Screening of miRNAs associated with lymph node metastasis in Her-2-positive breast cancer and their relationship with prognosis#

Screening of miRNAs associated with lymph node metastasis in Her-2-positive breast cancer and their relationship with prognosis # # Her-2阳性乳腺癌淋巴结转移相关的miRNA的筛选及其与患者预后关系的研究 first-author corresp ‡Corresponding Author ‡Corresponding Author †E-mail:zxp99688@sina.com †E-mail:zxp99688@sina.com zxp99688@sina.com Department of Breast Surgery, Cancer Hospital of University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China Department of Breast Surgery, Cancer Hospital of University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China The aim of this study was to identify some biomarkers for predicting lymph node metastasis and prognosis of human epidermal growth factor receptor 2 (Her-2)-positive breast cancer (BC). We analyzed correlations between microRNAs (miRNAs) and the prognosis of patients with BC based on data collected from The Cancer Genome Atlas (TCGA) database. The expression levels of miR-455, miR-143, and miR-99a were measured in clinical samples of Her-2-positive BC patients with different degrees of lymph node metastasis. We investigated the impacts of overexpressed miR-455 on the proliferation and invasiveness of MDA-MB-453 cells and measured its effects on the expression of long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 ( MALAT1 ) by quantitative real-time polymerase chain reaction (qRT-PCR). The expression of miR-455 was significantly and positively correlated to the prognosis and overall survival (OS) of the BC ( P =0.028), according to TCGA information. The expression level of miR-455 was positively correlated with OS and relapse-free survival (RFS) of patients with Her-2-positive BC, and was negatively correlated with the number of metastatic lymph nodes ( P < 0.05). Transwell assay suggested that MDA-MB-453 cells became much less invasive ( P < 0.01) after being transfected with miR-455 mimics. During the qRT-PCR, the expression level of MALAT1 declined significantly after transfection ( P < 0.01). Overexpressed miR-455 significantly inhibited the proliferation and migration of MDA-MB-453 cells and the expression of MALAT1 . We conclude that miR-455 may be a useful potential biomarker for forecasting lymph node metastasis and the prognosis of Her-2-positive BC patients. miR-455 may play an important role in lymph node metastasis of BC by interacting with MALAT1 . 目的 2 寻找一种或多种能预测人类表皮生长因子受体2(Her-2)阳性乳腺癌患者是否发生淋巴结转移及其预后的分子标志物. 创新点 2 本研究发现,miR-455与Her-2阳性乳腺癌转移相关,可能是一个预测Her-2阳性乳腺癌患者淋巴结转移和预后的分子标志物.miR-455可以通过与长链非编码RNA人肺腺癌转移相关转录本1( MALAT1 )的相互作用,在乳腺癌的淋巴结转移过程中发挥重要功能. 方法 2 通过下载肿瘤基因组图谱(TCGA)数据库中与乳腺癌相关的微小RNA(miRNA)测序数据,筛选与乳腺癌淋巴结转移相关的miRNA,进一步分析这些miRNA与乳腺癌患者预后的相关性.同时,用实时荧光定量聚合酶链反应(qRT-PCR)方法检测这些miRNA在不同程度淋巴结转移的Her-2阳性乳腺癌患者组织中的表达水平,及其与预后的相关性.通过细胞学实验研究过表达miR-455对Her-2阳性乳腺癌细胞系MDA-MB-453增殖和侵袭能力的影响,并用qRT-PCR检测过表达miR-455对 MALAT1 表达的影响. 结论 2 miR-455可能是Her-2阳性乳腺癌患者淋巴结转移和预后的潜在预测因子. Breast cancer (BC) Human epidermal growth factor receptor 2 (Her-2) Lymphatic metastasis MicroRNA (miRNA) Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1 ) 乳腺癌 人表皮生长因子受体2(Her-2) 淋巴结转移 微小RNA(miRNA) 人肺腺癌转移相关转录本1( MALAT1 ) Introduction 1 For breast cancer (BC), metastasis is most often and most easily detected in regional lymph nodes at the early stage, then in distant organs such as the lungs, bones, liver, and brain. The frequency and location of BC metastasis are closely associated with the type of primary tumors (Weigelt et al., 2005 2005 ; Zhao et al., 2017 2017 ). However, no measures have been found to be effective for forecasting and intervening in BC metastasis. Molecular subtypes largely reflect the clinical characteristics and prognosis of BC. Therefore, distinguishing different molecular subtypes of BC is helpful in the search for more effective therapies (Zhang and Liu, 2008 2008 ). Of all the molecular subtypes, prognosis of human epidermal growth factor receptor 2 (Her-2)-positive BC is only slightly better than that of triple negative breast cancer (TNBC). Her-2-positive BC is associated with a considerable proportion of brain metastases (Aversa et al., 2014 2014 ). Although Herceptin (trastuzumab) significantly improves the prognosis of Her-2-positive