Prediction of MiR-155 as Biomarkers in Breast Cancer: A Systematic Review

Prediction of MiR-155 as Biomarkers in Breast Cancer: A Systematic Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Prediction of MiR-155 as Biomarkers in Breast Cancer: A Systematic Review Xiaohua Chen, Ming Thong Ong, Huayun Qiu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7045756/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Despite significant advances in the detection and treatment of breast cancer (BC), it remains one of the most prevalent malignancies worldwide. MicroRNAs (miRNAs) have emerged as critical regulators in cancer biology, influencing tumor initiation, progression, immune evasion, and therapy resistance. Among them, miR-155 is widely recognized as an oncogenic miRNA that promotes tumor growth, angiogenesis, and invasiveness in BC. As a result, it has been extensively studied as a potential predictive biomarker and therapeutic target. However, its predictive value in BC patients remains to be fully elucidated. This systematic review aims to synthesize current evidence on the predictive significance of miR-155 in BC pathology. A comprehensive search of PubMed and Web of Science identified 640 potentially relevant studies, of which 37 met the inclusion criteria for full analysis. These studies assessed miR-155 expression in tissue, blood, and urine samples and its associations with clinical outcomes and pathological features in BC patients. Our analysis suggests that circulating and urinary miR-155 may offer comparable predictive value to tissue-derived miR-155, with potential applications in early diagnosis, disease monitoring, recurrence detection, treatment response, and metastasis prediction. We also identified challenges that limit the clinical translation of miR-155, emphasizing the need for greater consistency and validation across studies.. Overall, this review highlights the promising role of miR-155 in BC management while emphasizing the need for further validation through well-designed clinical studies. T his work has been registered in PROSPERO with registration number CRD420251001681 and date of registration 14th May 2025 . miR-155 breast cancer prediction tissue blood urine Figures Figure 1 1. Background Breast cancer (BC) is one of the most common malignancies among women worldwide, with its mortality rate continuing to rise due to population growth and aging [ 1 ]. In 2022 alone, an estimated 2.3 million new cases were reported, accounting for 11.6% of all cancer diagnoses, and approximately 666,000 deaths were attributed to BC, representing 6.9% of all cancer-related deaths [ 2 ]. The heterogeneity of BC subtypes—such as HER2-positive, Luminal A, Luminal B, and triple-negative breast cancer (TNBC)—contributes to their varying aggressiveness and high mortality rates [ 3 ]. Early detection and accurate classification are critical for effective treatment and improved outcomes [ 4 ]. Traditional clinical indicators, including tumor size, grade, lymph node (LN) involvement, patient age, and comorbidities, have been widely used for prognosis. However, over the past two decades, increasing attention has been given to identifying novel predictive biomarkers in tissues and biofluids (e.g., plasma, serum, urine) to enhance clinical decision-making. These biomarkers have the potential to improve diagnosis, monitor disease progression, and evaluate treatment response. MicroRNAs (miRNAs) are a class of small, non-coding RNA molecules, typically 18 to 26 nucleotides in length. They were first discovered in 1993 by Lee et al. in Caenorhabditis elegans , and officially named "microRNAs" in 2001 [ 5 ]. This discovery marked a significant milestone in the study of non-coding RNAs, uncovering a novel mechanism of gene regulation. As endogenous regulatory molecules, miRNAs modulate gene expression at the transcriptional or translational level [ 6 ]. They typically bind to complementary sequences in the 3′ untranslated regions (3′ UTRs) of target messenger RNAs (mRNAs), leading to either mRNA degradation or translational repression [ 7 ]. To date, over 2,300 mature human miRNAs have been identified and verified [ 8 ]. miRNAs are essential regulators of numerous cellular processes, including development, cell differentiation, and homeostasis [ 9 ]. They are also involved in the pathophysiological pathways of a wide range of diseases, such as cardiovascular disorders, neurodegenerative diseases, and various cancers, offering new insights into disease mechanisms and progression [ 10 , 11 ]. Due to their ability to modulate gene expression, miRNAs can function either as oncogenes or tumor suppressors, and their dysregulation has been explored for diagnostic and predictive applications in oncology [ 12 ]. Among the miRNAs deregulated in BC, miR-155 is one of the most frequently reported, although it lacks specificity for predictive use [ 13 , 14 ]. Regardless of its diagnostic role, numerous studies have investigated the potential predictive value of miR-155 in BC. Recent evidence suggests that a miRNA signature—including miR-155—was associated with predictive outcomes in TNBC [ 15 , 16 ]. However, the predictive significance of miR-155 across all BC subtypes has not yet been systematically reviewed. Therefore, a comprehensive analysis of the predictive role of miR-155 in BC is warranted. This systematic review aims to evaluate existing clinical studies investigating the role of miR-155 as a biomarker for BC in both tissue and peripheral blood samples. The objective is to assess the potential of miR-155 expression levels as biomarkers for diagnosis, recurrence, progression, therapeutic monitoring and metastasis. 2. Methods 2.1 search strategy For this systematic review, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Two authors (HY QIU, and XH CHEN) conducted systematic literature searches in Web of Science and PubMed. We did not apply any publication date limits in our search strategy to ensure comprehensive coverage of relevant studies..We employed the following search strategy: (miR-155 or microRNA-155 or miR155) and breast cancer and (prediction or predictive or tissue or circulation or serum or plasma). The key search terms are detailed in Supplementary Table S1. Additionally, we performed a manual search of the reference lists from relevant publications to identify any further eligible studies. 2.2 Study Selection This study focused on peer-reviewed articles investigating tissue- or blood-derived miR-155, specifically evaluating its potential utility as a biomarker for the prediction of breast cancer. Two researchers (HY QIU, and XH CHEN) independently screened the titles and abstracts of identified articles and the inclusion criteria were as follows: (1) studies evaluating the predictive role of miR-155 in breast tissue and/or blood samples from breast cancer patients; (2) original research articles; (3) studies published in English; (4) experimental studies involving any subtype or stage of BC. The exclusion criteria were: (1) non-original publications (e.g., reviews, editorials); (2) non-English articles; (3) studies not focused on BC. Disagreements between the two reviewers were resolved by consensus or, if necessary, through discussion with a third researcher (MT ONG). A comprehensive literature search was conducted on December 12, 2024, with no restrictions on publication date. 2.3 Data extraction After protocol selection, data meeting the inclusion criteria were processed by one investigator (HY QIU) into a customized Excel spreadsheet database and verified by a second and third investigator (XH CHEN and MT ONG). From each eligible study, we extracted the following data: the specific microRNAs investigated, miR-155 expression levels; year of publication; country of the enrolled population; sample type (e.g., tissue, serum, plasma); number of patients and controls; parameters significantly associated with miR-155; its reported clinical relevance; references. 3. Results 3.1 Literature Review Results Following our search strategy, a total of 640 potentially relevant records related to the predictive role of miR-155 in BC were identified from the PubMed and Web of Science databases. The article selection process is illustrated in Fig. 1 . After removing 386 duplicate records, 254 unique articles remained. Of these, 161 were excluded based on title and abstract screening because they were reviews, meta-analyses, non-English publications, or conference abstracts. The full texts of the remaining 93 articles were assessed, and 55 were excluded for not meeting the inclusion criteria. Ultimately, 37 studies were included in this systematic review to evaluate the predictive role of miR-155 in BC, using tissue and/or plasma/serum samples. These studies were categorized into three groups: Group 1 included 17 studies, of which 13 focused exclusively on tissue samples and 4 examined both tissue and serum/plasma samples. Group 2 included 19 studies that analyzed the predictive role of circulating miR-155. Group 3 consisted of a single study that investigated urinary miR-155. In conclusion, the majority of the included studies focused on the predictive role of circulating miR-155 in BC. The main characteristics of the included studies are presented in Tables 1 , 2 , and 3 . In total, 37 original articles published between 2008 and 2024 were included, with sample sizes ranging from 5 to 283 and comprising a total of 3,793 samples. Of these, 32 studies included miR-155 as part of a broader panel of deregulated miRNAs, while the remaining 5 studies focused exclusively on miR-155. Among the selected articles, 24 studies investigated the association between miR-155 expression and predictive factors. These included patient-related factors (such as age, menopausal status, family history, treatment, and survival outcomes) and tumor-related factors (including tumor size, grade, receptor status, stage, and lymph node metastases). The studies were further categorized based on clinical relevance: 22 studies focused on BC diagnosis, 14 addressed disease progression and metastasis, and 9 examined treatment response and disease monitoring. Regarding expression trends, 32 studies reported upregulation of miR-155, while only 2 studies observed downregulation, suggesting that miR-155 is predominantly upregulated in BC. 3.2 Predictive Role of MiR-155 in Tissues of BC Patients Among the 17 studies evaluating the predictive role of miR-155 in tissues of BC patients (Table 1 ), 8 studies specifically achieved this goal by correlating miR-155 expression levels with diagnosis of BC, and 10 studies of that with progression and metastasis, while 4 studies of that with its response to treatment and disease monitoring, accounting for 36%, 46%, 18% respectively. As mentioned above, up-regulated miR-155 occurred in 16 studies, while only one study showed down-regulation of miR-155. In addition, of these 17 studies, miR-155 was screened in frozen- or FFPE- or fresh-tissue, and 4 of them analyzed miR-155 expression both in tissue and blood. Table 1 Comprehensive Characteristics and Clinical Relevance of Tissue-Based miR-155 Expression in Patients with Breast Cancer Year Country Sample Size Sample source miRNAs miR-155 Deregulation Clinical Relevance Significantly Associated Parameters Ref. 2008 USA 17 noninvasive, 45 invasive BC, 5 healthy Frozen T miR-155, -214, -21, -323 ↑ Progression and metastases detection EMT markers [ 17 ] 2010 China 68 BC, 40 healthy Frozen T + S miR-21, -106a, -126, -155, -199a, -335 ↑ Diagnosis(IDC) and progression detection Tumor grade, ER+, PR+ [ 18 ] 2012 China 92 BC Frozen T miR-155 ↑ Progression and metastases detection Tumor grade, stage, LN metastases, DFS, OS [ 19 ] 2012 China 67 IDC BC, 70 healthy Frozen T + P miR-155, -31 ↑ Diagnosis(IDC) and progression detection ER, PR, Age, TNM stage, tumor size [ 20 ] 2012 Saudi Arabia 40 BC Frozen T miR-10, 21, -155, -373, -30b, -126, -17p, -335 ↑ LNM detection Tumor size, ER-,PR- [ 21 ] 2014 Lebanon 57 BC, 20 healthy FFPE-T miR-148b, -10b, -21, -221, -155 ↑ Diagnosis (HER2+) Postmenopausal, age, PR-, HER2+ [ 22 ] 2014 china 15 TNBC Fresh T miR-155, -21, -181a, -181b, -183 ↑ Treatment response prediction (chemoresistance) ns [ 23 ] 2017 Iraq 60 BC, 30 healthy Frozen T + P miR-155, -21 ↑ Diagnosis(IDC) and progression detection TNM stage, tumor grade [ 24 ] 2018 Russia 80 BC Frozen T miR-21, -155, -222, -205, -221 ↑ Treatment (NAC) prediction and LNM detection LN metastases [ 25 ] 2018 Australia 5 BC FFPE-T miR-150, -126, -155 ↑ Diagnosis(IDC) and progression detection ns [ 26 ] 2019 UK 52 BC FFPE-T miR-132, -199a, -150, -155 ↑ Brain metastases detection BMFS, OS [ 27 ] 2019 Iran 30 BC, 10 healthy Frozen T + P miR-21, -155, -10b, Let-7a ↑ Diagnosis and treatment monitoring Treatment, TNM stage [ 28 ] 2019 Iran 50 BC FFPE-T miR-127-3p, -133a, -155, -199b, -342 ↑ Diagnosis (HER2+) TNM stage, HER2 [ 29 ] 2020 Italy 283 BC Frozen T miR-155 ↑ Response prediction to treatment (PARP1 inhibitors) TNM stage, treatment, LN metastases [ 30 ] 2020 Saudi Arabia 76 BC, 32 healthy FFPE-T miR-155, -150, -146a, -142 ↑ LNM detection LN metastases, TNM [ 31 ] 2023 Ukraine 56 BC, 22 healthy Frozen T miR-125b, -155, -221, -320a ↓ Response prediction to treatment (aromatase inhibitor) Stage, HER2+ [ 32 ] 2024 Tunisia 64 BC FFPE-T miR-21, -155, -182, -34a, -148a, -205 ↑ Diagnosis(PT) and progression detection Tumor grade [ 33 ] ↑ = up-regulated; ↓ = down-regulated; ns = not statistically significant; BC = Breast cancer; T = tissue; FFPE = Formalin-Fixed Paraffin-Embedded; TNM = Tumour Node Metastasis; LN = Lymph node, EMT = Epithelial - Mesenchymal Transition; IDC = Invasive Ductal Carcinoma; NAC = Neoadjuvant Chemotherapy; ER = Estrogen Receptor; PR = Progesterone Receptor; DFS = Disease-Free Survival; OS = Overall Survival; BMFS = Brain Metastasis-Free Survival; PT = Phyllodes Tumor. Table 2 Comprehensive Characteristics and Clinical Relevance of Blood-Based miR-155 Expression in Patients with Breast Cancer Year Country Sample Size Sample source miRNAs miR-155 Deregulation Clinical Relevance Significantly Associated Parameters Ref. 2009 USA 13 BC, 8 healthy S miR-16, -145, -155 ns Diagnosis(PR+) PR+ [ 34 ] 2012 China 103 BC, 55 healthy S miR-155 ↑ Diagnosis and treatment monitoring TNM stage, treatment [ 35 ] 2015 Egypt 120 BC, 50 healthy S miR-10b, -34a, -155, -195, -16 ↑ Progression and metastases detection Age, tumour grade, ER, PR, LN metastases [ 36 ] 2015 Egypt 130 BC, 30 healthy S miR-29b, -155, -197, -205 ↑ Diagnosis(IDC) and progression detection TNM stage, tumor size, LN metastases [ 37 ] 2016 China 106 BC, 106 healthy P miR-155, -21, -10b ↑ Diagnosis ns [ 38 ] 2017 USA 114 BC, 94 healthy P miR-155 ↑ Diagnosis(TN) TNM stage, tumour grade, family history [ 39 ] 2018 China 49 BC, 19 healthy S miR-16, -21, -155, -195 ↑ Diagnosis and TN subtype detection TNM stage, tumor size, TN subtype [ 3 ] 2019 Pakistan 37 BC, 34 healthy P miR-376c, -155, -17a, -10b ↑ Diagnosis(TN) Age, TNM stage, tumor grade [ 40 ] 2020 Indonesia 120 BC, 15 healthy P miR-155 ↑ Diagnosis and treatment monitoring Age, tumor size, treatment, [ 41 ] 2020 Turkey 45 BC, 48 healthy S miR-155, let-7c, -21 ↓ Differential diagnosis of IGM and BC ns [ 42 ] 2020 Iran 30 BC, 25 healthy P miR-21, -155 ↑ Diagnosis ns [ 43 ] 2020 China 183 BC S miR-1246, -155 ↑ Response prediction to treatment (resistance to trastuzumab ) EFS, PFS, treatment [ 44 ] 2022 Greece 66 BC, 16 healthy S miR-23b, -142, -29a, -181d, -16, -29b, -155, -181c ↑ Diagnosis and progression detection TN subtype [ 45 ] 2022 Iran 40 BC, 15 healthy P miR-155, -19a, -15a ns Response prediction to treatment (radiosensitivity) TNM, LN metastases [ 46 ] 2022 Egypt 99 BC, 40 healthy S miR-155, -373, -10b, -34a ↑ Diagnosis ER-, PR-, tumor grade [ 47 ] 2023 India 139 TNBC and 51 healthy S miR-205, -155, -21 ↑ Diagnosis(TN) TNM stage, distant metastasis [ 48 ] 2024 Ukraine 70 BC, 18 healthy P miR-25, -27, -155, -200, -335, -497 ns Diagnosis and treatment monitoring Menopausal status, stage, BC subtype [ 49 ] 2024 Egypt 75 BC, 20 healthy S miR-200a, -124, -205, -15a, -155 ↑ Diagnosis(TN) Stage, ER+, HER2+ [ 50 ] 2024 Egypt 48 metastatic, 50 nonmetastatic, 43 benign BC, 35 healthy S miR-155, -375 ↑ Metastases detection ns [ 51 ] ↑ = up-regulated; ↓ = down-regulated; ns = not statistically significant; BC = Breast cancer; S = Serum; P = Plasma; TN = triple negative.; TNM = Tumour Node Metastasis; LN = Lymph node; IDC = Invasive Ductal Carcinoma; IGM = Idiopathic Granulomatous Mastitis; ER = Estrogen Receptor; PR = Progesterone Receptor; EFS = Event-Free Survival; PFS = Progression-Free Survival. Table 3 Comprehensive Characteristics and Clinical Relevance of Urine-Based miR-155 Expression in Patients with Breast Cancer Year Country Sample Size Sample source miRNAs miR-155 Deregulation Clinical Relevance Significantly Associated Parameters Ref. 2015 Germany 24 BC, 24 healthy U + S miR-21, -34a, -125b, -155, -195, -200b, -200c, -375, -451 ↑ Diagnosis TNM stage,tumor grade [ 52 ] BC = Breast cancer; U = Urine; S = Serum; TNM = Tumour Node Metastasis. 3.2.1 Tissue MiR-155 and Diagnosis With the exception of one study, all the remaining studies indicated up-regulated miR-155, which contributed to the diagnosis of BC, however, the content of diagnosis varied. For instant, Khalighfard et al. [ 28 ] Showed that up-regulation of tissue miR-155 might be considered as a respectable diagnostic tool for monitoring of BC patients, whereas Wang et al. [ 18 ], Lu et al. [ 20 ], Meena et al. [ 24 ] and Soon et al. [ 26 ] pointed out miR-155 could contribute to diagnosis of invasive ductal carcinoma (IDC), and Nassar et al. [ 22 ] and Bitaraf et al. [ 29 ] indicating diagnosis of HER2 + BC. Moreover, All of the selected studies agreed that there was a high correlation of miR-155 expression level between tissues and blood, which encouraged further use of miRNAs in blood samples as an easy and convenient method of breast cancer screening. 3.2.2 Tissue MiR-155 and Progression or Metastasis Most of the selected studies reported a positive correlation between miR-155 overexpression and key pathological features such as tumor grade [ 18 , 19 , 24 , 26 ], tumor node metastasis (TNM) stage [ 19 , 20 , 24 , 31 ], and tumor sizes [ 20 , 21 ]. However, findings were inconsistent regarding the association between miR-155 expression and hormone receptor status (ER, PR, and HER2). For instance, Hafez et al. [ 21 ] found no association between miR-155 expression and ER/PR status. In contrast, Wang et al. [ 18 ] and Chen et al. [ 19 ] reported that high miR-155 expression was linked to ER/PR-negative status, whereas lower expression levels were associated with ER/PR-positive status. Meanwhile, Nassar et al. [ 22 ] observed no correlation between miR-155 overexpression and ER-negative status, but did find an association with PR-negative status. Only a few studies (n = 3) explored the relationship between miR-155 expression and HER2 status, and their findings were contradictory. Lu et al. [ 20 ] found no association, whereas Nassar et al. [ 22 ] and Bitaraf et al. [ 29 ] reported that high miR-155 expression was associated with HER2-positive status. Conversely, Pridko et al. [ 32 ] found that low miR-155 expression correlated with HER2 positivity. Finally, Giannoudis et al. [ 27 ] reported that miR-155 may serve as a potential biomarker to identify breast cancer patients at increased risk of developing brain metastases. 3.2.3 Tissue MiR-155 and Response to Treatment Chernyy et al. [ 25 ] investigated whether the relative expression of miR-155 could serve as a predictive biomarker for neoadjuvant chemotherapy (NAC) response and whether its differential expression in residual tumors post-treatment could be used to stratify non-responsive patients prognostically. In particular, they found that miR-155 expression was significantly decreased in tumour tissues of patients who received preoperative NAC compared with tumour tissues of patients without NAC in cohorts sub-classified to lymph node positive status. However, Ouyang et al. [ 23 ] focused on the association between 11 specific deregulated miRNAs, including miR-155, and chemoresistance in TNBC.In particular, they asserted deregulated miR-155 was associated with chemoresistance. Pasculli et al. [ 30 ] demonstrated miR-155 ectopic overexpression followed by Olaparib administration resulted in a greater reduction of cell viability as compared to Olaparib administration alone, suggesting that miR-155 might induce a synthetic lethal effect in TNBC when coupled with PARP-1-inhibition. Interestingly, Elango et al. [ 31 ] found most HER2 + BC patients had low levels of miR-155, which results were inconsistent with most other studies. They reported tumors that responded well to letrozole exhibited lower levels of miR-155 compared to non-responsive tumors, which indicated miR-155 could predict resistance to the letrozole treatment of BC. Furthermore, Khalighfard et al. [ 28 ] focused on the impact of operation, chemotherapy, and radiotherapy on miR-155 in BC patients. They found there was a significant difference in the miR-155 tissue level after the operation, chemotherapy, and radiotherapy. 3.3 Predictive Role of MiR-155 in Serum/Plasma of BC Patients Most of the selected studies summarized in Table 2 assessed the predictive value of circulating miR-155 by correlating its expression with clinically relevant endpoints. Specifically, 14 studies (61%) focused on diagnosis, 4 studies (17%) on disease progression and metastasis, and 5 studies (22%) on treatment response. Interestingly, when compared with tissue-based miR-155, circulating miR-155 appeared to have a different predictive focus. While tissue miR-155 was more commonly associated with progression and metastasis, circulating miR-155 was primarily investigated in the context of diagnosis. Furthermore, 16 out of the 19 studies on circulating miR-155 analyzed its dysregulation alongside other circulating miRNAs, highlighting its role within broader miRNA panels rather than as a standalone marker. 3.3.1 Circulating MiR-155 and Diagnosis Of the 19 studies that investigated circulating miR-155, 16 reported its upregulation in BC, supporting its potential utility as a diagnostic biomarker. Notably, several studies—including those by Gao et al. [ 39 ], Shaheen et al. [ 40 ], Kumar et al. [ 48 ], and Salum et al. [ 50 ]—highlighted significant upregulation of miR-155 in TNBC, suggesting its potential as an indicative marker for this aggressive subtype. In contrast, Zhu et al. [ 34 ] found that patients with PR-positive tumors had higher serum miR-155 expression compared to those with PR-negative tumors; however, they observed no significant difference in miR-155 levels between BC patients and healthy controls. Regarding diagnostic performance, seven studies [ 3 , 35 , 38 , 40 , 43 , 47 , 48 ] evaluated the receiver operating characteristic (ROC) curves for circulating miR-155 and reported area under the curve (AUC) values ranging from 0.801 to 0.949. These findings indicate that miR-155 exhibits high sensitivity and specificity, reinforcing its diagnostic potential in BC. 3.3.2 Circulating MiR-155 and Progression or Metastasis Studies examining the relationship between circulating miR-155 and breast cancer progression reported inconsistent findings. While most studies suggested an association between miR-155 levels and tumor stage, size, nodal involvement, and the presence of metastasis, results varied across individual investigations. For example, Shaker et al. [ 37 ] observed that elevated miR-155 expression was significantly correlated with tumor stage, tumor size, and lymph node involvement. In contrast, Anwar et al. [ 41 ] did not find any significant associations between miR-155 expression and tumor grade, subtype, or stage. However, they reported that patients over 40 years of age exhibited higher circulating miR-155 levels than those under 40, and that miR-155 expression was significantly elevated in patients with tumors larger than 5 cm. Regarding metastasis, Hagrass et al. [ 36 ], Shaker et al. [ 37 ], and Abdel-Hamed et al. [ 51 ] found significantly higher serum levels of miR-155 in patients with lymph node metastasis and distant metastasis (M1) compared to those without metastasis (M0). These findings suggest that miR-155 may play a role in promoting breast cancer progression and metastatic spread. 