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Review

Latest Update on lncRNA in Epithelial Ovarian Cancer—A Scoping Review

by
Katarzyna Kwas
*,
Maria Szubert
and
Jacek Radosław Wilczyński
Department of Surgical and Oncologic Gynaecology, 1st Department of Gynaecology and Obstetrics, Medical University of Lodz, 90-136 Łódź, Poland
*
Author to whom correspondence should be addressed.
Cells 2025, 14(7), 555; https://doi.org/10.3390/cells14070555
Submission received: 10 February 2025 / Revised: 22 March 2025 / Accepted: 24 March 2025 / Published: 7 April 2025
(This article belongs to the Special Issue Genetic Disorders in Breast and Ovarian Cancer)
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Abstract

:
Long noncoding RNAs (lncRNAs) are RNA molecules exceeding 200 nucleotides that do not encode proteins yet play critical roles in regulating gene expression at multiple levels, such as chromatin modification and transcription. These molecules are significantly engaged in cancer progression, development, metastasis, and chemoresistance. However, the function of lncRNAs in epithelial ovarian cancer (EOC) has not yet been thoroughly studied. EOC remains challenging due to its complex molecular pathogenesis, characterized by genetic and epigenetic alterations. Emerging evidence suggests that lncRNAs, such as XIST, H19, NEAT1, and MALAT1, are involved in EOC by modulating gene expression and signaling pathways, influencing processes like cell proliferation, invasion, migration, and chemoresistance. Despite extensive research, the precise mechanism of acting of lncRNAs in EOC pathogenesis and treatment resistance still needs to be fully understood, highlighting the need for further studies. This review aims to provide an updated overview of the current understanding of lncRNAs in EOC, emphasizing their potential as biomarkers and therapeutic targets. We point out the gaps in the knowledge regarding lncRNAs’ influence on epithelial ovarian cancer (EOC), deliberating on new possible research areas.

1. Introduction

1.1. Long Noncoding RNA (lncRNA)—Definition, Description

LncRNAs are a diverse class of RNA regulatory molecules that are longer than 200 nucleotides and do not encode proteins. Despite their lack of coding potential, lncRNAs are known to regulate gene expression at various levels, including chromatin modification, transcription, and post-transcriptional processing. These molecules can act as scaffolds, guiding chromatin-modifying complexes to specific genomic loci, or as decoys, sequestering transcription factors and other proteins. Additionally, lncRNAs form nuclear substructures and modulate mRNA stability and translation. Emerging research suggests that lncRNAs are pivotal in numerous biological processes and diseases and may serve as future biomarkers [1].
Long noncoding RNAs (lncRNAs) can indeed act as competing endogenous RNAs (ceRNAs) by interacting with microRNAs (miRNAs) to regulate cell functions. This so-called sponging mechanism allows lncRNAs to sequester miRNAs, preventing them from binding to target mRNAs and thus modifying gene expression. MicroRNAs, small RNA molecules about 22 nucleotides long, typically bind to the 3′ untranslated regions (UTRs) of target mRNAs, either promoting mRNA degradation or inhibiting protein translation. Through this “sponging”, lncRNAs help control various cellular processes, including cell invasion, metastasis, and apoptosis. In addition to this sponge effect, lncRNAs participate in fundamental biological activities, such as genomic imprinting, X chromosome inactivation, chromatin modifications, and transcriptional regulation. Dysregulated lncRNA expression is thought to play a vital role in several diseases, including endometriosis. Studying expression patterns may uncover differentially expressed lncRNAs contributing to the disease’s pathogenesis, offering potential biomarkers or therapeutic targets. Identifying these lncRNAs provides valuable insight into the molecular mechanisms driving endometriosis and highlights their importance in disease progression and treatment development [1,2]. The main mechanisms of lncRNAs have been presented in Figure 1.
This review aims to present the latest update on lncRNA in EOC, describe the most studied lncRNA, and explain their possible place in the pathogenesis of EOC.

1.2. LncRNA—From the Discovery to the Role in Carcinogenesis

The advancement in sequencing technologies has revealed that over 80% of human DNA is transcribed into noncoding RNAs. In the early 1990s, the first lncRNAs were described, among them H19 and XIST. Since then, the amount of data on lncRNAs has been rising logarithmically. Firstly, their role was established as gene-specific regulatory molecules, and then our understanding expanded in the areas of embryogenesis and epigenetic regulation of allelic expression, such as the processes of dosage compensation and genomic imprinting. Lastly, they were proven to control pluripotency and influence lineage specification. Studies confirmed their impact on mammals’ neuronal development, various diseases, and carcinogenesis [3,4,5,6,7,8,9,10,11,12,13,14,15,16,17]. They have already been studied in many cancers, in in vitro studies on pathogenesis [9], but also on animal models, in which they affected tumor growth, immune modulation, survival, and chemoresistance, especially to platinum-based therapies [13,16,17]. There is also a lot of data on gynecological malignancies. In cervical cancer, MALAT1 has been engaged in cancer cell proliferation and migration by affecting epithelial–mesenchymal transition (EMT) and other signaling pathways [3]. MEG3 acted as tumor suppressors, inhibiting cancer cell growth and inducing apoptosis through their involvement in p53-mediated pathways [4,5].
In endometrial cancer, specific lncRNAs similarly act as oncogenes or tumor suppressors, contributing to cancer progression, invasion, and metastasis. LncRNA HOTAIR has been identified as an oncogenic factor, promoting tumor growth by altering gene expression and interacting with chromatin-modifying complexes [6]. GAS5 was found to be a tumor suppressor [7].

1.3. Epithelial Ovarian Cancer—Pathological and Molecular Background

Epithelial ovarian cancer is the third most common gynecologic neoplasm worldwide and the most prevalent form of ovarian cancer, accounting for approximately 90% of all ovarian tumors. [18,19]. The disease primarily affects postmenopausal women, with most diagnoses occurring in those aged 55 to 64. Risk factors include genetic mutations (notably BRCA1 and BRCA2), family history of ovarian or breast cancer, age, nulliparity, early menarche, late menopause, and the use of hormone replacement therapy [20]. There have been various classifications of EOC according to histopathological subtypes, cancer aggressiveness, grading, and staging. For the actual review, we would like to familiarize readers with the WHO 2020 classification, which among serous tumors presents high-grade serous and low-grade serous cancers as separate entities: mucinous, endometrioid, clear cell, and undifferentiated carcinomas. These subtypes are differentiated based on their origin, microscopic appearance and biological behavior, prognosis, and the newest molecular findings, which, with high probability, will further influence this differentiation in the future [18,21,22].
Key genetic mutations implicated in ovarian carcinogenesis include BRCA1 and BRCA2 genes, which are involved in double-stranded break DNA repair mechanisms. Mutations in these genes disrupt homologous recombination, leading to genomic instability. Additionally, TP53 mutations presented in over 96% of high-grade serous ovarian carcinomas contribute to defective cell cycle regulation and apoptosis. Oncogenic signaling pathways, such as PI3K/AKT/mTOR and RAS/RAF/MEK/ERK, are frequently dysregulated, promoting cellular proliferation, survival, and metastasis. Epigenetic modifications, including DNA methylation and histone acetylation, further influence gene expression profiles, often silencing tumor suppressor genes and activating oncogenes. The tumor microenvironment, comprising stromal cells, immune cells, and extracellular matrix components, also plays a critical role in ovarian cancer progression. For instance, interactions between cancer cells and the tumor microenvironment can facilitate angiogenesis, immune evasion, and chemoresistance [22,23,24]. Emerging evidence highlights the significance of noncoding RNAs, such as microRNAs and long noncoding RNAs (lncRNAs), in modulating gene expression and signaling pathways relevant to ovarian cancer. Understanding these molecular underpinnings is essential for developing targeted therapies and improving ovarian cancer diagnostic, prognostic, and therapeutic strategies. Current reports suggest that lncRNAs may be a potential target, as they influence the development and persistence of ovarian cancer through the modulation of inflammation, proliferation, angiogenesis, and tissue remodeling [24,25].
(a)
Endometriosis-associated ovarian cancer (EAOC)
  • EAOC consists of ovarian endometrioid carcinoma (OEC) and ovarian clear cell carcinoma (OCCC) [25]. When examining tissue remodeling, one should remember that endometriosis is a benign condition that can become cancerous, with atypical endometriosis being an intermediate stage.
  • Despite numerous reports on EAOC, the precise mechanism of malignant transformation from endometriosis to ovarian cancer remains unclear. Kok et al. stated that endometriosis increased the risk of EOC fourfold [26]. A critical factor in the pathogenesis of EAOC is the ARID1A (AT-rich interactive domain 1A) suppressor gene, which encodes the BAF250a protein. The mutation rate of ARID1A in OCCC ranges from 40% to 95%, while in OEC, it is around 30%. It is confirmed as a first step in EAOC carcinogenesis [25]. Kristen rat sarcoma virus (KRAS) is another crucial gene involved in EAOC pathogenesis, with mutations identified in 29% of EAOC cases [27].
Additionally, oxidative stress and microRNAs are commonly implicated in the pathogenesis of EAOC. Recent reports suggest that lncRNAs may also be potential targets, as they influence the development and persistence of both ovarian cancer and endometriosis through the modulation of inflammation, proliferation, angiogenesis, and tissue remodeling. However, OCCC is a relatively rare cancer, and there is limited literature on the impact of lncRNAs on its pathogenesis. A similar situation exists for OEC; studies analyzing lncRNAs in their pathogenesis are scarce, with only two studies examining lncRNAs in OCCC [27,28,29]. Therefore, there is a considerable need for further studies that focus on the lncRNA role and expressions in OCCC and OEC.
(b)
High-grade serous ovarian cancer (HGSOC)
  • HGSOC accounts for 70% of all ovarian cancers and is characterized by high-grade histology, rapid progression, poor prognosis, and high recurrence rate. Genetically, HGSOC is distinguished from low-grade EOC by frequent mutations in the TP53 gene, which are found in nearly all cases, along with other molecular alterations, such as BRCA1 and BRCA2 mutations. HGSOC is often diagnosed at an advanced stage due to its asymptomatic progression. Despite advances in surgery and chemotherapy, overall survival is still unsatisfactory. Platinum-based chemotherapy combined with paclitaxel remains the cornerstone of treatment but, unfortunately, is usually followed by chemo-resistant recurrence. However, recent advancements in targeted therapies, including PARP inhibitors and anti-angiogenic agents, like bevacizumab, have improved outcomes for some patients.
Nonetheless, the development of chemoresistance remains a significant challenge in managing HGSOC, necessitating ongoing research into novel therapeutic strategies and better biomarkers for early detection [30,31]. Analysis of lncRNA in HGSOC shows that dysregulated lncRNAs contribute to tumor development and chemoresistance. For instance, specific oncogenic lncRNAs, such as HOTAIR, have been shown to promote cancer cell invasion and metastasis by influencing epithelial–mesenchymal transition (EMT).
LncRNA MALAT1 has enhanced chemoresistance in HGSOC by interacting with these networks and promoting cell survival under stress. Moreover, some lncRNAs are associated with modulation of the tumor microenvironment, influencing immune evasion and angiogenesis, which are critical for tumor growth and dissemination. In contrast, tumor suppressor lncRNAs, like MEG3, may inhibit cell proliferation and induce apoptosis [32,33]. Due to their specificity and involvement in multiple cancer-related pathways, lncRNAs are emerging as potential biomarkers for diagnosis, prognosis, and therapeutic targets in HGSOC.

