Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2012 Dec 28;7(12):e50946. doi: 10.1371/journal.pone.0050946

Prognostic Significance of Tumor-Associated Macrophages in Solid Tumor: A Meta-Analysis of the Literature

Qiong-wen Zhang 1,#, Lei Liu 1,*,#, Chang-yang Gong 1,#, Hua-shan Shi 1, Yun-hui Zeng 1, Xiao-ze Wang 1, Yu-wei Zhao 1, Yu-quan Wei 1
Editor: Mohammad O Hoque2
PMCID: PMC3532403  PMID: 23284651

Abstract

Purpose

Tumor associated macrophages (TAMs) are considered with the capacity to have both negative and positive effects on tumor growth. The prognostic value of TAM for survival in patients with solid tumor remains controversial.

Experimental Design

We conducted a meta-analysis of 55 studies (n = 8,692 patients) that evaluated the correlation between TAM (detected by immunohistochemistry) and clinical staging, overall survival (OS) and disease free survival (DFS). The impact of M1 and M2 type TAM (n = 5) on survival was also examined.

Results

High density of TAM was significantly associated with late clinical staging in patients with breast cancer [risk ratio (RR)  = 1.20 (95% confidence interval (CI), 1.14–1.28)] and bladder cancer [RR = 3.30 (95%CI, 1.56–6.96)] and with early clinical staging in patients with ovarian cancer [RR = 0.52 (95%CI, 0.35–0.77)]. Negative effects of TAM on OS was shown in patients with gastric cancer [RR = 1.64 (95%CI, 1.24–2.16)], breast cancer [RR = 8.62 (95%CI, 3.10–23.95)], bladder cancer [RR = 5.00 (95%CI, 1.98–12.63)], ovarian cancer [RR = 2.55 (95%CI, 1.60–4.06)], oral cancer [RR = 2.03 (95%CI, 1.47–2.80)] and thyroid cancer [RR = 2.72 (95%CI, 1.26–5.86)],and positive effects was displayed in patients with colorectal cancer [RR = 0.64 (95%CI, 0.43–0.96)]. No significant effect was showed between TAM and DFS. There was also no significant effect of two phenotypes of TAM on survival.

Conclusions

Although some modest bias cannot be excluded, high density of TAM seems to be associated with worse OS in patients with gastric cancer, urogenital cancer and head and neck cancer, with better OS in patients with colorectal cancer.

Introduction

Macrophages are a population of innate myeloid cells that are released from bone marrow as immature monocytic precursors and, after circulating in the blood stream, migrate into different tissues to undergo specific differentiation depending on local cues in the tissue [1], [2]. In response to different environment stimuli, macrophages can appear a range of different phenotypes [3]. The extremes of this range are recognized; the classically activated type M1 phenotype and the alternative activated M2 phenotype. The M1 macrophages are thought to be induced by interferon-γ, with or without lipopolysaccharide, tumor necrosis factor (TNF)-α, and activate cells of the adaptive immune system [4]. Differentiation of the M2 macrophages is induced by IL-4 or IL-13 and associated with parasite clearance, wound healing and dampen immune responses [5].

In 1863, it was fist found that a major leukocyte population was present in tumor, the so-called tumor-associated macrophages (TAM), which reflect the onset of cancer at site of previous chronic inflammation [1], [6]. These macrophages can induce neoplastic cell (cytotoxicity, apoptosis) and/or elicit tumor destructive reactions with the capacity to display both negative and positive effects on tumor growth depending on environmental stimuli of the tumor tissue [7], [8].

For long a large number of studies have been focused on identifying the prognostic value of TAM in solid tumors and most studies suggest that TAM is beneficial for tumor growth and, therefore, associated with poor prognosis [1]. However, there are some exceptions with high density of macrophages correlating with increased survival in different tumors [9]–[18] and even this contradiction has come up in the one type of tumor [11], [19]. This meta-analysis focused on the identifying diverse roles and functions of TAM and subpopulations of TAM for clinical outcome in patients with solid tumors.

Materials and Methods

Identification and Eligibility of Relevant Studies

We performed our meta-analysis according to a predetermined written protocol. To be eligible for our meta-analysis, studies had to deal with solid tumor at inclusion, to evaluate the correlation between TAM and survival, and to be published in English or Chinese languages. A computer-aided literature search of Pubmed (MEDLINE) 1950-present and EMBASE was conduced by combing search terms “cancer”, ”tumor”, “neoplasm”, “carcinoma”, “tumor-associated macrophage”, “tumor-infiltrating macrophage” and “intratumoral macrophage.” The deadline of the included articles was April 20th, 2012. Reference list from primary identified studies were also searched to prevent missing any studies by the electronic search strategies.

Inclusion criteria for primary studies were as follows: (1) proven diagnosis of solid tumor in humans, (2) using immunochemistry method to evaluate TAM by anti-CD68, M1-type TAM by anti-HLA-DR and M2-type TAM by anti-CD163, and (3) correlation of TAM with TNM staging, OS or DFS. Two independent reviewers processed primary assessment by identifying the eligibility of abstracts from database. Full articles were retrieved for further assessment if the eligibility was unclear from the abstracts. Any disagreements were resolved by serious discussion. We carefully examined the names of all authors and the medical centers involved in each publication to avoid duplication data. Whenever studies pertained to overlapping patients, we retained the studies with highest number of patients.

Definitions and Standardizations

We used preconcerted rules to standardize as much as possible the definition of TAM positivity. As 20% was the used as a cutoff value in majority of the included studies [18], [20]–[26], we defined TAM positivity as positive cell stain in at least 20% of tumor cells. When different definitions were used, we contacted the primary author of each articles to retrieve the cutoff value they used. When cutoff value was not possible to retrieve, we accepted the cutoff was closet to the 20% cutoff level. When cutoff value was closed to 20%, which ranged from 16.3% to 25%, we also accepted the cutoff as 20%.

Data Extraction

Data were carefully extracted from all of the included studies in duplicate by two of us, using a standard information collection form, with the following items, first author, year of publication, study design, median follow-up time, country of origin, number of patients involved, number of men included, mean or median age, tumor location, histological type, tumor-node-metastasis (TNM) staging, blinded reading, definition of TAM high, anti-cancer treatment(s) during follow up, OS or DFS or both. The main outcomes were tabulated in 2×2 tables showing the TNM staging status, occurrence or not of death or disease during follow-up according to TAM results.

Statistical Analyses

Included studies were divided into three groups for analysis: those with data regarding TNM staging, those regarding OS and those regarding DFS. A study was considered significant when the P for comparing survival distribution between groups with high and low TAM was inferior to 0.05. A study was termed “positive” when a high TAM predicted a late clinical staging or poorer survival, “negative” when a high TAM predicted a early clinical staging or better survival, “indeterminate” when no significant relationship between TAM and clinical staging or survival was found.

For the quantitative aggregation of survival result, impacts of TAM on survival were reported for individual studies by estimating RRs with 95% confidence interval values. We first simply extracted RR and their 95%CI from the original article. If not available, the published data including number of patients at risk and total number of events in each groups from articles were used to estimate RR according to the methods described by Parmer et al [27]. When data were only available in the form of figures, we read Kaplan-Meier curves by Engauge Digitizer version 4.1 (free software down-loaded from http://sourceforge.net) and extracted survival data to reconstruct RRs and its 95%CI. An observed RR>1 indicated worse outcome for the TAM high group relative to TAM low group and would be considered statistically significant if the 95%CI did not overlap 1, with p<0.05. Sensitivity analyses were performed to examine the TAM effect of limiting the evaluation to studies using the 20% cutoff on prognosis. The effect of publication bias on the outcomes was assessed graphically using funnel plots, and funnel plot asymmetry was assessed by Egger's linear regression method. (p<0.05 was considered statistically significant publication bias) [28]. Meta-analyses were carried out by the Stata version 11.0 (Stata Corporation, College Station, TX, USA).

