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BMC Cancer logoLink to BMC Cancer
. 2020 May 20;20:454. doi: 10.1186/s12885-020-06966-3

Tumor-associated tissue eosinophilia predicts favorable clinical outcome in solid tumors: a meta-analysis

Guoming Hu 1,✉,#, Shimin Wang 2,#, Kefang Zhong 1, Feng Xu 1, Liming Huang 1, Wei Chen 1,, Pu Cheng 3,
PMCID: PMC7240929  PMID: 32434481

Abstract

Background

Activated eosinophils have been deemed to affect carcinogenesis and tumor progression via various mechanisms in tumor microenvironment. However, the prognostic role of tumor-associated tissue eosinophilia (TATE) in human cancers remains controversial. Therefore, we conducted this meta-analysis to better comprehend the association between TATE and clinical outcomes of patients.

Methods

We searched PubMed, Embase and EBSCO to determine the researches assessing the association between TATE and overall survival (OS) and/or disease-free survival (DFS) in patients with cancer, then combined relevant data into hazard ratios (HRs) or odds ratio (OR) for OS, DFS and clinicopathological features including lymph node metastasis etc. with STATA 12.0.

Results

Twenty six researches with 6384 patients were included in this meta-analysis. We found that the presence of TATE was significantly associated with improved OS, but not with DFS in all types of cancers. In stratified analyses based on cancer types, pooled results manifested that the infiltration of eosinophils was remarkably associated with better OS in esophageal carcinoma and colorectal cancer. In addition, TATE significantly inversely correlated with lymph node metastasis, tumor stage and lymphatic invasion of cancer.

Conclusion

TATE promotes survival in cancer patients, suggesting that it is a valuable prognostic biomarker and clinical application of biological response modifiers or agonists promoting TATE may be the novel therapeutic strategy for patients.

Keywords: Tumor-associated tissue eosinophilia, Favorable outcome, Human solid tumor, Meta-analysis

Background

Tumor microenvironment (TME) linked closely with the initiation, promotion, and progression of cancer [1]. Innate and adaptive immunocytes such as mast cells, macrophages and memory T lymphocytes etc. are the vital components of TME [2]. Multitudinous studies have demonstrated that these immune cells were significantly associated with survival in solid tumors [3, 4]. However, it is essential to distinguish among different types of immune cells as they may play differential roles in the TME. Eosinophils, as the important component of innate immune cells, have proven to play significant roles in a multitude of solid tumors.

Eosinophils are granulocytic leukocytes that are associated with multitudinous pathologic conditions including allergic reactions, parasitic and bacterial infections etc. [5] These cells secrete massive proteins and cytokines upon activation and are involved in a variety of other functions including inducing tissue remodeling and promoting antigen presentation [6]. In the last decade, activated eosinophils have been deemed to affect carcinogenesis and tumor progression via various mechanisms including modulating innate and adaptive immune responses in TME [7]. Eosinophils infiltrating into tumor is also called tumor-associated tissue eosinophilia (TATE) [8]. Recent researches have investigated the TATE in tumor progression and survival, but their results were inconsistent even contradictory [9]. Hence, it needs further evaluation. In addition, the potential of TATE as prognostic biomarker and therapeutic strategy is also required to be investigated.

Herein, we carried out this meta-analysis to expound the relation between TATE and clinical outcomes including overall survival (OS) and disease-free survival (DFS) in patients with cancer.

Methods

Search strategy

This meta-analysis was guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) Statement issued in 2009 (Checklist S1). PubMed, Embase and EBSCO were searched for researches from 1980 to May 15th 2019. The keywords applied for search were: (eosinophil [Title/Abstract] OR eosinophilia [Title/Abstract]) AND (neoplasms [Title/Abstract] OR tumor [Title/Abstract] OR cancer [Title/Abstract] OR carcinoma [Title/Abstract]).

Inclusion and exclusion criteria

Researches included in this meta-analysis should meet the following inclusion criteria: (1) been published as original articles; (2) investigated human subjects; (3) examined eosinophils in primary tumor tissues; (4) reported hazard ratios (HRs) with 95% confidence interval (CI), or Kaplan – Meier curves of eosinophil infiltration with clinical outcomes.

The exclusion criteria were as follows: researches (1) were not published as research articles or full texts including commentaries, case reports, letters to the editors and meeting abstracts; (2) didn’t offer ample data to obtain HRs; (3) investigated eosinophils in metastases or not in tumor tissues.

Endpoints

In this study, OS and DFS were regarded as the primary and second endpoint respectively.

Data extraction

GM.H. and SM.W. reviewed and recorded data including number of patients, method to quantify eosinophils, cutoff value to determine TATE and time of follow-up etc. independently. OS, DFS and clinicopathological features such as tumor, node, metastasis (TNM) stage and lymphatic invasion were extracted from the text, tables, or Kaplan – Meier curves.

