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7 October 2026

28 Pages

The Role of Long Non-Coding RNAs in Breast Cancer Diagnosis and Treatment Based on Evidence from Clinical Studies: A Scoping Review

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1
School of Health Science, International Hellenic University, 57400 Thessaloniki, Greece
2
Department of Medical Oncology, European Interbalkan Medical Center, 55535 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Epigenomes2026, 10(4), 65;https://doi.org/10.3390/epigenomes10040065
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Abstract

Background/Objectives: The aim of this scoping review was to investigate the current role and possible clinical applications of long non-coding RNAs (lncRNAs) in breast cancer diagnosis and treatment. Methods: A thorough search of the PubMed/MEDLINE and Scopus/EMBASE databases was carried out in accordance with the PRISMA-ScR guidelines. The inclusion criteria were as follows: Studies with lncRNA analyses of specimens from breast cancer patients and clinically relevant studies. The exclusion criteria were as follows: in silico and in vitro studies involving animal models; reviews; case series; case reports; comments; editorials; and papers not written in English. The study protocol was registered in the Open Science Framework. Results: After the identification of 1139 records, 312 publications were retrieved and 228 articles were selected for data extraction. Data analysis and the synthesis of evidence showed that lncRNA studies were conducted in breast tumor specimens in 212 studies and in blood samples from breast cancer patients in 20 studies. The most commonly used method was quantitative RT-PCR (in 216 studies), while many studies were complemented by in vitro (n = 177) and animal experiments (n = 75). There were 39 studies that included at least 100 specimens from breast cancer patients. Conclusions: At present, lncRNA analysis is not used in routine clinical practice. Clinically relevant findings coupled by results from in vitro and animal experiments suggest that various lncRNAs after appropriate validation may be used as biomarkers for breast cancer diagnosis and treatment, most notably HSAT164, CCAT2, HOTAIR, and MALAT1. To this end, larger studies involving clinical specimens from clinically relevant subgroups of breast cancer patients will be needed.

1. Introduction

Breast cancer is the most commonly diagnosed malignancy and the leading cause of cancer death in women worldwide, followed by lung and colorectal cancer for both cancer incidence and mortality [1]. Since the early 1990s, breast cancer mortality rates have decreased in many high-income countries as a consequence of the widespread use of mammographic screening leading to early diagnosis and due to increasingly effective treatment methods [1,2]. In turn, decreased mortality rates have led to an increased prevalence of long-term breast cancer survivors, while recurrences continue to occur even more than three decades after primary diagnosis [3]. Circulating tumor cells (CTCs) and tumor cells in the bone marrow of breast cancer patients have been detected years before disease recurrence [3,4,5,6], suggesting that disease persists outside of the breast or local lymph nodes in a clinically latent state before it develops into manifest metastases, a concept also referred to as tumor dormancy [5]. Hence, it is not surprising that breast cancer remains the most common cause of death after breast cancer diagnosis, though other entities, mainly heart and cerebrovascular disease, represent a significant cause of mortality among breast cancer survivors [7,8].
For many years in the past, the decision of whether to administer systemic cytotoxic chemotherapy or not to patients with hormone receptor-positive early breast cancer has been a challenge in everyday clinical practice, as clinicians had to balance between the possibility of over-treatment with associated toxicity and under-treatment with the risk of early disease recurrence [9,10]. The development of multi-gene expression assays at the mRNA level has been a paradigm shift in the treatment of early breast cancer, as these assays now have paramount importance in the decision of whether to administer chemotherapy or not to patients with early luminal breast cancer [11,12]. Other than mRNA, in recent years, research has focused on investigating the potential role of long non-coding RNAs (lncRNAs) in breast cancer pathogenesis and tumor progression, with possible applications in diagnosis and treatment. Several lines of evidence have implicated lncRNAs in the regulation of cancer stem cells and the tumor microenvironment [13,14], the cell cycle [15], inflammation in breast cancer [16], and the possibility to be used as therapeutic targets [17,18]. However, it is unclear to clinicians if lncRNAs already have clinical applications in breast cancer diagnosis and treatment. Therefore, the objective of this scoping review was to investigate the current role and possible clinical applications of lncRNA analyses in breast cancer diagnosis and treatment.