BC, for BC where metastasis has occurred (especially brain metastasis), the combined use of Herceptin and lapatinib in targeted therapies contributes to a considerably higher survival rate than the use of Herceptin alone (Yap et al., 2012 2012 ). Therefore, there is an urgent need to find biomarkers for identifying the risks of tumor metastasis at the early stage, to customize more suitable personalized therapies for patients with Her-2-positive BC. Some studies regarding non-coding RNA (ncRNA), particularly microRNAs (miRNAs), have brought new hope for diagnosing and treating numerous types of malignancies (Wang et al., 2015 2015 ). miRNAs mainly play roles in mediating the degradation of target message RNAs (mRNAs) or inhibiting mRNA translation (McGuire et al., 2015 2015 ). Studies based on high-throughput sequencing have proven that changes in the expression of numerous miRNA transcripts are correlated with metastasis of BC (Volinia and Croce, 2013 2013 ; Markou et al., 2014 2014 ). More importantly, metastasis of BC is considerably suppressed by recovering the expression of some miRNAs (Tavazoie et al., 2008 2008 ). In addition, the expression levels of miRNAs differ significantly among molecular subtypes of BC. Hence, the identification of one or more miRNAs for a certain type of BC and clarifying its relationship to the development and metastasis of the BC can lead to the discovery of biomarkers related to metastasis, which may improve early diagnosis and treatment. The typical molecular mechanism underlying the role of miRNAs is as follows: miRNAs suppress translation of a target mRNA or promote its degradation by combination with its 3'-untranslated region (3'-UTR) or open reading frame (ORF) through complementary base pairing inside cells (Bartel, 2004 2004 ). Hence, miRNAs might regulate metastasis of BC by targeting some metastasis suppressor genes. Recent research has suggested that apart from binding with the target mRNA, some miRNAs might also interact with long non-coding RNAs (lncRNAs) to inhibit the binding between the miRNA and its target mRNA, thus activating the target mRNA. Therefore, these lncRNAs and target mRNAs are competing endogenous RNAs (ceRNAs) (Salmena et al., 2011 2011 ). In our early studies, the expression level of highly expressed lncRNA metastasis-associated lung adenocarcinoma transcript 1 ( MALAT1 ) was closely correlated with lymph node metastasis of Her-2-positive BC. MALAT1 knockdown at a cellular level significantly inhibits the proliferation and invasiveness of BC cells (Zhang et al., 2018 2018 ), which suggests that MALAT1 promotes lymph node metastasis of BC. As a ceRNA, MALAT1 has proved to be effective for regulating the expression of genes related to tumor metastasis such as enhancer of zeste homolog 2 ( EZH2 ) (Hirata et al., 2015 2015 ), matrix metalloproteinase-14 ( MMP14 ) and Snail (Luan et al., 2016 2016 ). However, which miRNAs regulate metastasis of BC or whether their regulation is based on their interactions with MALAT1 has not been clearly reported. In this study, miRNA sequencing (miR-seq) data for BC were downloaded from The Cancer Genome Atlas (TCGA) database (https://tcga-data.nci.nih.gov/tcga) and analyzed, and a literature search was conducted. The expression levels of miRNAs and lncRNA MALAT1 in clinical samples were measured via quantitative real-time polymerase chain reaction (qRT-PCR). Materials and methods 1 Results of miR-seq 2 Information about patients with BC was downloaded from the TCGA database on Dec. 16, 2016. Ultimately, miR-seq results of 1181 samples were obtained. They covered raw data on miR-seq of 1077 samples of BC tissues and 104 samples of paracancerous tissues as well as corresponding clinical information of 1078 samples. Screening of miRNAs related to lymph node metastasis of BC via bioinformatic analysis 2 The average expression level of miRNAs was determined based on miR-seq, and 109 miRNAs with an average expression level of above 500 were selected. Among the 1077 BC samples, Pearson’s correlation analysis was performed to analyze correlations between the 109 miRNAs and the number of metastatic lymph nodes, to calculate R and P values. miRNAs, with P values below 0.05, were sequenced based on R values. Thus, 