Quality assessment

Two authors independently assessed the quality of included cohort researches with Newcastle–Ottawa Scale (NOS), [10] and achieved consensus for each item under the help of third or more authors. Research scored 6 or above was regarded as high quality.

Statistical analysis

We combined extracted data using STATA 12.0 analysis software, and estimated statistical heterogeneity with the chi-squared based Q-test or I2 (25% was considered low-level heterogeneity, 25–50% moderate-level heterogeneity, and 50% high-level heterogeneity) [11]. Data were pooled based on the random-effect model in the presence of heterogeneity, [12] otherwise, the fixed-effect model was applied [13]. In addition, stratified analyses were conducted based on tumor types; sensitivity analysis, Begg’s funnel plot and Egger’s test [14] were employed to explore the impact of each research on the overall result and potential publication bias respectively. All P values were two-sided and below 0.05 was treated as statistical significance.

Results

Search results and description of studies

Flow chart diagram of research selection was displayed in Fig. S1. Twenty six researches with 6384 patients were ultimately included in this meta-analysis [1540]. And all the researches were scored 6 or above after careful evaluation with the Newcastle–Ottawa Scale (NOS); Characteristics of those researches being in the light of the inclusion criteria and suitable for data incorporation were exhibited in Table 1 and Table S1.

Table 1.

Main characteristics of the included studies

Study Year Tumor type No. of Patients Male/Female median age (range) (year) Staining TATE: Present / absent Tumor stage median follow-up date (months) Survival Quality Score (NOS)
Peurala, E. etal [15] 2018 Oral cancer 99 55/44 65.3 H&E 51/47 I - III 40.7 OS 8
Oliveira, D. T. etal [16] 2012 Oral cancer 71 55/16 59 (35, 77) H&E 35/36 I - II NR DFS 7
Tostes Oliveira, D. etal [19] 2009 Oral cancer 43 27/16 55.79 (28, 83) H&E 21/22 I - IV (3, 229) OS 7
Dorta, R. G. etal [17] 2002 Oral cancer 125 105/20 58 (30, 95) H&E 57/68 II - III 88.2 (0, 287.4) OS, DFS 7
Dante, P. etal [40] 2019 Tongue Carcinoma 259 223/36 53.0 ± 12.2 H&E NR I - IV NR OS, DFS 8
Alrawi, S. J. etal [18] 2005 Head and neck carcinoma 87 NR (41, 76) H&E 13/7 II - IV 36 (6, 216) OS, DFS 7
Ercan, I. etal [20] 2005 Laryngeal carcinoma 78 78/0 55.9 (35, 80) H&E 25/53 NR 41.91 OS 7
Sassler, A. M. etal [21] 1995 Laryngeal carcinoma 248 NR NR H&E 56/192 III - IV 48 OS, DFS 6
Thompson, A. C. etal [22] 1994 Laryngeal carcinoma 104 85/19 64.6 (39, 91) H&E 31/73 NR ≥ 60 OS 6
Fujii, M. etal [23] 2002 Nasopharyngeal carcinoma 53 40/13 49.4 (15, 81) H&E 26/27 I - IV 90.5 (35.3, 199.9) DFS 7
Leighton, S. E. etal [24] 1996 Nasopharyngeal carcinoma 96 68/28 NR H&E 65/31 NR 57 OS, DFS 6
Harbaum, L. etal [25] 2015 Colorectal cancer 381 166/215 68.5 H&E 101/280 I - IV 45 (1, 182) OS 8
Fernandez-Acenero, M. J. etal [26] 2000 Colorectal cancer 126 70/56 67.35 (32, 87) H&E 29/97 Duke’s A-C ≥ 60 OS, DFS 8
Nielsen, H.J. etal [27] 1999 Colorectal cancer 584 240/344 61 (49, 75) H&E 150/115 Duke’s A-D 61 (49, 75) OS 7
Prizment, A. E etal [28] 2016 Colorectal cancer 441 0/441 (55, 69) H&E; EPX 197 /244 NR 60 OS 8
Zhang, Y. etal [29] 2014 Esophageal carcinoma 36 25/11 59 (45, 77) H&E 18/18 I - IV 22 (2, 143) OS 7
Ishibashi, S. etal [30] 2006 Esophageal carcinoma 97 82/15 62.7 ± 8.9 H&E 30/31 NR 61.7 (5.3, 165.4) OS 7
Hollander, P. etal [31] 2018 Hodgkin’s lymphoma 459 242/217 < 45: 68%; ≥45: 32% H&E NR I - IV 154.8 OS 8
Kereszres, K. etal [32] 2007 Hodgkin’s lymphoma 104 54/50 33 (12, 72) H&E 64/40 I - IV 110 (24, 214) OS, DFS 7
von Wasielewski, R. etal [33] 2000 Hodgkin’s lymphoma 1511 745/766 (15, 75) H&E 510/823 I - IV 120 OS 8
Enblad, G.etal [34] 1993 Hodgkin’s lymphoma 140 NR 45 (11, 94) H&E 26/114 I - IV 48 (20, 85) DFS 6
van Driel, W.J. etal [35] 1996 Cervical cancer 83 0/83 42.1 H&E NR I - IIA 44.6 (5, 108) OS, DFS 7
Bethwaite, P. B. etal [36] 1993 Cervical cancer 67 0/67 43.7 (25, 76) H&E 28/39 IB 62.4 (1, 93) OS 7
Flamm, J. etal [37] 1992 Bladder cancer 428 289/139 70.2 (29, 91) H&E 99/329 NR 84 OS 7
Iwasaki, K. etal [38] 1986 Gastric cancer 647 364/283 (22, 84) H&E 157/490 I - IV (8, 92) OS 7
Ono, Y. etal [39] 2002 Penile cancer 17 17/0 68 (36, 84) H&E 9/8 I - IV NR OS 6