2. Results

2.1. Search Results

Figure 1 presents a flow chart of the study selection process and search results, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR) [19,20]. In detail, 1139 entries (431 in PubMed and 708 in Scopus) were identified by using the search terms “non-coding RNA” AND “breast cancer”, AND “ncRNA” AND “breast cancer”, with the limits “title” for PubMed and “Article title” for Scopus. First, duplicates, overlapping publications, and articles not written in English (n = 335) were removed. Next, the titles and/or abstracts of the remaining 804 records were evaluated, leading to the exclusion of 484 studies according to the exclusion criteria and 320 studies to be sought for retrieval. In total, 312 studies were retrieved and, following evaluation of their full-text, 84 studies were excluded based on the eligibility criteria. Finally, 228 articles were included [21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248], and extraction of the data followed.
Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR) flowchart.

2.2. Year of Publication and Geographical Area of Included Studies

Regarding the year of publication, all studies except one were published during the last 12 years, with the number of studies reaching a maximum in 2019 and decreasing thereafter. In detail, one study was published in 2009 [242], three studies in 2013 [239,240,241], three studies in 2014 [236,237,238], eight studies in 2015 [228,229,230,231,232,233,234,235], 12 studies in 2016 [216,217,218,219,220,221,222,223,224,225,226,227], 24 studies in 2017 [192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215], 25 studies in 2018 [166,167,168,169,170,171,172,173,174,175,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191], 40 studies in 2019 [125,126,127,128,129,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165], 37 studies in 2020 [74,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,130], 34 studies in 2021 [54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,75,76,77,78,80,81,82,83,84,85,86,87,88,89], 13 studies in 2022 [42,43,44,45,46,47,48,49,50,51,52,53,79], 11 studies in 2023 [25,32,33,34,35,36,37,38,39,40,41], eight studies in 2024 [22,24,26,27,28,29,30,31], six studies in 2025 [21,23,176,243,244,245], and three studies until April 2026 [246,247,248]. A timeline chart showing the number of publications over time is presented in Supplementary Figure S1.
Regarding the country of first author’s affiliation, 177 out of 228 studies (77.6%) came from China and the remaining 51 from the rest of the world, as follows: (a) 204 studies came from Asia, i.e., 177 from China [23,25,26,27,29,30,34,35,38,39,41,42,43,44,45,48,49,50,51,52,53,55,56,57,58,59,61,63,66,67,68,69,70,73,74,75,77,78,79,82,83,84,85,86,87,88,89,91,92,93,95,96,98,99,102,103,104,105,106,107,108,109,110,111,113,114,115,116,117,118,119,121,122,123,124,127,128,129,130,131,132,133,134,135,137,138,139,140,141,142,144,147,148,149,150,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,191,192,193,194,195,196,197,198,199,200,201,202,203,204,206,207,209,210,211,212,213,214,215,216,217,218,219,220,221,223,224,225,226,227,228,229,230,231,232,233,235,236,238,244], 19 from Iran [21,22,28,33,40,46,56,80,81,100,101,112,120,136,145,146,205,240,246], two from Saudia Arabia [32,60], one from India [37], one from Lebanon [97], one from South Korea [168], and one from Taiwan [148]; (b) 11 studies came from Europe, i.e., three from Denmark [62,234,239], one from Spain [24], one from Greece [36], one from Russia [47], one from Romania [71], one from Italy [94], one from France [208], one from Germany [237], and one from the Netherlands and Sweden [243]; (c) six studies came from North and South America, i.e., two from the USA [222,241], two from Brazil [72,126], one from Canada [242], and one from Mexico [125]; (d) eight studies came from Africa, all from Egypt [31,64,76,90,190,245,247,248]; and (e) one study came from Oceania, i.e., from New Zealand [143]. The geographical distribution of studies is diagrammatically presented in Supplementary Figure S2.

2.3. Clinical Relevance and Characteristics of Included Studies

Regarding the type of tissue specimen analyzed, lncRNA analysis was carried out in breast tumor specimens in 212 studies (Table 1 and Supplementary Table S1) and in blood samples from breast cancer patients in 20 studies (Table 2), i.e., 10 studies involving serum, seven studies involving plasma, and three studies involving whole blood. In four studies, both blood and breast tumor specimens were analyzed. Regarding the disease stage, in most studies, specimens from patients with primary invasive breast cancer (stages I–III) were analyzed, while specimens from patients with DCIS (stage 0) and metastatic breast cancer (stage IV) were included only rarely. The most commonly used method (in 216 studies) was quantitative reverse transcription polymerase chain reaction (qRT-PCR). Many studies were complemented by in vitro (n = 177 or 77.6% of included studies) and animal experiments (n = 75 or 32.9% of included studies) (Supplementary Table S2).

