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. 2022 Jun 8;12:816270. doi: 10.3389/fonc.2022.816270

Perineural Invasion Is a Significant Indicator of High Malignant Degree and Poor Prognosis in Esophageal Cancer: A Systematic Review and Meta-Analysis

Liuyang Bai 1,†, Liangying Yan 1,†, Yaping Guo 1,2,3, Luyun He 1,2,3, Zhiyan Sun 4, Wenbo Cao 1,2,3, Jing Lu 1,2,3, Saijun Mo 1,2,3,*
PMCID: PMC9213664  PMID: 35756642

Abstract

Background

Perineural invasion (PNI) is a malignant metastatic mode of tumors and has been reported in many tumors including esophageal cancer (EC). However, the role of PNI in EC has been reported differently. This systematic review and meta-analysis aims to focus on the role of PNI in EC.

Methods

Eight databases of CNKI, VIP, Wanfang, Scopus, Wiley, ISI, PubMed, and EBSCO are used for literature search. The association of PNI with gender, pathological stages of T and N (pT and pN), lymphovascular invasion (LVI), lymph node metastasis, 5-year overall survival (OS), and 5-year disease-free survival (DFS) was examined in the meta-analysis by Revman5.0 Software. The pooled OR/HR and 95% CI were used to assess the risk and prognostic value.

Results

Sixty-nine published studies were screened for analysis of PNI in EC. The incidence of PNI in esophageal squamous carcinoma (ESCC) and esophageal adenocarcinoma (EAC) was different, but not statistically significant (p > 0.05). The PNI-positive patients had a significantly higher risk of pT stage (OR = 3.85, 95% CI = 2.45–6.05, p < 0.00001), pN stage (OR = 1.86, 95% CI = 1.52–2.28, p < 0.00001), LVI (OR = 2.44, 95% CI = 1.55–3.85, p = 0.0001), and lymph node metastasis (OR = 2.87, 95% CI = 1.56–5.29, p = 0.0007). Furthermore, the cumulative analysis revealed a significant correlation between PNI and poor OS (HR = 1.37, 95% CI = 1.24–1.51, p < 0.0001), as well as poor DFS (HR = 1.55, 95% CI = 1.38–1.74, p < 0.0001).

Conclusion

PNI occurrence is significantly related to tumor stage, LVI, lymph node metastasis, OS, and DFS. These results indicate that PNI can serve as an indicator of high malignant degree and poor prognosis in EC.

Keywords: esophageal cancer, perineural invasion, lymphovascular invasion, lymph node metastasis, prognosis

Introduction

Esophageal cancer (EC) is one of the top ten malignant tumors. According to global cancer statistics in 2020, EC ranks seventh in terms of incidence and sixth in mortality overall (1). The histological types of EC mainly contain esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). ESCC is the most common histological type in China, accounting for more than 90%. In EC treatment, surgical excision is the best treatment for the early stage, and radiotherapy and chemotherapy are often used for the middle and late stage. Recently, neoadjuvant chemoradiation (nCRT) followed by esophagectomy is increasingly applied to locally advanced EC. However, the prognosis of EC is still poor after these treatments due to its insidious and highly invasive nature in the early stage. Most EC patients are prone to relapse and metastasis. In recent years, researchers found that there is a new metastasis pathway, perineural invasion (PNI), often happening in EC patients.

PNI refers to the phenomenon of cancer cells surrounding nerve fibers and entering the surrounding nerve, spreading local infiltration and metastasis. Now, the definition of PNI is that the tumor cells are in close contact with the nerve and surround at least 33% of the nerve periphery or invade any of the three layers of the nerve sheath, which is also taken as the current pathological diagnostic criteria for PNI (2, 3). The occurrence of PNI not only is with incomplete resection of the tumor and recurrence of prognosis, but also often leads to pain in many cancers, such as prostate cancer, pancreatic cancer, and head and neck cancer (2–5). However, the role of PNI in EC is differently reported. For example, PNI is associated with poor overall survival (OS) and can serve as an independent factor for OS in multivariate analysis (6–8), while Lee et al. thought PNI was not an important prognostic parameter in EC (9). These inconsistent conclusions may be due to the insufficient sample size. Hence, we collected a larger number of data from EC patients and used a systematic review and meta-analysis to obtain more accurate conclusions of PNI. The study determined the association of PNI with pathological parameters, OS and DFS, and then evaluated the role and effect of PNI on EC.