2. Material and Methods

Since medical literature is rich in thousands of lncRNAs studies and gigabytes of data in many databases, we adopted PRISMA guidelines to search for scientific data regarding lncRNAs in the development of ovarian cancer [20]. We registered a search in the PROSPERO database (number: CRD42024611928) to systematize lncRNA data and its influence on survival in ovarian cancer patients. We followed typical steps for scoping and systematic review: identifying the research question, searching for relevant studies, study selection, charting the data, summarizing, and reporting results. We searched through Pubmed, Medline, Web of Science, SCOPUS, and ScienceDirect, using questions: “lncRNA in ovarian cancer”, “lncRNA AND ovarian carcinoma”, and “lncRNA AND epithelial ovarian cancer”. Two independent reviewers screened over 800 positions in databases. After exclusions (review and case report articles, full text unavailable, inappropriate methodology, data not possible to obtain, articles published before 1 January 2020), the last search was performed on 30 July 2024, and over 300 manuscripts were qualified for analysis. Figure 2 shows the results of the search according to the PRISMA 2020 guidelines [30]. According to the scoping nature of the review, no statistical tests were applied at this point of the analysis.

3. Results

We present a scoping review of the most important findings to give readers a broad overview of the available literature on a topic, identifying known evidence and gaps in knowledge. Summarizing the literature, Table 1 (downregulated lncRNAs) and Table 2 (upregulated lncRNAs) present the latest updates on lncRNAs and their functions in ovarian cancer. The lncRNAs are divided into two groups based on their expression levels in ovarian cancer, with a larger group of upregulated lncRNAs.
Presented lncRNAs are involved in many vital processes: cell cycle regulation, invasion, proliferation, migration, and apoptosis, and they promote epithelial-to-mesenchymal transition and resistance to chemotherapy. High expression levels of some lncRNAs are correlated with clinicopathological features such as tumor stage, FIGO classification, poor prognosis, and overall survival rate [79,89,119,147,152,240].
Among the upregulated lncRNAs, two major families are mostly presented: SNHG and LINC. The LINC family is the most prominent and widely studied, primarily involved in cancer cell migration, invasion, and proliferation, while inhibiting apoptosis through miRNA-mediated mechanisms, such as the miR-134-5p/TRIM44 and miRNA-4315p/SOX9 pathways [171,183]. Similarly, the SNHG family of lncRNAs (small nucleolar RNA host gene) regulates the cell cycle and targets various miRNAs like miR-139-5p and miR-98-5p, influencing oncoproteins. Notably, some SNHG members have specific roles in chemotherapeutic resistance, with SNHG7 regulating resistance to paclitaxel (PTX) and SNHG12 affecting sensitivity to carboplatin (CBDCA) [259,272,274].
The downregulated lncRNA group is smaller than the upregulated group. Decreased expression of these lncRNAs in ovarian cancer promotes cell cycle functions and, in some cases, contributes to chemotherapeutic resistance. They are also associated with the FIGO stage and histological type [35,36,58,77]. These downregulated lncRNAs target specific oncoproteins, such as PTEN and c-Myc, influencing cancer initiation and progression by regulating molecular pathways like PI3K/AKT/mTOR and Wnt/β-catenin.

4. Discussion

Analysis of particular groups of ovarian cancer showed scarcity in the literature regarding both HGSOC and EAOC cancers. Searching databases, we found not only well-conducted studies but also studies without a clear pathological description of ovarian cancer samples, which makes drawing conclusions about the appropriate type of ovarian cancer impossible. Nevertheless, some key findings regarding many lncRNAs are worth testing in in vivo studies or populations of different origins of ovarian cancer. Yuan et al. stated that upregulated NEAT1 influences cancer cell proliferation and angiogenesis by sponging miR-365 [215]. NEAT1’s role has also been confirmed by Liu et al. and proposed as a therapeutic target [213]. UCA1 has been determined to interact with the miR-654-5p/SIK2 axis and affect proliferation, migration, and invasion [293]; LINC01094 by sponging miR-577 has been stated to promote lymph node metastasis, cell proliferation, migration, invasion, and EMT [181]. Similar outcomes have been observed in the analysis of THOR, LINC01605, HCP5, and other lncRNAs presented in Table 1 and Table 2 [133,188,280]. Several lncRNAs have been suggested to impact the chemoresistance in HGSOC; upregulated HULC, RMRP, SNHG7, and UCA1 were shown to influence the PTX-resistance, SNHG12 was determined to affect the carboplatin (CBDCA) sensitivity, whereas CASC10, PLADE were described to promote cisplatin (CDDP) sensitivity [153,253,259,271,292].
Evaluation of lncRNAs in EAOC also showed a deficit in the literature since not many studies included data concerning these specific types of ovarian cancer. Upregulated DLX6-AS1 has been found to promote cancer cell proliferation, migration, and invasion by impairing apoptosis. Wu et al. suggested that PVT1 miR-148a/AGO1 interactions affected survival rate, metastasis, cell viability, and proliferation and correlated with the FIGO stage [110,240]. Similar results were obtained in the analysis of the NEAT1, XIST, GAS5, LINC01094, SNHG7, and many other lncRNAs, as presented in Table 1 and Table 2. Unfortunately, the influence of lncRNAs on chemoresistance in EAOC has not been yet studied.
Since we aimed to provide readers with the most up-to-date data, we discuss below the lncRNAs that have been studied most frequently and are the most promising factors for future analysis.
The six most extensively studied lncRNAs in ovarian cancer.

