Literature DB >> 35116629

High expression of S100A8 and S100A9 is associated with poor disease-free survival in patients with cancer: a systematic review and meta-analysis.

Hyun Min Koh1, Hyun Ju Lee2,3, Dong Chul Kim4,5,6.   

Abstract

BACKGROUND: The expression of S100A8 and S100A9 is found to be related with the survival of cancer patients, but the results and information regarding their prognostic significance are inconsistent in literature. This study, therefore, aimed to perform a comprehensive meta-analysis and determine the prognostic significance of S100A8 and S100A9 expression in patients with cancer.
METHODS: Data were collected by performing a literature search on the PubMed, Cochrane library, and Scopus databases. Pooled hazard ratio (HR) with confidence interval (CI) was calculated to assess the correlation between S100A8 and S100A9 expression and survival in patients with cancer.
RESULTS: In total, 5 studies that enrolled 735 cancer patients were included in the meta-analysis. The pooled HR concerning S100A8 and S100A9 expression was 1.98 (95% CI: 1.20-3.29, P=0.008) for disease-free survival (DFS), indicating an association between high expression of S100A8 and S100A9 and poor DFS in cancer patients. However, the expression of S100A8 and S100A9 was not significantly correlated with disease-specific survival (HR 1.71, 95% CI: 0.86-3.40, P=0.128). DISCUSSION: The current meta-analysis revealed that S100A8 and S100A9 expression may be a potential prognosticator of DFS in cancer patients. The present systematic review is the first to investigate the survival outcomes of cancer patients with S100A8 and S100A9 expression. 2021 Translational Cancer Research. All rights reserved.

Entities:  

Keywords:  Neoplasms; S100A8; S100A9; meta-analysis; prognosis

Year:  2021        PMID: 35116629      PMCID: PMC8798155          DOI: 10.21037/tcr-21-519

Source DB:  PubMed          Journal:  Transl Cancer Res        ISSN: 2218-676X            Impact factor:   1.241


Introduction

Cancer is a major public health issue (1). In 2018, more than 18 million new cases and 9.5 million cancer-associated deaths were reported (2). Despite the vigorous efforts and advances in cancer management and therapy, the clinical outcome of cancer patients remains poor (1,2). Thus, it is essential to develop valuable biomarkers for cancer that could improve treatment efficacy and evaluate the prognosis of cancer patients (2,3). S100 belong to the family of EF-hand calcium-binding proteins (4). Thus far, more than 20 members have been identified (4). They are involved in rheumatoid arthritis, inflammatory bowel disease, and other inflammatory diseases as well as in physiological functions, such as chemo-attraction for leukocytes and macrophages, calcium homeostasis, protein phosphorylation, and regulation of enzyme activity (5-7). Moreover, recent studies have suggested that alterations in the function and expression of S100 proteins may represent an essential step during cancer development and progression (4). S100A8 and S100A9 are members of the S100 family and known to function as a heterodimer, calprotectin (5,8). The S100A8 and S100A9 proteins are overexpressed in various cancers, such as melanoma, lung, gastric, colon, prostate, ovarian, head and neck, and breast cancers (8). Moreover, S100A8 and S100A9 enhance cancer cell proliferation, invasion, and metastasis (9-11). However, the results regarding the prognostic significance of S100A8 and S100A9 expression remain controversial. Therefore, we performed a comprehensive meta-analysis to determine the prognostic significance of S100A8 and S100A9 expression in patients with cancer. We present the following article in accordance with the PRISMA reporting checklist (available at https://dx.doi.org/10.21037/tcr-21-519).

Methods

Search strategy

Studies published in literature up to January 2020 were identified through a search on the Scopus, PubMed, and Cochrane Library databases using the following search terms: (S100A8 or S100A9 or calprotectin) and (cancer or tumor or carcinoma or neoplasm or malignancy) and (prognostic or predict or prognosis or survival or outcome). All significant publications in the references of the reviewed articles were also manually evaluated.