Materials and Methods

Literature Search

A literature search was performed by using the CNKI, VIP, Wanfang, Scopus, Wiley, ISI, PubMed, and EBSCO databases from January 1, 1990 to March 30, 2022. The main keywords in the abstract were “perineural invasion”, “esophageal”, and “cancer”. The articles in CNKI, VIP, and Wanfang databases only come from the Chinese Core Journal. Duplicate articles were deleted and full articles were used for analysis. The articles with patient samples from the same institution in the repeated recruitment period, reviews, and case reports were excluded. The literatures of esophageal neuroendocrine carcinoma were also excluded. The quality of all studies was assessed by using the Newcastle–Ottawa Scale and was scored from 6 to 8 (full score = 9).

Literature Extraction

To analyze the positive rate of PNI in different pathological types of EC, the following information in the articles was extracted: first author, year of publication, country of study, patient samples of recruitment period, pathological types of EC (ESCC and EAC), and the number of samples who are PNI positive.

For meta-analysis to examine the association of PNI with gender, pT stage, pN stage, lymphovascular invasion (LVI), lymph node metastasis, 5-year OS, and 5-year disease-free survival (DFS), the extracted information contains the following: first author, year of publication, odds ratio (OR), hazard ratio (HR), and the corresponding 95% confidence interval (CI). The pooled HR and 95% CI were calculated using the method of inverse variance and the p-value threshold was set at 0.05. Some articles do not directly provide HR data, but provide RR data. HR and RR can be combined because without considering the time factor in the paper, they represent the same meaning.

Statistical Analysis

Statistical calculation was completed with SPSS21.0 software and statistical heterogeneity was tested using the Chi-square test. p < 0.05 indicated statistical significance. The forest and funnel plots of the meta-analysis were made using Review Manager 5.0 software (Revman5.0). p < 0.10 or/and I² > 50% were used to indicate heterogeneity.

Results

Literature Search Results

The systematic search identified 764 potentially eligible articles, 392 of which were excluded due to duplication. Of the remaining 372 studies, 296 were excluded because they were reviews or specimens of the same origin. Five studies were excluded for PNI recurrence after neoadjuvant therapy or chemotherapy. Finally, 71 studies were finally included in this study: 69 studies were used to analyze the positive rate of PNI in different pathological types of EC; 9, 10, 6, 8, 7, 20, and 11 studies were used to analyze the correlation between PNI and gender, pT stage, pN stage, LVI, lymph node metastasis, OS, and DFS, respectively. The detailed screening process is shown in Figure 1.

Figure 1.

Figure 1

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Flow chart of the database search.

The PNI Occurrence Is Different Between ESCC and EAC

A total of 69 studies were used to analyze the distribution of PNI in different pathological types of EC, including 24 studies on EC (ESCC, EAC, and other types including esophageal small cell undifferentiated carcinoma and esophagus carcinosarcoma) (6–8, 10–30), 32 studies on ESCC (9, 31–61), and 13 studies on EAC (62–74). The detailed information is shown in Table 1. The median of PNI incidence of EC, ESCC, and EAC was 33% (range from 5% to 66%), 24% (range from 6% to 85%), and 46% (range from 20% to 56%), respectively. Data analysis showed that the PNI occurrence rate has no significant difference between ESCC and EAC (Figure S1A).

Table 1.

The distribution of PNI in different pathological types of esophageal cancer.