4.1. XIST

The X inactivation-specific transcript (XIST) is the first long noncoding RNA (lncRNA) identified to play a role in the X chromosome inactivation. This lncRNA is dysregulated in various cancers, including liver, cervical, non-small cell lung, glioma, pancreatic, and breast cancers. The study by Jiang et al. demonstrated that lncRNA XIST is significantly upregulated in ovarian cancer (OC) tissues [301]. High expression of XIST was associated with poor prognosis of the patients. Moreover, Jiang et al. determined a negative relationship between XIST and miR-149-3p. Inhibition of XIST or promotion of miR-149-3p suppressed the proliferation, invasion, migration, and colony formation ability, thereby promoting apoptosis in vitro and limiting tumor growth in vivo [303]. Similar results were presented by Zuo et al., who stated that there was a significantly higher expression of XIST in EOC than in healthy ovarian epithelial tissue. Moreover, Zou et al. also studied the medical history of the patients. As stated, the expression of XIST was correlated with the tumor grade (p = 0.019), distant metastases (p = 0.021), and FIGO staging (p = 0.010). In further steps, the XIST expression was knocked down, and invasion and migration and the wound-healing ability of the EOC cells were determined to be reduced [304]. In the work of Xia et al., XIST expression and its association with miR-506-3p and FOXP1 in terms of (CBDCA) resistance in EOC were analyzed. XIST was upregulated in the EOC tissues, whereas miR-506-3p was downregulated. This overexpression of XIST was responsible for reduced apoptosis, and the result of XIST knockdown showed decreased cell autophagy, increased apoptosis, and resistance to CBDCA in EOC cells [298]. Finally, XIST was stated to positively regulate the FOXP1 expression sponging miR-506-3p, which showed the influence of this pathway on CBDCA resistance [305]. Interesting results were proposed by Wang et al., XIST was not only overexpressed in EOC, but its upregulation caused a significant increase in chemosensitivity. XIST was also associated with downregulated hsa-miR-214-3p. Moreover, the upregulation of hsa-miR-214-3p adversely regulated the anticancer effects of XIST overexpression in EOC [305]. According to Meng et al., XIST is involved in the regulation of tumor cell proliferation, invasion, and migration. Silencing XIST inhibits EOC cells’ proliferation, invasion, and migration by modulating the miR-335/BCL2L2 pathway [299]. Huang et al. identified XIST as a marker of chemotherapy response in ovarian cancer [300]. (Figure 3) Based on these data, a study on XIST expression as a blood marker in the population during chemotherapy could dispel doubts on its role as a prognostic factor for chemoresistance.

4.2. H19

H19 expression was upregulated in most patients with breast cancer; what is more, H19 was described to be associated with paclitaxel (PTX) and tamoxifen resistance in breast cancer. On the other hand, the low expression of H19 was linked with resistance to EFGR tyrosine kinase inhibitors in non-small cell lung cancer treatment [305]. Xu et al. showed that H19 is responsible for multiple cellular processes in EOC. H19 was used to sponge the miR-140-5p, activating the PI3K/AKT signal pathway and inducing proliferation, invasion, migration, and epithelial–mesenchymal transition (EMT) in OC. However, the H19 was overexpressed, whereas miR-140-5p tended to have lower expression in OC cells. Furthermore, based on the ROC analysis, Xu et al. also suggested that H19 and miR-140-5p may potentially be effective markers for the diagnosis of OC; H19 diagnostic sensitivity was 72.73%, and specificity equaled 96.67% (p < 0.05). The results for miR-140-5p were 75.76 and 76.67%, respectively (p < 0.001) [128]. The study of Wang et al. presented comparable results, where H19 was highly expressed in ovarian cancer tissues; this overexpression of H19 was correlated with a poor prognosis of OC. Moreover, H19 acted as ceRNA to miR-140, upregulated the Wnt1 expression, and promoted the proliferation and migration of OC [127]. Li et al. stated the H19 role in EMT since, as described, H19 promotes the induction of TGF-B1 to EMT by acting as competing endogenous RNA for miR-370-3p in ovarian cancer cells [306]. Besides the H19 participation in many cellular processes, researchers also speculated on its role in CBDCA chemoresistance. The study of Tian et al. targeted assessing the chemoresistance to CBDCA in EOC. As indicated, H19 levels were significantly higher in EOC than in healthy ovarian tissue. Analysis of the chemoresistance determined that silencing CBDCA H19 in resistant EOC cells can impact carboplatin sensitivity. Therefore, H19 was stated to sponge the miR-29b-3p and target STAT3 (signal transducer and activator of transcription) [126]. Wu et al. made comparable conclusions, which indicated that the overexpression of H19 was strongly associated with resistance to cisplatin (CDDP) chemotherapy in OC. Similarly, the low expression of lncRNA H19 improved cisplatin sensitivity. Moreover, the overexpression of H19 was found to cause the increased migration and EMT activity of OC cells [307]. Unfortunately, despite the mentioned research, the literature is still insufficient to explain H19 in EOC; therefore, further studies are needed. The molecular mechanisms of H19 were presented in the Figure 4.

4.3. NEAT1

Another well-known lncRNA in the pathogenesis of ovarian cancer is nuclear paraspeckle assembly transcript 1 (NEAT1). Specifically in ovarian cancer, NEAT1 has been shown to interact with biological macromolecules, including chromatin, protein, and RNA, suggesting its potential involvement in regulating gene expression and cellular processes. The work of Xu et al. focused on the oncogenic role of the upregulated NEAT1 in ovarian cancer pathogenesis. Its knockdown significantly inhibited cell proliferation, invasion, and migration compared to the healthy ovarian tissue. Furthermore, a negative correlation was stated between the miR-4500 and NEAT1 expressions; this relationship influenced multiple cell functions, including cell proliferation, apoptosis, formation, glycolysis, etc. This study also described the BZW1 (basic leucine zipper and W2 domain-containing protein 1) as directly targeted by miR-4500 [216].
The regulatory effects of NEAT1 in human epithelial ovarian tissue were modulated via the miR-4500/BZW1 axis [216]. Similar results were obtained by Liu et al., who confirmed the high expression of NEAT1 in EOC and its contribution to its pathogenesis. In this study, researchers determined the association and regulation of miR-214-3p expression, identifying it as a target for NEAT1 sponging. Moreover, NEAT1 expression was responsible for enhanced cell proliferation, migration, invasion, angiogenesis, and reduced apoptosis in EOC tissues [212]. Chen et al. described the NEAT1 in ovarian cancer prognosis prediction. The upregulated NEAT1 was correlated with the FIGO staging, grade, and metastasis (p = 0.000); however, no association between the NEAT1 expression and tumor size was stated. Patients with higher expressions of NEAT1 had a statistically shorter overall survival rate than those with lower expressions. Finally, the multivariate analysis also determined that NEAT1 is a risk factor for the overall survival rate in patients with ovarian cancer [308]. Interesting findings were published by An et al., who studied the NEAT1 in paclitaxel (PTX) resistance. The significant upregulation of NEAT1 and downregulation of miR-194 was stated in patients resistant to PTX therapy. Moreover, NEAT1 was found to regulate the miR-194 expression negatively; thereby, the knockdown of NEAT1 caused the improvement of PTX sensitivity in patients resistant to such therapy and in ovarian cancer in vivo [309]. Similar results were proposed by Lou et al. [218]. Here, it is essential to underline the importance of the study of Yin at al., who used ovarian cancer tissues and ovarian cancer cell lines of different origins [217]. The summary of NEAT1 molecular features was proposed in the Figure 5.

4.4. MALAT1

Metastasis-associated lung adenocarcinoma transcript 1(MALAT1) has been broadly studied in various types of cancer, including ovarian cancer. MALAT1 is crucial in regulating gene expression and cellular processes, such as cell proliferation, migration, and invasion. According to multiple authors, MALAT1 functions as a ceRNA to regulate the expression of target genes by sponging and sequestering miRNAs [310,311]. Its function in ovarian cancer was broadly described by researchers who confirmed that MALAT1 facilitates epithelial ovarian cancer progression by cell proliferation, invasiveness, or migration. The work of Pei et al. showed that upregulated MALAT1 promotes cell proliferation, migration, and invasion in epithelial ovarian cancer cells by acting as a sponge for downregulated miR-22. MALAT1 also increased the EMT of EOC acting through the miR-ss/c-myc axis. Finally, the inhibition of MALAT1 caused the decline in vivo of EOC growth and its metastasis [201].
Similar results were supported by Wu et al., who analyzed MALAT1 also in terms of clinicopathological characteristics, as it was reported that high MALAT1 expression was associated with advanced histological grade (G3, p < 0.001), higher FIGO stages (III-IV, p = 0.001), as well as the presence of lymph node metastases (p < 0.0001). Further analysis showed that the exogenous knockdown of MALAT1 inhibited the proliferation and migration of EOC, inducing apoptosis in EOC in vitro [310]. Likewise, Qiu et al. determined the high correlation between the serum exosomal, MALAT1 levels in EOC, and clinicopathological variables such as FIGO stage (p < 0.001) or lymph node metastases (p = 0.0020). Moreover, upregulated MALAT1 was determined to promote and regulate the angiogenesis in EOC [311]. Interesting results were published by Sun et al., who supported the idea that MALAT1 regulates EOC proliferation. In this study, upregulated MALAT1 correlated negatively, acting as ceRNA for miR-503-5p. Its knockdown resulted in an increased cell apoptosis inhibition as well as the inhibition of the JAK2/STAT3 signal pathway [59]. According to Mao et al., higher MALAT1 expression contributed to the resistance of PTX and CDDP in vitro. Overexpressed MALAT1 caused a significant increase in IL-1β, p-P38/p-NFκB/Cox2/PGE2 enhancing the inflammatory response. Increased levels of Bcl-2 and declined Caspase 3 levels were responsible for inhibiting cell apoptosis. In contrast, increased ZEB2, YAP, and vimentin with parallelly downregulated E-cadherin caused the amplification of EMT in EOC cells. This study also described that overexpression of MALAT1 in ovarian cancer-associated fibroblasts (CAFs) enhances the invasiveness of the cells [200]. In Figure 6, we summarized the MALAT1 molecular mechanisms.