3.3.3 Circulating MiR-155 and Response to Treatment Though Harashchenko et al. [ 49 ] reported no significant change of miR-155 expression in patients after neoadjuvant chemotherapy, most of the selected studies found a decreased level of serum miR-155 in BC patients after surgery and chemotherapy [ 35 , 41 ], which indicated miR-155 could serve as an indicator for clinical response prediction to treatment. Besides, Sun et al. [ 35 ]and his colleagues found the concentrations of carbohydrate antigen 15 − 3, carcinoembryonic antigen and tissue polypeptide specific antigen did not show this trend in patients after surgery and chemotherapy, highlighting the unique value of miR-155 in response to treatment. In particular, Rajabi et al. [ 46 ] reported a significant association between miR-155 expression levels and the frequency of chromatid breaks, suggesting that miR-155 could serve as a bioindicator for predicting cellular radiosensitivity in BC patients. Regarding prognostic factors, Zhang et al. [ 44 ] using Kaplan–Meier survival analysis, demonstrated that patients with high expression of miR-1246 and miR-155 had poorer outcomes. Specifically, early-stage patients with elevated miR-1246 and metastatic patients with elevated miR-155 exhibited shorter event-free survival (EFS) and progression-free survival (PFS), respectively, compared to those with lower expression levels. Conversely, some inconsistencies emerged. For example, Anwar et al. [ 41 ] reported that, although longer follow-up is necessary, patients with upregulated circulating miR-155 showed longer PFS, with mean survival times of 77 weeks versus 65 weeks, indicating a potential protective effect in their cohort. 3.4 Predictive Role of Urinary MiR-155 of BC Patients The detection of circulating miRNAs in the blood of BC patients has opened new avenues for their use as non-invasive biomarkers. However, the potential of urinary miRNAs as diagnostic or predictive biomarkers remains relatively unexplored. A study from Germany by Erbes et al. [ 52 ] provided early insight into this area. They analyzed the expression levels of nine urinary miRNAs (including miR-21, miR-34a, and miR-155) using real-time PCR in 24 untreated, primary BC patients and 24 healthy controls. Their findings showed that urinary miR-155 levels were significantly higher in BC patients compared to healthy controls (1.49 vs. 0.25). Moreover, the combined urinary miRNA profile achieved high diagnostic accuracy, with an area under the ROC curve (AUC) of 0.932, effectively distinguishing BC patients from healthy individuals. These results highlight the potential of urinary miRNAs—particularly miR-155—as innovative, non-invasive biomarkers for BC detection. However, across all reviewed databases, this was the only study evaluating the predictive role of urinary miR-155. Therefore, further research is needed to validate and expand upon these initial findings. 4. Discussion BC remains one of the leading causes of cancer-related death worldwide, underscoring the urgent need for early detection, a deeper understanding of tumor biology, and more effective treatment strategies. Currently, BC diagnosis primarily relies on clinical breast examination, mammography, breast ultrasound, magnetic resonance imaging (MRI) and tissue biopsy [ 53 , 54 ]. While each of these methods offers distinct advantages, they also present limitations in terms of sensitivity, specificity, invasiveness, cost, or accessibility. It is well- known that gene detection technologies such as Oncotype Dx Breast Recurrence Score®, MammaPrint, Prosigna®, EndoPredict®, and Breast Cancer Index (BCI) have been valuable in determining BC diagnosis, assessing disease progression, and predicting treatment outcomes. Although these tests can enhance disease understanding and inform treatment decisions, they are primarily tissue-dependent, pricey, require specialized interpretation, and may not be available at all circumstance [ 55 , 56 ]. However, circulating miRNAs in BC could provide unique benefits that complement and enhance current genetic tests and diagnosis. Due to be obtained non-invasively and require only a blood draw during disease characterization, they can improve the patient experience and simplify sample collection. Therefore, circulating miRNAs have the bright future for early disease detection. A single blood sample could meet the requirements and provide insights about all walks of the disease, such as early diagnosis, progression detection, treatment efficacy, and metastatic propensity. Most interestingly, when we searching the literature from all selected database, we found urine could also be used as sample to detect miRNAs based on certain studies that urinary miRNAs have a high potential in urological cancers. However, urine, as an easily accessible, non-invasive source of circulating miRNAs, has not been fully elucidated in the BC setting. Although Erbes 's [ 52 ] pilot study achieved surprising results about feasibility of urinary miRNAs detection in BC patients and its potential as an innovative non-invasive biomarker, no further research seems to be able to confirm these observations, so more researches are needed to confirm this result in the future. Here, we analyzed the potential predictive value of miR-155 in BC. miRNAs are effective biomarkers of a variety of diseases. In the past decade, many studies have emerged to examine the clinical value of miRNAs in BC, which is a global public health issue that poses a major challenge to disease management. In particularly, miR-155 is one of the most studied miRNAs in many diseases, including BC. miR-155 actually involves in tumor progression and is associated with drug resistance in BC. Therefore, many studies have confirmed that miR-155 antagonists can play a therapeutic role, but these studies were mainly conducted in vitro, and the lack of an effective delivery mechanism in vivo limits its therapeutic purpose in clinical practice [ 57 , 58 ]. Many researchers have investigated the potential of miR-155 as a biomarker for BC diagnosis, progression, metastasis, and treatment response. However, the predictive value of miRNAs—including miR-155—remains to be fully clarified. To address this, we conducted a systematic review of all available clinical studies evaluating the role of miR-155 in BC. Out of 640 initially identified records, 37 studies met the inclusion criteria and demonstrated potential clinical relevance of miR-155 expression. Most of these studies analyzed the association between miR-155 levels and predictive factors, including patient-related variables (such as age, menopausal status, family history, treatment, and survival outcomes) and tumor-related characteristics (such as tumor size, grade, receptor status, stage, and lymph node metastasis). However, not all studies assessed overall survival (OS) or disease-free survival (DFS), likely due to limited follow-up data, which weakens the clinical applicability of the findings. Interestingly, a few studies suggested a potential protective role for miR-155, contrasting with its more commonly described function as an oncomiR [ 32 , 42 ]. Additionally, three studies found no significant association between miR-155 expression and predictive outcomes [ 34 , 46 , 49 ]. More consistent evidence supports the role of miR-155 in treatment response. Several studies [ 25 , 28 , 35 , 41 ] reported a decrease in miR-155 expression following treatment—including surgery, chemotherapy, radiotherapy, or medication—suggesting its utility in therapeutic monitoring. 5. Conclusions Our systematic review highlights the promising potential of miR-155 as a predictive biomarker in BC, although it is not yet suitable for routine clinical use. Its possible clinical applications span disease diagnosis, monitoring of disease progression, prediction of metastasis, and assessment of treatment response. The non-invasive nature of circulating miRNA—detectable in blood or urine—further enhances their appeal as tools for clinical management. However, the studies included in this review did not provide sufficient or consistent evidence to definitively answer our research question. Limitations such as small sample sizes, heterogeneous patient cohorts, uneven distribution of BC subtypes, and limited follow-up data contribute to the overall lack of robustness in the findings. To clarify the predictive value of miR-155 in BC, large-scale, well-designed prospective studies with standardized methodologies and comprehensive follow-up are urgently needed. Overall, despite the promising potential of miRNAs, several challenges must still be addressed before their routine application in clinical practice can be realized. Abbreviations BC Breast cancer TNBC Triple-negative breast cancer T Tissue S Serum P Plasma FFPE Formalin-fixed paraffin-embedded TNM Tumour node metastasis LN Lymph node, EMT:Epithelial - mesenchymal transition IDC Invasive ductal carcinoma NAC Neoadjuvant chemotherapy ER Estrogen receptor PR Progesterone receptor DFS Disease-free survival OS Overall survival BMFS Brain metastasis-free survival EFS Event-free survival PFS Progression-free survival. Declarations Ethics, Consent to Participate, and Consent to Publish declarations: Not applicable. Competing interests No conflict of interest was reported by the author(s). Funding This research was supported by Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia. Author Contribution X. Chen — conceptualization, methodology, formal analysis, investigation, resources, writing (original draft preparation); H. Qiu — data curation, writing (review and editing); M.T. Ong — supervision, project administration, writing (review and proofreading), funding acquisition. Data Availability The following are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at the Institute for Research in Molecular Medicine, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia. Table S1: Key terms used in literature search, Table S2: PRISMA Checklist. References Lortet-Tieulent J, et al. 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Curr Opin Cell Biol. 2009;21(3):452–60. Alles J, et al. An estimate of the total number of true human miRNAs. Nucleic Acids Res. 2019;47(7):3353–64. Kimura M, et al. MicroRNAs in infectious diseases: potential diagnostic biomarkers and therapeutic targets. Clin Microbiol Rev. 2023;36(4):e0001523. Xiong B, et al. Recent advances microRNAs and metabolic reprogramming in colorectal cancer research. Front Oncol. 2023;13:1165862. Zaiou M, Rihn BH, Bakillah A. Epigenetic regulation of genes involved in the reverse cholesterol transport through interaction with miRNAs. Front Biosci (Landmark Ed). 2018;23(11):2090–105. Baylie T, et al. The role of miRNAs as biomarkers in breast cancer. Front Oncol. 2024;14:1374821. Grimaldi AM et al. Prognostic and Clinicopathological Significance of MiR-155 in Breast Cancer: A Systematic Review. Int J Mol Sci, 2020. 21(16). Mohan LP, et al. MicroRNAs as promising biomarkers and potential therapeutic agents in breast cancer management: a comprehensive review. Ann Med Surg (Lond). 2024;86(6):3543–50. Koleckova M, Janikova M, Kolar Z. MicroRNAs in triple-negative breast cancer. Neoplasma. 2018;65(1):1–13. Linares-Rodriguez M, Blancas I, Rodriguez-Serrano F. The Predictive Value of Blood-Derived Exosomal miRNAs as Biomarkers in Breast Cancer: A Systematic Review. Clin Breast Cancer, 2025. 25(1): p. e48-e55.e15. Kong W, et al. MicroRNA-155 is regulated by the transforming growth factor beta/Smad pathway and contributes to epithelial cell plasticity by targeting RhoA. Mol Cell Biol. 2008;28(22):6773–84. Wang F, et al. Correlation and quantitation of microRNA aberrant expression in tissues and sera from patients with breast tumor. Gynecol Oncol. 