Study Country Re. period N PNI+(%) Male(%) T stage(T1+T2/T3+T4) N stage(N-/N+) LVI+() LNM+() Outcome Study quality
EC
Alcan S, 2022 (10) Turkey 2008-2018 50 30(60%) 33(66%) 13/37 21/29 - - OS 7
Yıldırım ÖA, 2022 (11) Turkey 2011-2021 64 10(15.6%) 44(69%) - - 15(23%) - - 7
Huang Z, 2022 (12) China 2019-2020 533 180(33.8%) 433(81.2%) 201/332 247/286 326(61.2%) 286(53.7%) - 8
Wang YP, 2020 (6) China 2012-2016 162 32(19.8%) 127(79.5%) 66/96 82/80 - - OS DFS 7
Zheng CY, 2019 (13) China 2014-2016 182 120(65.9%) 144(79.1%) 112/70 - - - - 6
Velickovic D, 2019 (14) Serbia 2004-2016 409 135(33%) 333(81.4%) 86/316 80/325 - - - 7
Zhang WY, 2018 (15) China 2006-2012 408 72(17.6%) 357(87.5%) 173/235 205/203 - - - 7
Zeng YZ, 2018 (16) China 2014-2016 141 30(21.3%) 56(39.7%) 10/61 - - - - 6
Miao N, 2018 (17) China 2007-2014 250 47(18.8%) 175(70%) 115/115 165/85 - - - 7
Faiz Z, 2018 (18) Netherlands 2000-2015 81 51(63%) - 0/81 22/59 - - OS DFS 7
Zhu TY, 2017 (19) China 2012-2013 177 116(65.5%) 150(84.7%) 108/69 - - 111(62.7%) - 7
Gao X, 2017 (20) China 2008-2012 247 92(37.2%) 149(60.3%) - - - 128(51.8%) - 6
Li ZY, 2016 (21) China 2010-2015 1160 147(12.7%) 830(71.6%) 296/864 540/620 - - OS 7
Sun YH, 2015 (7) China 1981-2011 26 5(19.2%) 23(88.5%) 10/16 16/10 7(26.9%) - OS DFS 7
Dong X, 2014 (22[] China 2007-2010 248 14(6%) 184(74.2%) 114/134 - 127(51.2%) - - 7
Tachezy M, 2014 (23) Germany 1992-2009 644 36(6%) 517(80.3%) 295/347 242/395 209(32.5%) - - 7
Dolan JP, 2013 (24) USA 1995-2011 146 85(58.2%) 120(84.5%) - - - - - 6
Noble F, 2013 (8) UK 2005-2010 246 34(13.8%) 195(79.3%) 104/118 128/118 - - OS DFS 7
Gray RT, 2012 (25) UK 1999-2000 42 15(35.7%) 35(83.3%) 13/29 28/14 36(85.7%) - - 7
Fassan M, 2010 (26) Italy 2002-2006 111 37(33.3%) 93(83.8%) - - - - - 6
Izzo JG, 2006 (27) USA NR 43 16(37.2) 41(95%) 5/38 11/32 - - - 7
Khan OA, 2004 (28) UK 1987-2001 219 11(5%) 145(66.2%) - - - - - 6
Glickman JN, 1999 (29) USA 1985-1996 145 52(35.9%) - - - - 67(46.2%) - 6
Tanaka A, 1998 (30) Japan NR 104 48(46.2%) 84(80.8%) 30/74 46/55 69(66.3%) 55(52.9%) - 7
ESCC -
Cheng J, 2022 (31) China 2021-2022 149 15(10%) 123(82.6%) 5/144 10/139 8(5%) - - 7
Xie C, 2022 (32) China 2012-2018 195 42(21.5%) 140(71.8%) 72/122 91/104 - 91(46.7%) - 7
Li A, 2021 (33) China 2015-2020 143 39(27.3%) 85(59.4%) - - - - - 6
Peng H, 2021 (34) China 2013-2017 121 12(10%) 96(79.3%) 55/66 - - 58(47.9%) OS 7
Yeh JC, 2021 (35) China 2009-2017 278 63(22.7%) 251(90.3%) 95/128 180/98 80(28.8%) - - 8
Zeng YZ, 2021 (36) China 2014-2016 97 10(10.3%) 78(80.4%) 17/80 41/56 - 56(57.7%) DFS 7
Li QM, 2020 (37) China 2015-2019 443 58(13.1%) 259(58.5%) 277/166 - - 117(26.4%) - 7
Tian H, 2020 (38) China 2016-2018 150 35(23.3%) 102(68%) 70/80 - - 60(40%) - 7
Cui J, 2020 (39) China 2012-2018 407 210(51.6%) 390(95.8%） 114/293 - - 232(57%) - 7
Guo YN, 2020 (40) China 2009-2013 162 119(73.5%) 108(66.7%) 30/162 - - - - 6
Lee HK, 2020 (9) Korea 2000-2018 64 13(20.3%) 60(93.8%) 36/28 39/25 - - OS DFS 7