4.5. UCA1

The urothelial carcinoma associated 1 (UCA1) has been extensively studied in EOC, based on previous findings in various cancers, particularly urothelial carcinoma. Discovered as a tumor-associated RNA, UCA1 is overexpressed in several malignancies, contributing to tumor growth, metastasis, and chemoresistance. According to Qiu et al., the UCA1 expression was significantly higher in patients with EOC than in healthy ones. The upregulated UCA1 correlated with the FIGO stage (p = 0.005), histological grading (p = 0.000), peritoneal effusion (p = 0.00), as well as lymphatic metastases (p = 0.000), meaning that UCA1 may be involved in proliferation and invasion of ovarian cancer [312]. Furthermore, the expression of UCA1 was analyzed on epithelial ovarian cancer cell lines and epithelial cells from malignant ovarian cancer ascites; the results were comparable. Numerous studies investigated the UCA1 role in chemoresistance and chemotherapy in EOC cells. Li et al. described the upregulation of UCA1 in ovarian cancer cells and PTX resistance. Its knockdown caused the inhibition of PTX-resistant cell migration, invasion, and proliferation, suggesting the active role of UCA1 in regulating the PTX resistance in EOC cells. Furthermore, UCA1 expression was negatively correlated with the miR-654-5p in OC and PTX-resistant OC cells, indicating that UCA1 acts as a ceRNA for miR-654-5p. The authors concluded that UCA1 sponging the miR-654-5p also influenced the SIK2 protein expression, finally determining UCA1 in PTX resistance in EOC cells [293]. On the other hand, Wambecke et al.’s research determined that downregulation of the short isoform of UCA1 sensitized EOC cells to cisplatin by sponging miR-27a-5p, downregulating UBE2N, and regulating BIM protein expression, thereby increasing the sensitivity of cancer cells [292].
Similar results were proposed by Wang et al., and upregulated UCA1 was described to improve cell migration, invasion, and CDDP resistance. Moreover, SRPK1 kinase involvement in the effect of UCA1 was assessed, showing that inhibition of that kinase partially decreased the expression of UCA1 effect on EOC cells [313]. Another study showing the UCA1 role in CDDP resistance was presented by Li et al. In this study, researchers determined the subsequent pathway of the UCA1 mechanism, confirming the preceding results proposed by others. The upregulated UCA1 in EOC patients acts as ceRNA for miR-143 and targets FOSL2. The authors suggested that the UCA1/miR-143/FOSL2 pathway modulates the CDDP resistance and may be a potential therapeutic target for CDDP resistance in EOC patients [314]. The molecular mechanisms of UCA1 were summarized in Figure 7.

4.6. HOTAIR

Another crucial lncRNA, broadly described in the literature, is the HOT antisense intergenic RNA (HOTAIR). This lncRNA was found to be highly upregulated in epithelial ovarian cancer tissues and cell lines, regulating various functions regarding tumor growth and chemoresistance, according to the work of Qiu et al. HOTAIR is significantly upregulated in EOC, and its expression is strongly associated with clinicopathological features, including histological grade (p = 0.009), FIGO stage (p < 0.001), and lymph node metastasis (p < 0.001). Furthermore, HOTAIR silencing inhibited migration, invasion in EOC in vitro, and metastasis in vivo. The knockdown decreased the expressions of MMP3, MMP9, vimentin, and SNAIL and increased E-cadherin, thereby suggesting the regulatory role of HOTAIR in EMT [315]. Zhou et al. also showed that HOTAIR was significantly expressed in EOC cells. On the other hand, downregulation of HOTAIR inhibited the TGF- β1 and ZEB1 expression, increasing the E-cadherin expression, thereby declining the EOC cells’ cell migration, invasion, and tumorigenic capability [138]. Significant results were presented by Jiang et al., who focused on PTX resistance in EOC; highly expressed HOTAIR was strongly associated with poor survival rate (HR 1.28 [1–1.65], p = 0.054) and significantly associated with PTX resistance. Knockdown of HOTAIR caused cell cycle arrest in phase G2/M, restoration of PTX sensitivity, and inhibition of ovarian cancer cell proliferation. Finally, HOTAIR was stated to regulate the checkpoint kinase (CHEK1), which could reinstate the PTX sensitivity [139]. A similar conclusion was made by Wang et al., who analyzed HOTAIR in terms of CDDP resistance. A significantly greater expression level in EOC cells resistant to CDDP than in nonresistant cells was stated. Moreover, the knockdown of HOTAIR inhibited cell migration and invasion and reestablished CDDP sensitivity in CDDP-resistant cells [316]. Other studies also found an association between HOTAIR expression and poor prognosis [316,317,318]. The molecular mechanism of HOTAIR was proposed in the Figure 8.

Major Concerns

Since lncRNAs do not encode proteins, their function and acting would be easy to establish. Also, their genomic context and attempts to classify them according to genetic location do not provide breaking information about their activity or evolutionary origin. Several of the above-mentioned lnRNAs have an increasing body of evidence from in vivo studies, but most lncRNAs await further verification. This verification from in vivo settings is of key importance if we consider implementing lncRNA into practice. First, Domcke et al. and then Croft et al. pointed out that a genomic comparison between cell lines and primary samples sometimes fails to recapitulate the primary disease subtype, especially when the microenvironment of the tumor, immune components, and microvessels are considered [319,320]. Among those provided in Table 2, 28 downregulated lncRNA have been found to influence chemoresistance to one or more chemotherapeutics. Six upregulated lncRNA have been described to either sensitize or cause resistance in in vitro studies. The following conclusion can be drawn: besides the appropriate in vitro cancerous models mirroring each type of ovarian cancer, the lncRNAs should be studied in groups potentially targeting one clinical question. These groups can be established with the help of AI tools, advanced screening of genomic databases, and different programs facilitating lncRNAs’ connection tracing.

5. Future Perspectives and Clinical Utility

LncRNAs are becoming promising therapeutic targets due to their high specificity in different cancer types and ability to regulate oncogenes and tumor suppressors. Advances in lncRNA-based therapeutics include the development of antisense oligonucleotides (ASOs), small interfering RNAs (siRNAs), and CRISPR-based systems aimed at silencing oncogenic lncRNAs or restoring the function of tumor-suppressive lncRNAs. Additionally, lncRNAs are being explored as biomarkers for early cancer detection and prognosis, offering a more precise approach to personalizing treatment.
In prostate cancer, lncRNAs such as SChLAP1, lncRNA-p21, and PCA3 have demonstrated clinical utility. PCA3 has been linked to the survival of prostate tumor cells by influencing the androgen receptor signaling pathway. It also plays a role in regulating the EMT by modulation of key targets like E-cadherin and TWIST. Additionally, PCA3 is incorporated into the PROGENSA gene signature, which helps to identify patients who, despite a previous negative biopsy, may require a second one. PCA3 has been FDA-approved for reducing unnecessary biopsies. Moreover, the integration of lncRNAs with other molecular markers enhances diagnostic accuracy, as seen with the Mi Prostate Score test, which combines PCA3, PSA, and TMPRSS2-ERG detection, achieving high sensitivity [321].
LncRNA-based biomarkers in breast cancer remain underexplored. Studies indicate their potential in patient stratification based on hormone receptor expression, with promising lncRNAs like NEAT1, DSCAM-AS1, and GATA3-AS1.
The stability of lncRNAs in biological fluids (e.g., blood, urine, saliva) positions them as valuable prospects for non-invasive cancer diagnostics. Several lncRNAs, including HOTAIR, H19, and MALAT1, have been successfully detected in liquid biopsies for breast cancer, supporting their potential as circulating biomarkers. Advanced molecular techniques, such as ISH-RNA and spatial transcriptomics, have further enhanced the sensitivity and specificity of lncRNA detection. Additionally, the integration of machine learning and molecular imaging methodologies may refine oncological diagnostics and personalized treatment strategies [321]. However, further research and clinical validation are required to establish lncRNAs as routine biomarkers for cancer management.

