The Prognostic Value and Regulatory Mechanisms of Microrna-145 in Various Tumors: a Systematic Review and Meta-Analysis of 50 Studies

Published OnlineFirst January 2, 2019; DOI: 10.1158/1055-9965.EPI-18-0570

Review Cancer Epidemiology, Biomarkers The Prognostic Value and Regulatory Mechanisms & Prevention of microRNA-145 in Various Tumors: A Systematic Review and Meta-analysis of 50 Studies Liangliang Xu1, Yanfang Zhang2, Jianwei Tang1, Peng Wang1, Lian Li1, Xiaokai Yan1, Xiaobo Zheng1, Shengsheng Ren1, Ming Zhang1, and Mingqing Xu1

Abstract

Acting as an important tumor-related miRNA, the clinical (HR ¼ 1.78; 95% CI, 1.35–2.36; P < 0.001), glioma (HR ¼ significance and underlying mechanisms of miR-145 in 1.65; 95% CI, 1.30–2.10; P < 0.001), and osteosarcoma various malignant tumors have been investigated by (HR ¼ 2.28; 95% CI, 1.50–3.47; P < 0.001). For PFS, the numerous studies. This study aimed to comprehensively pooled results also showed that the downregulation of estimate the prognostic value and systematically illustrate the miR-145 was significantly associated with poor PFS in regulatory mechanisms of miR-145 based on all eligible patients with multiple tumors (HR ¼ 1.39; 95% CI, literature. 1.16–1.67; P < 0.001), and the subgroup analyses further Relevant studies were acquired from multiple online identified that the low miR-145 expression was associated databases. Overall survival (OS) and progression-free with worse PFS in patients with lung cancer (HR ¼ 1.97; survival (PFS) were used as primary endpoints. Detailed 95% CI, 1.25–3.09; P ¼ 0.003) and those of Asian descent subgroup analyses were performed to decrease the hetero- (HR ¼ 1.50; 95% CI, 1.23–1.82; P < 0.001). For the geneity among studies and recognize the prognostic value regulatory mechanisms, we observed that numerous of miR-145. All statistical analyses were performed with tumor-related transcripts could be targeted by miR-145- RevMan software version 5.3 and STATA software version 5p or miR-145-3p, as well as the expression and function of 14.1. A total of 48 articles containing 50 studies were miR-145-5p could be regulated by multiple molecules. included in the meta-analysis. For OS, the pooled results This meta-analysis indicated that downregulated miR-145 showed that low miR-145 expression in tumor tissues was in tumor tissues or peripheral blood predicted unfavorable significantly associated with worse OS in patients with prognostic outcomes for patients suffering from various malig- various tumors [HR ¼ 1.70; 95% confidence interval (CI), nant tumors. In addition, miR-145 was involved in multiple 1.46–1.99; P < 0.001). Subgroup analysis based on tumor tumor-related pathways and the functioning of significant type showed that the downregulation of miR-145 was biological effects. miR-145 is a well-demonstrated tumor associated with unfavorable OS in colorectal cancer suppressor, and its expression level is significantly correlated (HR ¼ 2.17; 95% CI, 1.52–3.08; P < 0.001), ovarian cancer with the prognosis of patients with multiple malignant (HR ¼ 2.15; 95% CI, 1.29–3.59; P ¼ 0.003), gastric cancer tumors.

crucial roles in the growth, differentiation, angiogenesis, metas- Introduction tasis, and drug resistance of various tumors (3, 4). Moreover, some As an important type of noncoding RNA, miRNA comprises a miRNAs are significantly associated with the prognosis of patients class of small endogenous RNAs of approximately 22 nt in length with various tumors and are potential prognostic predictors and that play a crucial role in the regulation of gene expression at the candidate treatment targets (5). Therefore, the recognition of the posttranscriptional level (1, 2). Previous studies have shown that clinical significance and regulatory mechanisms of miRNAs may many miRNAs are aberrantly expressed in tumor tissues and play assist with the diagnosis, prognosis prediction, and treatment of malignant tumors. miR-145 is derived from chromosome 5q32 and contains 1Department of Liver Surgery, West China Hospital, Sichuan University, 2 two mature subtypes of miR-145-5p and miR-145-3p (6). On Chengdu, Sichuan Province, China. Center of Infectious Diseases, West China the basis of the deep sequencing data referred to in miRBase (7), Hospital, Sichuan University, Chengdu, Sichuan Province, China. miR-145-5p is much more abundantly expressed than miR-145- Note: Supplementary data for this article are available at Cancer Epidemiology, 3p. Substantial data obtained from previous studies have dem- Biomarkers & Prevention Online (http://cebp.aacrjournals.org/). onstrated that miR-145 is downregulated in various tumors L. Xu and Y. Zhang contributed equally and are the co-first authors of this article. and corresponding cell lines to be considered as tumor suppres- Corresponding Author: Mingqing Xu, Department of Liver Surgery, West China sors (8–14). On the contrary, several studies have found that miR- Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China. 145 is upregulated in tumor tissues and functions as an onco- Phone: 8618-2005-60532; Fax: 86-28-85422475; E-mail: gene (15, 16). For example, Naito and colleagues (15) showed [email protected] that miR-145 was upregulated in patients with gastric cancer with doi: 10.1158/1055-9965.EPI-18-0570 more advanced tumor stages or with scirrhous type histology, and 2019 American Association for Cancer Research. highly expressed miR-145 was significantly associated with poor

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prognosis in patients with gastric cancer. To date, although the Outcomes and definition correlation between miR-145 expression and the prognosis of In this study, two primary outcomes, overall survival (OS) and patients with various tumors has been investigated by numerous progression-free survival (PFS), were selected to calculate the studies, the conclusions are not completely consistent. Therefore, association between miR-145 expression and survival outcome we aimed to conduct a meta-analysis based on all eligible evi- of patients with multiple tumors. OS was measured from the time dence to evaluate the association between miR-145 expression at which the baseline blood or tissue sample was obtained to the and the prognosis of patients with malignant tumors. In addition, date of death from any cause or the date of last follow-up. PFS was in response to the need for comprehensive recognition of miR- recorded as the time between the baseline blood and tissue 145, known regulatory mechanisms of miR-145 will be illustrated sampling for miRNA analysis and documentation of the first in this study via systematically reviewing previous studies. tumor progression, based on clinical or radiological findings. In different studies, OS was also expressed as disease-specific survival (DSS; ref. 17) and cancer-specific survival (CSS; ref. 15), while PFS Materials and Methods was also described as recurrence-free interval (RFI; ref. 8), disease- Identification of relevant studies free survival (DFS; refs. 9, 10, 18–26), biochemical-free survival A systematic literature search was conducted using online (BFS; ref. 27), metastasis-free survival (MFS; ref. 28), relapse-free databases including MEDLINE, Embase, PubMed, Google Schol- survival (RFS; ref. 29), and time to relapse (TTR; ref. 11). ar, and China Biology Medicine disc. The keywords used in the searches were "miR-145 or miRNA-145 or microRNA-145 (all Inclusion and exclusion criteria fields)." The categories of diseases and research types were not The following criteria were used to help select eligible literature: limited so that the maximum number of studies was identified. In (i) published studies that could be retrieved from the above- addition, the reference lists of relevant reviews, meta-analyses, mentioned online databases; (ii) the expression of miR-145 was and original studies were manually screened to acquire more measured in the tumor tissue, peripheral blood, or body liquid; studies. The language was not restricted. (iii) the association between miR-145 expression level and

