhou RM [53]	2016	China	Asian	EC	584/585	PCR-LDR	PB	9
Li Q [31]	2016	China	Asian	GC	101/141	PCR	HB	7
Tao [54]	2016	China	Asian	GC	350/500	Sequencing	HB	6
Du [55]	2017	China	Asian	NSCLC	320/199	Sequencing	HB	7
Zhou RM [56]	2017	China	Asian	EC	575/577	PCR-LDR	PB	9
Jahromi [57]	2017	Iran	Asian	Brain tumor	152/150	PCR-RFLP	PB	8
Li Y [58]	2017	China	Asian	OC	620/620	PCR-LDR	HB	7
Tan D [59]	2017	China	Asian	OC	164/170	qRT-PCR	PB	9
Tang WF [60]	2017	China	Asian	EC	1063/1677	PCR-LDR	HB	7
Cheng SG [32]	2017	China	Asian	HCC	123/141	PCR	HB	8
Wei L [33]	2017	China	Asian	OC	116/110	PCR	HB	7
Catalano [61]	2018	Czech	Caucasian	CRC	1424/1114	TaqMan	HB	7
Pirdelkhosh [62]	2018	Iran	Asian	NSCLC	206/173	PCR-RFLP	PB	8
Zhao YC [34]	2018	China	Asian	CRC	426/500	PCR-RFLP	HB	6
Shamsdin [63]	2018	Iran	Caucasian	CRC	76/73	PCR-RFLP	HB	6
Gabriela V [64]	2018	Brazil	Caucasian	Melanoma	250/250	PCR	PB	8
Fathi F [65]	2018	Iran	Asian	HNSCC	150/150	PCR-RFLP	HB	6
Xie [66]	2018	China	Asian	HCC	225/200	Sequencing	HB	7
Kasamatsu T [67]	2019	Japan	Asian	Myeloma	124/211	PCR-RFLP	PB	7
Fathi F [68]	2019	Iran	Asian	BCC	210/320	PCR-RFLP	HB	7
Ramzi [69]	2020	Iran	Asian	Leukemia	59/38	PCR-RFLP	HB	6
Karami S [70]	2020	Iran	Asian	BC	260/260	PCR-RFLP	HB	6
Demirci [71]	2020	Turkey	Asian	HCC	137/136	TaqMan	HB	7
Wagner W [13]	2020	Poland	Caucasian	RCC	237/260	TaqMan	PB	9
Zang B [72]	2020	China	Asian	EC	814/961	TaqMan	PB	9
Fathi F [73]	2021	Iran	Asian	BCC	210/220	PCR-RFLP	HB	6
Cevik M [74]	2021	Turkey	Caucasian	CRC	103/86	MassArray	HB	6
Al-Harbi [75]	2022	Saudi Arabian	Asian	CRC	100/100	TaqMan	HB	7
Wu [76]	2023	China	Asian	AML	285/342	MassArray	HB	7
Katarzyna [77]	2023	Poland	Caucasian	BC	30/30	TaqMan	HB	6
Hlaing [78]	2023	Japan	Asian	UCC	256/211	PCR-RFLP	HB	7
PB, Population-based; HB, Hospital-based; PCR-RFLP, Polymerase chain reaction-restriction fragment length polymorphism; ARMS-PCR, Amplification refractory mutation system-polymerase chain reaction; HWE, Hardy-Weinberg equilibrium; CC, cervical cancer; BC, breast cancer; HCC, hepatocellular carcinoma; CRC, colorectal cancer; TH, thyroid cancer; EC, esophageal cancer; OC, ovarian cancer; NSCLC, non-small cell lung cancer; RCC, renal cell carcinoma; BCC, basal cell carcinoma; AML, acute myelocytic leukemia.

Meta-analysis results of PD-1.5 (rs2227981) C/T polymorphism

A total of 25 studies with 7724 cases and 7320 controls were included in the meta-analysis to detect the association between PD-1.5 variation and cancer risk. The pooled ORs suggested no significant correlation between the PD-1.5 genotype and cancer susceptibility in all genetic models (T vs. C: OR = 0.99, 95% CI = 0.90-1.09, P = 0.807; TT vs. CC: OR = 0.93, 95% CI = 0.79-1.10, P = 0.386; CT vs. CC: OR = 1.05, 95% CI = 0.92-1.21, P = 0.476; TT+CT vs. CC: OR = 1.03, 95% CI = 0.90-1.17, P = 0.694; TT vs. CT+CC: OR = 0.92, 95% CI = 0.78-1.08, P = 0.288, Figure 2 and Table 2). Likewise, strong evidence of heterogeneity was found in each comparison, and then we conducted further subgroup analyses to determine the influence of confounding factors. These data showed that PD-1.5 was closely associated with risk of CC (T vs. C: OR = 0.83, 95% CI = 0.73-0.93, P = 0.002; TT vs. CC: OR = 0.69, 95% CI = 0.54-0.89, P = 0.004), GC (CT vs. CC: OR = 1.68, 95% CI = 1.04-2.72, P = 0.036; TT+CT vs. CC: OR = 1.66, 95% CI = 1.04-2.67, P = 0.035), NSCLC (T vs. C: OR = 0.83, 95% CI = 0.72-0.95, P = 0.009; TT vs. CC: OR = 0.65, 95% CI = 0.44-0.97, P = 0.036; TT+CT vs. CC: OR = 0.84, 95% CI = 0.71-0.99, P = 0.043), TC (T vs. C: OR = 2.12, 95% CI = 1.44-3.11, P = 0.000; TT vs. CC: OR = 3.47, 95% CI = 0.54-0.89, P = 0.004; CT vs. CC: OR = 2.48, 95% CI = 1.45-4.22, P = 0.001; TT+CT vs. CC: OR = 2.64, 95% CI = 1.59-4.38, P = 0.000), Brain tumor (T vs. C: OR = 1.85, 95% CI = 1.29-2.66, P = 0.001; TT vs. CC: OR = 2.57, 95% CI = 1.07-6.17, P = 0.035; CT vs. CC: OR = 2.19, 95% CI = 1.34-3.55, P = 0.001; TT+CT vs. CC: OR = 2.25, 95% CI = 1.42-3.56, P = 0.001), OC (T vs. C: OR = 0.84, 95% CI = 0.71-0.99, P = 0.036), AML (CT vs. CC: OR = 1.46, 95% CI = 1.04-2.05, P = 0.028; TT+CT vs. CC: OR = 1.41, 95% CI = 1.02-1.94, P = 0.036) and UCC (CT vs. CC: OR = 1.48, 95% CI = 1.01-2.19, P = 0.047). In stratified analysis by ethnicity, there was no remarkable correlation between the rs2227981 polymorphism and cancer risk in all genetic models, and so was it in subgroup analysis by source of controls and quality scores. The rs2227981 mutation was dramatically related to cancer risk in lager sample size (TT vs. CC: OR = 0.78, 95% CI = 0.61-1.00, P = 0.048; TT vs. CT+CC: OR = 0.80, 95% CI = 0.66-0.97, P = 0.021, Supplementary Table 3). It showed that heterogeneity existed in all genetic models of overall analysis, Asian, higher quality score, and BC. The random effect model was applied to make a reliable result.