6. Conclusions

Long noncoding RNAs are emerging as crucial therapeutic targets in ovarian cancer due to their regulatory roles in tumor growth, metastasis, and treatment resistance. These RNA molecules influence key oncogenic pathways such as MAPK signaling, EMT, and vasculogenic mimicry, making them potential candidates for precision medicine.
As the molecular functions of lncRNAs become better understood, integrating them into existing therapies, such as combining lncRNA-targeting agents with immune checkpoint inhibitors or chemotherapy, could enhance treatment efficacy. Ongoing research into improving lncRNA therapeutics’ stability and targeting mechanisms could lead to groundbreaking treatments, transforming cancer therapy into a more targeted, less toxic approach shortly. Moreover, lncRNAs could serve as predictive biomarkers, helping tailor the chemotherapy regimens based on the lncRNA profiles of individual tumors and leading to more personalized treatment approaches. As research advances, combining lncRNA-targeting therapies with conventional chemotherapy or novel agents, like PARP inhibitors or immune checkpoint inhibitors, could offer synergistic effects, overcoming resistance and enhancing patient outcomes. Taking it all together, further research is needed to thoroughly analyze lncRNAs mechanisms in the context of potential markers and therapeutic targets in all types of ovarian cancer.

Author Contributions

Conceptualization, J.R.W. and M.S.; methodology, K.K.; investigation, K.K., M.S. and J.R.W.; writing—original draft preparation, K.K.; writing—review and editing, M.S. and J.R.W.; visualization, K.K. and M.S.; supervision, J.R.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data supporting the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Regulatory mechanisms of lncRNA. (A). Guide lncRNA; (B)—scaffold lncRNA to promote RNP complexes; (C)—lncRNAs bind directly to protein molecules, impairing their functions; (D)—lncRNAs can act as ceRNAs (sponge), reducing effect upon the target mRNA, thereby regulating gene expression; (E)—lncRNA as miRNA precursor—some lncRNAs can act as precursors of miRNAs and modulate their activity; (F)—chromatin looping—lncRNAs serve as bridges to drive inter- or intra-chromosomal interactions.
Figure 1. Regulatory mechanisms of lncRNA. (A). Guide lncRNA; (B)—scaffold lncRNA to promote RNP complexes; (C)—lncRNAs bind directly to protein molecules, impairing their functions; (D)—lncRNAs can act as ceRNAs (sponge), reducing effect upon the target mRNA, thereby regulating gene expression; (E)—lncRNA as miRNA precursor—some lncRNAs can act as precursors of miRNAs and modulate their activity; (F)—chromatin looping—lncRNAs serve as bridges to drive inter- or intra-chromosomal interactions.
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Figure 2. PRISMA flow diagram showing the research results from the study.
Figure 2. PRISMA flow diagram showing the research results from the study.
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Figure 3. Summarizing of possible impact of XIST downregulated (red) and upregulated (green) in ovarian cancer in vitro studies.
Figure 3. Summarizing of possible impact of XIST downregulated (red) and upregulated (green) in ovarian cancer in vitro studies.
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Figure 4. Possible mechanisms of action of upregulated H19 (red) and downregulated (green). Detailed description and abbreviations in text.
Figure 4. Possible mechanisms of action of upregulated H19 (red) and downregulated (green). Detailed description and abbreviations in text.
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Figure 5. Summary of NEAT1 molecular mechanisms and features.
Figure 5. Summary of NEAT1 molecular mechanisms and features.
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Figure 6. Summary of MALAT1 molecular mechanisms and clinical correlations.
Figure 6. Summary of MALAT1 molecular mechanisms and clinical correlations.
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Figure 7. Summary of UCA1 molecular mechanisms and clinical features.
Figure 7. Summary of UCA1 molecular mechanisms and clinical features.
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Figure 8. Mechanisms of action of downregulation of HOTAIR (red) and upregulation (green).
Figure 8. Mechanisms of action of downregulation of HOTAIR (red) and upregulation (green).
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Table 1. Downregulated lncRNAs in epithelial ovarian cancer. (+) increased, (−) decreased, ECM—extracellular matrix, EMT—epithelial–mesenchymal transition, PTX—paclitaxel, CDDP—cisplatin. All the studies included in the table were published after 2020.
Table 1. Downregulated lncRNAs in epithelial ovarian cancer. (+) increased, (−) decreased, ECM—extracellular matrix, EMT—epithelial–mesenchymal transition, PTX—paclitaxel, CDDP—cisplatin. All the studies included in the table were published after 2020.
Type of
Ovarian
Cancer		LncRNATargetFunctionsReference
EOCAOC4P FIGO stage, migration, invasion (+)Lin et al. [33]
EOCASMTL-AS1miR-1228-3pFIGO stage, ascites cytology, lymph node (+) proliferation, migration,
invasion (−)		Xu et al. [34]
EOCCTBP1-AS2miR-216a/PTENpoor survival (+)Cui et al. [35]
EOCEPB41L4A-AS2miR-103acell proliferation, migration, invasion (+)Sun et al. [36]
EOCFAM225BDDX17/PDIA4progression, migration, invasion,
apoptosis (+)		Yao et al. [37]
EOC HGSOCFGD5-AS1miR-107/RBBP6proliferation, angiogenesis (+)Zhang et al. [38]
EOC OCCCGAS5miR-96-5p/PTENproliferation,
invasion		Dong et al. [39]
miR-23a/WT1migration, proliferation, poor prognosis (+) apoptosis (−)Zhou et al. [40]
miR-31-5p/ARID1Aviability, invasion (+)Zhang et al. [41]
PI3K/AKT/mTOR pathway, hnRNPKlow survival, migration, invasion,
proliferation (+) apoptosis (−)
EOCGAS8-AS1 viability, migration, invasion (−)Fang et al. [42]
EOC, HGSOCHAND2-AS1 viability, migration (−)Gokulnath et al. [43]
miR106a/PTENCDDP-resistance (−)Li et al. [44]
EOCHCG11miR-1270/PTEN; AKT/mTOR pathwayproliferation, migration, EMT (−)Chen et al. [45]
EOCHOTAIRM1miR-106a-5p, ARHGAP24proliferation, invasion (+) apoptosis (−)Chao et al. [46]
EOCLEMD1-AS1 OS, FIGO stage (−)Yang et al. [47]
miR-183-5p/TP53proliferation, migration, invasion (+)Guo et al. [48]
EOCLIFR-AS1 tumor size, grade, metastasis, poor prognosis (+)Liu et al. [49]
EOCLINC-PINTmiR-374a-5papoptosis (−) proliferation, migration,
invasion, EMT (+)		Hao et al. [50]
EOC, HGSOCLINC00629LINC00629/c-Mycproliferation, poor survival (+)Liu et al. [51]
EOCLINC00936miR-221-3pproliferation, migration, invasion,
angiogenesis		Shu et al. [52]