Records identified through electronic Records identified through manually database searching: OVID, Pubmed, searching previous reviews and CBM. (n = 1,262) meta-analysis. (n = 5) Identification Records after duplicates removed (n = 54)

Records excluded after reading titles Records screened and abstract, with reasons: not tumor n patients, published as meta-analysis, Screening ( = 1,213) review, abstract (n = 1,059)

Full-text articles excluded, with reasons: Full-text articles assessed only conducted in cell line, no survival n for eligibility ( = 154) data (n = 92) Eligibility Studies included in Eligible articles excluded, with reasons: qualitative synthesis HR was not used as survival endpoint or (n = 62) cannot be extracted or calculated (n = 14)

Studies included in quantitative synthesis

Included (n = 48 contain 50 researches)

Figure 1. A ﬂowchart illustrating the process of study selection. CBM, China Biology Medicine.

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Downloaded from cebp.aacrjournals.org on September 27, 2021. © 2019 American Association for Cancer Research. w.arorasogCne pdmo imresPe;2()My2019 May 28(5) Prev; Biomarkers Epidemiol Cancer www.aacrjournals.org Table 1. The main characteristics of all included studies in this meta-analysis miR-145 Detected Assay Expression Cut-off Sample Follow-up Survival HR Independent NOS

Downloaded from Study (Ref.) Year Country Subtype Tumor type sample method in tumor value size (low/high) (month) endpoints Source risk factor Score Schaefer (8) 2010 Germany 5p Prostate carcinoma FT qRT-PCR Down Median 75 (NR) 93 FRI Reported No 8 Chen (38) 2010 China 5p Prostate carcinoma FFPE qRT-PCR Down NR 106 (73/33) 82 PFS SC Yes 7 Drebber (39) 2011 Germany 5p Colorectal cancer FFPE qRT-PCR Down ROC curve 50 (15/35) 77 OS SC NR 8 Marchini (49) 2011 Italy 5p Ovarian cancer FT qRT-PCR NR Median 89 (NR) 143 PFS/OS Reported NR 7 Radojicic (9) 2011 Greece 5p Breast cancer FFPE qRT-PCR Down Mean 49 (28/21) 118 DFS/OS SC NR 8

Feber (40) 2011 USA 5p Esophageal cancer FFPE qRT-PCR Down Median 100 (50/50) 55 OS SC NR 8 Published OnlineFirstJanuary2,2019;DOI:10.1158/1055-9965.EPI-18-0570 Leite (27) 2011 Brazil 5p Prostate carcinoma FT qRT-PCR NR Median 49 (NR) 122 BFS SC No 6

cebp.aacrjournals.org Hamano (43) 2011 Japan 5p Esophageal cancer FFPE qRT-PCR Down Median 98 (49/49) 98 OS SC NR 8 Schee (28) 2012 Norway 5p Colorectal cancer FT qRT-PCR NR Median 193 (97/96) 63 MFS SC NR 7 Kang (41) 2012 Korea 5p Prostate carcinoma FFPE qRT-PCR NR Median 73 (36/37) 55 FRI SC No 7 Huang (44) 2012 China 5p Cervical carcinoma FFPE qRT-PCR NR NR 44 (18/26) 70 OS SC No 6 Ko (18) 2012 Canada 5p Esophageal cancer FFPE qRT-PCR NR Median 25 (12/13) 32 DFS SC NR 7 Law (10) 2012 China 5p HCC NR qRT-PCR Down 1.5 fold 47 (15/32) 144 DFS SC NR 7 Speranza (52) 2012 Italy 5p Glioblastoma FT qRT-PCR Down Median 20 (10/10) 102 PFS/OS SC NR 8 Tanaka (16) 2013 Japan 5p Esophageal cancer Serum qRT-PCR High Median 64 (32/32) 40 PFS SC No 8 Saija (50) 2013 Finland 5p Glioma FT Microarray Down Three-fold 268 (53/215) 130 OS SC NR 8 Campayo (11) 2013 Spain 5p Lung cancer FT qRT-PCR Down NR 70 (14/56) 36 TTR SC Yes 7 on September 27, 2021. © 2019American Association for Cancer Tang (53) 2013 China 5p Osteosarcoma Tissues qRT-PCR Down Median 166 (89/77) 152 DFS/OS SC Yes 8 Yu (58) 2013 China 5p HNC Tissues qRT-PCR Down Two-fold 250 (125/125) 60 OS SC NR 8 Avgeris (19) 2013 Greece 5p Prostate carcinoma FT qRT-PCR Down NR 62 (27/35) 75 DFS Reported Yes 8

Research. Muti-1 (17) 2014 Canada 5p Breast cancer Tissues Mircoarray down Median 740 (370/370) 310 DSS SC NR 8 Muti-2 (17) 2014 Canada 3p Breast cancer Tissues Mircoarray down Median 740 (370/370) 310 DSS SC NR 8 Naito (15) 2014 Japan 5p Gastric cancer FFPE qRT-PCR High Median 71 (36/35) 67 CSS SC No 8 Xia (55) 2014 Japan 5p TCL FFPE qRT-PCR NR NR 40 (10/30) 57 OS Reported Yes 7 (m) Slattery (51) 2015 USA 3p Colorectal cancer FFPE Mircoarray NR Expressed 1,141 (1,141/28) NR OS Reported NR 9 or not Xia (21) 2015 China 3p Lung cancer FFPE qRT-PCR Down Median 92 (36/46) 106 DFS/OS Reported Yes 9 Shen (20) 2015 China 5p Lung cancer FT qRT-PCR Down Median 48 (24/24) 24 DFS SC NR 7 miR-145 of Mechanism Regulatory and Value Prognostic Larne (12) 2015 Sweden 5p Prostate carcinoma FFPE qRT-PCR Down Median 49 (25/24) 204 OS Reported NR 9 Liang (48) 2015 China 5p Ovarian cancer Serum qRT-PCR Down Median 84 (42/42) 36 OS Reported NR 9 Avgeris (22) 2015 Greece 5p Bladder cancer Tissues qRT-PCR Down 1.5 fold 40 (22/18) 48 DFS/OS Reported(u) NR 9 Wang (54) 2015 China 5p Cervical cancer FT qRT-PCR Down Median 114 (63/51) 69 OS Reported Yes 9 (m) Ye (57) 2015 China 5p Lung cancer Tissues qRT-PCR Down Median 122 (61/61) 60 OS SC NR 8 Kim (45) 2015 Korea 3p Ovarian cancer FT qRT-PCR Down NR 74 (48/26) 90 OS Reported Yes 8 (m) Li (23) 2015 China 5p Colorectal cancer Serum qRT-PCR Down Median 175 (NR) 37 DFS Reported(u) No 8 Pecqueux (13) 2016 Germany 5p Colorectal cancer FT qRT-PCR Down Median 25 (12/13) 67 OS SC NR 8 Zhang (60) 2016 China 5p Gastric cancer FT qRT-PCR Down NR 145 (49/76) 65 OS Reported(u) Yes 8 Yang (56) 2016 USA 5p Colorectal cancer FFPE qRT- PCR Down Survival NR NR PFS/OS Reported NR 6 result Zhou (61) 2016 China 5p Colorectal cancer FT qRT-PCR Down NR 60 (27/33) 80 OS Reported(u) No 8 Shi-1 (63) 2016 China 5p Lung cancer Serum qRT-PCR NR NR Pemetrexed 76 117 PFS SC NR 6 (31/45) Shi-2 (63) 2016 China 5p Lung cancer Serum qRT-PCR NR NR Observation 72 78 PFS SC NR 6 (50/22) Li (47) 2016 China 5p Osteosarcoma Tissues qRT-PCR Down NR 39 (19/20) 60 OS SC NR 7 (Continued on the following page) OF3 Published OnlineFirst January 2, 2019; DOI: 10.1158/1055-9965.EPI-18-0570