19 miRNAs were found to be correlated with lymph node metastasis. Receiver operating characteristic (ROC) analysis was performed on the 19 miRNAs to measure and verify their expression levels for the final purpose of identifying the specificity and sensitivity of lymph node metastasis. Evaluation of correlations between expression levels of miRNAs and prognosis 2 The differential expression of 19 miRNAs related to lymph node metastasis between carcinoma and paracancerous tissues of different samples was determined by testing a negative binomial distribution using the software package edgeR. They were sequenced from the lowest to the highest based on the log fold change (logFC). Expression was deemed to differ significantly if the logFC was above 1 and P was below 0.05. Correlations between expression levels of candidate miRNAs related to lymph node metastasis (including miR-143, miR-455, and miR-99a) and the overall survival (OS) of patients were analyzed by the Kaplan-Meier model. A total of 1077 BC samples were divided into a high-expression group (the upper quartile) and a low-expression group (the later quartile) according to the expression levels of these miRNAs in these samples, to calculate log-rank P values and draw survival curves. The relative expression levels of candidate miRNAs related to lymph node metastasis in frozen tissue samples of patients with Her-2-positive infiltrating ductal carcinoma collected by the Zhejiang Cancer Hospital, Hangzhou, China were measured by qRT-PCR and internal controls were normalized. Subsequently, the relationship between the relative expression levels and OS was tested by Pearson’s correlation analysis. Collection of clinical BC samples 2 Frozen tissue samples of patients with Her-2-positive infiltrating ductal carcinoma were extracted from the tumor tissue bank of our hospital. Four Her-2-positive BC patients without metastatic lymph nodes, four patients with no more than three metastatic lymph nodes and four patients with more than three metastatic lymph nodes and undergoing radical surgeries for BC from February 2011 to November 2012, were enrolled from our hospital in this study. We collected samples of cancerous and paracancerous tissues from above Her-2-positive BC patients, which were stored at low temperature in the sample bank of our hospital. Patients had been followed up by phone and through visits to outpatient clinics by December 2018. All patients were between 43 and 70 years old and their average age was 55.8 years. No patients enrolled in this study received chemotherapy or radiotherapy before their operations. qRT-PCR detection, cell counting kit-8 assay, and transwell cell migration assay 2 The detection process was performed according to the method of Zhang et al. ( 2018 2018 ). The sequences of PCR primers are shown in Table S1 S1 . Cell culture and miRNA transfection 2 The cell line MDA-MB-453 was purchased from Shanghai Fuxiang Biological Technology Co., Ltd., China. Cells were cultured on complete Roswell Park Memorial Institute (RPMI) 1640 medium (Hyclone, UT, USA) under normoxic conditions. miRNA transfection was performed using cells in the logarithmic phase (confluence 50% to 80%). The miRNA mimics, miRNA inhibitor, and miRNA control were synthesized by Shanghai GenePharma Co., Ltd. (for sequences of miRNA mimics, refer to Table S2 S2 ). Transfection assays were performed according to the specifications of the Lipofectamine 2000 reagent kit (Invitrogen, CA, USA). Forty-eight hours after transfection, cells were collected for qRT-PCR to measure the expression of miRNA and MALAT1 . To test their proliferation and migration, cells were collected using cell counting kit-8 (CCK-8). Data analysis 2 All data were analyzed using SPSS 23.0 software and GraphPad Prism 6.0 (mapping software). The differences in expression of certain genes between the two groups were measured by Student’s t test. Pearson’s correlation coefficients were calculated to analyze the relationship between miRNA expression levels and prognostic factors such as pathological stage, degree of lymph node metastasis, OS, and relapse-free survival (RFS). The data were also analyzed using the Kaplan-Meier model. Two-tailed tests suggested that differences