Results

Studies Selection and Characteristics

The initial search algorithm retrieved a total of 3076 references and we evaluated 144 candidate studies in full text. Upon further review, 50 articles were eliminated due to inadequate data for meta-analysis and another 29 articles were out of scope because of evaluating other factors related to TAM (Figure 1). Overall, we identified 55 articles (n = 8693) with TAM measurements in patients with solid tumors.

Figure 1. Flow chart of the literature search and selection of included studies.

Figure 1

Open in a new tab

The characteristics of included studies are listed in Table 1. The median sample size for all studies was 158 patients (range = 24–1902). The median sample size for staging was 189 patients, that for OS was 164 patients and that for DFS was 202 patients. The total proportion of male subjects was around 45% and that of patients in grade I/II was 43%. All evaluated IHC staining in formalin-fixed paraffin-embedded tissue blocks. The study design was more often a retrospective (N = 25) than a prospective cohort study (N = 5). Only 20% studies had performed blinded reading during evaluating TAM. The median follow-up time for all included studies ranged from 1.84 to 25 years. Of the 55 studies, cut-off value for definition of TAM high only could be retrieved from 32 original articles or by contacting authors.

Table 1. Characteristics of the eligible studies.

First author (ref) Year Study design n (M/F) Tumor location Tumor stage I/II (III/IV) Median follow-up (y) Blinded reading Staining for TAM high RR estimation Analysis Result
Gastrointestinal cancer (N = 19)
Khorana (29) 2003 Prosp. 131 (69/53) 131 Colon 11 (118) 5 NR >2% Data extrapolated, Survival curve Stag., OS Indeterminate
Tan (12) 2005 Retro. 60 (35/25) 60 Colon 26 (34) NR NR >25% Data extrapolated, Survival curve Stag., OS Negative
Bacman (30) 2007 NR 310 (189/121) 310 Colon 178 (132) 7.5 NR NR Data extrapolated OS Indeterminate
Forssell (15) 2007 Retro. 488 (271/217) 488 Colon 207 (254) NR NR NR Data extrapolated, Reported in text Stag., OS Indeterminate, negative
Zhou (18) 2010 NR 160 (94/66) 160 Colon NR 5 Yes 20% Data extrapolated, reported in text Stag., OS Negative
Ishigami (31) 2003 Retro. 97 (72/25) 97 Stom 67 (30) NR NR >200 / HPF Data extrapolated, Survival curve Stag., OS Indeterminate, positive
Ohno (10) 2005 Retro. 84 (57/27) 84 Stom 41 (43) NR Yes >4.7% Survival curve DFS Negative
Hass (32) 2009 Prosp. 52 (40/12) 50 Stom 39 (13) 5.9 NR NR Reported in text DFS Indeterminate
Kawahara (33) 2010 NR 111 (77/34) 111 Stom 36 (75) NR NR NR Reported in text OS Positive
Osinsky (34) 2011 Prosp. 105 (71/34) 105 stom 48 (57) NR NR >23.0% Reported in text OS Positive
Zhu (22) 2008 Retro. 105 (96/9) 105 Liver 86 (19) 1.84 NR >20% Data extrapolated, reported in text Stag., OS, DFS Indeterminate, positive
Li (24) 2009 Retro. 302 (260/42) 302 Liver 237 (65) 4.83 NR >20% Data extrapolated, reported in text Stag., OS, DFS Indeterminate, negative
Ding (35) 2009 Retro. 107 (87/20) 107 Liver 98 (39) 2.5 MR >23% Reported in text OS, DFS Positive
Kuang (36) 2009 Retro. 262 (NR) 206 Liver 249 (13) NR NR NR Reported in text OS, DFS Positive
Ju (23) 2009 Retro. 130 (112/18) 130 Liver 66 (64) 2.65 NR >20% Reported in text Stag., OS, DFS Positive
Koide (9) 2002 Retro. 56 (42/14) 56 Esophagus 30 (26) NR NR NR Data extrapolated, survival cure Stag., OS Indeterminate, negative
Guo (19) 2007 NR 137 (103/34) 137 Esophagus 86 (51) NR NR >25% Reported in text Stag., OS Indeterminate, positive
Kurahara (37) 2012 Retro. 76 (52/24) 52 Pancreas 29 (47) NR Yes NR Survival curve OS, OSb Indeterminate
Hasita (38) 2010 NR 39 (27/12) 55 Bile duct 29 (10) 3.33 Yes NR Data extrapolated, survival curve Stag., OS, DFS, Stag.b, OSb, DFSb Indeterminate
Urogenital cancer (N = 20)
Leek (39) 1996 Retro. 101 (0/101) 5 Breast NR NR NR MD > = 12 Reported in text OS, DFS Positive
Toi (40) 1999 NR 229 (0/229) 229 Breast NR 4 Yes NR Survival curve DFS Indeterminate
Valkovic (41) 2002 NR 97 (0/97) 97 Breast 82 (15) NR NR NR Data extrapolated Stag. Indeterminate
Bolat (42) 2006 Retro. 78 (0/78) 78 Breast 38 (10) NR NR NR Data extrapolated Stag. Indeterminate
Mahmound (43) 2012 Retro. 1902 (0/1902) 1902 Breast 220 (1682) NR NR NR Data extrapolated, survival curve Stag., DFS Positive, indeterminate
Salvesen (44) 1999 Prosp. 60 (0/60) 60 Endometrium 50(10) 11 NR NR Data extrapolated, reported in text Stag., OS Positive, indeterminate
Hashimoto (45) 2000 NR 109 (0/109) 109 Endometrium 56(53) 4.58 NR NR Data extrapolated Stag., DFS Indeterminate
Ohno (11) 2004 Retro. 70 (0/70) 70 Endometrium NR NR NR MD >10.7 Survival curve DFS Negative
Soeda (46) 2008 Retro. 76 (0/76) 76 Endometrium 59(17) 6.83 NR NR Survival curve OS, DFS Positive, indeterminate
Espinosa (47) 2010 NR 64 (0/64) 64 Endometrium 23(26) NR NR NR Data extrapolated Stag.b Indeterminate
Lissbrant (48) 2000 Retro. 85 (85/0) 85 Prostate 75(10) NR NR > = 0.97% Survival curve Stag., OS Indeterminate
Shimura (49) 2000 NR 81 (81/0) 81 Prostate 67(13) 3.9 NR NR Reported in text DFS Indeterminate
Nonomura (50) 2011 NR 131 (131/0) 131 Prostate 30(41) 2.9 NR MD > = 22 Survival curve DFS Positive
Heller (51) 2002 Retro. 24 (0/24) 24 Cervix 20/4 NR NR NR Data extrapolated Stag. Indeterminate
Kawanaka (52) 2008 Retro 73 (0/73) 73 Cervix 22/51 NR Yes MD > = 55 Survival curve DFS Indeterminate
Hanada (53) 2000 NR 63 (51/12) 63 Bladder 42/21 5.4 Yes MD > = 67 Data extrapolated, reported in text Stag., OS Positive
Takayama (54) 2009 NR 41 (38/3) 41 Bladder NR 25 NR > = 4 Reported in text DFS Positive
Tanaka (55) 2004 NR 89 (0/89) 89 Ovary 22/67 6.8 NR > = 25% Data extrapolated, reported in text, survival curve Stag., OS, DFS Negative, positive, indeterminate
Wan (25) 2009 NR 67 (0/67) 67 Ovary 0/67 NR NR >20% Survival curve OS Positive
Chai (20) 2008 NR 99 (42/57) 99 Uroth NR NR NR >20% Reported in text OS, DFS Indeterminate, positive
Lung cancer (N = 10)
Takanami (56) 1999 Retro. 113 (66/47) 113 Lung 61/52 NR NR MD>32 Survival curve OS Positive
Chen (57) 2005 NR 41 (27/14) 41 Lung 23/18 NR NR MD> = 163 Survival curve DFS Indeterminate
Welsh (13) 2005 Retro. 175 (116/59) 175 Lung 123/38 NR Yes NR Data extrapolated Stag., DFS Negative
Zeni (58) 2007 NR 50 (43/7) 43 Lung NR NR NR >16.3% Reported in text, survival curve Stag., OS Positive
Kawai (16) 2008 NR 199 (139/60) 199 Lung NR NR NR NR Reported in text OS Negative
Ohri (17) 2009 Retro. 40 (16/24) 40 Lung 34/6 NR NR NR Survival curve OS Negative
Al-shibli (59) 2009 Retro. 371 (253/82) 371 Lung 303/32 8 NR > = 25% Data extrapolated, survival curve OS, DFS Indeterminate
Ma (26) 2010 NR 50 (40/10) 50 Lung 33/17 NR NR >20% Reported in text OSa, OSb Indeterminate
Ohtaki (60) 2010 Prosp. 170 (85/85) 170 Lung NR 10.1 NR NR Data extrapolated Stag., OS Positive
Zhang (61) 2011 Retro. 65 (38/27) 65 Lung 38/27 NR Yes TAM counts >102 Survival curve OS Positive
Head and neck cancer (N = 4)
Liu (21) 2008 NR 112 (93/19) 112 Oral 50/62 NR NR >20% Data extrapolated, survival curve Stag., OS Positive
Fujii (62) 2012 NR 108 (31/10) 108 Oral 46/62 NR NR > = 2/HPF Data extrapolated, reported in text Stag., stag.b, OSb Positive, indeterminate, positive
Peng (14) 2006 NR 60 (38/22) 60 Oral 15/45 NR NR > = 63.7/HPF Data extrapolated OS Negative
Lin (63) 2011 NR 84 (77/7) 84 Lar 30/54 NR NR > = 10/HPF Data extrapolated, reported in text Stag., OS, DFS Indeterminate, indeterminate, positive
Thyroid cancer (N = 1)
Ryder (64) 2008 NR 37 (13/24) 37 Thyr 5/32 NR Yes > = 10/HPF Survival curve OS Positive
Mesothelioma (N = 1)
Burt (65) 2011 Retro. 667 (531/136) 667 Meso 64/603 NR Yes NR Reported in text OS Indeterminate
Open in a new tab