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survival outcome was analyzed; and (iv) HR and 95% conﬁdence rence; NOS Score interval (CI) were reported or enough information was provided to calculate such parameters. Studies were excluded if they included the following items: (i) the patients did not suffer from malignant tumors; (ii) the study was only conducted on an animal model or tumor cell lines; and (iii) no data could be extracted or Independent risk factor NR 6 Yes 9 the studies were published as abstracts, reviews, conference reports, letters, or editorials. (m) (m) Study selection and data extraction

HR Source To make the management of literature more convenient, all identiﬁed citations were imported into an EndNote library (Thomson Corporation). After removing duplicated studies, two independent investigators (Y. Zhang and J. Tang) carefully

Survival endpoints screened the relevant studies by reading the titles and abstracts. Then, the entire text of potential eligible studies was evaluated to conﬁrm the ﬁnal inclusion. Any discrepancies during the study selection were resolved by discussion with the corresponding

Follow-up (month) author (M. Xu) for consensus. The relevant information was extracted from all included studies by two independent authors (P. Wang and L. Li). The following data elements were sought and recorded: (i) ﬁrst author, publication year, and nationality of study population;

Sample size (low/high) (ii) miR-145 subtype, tumor type, sample type, and miR-145 assay method; and (iii) sample size, period of follow up, cut-off value, HR, and corresponding 95% CI. When a study reported the survival results of both univariate and multivariate analyses, only the latter was extracted because it is more accurate as it accounts Cut-off value for confounding factors. If a study only reported the survival results using Kaplan–Meier curves, then the statistical variables were read from the graphical survival plots with the Engauge Digitizer 4.1 software program, and then the HR value and 95% CI Expression in tumor were calculated via the method reported by Tierney and colleagues (30). Regarding other missing information, e-mails were sent to corresponding authors requesting useful data. Finally, the extracted data forms were crosschecked between the abovemen- Assay method tioned two reviewers, and any disagreements during the process of data extraction were resolved by discussions with a third author (M. Zhang). Detected sample Quality assessment In this study, the quality of included studies was assessed by c survival; FT, frozen tissues; HCC, hepatocellular carcinoma; HNC, head and neck cancer; NOS, Newcastle-Ottawa Scale; NR, not reported; Ref., refe ﬁ two independent investigators (P. Wang and L. Li) using the Newcastle-Ottawa Scale (NOS; ref. 31). This is an acknowledged tool for assessing the quality of nonrandomized studies via the judgment of three main study characteristics as follows: selection and deﬁnition of the study groups, comparability of the groups, and ascertainment of outcomes. Then, a possible score of 0–9 was assigned to each study. A study with a NOS score greater than 6

miR-145 Subtype Tumor type was considered to be high quality.

Statistical analysis The RevMan software version 5.3 (Cochrane Collaboration) and STATA software version 14.1 (StataCorp) were used to per- form statistical analyses in this study. The pooled HR and corre- 2017 Iran 5p Cervical cancer FT qRT-PCR Down Median 35 (18/17) 54 OS Reported sponding 95% CI values were used to evaluate the prognostic value of miR-145 for various malignant neoplasms. The statistical signiﬁcance of the outcomes was determined by the Z-test and P The main characteristics of all included studies in this meta-analysis (Cont'd ) values less than 0.05 were considered statistically signiﬁcant. miR- 145 is a known tumor suppressor in most tumors; therefore, low (14) Table 1. Study (Ref.) Year Country Zhan (59)Namkung (25)Zhao 2016 (62) 2016 KoreaLiu (24) ChinaLi (46) 5pKapodistrias (29) 5p 2016Gan 2017 (42) China GreeceAzizmohammadi 2016 China Pancreatic 5p cancer 5p 2017 Gallbladder cancer China FT 2017 FFPE 5p China 5p Gastric Liposarcoma cancer qRT-PCR 5p Mircoarray Breast cancer Down NR FFPE Gastric FFPE cancer Lung FT cancer qRT-PCR Median qRT-PCR TCGA NR Down Down FFPE 82 qRT-PCR (41/41) Mircoarray Down NR Mean qRT-PCR 104 Median 93 Down NR 61 63 (31/30) (44/19) Median OS Mean NR 188 36 117 361 (NR) (157/204) 66 101 (65/36) SC DFS/OS RFS/OS OS 60 51 Reported SC OS NR DFS/OS SC OS SC SC No 8 NR SC NR NR 8 8 NR 7 6 8 Zhao (26)Abbreviations: 3P, miR-145-3P; 5P, miR-145-5P; CSS, cancer-speci SC, survival curve; TCGA, The Cancer 2017 Genome Altas; TCL, T-cell USA leukemia/lymphoma. 5pexpression Glioma of miR-145 Serum Mircoarray NR was thought Median as 106 a (53/53) riskfactor 24 and DFS/OS HR greater Reported NR 8

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Figure 2. Frost plot of the association between the downregulation of miR-145 and OS of patients with various tumors.

than one indicated a poor prognosis. The heterogeneity among Results studies was assessed using Cochran Q test and Higgins I-square Literature selection (I2) statistic (32, 33). If a significant heterogeneity was observed, A total of 1,262 studies were identified from online databases namely P < 0.05 and/or I2 > 50%, the random-effects model MEDLINE, Embase, PubMed, Google Scholar, and China Biology (DerSimonian and Laird method; ref. 34) was used. Alternatively, Medicine disc. Another five studies (17, 38–41) were acquired the fixed-effects model (Mantel–Haenszel method; ref. 35) was through manually screening the reference lists of relevant reviews applied to calculate the pooled HR and 95% CI of survival and meta-analyses. After removing 54 duplicated publications, outcomes. To decrease the heterogeneity among studies and the remaining 1,213 studies were evaluated by carefully reading recognize the prognostic value of miR-145 in greater detail, the titles and abstracts, after which 1,059 studies were excluded subgroup analyses were conducted on the basis of multiple because of the following reasons: not tumor studies, unpublished, criteria such as miR-145 subtype, tumor type, sample type, and withdrawn articles, letters, abstracts, reviews, or meta-analyses. patient ethnicity. In addition, Begg test (rank correlation test; Next, the entire text of the remaining 154 studies was assessed. ref. 36) and Egger test (weighted linear regression test; ref. 37) Among them, 106 were removed because survival analyses were were employed to evaluate the potential publication bias (P < not performed in 92 studies, and HR could not be extracted or 0.05 was considered statistically significant). Furthermore, one- calculated from the other 14 studies. Finally, 48 articles contain- way sensitivity analysis was performed to identify studies that had ing 50 studies, which were published between 2010 and 2017, a crucial influence on the pooled HR by removing one study at a were included in the meta-analysis for this study. A detailed time.