Table 2. Results of meta-analysis in the PD-1 and PD-L1 gene polymorphisms.

SNP	Model	OR (95% CI)	P	I2(%)	P(H)	Effect model
PD-1.5 rs2227981C/T	Allelic (T vs. C)	0.99 (0.91, 1.09)	0.879	66.4	0.000	REM
	Homozygous (TT vs. CC)	0.92 (0.78, 1.08)	0.305	44.4	0.009	REM
	Heterozygous (CT vs. CC)	1.07 (0.93, 1.22)	0.350	69.3	0.000	REM
	Dominant (TT+CT vs. CC)	1.04 (0.91, 1.18)	0.568	69.2	0.000	REM
	Recessive (TT vs. CT+CC)	0.90 (0.77, 1.05)	0.167	46.9	0.006	REM
PD-1.9 rs2227982C/T	Allelic (T vs. C)	0.98 (0.89, 1.07)	0.629	56.5	0.002	REM
	Homozygous (TT vs. CC)	0.96 (0.77, 1.19)	0.693	64.6	0.000	REM
	Heterozygous (CT vs. CC)	0.98 (0.86, 1.11)	0.744	47.2	0.017	REM
	Dominant (TT+CT vs. CC)	0.98 (0.86, 1.11)	0.694	52.2	0.006	REM
	Recessive (TT vs. CT+CC)	0.97 (0.82, 1.15)	0.702	60.2	0.00	REM
PD-1.3 rs11568821G/A	Allelic (A vs. G)	0.93 (0.73, 1.19)	0.583	70.3	0.000	REM
	Homozygous (AA vs. GG)	1.33 (0.90, 1.97)	0.156	38.1	0.095	FEM
	Heterozygous (GA vs. GG)	0.83 (0.72, 0.96)	0.012*	36.7	0.089	FEM
	Dominant (AA+GA vs. GG)	0.90 (0.71, 1.13)	0.360	58.3	0.004	REM
	Recessive (AA vs. GA+GG)	1.34 (0.92, 1.96)	0.124	20.8	0.246	FEM
PD-1.1 rs36084323G/A	Allelic (A vs. G)	0.93 (0.78,1.10)	0.380	85.7	0.000	REM
	Homozygous (AA vs. GG)	1.14 (0.89, 1.47)	0.300	68.8	0.000	REM
	Heterozygous (GA vs. GG)	0.88 (0.72, 1.09)	0.247	76.4	0.000	REM
	Dominant (AA+GA vs. GG)	0.88 (0.70, 1.11)	0.294	82.9	0.000	REM
	Recessive (AA vs. GA+GG)	1.12 (0.93, 1.34)	0.224	59.6	0.004	REM
PD-1 rs7421861T/C	Allelic (C vs. T)	1.02 (0.89, 1.17)	0.734	73.7	0.000	REM
	Homozygous (CC vs. TT)	0.90 (0.75, 1.08)	0.246	18.3	0.285	FEM
	Heterozygous (CT vs. TT)	1.05 (0.88, 1.24)	0.582	70.3	0.001	REM
	Dominant (TT+CT vs. CC)	1.03 (0.87, 1.22)	0.717	72.3	0.001	REM
	Recessive (CC vs. CT+TT)	0.89 (0.77, 1.03)	0.107	5.6	0.387	FEM
PD-L1 rs4143815G/C	Allelic (C vs. G)	0.85 (0.72, 1.01)	0.063	84.2	0.000	REM
	Homozygous (CC vs. GG)	0.73 (0.52, 1.03)	0.072	82.6	0.000	REM
	Heterozygous (CG vs. GG)	0.78 (0.59, 1.04)	0.091	81.1	0.000	REM
	Dominant (CC+CG vs. GG)	0.76 (0.57, 1.03)	0.074	84.8	0.000	REM
	Recessive (CC vs. CG+GG)	0.86 (0.71, 1.04)	0.123	68.0	0.000	REM
PD-1.6 rs10204525A/G	Allelic (G vs. A)	0.98 (0.86, 1.11)	0.761	75.5	0.000	REM
	Homozygous (GG vs. AA)	0.98 (0.73, 1.32)	0.904	70.1	0.000	REM
	Heterozygous (GA vs. AA)	1.02 (0.88, 1.18)	0.770	61.0	0.002	REM
	Dominant (GG+GA vs. AA)	1.01 (0.86, 1.19)	0.898	70.8	0.000	REM
	Recessive (GG vs. GA+AA)	0.96 (0.79, 1.17)	0.673	57.5	0.005	REM
PD-L1 rs2890658A/C	Allelic (C vs. A)	1.03 (0.75, 1.42)	0.859	85.2	0.000	REM
	Homozygous (CC vs. AA)	0.91 (0.59, 1.41)	0.671	9.4	0.357	FEM
	Heterozygous (CA vs. AA)	1.14 (0.82, 1.57)	0.441	67.4	0.002	REM
	Dominant (CC+CA vs. AA)	1.11 (0.79, 1.56)	0.562	72.9	0.000	REM
	Recessive (CC vs. CA+AA)	0.81 (0.50, 1.32)	0.400	57.3	0.016	REM
PD-L1 rs10815225G/C	Allelic (C vs. G)	1.00 (0.69, 1.43)	0.957	73.9	0.022	REM
	Homozygous (CC vs. GG)	0.84 (0.41, 1.68)	0.613	36.5	0.207	FRM
	Heterozygous (CG vs. GG)	1.03 (0.61,1.77)	0.903	85.3	0.001	REM
	Dominant (CC+CG vs. GG)	1.01 (0.63, 1.63)	0.958	81.9	0.004	REM
	Recessive (CC vs. CG+GG)	0.80 (0.40, 1.62)	0.538	41.7	0.180	FRM
PD-L1 rs17718883C/G	Allelic (G vs. C)	0.07 (0.20, 0.25)	0.000*	85.1	0.022	REM
	Homozygous (GG vs. CC)	0.04 (0.01, 0.12)	0.000*	0.0	0.829	FEM
	Heterozygous (CG vs. CC)	0.07 (0.02, 0.30)	0.000*	84.4	0.002	REM
	Dominant (GG+CG vs. CC)	0.06 (0.02, 0.24)	0.000*	84.6	0.001	REM
	Recessive (GG vs. CG+CC)	0.06 (0.02, 0.20)	0.000*	0.0	0.855	FEM
PD-L1 rs2297136G/C	Allelic (C vs. G)	1.00 (0.75, 1.35)	0.982	71.4	0.015	REF
	Homozygous (CC vs. GG)	0.85 (0.45, 1.62)	0.624	58.8	0.065	REF
	Heterozygous (CG vs. GG)	1.04 (0.57, 1.90)	0.889	87.3	0.000	REF
	Dominant (CC+CG vs. GG)	1.03 (0.59, 1.41)	0.924	82.8	0.001	REF
	Recessive (CC vs. CG+GG)	0.86 (0.51, 1.44)	0.554	55.7	0.079	REF
P, P-value of Z-test for statistical significance; PH, P-value of Q-test for heterogeneity test. *P<0.05.