2010;119(3):586–93. Chen J, Wang BC, Tang JH. Clinical significance of microRNA-155 expression in human breast cancer. J Surg Oncol. 2012;106(3):260–6. LU Z, et al. miR-155 and miR-31 are differentially expressed in breast cancer patients and are correlated with the estrogen receptor and progesterone receptor status. Oncol Lett. 2012;4(5):1027–32. Hafez MM, et al. MicroRNAs and metastasis-related gene expression in Egyptian breast cancer patients. Asian Pac J Cancer Prev. 2012;13(2):591–8. Nassar FJ, et al. miRNA as potential biomarkers of breast cancer in the Lebanese population and in young women: a pilot study. PLoS ONE. 2014;9(9):e107566. Ouyang M, et al. MicroRNA profiling implies new markers of chemoresistance of triple-negative breast cancer. PLoS ONE. 2014;9(5):e96228. Meena MA, Najat AH, Alaa GH. The Inverse Correlation of MicroRNA-21 and MicroRNA-155 with the Tissue Inhibitor of Metalloproteinase 3 may Foster the Invasiveness of Breast Cancer. Volume 6. INTERNATIONAL JOURNAL OF MEDICAL RESEARCH & HEALTH SCIENCES; 2017. pp. 105–20. 12. Chernyy V, et al. Increased expression of miR-155 and miR-222 is associated with lymph node positive status. J Cancer. 2018;9(1):135–40. Soon PS, et al. Profiling differential microRNA expression between in situ, infiltrative and lympho-vascular space invasive breast cancer: a pilot study. Clin Exp Metastasis. 2018;35(1–2):3–13. Giannoudis A, et al. A novel panel of differentially-expressed microRNAs in breast cancer brain metastasis may predict patient survival. Sci Rep. 2019;9(1):18518. Khalighfard S, et al. Plasma miR-21, miR-155, miR-10b, and Let-7a as the potential biomarkers for the monitoring of breast cancer patients. Sci Rep. 2018;8(1):17981. Bitaraf A, Babashah S, Garshasbi M. Aberrant expression of a five-microRNA signature in breast carcinoma as a promising biomarker for diagnosis. J Clin Lab Anal. 2020;34(2):e23063. Pasculli B, et al. Hsa-miR-155-5p Up-Regulation in Breast Cancer and Its Relevance for Treatment With Poly[ADP-Ribose] Polymerase 1 (PARP-1) Inhibitors. Front Oncol. 2020;10:1415. Elango R, et al. MicroRNA Expression Profiling on Paired Primary and Lymph Node Metastatic Breast Cancer Revealed Distinct microRNA Profile Associated With LNM. Front Oncol. 2020;10:756. Pridko O, ASSOCIATION OF miRNA EXPRESSION PATTERN WITH OUTCOME OF LETROZOLE THERAPY IN BREAST CANCER PATIENTS, et al. Exp Oncol. 2023;45(2):180–6. Hachana MR, et al. microRNAs expression profile in phyllodes tumors of the breast. Heliyon. 2024;10(2):e24803. Zhu W, et al. Circulating microRNAs in breast cancer and healthy subjects. BMC Res Notes. 2009;2:89. Sun Y, et al. Serum microRNA-155 as a potential biomarker to track disease in breast cancer. PLoS ONE. 2012;7(10):e47003. Hagrass HA, et al. Circulating microRNAs - a new horizon in molecular diagnosis of breast cancer. Genes Cancer. 2015;6(5–6):281–7. Shaker O, et al. Role of microRNAs – 29b-2, -155, -197 and – 205 as diagnostic biomarkers in serum of breast cancer females. Gene. 2015;560(1):77–82. Zhang JQ, et al. Diagnostic value of circulating miR-155, miR-21, and miR-10b as promising biomarkers in human breast cancer. Volume 9. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY; 2016. pp. 10258–65. 10. Gao S, et al. MicroRNA-155, induced by FOXP3 through transcriptional repression of BRCA1, is associated with tumor initiation in human breast cancer. Oncotarget. 2017;8(25):41451–64. Shaheen J, et al. Identification of Circulating miRNAs as Non-Invasive Biomarkers of Triple Negative Breast Cancer in the Population of Pakistan. PAKISTAN J Zool. 2019;51(3):1113–21. Anwar SL, et al. Dynamic Changes of Circulating Mir-155 Expression and the Potential Application as a Non-Invasive Biomarker in Breast Cancer. Asian Pac J Cancer Prev. 2020;21(2):491–7. Aksan H, et al. Circulating miR-155, let-7c, miR-21, and PTEN levels in differential diagnosis and prognosis of idiopathic granulomatous mastitis and breast cancer. BioFactors. 2020;46(6):955–62. Soleimanpour E, et al. Circulating miR-21 and miR-155 as potential noninvasive biomarkers in Iranian Azeri patients with breast carcinoma. J Cancer Res Ther. 2019;15(5):1092–7. Zhang Z, et al. Exosomal miR-1246 and miR-155 as predictive and prognostic biomarkers for trastuzumab-based therapy resistance in HER2-positive breast cancer. Cancer Chemother Pharmacol. 2020;86(6):761–72. Triantafyllou A, et al. Circulating miRNA Expression Profiling in Breast Cancer Molecular Subtypes: Applying Machine Learning Analysis in Bioinformatics. Cancer Diagn Progn. 2022;2(6):739–49. Rajabi F, Mozdarani H. Expression level of miR-155, miR-15a and miR-19a in peripheral blood of ductal carcinoma breast cancer patients: Possible bioindicators for cellular inherent radiosensitivity. Exp Mol Pathol. 2022;126:104758. Mohamed AA et al. Evaluation of Expressed MicroRNAs as Prospective Biomarkers for Detection of Breast Cancer. Diagnostics (Basel), 2022. 12(4). Kumar V, et al. Impact of three miRNA signature as potential diagnostic marker for triple negative breast cancer patients. Sci Rep. 2023;13(1):21643. Harashchenko Capital O, ASSESSMENT OF CIRCULATING miRNA LEVELS IN BREAST CANCER PATIENTS DEPENDING ON CLINICAL CHARACTERISTICS AND CHEMOTHERAPY. Exp Oncol. 2024;45(4):451–6. Salum GM, et al. Evaluation of tumorigenesis-related miRNAs in breast cancer in Egyptian women: a retrospective, exploratory analysis. Sci Rep. 2024;14(1):29757. Abdel-Hamed AR et al. CD-36 variants and circulating miRNAs as prognostic biomarkers and potential therapeutic targets in breast cancer patients. GENE Rep, 2024. 35. Erbes T, et al. Feasibility of urinary microRNA detection in breast cancer patients and its potential as an innovative non-invasive biomarker. BMC Cancer. 2015;15:193. Wang Y, et al. Comparison of ultrasound and mammography for early diagnosis of breast cancer among Chinese women with suspected breast lesions: A prospective trial. Thorac Cancer. 2022;13(22):3145–51. Wekking D, Breast MRI, et al. Clinical Indications, Recommendations, and Future Applications in Breast Cancer Diagnosis. Curr Oncol Rep. 2023;25(4):257–67. Venetis K et al. The Evolving Role of Genomic Testing in Early Breast Cancer: Implications for Diagnosis, Prognosis, and Therapy. Int J Mol Sci, 2024. 25(11). Zeng C, Zhang J. A narrative review of five multigenetic assays in breast cancer. Transl Cancer Res. 2022;11(4):897–907. Anastasiadou E, et al. Cobomarsen, an Oligonucleotide Inhibitor of miR-155, Slows DLBCL Tumor Cell Growth In Vitro and In Vivo. Clin Cancer Res. 2021;27(4):1139–49. Razaviyan J et al. Exosomal Delivery of miR-155 Inhibitor can Suppress Migration, Invasion, and Angiogenesis Via PTEN and DUSP14 in Triple-negative Breast Cancer. Curr Med Chem, 2024. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 17 Aug, 2025 Reviewers agreed at journal 12 Aug, 2025 Reviewers invited by journal 11 Aug, 2025 Editor assigned by journal 11 Aug, 2025 Editor invited by journal 29 Jul, 2025 Submission checks completed at journal 25 Jul, 2025 First submitted to journal 25 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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18:01:52","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":138419,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7045756/v1/a1a5f6ef73e7e67fe941cc78.html"},{"id":97369059,"identity":"b5816320-9a4e-40e1-9979-7296f86bf48d","added_by":"auto","created_at":"2025-12-03 16:23:34","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":249381,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the search strategy and inclusion/exclusion processes.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7045756/v1/a66fb47d141086ef94f57bec.jpeg"},{"id":97892770,"identity":"38fb61cc-c817-4f48-a3be-be85af3e1f28","added_by":"auto","created_at":"2025-12-10 15:20:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1468800,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7045756/v1/875ae91e-4614-4858-9d43-d962f8e7cd4e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction of MiR-155 as Biomarkers in Breast Cancer: A Systematic Review","fulltext":[{"header":"1. Background","content":"\u003cp\u003eBreast cancer (BC) is one of the most common malignancies among women worldwide, with its mortality rate continuing to rise due to population growth and aging [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In 2022 alone, an estimated 2.3\u0026nbsp;million new cases were reported, accounting for 11.6% of all cancer diagnoses, and approximately 666,000 deaths were attributed to BC, representing 6.9% of all cancer-related deaths [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The heterogeneity of BC subtypes\u0026mdash;such as HER2-positive, Luminal A, Luminal B, and triple-negative breast cancer (TNBC)\u0026mdash;contributes to their varying aggressiveness and high mortality rates [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Early detection and accurate classification are critical for effective treatment and improved outcomes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Traditional clinical indicators, including tumor size, grade, lymph node (LN) involvement, patient age, and comorbidities, have been widely used for prognosis. However, over the past two decades, increasing attention has been given to identifying novel predictive biomarkers in tissues and biofluids (e.g., plasma, serum, urine) to enhance clinical decision-making. These biomarkers have the potential to improve diagnosis, monitor disease progression, and evaluate treatment response.\u003c/p\u003e\u003cp\u003eMicroRNAs (miRNAs) are a class of small, non-coding RNA molecules, typically 18 to 26 nucleotides in length. They were first discovered in 1993 by Lee et al. in \u003cem\u003eCaenorhabditis elegans\u003c/em\u003e, and officially named \"microRNAs\" in 2001 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This discovery marked a significant milestone in the study of non-coding RNAs, uncovering a novel mechanism of gene regulation. As endogenous regulatory molecules, miRNAs modulate gene expression at the transcriptional or translational level [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. They typically bind to complementary sequences in the 3\u0026prime; untranslated regions (3\u0026prime; UTRs) of target messenger RNAs (mRNAs), leading to either mRNA degradation or translational repression [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo date, over 2,300 mature human miRNAs have been identified and verified [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. miRNAs are essential regulators of numerous cellular processes, including development, cell differentiation, and homeostasis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. They are also involved in the pathophysiological pathways of a wide range of diseases, such as cardiovascular disorders, neurodegenerative diseases, and various cancers, offering new insights into disease mechanisms and progression [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Due to their ability to modulate gene expression, miRNAs can function either as oncogenes or tumor suppressors, and their dysregulation has been explored for diagnostic and predictive applications in oncology [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Among the miRNAs deregulated in BC, miR-155 is one of the most frequently reported, although it lacks specificity for predictive use [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Regardless of its diagnostic role, numerous studies have investigated the potential predictive value of miR-155 in BC. Recent evidence suggests that a miRNA signature\u0026mdash;including miR-155\u0026mdash;was associated with predictive outcomes in TNBC [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the predictive significance of miR-155 across all BC subtypes has not yet been systematically reviewed. Therefore, a comprehensive analysis of the predictive role of miR-155 in BC is warranted.