Inclusion and exclusion criteria

The studies were required to meet the following criteria for inclusion: (I) the expression of detection of S100A8 and S100A9 in the tumor cells of human cancer tissues was assessed using immunohistochemistry (IHC); (II) relationship of S100A8 and S100A9 expression with the clinical outcome was assessed; (III) hazard ratio (HR) and 95% confidence interval (CI) evaluating multivariate regression model for clinical outcome were provided. Articles were excluded from further consideration if they met the following criteria: (I) duplicate studies; (II) reviews, case reports, letters, conference abstracts, and non-English articles; (III) preclinical studies, such as laboratory or in vitro studies; (IV) studies of patients and children with hematological malignancy; and (V) studies with unavailable survival data for further calculations (including survival curves yet without HR reported).

Data extraction

Data for the following variables were extracted from the selected articles: first author, publication year, country, cancer type, demographic characteristics (number of patients, sex, and mean or median age), endpoints, follow-up period, study period, S100A8 and S100A9 expression associated with poor prognosis, cut-off value for S100A8 and S100A9 expression, and reported values for HR and 95% CI for survival. Eligibility of the studies for inclusion was assessed by two authors individually, with any discordance being revised and re-evaluated.

Quality assessment

The Newcastle-Ottawa Scale (NOS) was used for estimating the quality of the eligible studies. The scale covered study group selection, comparability, and outcome ascertainment, and the scores ranged from 0 to 9. Articles that had a score greater than 6 were considered high quality. Two authors independently performed quality evaluation for each study.

Statistical analysis

The current meta-analysis was performed using StataSE12 (Stata, College Station, TX, USA). To investigate the prognostic significance of S100A8 and S100A9 expression, pooled HR and 95% CI were calculated and applied. Cochran’s Q and I2 statistics were used to assess heterogeneity among the selected studies. I2>50% or P<0.1 was regarded as statistically significant in a random-effects model. Insignificant heterogeneity was applied using the fixed-effects model. A subgroup analysis was conducted to determine the source of heterogeneity. Funnel plot and Egger’s regression test were also performed to reveal publication bias. Sensitivity analysis was conducted to check the stability of the initial results. P<0.05 was considered to indicate statistical significance.

Results

Characteristics of the included studies

As shown in , five studies were selected from 576 articles initially searched for current meta-analysis. The main features of the included studies are presented in . There were 735 cancer patients; therefore, 37 was the minimum sample size and 158 was the largest sample size. The enrolled studies covered five types of cancers: renal cell carcinoma (n=2), lung squamous cell carcinoma (n=1), lung adenocarcinoma (n=1), breast cancer (n=1), and non-muscle-invasive bladder cancer (n=1). All the enrolled studies performed IHC to detect S100A8 and S100A9 expression in the tumor cells of human cancer tissue. The HR and 95% CI were corrected from the original articles calculated using multivariate analysis. The NOS score of all included studies was 8.
Figure 1

Flow diagram of the study selection process.

Table 1

Basic characteristics of the included studies

StudyCountryCancer typeProtein typeSample sizeSex (male/female)Mean age (years)Mean follow-up (months)EndpointsS100A8/S100A9 expression associated with poor prognosisCut-off value of S100A8/S100A9 expressionNOS
Koh et al. (2019-1)South KoreaRenal cell carcinomaS100A9152109/4359.9 (32–83)51.96DSS, DFSHigh proportion of positive tumor cells>25%8
An et al. (2019)South KoreaRenal cell carcinomaS100A8152109/4359.9 (32–83)51.96DSS, DFSHigh expression in tumor cellsStaining intensity: stronger than capillary endothelial cells8
Koh et al. (2019-2)South KoreaLung squamous cell carcinomaS100A996NANa113DSS, DFSHigh proportion of positive tumor cells>50%8
Lung adenocarcinomaS100A937NANa113DSS, DFSHigh proportion of positive tumor cells>50%
Wang et al. (2018)ChinaBreast cancerS100A8140NAMedian 54 (29–87)108 (26–132)OS, DFSHigh proportion of positive tumor cells> average number8
Nicklas et al. (2018)ChinaNon-muscle-invasive bladder cancerS100A8158122/36Median 69 (32–90)Median 49 (4–139)CSS, RFS, PFSHigh expression in tumor cellsNA8

CSS, cancer-specific survival; DFS, disease-free survival; DSS, disease-specific survival; NA, not available; NOS, Newcastle-Ottawa Scale; PFS, progression-free survival; RFS, recurrence-free survival; OS, overall survival.