H&E haematoxilyn and eosin, EPX eosinophil peroxide, NR not reported

Meta-analyses

Overall survival (OS)

In this meta-analysis, we discovered that the presence of TATE was notably associated with improved OS (HR = 0.82, 95% CI 0.68 to 0.99, P = 0.041) in patients with solid tumor. (Fig. 1).

Fig. 1.

Fig. 1

Forest plots describing HR of the association between TATE and OS in human solid tumors

In stratified analyses according to tumor types, the combined results manifested that TATE was markedly associated with better OS in colorectal cancer (CRC) (HR = 0.70, 95% CI 0.58 to 0.84, P = 0.000), with no heterogeneity detected (I2 = 0%, P = 0.449). Similar data was obtained between TATE and OS in esophageal carcinoma (EC) (HR = 0.35, 95% CI 0.14 to 0.88, P = 0.026); Whereas no distinct relation existed between eosinophil infiltration and OS in oral cancer (OC) (HR = 0.89, 95% CI 0.53 to 1.49, P = 0.657), laryngeal carcinoma (HR = 0.87, 95% CI 0.51 to 1.48, P = 0.599), Hodgkin’s lymphoma (HR = 0.90, 95% CI 0.48 to 1.69, P = 0.741) or cervical cancer (HR = 2.14, 95% CI 0.38 to 12.24, P = 0.391). (Fig. 2).

Fig. 2.

Fig. 2

Stratified analyses describing HRs of the association between TATE and OS

Disease-free survival (DFS)

As for DFS, the meta-analysis indicated that no noticeable association existed between eosinophil infiltration and DFS (HR = 1.13, 95% CI 0.72 to 1.77, P = 0.598) in solid tumors. (Fig. 3) In the stratified analyses, the incorporated results revealed that TATE was not significantly associated with improved DFS in oral cancer (HR = 1.83, 95% CI 0.65 to 5.15, P = 0.253), nasopharyngeal carcinoma (HR = 0,50, 95% CI 0.23 to 1.08, P = 0.079) or Hodgkin’s lymphoma (HR = 0.73, 95% CI 0.18 to 2.98, P = 0.657). (Fig. 4).

Fig. 3.

Fig. 3

Forest plots describing HR of the association between TATE and DFS in human solid tumors

Fig. 4.

Fig. 4

Stratified analyses describing HRs of the association between eosinophil infiltration and DFS

Clinicopathological features

We next tested the relation between TATE and clinicopathological features, and found that TATE was remarkably inversely correlated with lymph node metastasis (OR = 0.59, 95% CI 0.40 to 0.87, P = 0.007), TNM stage (OR = 1.70, 95% CI 1.12 to 2.58, P = 0.013) and lymphatic invasion (OR = 0.58, 95% CI 0.36 to 0.91, P = 0.018), but not with vascular invasion (OR = 0.79, 95% CI 0.50 to 1.25, P = 0.308) of patients. (Fig. 5).

Fig. 5.

Fig. 5

Forest plots indicating ORs of the association between eosinophil infiltration and clinicopathological feature

Sensitivity analysis

Sensitivity analysis demonstrated that each included research had no impact on the overall result for OS or DFS. (Fig. S2).

Publication bias

No publication bias existed between TATE and OS (P = 0.152) or DFS (P = 0.876) in patients by Funnel plot (Fig. S3) and Egger’s test.

Discussion

Eosinophilia is commonly associated with allergies, helminth infections and several inflammatory states. Recently, it has also been noted in human solid tumors. The present meta-analysis revealed that TATE had a positive effect in improving survival in human solid tumors, especially in CRC and EC. Moreover, It significantly inversely correlated with lymph node metastasis etc. of tumor. Hence, these data offered important evidence in uncovering the positive prognostic role of TATE in human solid tumors.