\u003c/p\u003e\u003cp\u003eThis systematic review aims to evaluate existing clinical studies investigating the role of miR-155 as a biomarker for BC in both tissue and peripheral blood samples. The objective is to assess the potential of miR-155 expression levels as biomarkers for diagnosis, recurrence, progression, therapeutic monitoring and metastasis.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 search strategy\u003c/h2\u003e\u003cp\u003eFor this systematic review, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Two authors (HY QIU, and XH CHEN) conducted systematic literature searches in Web of Science and PubMed. We did not apply any publication date limits in our search strategy to ensure comprehensive coverage of relevant studies..We employed the following search strategy: (miR-155 or microRNA-155 or miR155) and breast cancer and (prediction or predictive or tissue or circulation or serum or plasma). The key search terms are detailed in Supplementary Table S1. Additionally, we performed a manual search of the reference lists from relevant publications to identify any further eligible studies.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Study Selection\u003c/h2\u003e\u003cp\u003eThis study focused on peer-reviewed articles investigating tissue- or blood-derived miR-155, specifically evaluating its potential utility as a biomarker for the prediction of breast cancer. Two researchers (HY QIU, and XH CHEN) independently screened the titles and abstracts of identified articles and the inclusion criteria were as follows: (1) studies evaluating the predictive role of miR-155 in breast tissue and/or blood samples from breast cancer patients; (2) original research articles; (3) studies published in English; (4) experimental studies involving any subtype or stage of BC. The exclusion criteria were: (1) non-original publications (e.g., reviews, editorials); (2) non-English articles; (3) studies not focused on BC. Disagreements between the two reviewers were resolved by consensus or, if necessary, through discussion with a third researcher (MT ONG). A comprehensive literature search was conducted on December 12, 2024, with no restrictions on publication date.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data extraction\u003c/h2\u003e\u003cp\u003eAfter protocol selection, data meeting the inclusion criteria were processed by one investigator (HY QIU) into a customized Excel spreadsheet database and verified by a second and third investigator (XH CHEN and MT ONG). From each eligible study, we extracted the following data: the specific microRNAs investigated, miR-155 expression levels; year of publication; country of the enrolled population; sample type (e.g., tissue, serum, plasma); number of patients and controls; parameters significantly associated with miR-155; its reported clinical relevance; references.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Literature Review Results\u003c/h2\u003e\u003cp\u003eFollowing our search strategy, a total of 640 potentially relevant records related to the predictive role of miR-155 in BC were identified from the PubMed and Web of Science databases. The article selection process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. After removing 386 duplicate records, 254 unique articles remained. Of these, 161 were excluded based on title and abstract screening because they were reviews, meta-analyses, non-English publications, or conference abstracts. The full texts of the remaining 93 articles were assessed, and 55 were excluded for not meeting the inclusion criteria. Ultimately, 37 studies were included in this systematic review to evaluate the predictive role of miR-155 in BC, using tissue and/or plasma/serum samples. These studies were categorized into three groups: Group 1 included 17 studies, of which 13 focused exclusively on tissue samples and 4 examined both tissue and serum/plasma samples. Group 2 included 19 studies that analyzed the predictive role of circulating miR-155. Group 3 consisted of a single study that investigated urinary miR-155. In conclusion, the majority of the included studies focused on the predictive role of circulating miR-155 in BC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe main characteristics of the included studies are presented in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In total, 37 original articles published between 2008 and 2024 were included, with sample sizes ranging from 5 to 283 and comprising a total of 3,793 samples. Of these, 32 studies included miR-155 as part of a broader panel of deregulated miRNAs, while the remaining 5 studies focused exclusively on miR-155. Among the selected articles, 24 studies investigated the association between miR-155 expression and predictive factors. These included patient-related factors (such as age, menopausal status, family history, treatment, and survival outcomes) and tumor-related factors (including tumor size, grade, receptor status, stage, and lymph node metastases). The studies were further categorized based on clinical relevance: 22 studies focused on BC diagnosis, 14 addressed disease progression and metastasis, and 9 examined treatment response and disease monitoring. Regarding expression trends, 32 studies reported upregulation of miR-155, while only 2 studies observed downregulation, suggesting that miR-155 is predominantly upregulated in BC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Predictive Role of MiR-155 in Tissues of BC Patients\u003c/h2\u003e\u003cp\u003eAmong the 17 studies evaluating the predictive role of miR-155 in tissues of BC patients (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), 8 studies specifically achieved this goal by correlating miR-155 expression levels with diagnosis of BC, and 10 studies of that with progression and metastasis, while 4 studies of that with its response to treatment and disease monitoring, accounting for 36%, 46%, 18% respectively. As mentioned above, up-regulated miR-155 occurred in 16 studies, while only one study showed down-regulation of miR-155. In addition, of these 17 studies, miR-155 was screened in frozen- or FFPE- or fresh-tissue, and 4 of them analyzed miR-155 expression both in tissue and blood.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComprehensive Characteristics and Clinical Relevance of Tissue-Based miR-155 Expression in Patients with Breast Cancer\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSample Size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSample source\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiRNAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003emiR-155 Deregulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eClinical Relevance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSignificantly Associated Parameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 noninvasive, 45 invasive BC, 5 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -214, -21, -323\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eProgression and metastases detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eEMT markers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68 BC, 40 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T + S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-21, -106a, -126, -155, -199a, -335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(IDC) and progression detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTumor grade, ER+, PR+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eProgression and metastases detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTumor grade, stage, LN metastases, DFS, OS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67 IDC BC, 70 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T + P\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(IDC) and progression detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eER, PR, Age, TNM stage, tumor size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSaudi Arabia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-10, 21, -155, -373, -30b, -126, -17p, -335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLNM detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTumor size, ER-,PR-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLebanon\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57 BC, 20 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE-T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-148b, -10b, -21, -221, -155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis (HER2+)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePostmenopausal, age, PR-, HER2+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 TNBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFresh T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -21, -181a, -181b, -183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTreatment response prediction (chemoresistance)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIraq\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 BC, 30 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T + P\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(IDC) and progression detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage, tumor grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRussia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-21, -155, -222, -205, -221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTreatment (NAC) prediction and LNM detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLN metastases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE-T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-150, -126, -155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(IDC) and progression detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE-T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-132, -199a, -150, -155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eBrain metastases detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eBMFS, OS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIran\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 BC, 10 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T + P\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-21, -155, -10b, Let-7a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis and treatment monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTreatment, TNM stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIran\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE-T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-127-3p, -133a, -155, -199b, -342\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis (HER2+)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage, HER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItaly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e283 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eResponse prediction to treatment (PARP1 inhibitors)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage, treatment, LN metastases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSaudi Arabia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76 BC, 32 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE-T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -150, -146a, -142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLNM detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLN metastases, TNM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUkraine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56 BC, 22 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrozen T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-125b, -155, -221, -320a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026darr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eResponse prediction to treatment (aromatase inhibitor)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eStage, HER2+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTunisia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE-T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-21, -155, -182, -34a, -148a, -205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(PT) and progression detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTumor grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u0026uarr; = up-regulated; \u0026darr; = down-regulated; ns\u0026thinsp;=\u0026thinsp;not statistically significant; BC\u0026thinsp;=\u0026thinsp;Breast cancer; T\u0026thinsp;=\u0026thinsp;tissue; FFPE\u0026thinsp;=\u0026thinsp;Formalin-Fixed Paraffin-Embedded; TNM\u0026thinsp;=\u0026thinsp;Tumour Node Metastasis; LN\u0026thinsp;=\u0026thinsp;Lymph node, EMT\u0026thinsp;=\u0026thinsp;Epithelial - Mesenchymal Transition; IDC\u0026thinsp;=\u0026thinsp;Invasive Ductal Carcinoma; NAC\u0026thinsp;=\u0026thinsp;Neoadjuvant Chemotherapy; ER\u0026thinsp;=\u0026thinsp;Estrogen Receptor; PR\u0026thinsp;=\u0026thinsp;Progesterone Receptor; DFS\u0026thinsp;=\u0026thinsp;Disease-Free Survival; OS\u0026thinsp;=\u0026thinsp;Overall Survival; BMFS\u0026thinsp;=\u0026thinsp;Brain Metastasis-Free Survival; PT\u0026thinsp;=\u0026thinsp;Phyllodes Tumor.