would be significant if the P value was < 0.05. Results 1 Corrections between miR-143, miR-455, miR-99a and lymph node metastasis of BC 2 To identify genes related to lymph node metastasis, we searched the miR-seq results related to the sampled cancerous and paracancerous tissues using the keyword “BRCA” in the TCGA database, from which miR-seq results and corresponding information of about 1181 samples (including 1077 sampled cancerous and paracancerous tissues of BC) were downloaded. We analyzed correlations between miRNA expression levels and the number of metastatic lymph nodes in different samples. The results showed that 19 miRNAs were correlated to the number of metastatic lymph nodes ( P< 0.05), and these were sequenced according to the R values of the correlations (Table 1 1 ). logCPM: logarithm of counts per million reads; logFC: logarithm of fold change Gene symbol logCPM P R logFC (cancer vs. para-cancer) Reference Oncogene or tumor suppressor Reported as breast cancer metastasis biomarkers Hsa-miR-542 8.0748 0.0012 0.1068 0.1965 He et al., 2014 2014 , 2015 2015 ; Venkatadri et al., 2016 2016 Tumor suppressor Controversial Hsa-miR-10b 16.4057 0.0026 0.0993 −1.9257 Singh et al., 2014 2014 ; M'hamed et al., 2015 2015 ; Wang N et al., 2016 2016 Oncogene Positive correlation Hsa-miR-99a 9.8641 0.0043 0.0943 −2.0557 Wang et al., 2015 2015 ; Xia et al., 2016 2016 Tumor suppressor Inverse correlation Hsa-miR-143 15.5453 0.0066 0.0898 −1.1712 Smeets et al., 2011 2011 ; Ng et al., 2014 2014 ; Li DG et al., 2015 2015 ; Zhou et al., 2017 2017 Tumor suppressor Inverse correlation Hsa-miR-151 11.2302 0.0077 0.0881 0.5065 Krell et al., 2012 2012 ; Yeh et al., 2016 2016 Tumor suppressor Inverse correlation Hsa-miR-193a 9.0143 0.0081 0.0875 −1.1926 Pronina et al., 2017 2017 Tumor suppressor Not yet reported Hsa-miR-625 8.0756 0.0179 0.0783 0.3222 Zhou et al., 2016 2016 Tumor suppressor Not yet reported Hsa-miR-149 7.4347 0.0183 0.0780 1.1149 Chan et al., 2014 2014 ; Dong et al., 2017 2017 Tumor suppressor Not yet reported Hsa-let-7c 11.5462 0.0270 0.0731 −1.7128 Li XX et al., 2015 2015 ; Sun et al., 2016 2016 ; Fu et al., 2017 2017 Tumor suppressor Not yet reported Hsa-miR-182 15.4684 0.0288 0.0723 2.2852 Lei et al., 2014 2014 ; Chiang et al., 2016 2016 ; Zhan et al., 2017 2017 Oncogene Positive correlation Hsa-miR-142 11.5267 0.0289 −0.0722 1.9148 Wang et al., 2014 2014 ; Schwickert et al., 2015 2015 ; Cao et al., 2016 2016 ; Jia et al., 2018 2018 Tumor suppressor Controversial Hsa-miR-455 8.1890 0.0319 −0.0709 1.1797 Liu et al., 2016 2016 ; Wang B et al., 2017 2017 Tumor suppressor Inverse correlation Hsa-miR-21 17.8459 0.0328 0.0706 2.1131 Pan et al., 2014 2014 ; Zhang CF et al., 2016 2016 ; Wang JL et al., 2017 2017 Oncogene Positive correlation Hsa-let-7f-2 12.8123 0.0346 0.0699 −0.0030 Sakurai et al., 2012 2012 Tumor suppressor Not yet reported Hsa-miR-25 13.3016 0.0396 0.0680 0.0233 Chang et al., 2016 2016 ; Asaduzzaman et al., 2017 2017 Oncogene Not yet reported Hsa-miR-26a-2 10.9111 0.0416 0.0674 −0.4407 Gao et al., 2013 2013 ; Liu et al., 2015 2015 ; M'hamed et al., 2015 2015 Tumor suppressor Inverse correlation Hsa-miR-16-1 9.5544 0.0426 −0.0670 0.4870 Patel et al., 2016 2016 ; Rinnerthaler et al., 2016 2016 Tumor suppressor Inverse correlation Hsa-miR-181a-2 9.5920 0.0451 0.0663 0.0798 Guo and Zhang, 2012 2012 ; Taylor et al., 2013 2013 ; Wang et al., 2014 2014 ; Li YY et al., 2015 2015 Controversial Inverse correlation Hsa-miR-30d 13.0231 0.0475 0.0655 0.0295 Han et al., 2016 2016 ; Zhang S et al., 2016 2016 To be determined Not yet reported The ROC, which is commonly used as classifier, accurately reflects the sensitivity and specificity of miRNAs used as markers for diagnosis and prognostic tests. To further narrow the research scope, we built ROC models to analyze the 19 miRNAs to identify their sensitivity and specificity to lymph node metastasis of BC. As the pathological tumor-node-metastasis (pTNM) stage is closely correlated to the number of metastatic lymph nodes and is an important indicator forming the basis for the clinical diagnosis of BC, ROC curves of the 19 miRNAs were analyzed and drawn to verify the correlations. To analyze the correlations between the number of metastatic