2.3.1. Studies with Non-Coding RNA Analyses in Breast Cancer Tissue

Long non-coding RNA analyses were carried out in breast tumor tissue with or without normal breast tissue specimens in 212 studies. The number of specimens analyzed ranged between 18 and 99 in 179 studies; there were 23 studies with 100–200 specimens [38,48,58,61,62,78,88,93,125,146,149,154,161,162,170,199,201,207,218,224,232,234,239] and only 10 studies [84,124,169,195,200,216,217,223,227,241] with more than 200 specimens analyzed.
In Table 1, the 33 largest studies [38,48,58,61,62,78,84,88,93,124,125,146,149,154,161,162,169,170,195,199,200,201,207,216,217,218,223,224,227,232,234,239,241] of lncRNA analyses with at least 100 breast tumor tissue specimens with or without normal breast tissue samples are presented in descending order of the number of specimens. The following lncRNAs were identified as potential diagnostic biomarkers and/or therapeutic targets in breast cancer tissue: HSAT164 [84], CCAT2 [241], C19orf33, C3orf52 C15orf48, and C4orf19 [195]; MVIH [217], EPB41L4A-AS2 [223], MALAT1 [216,218,247], HUMT [124], Linc-ITGB1 [200], BANCR [169], MEG3 [227], CRALA [201], MIAT [170], HOTAIR [239], RHPN1-AS1 [161], LncKLHDC7B [125], LUCAT1 [162], MIR-1 [232], RACGAP1P [88], MCF2L-AS1 [48], COX10-DT [38], HOXA-AS2 [93], Lnc-BTG3-7:1 [61], ST8SIA6-AS1, lnc-HIST1H2BJ-5:1, lnc PRICKLE2-3:2, RP1-86C11.7, RP11-15F12.1, ZNF670-ZNF695, and lnc-STRN3-12:1 [58]; and LINC01287 [149], H19 [146], NORAD [78], AFAP1-AS1 [224], SPRY4-IT1 [154], TUG1 [199], and HOXA11-AS [207]. Supplementary Table S1 presents the 179 studies with fewer than 100 breast tumor tissue specimens with or without normal breast tissue samples, in descending order of the number of specimens.
Table 1. The largest studies with non-coding RNA analyses in breast tumor specimens and/or normal breast tissue (in descending order of the number of specimens).
Table 2. Studies with non-coding RNA analyses in blood samples from breast cancer patients (in descending order of the number of blood samples).

2.3.2. Studies with Non-Coding RNA Analyses in Blood Samples from Breast Cancer Patients

Table 2 presents an overview of all studies with lncRNA analysis of blood samples from breast cancer patients. Six studies included more than 100 blood samples from breast cancer patients [49,90,147,175,177,212]. RNA was extracted from serum in 10 studies [31,36,49,64,87,90,191,220,240,248], from plasma in seven studies [28,60,147,151,153,175,212], and from whole blood in three studies [86,177,214]. The following non-coding RNAs were identified as potential diagnostic biomarkers and/or therapeutic targets in blood from breast cancer patients: HOTAIR [31,64,151,175], MALAT1 [177,191,220], rs3787016 TT [212], NEAT1 [64,87,147], MEG3 [90], DANCR [49], ROR [214], IGF2-AS [86], AP001429.1 [60], HAND2-AS1 [153], TINCR [28], PVT1 [64], and HOTTIP [36].