Of the included studies, 19 studies focused on gastrointestinal cancers, including colorectal cancer (N = 5), gastric cancer (N = 5), liver cancer (N = 5), esophagus cancer (N = 2), pancreatic caner (N = 1) and cholangiocarcinoma (N = 1). 20 studies analyzed the impact of TAM on survival in patients with urogenital cancers, including breast cancer (N = 5), endometrial cancer (N = 5), prostate cancer (N = 3), cervical cancer (N = 2), bladder cancer (N = 2), ovary cancer (N = 2) and urothelial cancer (N = 1). 5 studies mentioned the value of M2-type TAM on survival [26], [37], [38], [47], [62].

Data Synthesis: Clinical Staging

As shown in Figure 2A, the combining data of TAM on clinical staging showed a nonstatistically significant RR of 1.13 (95%CI 0.97–1.31). For sub-group analysis, all of the studies were dispatched into several classes according to the tumor location. Our data showed that high density of TAM was significantly higher in patients with advanced tumor stage (III+IV) than in the patients with early stage (I+II), which occurred in breast cancer [RR = 1.20 (95%CI, 1.14–1.28)], oral cancer [RR = 1.49 (95%CI, 1.17–1.89)] and bladder cancer [RR = 3.30 (95%CI, 1.78–7.92)],whereas 1 article focused on ovary cancer found high density of TAM was associated with early stage [RR = 0.52 (95%CI, 0.36–0.77)]. Other sub-group analysis found no relation between TAM and clinical staging. In studies specific defining TAM positivity as at least 20% positive staining cells in tumor tissue, no significant relation was found between TAM and clinical staging (RR = 1.23 (95%CI, 0.74–2.02). Analysis for M2-type TAM on staging also showed no significant effect [RR = 1.43 (95%CI, 0.70–2.93)].

Figure 2. Forrest plots and meta-analysis of studies evaluating RR of high TAM counts as compared to low counts.

Figure 2

Open in a new tab

Clinical staging and survival data are reported as (A) staging, (B) overall survival (OS) and (C) disease free survival (DFS).

Data Synthesis: Overall Survival

For overall population, high density of TAM was associated with a worse prognosis regarding overall survival (Figure 2B). However, mortality was only 1.15-fold higher in high TAM patients with solid tumor, which showed modest effect. In sub-group analysis (Figure 3), high density of TAM was significantly correlated with poor OS in patients with urogenital cancer [RR = 1.95 (95%CI, 1.32–2.86)], including breast cancer [RR = 8.62 (95%CI, 3.10–23.95)], endometrial cancer [RR = 1.85 (95%CI, 0.10–34.63)], prostate cancer [RR = 1.16 (95%CI, 0.96–1.40)], bladder cancer [RR = 5.00 (95%CI, 1.98–12.63)], ovary cancer [RR = 2.55 (95%CI, 1.60–4.06)] and urothelial cancer [RR = 1.01 (95%CI, 1.32–2.86)]. In addition, gastric cancer and oral cancer showed significant RR between TAM and OS [RR = 1.54 (95%CI 1.24–2.16), 2.03 (95%CI 1.47–2.80)]. However, analysis of studies on colorectal cancer showed that there was a significant correlation between high density of TAM and longer OS [RR = 0.64 (95%CI, 0.43–0.96)]. No significant correlation between TAM and OS was found in other sub-group analysis. Five studies reported that there was no significant correlation between M2-type TAM and OS [RR = 0.98 (95%CI, 0.71–1.35)], one study reported that the M1-type TAM density in the tumor islet is positively associated with extended survival in patients with lung cancer [17]. There was also no difference in the summary estimate of TAM on overall survival when cutoff value was specific to 20% (RR = 1.41 (95%CI, 1.03–2.09).

Figure 3. Forrest plots and meta-analysis of studies evaluating RR of high TAM counts as compared to low counts in different subgroup of tumors.

Figure 3

Open in a new tab

Clinical staging and survival data are reported as (A) gastrointestinal cancer, (B) urogenital cancer, (C) lung cancer and (D) head and neck cancer.

Data Synthesis: Disease free survival

For the overall population, no significant relation was observed between TAM and DFS [RR = 1.01 (95%CI, 0.99–1.04)](Figure 2C). No significant effect was showed in sub-group analysis. One article [38] with data on M2-type TAM and DFS also showed a non-significant effect [RR = 1.09 (95%CI, 0.77–1.54)]. Analysis for specific 20% cutoff also showed no significant effect (RR = 1.19 (95%CI, 0.78–1.57).

Data Synthesis in sub-groups: clinic-pathological factors

The impact of TAM density on clinic-pathological in patients with different cancer was further analyzed and described in Table 2. Two studies [12], [29] showed a significant correlation between T status and TAM density, nevertheless, no correlation was found between TAM density and lymph node metastasis nor distant metastasis. High density of TAM was also correlated with nonmucinous type of colon cancer. Additionally, two of the studies on gastric cancer described that low density of TAM was significantly correlated with lymph node metastasis [31], [32]. In the breast cancer group, Negative effects of TAM were found not only on TNM stage, but also histological grade, lymph node metastasis, tumor size, vascular invasion and HER-2 status. Similar phenomena were seen in bladder cancer and oral squamous group, and high density of TAM was significantly correlated with TNM stage, T status, lymph node metastasis and distant metastasis. In addition, one study demonstrated that the density of TAM was significantly lower in patients with advanced tumor stage (III/IV) than in patients with early stage (I/II) [55].

Table 2. Meta-analysis of the subgroups based on clinic-pathological factors related to TAM density from the available published studies.