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Table 2. Subgroup analysis of OS and PFS in patients with various cancers OS (n ¼ 36) PFS (n ¼ 26) Number Pooled HR Number Pooled HR Subgroup of studies Model (95% CI) P HG I2 % of studies Model (95% CI) P HG I2 % miR-145 Type miR-145-5P 32 Random 1.66 (1.40–1.97) <0.001 65 25 Random 1.37 (1.14–1.65) <0.001 70 miR-145-3P 4 Fixed 1.99 (1.53–2.59) <0.001 0 1 ND 2.18 (1.30–3.65) 0.003 ND Tumor type Prostate cancer 1 ND 3.00 (1.50–6.00) 0.002 ND 5 Random 1.14 (0.83–1.56) 0.41 75 Colorectal cancer 5 Fixed 2.17 (1.52–3.08) <0.0001 0 4 Random 1.22 (0.69–2.16) 0.5 69 Lung cancer 3 Random 1.54 (0.70–3.36) 0.28 77 5 Random 1.97 (1.25–3.09) 0.003 68 Ovarian cancer 3 Fixed 2.15 (1.29–3.59) 0.003 21 1 ND 0.20 (0.05–0.87) 0.03 ND Cervical cancer 3 Random 1.32 (0.64–2.68) 0.45 84 ND ND ND ND ND Esophageal cancer 2 Random 0.97 (0.30–3.09) 0.95 83 2 Fixed 0.43 (0.19–1.00) 0.05 0 Gastric cancer 4 Random 1.40 (0.79–2.48) 0.24 77 ND ND ND ND ND Breast cancer 4 Random 1.19 (0.79–1.81) 0.41 66 2 Fixed 1.28 (0.94–1.75) 0.12 47 Glioma 3 Fixed 1.65 (1.30–2.10) <0.0001 0 2 Random 2.56 (0.86–7.63) 0.09 65 Osteosarcoma 2 Fixed 2.28 (1.50–3.47) 0.0001 0 1 ND 1.56 (1.12–2.17) 0.008 ND Others 6 Random 2.36 (1.55–3.59) <0.0001 61 4 Random 1.96 (1.13–3.37) 0.02 59 Sample type Frozen tissues 10 Random 1.81 (1–39–2.35) <0.0001 51 11 Random 1.51 (0.96–2.37) 0.08 75 FFPE 15 Random 1.35 (0.99–1.84) 0.06 72 7 Random 1.18 (0.94–1.48) 0.15 63 Serum 2 Fixed 1.74 (1.21–2.49) 0.003 0 5 Random 1.26 (0.86–1.86) 0.23 61 Others 9 Random 2.17 (1.64–2.88) <0.0001 57 3 Random 2.33 (1.22– 4.46) 0.01 62 HR Resource Reported 15 Fixed 2.02 (1.74–2.34) <0.0001 0 10 Random 1.62 (1.18–2.24) 0.003 54 SC 21 Random 1.43 (1.14–1.79) 0.002 72 16 Random 1.28 (1.03–1.60) 0.03 73 Ethnicity Asian 21 Random 1.73 (1.38–2.17) <0.0001 72 13 Random 1.50 (1.23–1.82) <0.0001 68 European 9 Fixed 1.75 (1.40–2.18) <0.0001 26 9 Random 1.41 (0.87–2.29) 0.16 69 American 6 Fixed 1.57 (1.29–1.90) <0.0001 49 4 Random 0.80 (0.32–2.02) 0.64 84 Assay method qRT-PCR 29 Random 1.68 (1.37–2.06) <0.0001 68 24 Random 1.36 (1.12–1.66) 0.002 71 Microarray 7 Fixed 1.75 (1.49–2.06) <0.0001 0 2 Fixed 1.70 (1.22–2.35) 0.001 0 Cut-off value Median 19 Random 1.59 (1.31–1.92) <0.0001 60 15 Random 1.14 (0.86–1.51) 0.37 72 Others 17 Random 1.88 (1.44–2.45) <0.0001 66 11 Random 1.72 (1.34–2.21) <0.0001 64 Abbreviations: HG, heterogeneity; ND, no data; SC, survival curve.

flowchart illustrating the process of literature selection is shown With respect to the quality of included studies, most included in Fig. 1. studies (43/50, 86%) were high quality with the NOS score greater than 6. Other detailed information of enrolled studies is listed Literature characteristics in Table 1. Among the 50 included studies, 46 studies investigated the prognostic value of miR-145-5p for malignant tumors and only 4 Meta-analysis of miR-145 expression and overall survival studies focused on miR-145-3p. A total of 6,875 patients suffering A total of 36 (9, 12–15, 17, 21, 22, 24–26, 29, 39, 40, 42–62) of from 18 different tumors were included in the meta-analysis, with the 50 studies that included 5,074 patients evaluated the rela- the sample size in each study ranging from 20 to 1,141 patients tionship between miR-145 expression and OS of patients suffer- (median 74.5). Quantitative real-time PCR was the method used ing from various tumors. Among them, two studies investigated most often to measure the expression of miR-145 (43/50, 86%). A the expression level and prognostic value of miR-145 in blood total of 17 of 50 studies (34%) measured the expression of miR- samples, and the results of these two studies were similar with 145 in frozen tissues, 18 (36%) in formalin-fixed, paraffin- most tissue studies. Therefore, a pooled analysis containing blood embedded tissues (FFPE), 6 (12%) in plasma or serum, while and tissue studies were performed. Owing to a significant hetero- the remaining 8 studies (16%) did not specifically report the tissue geneity existing among studies (I2 ¼ 62%, P < 0.001), a random type used. The cut-off value that stratified patients into high and model was employed to calculated the pooled HR and 95% CI of low expression groups varied among the different studies, with OS. The result showed that low miR-145 expression was associ- the median value being the most widely used value (28/50, 56%). ated with poor OS in multiple tumors, with a pooled HR of 1.70 For the prognosis, 25 studies reported a correlation between miR- (95% CI, 1.46–1.99; P < 0.001; Fig. 2). To decrease the hetero- 145 expression and OS, 14 reported PFS, and the remaining 11 geneity among studies, subgroup analyses were performed on the reported both OS and PFS. The length of follow-up ranged from basis of 7 criteria: miR-145 subtype, tumor type, sample type, HR 24 to 310 months with a median of 69.5 months. With respect to resource, patient ethnicity, miR-145 assay method, and cut-off HR, 18 studies reported the HR and 95% CI directly, whereas the value (Table 2; Supplementary Figs. S1A–S7A). The results remaining 32 studies reflected the survival outcomes using sur- showed that low expression of miR-145 was significantly associ- vival curves, and thus the HR and 95% CI could be calculated. ated with worse OS in subgroup analyses of miR-145 subtype, HR