Figure 2. Forest plot for the association between PD-1.5 gene polymorphism and cancer risk under all the five models. For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs. (A) Allele model; (B) homozygote model; (C) heterozygote model; (D) dominant model; (E) recessive model.

Meta-analysis results of PD-1.9 (rs2227982) C/T polymorphism

Through the pooled analysis of genetic data of 6029 cases and 7310 controls in a total of 17 studies, of which 2 studies were performed in Caucasians, 15 studies were in Asians. Overall, there was no evident relation between the PD-1.9 and cancer risk (T vs. C: OR = 0.98, 95% CI = 0.89-1.07, P = 0.629; TT vs. CC: OR = 0.96, 95% CI = 0.77-1.19, P = 0.693; CT vs. CC: OR = 0.98, 95% CI = 0.86-1.11, P = 0.744; TT+CT vs. CC: OR = 0.98, 95% CI = 0.86-1.11, P = 0.694; TT vs. CT+CC: OR = 0.97, 95% CI = 0.82-1.15, P = 0.702, Figure 3 and Table 2). Interestingly, the PD-1.9 T-allele prominently reduced the risk of BC (T vs. C: OR = 0.85, 95% CI = 0.75-0.95, P = 0.004; TT vs. CC: OR = 0.72, 95% CI = 0.57-0.92, P = 0.007; CT vs. CC: OR = 0.74, 95% CI = 0.61-0.90, P = 0.002; TT+CT vs. CC: OR = 0.74, 95% CI = 0.61-0.88, P = 0.001) and AML (T vs. C: OR = 0.66, 95% CI = 0.53-0.83, P = 0.000; TT vs. CC: OR = 0.27, 95% CI = 0.15-0.48, P = 0.000; TT vs. CC+CT: OR = 0.26, 95% CI = 0.16-0.44, P = 0.000), whereas the variant was correlated with enhanced risk of EC (CT vs. CC: OR = 1.17, 95% CI = 1.02-1.34, P = 0.028; TT+CT vs. CC: OR = 1.14, 95% CI = 1.00-1.30, P = 0.047) and OC (T vs. C: OR = 1.55, 95% CI = 1.09-2.21, P = 0.016; TT+CT vs. CC: OR = 1.67, 95% CI = 1.07-2.59, P = 0.023, Supplementary Table 3). Stratified analyses by ethnicity, source of controls, quality scores and sample size revealed no significant associations with cancer risk in five genetic comparisons. Results of heterogeneity test showed that heterogeneity exists in all the genetic models, so the random effect model was applied to obtain a reliable result.

Figure 3. Forest plot for the association between PD-1.9 gene polymorphism and cancer risk under all the five models. For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs. (A) Allele model; (B) homozygote model; (C) heterozygote model; (D) dominant model; (E) recessive model.