Cancer type Clinic-pathological factors Number of studies Number of total patients HR (95% CI) p-value Results Reference
Colon cancer
TNM Stage (I/II vs. III/IV) 2 619 0.71 (0.35, 1.45) 0.194 Indeterminate (15), (29)
T status (T1/T2 vs. T3/T4) 2 191 0.35 (0.13, 0.90) 0.246 Positive (12), (29)
Lymph node metastasis 2 370 0.72 (0.13, 4.06) 0.013 Indeterminate (12), (30)
Distant metastasis 3 530 0.72 (0.24, 2.11) 0.005 Indeterminate (12), (18), (30)
Histological grade (well/moderate vs. poor) 3 858 0.26 (0.06, 1.06) 0.005 Indeterminate (12), (15), (30)
Pathologic classification (mucinous vs. nonmucinous) 2 648 2.53 (1.35, 4.73) 0.675 Negative (15), (18)
Gastric cancer
TNM Stage (I/II vs. III/IV) 1 97 2.40 (0.98, 5.91) NR Indeterminate (31)
T status (T1/T2 vs. T3/T4) 1 97 1.36 (0.54, 3.46) NR Indeterminate (31)
Lymph node metastasis 2 149 0.39 (0.19, 0.80) 0.302 Positive (31), (32)
Distant metastasis 1 52 1.30 (0.40, 4.28) NR Indeterminate (32)
Histological grade (well/moderate vs. poor) 1 97 0.54 (0.22, 1.32) NR Indeterminate (31)
Liver cancer
TNM Stage (I/II vs. III/IV) 3 514 1.27 (0.84, 1.93) 0.702 Indeterminate (22), (24), (35)
Vascular invasion (absent vs. present) 3 514 1.38 (0.87, 2.21) 0.410 Indeterminate (22), (24), (35)
Tumor differentiation 2 409 1.08 (0.70, 1.66) 0.956 Indeterminate (24), (35)
Tumor size (≤5 vs. >5cm) 2 409 1.76 (1.19, 2.60) 0.329 Negative (24), (35)
Hepatitis history (No vs. Yes) 2 407 1.45 (0.80, 2.60) 0.456 Indeterminate (22), (24)
Liver cirrhosis (No vs. Yes) 3 514 1.18 (0.75, 1.88) 0.886 Indeterminate (22), (24), (35)
Fibrous capsule (absent vs. present) 3 514 0.83 (0.58, 1.19) 0.750 Indeterminate (22), (24), (35)
Esophagus cancer
T status (T1/T2 vs. T3/T4) 1 56 2.73 (0.70, 10.60) NR Indeterminate (9)
Lymph node metastasis 1 56 0.75 (0.21, 2.59) NR Indeterminate (9)
Lymphatic invasion (absent vs. present) 1 56 3.21 (0.81, 12.8) NR Indeterminate (9)
Venous invasion (absent vs. present) 1 56 6.22 (1.48, 26.1) NR Negative (9)
Intrahepatic cholangiocarcinoma
UICC stage (I/II vs. III/IV) 1 55 3.31 (0.71, 15.4) NR Indeterminate (38)
Histological grade (well/moderate vs. poor) 1 55 5.25 (0.93, 29.7) NR Indeterminate (38)
Lymph node metastasis 1 55 1.06 (0.19, 6.05) NR Indeterminate (38)
Vascular invasion (absent vs. present) 1 55 2.13 (0.34, 13.2) NR Indeterminate (38)
Tumor size (<4 vs. ≥4cm) 1 55 1.38 (0.39, 4.87) NR Indeterminate (38)
Breast cancer
TNM Stage (I/II vs. III/IV) 1 78 1.20 (1.14, 1.28) NR Negative (42)
Histological grade (I/II vs. III) 3 2077 3.42 (2.71, 4.30) 0.742 Negative (41), (42), (43)
Lymph node metastasis 3 2077 1.29 (1.04, 1.62) 0.604 Negative (41), (42), (43)
Tumor size (≤2 vs. >2cm) 3 2077 1.43 (1.14, 1.80) 0.963 Negative (41), (42), (43)
Vascular invasion (absent vs. present) 1 1902 1.74 (1.35, 2.23) NR Negative (43)
HER-2 status (negative vs. positive) 1 1902 2.59 (1.75, 3.85) NR Negative (43)
Endometrial cancer
FIGO stage (I/II vs. III/IV) 2 169 2.34 (0.36, 15.39) 0.021 Indeterminate (44), (45)
Lymph node metastasis 1 109 0.43 (0.12, 1.53) NR Indeterminate (45)
Myometrial invasion (negative vs. positive) 1 109 2.09 (0.65, 6.69) NR Indeterminate (45)
Histological grade (I/II vs. III) 2 169 4.34 (0.70, 27.08) 0.044 Indeterminate (44), (45)
Pathologic classification (Endometrioid vs.non-endometrioid) 1 109 1.37 (0.41, 4.62) NR Indeterminate (45)
Prostate cancer
T status (T1/T2 vs. T3/T4) 1 85 3.30 (1.56, 6.96) NR Indeterminate (48)
Distant metastasis 1 85 1.06 (0.25, 4.54) NR Indeterminate (48)
Cervical cancer
FIGO stage (I/II vs. III/IV) 2 97 0.68 (0.06, 8.26) 0.063 Indeterminate (51), (52)
Lymph node metastasis 1 24 1.75 (0.26, 11.7) NR Indeterminate (51)
Bladder cancer
TNM Stage (I/II vs. III/IV) 1 63 5.76 (1.76, 18.9) NR Negative (53)
T status (T1/T2 vs. T3/T4) 1 63 17.6 (4,34, 71.1) NR Negative (53)
Distant metastasis 1 63 12.4 (2.50, 61.0) NR Negative (53)
Vascular invasion (absent vs. present) 1 63 10.8 (1.26, 92.4) NR Negative (53)
Ovary cancer
TNM Stage (I/II vs. III/IV) 1 89 0.52 (0.35, 0.77) NR Positive (54)
Lymph node metastasis 1 89 0.14 (0.05, 0.35) NR Positive (54)
Tumor differentiation 1 89 0.79 (0.34, 1.83) NR Indeterminate (54)
Tumor size (≤5 vs. >5cm) 1 89 0.94 (0.41, 2.17) NR Indeterminate (54)
Histological type (serous vs. nonserous) 1 89 0.81 (0.34, 1.9) NR Indeterminate (54)
Lung cancer
Pathologic stage (I vs. II/III/IV 2 345 1.29 (0.24, 6.78) <0.001 Indeterminate (13), (60)
Tumor differentiation 1 170 5.80 (2.99, 11.2) NR Negative (60)
T status (T1/T2 vs. T3/T4) 1 170 2.70 (1.40, 5.21) NR Negative (60)
Lymph node metastasis 1 170 2.72 (1.27, 5.82) NR Negative (60)
Vessel invasion 1 170 3.24 (1.69, 6.24) NR Negative (60)
Oral squamous cell carcinoma
TNM Stage (I/II vs. III/IV) 2 220 2.53 (1.46, 4.38) 0.888 Negative (21), (62)
T status (T1/T2 vs. T3/T4) 2 220 2.33 (1.34, 4.03) 0.328 Negative (21), (62)
Lymph node metastasis 2 220 2.56 (1.46, 4.47) 0.528 Negative (21), (62)
Tumor differentiation 2 220 1.32 (0.68, 2.57) 0.294 Indeterminate (21), (62)
Thyroid cancer
TNM Stage (I/II vs. III/IV) 1 37 4.31 (0.42, 43.7) NR Indeterminate (64)
Distant metastasis 1 37 4.17 (0.66, 26.1) NR Indeterminate (64)
Open in a new tab

Evaluation of publication bias

Both Begg's funnel plot and Egger's test were performed to assess the publication bias in all studies evaluating staging, OS, DFS separately, and evaluation was also performed in sub-group analysis. Begg's funnel plot did not reveal any evidence of significant asymmetry in the overall meta-analysis of staging (p = 0.679), OS (p = 0.065) and DFS (p = 0.792)(Figure 4). There was also no indication of publication in Egger's test of staging (p = 0.993), OS (p = 0.058) and DFS (p = 0.357). For sub-group evaluation of publication bias, no significant publication bias was shown from either Egger's or Begg's test (not shown).

Figure 4. Funnel graph for assessment of potential publication bias in studies of TAM density in patients with solid tumor.

Figure 4

Open in a new tab

(A) Staging, (B) OS, (C) DFS. The funnel graph plots log HR against the standard error of the log HR. The result of the Egger's test showed no statistical significant (p>0.05).