Flow diagram of the study selection process. CSS, cancer-specific survival; DFS, disease-free survival; DSS, disease-specific survival; NA, not available; NOS, Newcastle-Ottawa Scale; PFS, progression-free survival; RFS, recurrence-free survival; OS, overall survival.

Association between S100A8 and S100A9 expression and disease-specific survival

Five studies that included cancer patients reported the relationship of S100A8 and S100A9 expression with cancer-specific survival (CSS), disease-specific survival (DSS), and overall survival (OS). Koh et al. (12) reported the HRs in squamous cell carcinoma and adenocarcinoma of the lung. In this meta-analysis, CSS and OS were regarded as DSS, and the HRs reported by Koh et al. (12) in both types of lung cancer were included. The pooled HR was evaluated using the random-effects model due to severe heterogeneity (I2=74.1%, P=0.002). The expression of S100A8 and S100A9 was not significantly correlated with DSS (HR 1.71, 95% CI: 0.86–3.40, P=0.128; ) (P value is not shown in the figure). Subgroup analysis, which was performed to reveal the cause of heterogeneity, revealed that the main sources of heterogeneity could be the protein type (S100A9, I2=83.3%, P=0.003), cancer type (non-urinary system cancer, I2=86.7%, P=0.001), and sample size (sample size fewer than 100, I2=70.5%, P=0.066) ().
Figure 2

Forest plot presenting the association of S100A8 and S100A9 expression with disease-specific survival in cancer patients.

Figure 3

Forest plot for disease-specific survival subgrouped by protein type (A), cancer type (B), and sample size (C).

Forest plot presenting the association of S100A8 and S100A9 expression with disease-specific survival in cancer patients. Forest plot for disease-specific survival subgrouped by protein type (A), cancer type (B), and sample size (C).

Association between S100A8 and S100A9 expression and disease-free survival

Five studies that included 735 cancer patients reported the relationship of S100A8 and S100A9 expression with recurrence-free survival (RFS), disease-free survival (DFS), and progression-free survival (PFS). Nicklas et al. (13) reported the HRs related to RFS and PFS in non-muscle-invasive bladder cancer. In this analysis, RFS and PFS were regarded as DFS, and the HRs reported by Nicklas et al. (13) were included. The pooled HR was assessed using the random-effects model because of significant heterogeneity (I2=65.9%, P=0.007). The pooled HR was 1.98 (95% CI: 1.20–3.29, P=0.008) (P value is not shown in the figure), which indicated a significant association between high expression of S100A8 and S100A9 and poor DFS in patients with cancer (). Subgroup analysis demonstrated that protein type (S100A9, I2=66.5%, P=0.050) and cancer type (non-urinary system cancer, I2=76.8%, P=0.013) may be the causes of heterogeneity ().
Figure 4

Forest plot presenting the association of S100A8 and S100A9 expression with disease-free survival in cancer patients.

Figure 5

Forest plot for disease-free survival subgrouped by protein type (A), cancer type (B), and sample size (C).

Forest plot presenting the association of S100A8 and S100A9 expression with disease-free survival in cancer patients. Forest plot for disease-free survival subgrouped by protein type (A), cancer type (B), and sample size (C).

Sensitivity analysis

Sensitivity analysis suggested that the results from Koh et al. (12) had a significant impact on the outcomes. However, the pooled HR did not prominently change after excluding each study one by one, which indicated that our results were consistent and robust (DSS, HR 1.48, 95% CI: 1.07–2.04; DFS, HR 1.77, 95% CI: 1.35–2.33; ).
Figure 6

Sensitivity analysis for disease-specific survival (A) and disease-free survival (B).