Meta-analysis results of PD-1.3 (rs11568821) G/A polymorphism

A total of thirteen studies involving 2620 patients and 2733 controls examined the association of PD-1.3 with cancer predisposition. Overall, a notably decreased cancer risk was found in the heterozygous model (GA vs. GG: OR = 0.82, 95% CI = 0.71–0.95, P = 0.008, Figure 4 and Table 2). Similarly, the association remained statistically significant in Asian population (GA vs. GG: OR = 0.80, 95% CI = 0.69-0.93, P = 0.004), PB (A vs. G: OR = 0.83, 95% CI = 0.68-0.99, P = 0.042; GA vs. GG: OR = 0.79, 95% CI = 0.66-0.94, P = 0.009; TT+CT vs. CC: OR = 0.80, 95% CI = 0.67-0.95, P = 0.012) and high quality score (GA vs. GG: OR = 0.81, 95% CI = 0.67-0.98, P = 0.030; AA+GA vs. GG: OR = 0.82, 95% CI = 0.69-0.99, P = 0.039). However, the PD-1.3 variant evidently increased the risk of CRC (A vs. G: OR = 2.36, 95% CI = 1.54-3.61, P = 0.000; AA vs. GG: OR = 3.80, 95% CI = 1.77-8.18, P = 0.001; AA+GA vs. GG: OR = 2.60, 95% CI = 1.35-5.01, P = 0.004; AA vs. GG+GA: OR = 2.76, 95% CI = 1.44-5.27, P = 0.002). Moreover, the allelic, heterozygous and dominant models of PD-1.3 were remarkably linked with lower risk of BCC (A vs. G: OR = 0.61, 95% CI = 0.39-0.95, P = 0.028; GA vs. GG: OR = 0.58, 95% CI = 0.35-0.96, P = 0.035; AA+GA vs. GG: OR = 0.58, 95% CI = 0.36-0.94, P = 0.028, Supplementary Table 3). Subgroup analysis based on sample size manifested no remarkable association between PD-1.3 polymorphism and cancer risk in any genetic models. It showed that heterogeneity existed in the allelic and domain models of overall group and Asian, but no heterogeneity was found in NSCLC subgroup.

Figure 4. Forest plot for the association between PD-1.3 gene polymorphism and cancer risk under all the five models. For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs. (A) Allele model; (B) homozygote model; (C) heterozygote model; (D) dominant model; (E) recessive model.

Meta-analysis results of PD-1.1 (rs36084323) G/A polymorphism

Fifteen studies with 5693 cases and 6749 controls were qualified for the association between PD-1.1 SNP and cancer predisposition. Among these eligible studies, four studies were from the Caucasians, and eleven studies from Asians. The pooled analysis disclosed no relevance between PD-1.1 variation and cancer risk (A vs. G: OR = 0.93, 95% CI = 0.78-1.10, P = 0.380; AA vs. GG: OR = 1.14, 95% CI = 0.89-1.47, P = 0.300; GA vs. GG: OR = 0.88, 95% CI = 0.72-1.09, P = 0.247; AA+GA vs. GG: OR = 0.88, 95% CI = 0.70-1.11, P = 0.294; AA vs. GA+GG: OR = 1.12, 95% CI = 0.93-1.34, P = 0.224, Figure 5 and Table 2). The carriers with PD-1.1 A-allele was slightly related to increased risk.of BC (GA vs. GG: OR = 1.42, 95% CI = 1.04-1.93, P = 0.026; AA+GA vs. GG: OR = 1.41, 95% CI = 1.06-1.89, P = 0.020) and OC (AA vs. GA+GG: OR = 1.50, 95% CI = 1.18-1.91 P = 0.185). There was a positive relevance between the PD-1.1 variant and cancer predisposition in the Asian descents (AA vs. GG: OR = 1.18, 95% CI = 1.02-1.38, P = 0.032; AA vs. GA+GG: OR = 1.12, 95% CI = 1.01-1.25, P = 0.039, Supplementary Table 3), indicating that the PD-1.1varant might serve as a risk factor in Asians. Not only that, further stratification analyses by type of cancer, source of control, quality score and sample size also revealed similar results. Heterogeneity was found to be present in all genetic models, so a random effect pattern was selected.

Figure 5. Forest plot for the association between PD-1.1 gene polymorphism and cancer risk under all the five models. For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs. (A) Allele model; (B) homozygote model; (C) heterozygote model; (D) dominant model; (E) recessive model.

Meta-analysis results of PD-1 rs7421861 T/C polymorphism

Eight eligible studies with 4632 patients and 5873 controls reported association of PD-1 rs7421861 polymorphism with cancer risk in our study. In overall analysis, no significant association with cancer susceptibility was found (C vs. T: OR = 1.02, 95% CI = 0.89-1.17, P = 0.734; CC vs. TT: OR = 0.90, 95% CI = 0.75-1.24, P = 0.246; CT vs. TT: OR = 1.05, 95% CI = 0.88-1.24, P = 0.582; TT+CT vs. TT: OR = 1.07, 95% CI = 0.91-1.27, P = 0.717; CC vs. CT+TT: OR = 0.89, 95% CI = 0.77-1.03, P = 0.107, Figure 6 and Table 2). And then, we did not detect the relationship between the rs7421861 variation and cancer risk in subgroups of ethnicity, source of control, quality score and sample size. The heterozygote and dominant models of rs7421861 were significantly correlated with enhanced risk of BC (CT vs. TT: OR = 1.42, 95% CI = 1.04-1.93, P = 0.026; TT+CT vs. TT: OR = 1.41, 95% CI = 1.06-1.89, P = 0.020) and OC (CC vs. CT+TT: OR = 1.50, 95% CI = 1.18-1.91, P = 0.001 Supplementary Table 3). As heterogeneity of the rs7421861 existed in allele, heterozygote and dominant models, the random effects model was selected in the above models.