lymph nodes and the stage (above IIB) based on the ROC, miRNAs such as miR-143, miR-455, and miR-99a were found to cover the largest areas under the curve (AUCs), as shown in Tables 2 2 – 4 4 and Fig. 1 1 . Conjoint analysis was performed on the expression levels of miRNAs. The results suggested that miR-143 and miR-99a occupied the largest AUC in identifying correlations between the number of metastatic lymph nodes and the pathological stage (Tables 2 2 and 3 3 , Fig. 1 1 ). Above all, pure miR-455 or miR-143 and miR-99a might be useful as molecular markers for forecasting the pTNM stage and degree of lymph node metastasis. ROC: receiver operating characteristic; SEN: sensitivity; SPE: specificity ROC: receiver operating characteristic; AUC: area under curve; CI: confidence interval; SEN: sensitivity; SPE: specificity; 0.5 is the pathological stage Gene symbol AUC 95% CI SEN (0.5) 1−SPE (0.5) P value miR-455 0.544 0.506–0.582 0.545 0.482 0.023 miR-99a 0.586 0.501–0.671 0.620 0.503 0.040 miR-625 0.538 0.501–0.576 0.535 0.487 0.045 miR-16-1 0.538 0.501–0.576 0.539 0.470 0.046 miR-143, miR-455, or let-7c 0.563 0.526–0.600 0.554 0.456 0.001 miR-455 or miR-99a 0.562 0.525–0.600 0.556 0.467 0.001 miR-455, miR-99a, or let-7c 0.562 0.525–0.599 0.557 0.462 0.001 miR-143, miR-455, miR-99a, or let-7c 0.562 0.525–0.600 0.553 0.457 0.001 miR-143 or miR-455 0.561 0.524–0.599 0.555 0.459 0.001 miR-143, miR-455, or miR-99a 0.561 0.524–0.598 0.553 0.459 0.001 miR-455 or let-7c 0.557 0.520–0.595 0.554 0.465 0.003 miR-143+miR-99a or miR-16-1 0.553 0.515–0.591 0.546 0.456 0.007 miR-143+miR-99a 0.613 0.516–0.709 0.658 0.503 0.019 miR-143+miR-99a+miR-625 0.608 0.509–0.706 0.649 0.503 0.026 miR-143+miR-99a+miR-30d 0.601 0.500–0.702 0.639 0.504 0.040 miR-143+miR-99a or miR-625 0.539 0.502–0.577 0.536 0.486 0.041 ROC: receiver operating characteristic; AUC: area under curve; CI: confidence interval; SEN: sensitivity; SPE: specificity; 0.45 is the pathological stage Gene symbol AUC 95% CI SEN (4.5) 1–SPE (4.5) P value miR-99a 0.617 0.537–0.697 0.720 0.480 0.005 miR-455 0.550 0.512–0.587 0.530 0.464 0.010 miR-143 0.569 0.515–0.622 0.615 0.472 0.011 miR-30d 0.545 0.507–0.583 0.545 0.458 0.021 Let-7c 0.574 0.507–0.641 0.627 0.480 0.026 miR-143, miR-455, or let-7c 0.583 0.546–0.620 0.556 0.418 0.000 miR-143 or miR-455 0.581 0.544–0.618 0.557 0.422 0.000 miR-143, miR-455, or miR-99a 0.581 0.544–0.618 0.557 0.419 0.000 miR-143, miR-455, miR-99a, or let-7c 0.581 0.544–0.618 0.555 0.418 0.000 miR-455, miR-99a, or let-7c 0.575 0.538–0.612 0.554 0.431 0.000 miR-455 or miR-99a 0.573 0.536–0.610 0.554 0.437 0.000 miR-455 or let-7c 0.573 0.536–0.610 0.552 0.435 0.000 miR-143+miR-99a 0.653 0.566–0.740 0.789 0.480 0.001 miR-143+miR-99a+miR-30d 0.654 0.562–0.745 0.778 0.481 0.002 miR-143+miR-99a+miR-625 0.653 0.564–0.742 0.784 0.481 0.002 miR-143+miR-99a+let-7c 0.638 0.544–0.732 0.765 0.482 0.006 miR-143+let-7c 0.603 0.525–0.681 0.689 0.479 0.007 miR-99a+let-7c 0.614 0.529–0.700 0.714 0.482 0.012 miR-99a or let-7c 0.580 0.515–0.644 0.637 0.477 0.012 miR-143 or miR-99a 0.564 0.512–0.615 0.605 0.471 0.014 miR-99a+miR-182 0.604 0.521–0.687 0.702 0.482 0.016 miR-143+miR-99a or miR-30d 0.546 0.508–0.584 0.547 0.456 0.018 miR-143 or let-7c 0.558 0.508–0.609 0.592 0.472 0.021 miR-143+miR-182 0.562 0.508–0.616 0.608 0.474 0.023 miR-143, miR-99a, or let-7c 0.557 0.507–0.607 0.590 0.472 0.024 Gene symbol log-rank P  miR-455 0.028  miR-149 0.132  miR-542 0.139  miR-142 0.182  miR-26a 0.228  miR-25 0.315  miR-181a 0.327  miR-21 0.341  miR-625 0.346  miR-99a 0.417  miR-16 0.491  miR-30d 0.538  Let-7c 0.551  miR-143 0.668  miR-193a 0.696  Let-7f 0.722  miR-10b 0.756  miR-182 0.839  miR-151 0.885  miR-143+miR-99a 0.932 Correlations between miR-455 and survival/prognosis of BC 2 To analyze how the miRNAs were correlated with the survival and prognosis of BC, we first carried out negative binomial distribution tests and difference analysis on the expression levels of the 19 miRNAs in cancerous and paracancerous tissues, to calculate the logFC for differences in expression levels (Table 1 1 ). The results suggested that miR-143 and miR-99a were highly expressed in paracancerous tissues, but poorly expressed in cancerous tissues. The expression