2.3.3. Studies Involving Clinical Samples Complemented by In Vitro and Animal Experiments

Supplementary Table S2 presents 177 studies involving clinical samples from breast cancer patients complemented by additional in vitro analyses and 75 studies that included additional animal experiments. The most commonly used additional assays were the following: Cell culture, Cell counting kit-8 (CCK-8) assay, Cell growth assay, Cell invasion assay, Cell migration assay, Cell proliferation assays, Cell transfections, Cell viability assays, Chromatin immunoprecipitation (ChIP)-assay, Colony formation assay, Dual-luciferase reporter assay, 5-Ethynyl-2′-Deoxyuridine (EdU) Assay, Flow cytometry, Fluorescence In Situ Hybridization (FISH), Immunohistochemistry (IHC), RNA immunoprecipitation (RIP) assay, RNA pull-down, Transwell Assay, Western blot, and Wound Healing. Less commonly, the following additional assays were used: Cell phenotype assays, Annexin V apoptosis assay, Boyden assay, BrdU assay, Cell cycle analysis, DNA methylation analysis, ELISA, Gene strand-specific RT-PCR, Glucose metabolism, Glycolysis stress test, Immunofluorescence, Immunoblotting, In situ Hybridization (ISH), JC-1 assay, Laser capture microdissection, Mass spectrometry, Methylation-specific PCR, Microarray analysis, mRNA stability analysis, MTT-assay, Northern blot, 5′ and 3′ rapid amplification of cDNA ends (RACE), RNA-interference, triple-primer-PCR, TUNEL assay, and RNA-RNA in vitro interaction assay. Among these 177 studies that were complemented by additional in vitro analyses and 75 studies that included animal experiments, there were only six studies that analyzed at least 100 breast tumor tissue specimens with or without normal breast tissue samples [78,88,124,161,162,218]; the following lncRNAs were identified in these six studies as potential diagnostic biomarkers and/or therapeutic targets: NORAD [78], RACGAP1P [88], HUMT [124], RHPN1-AS1 [161], LUCAT1 [162], and MALAT1 [218].