Discussion

So far, a group of original articles and reviews has studied the prognostic significance of TAM in solid tumors, and the presence of both significant and non-significant studies addressing the importance of TAM on survival made it necessary to perform a quantitative aggregation of the survival results. The present result showed that high density of TAM, as detected with immunohistochemistry, was significant associated with worse overall survival in solid tumor, with a global RR of 1.15. As potential bias exists between studies on different tumors, subgroup analysis was also performed, which suggested that high density of TAM was significant associated with OS in patients with gastric cancer [RR = 1.64 (95%CI, 1.24–2.16)], breast cancer [RR = 8.62 (95%CI, 3.10–23.95)], bladder caner [RR = 5.00 (95%CI, 1.98–12.63)], ovarian cancer [RR = 2.55 (95%CI, 1.60–4.06)], oral cancer [RR = 2.03 (95%CI, 1.47–2.80)] and thyroid cancer [RR = 2.72 (95%CI, 1.26–5.86)]. Moreover, there showed positive effect in patients with colorectal cancer [RR = 0.64 (95%CI, 0.43–0.96)]. However, no significant effect was seen between TAM and DFS.

When comparing the results of different types of tumors, several key differences were observed. As mentioned above, although macrophages under certain conditions can kill tumor cells, they can also play potential roles as tumor promoters to secrete a variety of factors that directly stimulate tumor invasion and metastasis. The combing effect of TAM on prognosis in patients with different tumors depends on stimulating factors from two opposite aspects in tumor environments. In this meta-analysis, we reach a conclusion that high TAM infiltration is associated with worsen prognosis in patients with urogenital cancer or gastric cancer, not all cancer type. In other hand, TAM showed antitumorigenic properties in combing 5 studies on colorectal cancer, resulting in improved prognosis.

To further investigate the prognostic value of TAM in different type of cancer, we analyzed the relation between the density of TAM and clinic-pathological factors that was also associated with outcome of cancer patients. As the density of TAM has a negative effect on survival in patients with gastric cancer, breast cancer, bladder cancer, ovary cancer, and oral squamous cell carcinoma, negative effects are also seen in clinic-pathological factors such as TNM staging (breast cancer, bladder cancer and oral squamous cell carcinoma), T status (breast cancer and oral squamous cell carcinoma), lymph node metastasis (breast cancer, bladder cancer and oral squamous cell carcinoma), and distant metastasis (bladder cancer), which contributed to tumor progression and patient survival. Interestingly, there also demonstrated a positive effect of TAM on lymph node metastasis in gastric and ovary cancer, which indicated that high density of TAM was associated with less probability of lymph node metastasis, however, significant negative effect was shown on overall survival. Thus, more studies are needed to clarify this ambivalent phenomenon. Contrary to tumors we mentioned above, our data suggested that an incremental increase in density of TAM improved overall survival in patients with colon cancer, with a homodromous effect on T status. There was also a trend towards lower rate of lymph node metastasis and distant metastasis in TAM rich tumors. In addition, a high density of TAM infiltration was found related to nonmucious type of colon cancer.

The mechanisms behind the oncogenic and anti-tumorigenic effects of TAMs have not been fully elucidated and a great number of studies have focused on explaining these apparently contradictory effects of TAM in different cancer outcome. The functions of TAM in different type of tumors are concerned as the most important determining factor to the prognosis, which are profoundly affected by microenvironmental signals and can range from powerful stimulation of inflammatory responses to induction of immunosuppression [66]. Tumor necrosis factor (TNF)-α, nitric oxide (NO), and monocyte chemoattractant protein (MCP)-1 released from TAM are major intermediate molecules for tumor cell killing [67]–[69], and TAM associated vascular endothelial growth factor (VEGF) and matrix metalloproteinases (MMPs) are independent predictor of poor prognostic factor in cancer patients [34]. In addition, a macrophage balance hypothesis between M1 and M2 type macrophages has been proposed and two different macrophage populations range from polarized potent killer M1 cells to alternatively activated M2 macrophages with tumor-promoting capability [70]. However, this study showed no significant relation between the density of two phenotype of TAM and survival of patients. Furthermore, histological classification of the tumor should also be considered as a factor correlated with the function of TAM. A previous study on colon cancer demonstrated that a histologically more malignant phenotype was associated with macrophage infiltration, disorganized matrix deposition, and extensive stromal reaction [71]. In one included study of this meta-analysis, the number of infiltrating TAM was found to be significantly correlated with poor outcome in patients with intestinal type of gastric cancer, but not in patients with diffuse type, indicating that TAM could affect malignant progression and prognosis on the basis of the histological type of gastric cancer [33].

Although the results of meta-analysis are considered as gold standards by authors worldwide [72], potential bias still exists between studies and cannot be completely eliminated. Although Begg's funnel plot and Egger's test were performed in this meta-analysis and found no statistically significant publication bias, results of this study should be interpreted very cautiously and several aspects of importance in this field should be discussed. First of all, we only included studies from which we could extract RR or estimate RR, leading to data inaccessible for data aggregation from studies, which only showed the conclusion on this topic without data presented. Take one excluded study on evaluating the prognostic value of TAM on oral cavity and oropharyngeal squamous cell carcinoma for example, they found that macrophage content was an independent predictor of lymph node metastasis, however, no data was accessible for meta-analysis from this study [73]. Furthermore, considerable attention should be paid to some cancers with few study included in this meta-analysis study. TAM was found associated with worse prognosis in one study on oral cancer [RR = 2.03 (95%CI, 1.47–2.80)] [21] and one study on thyroid cancer [RR = 2.72 (95%CI, 1.26–5.86)] [64]. As meta-analysis could not be performed with such small number of primary studies, more researches are needed in further investigation on these tumors.

Second, macrophages can be identified by cell surface markers, expression of transcriptional factors, the production of cytokines and their functions in vitro [2]. However, we only included literatures evaluating TAM with the use of antibodies to the glycoprotein CD68. Sikert et al quantified TAM by immunohistochemistry with antibodies to PG-M1, KP-1, MRP8, MRP14 and MRP8/14 antigens and found different TAM subpopulation were positively correlated with clinicopathological characteristics in colon cancer [74]. Macrophage differentiation, growth, and chemotaxis are regulated by several growth factors, including colony-stimulating factor (CSF)-1, macrophage chemoattractant protein (MCP)-1 and extracellular matrix protease such as urokinase-type plasminogen activator (uPA) [75]. For example, over expression of CSF is associated with poor prognosis in nongynecological leiomyosarcoma [76]. In breast cancer, TAM density is showed correlated with angiogenesis and poor prognosis [77]–[79]. Ohba et al provide the evidence that uPA has prognostic value in patients with renal cell carcinoma via TAM [80]. Also other factors could be used to evaluate M1 and M2 type macrophages in tumor tissues. As M2 type TAM express high level of interleukin-10 (IL-10) which can be used to discriminate between M1 and M2 macrophages [81], [82], a study assessed IL-10 expression in TAM, and found the high level of IL-10 in TAM significantly correlated with clinical staging and histologic poor differentiation in patients with lung cancer [83]. So, considerable attention should be paid to various kinds of factors related to density of TAM, which might be a potential prognostic marker in solid tumor.

Third, variability in definitions, outcomes, measurements, experimental procedure, and even antibody concentration may contribute to heterogeneity between studies [84]. Multivariate analyses was tried to minimize confounding bias, but the factors controlled for were few and differed between studies. Quality criteria are needed for future studies in this field, and we make the following recommendation: blindly assess the prognostic marker to patient outcome, adequately describe the assay method used for TAM evaluation including antibody concentration and cut-off value staining for TAM high, and precisely define outcome with certain follow-up time. More importantly, in this meta-analysis, some studies have used 20% as the cutoff value, whereas others have chosen score system, mean, median or arbitrary cutoff values, thus cutoff value is a source of considerable interstudy heterogeneity. Although specific synthesis of studies using standardized cutoff value on survival did not differ significantly form the overall result in the total population analysis, conclusions need to be considered cautiously.