levels of these two miRNAs were respectively 1.17 and 2.05 times higher in paracancerous tissues than in cancerous tissues. The expression level of miR-455 was high in paracancerous tissues, but low in cancerous tissues, and the difference was as high as 1.18-fold. Only the expression level of miR-455 was found to be significantly correlated to survival and prognosis after the corresponding correlation analysis was performed using the Kaplan-Meier model. According to the results, prognosis was better in the group where the expression level of miR-455 was higher (Fig. 2 2 ). In our study, we proved that a higher expression level of miR-455 in cancerous tissues was associated with fewer lymph nodes and a better prognosis. BC: breast cancer; OS: overall survival To further verify how miR-143, miR-455, and miR-99a in sampled Her-2-positive BC tissues were correlated to lymph node metastasis, prognosis and survival of BC, we collected four Her-2-positive BC samples without lymph node metastasis, four cases with no more than three metastatic lymph nodes and four cases with more than three metastatic lymph nodes to measure the expression levels of miR-143, miR-455, and miR-99a in these samples via qRT-PCR. All patients performed radical surgeries for BC from February 2011 to November 2012. The results suggested that the expression level of miR-455 in the group with a few metastatic lymph nodes was significantly lower than that in the group without lymph node metastasis ( P < 0.05; Fig. 3 3 ). Unlike in paracancerous tissues, we did not notice a significant increase in the expression level of miR-455 in cancerous tissues (Fig. 3 3 ). In addition, no significant increase was detected in the relative expression level of miR-143 or miR-99a compared with samples without lymph node metastasis or with only a few metastatic lymph nodes. On average, the expression levels of miR-143 and miR-99a were significantly higher in paracancerous tissues than in the group without lymph node metastasis ( P< 0.05; Fig. 3 3 ). The relationships between the relative expression levels of miR-143, miR-455 and miR-99a and survivals (including OS and RFS) and prognostic factors (pTNM stage and number of metastatic lymph nodes) were analyzed. Among these three categories of miRNAs, only the expression level of miR-455 was significantly positively correlated with the OS and RFS of patients with Her-2-positive BC ( R =0.6394 and R =0.7151, respectively), but there were significant negative correlations with the number of metastatic lymph nodes ( R =−0.5769). Nonetheless, the expression levels of all three miRNAs were not correlated with the pTNM stage (Fig. 3 3 , Table 5 5 ). These results suggest that the relative expression level of miR-455 could be helpful as a molecular marker for predicting lymph node metastasis and the prognosis of BC. On the other hand, no significant difference existed in the expression level of miR-455 between cancerous and paracancerous tissues of Her-2-positive BC. This implies that miR-455 possibly plays crucial roles in lymph node metastasis, but is not critical for other stages of BC, such as the initial stage and advancement. (a) Expression levels of miR-143, miR-455, and miR-99a in Her-2-positive BC samples with different degrees of lymph node metastasis were determined by qRT-PCR. The results are represented by the mean±SD. * P < 0.05. (b–d) Relationships between the expression levels of miR-143 (b), miR-455 (c), and miR-99a (d) in Her-2-positive BC samples and prognosis were analyzed. r is Pearson’s correlation coefficient. Each data point denotes the ratio between the normalized expression of a patient’s internal control and the normalized expression in paracancerous tissues. Her-2: human epidermal growth factor receptor 2; BC: breast cancer; qRT-PCR: quantitative real-time polymerase chain reaction; SD: standard deviation; OS: overall survival Her-2: human epidermal growth factor receptor 2; BC: breast cancer; OS: overall survival; RFS: relapse-free survival 2  Clinical index 2 miR-143 2 miR-455 2 miR-99a R P R P R P  OS 0.3246 0.3032 0.6394 0.0252 0.4399 0.1524  RFS 0.3515 0.2625 0.7151 0.0089 0.4072 0.1890  Number of lymph node metastases −0.5554 0.0608 −0.5769 0.0495 −0.3548 0.2578  Pathological