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Figure 3. Frost plot of the association between the downregulation of miR-145 and PFS of patients with various tumors.

resource, patient ethnicity, miR-145 assay method, and cut-off association between the downregulation of miR-145 in FFPE value. However, the results from subgroup analysis of tumor type tissues and OS was not statistically significant (HR ¼ 1.35; suggested that the downregulation of miR-145 was obviously 95% CI, 0.99–1.84; P ¼ 0.06). associated with poor OS in colorectal cancer (HR ¼ 2.17; 95% CI, 1.52–3.08; P < 0.001), ovarian cancer (HR ¼ 2.15; 95% CI, 1.29– Meta-analysis of miR-145 expression and PFS 3.59; P ¼ 0.003), glioma (HR ¼ 1.65; 95% CI, 1.30–2.10; P < In this study, PFS was analyzed along with disease-free survival 0.001), and osteosarcoma (HR ¼ 2.28; 95% CI, 1.50–3.47; P < (DFS), recurrence-free interval (FRI), biochemical-free survival 0.001), but not in lung cancer (HR ¼ 1.54; 95% CI, 0.70–3.36; P ¼ (BFS), metastasis-free survival (MFS), time to relapse (TTR), and 0.28), cervical cancer (HR ¼ 1.32; 95% CI, 0.64–2.68; P ¼ 0.45), relapse-free survival (RFS), because all these indices were used to esophageal cancer (HR ¼ 0.97; 95% CI, 0.30–0.09; P ¼ 0.95), and indicate the tumor recurrence or deterioration after surgery or breast cancer (HR ¼ 1.19; 95% CI, 0.79–1.81; P ¼ 0.41). The study treatment. A total of 26 studies (8–11, 16, 18–29, 38, 41, 49, 52, conducted by Naito and colleagues (15) found that miR-145 was 53, 56, 61, 63) encompassing 1,971 patients with carcinoma upregulated in scirrhous type gastric cancer and the downregula- evaluated the correlation between miR-145 expression and PFS. tion of miR-145 was significantly associated with better OS in The random-effects model was employed to estimate the pooled gastric cancer (HR ¼ 0.50; 95% CI, 0.26–2.98; P ¼ 0.44; ref. 15). HR owing to an obvious heterogeneity among studies (I2 ¼ 70%, The pathologic type and survival result from this previous P < 0.001). Results showed that downregulated miR-145 signif- study were totally different from other studies focusing on the icantly predicted unfavorable PFS in various cancers, with a HR of association between miR-145 expression and OS in gastric can- 1.39 (95% CI, 1.16–1.67; P < 0.001; Fig. 3). Similar to OS, cer (46, 60). Therefore, further subgroup analysis for gastric cancer subgroup analyses of PFS were also performed. The results was performed after omitting the study conducted by Naito and showed that the predictive value of miR-145 on PFS in various colleagues, and the result without heterogeneity (I2 ¼ 0; P ¼ 0.55) cancers was not altered when patients were stratified on the basis suggested that the low miR-145 expression also indicated worse of HR resource and miR-145 assay method (Table 2; Supplemen- OS in gastric cancer (HR ¼ 1.78; 95% CI, 1.35–2.36; P < 0.001). tary Figs. S1B–S7B). Nevertheless, the results from the subgroup For the subgroup analysis of sample type, the downregulated miR- analysis of tumor type showed that the low miR-145 expression 145 in frozen tissues and serum was significantly associated with was only significantly associated with worse PFS in lung cancer poor OS (frozen tissues: HR ¼ 1.81; 95% CI, 1.39–2.35; P < 0.001; (HR ¼ 1.97; 95% CI, 1.25–3.09; P ¼ 0.003). The subgroup serum: HR ¼ 1.74; 95% CI, 1.21–2.49; P ¼ 0.003), whereas the analysis based on patient ethnicity found that the downregulated

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Figure 4. Begg funnel plot and Egger test were used to evaluate the publication bias. A and C, Begg funnel plot of OS and PFS. B and D, Egger test of OS and PFS.

miR-145 was only associated with poor PFS in Asian patients dataset, demonstrating that the results of this meta-analysis (HR ¼ 1.50; 95% CI, 1.23–1.82; P < 0.001) and not with the were robust. European (HR ¼ 1.41; 95% CI, 0.87–2.29; P ¼ 0.16) or American patients (HR ¼ 0.80; 95% CI, 0.32–2.02; P ¼ 0.64). For the miR-145 can be regulated by multiple factors subgroup analysis of the cut-off value, the results showed that Consistent with other mammalian miRNAs, miR-145 was first the PFS of patients in high and low miR-145 expression groups transcribed from its parental gene and termed as pri-miRNA, then that were stratified using the median value was comparable the pri-miRNA was cleaved into hairpin intermediates (pre-miR- (HR ¼ 1.14; 95% CI, 0.86–1.51; P ¼ 0.37). The subgroup analysis NAs) by the nuclear RNase III Drosha and further processed to found that the low miR-145 expression in all types of tissues was mature miRNAs by cytosolic Dicer, another RNase-III related not associated with the PFS (frozen tissue: HR ¼ 1.51; 95% CI, enzyme (Fig. 6; refs. 64, 65). Therefore, the expression level of 0.96–2.37; P ¼ 0.08; FFPE tissue: HR ¼ 1.18; 95% CI, 0.94–1.48; miR-145 might be regulated in the transcription and maturation P ¼ 0.15; serum: HR ¼ 1.26; 95% CI, 0.86–1.86; P ¼ 0.23). process by various factors. During the transcription step, Sachdeva and colleagues (66) first discovered that P53, a well-demonstrated The assessment of publication bias central tumor suppressor, could induce miR-145 transcription by In this study, the funnel plots of Begg and Egger tests were directly interacting with its promoter. From then on, other mole- employed to evaluate the publication bias of all included studies. cules including EWS-FLI-1 (67), FOXO (68), TP53 (69), No obvious asymmetry was observed in the funnel plots of Begg EGFR (70), PPARg (71), DNMT3b (72), AR (73), and DDX3 (74) (OS, P ¼ 0.17, Fig. 4A; PFS, P ¼ 0.63, Fig. 4C) and the P values of could also stimulate the transcription of miR-145 by enhancing the Egger tests were all higher than 0.05 (OS, P ¼ 0.41, Fig. 4B; PFS, promoter activity. On the contrary, DNA methylation at the miR- P ¼ 0.33, Fig. 4D). Therefore, significant publication bias did not 145 promoter region (75), C/EBP-b (76), DCLK1 (77), exist in this meta-analysis. RREB1 (78), and ZEB2 (79) caused the downregulation of miR-145 by repressing the activity of the miR-145 promoter. Sensitivity analysis With regard to the maturation-process, P53 (80) and BRCA1 (81) Sensitivity analysis of OS and PFS was performed to inves- could increase the expression of miR-145 by directly interacting tigate the influence of each individual study on the pooled HRs with the Drosha complex, whereas p70S6K (82), methyltransfer- (Fig. 5A and B). The result showed that the pooled results were ase BCDIN3D (83), and TARBP2 (84) restrained the maturation not significantly altered by sequentially omitting any single of miR-145 via inhibition of Dicer activity. Moreover, recent