Tang Y, 2019 (41) China 2010-2015 347 44(12.7%) 267(76.9%) - - - - - 6
Lin G, 2019 (42) China 2011-2017 101 86(85.1%) 78(77.2%) 50/50 - - - - 7
Rong L, 2019 (43) China 1999-2003 378 125(33.1%) 307(81.2%) 103/275 189/189 - - OS DFS 7
Wang H, 2018 (44) China 2008-2014 117 30(25.6%) 87(74.4%) 60/57 75/42 - 43 (36.8%) - 7
Hong ZP, 2018 (45) China 2014-2017 108 43(39.8%) 106(98.1%) 10/98 - - 87(80.6%) - 7
Tsai CY, 2017 (46) China 1998-2008 177 77(43.5) 171 (96.6%) 60/117 103/74 71 (40.1%) - - 7
Tu CC, 2017 (47) China 2009-2014 91 15(16.5%) 88(96.7%) 21/70 27/54 21(23.1%) - OS DFS 7
Wang H, 2017 (48) China 2010-2015 446 113(25.3%) 310(69.5%) 70/376 282/164 - 164(36.8%) OS 8
Xu G, 2017 (49) China 2008-2011 302 153(50.7%) 233(77.2%) 146/156 165/137 - - DFS 7
Hsieh CC, 2016 (50) China 2006-2013 81 24(29.6%) 70(86.4%) 24/57 31/50 36(44.4%) - OS DFS 8
Wu J, 2016 (51) China 2003-2010 1435 274(19.1%) 1254(87.4%) 430/1005 671/764 - - OS 7
Sato-Kuwabara Y, 2016 (52) Brazil 1980-1999 95 27(28.4%) 78(82.1%) - - - - - 6
Ning ZH, 2015 (53) China 2005-2010 243 54(22.2%) 194(79.8%) 51/192 106/137 - - OS DFS 7
Park SY, 2015 (54) Korea 2010-2014 85 5(6%) 77(90.6%) - - - - - 6
Chen JW, 2014 (55) China 2000-2007 433 209(48.3%) 321(74.1%) 124/309 233/200 - - - 8
Szumilo J, 2009 (56) Poland 1995-2001 39 27(69.2%) 36(92.3%) 1/38 7/32 - - - 6
Lee EJ, 2008 (57) Korea 1994-2001 251 14(6%) 110(92%) - - 7(3%) - - 6
Wang Y, 2004 (58) China 2000-2000 25 5(20%) 19(76%) 9/16 15/10 - - - 7
Roh MS, 2004 (59) Korea 1996-2003 56 12(21.4%) 51(91.1%) 24/32 - 22(39.3%) 27(48.2%) - 7
Chaves P,1997 (60) Portugal 1986-1990 37 17(45.9%) 31(83.8%) 8/29 - - - - 7
Sarbia M, 1995 (61) Germany 1978-1992 161 42(26.1%) 132(82%) 42/119 64/97 - - - 6
EAC
Merritt RE, 2020 (62) USA 2010-2018 215 44(20.5%) 186(86.5%) 55/163 85/130 53 (24.7%) - OS 8
Tapias L, 2020 (63) USA 2002-2017 196 104(53.1%) 166(84.7%) - 61/135 - 135(68.9%) OS 7
Turato C, 2019 (64) Italy NR 75 35(46.7%) 67(89.3%) - - - - - 6
Dislich B, 2017 (65) Switzerland 1990-2011 112 46(41.1%) - 43/69 - - 60(53.6%) - 7
Drage MG, 2017 (66) USA 1989-2011 120 34(28.3%) 97(80.8%) - - 46 (38.3%) - - 6
Patel AK, 2016 (67) USA 1996-2015 73 29(39.7%) 67(91.8%) 21/37 32/38 14(19.2%) - - 7
Thies S, 2016 (68) Germany
Switzerland 		1996-2011 200 63(31.5%) - 88/112 - 107(53.5%) 107(53.5%) - 7
Singhi AD, 2015 (69) USA 1997-2009 205 94(45.9%) 170(83%) 60/145 26/179 158(77.1%) - OS 8
Castonguay MC, 2014 (70) Canada 1998-2005 103 57(55.3%) 86(83.5%) 38/65 35/68 - - - 6
Mehta KS, 2014 (71) USA NR 128 63(49.2%) 95(74.2%) - - - - - 6
Smith E, 2014 (72) Australia NR 65 30(46.2%) 56(86.2%) 25/40 28/37 - - OS 7
Lagorce C, 2003 (73) France 1976-1997 66 37(56.1%) 63(95.5%) - - - - - 6
Torres C, 1999 (74) USA 1987-1996 96 31(32.3%) 83(86.5%) 35/48 - - 36(37.5%) - 6
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LVI, lymphovascular invasion; LNM, Lymph node metastasis; NR, No reported.