EOCLINC01296miR-29c-3pproliferation, invasion and migration (+)Xu et al. [53]
EOCLINC01508Hippo/YAPCDDP-resistance (+)Xiao et al. [54]
EOCLINC01554 FIGO stage, metastasis (+)Luo et al. [55]
EOC HGSOCMAGI2-AS3miR-525-5p/MXD1cell proliferation, cell cycle, migration, invasion (+)Chang et al. [56]
EOCMALAT1miR-503-5pproliferation (+) apoptosis (−)Sun et al. [57]
HGSOC
EOC		MEG3PTENmigration, invasion, growth, proliferation, spheroid growth in ECM (+)Butarelli et al. [31]
miR-30e-3p, LAMA4angiogenesis (+)Liu et al. [58]
miR-376a/RASA1proliferation (+) apoptosis (−)Li et al. [59]
EOCMIR503HG proliferation, invasion (+)
apoptosis (−)		Tian et al. [60]
EOCMSC-AS1miR-425-5pproliferation (+) apoptosis (−)Zhao et al. [61]
EOCNPBWR1-2 viability, proliferation, migration,
invasion (+) apoptosis (−)		Liu et al. [62]
EOCPAXIP1-AS1 tumor grade, invasion,Chen et al. [63]
immune infiltration (+)
EOCPITPNA-AS1miR-223-3p/RHOBapoptosis (−)Zhang et al. [64]
migration, proliferation, EMT (+)
HGSOCPLADEHNRNPDproliferation, migration, invasion (−)Liu et al. [65]
CDDP sensitivity, apoptosis (+)
EOCRFPL1S-202IFN/STAT1CDDP, PTX cytotoxicity (+) proliferation, invasion, migration (−)Liu et al. [66]
EOCRP11-499E18.1PAK2-SOX2proliferation, migration, EMT (+)Yang et al. [67]
EOCSDCBP2-AS1miR-100-5p, EPDR1viability, migration, invasion (+)
apoptosis (−)		Liu et al. [68]
EOCSLC25A21-AS1KCNK4, EZH2sensitivity to PTX, CDDP (+) proliferation, invasion, migration (−)Huang et al. [69]
PTBP3proliferation, metastasis (+)Li et al. [70]
EOCSNHG10miR-200a-3p/BIN1proliferation, colony formation,
migration, invasion (−)		Lv et al. [71]
EOCSNHG5miR-23aPTX sensitivity (+)Lin et al. [72]
EOCSNHG9miR-214-5pFIGO stage, metastasis, migration, proliferation, invasion (+)Chen et al. [73]
EOCTTN-AS1miR-15b-5p/FBXW7proliferation (+) apoptosis (−)Miao et al. [74]
EOCTUSC7miR-616-5p/GSK3βpoor prognosis, proliferation, invasion,
migration (+)		Zhu et al. [75]
Table 2. Upregulated lncRNAs in epithelial ovarian cancer. (+) increased, (−) decreased, EMT—epithelial–mesenchymal transition, PTX—paclitaxel, DTX—docetaxel, CDPP—cisplatin, CBDCA—carboplatin. All the studies included in the table were published after 2020.
Table 2. Upregulated lncRNAs in epithelial ovarian cancer. (+) increased, (−) decreased, EMT—epithelial–mesenchymal transition, PTX—paclitaxel, DTX—docetaxel, CDPP—cisplatin, CBDCA—carboplatin. All the studies included in the table were published after 2020.
Type of
Ovarian Cancer		LncRNATargetFunctionReference
EOCAC005224.4miR-140-3p/SNAI2proliferation, migration, invasion, EMT (+)Xiong et al. [76]
EOCACTA2-AS1miR-378a-3p/Wnt5aCDDP-resistanceLin et al. [77]
miR-532-5p, CXCL2proliferation and invasion (+) apoptosis (−)Li et al. [78]
EOCADAMTS9-AS1miR-587/SLC7A11ferroptosis (+)Cai et al. [79]
EOCAFAP1-AS1 FIGO stage, tumor size, proliferation,
metastasis		Zhou et al. [80]
miR-107/PDK4migration, invasion (+)Liu et al. [81]
EOCARAP1-AS1miR-4735-3p/PLAGL2proliferation, migration, invasion (+)Li et al. [82]
EOCASAP1IT1miR-2278/LATS2proliferation (+) apoptosis (−)Wang et al. [83]
EOCASB16-AS1miR-3918proliferation, migration, invasion (+)
apoptosis (−)		Fan et al. [84]
EOCATBmiR-204-3pproliferation, invasion, migration (+)
apoptosis (−)		Yuan et al. [85]
EZH2proliferation, invasion, migration (+)Chen et al. [86]
miR-204-3p/TGFβR2viability, angiogenesis, migration (+)Yuan et al. [87]
EOCBBOX1-AS1miR-361-3p/PODXLproliferation (+) apoptosis (−)Yao et al. [88]
EOCBC041954miR-197-3p; miR-23b-3p; miR-149-3pl;FIGO stage, metastasis (+)Lu et al. [89]
miR-193a
EOCBLACAT1miRNA-519d-3pproliferation, migration, and invasion (+)Yang et al. [90]
EOCCACNA1G-AS1FTH1-IGF2BP1ferroptosis/ferritinophagy (−)Jin et al. [91]
proliferation, migration (+)
EOC HGSOCCASC10 apoptosis, proliferation, invasion (−)Noriega-Rivera et al. [92]
CDDP sensitivity (+)
EOC
OCCC		CASC15miR-23b-3p/miR-24-3p; TGF-β/SMAD3OS (−) migratiOn, invasion, EMT (+)Lin et al. [93]
EOCCCAT1miR-454/survivinCDDP-resistance (−)Wang et al. [94]
EOCCCNG1miR-488-3pproliferation, migration, invasion (+)Sun et al. [95]
EOCCDKN2A-AS1SOSTDC1proliferation, migration, invasion (+)Zhao et al. [96]
miR-143-3p/SMAD3proliferation, invasion, migration (+)
apoptosis (−)		Xu et al. [97]
EOCCDKN2BASGAS6proliferation, migration (+)Wang et al. [98]
EOCCRNDEmiR-423-5p/FSCN1proliferation, invasion, migration (+)Wang et al. [99]
SRSF1/TIA1CDDP-resistance (+)Wu et al. [100]
HGSOCCTBP1-DTmiR-188-5p/MAP3K3proliferation, migration, invasion (+)Liu et al. [101]
EOCDDUP Ren et al. [102]
EOCCTD-2288O8EGFR/AKTCDDP-resistance, viability, proliferation, invasion (+)Liu et al. [103]
EOCCTSLP8PKM2/c-Mycproliferation, CDDP-resistance, glycolysisLi et al. [104]
miR-199a-5p, CTSL1autophagy, EMT (+)Wang et al. [105]
EOCDANCRmiR-214viability, migration, and invasion (+)Huang et al. [106]
EOCDARS-AS1miR-194-5p/RBX1proliferation, migration, apoptosis (+)Zhou et al. [107]
EOCDATOC-1miR-7proliferation, invasion (+)Qin et al. [108]
EOCDLEU1miR-429/TFAP2Aproliferation, migration, invasion (+)Xu et al. [109]
EOC OCCCDLX6-AS1miR-195-5pproliferation, migration, invasion (+)
apoptosis (−)		Kong et al. [110]
EOC
OCCC		DNM3miR-193a-3p/MAP3K3proliferation, migration, invasion (+)He et al. [111]
EOCDSCR8miR-98-5p/STAT3/HIF-αpoor survival, proliferation, invasion, EMT (+) apoptosis (−)Dong et al. [112]
EOC OCCCDUXAP8microRNA-29a-3ppoor prognosis, proliferation, migrationLi et al. [113]
miR-590-5pproliferation (+) apoptosis (−)Meng et al. [114]
EOCELFN1-AS1miR-497-3p/CLDN4poor prognosis, proliferation, invasion,
migration (+)		Jie et al. [115]
EOCFAM83H-AS1 OSYuan et al. [116]
EOCFEZF1-AS1miR-130a-5p/SOX4proliferation, migration, invasion (+)Sun et al. [117]
EOCFGD5-AS1miR-142-5p/PD-L1proliferation, migration, invasion (+)Aichen et al. [118]
EOCFGFR3-AS1 tumor grade, FIGO stage, poor prognosis, cell growth, proliferation (+) apoptosis (−)Zhang et al. [119]
EOCFLVCR1-AS1miR-513/YAP1growth, migration, invasion, and EMT (+)apoptosis (−)Yan et al. [120]
EOCFOXD2-AS1miR-4492proliferation, invasion (+)Gao et al. [121]
EOCFTXmiR-7515/TPD52migration, invasion, EMT (+)Li et al. [122]
EOCGClnc1p53proliferation, migrationLi et al. [123]
NOTCH1/NF-κB/Snailproliferation, EMT (+)Wu et al. [124]
EOCH19 migration, invasionMa et al. [125]
miR-29b-3pCBDCA-resistanceTian et al. [126]
miRNA-140/Wnt1proliferation, migrationWang et al. [127]
miR-140-5pproliferation, invasion, migration, EMT (+)Xu et al. [128]
EOCHAGLROSmiRNA-26b-5pproliferation (+) apoptosis (−)Zhu et al. [129]
EOCHCG11miR-144-3p/PBX3viability, metastasis (+)Li et al. [130]
EOCHCG18miR-29a/b/TRAF4/5proliferation, migration, EMT (+)Zhang et al. [131]