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComprehensive Characteristics and Clinical Relevance of Blood-Based miR-155 Expression in Patients with Breast Cancer\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSample Size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSample source\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiRNAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003emiR-155 Deregulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eClinical Relevance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSignificantly Associated Parameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 BC, 8 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-16, -145, -155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(PR+)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePR+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e103 BC, 55 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis and treatment monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage, treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEgypt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120 BC, 50 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-10b, -34a, -155, -195, -16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eProgression and metastases detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eAge, tumour grade, ER, PR, LN metastases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEgypt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e130 BC, 30 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-29b, -155, -197, -205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(IDC) and progression detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage, tumor size, LN metastases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e106 BC, 106 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -21, -10b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e114 BC, 94 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(TN)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage, tumour grade, family history\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49 BC, 19 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-16, -21, -155, -195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis and TN subtype detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage, tumor size, TN subtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePakistan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37 BC, 34 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-376c, -155, -17a, -10b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(TN)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eAge, TNM stage, tumor grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndonesia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120 BC, 15 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis and treatment monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eAge, tumor size, treatment,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTurkey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45 BC, 48 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, let-7c, -21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026darr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDifferential diagnosis of IGM and BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIran\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 BC, 25 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-21, -155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e183 BC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-1246, -155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eResponse prediction to treatment (resistance to trastuzumab )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eEFS, PFS, treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGreece\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66 BC, 16 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-23b, -142, -29a, -181d, -16, -29b, -155, -181c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis and progression detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTN subtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIran\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 BC, 15 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -19a, -15a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eResponse prediction to treatment (radiosensitivity)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM, LN metastases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEgypt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99 BC, 40 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -373, -10b, -34a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eER-, PR-, tumor grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e139 TNBC and 51 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-205, -155, -21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(TN)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage, distant metastasis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUkraine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70 BC, 18 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-25, -27, -155, -200, -335, -497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis and treatment monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMenopausal status, stage, BC subtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEgypt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75 BC, 20 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-200a, -124, -205, -15a, -155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis(TN)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eStage, ER+, HER2+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEgypt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48 metastatic, 50 nonmetastatic, 43 benign BC, 35 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-155, -375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMetastases detection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u0026uarr; = up-regulated; \u0026darr; = down-regulated; ns\u0026thinsp;=\u0026thinsp;not statistically significant; BC\u0026thinsp;=\u0026thinsp;Breast cancer; S\u0026thinsp;=\u0026thinsp;Serum; P\u0026thinsp;=\u0026thinsp;Plasma; TN\u0026thinsp;=\u0026thinsp;triple negative.; TNM\u0026thinsp;=\u0026thinsp;Tumour Node Metastasis; LN\u0026thinsp;=\u0026thinsp;Lymph node; IDC\u0026thinsp;=\u0026thinsp;Invasive Ductal Carcinoma; IGM\u0026thinsp;=\u0026thinsp;Idiopathic Granulomatous Mastitis; ER\u0026thinsp;=\u0026thinsp;Estrogen Receptor; PR\u0026thinsp;=\u0026thinsp;Progesterone Receptor; EFS\u0026thinsp;=\u0026thinsp;Event-Free Survival; PFS\u0026thinsp;=\u0026thinsp;Progression-Free Survival.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComprehensive Characteristics and Clinical Relevance of Urine-Based miR-155 Expression in Patients with Breast Cancer\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSample Size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSample source\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiRNAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003emiR-155 Deregulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eClinical Relevance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSignificantly Associated Parameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGermany\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 BC, 24 healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eU\u0026thinsp;+\u0026thinsp;S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emiR-21, -34a, -125b, -155, -195, -200b, -200c, -375, -451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026uarr;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTNM stage,tumor grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eBC\u0026thinsp;=\u0026thinsp;Breast cancer; U\u0026thinsp;=\u0026thinsp;Urine; S\u0026thinsp;=\u0026thinsp;Serum; TNM\u0026thinsp;=\u0026thinsp;Tumour Node Metastasis.\u003c/p\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1 Tissue MiR-155 and Diagnosis\u003c/h2\u003e\u003cp\u003eWith the exception of one study, all the remaining studies indicated up-regulated miR-155, which contributed to the diagnosis of BC, however, the content of diagnosis varied. For instant, Khalighfard et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] Showed that up-regulation of tissue miR-155 might be considered as a respectable diagnostic tool for monitoring of BC patients, whereas Wang et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], Lu et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], Meena et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and Soon et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] pointed out miR-155 could contribute to diagnosis of invasive ductal carcinoma (IDC), and Nassar et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and Bitaraf et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] indicating diagnosis of HER2\u0026thinsp;+\u0026thinsp;BC. Moreover, All of the selected studies agreed that there was a high correlation of miR-155 expression level between tissues and blood, which encouraged further use of miRNAs in blood samples as an easy and convenient method of breast cancer screening.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e3.2.2 Tissue MiR-155 and Progression or Metastasis\u003c/h2\u003e\u003cp\u003eMost of the selected studies reported a positive correlation between miR-155 overexpression and key pathological features such as tumor grade [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], tumor node metastasis (TNM) stage [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and tumor sizes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, findings were inconsistent regarding the association between miR-155 expression and hormone receptor status (ER, PR, and HER2). For instance, Hafez et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] found no association between miR-155 expression and ER/PR status. In contrast, Wang et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and Chen et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] reported that high miR-155 expression was linked to ER/PR-negative status, whereas lower expression levels were associated with ER/PR-positive status. Meanwhile, Nassar et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] observed no correlation between miR-155 overexpression and ER-negative status, but did find an association with PR-negative status. Only a few studies (n\u0026thinsp;=\u0026thinsp;3) explored the relationship between miR-155 expression and HER2 status, and their findings were contradictory. Lu et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found no association, whereas Nassar et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and Bitaraf et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] reported that high miR-155 expression was associated with HER2-positive status. Conversely, Pridko et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] found that low miR-155 expression correlated with HER2 positivity. Finally, Giannoudis et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] reported that miR-155 may serve as a potential biomarker to identify breast cancer patients at increased risk of developing brain metastases.