stage −0.0067 0.9836 −0.0981 0.7616 −0.5649 0.0556 Effectiveness of miR-455 for inhibiting cell proliferation and migration in Her-2-positive BC cell lines 2 To further examine the effects of miR-455 upon proliferation and migration of Her-2-positive BC cells, we studied MDA-MB-453 cells (a kind of Her-2-positive BC cell line) in vitro. The transwell test results suggested that cells became considerably less invasive ( P< 0.01) after the cell line MDA-MB-453 was transfected into miR-455 mimics, while overexpressed miR-455 significantly inhibited proliferation and migration of this cell line (Fig. 4 4 ). According to these results, miR-455 plays important roles in the proliferation and migration of Her-2-positive BC cells. (a) Overexpression of miR-455 in MDA-MB-453 cells after their transfection into miR-455 mimics; (b) Changes to cell proliferation detected by CCK-8 after MDA-MB-453 cell transfection into miR-455 mimics; (c, d) Changes to cell invasiveness by transwell assays after MDA-MB-453 cell transfection into miR-455 mimics. The results are represented by the mean±SD ( n =3). ** P < 0.01. The scale bar is 20 μm, which has a magnification of 40×under an objective length. CCK-8: cell counting kit-8; SD: standard deviation; OD: optical density In our previous study, we proved that MALAT1 is favorable for regulating the proliferation and regulation of Her-2-positive BC cells (Zhang et al., 2018 2018 ). Likewise, miR-455 also regulates the proliferation and invasion of Her-2-positive BC cells. Thus, we attempted to explore if miR-455 interacts with MALAT1 . The starBase forecasted that binding bites would exist between MALAT1 and miR-455 (Fig. 5 5 ). qRT-PCR suggested that after transfection of MDA-MB-453 cells into miR-455 mimics, the expression level of MALAT1 declined significantly ( P< 0.01; Fig. 5 5 ). Finally, we found that miR-455 was effective in inhibiting MALAT1 expression inside cells. The miR-455 sequence had binding sites for MALAT1 and overexpressed miR-455 inhibited the expression of MALAT1 . As it is likely to interact with MALAT1 , miR-455 plays significant roles in BC proliferation and migration. (a) Binding sites between MALAT1 and miR-455-5p forecasted by starBase; (b) Expression level of MALAT1 measured by qRT-PCR assay after MDA-MB-453 cell transfection into miR-455 mimics. The results are represented by the mean±SD ( n =3). ** P < 0.01. qRT-PCR: quantitative real-time polymerase chain reaction; SD: standard deviation Discussion 1 Some miRNAs promote tumor metastasis and advancement, while others play opposite roles (Wang and Luo, 2015 2015 ). Numerous studies have suggested that lymph node metastasis of BC is closely associated with miRNAs (Chen X et al., 2018 2018 ; Shiino et al., 2019 2019 ). High-throughput sequencing and transcriptome analysis are primary options for studying and screening miRNAs. However, a study with a small sample size is subject to great limitations and systematic deviations. To avoid these shortcomings, we intensively analyzed miR-seq results of 1181 BC samples from the TCGA database, to identify miRNAs related to lymph node metastasis of BC. After analysis, we screened 19 miRNAs related to lymph node metastasis, among which miR-455, miR-143, and miR-99a were found to be highly sensitive and specific for predicting lymph node metastasis. Further analysis suggested that miR-455 was not only related to lymph node metastasis, but also predicted the prognosis of patients. Cytological research showed that miR-455 has biological functions for inhibiting Her-2-positive BC proliferation and migration, which is in line with previous research findings (Wang B et al., 2017 2017 ; Guo et al., 2018 2018 ) and further verifies the effectiveness of miR-455 in suppressing cancer. Compared with studies with a small sample size, analysis based on the TCGA is more representative and objective. Above all, our study proved that miR-455, exhibiting low expression in BC tissues, might be used as a molecular marker for forecasting lymph node metastasis and the prognosis of BC. However, we also noticed that our analysis results conflicted with some previous reports. Among our 19 screened miRNAs related to lymph node metastasis, some miRNAs (including miR-143 and