EOC miR-525-5p/PRC1proliferation, invasion, migration, EMT (+)Wang et al. [132]
HGSOCHCP5PTBP1apoptosis (−) proliferation, migration (+)Shou et al. [133]
EOCHEIHmiR-3619-5p/CTTNBP2poor prognosis, proliferation,Si et al. [134]
migration, invasion (+)
EOCHIF1A-AS3 proliferation (+)Xie et al. [135]
miR-21-3p/PEG3 Fang et al. [136]
EOCHOTAIRmiR-222-3p/CDK19proliferation, migration, metastasis (+)Fan et al. [137]
ZEB1 and TGF-β1 Zhou et al. [138]
CHEK1 Jiang et al. [139]
EZH2, H3K27anoikis resistance (+)Dai et al. [140]
miR-138-5p, EZH2CDDP-resistanceZhang et al. [141]
miR-206/TBX3steamness of stem cells (+)Zhang et al. [142]
EOCHOTAIRM1 proliferation (+) apoptosis (−)Ye et al. [143]
EOCHOTTIPinteraction with HIF-1αmigration, invasion, viability, apoptosisZhang et al. [144]
MEK/ERKproliferation, migration (+)Liu et al. [145]
miR-615-3p/SMARCE1migration, invasion (+)
miR-148a-3p/AKT2 Tan et al. [146]
miR-205/ZEB2CDDP-resistance (+)Dong et al. [147]
EOCHOXAAS2miR372metastasis. FIGO stage, proliferation (+) apoptosis (−)Wang et al. [148]
metastasis, proliferation, migration (+)Eoh et al. [149]
EOCHOXA11-AS viability, migration, invasion (+)Chen et al. [150]
apoptosis, DDP sensitivity (−)
EOCHOXB-AS3miR-378a-3pproliferation, invasion, migration (+)Xu et al. [151]
EOCHOXC-AS3miR-96proliferation (+)Yang et al. [152]
EOC
HGSOC		HULCmiR-137/ITGB8tumor growth, PTX-resistance (+)Huang et al. [153]
EOCIDH1-AS1miR-518c-5p/RBM47poor prognosis, OS, progression (+)Zhou et al. [154]
EOCIL21-AS1miR-561-5p/CD24
proliferation (+)
apoptosis, phagocytosis (−)		Liu et al. [155]
EOCKCNQ1OT1miR-142-5p/CAPN10proliferation, metastasis (+)Liu et al. [156]
miR-125b-5p/CD147Chen et al. [157]
EIF2B5He et al. [158]
EOCKHDRBS3miR17H/CLDN6PTX sensitivity, cell proliferation, colony formation, glycolysis (+)Wu et al. [159]
EOCKTN1-AS1miR-505-3p/ZNF326proliferation, invasion, migration (+)Xie et al. [160]
EOCLBX2-AS1miR-4784/KDM5Ccell proliferation, migration, stemness (+) apoptosis (−)Gu et al. [161]
EOCLEF1-AS1miR-1285-3pmetastasis, FIGO stage, cell proliferation, migration, invasion (+)Zhang et al. [162]
EOCLINC00152BCL6
Bcl-2, Bax Caspase-3		proliferation, invasion (+)CDDP chemonseitivity (−)Wang et al. [163]
Zou et al. [164]
EOCLINC00176BCL3EMT (+)Dai et al. [165]
EOCLINC00273 proliferation, invasion (−)Shu et al. [166]
EOCLINC00452miR-501-3pviability, migration, invasion (+)Yang et al. [167]
EOCLINC00494NFκB1, FBXO32migration, invasion (+)Shu et al. [168]
EOCLINC00504miR-1244proliferation, apoptosis (+)Liu et al. [169]
EOCLINC00662miR-375OS (−)Tao et al. [170]
LINC00665miR-148b-3p/KLF5cell proliferation, invasion, migration (+) apoptosis (−)Wang et al. [171]
EOCLINC00665miR-181a-5p/FHDCviability, proliferation, migration (+)Wang et al. [172]
EOCLINC00707miR-382-5p/LRRK2 Zhao et al. [173]
LINC00852miR-140-3p/AGTR1proliferation, invasion (+)Qiao et al. [174]
EOCLINC00857miR-486-5pproliferation, migration, invasion,
glycolysis (+) apoptosis (−)		Lin et al. [175]
EOCLINC00858miR-134-5p/RAD18proliferation, motility, EM (+), apoptosis (−)Xue et al. [176]
miR-134-5p/TRIM44proliferation, migration, invasion (+)Li et al. [177]
EOCLINC00909miR-23b-3p/MRC2proliferation, migration, invasion (+)Yang et al. [178]
EOCLINC00922miR-361-3pproliferation, migration, invasion, EMT (+)Wang et al. [179]
EOCLINC00958Wnt/β-cateninproliferation, migration, invasion (+)Xie et al. [180]
EOC HGSOC
OCCC		LINC01094miR-577FIGO stage, lymph node metastasis, cell proliferation, migration, invasion and EMT (+)Xu et al. [181]
EOCLINC01123miR-516b-5pproliferation, metastasis (+) apoptosis (−)Dong et al. [182]
EOCLINC01132miRNA4315p/SOX9proliferation, migration, invasion (+)
apoptosis (−)		Zhu et al. [183]
EOCLINC01133miR-495-3pmigration, invasion (+)Liu et al. [184]
EOCLINC01215RUNX3proliferation, migration, invasion, EMT,
metastasis (+)		Liu et al. [185]
EOCLINC01342miRNA-30c-2-3pproliferation, metastasis (+)Zhang et al. [186]
EOCLINC01503miR-766-5p/PD-L1CBDCA-resistanceLi et al. [187]
EOC HGSOCLINC01605mut_p53migration (+)Coan et al. [188]
EOCLINC01969miR-144-5p/LARP1migration, invasion, proliferation (+)Chen et al. [189]
EOCLINC02323miR-1343-3pproliferation, migration (+)Li et al. [190]
EOCLINK-A Maleki et al. [191]
EOCLNC00115miR-7/ERKCDDP-resistance, invasion, migration (+)Jang et al. [192]
EOCLOC102724169 cell viability, CDDP efficacy (+) apoptosis (−)Zhou et al. [193]
EOCLOC285194 proliferation, migration, poor prognosis (+)
apoptosis (−)		Yim et al. [194]
EOCLOC642852 invasion (+)Filippov-Levy et al. [195]
EOCLOC646029miR-627-3p/SPRED1proliferation, invasion, metastasis,
poor prognosis (+)		Zhao et al. [196]
EOCLOXL1-AS1miR-18b-5p/VMA21proliferation, migration, invasion,
metastasis (+)		Xue et al. [197]
LUCAT1miR-199a-5pproliferation, apoptosis (+)Liu et al. [198]
EOCMAFG-AS1miR-339-5ptumor stage, size, lymph node metastasis,
invasion, EMT, migration (+)
Bai et al. [199]
EOCMALAT1 migration, invasion (+) apoptosis (−)Mao et al. [200]
miRNA-22proliferation, migration, invasion (+)Pei et al. [201]
miR-503-5pproliferation (+) apoptosis (−)Sun et al. [59]
EOCMCF2L-AS1IGF2BP1/IGF2/
MEK/ERK axis		PTX-resistance (+)Zhu et al. [202]
EOCMIATmiR-150-5pcell growth, migration, invasion, EMT (+)Zhou et al. [203]
EOCMIF-AS1miRNA-31-5pproliferation, migration, invasion (+)Fan et al. [204]
EOCMIR210HG EMT, angiogenesis (+)Liu et al. [205]
EOCMIR4435-2HGmiR-128-3p/CDK14proliferation, invasion, migration (+),
apoptosis (−)		Zhu et al. [206]
EOCMNX1-AS1miR-4697-3p/HOXB13CBDCA-resistanceWu et al. [207]
miR-744-5p/SOX12cell proliferation, migration, invasion (+) apoptosis (−)Shen et al. [208]
EOCMYCNmiR-152/MKK7poor survival, proliferation (+)Zhang et al. [209]
EOCMYUmiR-6827-5pFIGO stage, metastasis, proliferation (+)Wang et al. [210]
EOCNCK1-AS1miR-137cell proliferation, migration, invasion,
chemoresistance (+)		Chang et al. [211]
EOC
OCC
HGSOC		NEAT1CSTF3CDDP sensitivity (−)Luo et al. [212]
miR-214-3pproliferation, migration, invasion, angiogenesis (+) apoptosis (−)Liu et al. [213]
miR-770-5p/PARP1CDDP-resistance, viability (+) apoptosis (−)Zhu et al. [214]
miR-365proliferation, angiogenesisYaun et al. [215]
miR4500/BZW1proliferation, colony formation, migration, invasion, glycolysis (+) apoptosis (−)Xu et al. [216]
let-7 g/MEST/ATGLproliferation, migration, invasion (+)Yin et al. [217]
miR1321migration, invasion (+)Luo et al. [218]
EOCNORADmiR-199a-3pproliferation, invasion, migration, EMT (+)Xu et al. [219]
EOCNRSN2-AS1miR-744-5p/PRKXmigration, invasion (+)Chen et al. [220]
PTK2/β-cateninproliferation, metastasis (+)Wu et al. [221]
EOCOIP5-AS1miR-92aEMT, viavbility, proliferation, migration, invasion (+) apoptosis (−)Wang et al. [222]