Sensitivity analysis for disease-specific survival (A) and disease-free survival (B).

Publication bias

The funnel plot showed asymmetry (). This presents the possibility of publication bias, although Egger’s regression test was not significant (DSS, P=0.470; DFS, P=0.347). Thus, we conducted the trim and fill method. The test also did not change our initial results ().
Figure 7

Funnel plot and trim and fill method for disease-specific survival (A,C) and for disease-free survival (B,D).

Funnel plot and trim and fill method for disease-specific survival (A,C) and for disease-free survival (B,D).

Discussion

Calprotectin (S100A8/S100A9), a heterodimer of the two calcium-binding proteins S100A8 and S100A9, was primarily discovered as an immunogenic protein expressed and secreted by neutrophils (14). It has become evident as a valuable pro-inflammatory mediator in inflammation (14). In fact, S100A8 and S100A9 are considered biomarkers for inflammatory diseases, including multiple sclerosis, inflammatory bowel disease, rheumatoid arthritis, psoriasis, and cystic fibrosis (9). The relationship between inflammation and tumorigenesis has been identified (9). Overexpression of S100A8 and S100A9 has been found in inflammatory lesions associated with tumorigenesis (9). More recently, upregulation of S100A8 and S100A9 expression was reported in various human cancers, such as lung, gastric colon, prostate, breast, and skin cancers, with high expression in cancer cells (6,9). Furthermore, S100A8 and S100A9 have been clearly recognized as new prognostic candidates playing important roles in regulating tumor cell growth, invasion, and metastasis (9). Therefore, we performed this meta-analysis to systematically understand the prognostic role of S100A8 and S100A9 expression in patients with cancer. For this meta-analysis, we identified 5 eligible articles that included cancer patients. Koh et al. (15) revealed that S100A9 could be an important prognostic factor for poor DSS and DFS, and An et al. (16) showed that high expression of S100A8 was associated with poor DFS in patients with clear cell renal cell carcinoma. Koh et al. (12) also reported that S100A8 and S100A9 expression was associated with survivability in patients with squamous cell carcinoma and adenocarcinoma of the lung. Wang et al. (17) demonstrated that patients with increased S100A8 expression levels in breast cancer had significantly shorter DFS and OS. Nicklas et al. (13) reported that S100A8 expression was a promising marker for the identification of non-muscle-invasive bladder cancer patients who are at high risk of progression and recurrence. In this meta-analysis, we showed that high expression of S100A8 and S100A9 was associated with poor DFS in patients with cancer. The pooled HR for S100A8 and S100A9 expression was 1.98 (95% CI: 1.20–3.29, P=0.008, P value is not shown in ) for DFS. However, we did not find that the expression of S100A8 and S100A9 was significantly correlated with DSS (HR 1.71, 95% CI: 0.86–3.40, P=0.128, P value is not shown in ). Furthermore, sensitivity analysis demonstrated that our results are consistent (DFS, HR 1.77, 95% CI: 1.35–2.33). Thus, S100A8 and S100A9 expression may be a potential prognostic biomarker of DFS in cancer patients. To the best of our knowledge, the current study is the first systematic review and meta-analysis to focus on survival in cancer patients based on S100A8 and S100A9 expression. This meta-analysis has several limitations. First, some results had heterogeneity, although the random-effects model was used and subgroup analysis was performed, which may have caused bias in the results. Second, the cut-off value for S100A8 and S100A9 expression varied among the included articles, which may have caused heterogeneity in the results. Finally, the sample size of the included articles was small, which could have resulted in a bias in the outcome. In conclusion, the current systematic review and meta-analysis showed that high expression of S100A8 and S100A9 may be a poor prognostic marker of DFS in cancer patients.
  17 in total

1.  Clinicopathological roles of S100A8 and S100A9 in cutaneous squamous cell carcinoma in vivo and in vitro.

Authors:  Dae-Kyoung Choi; Zheng Jun Li; In-Kyu Chang; Min-Kyung Yeo; Jin-Man Kim; Kyung-Cheol Sohn; Myung Im; Young-Joon Seo; Jeung-Hoon Lee; Chang-Deok Kim; Young Lee
Journal:  Arch Dermatol Res       Date:  2014-02-19       Impact factor: 3.017

Review 2.  A review of the S100 proteins in cancer.