3. Discussion

In recent years, long non-coding RNA (lncRNA) analyses have been widely conducted in pre-clinical and clinical breast cancer research in the hope of identifying new diagnostic biomarkers and potential therapeutic targets. However, the large volume of published studies in this area has blurred the big picture of existing knowledge and missing evidence, and the crucial question remains as to whether lncRNA analyses can be used in routine clinical practice at present or in the near future. Therefore, based on the commonly accepted guidelines upon secondary analysis of the published literature [19,20,249], we carried out the present scoping review in order to identify the types of available evidence in this area, to clarify key concepts in the literature, to examine how research is conducted, and to identify and analyze possible knowledge gaps [249].
Following a comprehensive search of the pertinent literature, we identified and included 230 clinically relevant studies [21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248]. After data extraction, data analysis, and the synthesis of the results, we found that most studies were carried out in specimens taken from patients with primary invasive breast cancer (stages I–III), as compared with metastatic disease (stage IV) and ductal carcinoma in situ (DCIS; stage 0). Therefore, the current knowledge regarding the possible role of lncRNAs in DCIS and metastatic breast cancer appears to be limited; future studies should focus on investigating the role of lncRNAs in DCIS and metastatic disease. It is worth noting that only a small proportion of studies included more than 100 tissue specimens (Table 1 and Table 2), suggesting that the results from most studies cannot be easily generalized. Hence, taking into account this limitation, future lncRNA analyses should include larger numbers of clinical specimens from breast cancer patients. In particular, as shown in Table 1, among the included studies of lncRNA analyses, the highest numbers of breast cancer tissue specimens were 5634 [84] and 1048 [241], and the highest numbers of blood samples from breast cancer patients were 969 [175] and 487 [177]; none of these studies had any direct effect on clinical practice. For comparison, clinical studies evaluating the prognostic and/or predictive value of gene signatures in early breast cancer included analyses from 10,273 patients for the 21-gene assay OncotypeDX [250], 6600 patients for the 70-gene assay Mammaprint [251], 2558 patients for the 50-gene assay PAM50 [252] and 2185 for the 12-gene assay Endopredict [253], and all of these assays are currently routinely used in clinical practice. Therefore, the maturity in the field of lncRNA analysis in breast tumor specimens should not be overestimated.
In the present scoping review, we also found that most lncRNA analyses ofclinical specimens were carried out in breast cancer tissue, with or without normal breast tissue (n = 231; Table 1 and Supplementary Table S1), and only a small proportion were carried out in blood samples from breast cancer patients (n = 21), i.e., 10 studies involving serum, seven studies involving plasma, and four studies involving whole blood (Table 2). Interestingly, unlike other molecular analytical approaches in breast cancer research, such as the use of proteomics [254], we did not identify any study with lncRNA analyses in other biologic materials such as nipple aspiration fluid (NAF), urine, saliva, tear fluid or pleural effusions. Although blood samples are more easily accessible than normal and cancerous breast tissue specimens, and despite the fact that blood samples may be obtained more than once during the course of disease, technical issues, especially those regarding RNA isolation and stability in blood samples [255], may explain this paucity of studies involving blood as compared with studies involving tissue samples from breast cancer patients. Therefore, given the knowledge gap in this direction, future research may focus on evaluating the possible role of lncRNAs in blood samples from breast cancer patients. In particular, bearing in mind the concept of tumor dormancy, which is firmly supported by the detection of circulating tumor cells (CTCs) and tumor cells in the bone marrow of breast cancer patients years before disease recurrence [3,4,5,6] and the most recent advances on the clinical validity and repeated CTC enumeration in metastatic breast cancer [256,257], delving deeper into the role of lncRNAs in blood samples from breast cancer patients seems to be a promising new frontier for translational research. However, current knowledge in this field should not be overestimated.
In the largest study to date in breast cancer tissue, Xu et al. [84] performed a two-stage genome-wide lncRNA association study onHan Chinese women, covering 5634 breast cancer patients and 6308 healthy controls, and identified a novel breast cancer-associated lncRNA, i.e., lncHSAT164, whichis implicated in regulating the cell cycle and may be a potential therapeutic target in breast cancer. Some years earlier, in a multicenter study, Redis et al. [241] analyzed the expression of CCAT2 in a set of 30 breast cancersamples from Romania, a tissue array containing 18 tumors from the USA, and an independent set of 997 primary breast cancers from the Netherlands, and concluded that the expressionof lncCCAT2 can predict clinical outcomes for a specific subgroup of breast cancer patients. In the largest study onblood samples, Lin et al. [175] assessed the interaction between three single-nucleotide polymorphisms (SNPs) of the lncRNA HOTAIR on the risk and clinical outcome of breast cancer in a Chinese Han population that included 969 breast cancer cases and 970 healthy controls and found that two SNPs (rs1899663 and rs7958904) were significantly associated with increased risk of breast cancer. In another large study, Peng et al. [177] assessed three SNPs of the lncRNA MALAT1 in a Chinese Han population that included 487 breast cancer cases and 489 cancer-free controls and found that the genetic variants of lncRNA MALAT1, particularlyrs619586, were associated with susceptibility to breast cancer. It is noteworthy that both HOTAIR and MALAT1 have been studied in multiple studies both in breast cancer tissue and blood from breast cancer patients, i.e., HOTAIR in six studies [31,64,151,175,239,248] and MALAT1 in 13 studies [33,64,66,76,121,177,191,215,216,218,220,226,232,247]. The role of these lncRNAs should not be overestimated, as these are the most extensively investigated or evaluated in the largest clinical cohorts, rather than fully validated clinical biomarkers. Other lncRNAs for which our literature search showed were evaluated in a relatively small number of specimens—for example, the female-specific lncRNA Xist [76,190,258]—may also deserve more attention in future studies.
Our comprehensive analysis of the literature also showed that lncRNA analyses of clinical samples from breast cancer patients were complemented by additional in vitro analyses in most of these studies (i.e., 177 out of 228, or 77.6% of the included studies). Furthermore, almost one-third of these studies (i.e., 75 out of 228, or 32.9% of the included studies) also included additional animal experiments (see Supplementary Table S2). Although these additional analyses reinforce the scientific basis and the validity of analyses of clinical specimens, still, their results cannot be directly translated into clinical applications. Therefore, future research should focus on analyzing lncRNAs in clinical samples of breast cancer patients, using the evidence already acquired from basic science approaches.
From a clinical perspective, among other breast cancer molecular subtypes, triple-negative tumors (i.e., tumors negative for estrogen receptors, progesterone receptors and HER2) have the poorest prognosis and limited treatment options. Therefore, it was not surprising that numerous studies on lncRNA analyses in clinical breast cancer specimens focused on triple-negative tumors [25,32,35,41,51,52,53,55,59,61,71,72,77,79,91,94,98,103,105,107,117,124,132,147,153,158,159,176,179,180,189,206,211,215,218,224,228], so that the role of lncRNA in triple-negative breast cancer could be further evaluated in a focused systematic review. On the other hand, studies on lncRNA in the neoadjuvant setting were scarce [93,110] despite the fact that in recent years, the administration of various combinations of neoadjuvant chemotherapy to breast cancer patients has been increasingly investigated in clinical trials. Hence, future studies should focus on evaluating possible clinical applications of lncRNAs in the neoadjuvant setting.
The main strength of the present scoping review is that this is the first comprehensive analysis of the literature regarding the current role of lncRNA in breast cancer diagnosis and treatment, providing an overview of research conducted in this area. Other published reviews on this topic were narrative reviews focusing on various issues, including the role of lncRNAs in the regulation of cancer stem cells and the tumor microenvironment [13,14], the cell cycle [15], inflammation in breast cancer [16], and the possibility to be used as therapeutic targets [17,18]. Therefore, the present review may be useful in designing primary studies investigating the possible role of lncRNAs as diagnostic and prognostic biomarkers and therapeutic targets for breast cancer patients. Furthermore, another strength of this scoping review is that we focused on studies analyzing lncRNA in clinical samples, i.e., in breast cancer tissue and/or blood from breast cancer patients, and also that we excluded studies conducted only in cell lines and in silico studies. With this approach, we provide a comprehensive outline of the current clinical role of lncRNAs in breast cancer. On the other hand, the exclusion of in vitro and in silico studies may be seen as a limitation, as some of these studies may well contain clinically relevant information. Another limitation of this scoping review lies in the search terms used, i.e., “non-coding RNA” and “ncRNA”, and the limit “title”. The use of more specific terms, such as “long non-coding RNA”, “lncRNA”, and “lincRNA”, as well as extending the search scope to the “Title/Abstract” field, might have yielded more relevant studies; this should be taken into account when designing relevant structured reviews in the future. It is worth noting that most studies (77.8%) included in the present scoping review were conducted in one country, namely China; this geographic concentration may limit the reproducibility, external validity and generalizability of findings across different populations due to existence of specific genotypes and specific healthcare system characteristics in a certain geographical area. Since this is a scoping review, in-depth analysis and the discussion of broader trends and several other aspects are beyond the scope of this article, and they would rather be the subject of focused systematic reviews; such aspects includethereproducibility of findings, especially in blood compared with tissue; consistency of the available evidence; extensive presentation of the remaining knowledge gaps in the field, findings from prospective vs. retrospective and single vs. multi-center studies; pooled Hazard Ratios; pooled sensitivity/specificity; survival analyses; Receiver-Operating Characteristic (ROC) comparisons for each lncRNA; comparisons of different primers used to detect the same lncRNA across studies; additional methods used for validation of findings; independent validation across multiple cohorts;the role of lncRNAs in different breast cancer subtypes and stages, especially in triple-negative and metastatic breast cancer; and the possible clinical utility of specific lncRNAs as prognostic and/or therapeutic biomarkers.