miR-99a) were proven to inhibit BC, although they were positively correlated to lymph node metastasis. This suggests that the expression levels of miRNAs in tumor cells are not necessarily related to their functions. Ng et al. ( 2014 2014 ) pointed out that miR-143 exhibited low expression in BC tissues and significantly inhibited cell proliferation once it was overexpressed. Through microarray analysis, Smeets et al. ( 2011 2011 ) found that ten kinds of miRNAs, including miR-143, were highly expressed in metastasis-free BC, but exhibited low expression in BC with lymph node metastasis. On the other hand, it was noticed that miR-99a significantly inhibited cell proliferation and migration in triple negative BC cells (Xia et al., 2016 2016 ). Another microarray study suggested that the expression level of miR-99a was relatively low in BC tissues with lymph node metastasis (Wang et al., 2015 2015 ). However, the sample sizes in all these studies were small and molecular subtypes were not identified. In this study, for a small amount of Her-2-positive BC samples, the expression levels of miR-143 and miR-99a were found to be relatively low in samples with lymph node metastasis, but analysis of data from the TCGA database suggested that they were high (Table 1 1 , Fig. 3 3 ). Therefore, studies with a larger sample size must be carried out to find out if the expression of miR-143 differs among different molecular subtypes of BC. Furthermore, miRNAs might play different roles at different stages of BC. For instance, miR-455 exhibits lower expression in more metastatic BC tissues, whereas its expression level does not differ significantly between poorly metastatic BC tissues and paracancerous tissues (Fig. 3 3 ). Analysis of TCGA data suggested that miR-455 even increased slightly in cancerous tissues (Table 1 1 ). Therefore, analyzing BC samples at a certain stage is helpful to further identify the expression and biological functions of miRNAs at different stages of BC. In addition to miRNAs, there is another kind of ncRNA which generally has more than 200 nucleotides in eukaryocytes. These lncRNAs differ slightly from miRNAs in their mechanisms of action, and regulate physiological functions of organisms from multiple perspectives, including epigenetics, transcription, and post-transcription (Vikram et al., 2014 2014 ). MALAT1 is a type of conservative lncRNA, highly expressed in multiple categories of cancers including BC (Jadaliha et al., 2016 2016 ). However, the molecular mechanism through which MALAT1 promotes the proliferation and invasion of BC cells is still unknown. According to the study of Chou et al. ( 2016 2016 ), MALAT1 might hinder miRNAs from binding to mRNAs of their target genes by competitively binding to miRNAs as ceRNA inside cells. Our study has proven that miR-455 interacts with MALAT1 . Nevertheless, more in vitro and in vivo experiments need to be performed to verify the impact of their interactions on their respective biological functions. Moreover, intensive sequencing and bioinformatic analyses need to be carried out to examine the regulatory network of ceRNA and the roles of this gene in BC genesis/advancement in specific cell and tissue environments, although databases including starBase have been used to prove theoretically the interactions between miRNA and lncRNA. Conclusions 1 According to the TCGA database, we have found that lymph node metastasis of BC could be effectively forecasted according to the expression level of miR-455, because the expression of miR-455 was significantly and positively correlated with the prognosis and OS of BC. 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The research involving human subjects, human material, and human data was performed in accordance with the Declaration of Helsinki 2008 (5) and was approved by an appropriate ethics committee of Zhejiang Cancer Hospital, Hangzhou, China. 10.1631/jzus.B1900584 Project supported by the Foundation for Key Platform Technological Project of Zhejiang Medical Science and Hygiene (No. 2016ZDB003), China 2019-10-07 2020-03-10 2022-01-05 Copyright © Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2020 2020 Journal of Zhejiang University-SCIENCE B (Biomedicine and Biotechnology) 06 21