Figure 6. Forest plot for the association between rs7421861 gene polymorphism and cancer susceptibility under all the five models. For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs. (A) Allele model; (B) homozygote model; (C) heterozygote model; (D) dominant model; (E) recessive model.

Meta-analysis results of PD-L1 rs4143815 G/C polymorphism

A total of 12 eligible studies embodying 4008 cases and 4147 controls were examined for correlation of PD-L1 rs4143815 with the risk of cancer. Overall, there was no statistically significant association between the rs4143815 SNP and cancer risk in all genetic models (C vs. G: OR = 0.85, 95% CI = 0.72-1.01, P = 0.063; CC vs. GG: OR = 0.73, 95% CI = 0.52-1.03, P = 0.072; CG vs. GG: OR = 0.78, 95% CI = 0.59-1.04, P = 0.091; CC+CG vs. GG: OR = 0.76, 95% CI = 0.57-1.03, P = 0.074; CC vs. CG+GG: OR = 0.86, 95% CI = 0.71-1.04, P = 0.123, Figure 7 and Table 2). When stratified analysis was performed by ethnicity, we identified no significant relevance. According to subgroup analyses by quality score, source of control and sample size, there was no dramatic relationship between the rs4143815 polymorphism and cancer risk. Intriguingly, the rs4143815 mutation was markedly associated with risk of GC (C vs. G: OR = 0.66, 95% CI = 0.45-0.99, P = 0.045; CC vs. GG: OR = 0.44, 95% CI = 0.24-0.81, P = 0.008; CG vs. GG: OR = 0.51, 95% CI = 0.29-0.92, P = 0.025; CC+CG vs. GG: OR = 0.49, 95% CI = 0.28- 0.85, P = 0.012), OC (C vs. G: OR = 0.65, 95% CI = 0.48-0.88, P = 0.005; CC vs. GG: OR = 0.43, 95% CI = 0.23-0.79, P = 0.006; CC vs. GG+CG: OR = 0.50, 95% CI = 0.30-0.83, P = 0.007), HCC (CC vs. GG: OR = 0.46, 95% CI = 0.21-0.99, P = 0.047; CG vs. GG: OR = 0.42, 95% CI = 0.28-0.64, P = 0.000; CC+CG vs. GG: OR = 0.43, 95% CI = 0.29-0.63, P = 0.000) and BC (CC vs. GG: OR = 1.93, 95% CI = 1.04-3.57, P = 0.037; CG vs. GG: OR = 2.45, 95% CI = 1.37-4.37, P = 0.003; CC+CG vs. GG: OR = 2.25, 95% CI = 1.28-3.95, P = 0.005, Supplementary Table 3). These data with high heterogeneity applied the random-effect model for quantitative synthesis.

Figure 7. Forest plot for the association between PD-L1 rs4143815 gene polymorphism and cancer susceptibility under all the five models. For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs. (A) Allele model; (B) homozygote model; (C) heterozygote model; (D) dominant model; (E) recessive model.

Meta-analysis results of PD-1.6 (rs10204525) A/G polymorphism

By integrating quantitatively allele or genotype distribution of 5528 patients and 6875 controls, we did not discover any significant relationship between the PD-1.6 SNP and cancer risk in five genetic comparisons (G vs. A: OR = 0.98, 95% CI = 0.86-1.11, P = 0.761; GG vs. AA: OR = 0.98, 95% CI = 0.73-1.32, P = 0.904; GA vs. AA: OR = 1.02, 95% CI = 0.88-1.18, P = 0.861; GG+GA vs. AA: OR = 1.01, 95% CI = 0.86-1.19, P = 0.898; GG vs. GA+AA: OR = 0.96, 95% CI = 0.79-1.17, P = 0.673, Figure 8 and Table 2). As shown in Supplementary Table 3, the PD-1.6 variant was not dramatically associated with cancer susceptibility in stratified analyses by ethnicity, source of control, quality score and sample size. Based on subgroup analysis by type of cancer, the PD-1.6 polymorphism remarkably elevated the risk of AML (G vs. A: OR = 1.34, 95% CI = 1.06-1.71, P = 0.017; GA vs. AA: OR = 1.49, 95% CI = 1.06-2.09, P = 0.020; GG+GA vs. AA: OR = 1.52, 95% CI = 1.10-2.09, P = 0.011, Supplementary Table 3). Heterogeneity results indicated that heterogeneity nearly existed in all genetic models.

Figure 8. Forest plot for the association between PD-1.6 gene polymorphism and cancer susceptibility under all the five models. For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs. (A) Allele model; (B) homozygote model; (C) heterozygote model; (D) dominant model; (E) recessive model.

Meta-analysis results of PD-L1 rs2890658 A/C, rs10815225 G/C, rs17718883 C/G, and rs2297136 A/G polymorphisms

Relationships of PD-L1 rs2890658, rs10815225, rs17718883, and rs2297136 with cancer risk were examined in 9 studies, 3 studies, 3 studies, and 4 studies, respectively. All studies about these four SNPs are conducted in Asian population (Supplementary Figure 1). In general, an obvious association between PD-L1 rs17718883 SNP and lower cancer risk was discovered in all genetic models (G vs. C: OR = 0.07, 95% CI = 0.20-0.25, P = 0.000; GG vs. CC: OR = 0.04, 95% CI = 0.01-0.12, P = 0.000; GC vs. CC: OR = 0.07, 95% CI = 0.02-0.30, P = 0.000; GG+GC vs. CC: OR = 0.06, 95% CI = 0.02-0.24, P = 0.000; GG vs. GC+CC: OR = 0.06, 95% CI = 0.02-0.20, P = 0.000, Table 2). Similar results were detected in subgroups of Asian, PB, small sample size, low quality score (G vs. C: OR = 0.12, 95% CI = 0.04-0.35, P = 0.000; GG vs. CC: OR = 0.05, 95% CI = 0.01-0.16, P = 0.000; GC vs. CC: OR = 0.12, 95% CI = 0.03-0.48, P = 0.000; GG+GC vs. CC: OR = 0.10, 95% CI = 0.03-0.36, P = 0.000; GG vs. GC+CC: OR = 0.07, 95% CI = 0.02-0.24, P = 0.000) and high quality score (G vs. C: OR = 0.01, 95% CI = 0.00-0.08, P = 0.000; GG vs. CC: OR = 0.02, 95% CI = 0.00-0.32, P = 0.006). However, we did not detect any associations between other three SNPs and risk of cancer in subgroup analyses by ethnicity, sample size, source of control and quality scores.