4. Materials and Methods

The present scoping review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR) [19]; Supplementary Table S3 presents the PRISMA-ScR Checklist. The review protocol was registered in the Open Science Framework (registration DOI: 10.17605/OSF.IO/P3A).

4.1. Eligibility Criteria

The following population, concept, and context (PCC) criteria [19,20] were used: (1) Population: Patients diagnosed with breast cancer. (2) Concept: lncRNA analyses in breast cancer clinical research. (3) Context: Breast cancer and normal breast tissue, lymph nodes, serum, and/or plasma from breast cancer patients. Studies only concerningbreast cancer cell lines were not included.
The following inclusion criteria were applied: (1) Studies with lncRNA analyses of samples taken from breast cancer patients (in situ, primary and metastatic lesions, normal breast tissue, lymph nodes, serum, and plasma); (2) clinically relevant studies, with lncRNA analyses aiming at diagnostic and therapeutic target discovery and validation; (3) clinical studies. The following exclusion criteria were applied: (1) studies onmitochondrial ncRNA; (2) studies onother ncRNAs, including miRNAs and piRNAs; (3) in silico studies; (4) studies only onbreast cancer cell lines; (5) studies solely onanimal models; (6) reviews, comments, editorials, case series, case reports, and papers with specimens from fewer than 10 breast cancer patients analyzed; (7) retracted papers; and (8) papers in languages other than English.

4.2. Information Sources and Search of the Literature

This study was carried out by searching the two primary online medical databases: the PubMed/MEDLINE database (PubMed) and the EMBASE database (Scopus) for articles published until 14 April 2026. The following search terms were used in both database searches: “non-coding RNA” AND “breast cancer”, and “ncRNA” AND “breast cancer”, with the limit “title”.