The Significant Correlation Between PNI and Pathological Parameters of EC

Nine, 10, and 6 studies published from 1995 to 2022 were used to analyze the relationship between PNI and gender (6, 21, 23, 30, 46, 49, 53, 55, 75), T stage (6, 21, 23, 30, 46, 49, 53, 55, 61, 75), and N stage (6, 21, 23, 49, 53, 55), respectively.

The occurrence of PNI has no correlation with gender (OR = 1.22, 95% CI: 0.98–1.52, I² = 0, p = 0.08) (Figure 2A), while the PNI-positive patients have a significantly higher risk of pT stage (OR = 3.85, 95% CI = 2.45–6.05, p < 0.00001) (Figure 2B) and pN stage (OR = 1.86, 95% CI = 1.52–2.28, p < 0.00001) (Figure 2C). In addition, in the meta-analysis for the relationship between PNI and pT stage, no obvious publication bias was observed in the entire funnel plots (Figure S1B).

Figure 2.

Figure 2

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Forest plot of the pooled OR for the association of PNI with Gender (A), pTstage (B), and pN stage (C).

A total of 2,332 patients from 8 studies were included in the meta-analysis of the correlation between PNI and LVI (6, 18, 21, 30, 46, 49, 53, 70). In PNI-positive (+) patients, the positive rate of LVI was 47.85% (323/675) and the negative rate of LVI was 52.15% (352/675), while in PNI-negative (−) patients, the positive rate of LVI was 21.85% (362/1,657) and the negative rate of LVI was 78.15% (1,295/1,657). The Chi-square test showed that PNI was significantly correlated with LVI (χ2 = 156.347, p = 0.000, r = 0.259). The forest plot was also statistically significant (OR = 2.44, 95% CI = 1.55–3.85, p = 0.0001) using a random-effect model for calculation (heterogeneity: I² = 72%, p = 0.0001) (Figure 3A).

Figure 3.

Figure 3

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Forest plot analysis of the relationship between PNI and lymphovascularinvasion (A), and lymph node metastasis (B).

Seven studies with a total of 1,738 patients provided data about lymph node metastasis (30, 37, 39, 45, 48, 54, 75). Lymph node metastasis occurred in 317 of the 516 PNI(+) patients (61.43%) and in 346 of the 1,222 PNI(−) patients (28.31%). There was a significant correlation between lymph node metastasis and PNI in EC patients (χ2 = 168.665, p = 0.000, r = 0.312). Of these seven studies, there was a significant association between PNI with lymph node metastasis (OR = 2.87, 95% CI = 1.56–5.29, p = 0.0007; Figure 3B) using a random-effect model for calculation (heterogeneity: I² = 85%, p = 0.0007).

The Effect of PNI on 5-Year Overall Survival and 5-Year Disease-Free Survival in EC

We also studied the effect of PNI on 5-year OS and 5-year DFS of EC patients. HR and 95% CI of OS and DFS were directly reported in 20 (6–10, 18, 21, 34, 43, 47, 48, 50, 51, 53, 62, 63, 69, 72, 75, 76) and 11 (6–9, 18, 36, 43, 47, 49, 50, 53) articles, respectively. Since some studies did not provide HR directly, we used fixed-effect models for the prognostic analysis regardless of the heterogeneity. There was a significant association between PNI and OS (HR = 1.37, 95% CI = 1.24–1.51, p < 0.0001; Figure 4A) using a fixed-effect model for calculation (heterogeneity: I2 = 83%, p < 0.0001), and the entire funnel plots had obvious publication bias (Figure S1C). A meta-analysis of 10 studies on DFS showed that PNI was associated with poor prognosis in EC patients (HR = 1.55, 95% CI = 1.38–1.74, p < 0.0001; Figure 4B) using a fixed-effect model for calculation (heterogeneity: I² = 71%, p < 0.0001). In this meta-analysis, a funnel plot was used to assess the publication bias. The entire funnel plots had no obvious publication bias (Figure S1D).

Figure 4.

Figure 4

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Forest plot analysis for significant correlation between the presence of PNI and5-year OS (A), 5-year DFS (B).