Results demonstrated that PD-L1 rs2890658 was dramatically correlated with the lower risk of HCC (C vs. A: OR = 0.74, 95% CI = 0.55-1.00, P = 0.046) and BC (C vs. A: OR = 0.53, 95% CI = 0.40-0.71, P = 0.000; CC vs. AA+CA: OR = 0.40, 95% CI = 0.28-0.57, P = 0.000), while the variant notably enhanced the risk of NSCLC (C vs. A: OR = 1.72, 95% CI = 1.39-2.13, P = 0.000; CA vs. AA: OR = 1.74, 95% CI = 1.37-2.19, P = 0.000). The rs10815225 variant significantly decreased the risk of GC (C vs. G: OR = 0.65, 95% CI = 0.45-0.96, P = 0.028; GC vs. GG: OR = 0.57, 95% CI = 0.38-0.85, P = 0.006; CC+GC vs. GG: OR = 0.60, 95% CI = 0.40-0.89, P = 0.0011). Furthermore, the rs17718883 was remarkably correlative with reduced HCC (G vs. C: OR = 0.03, 95% CI = 0.01-0.23, P = 0.001; GG vs. CC: OR = 0.03, 95% CI = 0.01-1.13, P = 0.000; GC vs. CC: OR = 0.04, 95% CI = 0.01-0.15, P = 0.000; GG+GC vs. CC: OR = 0.03, 95% CI = 0.01-0.16, P = 0.000; GG vs. CC+GC: OR = 0.05, 95% CI = 0.02-0.20, P = 0.000) and GC risk (G vs. C: OR = 0.20, 95% CI = 0.11-0.36, P = 0.000; GG vs. CC: OR = 0.06, 95% CI = 0.01-0.43, P = 0.005; GC vs. CC: OR = 0.24, 95% CI = 0.12-0.48, P = 0.000; GG+GC vs. CC: OR = 0.19, 95% CI = 0.10-0.37, P = 0.000; GG vs. CC+GC: OR = 0.08, 95% CI = 0.01-0.60, P = 0.014). As for PD-L1 rs2297136, the mutant was closely related to NSCLC (C vs. G: OR = 1.30, 95% CI = 1.00-1.70, P = 0.048; GC vs. GG: OR = 2.29, 95% CI = 1.56-3.36, P = 0.000; CC+GC vs. GG: OR = 2.09, 95% CI = 1.43-3.04, P = 0.000; CC vs. GG+GC: OR = 0.44, 95% CI = 0.20-0.97, P = 0.042) and HCC risk (C vs. G: OR = 0.68, 95% CI = 0.49-0.93, P = 0.017; CC vs. GG: OR = 0.39, 95% CI = 0.18-0.85, P = 0.018; GC vs. GG: OR = 0.24, 95% CI = 0.12-0.48, P = 0.000; CC+GC vs. GG: OR = 0.19, 95% CI = 0.10-0.37, P = 0.000; CC vs. GG+GC: OR = 0.08, 95% CI = 0.01-0.60, P = 0.014, Supplementary Table 3).

Sensitivity analyses and publication bias

Sensitivity analysis was applied to detect individual study’s influence on the composite results by sequentially removing single eligible study and no significant change was observed in certain models, suggesting the credibility of our research results (Figure 9 and Supplementary Figure 2). The Begg’s funnel plot and Egger’s test were applied to assess the potential publication bias in this meta-analysis. Except for the PD-1.5, most of the funnel plots were symmetrical distribution, indicating absence of publication bias (Table 3, Figure 10 and Supplementary Figure 3).

Figure 9. Analyses of the influence of a single study on the total combined OR in the dominant model. (A) PD-1.5 polymorphism; (B) PD-1.9 polymorphism; (C) PD-1.3 polymorphism; (D) PD-1.1 polymorphism; (E) PD-1 rs7421861 polymorphism; (F) PD-L1 rs4143815 polymorphism.

Table 3. Publication bias of various models for PD1 and PD-L1 gene polymorphisms.