4.3. Selection of Sources of Evidence

For study selection, two reviewers (PP and IG) screened independently all studies in order to cut out overlapping and duplicate studies and publications not written in English. The same two authors evaluated the titles and/or abstracts of the remaining articles based on the inclusion and exclusion criteria. Then, eligible studies were retrieved and the fulltexts were further evaluated in accordance with the inclusion and exclusion criteria. Conflicts were resolved by discussion or referral to a third reviewer (MZ), who also re-evaluated the selection of studies.

4.4. Data Charting Process, Data Items, and Synthesis of Results

Data collection was conducted independently by two authors (PP and IG) using Microsoft Excel. Conflicts were resolved by discussion or referral to a third reviewer (MZ), who also re-evaluated and confirmed collection of data. The following data were extracted from the included studies: first author; publication year; country of first author’s affiliation; clinical setting, i.e., if the possible clinical application was relevant to diagnosis or treatment; disease stage, i.e., ductal carcinoma in situ (DCIS, stage 0), primary invasive breast cancer (stages I, II and III), and metastatic breast cancer (stage IV); type of specimen analyzed, i.e., normal or tumor tissue, serum, or plasma; number of specimens analyzed; additional in vitro analyses; additional animal experiments; the primary method used in clinical samples; other methods used in clinical specimens, cell lines or animal samples; main conclusions. Extracted data were further analyzed according to clinical relevance, i.e., according to (a) the type of tissue specimen analyzed, (b) the number of specimens analyzed, and (c) the disease stage.

5. Conclusions

This is the first scoping review evaluating the current role of lncRNAs in clinically relevant breast cancer research. Our data analysis and synthesis of evidence showed that most lncRNA studies on clinical specimens were conducted in breast tumor specimens rather than blood samples from breast cancer patients. The most commonly used method was quantitative RT-PCR, and most studies were complemented by in vitro assays and almost one third by animal experiments. There were 39 studies that included at least 100 specimens from breast cancer patients, 33 studies on breast cancer tissue, and six studies on blood from breast cancer patients. A considerable number of studies focused on triple-negative breast cancer. The long non-coding RNAs HSAT164 and CCAT2 were identified in the two largest studies on breast cancer tissue and HOTAIR and MALAT1 in the two largest studies on blood, as clinically relevant. It should be noted, however, that these are not fully validated clinical biomarkers. At present, non-coding RNA analyses are not used routinely in clinical practice, but multiple studies on clinical specimens reinforced by results from in vitro and animal experiments suggest that various non-coding RNAs may be potential biomarkers for the diagnosis, disease monitoring, and treatment of breast cancer. However, since current supporting evidence comes only from observational studies supplemented by mechanistic laboratory experiments, the maturity of the field should not be overestimated.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/epigenomes10040065/s1, Figure S1: A timeline chart presenting the number of studies of lncRNA in breast cancer published each year since 2009; Figure S2: Geographical distribution of published studies regarding lncRNA in breast cancer; Table S1: Studies with lncRNA analyses in less than 100 breast tumor specimens and/or normal breast tissue (in descending order of the number of specimens); Table S2: Studies with lncRNA analyses in specimens from breast cancer patents complemented by in vitro and animal experiments; Table S3: PRISMA-ScR Checklist.

Author Contributions

Conceptualization: M.Z.; methodology: M.Z.; formal analysis and investigation M.Z., I.G. and P.P.; writing, original draft preparation: M.Z., P.P. and I.G.; writing—review and editing: M.Z., C.E. and M.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding. The APC was covered by the journal.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original data presented in the study are openly available inMedline/PubMed (https://pubmed.ncbi.nlm.nih.gov/) and EMBASE/Scopus (https://www.elsevier.com/products/scopus), accessed on 14 April 2026.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
BCBreast Cancer
CTCsCirculating tumor cells
DCISDuctal Carcinoma In Situ
lncRNALong non-coding ribonucleic acid
PRISMAPreferred Reporting Items for Systematic Reviews and Meta-analyses
qRT-PCRQuantitative Reverse Transcription Polymerase Chain Reaction
ScRScoping Review
TNBCTriple-Negative Breast Cancer

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