In conclusion, it is clear that TAM has protumorigenic as well as antitumorigenic properties in solid tumor. As discussed above, there have been showed a “macrophage balance” on prognosis depending on the microenvironment of the tumor tissue in different type of solid tumor. It may be possible in the future to use or induce activated macrophages to restrain tumor growth and improve patient survival, through altering tumor microenvironment. Moreover, targeted therapies that uniquely strike macrophages may provide innovative therapeutic strategies against tumor progression.

Acknowledgments

We thank all authors whose publications could be included in our meta-analysis, and especially Prof. Liu G (Chinese Evidence-Based Medicine Centre, West China Hospital, Sichuan University, Chengdu, China), Nie Y (West China School of Medicine, Sichuan University, GuoXueXiang 37#, Chengdu, China) for providing us with statistical guidance.

Funding Statement

This work was financially supported by National Natural Science Foundation of China (NSFC 81101729). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1. Bingle L, Brown NJ, Lewis CE (2002) The role of tumour-associated macrophages in tumour progression: implications for new anticancer therapies. J Pathol 196: 254–265. [DOI] [PubMed] [Google Scholar]
  • 2. Heusinkveld M, van der Burg SH (2011) Identification and manipulation of tumor associated macrophages in human cancers. J Transl Med 9: 216. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Siveen KS, Kuttan G (2009) Role of macrophages in tumour progression. Immunol Lett 123: 97–102. [DOI] [PubMed] [Google Scholar]
  • 4. Mantovani A, Sozzani S, Locati M, Allavena P, Sica A (2002) Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes. Trends Immunol 23: 549–555. [DOI] [PubMed] [Google Scholar]
  • 5. Biswas SK, Mantovani A (2010) Macrophage plasticity and interaction with lymphocyte subsets: cancer as a paradigm. Nat Immunol 11: 889–896. [DOI] [PubMed] [Google Scholar]
  • 6.Virchow R (1863) Aetologie der neoplastichen Geschwulste/ Pathogenie der neoplastischen Geschwulste. Die Krankhaften Geschwulste Berlin: Verlag von August Hirshwald: 57–101.
  • 7.Mantovuni BB, Colotta F, Sozzani S, Ruco L (1992) The origin and function of tumor associated macrophages. Immunol Today 13: p. 2–74. [DOI] [PubMed]
  • 8. Mantovuni A (1994) Biology of disease: tumor-associated macrophages in neoplastic progression: a paradigm for the in vivo function of chemokines. Lab Invest 71: 5–16. [PubMed] [Google Scholar]
  • 9. Koide N, Nishio A, Hiraguri M, Kishimoto K, Nakamura T, et al. (2002) Differences and relationships of thymidine phosphorylase expression in tumor-associated macrophages and cancer cells in squamous cell carcinoma of the esophagus. Dis Esophagus 15: 67–73. [DOI] [PubMed] [Google Scholar]
  • 10. Ohno S, Inagawa H, Dhar DK, Fujii T, Ueda S, et al. (2003) The degree of macrophage infiltration into the cancer cell nest is a significant predictor of survival in gastric cancer patients. Anticancer Res 23: 5015–5022. [PubMed] [Google Scholar]
  • 11. Ohno S, Ohno Y, Suzuki N, Kamei T, Koike K, et al. (2004) Correlation of histological localization of tumor-associated macrophages with clinicopathological features in endometrial cancer. Anticancer Res 24: 3335–3342. [PubMed] [Google Scholar]
  • 12. Tan SY, Fan Y, Luo HS, Shen ZX, Guo Y, et al. (2005) Prognostic significance of cell infiltrations of immunosurveillance in colorectal cancer. World J Gastroenterol 11: 1210–1214. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Welsh TJ, Green RH, Richardson D, Waller DA, O'Byrne KJ, et al. (2005) Macrophage and mast-cell invasion of tumor cell islets confers a marked survival advantage in non-small-cell lung cancer. Journal of Clinical Oncology 23: 8959–8967. [DOI] [PubMed] [Google Scholar]
  • 14. Peng J, Ding T, Zheng LM, Shao JY (2006) Influence of tumor-associated macrophages on progression and prognosis of nasopharyngeal carcinoma. Ai Zheng 25: 1340–1345. [PubMed] [Google Scholar]
  • 15. Forssell J, Oberg A, Henriksson ML, Senling R, Jung A, et al. (2007) High macrophage infiltration along the tumor front correlates with improved survival in colon cancer. Clin Cancer Res 13: 1472–1479. [DOI] [PubMed] [Google Scholar]
  • 16. Kawai O, Ishii G, Kubota K, Murata Y, Naito Y, et al. (2008) Predominant infiltration of macrophages and CD8(+) T Cells in cancer nests is a significant predictor of survival in stage IV nonsmall cell lung cancer. Cancer 113: 1387–1395. [DOI] [PubMed] [Google Scholar]
  • 17. Ohri CM, Shikotra A, Green RH, Waller DA, Bradding P (2009) Macrophages within NSCLC tumour islets are predominantly of a cytotoxic M1 phenotype associated with extended survival. Eur Respir J 33: 118–126. [DOI] [PubMed] [Google Scholar]
  • 18. Zhou Q, Peng RQ, Wu XJ, Xia Q, Hou JH, et al. (2010) The density of macrophages in the invasive front is inversely correlated to liver metastasis in colon cancer. J Transl Med 8: 13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Guo SJ, Lin DM, Li J, Liu RZ, Zhou CX, et al. (2007) Tumor-associated macrophages and CD3-zeta expression of tumor-infiltrating lymphocytes in human esophageal squamous-cell carcinoma. Dis Esophagus 20: 107–116. [DOI] [PubMed] [Google Scholar]
  • 20. Chai CY, Chen WT, Hung WC, Kang WY, Huang YC, et al. (2008) Hypoxia-inducible factor-1alpha expression correlates with focal macrophage infiltration, angiogenesis and unfavourable prognosis in urothelial carcinoma. J Clin Pathol 61: 658–664. [DOI] [PubMed] [Google Scholar]
  • 21. Liu SY, Chang LC, Pan LF, Hung YJ, Lee CH, et al. (2008) Clinicopathologic significance of tumor cell-lined vessel and microenvironment in oral squamous cell carcinoma. Oral Oncol 44: 277–285. [DOI] [PubMed] [Google Scholar]
  • 22. Zhu XD, Zhang JB, Zhuang PY, Zhu HG, Zhang W, et al. (2008) High expression of macrophage colony-stimulating factor in peritumoral liver tissue is associated with poor survival after curative resection of hepatocellular carcinoma. J Clin Oncol 26: 2707–2716. [DOI] [PubMed] [Google Scholar]
  • 23. Ju MJ, Qiu SJ, Fan J, Xiao YS, Gao Q, et al. (2009) Peritumoral activated hepatic stellate cells predict poor clinical outcome in hepatocellular carcinoma after curative resection. Am J Clin Pathol 131: 498–510. [DOI] [PubMed] [Google Scholar]
  • 24. Li YW, Qiu SJ, Fan J, Gao Q, Zhou J, et al. (2009) Tumor-infiltrating macrophages can predict favorable prognosis in hepatocellular carcinoma after resection. J Cancer Res Clin Oncol 135: 439–449. [DOI] [PubMed] [Google Scholar]
  • 25. Wan T, Liu JH, Zheng LM, Cai MY, Ding T (2009) Prognostic significance of tumor-associated macrophage infiltration in advanced epithelial ovarian carcinoma. Ai Zheng 28: 323–327. [PubMed] [Google Scholar]
  • 26. Ma J, Liu L, Che G, Yu N, Dai F, et al. (2010) The M1 form of tumor-associated macrophages in non-small cell lung cancer is positively associated with survival time. BMC Cancer 10: 112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Parmar MK, Torri V, Stewart L (1998) Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med 17: 2815–2834. [DOI] [PubMed] [Google Scholar]