Discussion

PNI was identified in a variety of malignant tumors, such as prostate cancer, pancreatic cancer, and head and neck cancer (2–5). The percentage of patients with PNI in pancreatic ductal adenocarcinoma is 70%–100%, and is closely related to the occurrence of ache (3). In colorectal cancer, PNI is an independent risk factor of recurrence, which indicates a worse phenotype of tumor (3). EC is one of the common malignant tumors with high invasion. PNI often occurs in EC, but there are conflicting reports about the effects on EC of PNI (13, 16, 25, 28). This review and meta-analysis was conducted to better understand the relationship of PNI with the development process and prognosis of EC.

The esophageal nerve includes the vagal nerve and sympathetic nerve. The abundant nerve plexus is mainly distributed in the submucosa and smooth muscle layer and is often accompanied by blood vessels and lymphatic vessels. The development of PNI implies advanced tumor staging, the depth and range of LVI, and lymph node metastasis, as reported by studies (18, 30). However, other studies indicated that there was no relation between PNI and tumor staging, LVI, and lymph node metastasis (6, 54). According to our study, we found that the incidence of PNI in ESCC and EAC was different, but not statistically significant. PNI had a significant association with pT stage, pN stage, LVI, and lymph node metastasis in EC, which are well-known malignant characteristics of EC (77, 78). Moreover, it is worth noting that in cancer tissues with PNI, researchers not only found abundant blood vessels and lymphatic vessels, but also found angiogenesis and lymphangiogenesis, further promoting the development and metastasis of tumor (79, 80). Thus, these results further suggested that PNI was an important feature for the malignant degree of cancer.

It is well known that the malignant degree of EC has a significant association with poor prognosis of EC. Faiz et al. and Noble et al. reported that PNI is positively related to poor prognosis (8, 18), while Li et al. and Dong et al. identified that it was negatively related to poor outcome (21, 22). We evaluated the effect of PNI on 5-year OS and 5-year DFS of EC and found that there was a statically significant association between PNI and OS and DFS. These results indicated that PNI was an independent risk factor for the prognosis of EC. However, no matter what the treatment is, PNI is also significantly associated with worse OS and DFS, and can be evaluated as a prognostic predictor (42, 81).

At present, it is believed that PNI is the result of the interaction between tumor cells and nerves. The occurrence of PNI is not only closely related to the distribution of nerves in tissues and tumor progression, but also associated with the regulation at the molecular level. In ESCC PNI, studies indicated that several genes, such as NF-KB (27), P53 (60), nuclear programmed cell death 4 (PDCD4) (82), and NK1R (83), were significantly positively associated with PNI development, while an inverse correlation was found between platelet counts and PNI (84). The expression of nuclear PDCD4 can predict the prognosis of EC. Moreover, nuclear PDCD4 expression was negatively correlated with PNI (82). Substance P (SP) plays an important role in several types of cancer promotion and progression by binding to its preferential neurokinin 1 receptor (NK1R). NK1R was upregulated, and its overexpression correlated with larger tumor size, deeper tumor invasion, more PNI, and eventually caused poorer OS (83). However, the exact molecular mechanism of PNI in EC remains unclear and is worth further exploring.

In brief, PNI is a dynamic pathological process, and its underlying molecular mechanisms need to be further investigated. Our study only proves that PNI plays an important role in EC. Moreover, our results suggested that PNI can be incorporated into patient stratification factors to make more accurate surgical or treatment plans. This not only greatly improves the survival rate and prognosis of patients, but also enables the further development of precision medicine.

Conclusion

This review and meta-analysis was conducted to better understand the relationship of PNI with the development process and prognosis of EC. The results indicated that the effect of PNI on poor prognosis is not isolated and associated with gene expression, especially the presence of a number of adverse prognostic factors, such as depth of invasion, clinical stage, LVI, and lymph node metastasis. In general, PNI is a significant indicator of high malignant degree and poor prognosis in EC.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

Author Contributions

LB provided the idea and logic of the article, and was responsible for the data collection and statistical processing of it. LY assisted LB to complete the production of pictures and tables, and put forward other ideas. The other authors put forward valuable suggestions and revised and polished the manuscript in the process of writing the article. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by the National Natural Science Foundation of China (Grant no. 81101686), the Foundation of Henan Educational Committee (Grant no. 21A310030 and Grant no. 22A310024), and the Natural Science Foundation for Young Teachers’ Basic Research of Zhengzhou University (Grant no. JC202035025).

Conflict of Interest

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

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2022.816270/full#supplementary-material

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