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e3.2.3 Tissue MiR-155 and Response to Treatment\u003c/h2\u003e\u003cp\u003eChernyy et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] investigated whether the relative expression of miR-155 could serve as a predictive biomarker for neoadjuvant chemotherapy (NAC) response and whether its differential expression in residual tumors post-treatment could be used to stratify non-responsive patients prognostically. In particular, they found that miR-155 expression was significantly decreased in tumour tissues of patients who received preoperative NAC compared with tumour tissues of patients without NAC in cohorts sub-classified to lymph node positive status. However, Ouyang et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] focused on the association between 11 specific deregulated miRNAs, including miR-155, and chemoresistance in TNBC.In particular, they asserted deregulated miR-155 was associated with chemoresistance.\u003c/p\u003e\u003cp\u003ePasculli et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] demonstrated miR-155 ectopic overexpression followed by Olaparib administration resulted in a greater reduction of cell viability as compared to Olaparib administration alone, suggesting that miR-155 might induce a synthetic lethal effect in TNBC when coupled with PARP-1-inhibition. Interestingly, Elango et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] found most HER2\u0026thinsp;+\u0026thinsp;BC patients had low levels of miR-155, which results were inconsistent with most other studies. They reported tumors that responded well to letrozole exhibited lower levels of miR-155 compared to non-responsive tumors, which indicated miR-155 could predict resistance to the letrozole treatment of BC. Furthermore, Khalighfard et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] focused on the impact of operation, chemotherapy, and radiotherapy on miR-155 in BC patients. They found there was a significant difference in the miR-155 tissue level after the operation, chemotherapy, and radiotherapy.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Predictive Role of MiR-155 in Serum/Plasma of BC Patients\u003c/h2\u003e\u003cp\u003eMost of the selected studies summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e assessed the predictive value of circulating miR-155 by correlating its expression with clinically relevant endpoints. Specifically, 14 studies (61%) focused on diagnosis, 4 studies (17%) on disease progression and metastasis, and 5 studies (22%) on treatment response. Interestingly, when compared with tissue-based miR-155, circulating miR-155 appeared to have a different predictive focus. While tissue miR-155 was more commonly associated with progression and metastasis, circulating miR-155 was primarily investigated in the context of diagnosis. Furthermore, 16 out of the 19 studies on circulating miR-155 analyzed its dysregulation alongside other circulating miRNAs, highlighting its role within broader miRNA panels rather than as a standalone marker.\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 Circulating MiR-155 and Diagnosis\u003c/h2\u003e\u003cp\u003eOf the 19 studies that investigated circulating miR-155, 16 reported its upregulation in BC, supporting its potential utility as a diagnostic biomarker. Notably, several studies\u0026mdash;including those by Gao et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], Shaheen et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], Kumar et al. [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], and Salum et al. [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u0026mdash;highlighted significant upregulation of miR-155 in TNBC, suggesting its potential as an indicative marker for this aggressive subtype. In contrast, Zhu et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] found that patients with PR-positive tumors had higher serum miR-155 expression compared to those with PR-negative tumors; however, they observed no significant difference in miR-155 levels between BC patients and healthy controls. Regarding diagnostic performance, seven studies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] evaluated the receiver operating characteristic (ROC) curves for circulating miR-155 and reported area under the curve (AUC) values ranging from 0.801 to 0.949. These findings indicate that miR-155 exhibits high sensitivity and specificity, reinforcing its diagnostic potential in BC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 Circulating MiR-155 and Progression or Metastasis\u003c/h2\u003e\u003cp\u003eStudies examining the relationship between circulating miR-155 and breast cancer progression reported inconsistent findings. While most studies suggested an association between miR-155 levels and tumor stage, size, nodal involvement, and the presence of metastasis, results varied across individual investigations. For example, Shaker et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] observed that elevated miR-155 expression was significantly correlated with tumor stage, tumor size, and lymph node involvement. In contrast, Anwar et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] did not find any significant associations between miR-155 expression and tumor grade, subtype, or stage. However, they reported that patients over 40 years of age exhibited higher circulating miR-155 levels than those under 40, and that miR-155 expression was significantly elevated in patients with tumors larger than 5 cm. Regarding metastasis, Hagrass et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], Shaker et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and Abdel-Hamed et al. [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] found significantly higher serum levels of miR-155 in patients with lymph node metastasis and distant metastasis (M1) compared to those without metastasis (M0). These findings suggest that miR-155 may play a role in promoting breast cancer progression and metastatic spread.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3 Circulating MiR-155 and Response to Treatment\u003c/h2\u003e\u003cp\u003eThough Harashchenko et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] reported no significant change of miR-155 expression in patients after neoadjuvant chemotherapy, most of the selected studies found a decreased level of serum miR-155 in BC patients after surgery and chemotherapy [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], which indicated miR-155 could serve as an indicator for clinical response prediction to treatment. Besides, Sun et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]and his colleagues found the concentrations of carbohydrate antigen 15\u0026thinsp;\u0026minus;\u0026thinsp;3, carcinoembryonic antigen and tissue polypeptide specific antigen did not show this trend in patients after surgery and chemotherapy, highlighting the unique value of miR-155 in response to treatment. In particular, Rajabi et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] reported a significant association between miR-155 expression levels and the frequency of chromatid breaks, suggesting that miR-155 could serve as a bioindicator for predicting cellular radiosensitivity in BC patients. Regarding prognostic factors, Zhang et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] using Kaplan\u0026ndash;Meier survival analysis, demonstrated that patients with high expression of miR-1246 and miR-155 had poorer outcomes. Specifically, early-stage patients with elevated miR-1246 and metastatic patients with elevated miR-155 exhibited shorter event-free survival (EFS) and progression-free survival (PFS), respectively, compared to those with lower expression levels. Conversely, some inconsistencies emerged. For example, Anwar et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] reported that, although longer follow-up is necessary, patients with upregulated circulating miR-155 showed longer PFS, with mean survival times of 77 weeks versus 65 weeks, indicating a potential protective effect in their cohort.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Predictive Role of Urinary MiR-155 of BC Patients\u003c/h2\u003e\u003cp\u003eThe detection of circulating miRNAs in the blood of BC patients has opened new avenues for their use as non-invasive biomarkers. However, the potential of urinary miRNAs as diagnostic or predictive biomarkers remains relatively unexplored. A study from Germany by Erbes et al. [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] provided early insight into this area. They analyzed the expression levels of nine urinary miRNAs (including miR-21, miR-34a, and miR-155) using real-time PCR in 24 untreated, primary BC patients and 24 healthy controls. Their findings showed that urinary miR-155 levels were significantly higher in BC patients compared to healthy controls (1.49 vs. 0.25). Moreover, the combined urinary miRNA profile achieved high diagnostic accuracy, with an area under the ROC curve (AUC) of 0.932, effectively distinguishing BC patients from healthy individuals. These results highlight the potential of urinary miRNAs\u0026mdash;particularly miR-155\u0026mdash;as innovative, non-invasive biomarkers for BC detection. However, across all reviewed databases, this was the only study evaluating the predictive role of urinary miR-155. Therefore, further research is needed to validate and expand upon these initial findings.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eBC remains one of the leading causes of cancer-related death worldwide, underscoring the urgent need for early detection, a deeper understanding of tumor biology, and more effective treatment strategies. Currently, BC diagnosis primarily relies on clinical breast examination, mammography, breast ultrasound, magnetic resonance imaging (MRI) and tissue biopsy [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. While each of these methods offers distinct advantages, they also present limitations in terms of sensitivity, specificity, invasiveness, cost, or accessibility. It is well- known that gene detection technologies such as Oncotype Dx Breast Recurrence Score\u0026reg;, MammaPrint, Prosigna\u0026reg;, EndoPredict\u0026reg;, and Breast Cancer Index (BCI) have been valuable in determining BC diagnosis, assessing disease progression, and predicting treatment outcomes. Although these tests can enhance disease understanding and inform treatment decisions, they are primarily tissue-dependent, pricey, require specialized interpretation, and may not be available at all circumstance [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. However, circulating miRNAs in BC could provide unique benefits that complement and enhance current genetic tests and diagnosis. Due to be obtained non-invasively and require only a blood draw during disease characterization, they can improve the patient experience and simplify sample collection. Therefore, circulating miRNAs have the bright future for early disease detection. A single blood sample could meet the requirements and provide insights about all walks of the disease, such as early diagnosis, progression detection, treatment efficacy, and metastatic propensity.\u003c/p\u003e\u003cp\u003eMost interestingly, when we searching the literature from all selected database, we found urine could also be used as sample to detect miRNAs based on certain studies that urinary miRNAs have a high potential in urological cancers. However, urine, as an easily accessible, non-invasive source of circulating miRNAs, has not been fully elucidated in the BC setting. Although Erbes 's [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] pilot study achieved surprising results about feasibility of urinary miRNAs detection in BC patients and its potential as an innovative non-invasive biomarker, no further research seems to be able to confirm these observations, so more researches are needed to confirm this result in the future.