The close relation between TATE and better clinical outcome identified in this study possibly attribute to the following reasons: eosinophils in the TME can express same receptors and mediators such as granzyme A etc. as cytotoxic T lymphocytes (CTLs) and be directly involved in anti-tumor response, [41] and they can also secret several chemokines including CCL5, CXCL9 to promote anti-tumor immunity through attracting CD8+ T cells to the tumor site [42]. In addition, eosinophils are capable of regulating immunity, for instance, they can release major basic protein (MBP), a highly cationic protein to stimulate maturation of dendritic cells by increasing cell surface activation markers including MHC-II, CD80 and CD86, [43] which has the potential to overcome immune tolerance and induce anti-tumor immunity with the powerful antigen-presentation ability [44]. Furthermore, they can induce cell death of various cell lines such as colo-205 cell line with some selectivity in their tumoricidal properties, which are dependent on the CD11a/CD18-mediated stable contacts with target cells [45]. Hence, it is rational to conclude that TATE is capable of regulating tissue homeostasis of the TME and inhibiting tumor growth and metastasis thereby improving survival. However, in other tumor types, TATE as a prognostic marker for survival has been a controversial issue. This may be because of differences in methods of counting TATE as well as heterogeneity of material.

Previous studies have demonstrated that cytokines such as IL-2, IL-4 could recruit eosinophils and lead to eosinophilia and enhanced eosinophil activation, thereby exert potent anti-tumor immune responses [41, 46]. Thus, based on our present result that TATE improving survival in human solid tumors identified in this study and the function of IL-2 and IL-4 stated above, we harbor the idea that clinical application of biological response modifiers (BRM) such as carrier-assisted recombined human IL-2 /or IL-4 may have the potential to treat human solid tumors.

Quite a few limitations should be noted from this study. First, morphometric analyses for TATE adopted in included researches were not exactly consistent. In addition, researches with negative results might not be published, which might result in potential publication bias.

Conclusions

TATE promotes survival in solid tumors especially in CRC and EC, suggesting that it is a valuable prognostic biomarker and clinical application of biological response modifiers or agonists promoting TATE may be a novel therapeutic strategy for patients.

Supplementary information

12885_2020_6966_MOESM1_ESM.pdf (552.9KB, pdf)

Additional file 1: Figure S1. Flow chart diagram of study selection. Figure S2. Plots describing the influence of individual studies on the overall HRs for OS (A) and DFS (B) in human cancers. Figure S3. Funnel plots displayed the potential publication bias between TATE and OS (A) or DFS (B) in patients. Table S1. Characteristics of the included studies for OR analysis of clinicopathological features.

Acknowledgements

Not applicable.

Abbreviations

TATE

Tumor-associated tissue eosinophilia

OS

Overall survival

DFS

Disease-free survival

HR

Hazard ratio

OR

Odds ratio

Cl

Confidence interval

TNM

Tumor, node, metastasis

OC

Oral cancer

CRC

Colorectal cancer

EC

Esophageal carcinoma

NR

Not reported

TME

Tumor microenvironment

BRM

Biological response modifier

Authors’ contributions

GM.H. conceived of the study, participated in its design, extracted data, performed the statistical analysis and drafted the manuscript. SM.W. participated in data extraction; KF.Z., F. X. and LM.H. participated in statistical analysis and manuscript revision. W.C. and P.C. participated in its design and manuscript revision. All authors read and approved the final manuscript.

Funding

This work was funded by the National Natural Science Foundation of China (Grant No. 81702803, GMH) and was also partly supported by Shaoxing Science and TechnologyPlanProject (2018C30055, LMH; 2018C30075, KFZ; 2017B70036, FX). We used the funding to perform data collection, analysis and interpretation.

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article.

Ethics approval and consent to participate

The ethical approval was unnecessary because this study based on summary and analysis of the results of previous studies.

Consent for publication

Not applicable.

Competing interests

The authors have declared that no competing interests exist.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Guoming Hu and Shimin Wang contributed equally to this work.

Contributor Information

Guoming Hu, Email: hgmplj@126.com.

Wei Chen, Email: cwzjsx5018@163.com.

Pu Cheng, Email: drchengpu@zju.edu.cn.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s12885-020-06966-3.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

12885_2020_6966_MOESM1_ESM.pdf (552.9KB, pdf)

Additional file 1: Figure S1. Flow chart diagram of study selection. Figure S2. Plots describing the influence of individual studies on the overall HRs for OS (A) and DFS (B) in human cancers. Figure S3. Funnel plots displayed the potential publication bias between TATE and OS (A) or DFS (B) in patients. Table S1. Characteristics of the included studies for OR analysis of clinicopathological features.

Data Availability Statement

The datasets supporting the conclusions of this article are included within the article.


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