Variables	Allelic		Homozygous		Heterozygous		Dominant		Recessive
	P B	PE	P B	PE	P B	PE	P B	PE	P B	PE
PD-1.5 rs2227981C/T	0.011*	0.015*	0.071	0.022*	0.032*	0.033*	0.032*	0.029	0.091	0.014*
PD-1.9 rs2227982C/T	0.893	0.777	0.827	0.810	0.685	0.670	0.620	0.655	0.743	0.843
PD-1.3 rs11568821G/A	0.945	0.852	0.592	0.017*	0.631	0.400	0.837	0.436	0.592	0.005*
PD-1.1 rs36084323G/A	0.198	0.148	0.631	0.330	0.428	0.189	0.428	0.184	0.631	0.391
PD-1 rs7421861T/C	0.902	0.739	0.711	0.492	0.174	0.018*	0.108	0.018*	0.711	0.119
PD-L1 rs4143815G/C	0.732	0.563	1.000	0.879	0.945	0.568	1.000	0.607	0.537	0.502
PD-1.6 rs10204525A/G A/Grs10204525A/G	0.373	0.253	0.244	0.322	0.244	0.496	0.304	0.496	0.064	0.059
PD-L1 rs2890658A/C	0.711	0.611	1.000	0.609	0.902	0.309	0.902	0.330	0.902	0.443
PD-L1 rs10815225G/C	1.000	0.679	0.296	0.615	1.000	0.691	1.000	0.690	0.296	0.614
PD-L1 rs17718883C/G	0.296	0.490	1.000	0.687	0.296	0.377	0.296	0.447	1.000	0.687
PD-L1 rs2297136G/C	0.308	0.268	1.000	0.754	0.308	0.210	0.734	0.218	0.734	0.279
P B, P-value of Begg’s rank correlation test; PE, P-value of Egger’s linear regression test. *P<0.05.

Figure 10. Begg’s funnel plot and Egger’s linear regression test for the publication biases under the dominant model. (A) Begg’s test for PD-1.5 polymorphism; (B) Egger’s test for PD-1.5 polymorphism; (C) Begg’s test for PD-1.9 polymorphism; (D) Egger’s test for PD-1.9 polymorphism.
(E) Begg’s test for PD-1.3 polymorphism; (F) Egger’s test for PD-1.3 polymorphism; (G) Begg’s test for PD-1.1 polymorphism; (H) Egger’s test for PD-1.1 polymorphism; (I) Begg’s test for PD-1 rs7421861 polymorphism; (J) Egger’s test for PD-1 rs7421861 polymorphism; (K) Begg’s test for PD-L1 rs4143815 polymorphism; (L) Egger’s test for PD-L1 rs4143815 polymorphism.

FPRP results

We investigated determinants of FPRP across a range of probabilities to determine whether a given relationship of PD-1 and PD-L1 SNPs and cancer predisposition is deserving of attention or is noteworthy. Table 4 represents the calculated FPRP values for the main evident findings in this meta-analysis. With the assumption of a prior probability of 0.25, the FPRP values were less than 0.2, implying the observed correlations were significant. The heterozygote model of PD-1.3 was related to cancer risk, as well as the allele model of PD-L1 rs4143815. Similarly, with a prior probability of 0.25, the allele, homozygote, dominant and recessive models of PD-L1rs17718883 was notably associated with cancer risk (P < 0.2, Table 4).

Table 4. False-positive report probability analysis of the noteworthy results.