\u003c/p\u003e\u003cp\u003eHere, we analyzed the potential predictive value of miR-155 in BC. miRNAs are effective biomarkers of a variety of diseases. In the past decade, many studies have emerged to examine the clinical value of miRNAs in BC, which is a global public health issue that poses a major challenge to disease management. In particularly, miR-155 is one of the most studied miRNAs in many diseases, including BC. miR-155 actually involves in tumor progression and is associated with drug resistance in BC. Therefore, many studies have confirmed that miR-155 antagonists can play a therapeutic role, but these studies were mainly conducted in vitro, and the lack of an effective delivery mechanism in vivo limits its therapeutic purpose in clinical practice [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMany researchers have investigated the potential of miR-155 as a biomarker for BC diagnosis, progression, metastasis, and treatment response. However, the predictive value of miRNAs\u0026mdash;including miR-155\u0026mdash;remains to be fully clarified. To address this, we conducted a systematic review of all available clinical studies evaluating the role of miR-155 in BC. Out of 640 initially identified records, 37 studies met the inclusion criteria and demonstrated potential clinical relevance of miR-155 expression. Most of these studies analyzed the association between miR-155 levels and predictive factors, including patient-related variables (such as age, menopausal status, family history, treatment, and survival outcomes) and tumor-related characteristics (such as tumor size, grade, receptor status, stage, and lymph node metastasis). However, not all studies assessed overall survival (OS) or disease-free survival (DFS), likely due to limited follow-up data, which weakens the clinical applicability of the findings. Interestingly, a few studies suggested a potential protective role for miR-155, contrasting with its more commonly described function as an oncomiR [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Additionally, three studies found no significant association between miR-155 expression and predictive outcomes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. More consistent evidence supports the role of miR-155 in treatment response. Several studies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] reported a decrease in miR-155 expression following treatment\u0026mdash;including surgery, chemotherapy, radiotherapy, or medication\u0026mdash;suggesting its utility in therapeutic monitoring.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eOur systematic review highlights the promising potential of miR-155 as a predictive biomarker in BC, although it is not yet suitable for routine clinical use. Its possible clinical applications span disease diagnosis, monitoring of disease progression, prediction of metastasis, and assessment of treatment response. The non-invasive nature of circulating miRNA\u0026mdash;detectable in blood or urine\u0026mdash;further enhances their appeal as tools for clinical management. However, the studies included in this review did not provide sufficient or consistent evidence to definitively answer our research question. Limitations such as small sample sizes, heterogeneous patient cohorts, uneven distribution of BC subtypes, and limited follow-up data contribute to the overall lack of robustness in the findings. To clarify the predictive value of miR-155 in BC, large-scale, well-designed prospective studies with standardized methodologies and comprehensive follow-up are urgently needed. Overall, despite the promising potential of miRNAs, several challenges must still be addressed before their routine application in clinical practice can be realized.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBreast cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTNBC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTriple-negative breast cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTissue\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSerum\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePlasma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFFPE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFormalin-fixed paraffin-embedded\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTNM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTumour node metastasis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLymph node, EMT:Epithelial - mesenchymal transition\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIDC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNAC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNeoadjuvant chemotherapy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eER\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEstrogen receptor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProgesterone receptor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDFS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDisease-free survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOverall survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMFS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBrain metastasis-free survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEFS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEvent-free survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePFS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProgression-free survival.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics, Consent to Participate, and Consent to Publish declarations:\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eNo conflict of interest was reported by the author(s).\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research was supported by Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eX. Chen \u0026mdash; conceptualization, methodology, formal analysis, investigation, resources, writing (original draft preparation); H. Qiu \u0026mdash; data curation, writing (review and editing); M.T. Ong \u0026mdash; supervision, project administration, writing (review and proofreading), funding acquisition.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe following are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at the Institute for Research in Molecular Medicine, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia. Table S1: Key terms used in literature search, Table S2: PRISMA Checklist.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLortet-Tieulent J, et al. Profiling global cancer incidence and mortality by socioeconomic development. 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Exp Oncol. 2024;45(4):451\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalum GM, et al. Evaluation of tumorigenesis-related miRNAs in breast cancer in Egyptian women: a retrospective, exploratory analysis. Sci Rep. 2024;14(1):29757.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbdel-Hamed AR et al. CD-36 variants and circulating miRNAs as prognostic biomarkers and potential therapeutic targets in breast cancer patients. GENE Rep, 2024. 35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eErbes T, et al. Feasibility of urinary microRNA detection in breast cancer patients and its potential as an innovative non-invasive biomarker. BMC Cancer. 2015;15:193.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, et al. Comparison of ultrasound and mammography for early diagnosis of breast cancer among Chinese women with suspected breast lesions: A prospective trial. Thorac Cancer. 2022;13(22):3145\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWekking D, Breast MRI, et al. Clinical Indications, Recommendations, and Future Applications in Breast Cancer Diagnosis. Curr Oncol Rep. 2023;25(4):257\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVenetis K et al. The Evolving Role of Genomic Testing in Early Breast Cancer: Implications for Diagnosis, Prognosis, and Therapy. Int J Mol Sci, 2024. 25(11).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeng C, Zhang J. A narrative review of five multigenetic assays in breast cancer. Transl Cancer Res. 2022;11(4):897\u0026ndash;907.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnastasiadou E, et al. Cobomarsen, an Oligonucleotide Inhibitor of miR-155, Slows DLBCL Tumor Cell Growth In Vitro and In Vivo. Clin Cancer Res. 2021;27(4):1139\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRazaviyan J et al. Exosomal Delivery of miR-155 Inhibitor can Suppress Migration, Invasion, and Angiogenesis Via PTEN and DUSP14 in Triple-negative Breast Cancer. Curr Med Chem, 2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"miR-155, breast cancer, prediction, tissue, blood, urine","lastPublishedDoi":"10.21203/rs.3.rs-7045756/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7045756/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDespite significant advances in the detection and treatment of breast cancer (BC), it remains one of the most prevalent malignancies worldwide. MicroRNAs (miRNAs) have emerged as critical regulators in cancer biology, influencing tumor initiation, progression, immune evasion, and therapy resistance. Among them, miR-155 is widely recognized as an oncogenic miRNA that promotes tumor growth, angiogenesis, and invasiveness in BC. As a result, it has been extensively studied as a potential predictive biomarker and therapeutic target. However, its predictive value in BC patients remains to be fully elucidated. This systematic review aims to synthesize current evidence on the predictive significance of miR-155 in BC pathology. A comprehensive search of PubMed and Web of Science identified 640 potentially relevant studies, of which 37 met the inclusion criteria for full analysis. These studies assessed miR-155 expression in tissue, blood, and urine samples and its associations with clinical outcomes and pathological features in BC patients. Our analysis suggests that circulating and urinary miR-155 may offer comparable predictive value to tissue-derived miR-155, with potential applications in early diagnosis, disease monitoring, recurrence detection, treatment response, and metastasis prediction. We also identified challenges that limit the clinical translation of miR-155, emphasizing the need for greater consistency and validation across studies.. Overall, this review highlights the promising role of miR-155 in BC management while emphasizing the need for further validation through well-designed clinical studies. T\u003cb\u003ehis work has been registered in PROSPERO with registration number CRD420251001681 and date of registration 14th May 2025\u003c/b\u003e.\u003c/p\u003e","manuscriptTitle":"Prediction of MiR-155 as Biomarkers in Breast Cancer: A Systematic Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 18:01:47","doi":"10.21203/rs.3.rs-7045756/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-08-17T15:01:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93972007608743818762087988091118440199","date":"2025-08-12T14:05:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-11T09:10:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-11T09:10:17+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-29T06:45:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-25T17:42:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-07-25T13:02:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"37538a0a-7876-4e54-bf44-18adf5f07d8e","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-02T18:01:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-02 18:01:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7045756","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7045756","identity":"rs-7045756","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}