  • 28. Egger M, Davey Smith G, Schneider M, Minder C (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315: 629–634. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Khorana AA, Ryan CK, Cox C, Eberly S, Sahasrabudhe DM (2003) Vascular endothelial growth factor, CD68, and epidermal growth factor receptor expression and survival in patients with Stage II and Stage III colon carcinoma: a role for the host response in prognosis. Cancer 97: 960–968. [DOI] [PubMed] [Google Scholar]
  • 30. Bacman D, Merkel S, Croner R, Papadopoulos T, Brueckl W, et al. (2007) TGF-beta receptor 2 downregulation in tumour-associated stroma worsens prognosis and high-grade tumours show more tumour-associated macrophages and lower TGF-beta1 expression in colon carcinoma: a retrospective study. BMC Cancer 7: 156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Ishigami S, Natsugoe S, Tokuda K, Nakajo A, Okumura H, et al. (2003) Tumor-associated macrophage (TAM) infiltration in gastric cancer. Anticancer Res 23: 4079–4083. [PubMed] [Google Scholar]
  • 32. Haas M, Dimmler A, Hohenberger W, Grabenbauer GG, Niedobitek G, et al. (2009) Stromal regulatory T-cells are associated with a favourable prognosis in gastric cancer of the cardia. BMC Gastroenterol 9: 65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Kawahara A, Hattori S, Akiba J, Nakashima K, Taira T, et al. (2010) Infiltration of thymidine phosphorylase-positive macrophages is closely associated with tumor angiogenesis and survival in intestinal type gastric cancer. Oncol Rep 24: 405–415. [DOI] [PubMed] [Google Scholar]
  • 34. Osinsky S, Bubnovskaya L, Ganusevich I, Kovelskaya A, Gumenyuk L, et al. (2011) Hypoxia, tumour-associated macrophages, microvessel density, VEGF and matrix metalloproteinases in human gastric cancer: Interaction and impact on survival. Clinical and Translational Oncology 13: 133–138. [DOI] [PubMed] [Google Scholar]
  • 35. Ding T, Xu J, Wang F, Shi M, Zhang Y, et al. (2009) High tumor-infiltrating macrophage density predicts poor prognosis in patients with primary hepatocellular carcinoma after resection. Hum Pathol 40: 381–389. [DOI] [PubMed] [Google Scholar]
  • 36. Kuang DM, Zhao Q, Peng C, Xu J, Zhang JP, et al. (2009) Activated monocytes in peritumoral stroma of hepatocellular carcinoma foster immune privilege and disease progression through PD-L1. J Exp Med 206: 1327–1337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Kurahara H, Takao S, Kuwahata T, Nagai T, Ding Q, et al.. (2012) Clinical Significance of Folate Receptor beta-expressing Tumor-associated Macrophages in Pancreatic Cancer. Ann Surg Oncol. [DOI] [PubMed]
  • 38. Hasita H, Komohara Y, Okabe H, Masuda T, Ohnishi K, et al. (2010) Significance of alternatively activated macrophages in patients with intrahepatic cholangiocarcinoma. Cancer Sci 101: 1913–1919. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Leek RD, Lewis CE, Whitehouse R, Greenall M, Clarke J, et al. (1996) Association of macrophage infiltration with angiogenesis and prognosis in invasive breast carcinoma. Cancer Res 56: 4625–4629. [PubMed] [Google Scholar]
  • 40. Toi M, Ueno T, Matsumoto H, Saji H, Funata N, et al. (1999) Significance of thymidine phosphorylase as a marker of protumor monocytes in breast cancer. Clin Cancer Res 5: 1131–1137. [PubMed] [Google Scholar]
  • 41. Valkovic T, Dobrila F, Melato M, Sasso F, Rizzardi C, et al. (2002) Correlation between vascular endothelial growth factor, angiogenesis, and tumor-associated macrophages in invasive ductal breast carcinoma. Virchows Arch 440: 583–588. [DOI] [PubMed] [Google Scholar]
  • 42. Bolat F, Kayaselcuk F, Nursal TZ, Yagmurdur MC, Bal N, et al. (2006) Microvessel density, VEGF expression, and tumor-associated macrophages in breast tumors: correlations with prognostic parameters. J Exp Clin Cancer Res 25: 365–372. [PubMed] [Google Scholar]
  • 43. Mahmoud SM, Lee AH, Paish EC, Macmillan RD, Ellis IO, et al. (2012) Tumour-infiltrating macrophages and clinical outcome in breast cancer. J Clin Pathol 65: 159–163. [DOI] [PubMed] [Google Scholar]
  • 44. Salvesen HB, Akslen LA (1999) Significance of tumour-associated macrophages, vascular endothelial growth factor and thrombospondin-1 expression for tumour angiogenesis and prognosis in endometrial carcinomas. Int J Cancer 84: 538–543. [DOI] [PubMed] [Google Scholar]
  • 45. Hashimoto I, Kodama J, Seki N, Hongo A, Miyagi Y, et al. (2000) Macrophage infiltration and angiogenesis in endometrial cancer. Anticancer Res 20: 4853–4856. [PubMed] [Google Scholar]
  • 46. Soeda S, Nakamura N, Ozeki T, Nishiyama H, Hojo H, et al. (2008) Tumor-associated macrophages correlate with vascular space invasion and myometrial invasion in endometrial carcinoma. Gynecol Oncol 109: 122–128. [DOI] [PubMed] [Google Scholar]
  • 47. Espinosa I, Jose Carnicer M, Catasus L, Canet B, D'Angelo E, et al. (2010) Myometrial invasion and lymph node metastasis in endometrioid carcinomas: tumor-associated macrophages, microvessel density, and HIF1A have a crucial role. Am J Surg Pathol 34: 1708–1714. [DOI] [PubMed] [Google Scholar]
  • 48. Lissbrant IF, Stattin P, Wikstrom P, Damber JE, Egevad L, et al. (2000) Tumor associated macrophages in human prostate cancer: relation to clinicopathological variables and survival. Int J Oncol 17: 445–451. [DOI] [PubMed] [Google Scholar]
  • 49. Shimura S, Yang G, Ebara S, Wheeler TM, Frolov A, et al. (2000) Reduced infiltration of tumor-associated macrophages in human prostate cancer: association with cancer progression. Cancer Res 60: 5857–5861. [PubMed] [Google Scholar]
  • 50. Nonomura N, Takayama H, Nakayama M, Nakai Y, Kawashima A, et al. (2011) Infiltration of tumour-associated macrophages in prostate biopsy specimens is predictive of disease progression after hormonal therapy for prostate cancer. BJU Int 107: 1918–1922. [DOI] [PubMed] [Google Scholar]
  • 51. Heller DS, Hameed M, Cracchiolo B, Wiederkehr M, Scott D, et al. (2003) Presence and quantification of macrophages in squamous cell carcinoma of the cervix. Int J Gynecol Cancer 13: 67–70. [DOI] [PubMed] [Google Scholar]
  • 52. Kawanaka T, Kubo A, Ikushima H, Sano T, Takegawa Y, et al. (2008) Prognostic significance of HIF-2alpha expression on tumor infiltrating macrophages in patients with uterine cervical cancer undergoing radiotherapy. J Med Invest 55: 78–86. [DOI] [PubMed] [Google Scholar]
  • 53. Hanada T, Nakagawa M, Emoto A, Nomura T, Nasu N, et al. (2000) Prognostic value of tumor-associated macrophage count in human bladder cancer. Int J Urol 7: 263–269. [DOI] [PubMed] [Google Scholar]
  • 54. Takayama H, Nishimura K, Tsujimura A, Nakai Y, Nakayama M, et al. (2009) Increased infiltration of tumor associated macrophages is associated with poor prognosis of bladder carcinoma in situ after intravesical bacillus Calmette-Guerin instillation. J Urol 181: 1894–1900. [DOI] [PubMed] [Google Scholar]