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Meta-analysis fixed-effects estimates (exponential form) B Meta-analysis fixed-effects estimates (exponential form) A Study omitted Study omitted

Avgeris 2015 Avgeris 2013 Zhao 2017 Avgeris 2015 Zhao 2016 Zhang 2016 Campayo 2013 Zhan 2016 Chen 2010 Yu 2013 Kang 2012 Ye 2015 Yang 2016 Kapodistrias 2017 Xia 2015 Ko 2012 Xia 2014 Wang 2015 Law 2012 Tang 2013 Leite 2011 Speranza 2012 Slattery 2015 Li 2015 Saija 2013 Liu 2016 Radojicic 2011 Marchini 2011 Pecqueux 2016 Namkung 2016 Namkung 2016 Naito 2014 Radojicic 2011 Muti-2 2014 Muti-1 2014 Schaefer 2010 Marchini 2011 Schee 2012 Liu 2016 Shen 2015 Liang 2015 Li 2017 Shi-1 2016 Li 2016 Shi-2 2016 Larne 2015 Kim 2015 Speranza 2012 Kapodistrias 2017 Tanaka 2013 Huang 2012 Tang 2013 Hamano 2011 Gan 2017 Xia 2015 Feber 2011 Yang 2016 Drebber 2011 Zhao 2017 Azizmohammadi 2017 Avgeris 2015 Zhou 2016 1.49 1.52 1.66 1.81 1.87 1.16 1.18 1.28 1.39 1.47

Figure 5. Sensitivity analysis of the relationship between miR-145 expression and OS (A) as well as PFS (B).

studies have shown that the function of miR-145 could also be sively increased both the mRNA and protein levels of Ets1, and repressed by various competing endogenous RNAs (ceRNA) thus promoted the metastasis and angiogenesis of gastric cancer including transcribed pseudogenes (e.g., OCT4-pg4; ref. 85), cells (99). In addition, some genes can be regulated by miR-145- lncRNAs [e.g., lncRNA RoR (86–88), TUG1 (89), MALAT1 (90), 5p in multiple tumors. For example, FSCN1, one of the most UCA1 (91), and CRNDE (92)], and circular RNAs [e.g., cir- frequently reported target genes of miR-145-5p, was involved in cRNA_001569 (93) and circBIRC6 (94)]. The ceRNAs identified bladder cancer (100), esophageal cancer (101), hepatocellular thus far mainly regulate the function of miR-145-5p instead of carcinoma (HCC; ref. 102), lung cancer (103), nasopharyngeal miR-145-3p. cancer (104), and prostate cancer (105). Compared with miR- 145-5p, the biological functions of miR-145-3p, which were The target genes regulated by miR-145-5p/3p in various derived from the antisense of miR-145-5p, have been reported malignant tumors in few studies. It was reported that three genes, HMGA2 (45), Ang- After processing with Dicer, pre-miR-145 generated two mature 2 (106), and HIF-2a (107), could be regulated by miR-145-3p in subtypes named miR-145-5p and miR-145-3p. Then, an RNA- ovarian cancer, pancreatic cancer, and neuroblastoma, respective- induced silencing complex that silenced the expression of target ly, to inhibit tumor growth or metastasis. Furthermore, previous transcripts by either facilitating corresponding mRNA degrada- studies found that MDTH (108) and UHRF1 (109) could be tion or blocking its translation was formed (64). By systematically coregulated by both miR-145-5p and miR-145-3p in lung cancer reviewing previous studies, the transcripts that could be targeted and bladder cancer, respectively. by miR-145-5p, miR-145-3p, or both miR-145-5p and miR-145- 3p in different malignant tumors were summarized (Table 3). Generally, most of them focused on miR-145-5p and it was found Discussion to silence many genes, which participated in almost every aspect Although miRNAs only encompass 19–23 nucleotides and do of tumor activities, including tumor growth, metastasis, differen- not have the ability to encode proteins, they are involved in tiation, angiogenesis, and drug resistance. Among these genes, multiple cellular pathways and play crucial roles in various some played important roles in only one aspect of tumor behav- diseases (1). Identifying aberrantly expressed miRNAs and illus- ior. Minami and colleagues (95) revealed that miR-145-5p per- trating their underlying mechanisms may assist with early diag- turbed the Warburg effect by silencing KLF4 in bladder cancer nosis, prognosis evaluation, and treatment development of cells, resulting in significant cell growth inhibition. Eades and numerous diseases (110, 111). Among thousands of known colleagues (96) found that the small GTPase ADP-ribosylation cancer-related miRNAs, miRNA-145 is considered an important factor 6, a target of miR-145-5p in the triple-negative breast one whose biological function and clinical significance have been cancer, promoted cell invasion by regulating E-cadherin locali- investigated by many studies. To date, only two other meta- zation and impacting cell–cell adhesion. Gao and colleagues (97) analyses have assessed the association between miR-145 expres- suggested overexpression of miR-145-5p sensitized breast cancer sion and the prognosis of patients with malignant tumors cells to doxorubicin in vitro and enhanced the doxorubicin che- (112, 113). Zhang and colleagues (112) utilized four prostate motherapy in vivo via inhibition of the multidrug resistance- cancer studies and evaluated the predicted value of miR-145 for associated protein 1. Yet, some targeted genes of miR-145-5p the DFS. In this study, the author defined the pooled HR < 1 possess multiple functions in an individual tumor type. For indicated poor prognosis for the groups with lower miR-145 instance, overexpression of miR-145-5p suppressed esophageal expression and was considered statistically significant if the squamous cell carcinoma cell proliferation and invasion via 95% CI did not overlap 1. The pooled result indicated that the targeting c-Myc (98), and the knockdown of miR-145-5p respon- low expression of miR-145 in prostate cancer tissues predicted

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Figure 6. The expression and function of miR- 145 could be regulated by numerous factors. AR, androgen receptor; BCDIN3D, BCDIN3 domain containing RNA methyltransferase; BRCA1, breast cancer 1; C/EBP-b, CCAAT/ enhancer binding protein beta; DCLK1, doublecortin-like kinase 1; DDX3, DEAD (Asp-Glu-Ala-Asp) box polypeptide 3; DNMT3b, DNA methyltransferase 3 beta; EWS-FLI- 1, EWS-FLI-1 fusion protein; FOXO, forkhead box, subgroup O; OCT4- pg4, a pseudogene of OCT4; PPARg, peroxisome proliferator activated receptor gamma; RREB1, ras-responsive element binding protein 1; S6K, ribosomal protein S6 kinase; TARBP2, TARBP2 RISC loading complex RNA binding subunit; TP53, tumor protein p53; ZEB2, zinc ﬁnger E-box binding homeobox 2.