SNP	Genetic model	OR (95% CI)	P	Power	Prior probability
					0.25	0.1	0.01	0.001	0.0001
PD-1.5 rs2227981C/T	Allele	0.99 (0.91, 1.09)	0.838	1.000	0.715	0.883	0.988	0.999	1.000
	Homozygote	0.92 (0.78, 1.08)	0.308	1.000	0.480	0.735	0.968	0.997	1.000
	Heterozygote	1.07 (0.93, 1.22)	0.312	1.000	0.484	0.737	0.969	0.997	1.000
	Dominant	1.04 (0.91, 1.18)	0.543	1.000	0.620	0.830	0.982	0.998	1.000
	Recessive	0.90 (0.77, 1.05)	0.308	1.000	0.480	0.735	0.968	0.997	1.000
PD-1.9 rs2227982C/T	Allele	0.98 (0.89, 1.07)	0.652	1.000	0.662	0.854	0.985	0.998	1.000
	Homozygote	0.96 (0.77, 1.19)	0.709	1.000	0.680	0.865	0.986	0.999	1.000
	Heterozygote	0.98 (0.86, 1.11)	0.756	1.000	0.694	0.872	0.987	0.999	1.000
	Dominant	0.98 (0.86, 1.11)	0.756	1.000	0.694	0.872	0.987	0.999	1.000
	Recessive	0.97 (0.82, 1.15)	0.726	1.000	0.685	0.867	0.986	0.999	1.000
PD-1.3 rs11568821G/A	Allele	0.93 (0.73, 1.19)	0.564	1.000	0.629	0.835	0.982	0.998	1.000
	Homozygote	1.33 (0.90, 1.97)	0.155	0.979	0.322	0.587	0.940	0.994	0.999
	Heterozygote	0.83 (0.72, 0.96)	0.012	1.000	0.035*	0.098*	0.545	0.923	0.992
	Dominant	0.90 (0.71, 1.13)	0.364	1.000	0.522	0.766	0.973	0.997	0.997
	Recessive	1.34 (0.92, 1.96)	0.131	0.980	0.287	0.547	0.930	0.993	0.999
PD-1.1 rs36084323G/A	Allele	0.93 (0.78, 1.10)	0.397	1.000	0.543	0.781	0.975	0.997	1.000
	Homozygote	1.14 (0.89, 1.47)	0.312	1.000	0.484	0.738	0.969	0.997	1.000
	Heterozygote	0.88 (0.72, 1.09)	0.242	1.000	0.420	0.685	0.982	0.998	1.000
	Dominant	0.88 (0.70, 1.11)	0.281	1.000	0.457	0.716	0.965	0.996	1.000
	Recessive	1.12 (0.93, 1.34)	0.216	1.000	0.393	0.660	0.955	0.995	1.000
PD-1 rs7421861T/C	Allele	1.02 (0.89, 1.17)	0.778	1.000	0.480	0.735	0.968	0.997	1.000
	Homozygote	0.90 (0.75, 1.08)	0.250	0.996	0.430	0.693	0.961	0.996	1.000
	Heterozygote	1.05 (0.88, 1.24)	0.565	1.000	0.629	0.836	0.982	0.998	1.000
	Dominant	1.07 (0.91, 1.27)	0.439	1.000	0.568	0.798	0.978	0.998	1.000
	Recessive	0.89 (0.77, 1.03)	0.118	1.000	0.261	0.515	0.921	0.992	0.999
PD-L1 rs4143815G/C	Allele	0.85 (0.72, 1.01)	0.065	1.000	0.163*	0.368	0.865	0.985	0.998
	Homozygote	0.73 (0.52, 1.03)	0.358	1.000	0.518	0.763	0.973	0.997	1.000
	Heterozygote	0.78 (0.59, 1.04)	0.217	1.000	0.395	0.662	0.956	0.995	1.000
	Dominant	0.76 (0.57, 1.03)	0.190	1.000	0.363	0.631	0.950	0.995	0.999
	Recessive	0.86 (0.71, 1.04)	0.880	1.000	0.706	0.878	0.988	0.999	1.000
PD-1.6 rs10204525A/G	Allele	0.98 (0.86, 1.11)	0.751	1.000	0.692	0.871	0.987	0.999	1.000
	Homozygote	0.98 (0.73, 1.32)	0.894	1.000	0.728	0.889	0.989	0.999	1.000
	Heterozygote	1.02 (0.88, 1.18)	0.790	1.000	0.703	0.877	0.987	0.999	1.000
	Dominant	1.01 (0.86, 1.19)	0.905	1.000	0.731	0.891	0.989	0.999	1.000
	Recessive	0.96 (0.79, 1.17)	0.686	1.000	0.673	0.861	0.985	0.999	1.000
PD-L1 rs2890658A/C	Allele	1.03 (0.75, 1.42)	0.857	1.000	0.720	0.885	0.988	0.999	1.000
	Homozygote	0.91 (0.59, 1.41)	0.673	0.996	0.670	0.859	0.985	0.999	1.000
	Heterozygote	1.14 (0.82, 1.57)	0.422	1.000	0.559	0.492	0.977	0.998	1.000
	Dominant	1.11 (0.79, 1.56)	0.548	1.000	0.622	0.831	0.982	0.998	1.000
	Recessive	0.81 (0.50, 1.32)	0.398	0.974	0.551	0.786	0.976	0.998	1.000
PD-L1 rs10815225G/C	Allele	1.00 (0.69, 1.43)	0.957	1.000	0.742	0.896	0.990	0.999	1.000
	Homozygote	0.84 (0.41, 1.68)	0.622	0.929	0.668	0.858	0.985	0.999	1.000
	Heterozygote	1.03 (0.61,1.77)	0.914	0.992	0.735	0.892	0.989	0.999	1.000
	Dominant	1.01 (0.63, 1.63)	0.967	0.997	0.744	0.897	0.990	0.999	1.000
	Recessive	0.80 (0.40, 1.62)	0.553	0.904	0.640	0.842	0.983	0.998	1.000
PD-L1 rs17718883C/G	Allele	0.07 (0.02, 0.25)	0.000	0.001	0.093*	0.236	0.772	0.972	0.997
	Homozygote	0.04 (0.01, 0.12)	0.000	0.000	0.008*	0.025*	0.218	0.738	0.966
	Heterozygote	0.07 (0.02, 0.30)	0.001	0.000	0.202	0.432	0.893	0.988	0.999
	Dominant	0.06 (0.02, 0.24)	0.000	0.000	0.133*	0.315	0.835	0.981	0.998
	Recessive	0.06 (0.02, 0.20)	0.000	0.000	0.048*	0.131*	0.623	0.943	0.994
PD-L1 rs2297136G/C	Allele	1.00 (0.75, 1.35)	0.949	1.000	0.740	0.895	0.989	0.999	1.000
	Homozygote	0.85 (0.45, 1.62)	0.621	0.947	0.663	0.855	0.985	0.998	1.000
	Heterozygote	1.04 (0.57, 1.90)	0.898	0.983	0.733	0.892	0.989	0.999	1.000
	Dominant	1.03 (0.59, 1.41)	0.854	1.000	0.719	0.885	0.988	0.999	1.000
	Recessive	0.86 (0.51, 1.44)	0.566	0.980	0.634	0.839	0.983	0.998	1.000
*P < 0.2.

Abbreviations

CI: confidence interval; GWAS: Genome-Wide Association Studies; GWAS: genome-wide association studies; SNPs: single nucleotide polymorphism; APCs: antigen-presenting cells; HR: hazardous ratio; HWE: Hardy-Weinberg equilibrium; NOS: Newcastle-Ottawa scale; OR: odds ratio; SE: standard error; SNP: single nucleotide polymorphism; PDCD1: programmed cell death 1; PD-L1: programmed death-1 and its ligand-1; BC: breast cancer; NSCLC: non-small cell lung cancer; HCC: hepatocellular carcinoma; GC: gastric cancer; CRC: colorectal cancer; HNSCC: head and neck squamous cell carcinomas; TH: thyroid cancer; EC: esophageal cancer; OC: ovarian cancer; CC: cervical cancer; RCC: renal cell carcinoma; BCC: basal cell carcinoma; AML: acute myelocytic leukemia; UCC: urothelial cell carcinoma.

Author Contributions

Maoquan Yang and Qiqi Jiang conceptualized and designed the study. Maoquan Yang, Yan Liu, and Shuangshuang Zheng were responsible for the literature search and data extraction. Maoquan Yang and Yan Liu were responsible for the quality assessment. Peizhen Geng, Yikuan Feng, Tianhao He, and Linan Lu conducted statistical analysis and prepared the figures and tables. Maoquan Yang, Peizhen Geng and Yikuan Feng performed FPRP analysis and improved the revised content. All authors read and approved the manuscript.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Funding

The study was supported by Weifang Science and Technology Development Project (No.2018YX046).

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