  • 55. Tanaka Y, Kobayashi H, Suzuki M, Kanayama N, Terao T (2004) Upregulation of bikunin in tumor-infiltrating macrophages as a factor of favorable prognosis in ovarian cancer. Gynecol Oncol 94: 725–734. [DOI] [PubMed] [Google Scholar]
  • 56. Takanami I, Takeuchi K, Kodaira S (1999) Tumor-associated macrophage infiltration in pulmonary adenocarcinoma: association with angiogenesis and poor prognosis. Oncology 57: 138–142. [DOI] [PubMed] [Google Scholar]
  • 57. Chen JJ, Lin YC, Yao PL, Yuan A, Chen HY, et al. (2005) Tumor-associated macrophages: the double-edged sword in cancer progression. J Clin Oncol 23: 953–964. [DOI] [PubMed] [Google Scholar]
  • 58. Zeni E, Mazzetti L, Miotto D, Lo Cascio N, Maestrelli P, et al. (2007) Macrophage expression of interleukin-10 is a prognostic factor in nonsmall cell lung cancer. Eur Respir J 30: 627–632. [DOI] [PubMed] [Google Scholar]
  • 59. Al-Shibli Ibrahim K, Al-Saad S, Donnem T, Persson M, Bremnes R, et al. (2009) The prognostic value of intraepithelial and stromal innate immune system cells in non-small cell lung carcinoma. Virchows Archiv 455: S85. [DOI] [PubMed] [Google Scholar]
  • 60. Ohtaki Y, Ishii G, Nagai K, Ashimine S, Kuwata T, et al. (2010) Stromal macrophage expressing CD204 is associated with tumor aggressiveness in lung adenocarcinoma. J Thorac Oncol 5: 1507–1515. [DOI] [PubMed] [Google Scholar]
  • 61. Zhang BC, Gao J, Wang J, Rao ZG, Wang BC, et al. (2011) Tumor-associated macrophages infiltration is associated with peritumoral lymphangiogenesis and poor prognosis in lung adenocarcinoma. Med Oncol 28: 1447–1452. [DOI] [PubMed] [Google Scholar]
  • 62.Fujii N, Shomori K, Shiomi T, Nakabayashi M, Takeda C, et al.. (2012) Cancer-associated fibroblasts and CD163-positive macrophages in oral squamous cell carcinoma: their clinicopathological and prognostic significance. J Oral Pathol Med. [DOI] [PubMed]
  • 63. Lin JY, Li XY, Tadashi N, Dong P (2011) Clinical significance of tumor-associated macrophage infiltration in supraglottic laryngeal carcinoma. Chin J Cancer 30: 280–286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64. Ryder M, Ghossein RA, Ricarte-Filho JC, Knauf JA, Fagin JA (2008) Increased density of tumor-associated macrophages is associated with decreased survival in advanced thyroid cancer. Endocr Relat Cancer 15: 1069–1074. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65. Burt BM, Rodig SJ, Tilleman TR, Elbardissi AW, Bueno R, et al. (2011) Circulating and tumor-infiltrating myeloid cells predict survival in human pleural mesothelioma. Cancer 117: 5234–5244. [DOI] [PubMed] [Google Scholar]
  • 66. Gordon S (2003) Alternative activation of macrophages. Nat Rev Immunol 3: 23–35. [DOI] [PubMed] [Google Scholar]
  • 67. Xie QW, Cho HJ, Calaycay J, Mumford RA, Swiderek KM, et al. (1992) Cloning and characterization of inducible nitric oxide synthase from mouse macrophages. Science 256: 225–228. [DOI] [PubMed] [Google Scholar]
  • 68. Bonta IL, Ben-Efraim S (1993) Involvement of inflammatory mediators in macrophage antitumor activity. J Leukoc Biol 54: 613–626. [DOI] [PubMed] [Google Scholar]
  • 69. Nesbit M, Schaider H, Miller TH, Herlyn M (2001) Low-level monocyte chemoattractant protein-1 stimulation of monocytes leads to tumor formation in nontumorigenic melanoma cells. J Immunol 166: 6483–6490. [DOI] [PubMed] [Google Scholar]
  • 70. Umemura N, Saio M, Suwa T, Kitoh Y, Bai J, et al. (2008) Tumor-infiltrating myeloid-derived suppressor cells are pleiotropic-inflamed monocytes/macrophages that bear M1- and M2-type characteristics. J Leukoc Biol 83: 1136–1144. [DOI] [PubMed] [Google Scholar]
  • 71. Oosterling SJ, van der Bij GJ, Meijer GA, Tuk CW, van Garderen E, et al. (2005) Macrophages direct tumour histology and clinical outcome in a colon cancer model. J Pathol 207: 147–155. [DOI] [PubMed] [Google Scholar]
  • 72. Stewart LA, Parmar MK (1993) Meta-analysis of the literature or of individual patient data: is there a difference? Lancet 341: 418–422. [DOI] [PubMed] [Google Scholar]
  • 73. Marcus B, Arenberg D, Lee J, Kleer C, Chepeha DB, et al. (2004) Prognostic factors in oral cavity and oropharyngeal squamous cell carcinoma. Cancer 101: 2779–2787. [DOI] [PubMed] [Google Scholar]
  • 74. Sickert D, Aust DE, Langer S, Haupt I, Baretton GB, et al. (2005) Characterization of macrophage subpopulations in colon cancer using tissue microarrays. Histopathology 46: 515–521. [DOI] [PubMed] [Google Scholar]
  • 75. Liguori M, Solinas G, Germano G, Mantovani A, Allavena P (2011) Tumor-associated macrophages as incessant builders and destroyers of the cancer stroma. Cancers 3: 3740–3761. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76. Espinosa I, Edris B, Lee CH, Cheng HW, Gilks CB, et al. (2011) CSF1 expression in nongynecological leiomyosarcoma is associated with increased tumor angiogenesis. Am J Pathol 179: 2100–2107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77. Valkovic T, Lucin K, Krstulja M, Dobi-Babic R, Jonjic N (1998) Expression of monocyte chemotactic protein-1 in human invasive ductal breast cancer. Pathol Res Pract 194: 335–340. [DOI] [PubMed] [Google Scholar]
  • 78. Ueno T, Toi M, Saji H, Muta M, Bando H, et al. (2000) Significance of macrophage chemoattractant protein-1 in macrophage recruitment, angiogenesis, and survival in human breast cancer. Clin Cancer Res 6: 3282–3289. [PubMed] [Google Scholar]
  • 79. Fujimoto H, Sangai T, Ishii G, Ikehara A, Nagashima T, et al. (2009) Stromal MCP-1 in mammary tumors induces tumor-associated macrophage infiltration and contributes to tumor progression. Int J Cancer 125: 1276–1284. [DOI] [PubMed] [Google Scholar]
  • 80. Ohba K, Miyata Y, Kanda S, Koga S, Hayashi T, et al. (2005) Expression of urokinase-type plasminogen activator, urokinase-type plasminogen activator receptor and plasminogen activator inhibitors in patients with renal cell carcinoma: correlation with tumor associated macrophage and prognosis. J Urol 174: 461–465. [DOI] [PubMed] [Google Scholar]
  • 81. Avila-Moreno F, Lopez-Gonzalez JS, Galindo-Rodriguez G, Prado-Garcia H, Bajana S, et al. (2006) Lung squamous cell carcinoma and adenocarcinoma cell lines use different mediators to induce comparable phenotypic and functional changes in human monocyte-derived dendritic cells. Cancer Immunol Immunother 55: 598–611. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82. Verreck FA, de Boer T, Langenberg DM, van der Zanden L, Ottenhoff TH (2006) Phenotypic and functional profiling of human proinflammatory type-1 and anti-inflammatory type-2 macrophages in response to microbial antigens and IFN-gamma- and CD40L-mediated costimulation. J Leukoc Biol 79: 285–293. [DOI] [PubMed] [Google Scholar]
  • 83. Wang R, Lu M, Zhang J, Chen S, Luo X, et al. (2011) Increased IL-10 mRNA expression in tumor-associated macrophage correlated with late stage of lung cancer. J Exp Clin Cancer Res 30: 62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 84. Simon R, Altman DG (1994) Statistical aspects of prognostic factor studies in oncology. Br J Cancer 69: 979–985. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from PLoS ONE are provided here courtesy of PLOS

RESOURCES