poor DFS (HR ¼ 0.48; 95% CI, 0.30–0.75; P ¼ 0.001). However, and peripheral blood was better than that of FFPE tissues, which the result of their study cannot be applied to other cancers due to was probably caused by higher speed of RNA degradation in FFPE the heterogeneity among different tumors and the small sample tissues than that in the other two types of tissues (114). size. Yang and colleagues (113) reported that overexpression of Consistent with OS, the pooled results showed that the down- miR-145 was significantly associated with favorable OS in various regulation of miR-145 was significantly associated with worse PFS carcinomas (HR ¼ 0.47; 95% CI, 0.31–0.72; P < 0.01), but not in patients with various cancers. This result did not change when with DFS (HR ¼ 0.87; 95% CI, 0.51–1.47; P ¼ 0.569). However, the patients were assigned to different subgroups based on miR- the conclusion of their study was not robust enough because it was 145 subtype, HR resource, and miR-145 assay method. However, published 3 years ago and only included 18 studies. In this study, a the subgroup analysis based on tumor types showed that the comprehensive literature search was performed to collect all downregulation of miR-145 was only associated with poor PFS in relevant evidence available from previous studies, and we per- patients suffering from lung cancer, and not those with prostate formed more detailed subgroup analyses to recognize the prog- cancer, colorectal cancer, esophageal cancer, breast cancer, and nostic value of miR-145 in greater detail. glioma. Meanwhile, the subgroup analysis based on patient A total of 50 studies that included 6,875 patients evaluated the ethnicity found that the downregulation of miR-145 was only association between miR-145 expression and the prognosis of associated with poor PFS among Asian patients, but not with the patients with malignant tumors. The pooled results from 36 European and American patients. This discrepancy might arise studies suggested that low expression of miR-145 significantly from differences in environment or genetic background. Never- predicted a poor OS, and this result was not altered when the theless, the subgroup analyses indicated that the aberrantly patients were stratified into different subgroups based on HR expressed miR-145 in all types of tissues (e.g., blood, frozen, and resource, patient ethnicity, miR-145 assay method, and cut-off FFPE tissues) was not significantly associated with PFS. In addi- value. The subgroup analysis based on tumor type suggested that tion, there was no significant difference in PFS between high and the downregulation of miR-145 was obviously associated with low miR-145 expressed groups, which was classified by median poor OS in colorectal cancer, ovarian cancer, gastric cancer, values. glioma, and osteosarcoma. In addition, the subgroup analysis In response to the need for comprehensive recognition of miR- based on tissue type found the prognosis value of frozen tissue 145, the regulatory mechanisms of miR-145-5p/3p were

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Table 3. The target genes regulated by miR-145 in various malignant tumors Tumor type Number of studies Function Target gene miR-145-5p Bladder cancer 7 Growth KLF4/PTBP1, ILK, SOCS7, FSCN1 Metastasis PAK1, PAI-1 Growth and metastasis IGFIR Breast cancer 7 Growth RTKN, MMP11, Rab27a Metastasis ARF6, MUC1 Growth and metastasis ERBB3 Drug resistance MRP1 Growth and angiogenesis NRAS, VEGFA Cervical cancer 5 Growth CDK6 Growth and metastasis SIP1 Radiation resistance HLTF, OCT4 Colorectal cancer 14 Growth NAIP, IGF1R, YES, STAT1, DFF45 Metastasis Paxillin, LASP1, ERG Growth and metastasis FSCN1, N-RAS, IRS1, PAK4 Growth and angiogenesis p70S6K1 Drug resistance RAD18 Growth and drug resistance FLI-1 Esophageal carcinoma 4 Growth and metastasis PLCE1, c-Myc, FSCN1 Gastric cancer 6 Metastasis CTNND1, N-cadherin, ZEB2, Growth E2F3 Drug resistance CD44 Metastasis and angiogenesis Ets1 Glioma 4 Metastasis ABCG2, ROCK1, ADAM17 Growth SOX9, ADD3 Hepatocellular carcinoma 6 Growth IRS1, ADAM17, HDAC2, IRS1, IRS2 Metastasis ADAM17 Growth and metastasis FSCN1 Lung cancer 8 Growth ICP27, OCT4 Metastasis OCT4, FSCN1, MTDH, SMAD3, N-cadherin Growth and metastasis Mucin 1 Melanoma 2 Metastasis FSCN1 Growth and metastasis NRAS Nasopharyngeal cancer 3 Metastasis SMAD3, FSCN1, ADAM17 Osteosarcoma 7 Metastasis MMP16, Snail, VEGF Growth and metastasis CDK6, FLI-1, ROCK1 Ovarian cancer 4 Growth c-Myc, Drug resistance SP1, CDK6 Growth and metastasis TRIM2, p70S6K1, MUC1 Pancreatic cancer 3 Growth and metastasis NEDD9, MUC13 Drug resistance p70S6K1 Prostate cancer 8 Growth SOX2, SENP1, ERG, BNIP3 Metastasis DAB2, HEF1, SWAP70 Growth and metastasis FSCN1 Renal cell carcinoma 2 Growth and metastasis ANGPT2, NEDD9, HK2 Others 10 Growth c-Myc, CDK6, DUSP6, CBFB, PPP3CA, CLINT1 Metastasis CTGF Growth and metastasis NUAK1, SOX2, AKT3, ADAM19 Drug resistance MRP1 Differentiation OCT4 miR-145-3p Ovarian cancer 1 Growth and metastasis HMGA2 Pancreatic cancer 1 Metastasis Ang-2 Neuroblastoma 1 Growth and metastasis HIF-2a miR-145-3p/5p Lung cancer 1 Growth MTDH Bladder cancer 1 Growth and metastasis UHRF1 Abbreviations: ABCG2, ATP binding cassette subfamily G member 2; ADAM17, ADAM metallopeptidase domain 17; ADD3, adducin 3; AKT3, AKT serine/threonine kinase 3; Ang-2, angiogenin, ribonuclease A family, member 2; ANGPT2, angiopoietin 2; ARF6, ADP ribosylation factor 6; BNIP3, BCL2 interacting protein 3; CBFB, core-binding factor subunit beta; CDK6, cyclin dependent kinase 6; CLINT1, clathrin interactor 1; CTGF, connective tissue growth factor; CTNND1, catenin delta 1; DAB2, DAB2, clathrin adaptor protein; DFF45, DNA fragmentation factor subunit alpha; DUSP6, dual specificity phosphatase 6; E2F3, E2F transcription factor 3; ERBB3, erb-b2 receptor tyrosine kinase 3; ERG, ERG, ETS transcription factor; Ets1, ETS proto-oncogene 1, transcription factor; FLI-1, Fli-1 proto-oncogene, ETS transcription factor; FSCN1, fascin actin-bundling protein 1; HDAC2, histone deacetylase 2; HK2, hexokinase 2; HLTF, helicase like transcription factor; HMGA2, high mobility group AT-hook 2; IGF-IR, insulin like growth factor 1 receptor; ILK, integrin linked kinase; IRS1/2, insulin receptor substrate 1/2; KLF4, Kruppel like factor 4; LASP1, LIM and SH3 protein 1; MMP11, matrix metallopeptidase 11; MRP1, mitochondrial 37S ribosomal protein MRP1; MTDH, metadherin; MUC1, mucin 1, cell surface associated; MUC1/13, mucin 1/13, cell surface associated; NAIP, NLR family apoptosis inhibitory protein; NEDD9, neural precursor cell expressed, developmentally down-regulated 9; NRAS, NRAS proto-oncogene, GTPase; NUAK1, NUAK family kinase 1; OCT4, organic cation/carnitine transporter4; PAI-1, serpin family E member 1; PAK1, p21 (RAC1) activated kinase 1; PAK4, p21 (RAC1) activated kinase 4; PLCE1, phospholipase C epsilon 1; PPP3CA, protein phosphatase 3, catalytic subunit, alpha isoform; PTBP1, polypyrimidine tract binding protein 1; RAD18, RAD18, E3 ubiquitin protein ligase; Rab27a, RAB27A, member RAS oncogene family; ROCK1, Rho- associated coiled-coil containing protein kinase 1; RTKN, rhotekin; S6K, Ribosomal protein S6 kinase; SENP1, SUMO-specific peptidase 1; SMAD3, SMAD family member 3; SOCS7, suppressor of cytokine signaling 7; SOX2/9, SRY (sex determining region Y)-box 2/9; STAT1, signal transducer and activator of transcription 1; TRIM2, tripartite motif containing 2; UHRF1, ubiquitin like with PHD and ring finger domains 1; VEGFA, vascular endothelial growth factor A; YES, YES proto-oncogene, Src family tyrosine kinase; ZEB2, zinc finger E-box binding homeobox 2. www.aacrjournals.org Cancer Epidemiol Biomarkers Prev; 28(5) May 2019 OF11