Authors:  I Salama; P S Malone; F Mihaimeed; J L Jones
Journal:  Eur J Surg Oncol       Date:  2007-06-13       Impact factor: 4.424

3.  Tumor-infiltrating monocytes/macrophages promote tumor invasion and migration by upregulating S100A8 and S100A9 expression in cancer cells.

Authors:  S Y Lim; A E Yuzhalin; A N Gordon-Weeks; R J Muschel
Journal:  Oncogene       Date:  2016-04-18       Impact factor: 9.867

4.  Calgranulin A (S100A8) Immunostaining: A Future Candidate for Risk Assessment in Patients with Non-Muscle-Invasive Bladder Cancer (NMIBC).

Authors:  André P Nicklas; Mario W Kramer; Jürgen Serth; Jörg Hennenlotter; Marie C Hupe; Daniel U Reimer; Arnulf Stenzl; Axel S Merseburger; Markus A Kuczyk; Christoph-Alexander J von Klot
Journal:  Adv Ther       Date:  2018-09-19       Impact factor: 3.845

5.  Prognostic significance of CXCR7 in cancer patients: a meta-analysis.

Authors:  Huiqian Fan; Weijun Wang; Jingjing Yan; Li Xiao; Ling Yang
Journal:  Cancer Cell Int       Date:  2018-12-19       Impact factor: 5.722

6.  Prognostic role of S100A9 expression in patients with clear cell renal cell carcinoma.

Authors:  Hyun Min Koh; Hyo Jung An; Gyung Hyuck Ko; Jeong Hee Lee; Jong Sil Lee; Dong Chul Kim; Dae Hyun Song
Journal:  Medicine (Baltimore)       Date:  2019-10       Impact factor: 1.889

7.  Prognostic Role of S100A8 and S100A9 Protein Expressions in Non-small Cell Carcinoma of the Lung.

Authors:  Hyun Min Koh; Hyo Jung An; Gyung Hyuck Ko; Jeong Hee Lee; Jong Sil Lee; Dong Chul Kim; Jung Wook Yang; Min Hye Kim; Sung Hwan Kim; Kyung Nyeo Jeon; Gyeong-Won Lee; Se Min Jang; Dae Hyun Song
Journal:  J Pathol Transl Med       Date:  2018-11-26

8.  Prognostic and Clinicopathological Significance of Long Non-coding RNA PANDAR Expression in Cancer Patients: A Meta-Analysis.

Authors:  Lizhi Han; Bo Wang; Ruoyu Wang; Zijian Wang; Song Gong; Guo Chen; Dionne Telemacque; Yong Feng; Weihua Xu
Journal:  Front Oncol       Date:  2019-12-03       Impact factor: 6.244

9.  Presence of S100A9-positive inflammatory cells in cancer tissues correlates with an early stage cancer and a better prognosis in patients with gastric cancer.

Authors:  Biao Fan; Lian-Hai Zhang; Yong-Ning Jia; Xi-Yao Zhong; Yi-Qiang Liu; Xiao-Jing Cheng; Xiao-Hong Wang; Xiao-Fang Xing; Ying Hu; Ying-Ai Li; Hong Du; Wei Zhao; Zhao-Jian Niu; Ai-Ping Lu; Ji-You Li; Jia-Fu Ji
Journal:  BMC Cancer       Date:  2012-07-28       Impact factor: 4.430

10.  Clinical Significance of Elevated S100A8 Expression in Breast Cancer Patients.

Authors:  Dujuan Wang; Guohong Liu; Balu Wu; Li Chen; Lihua Zeng; Yunbao Pan
Journal:  Front Oncol       Date:  2018-11-05       Impact factor: 6.244

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