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elucidated in this study. Normally, miR-145 was downregulated statistical power of the meta-analysis. Second, owing to relevant in tumor tissues. Chivukula and colleagues (115) found that miR- studies being less than two, the prognostic value of miR-145 for 145 was not expressed in colonic epithelial cells, but highly some important solid tumors such as HCC, pancreatic cancer, and expressed in mesenchymal cells, such as fibroblasts and smooth renal cell cancer could not be evaluated during this meta-analysis; muscle cells, this result was further validated by Kent and collea- therefore, more well-designed clinical studies with larger sample gues (116). Hence, they considered that the downregulation of sizes for these tumors are imperative. Third, the cut-off value in miR-145 in colorectal tumor tissues was the depletion of mesen- each study varied, with a golden standard regarding the cut-off chymal cells in tumors relative to adjacent normal tissues. In value should be verified to better evaluate the prognostic value of addition, the underlying molecular mechanisms of the down- miR-145. Fourth, owing to several eligible studies not providing regulation of miR-145 were also investigated in multiple previous the survival data directly, corresponding HRs and 95% CIs were studies. In tumor tissues and cell lines, the factors that prompted calculated from survival curves, which might cause several micro the transcription and maturation of miR-145 were downregu- statistical errors. Fifth, although no significant publication bias lated, whereas the molecules that repressed the transcription and was identified in this meta-analysis, potential publication bias maturation of miR-145 were upregulated. These contributed to might exist owing to desirable results being published more the downregulation of miR-145. Furthermore, the function of easily, resulting in over estimation of survival outcomes. Finally, miR-145-5p could also be restrained by various ceRNAs in the this study only collected the regulatory mechanisms and biolog- cytoplasm. OCT4-pg4, a pseudogene of OCT4, holds the com- ical functions of miR-145-5p/3p reported thus far, and more mon binding sequence with OCT4 for miR-145-5p, and thus novel biological mechanisms containing miR-145-5p/3p might functions as a natural miR-145-5p sponge to protect the OCT4 be unveiled in the future. transcript from being inhibited by miR-145 (85). Long noncoding In conclusion, based on all eligible evidence, our study dem- RNAs (lncRNAs) are an important class of noncoding RNA and onstrated that the downregulation of miR-145 was significantly partly serve as molecular sponges to competitively inhibit miR- associated with the poor prognosis of patients with various NAs. Previous studies have demonstrated that the function of malignant tumors. The subgroup analyses indicated that low miR-145-5p could be restrained by multiple lncRNAs in various expression of miR-145 significantly predicted worse OS in diseases, such as lncRNA-ROR in lung cancer (117), pancreatic patients with colorectal cancer, ovarian cancer, glioma, and oste- cancer (87), endometrial cancer (86), and colorectal cancer (88); osarcoma. Low expression of miR-145 was also significantly lncRNA-TUG1 in gastric cancer (118) and bladder cancer (89); associated with PFS in patients with lung cancer and those of and lncRNA-MALAT1 in cervical cancer (90). In addition, the Asian descent. In addition, via comprehensively review previous biological function of miR-145-5p could also be inhibited by studies, we found that miR-145 is involved in multiple tumor circular RNAs (circRNA), which is a novel class ceRNA shaped by a activities by targeting numerous genes, and the expression level of covalently closed loop without 50-30 polarity (119). Xie and miR-145 could also be regulated by multiple factors. colleagues (93) found that circ-001569 promoted the proliferation and invasion of colorectal cancer cell by sequestering miR- Disclosure of Potential Conflicts of Interest 145-5p. Yu and colleagues (94) found that circBIRC6 directly No potential conflicts of interest were disclosed. interacts with miR-145-5p and miR-34a to modulate target genes that maintain human pluripotency and differentiation. The dem- Acknowledgments onstrated target genes of miR-145-5p/3p and their biological This study was supported by grants from the National Natural Science functions in different neoplasms were also illustrated in this Foundation of China (grant no. 71673193) and the Key Technology Research and Development Program of the Sichuan Province (grant nos. 2015SZ0131 study. It was shown that numerous oncogenes that are involved and 2017FZ0082). in almost every aspect of tumor activity can be regulated by miR- 145-5p/3p. The costs of publication of this article were defrayed in part by the Although this study provides important information in recog- payment of page charges. This article must therefore be hereby marked nition of the clinical value and regulatory mechanism of miR-145, advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate many limitations in the study should be noted. First, despite 50 this fact. relevant studies being utilized, the number of studies belonging to each type of tumor was not sufficient and the sample sizes in most Received May 22, 2018; revised August 16, 2018; accepted December 26, of the studies were small, with these factors compromising the 2018; published first January 2, 2019.

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The Prognostic Value and Regulatory Mechanisms of microRNA-145 in Various Tumors: A Systematic Review and Meta-analysis of 50 Studies

Liangliang Xu, Yanfang Zhang, Jianwei Tang, et al.

Cancer Epidemiol Biomarkers Prev Published OnlineFirst January 2, 2019.

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