miR-324-3p/NFIBviability, invasion, migration (+)Liu et al. [223]
miR-137/ZNF217proliferation, migration, invasion, EMT (+)Guo et al. [224]
miR-34ainvasion, migration (+)Jiang et al. [225]
miR1283p/CCNG1cell viability, migration, invasion, glycolysis (+) apoptosis (−)Liu et al. [226]
EOCOR3A4KLF6proliferation and migration (+)Guo et al. [227]
EOCPART1miR-150-5p/MYBproliferation, migration, invasion (+)Wang et al. [228]
miR-6884-5p/RACGAP1/RRM2proliferation, invasion, migration (+)Li et al. [229]
miR-503-5pcell viability, migration, invasion (−)
apoptosis (+)		Li et al. [230]
EOCPCA3miR-106b-5pcell proliferation, migration, invasion.(+)
protein expression (+)		Liu et al. [231]
EOCPLAC2CDK2proliferation (+)He et al. [232]
EOCPRLBmiR-150-5p,
PRLB/RSF1		apoptosis (−) PTX-resistance (+)Zhao et al. [233]
EOCPRNCR1miR-653-5p/ELF2invasion, migration, proliferation (+)Qi et al. [234]
EOCPRPF6SNHG16-L/CEBPB/GATA3FIGO stage, metastasis, PTX-resistance
progression (+)		Wang et al. [235]
EOCPSMA3-AS1miR-378a-3p/GALNT3proliferation, migration, invasion (+)Xu et al. [236]
EOCPTALmiR-101/fn1invasion, migration (+)Liang et al. [237]
EOCPURPLmiR-338-3pFIGO stage, metastasis (+)Zhang et al. [238]
EOC
OCCC		PVT1CTGFproliferation, migration, invasion, EMT (+)Dong et al. [239]
miR-148a/AGO1FIGO stage, poor survival rate, metastasis, cell viability, proliferation (+) apoptosis (−)Wu et al. [240]
miR-149-5p/FOXM1proliferation, migration, invasion (+)Li et al. [241]
miR-370, miR-576, FOXM1migration, invasion, proliferation,Yi et al. [242]
chemoresistance (+)
miR-543/SERPINI1proliferation, migration, invasion (+)
apoptosis (−)		Qu et al. [243]
cell survival, growth, migration,
chemoresistance (+)		Tabury et al. [244]
EOCRAD51-AS1miR-140-3p/EIF5A2poor prognosis (+)Zhao et al. [245]
EOCRBAT1 FIGO stage, metastasis (+)Luo et al. [246]
EOCRHPN1-AS1PI3K/AKTviability, migration, invasion, tumor growth (+)Cui et al. [247]
miR-1299proliferation, migration, invasion, low survival rate (+)Zhao et al. [248]
miR-665/Akt3cell proliferation, migration, invasion (+)Zhao et al. [249]
miR-596/LETM1proliferation, invasion, viability (+)Wang et al. [250]
miR-6884-5pproliferation, viability, adhesion, migration (+) apoptosis (−)Cui et al. [251]
miR4855pproliferation, apoptosis, adhesion,
migration (+)		Cui et al. [252]
EOC
HGSOC		RMRPmiR-580-3pproliferation (+) apoptosis (−)
PTX-resistance (+)		Li et al. [253]
EOCRP5miR-545-5p/PTP4A1proliferation, metastasis (+)Sun et al. [254]
EOCSBF2-AS1miR-338-3pproliferation, invasion (+)Luan et al. [255]
EOCSCAMP1miR-137/CXCL12invasion, angiogenesis (+)Song et al. [256]
EOCSDHAP1miR-4465/EIF4G2PTX-resistance (+)Zhao et al. [257]
EOC
OCCC		SNHG1miR-454/ZEB1proliferation (+)Wu et al. [258]
EOC HGSOCSNHG12 CBDCA sensitivity (+)Abildgaard et al. [259]
EOC
OCCC		SNHG17miR-18a-5pmigration and invasion (+)Zhang et al. [260]
miR-370-3p/CDK6poor prognosis, migration, proliferation (+)Wang et al. [261]
CCL13-CCR2proliferation, invasion, migration, EMT, metastasis (+)Liang et al. [262]
miR-214-3ppoor prognosis, proliferation (+) apoptosis (−)Pan et al. [263]
miR-485-5p/AKT1proliferation (+) apoptosis (−)Wang et al. [264]
EOCSNHG20miR-148a/ROCK1invasion, migration, proliferation (+)
apoptosis (−)		Yang et al. [265]
miR-217cell proliferation, invasion (+)Xing et al. [266]
miR-338-3p/MCL1proliferation, migration, invasion, EMT (+) apoptosis (−)Wang et al. [267]
EOCSNHG22SP1poor prognosis, glycolysis, proliferation (+)Guan et al. [268]
EOCSNHG25COMPproliferation, migration, invasion (+)
apoptosis (−)		Liu et al. [269]
EOCSNHG3miR-139-5pproliferation, migration (+)Zhang et al. [270]
HGSOCmiR-339-5p/TRPC3poor prognosis, apoptosis (+)Liu et al. [271]
EOCSNHG4miR-98-5p/TMED5proliferation, migration, invasion (+)
apoptosis (−)		Liu et al. [272]
EOCSNHG6miR-543/YAP1proliferation, migration, invasion, EMTSu et al. [273]
EOC
HGSOC
OCCC		SHNG7EIF4G2cell viability, migration, invasion, PTX-resistance (+)Zhang et al. [274]
KLF2, EZH2invasion and proliferation (+)Bai et al. [275]
EOCSNHG8Wnt/β-cateninproliferation, migration, EMT (+)Miao et al. [276]
EOC HGSOCSPOCD1-ASG3BP1 Wang et al. [277]
EOCSRA proliferation, invasion, migration (+)Kim et al. [278]
EOCTC0101441KiSS1invasion, migration, metastasis, EMT (+)Qiu et al. [279]
EOC HGSOCTHORIL-6/STAT3poor prognosis, proliferation, invasion (+)Ge et al. [280]
EOC HGSOCTHUMPD3-AS1miR-320d/ARF1apoptosis (−) viability (+)Mu et al. [281]
EOCTLR8-AS1 metastasis, chemoresistance (+)Xu et al. [282]
EOCTMPO-AS1LCN2migration, proliferation, invasion,
angiogenesis (+)		Zhao et al. [283]
miR-200c/TMEFF2invasion, migration, and 5-Fu resistance, EMT (+)Li et al. [284]
EOCTONSL-AS1miR-490-3p/CDK1proliferation (+)Liu et al. [285]
EOC HGSOCTRPM2-AS1miR-138-5p/SDC3proliferation, invasion, migration,
PTX-resistance (+) apoptosis (−)		Ding et al. [286]
EOCTUG1miR-582-3pviability and migration (+)Dai et al. [287]
miR-29b-3pPTX-resistance (+)Gu et al. [288]
miR-1299/NOTCH3proliferation (+)Pei et al. [289]
miR-186-5p/ZEB1proliferation, invasion (+)Zhan et al. [290]
miR-4687-3p, miR-6088CDDP sensitivity (+)Sonobe et al. [291]
EOCUCA1miR-27a-5p/UBE2NCDDP-resistanceWambecke et al. [292]
EOC HGSOCmiR-654-5p/SIK2proliferation, migration, invasion, PTX-resistance (+) apoptosis (−)Li et al. [293]
EOCUNC5B-AS1H3K27me, NDRG2proliferation (+) apoptosis (−)Wang et al. [294]
EOC
OCCC		USP2-AS1miR-520d-3pproliferation, migration (+)Guo et al. [295]
EOCUSP30-AS1 Xiong et al. [296]
EOCWDFY3-AS2miR-139-5p/SDC4CDDP-resistance, cell proliferation,
migration, invasion (+) apoptosis (−)		Wu et al. [297]
EOCXISTmiR-506-3p/FOXPapoptosis (−) CBDCA -resistance,
autophagy (+)		Xia et al. [298]
OCCCmiR-335/BCL2L2proliferation invasion, migration (+)Meng et al. [299]
miR-93-5p/KMT2CPTX resistance (+)Huang et al. [300]
miR-149-3ppoor prognosis, proliferation, invasion, migration (+) apoptosis (−)Jiang et al. [301]
EOCZEB1-AS1MMP19PTX, CDDP-resistance (−)Dai et al. [302]
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Kwas, K.; Szubert, M.; Wilczyński, J.R. Latest Update on lncRNA in Epithelial Ovarian Cancer—A Scoping Review. Cells 2025, 14, 555. https://doi.org/10.3390/cells14070555

AMA Style

Kwas K, Szubert M, Wilczyński JR. Latest Update on lncRNA in Epithelial Ovarian Cancer—A Scoping Review. Cells. 2025; 14(7):555. https://doi.org/10.3390/cells14070555

Chicago/Turabian Style

Kwas, Katarzyna, Maria Szubert, and Jacek Radosław Wilczyński. 2025. "Latest Update on lncRNA in Epithelial Ovarian Cancer—A Scoping Review" Cells 14, no. 7: 555. https://doi.org/10.3390/cells14070555

APA Style

Kwas, K., Szubert, M., & Wilczyński, J. R. (2025). Latest Update on lncRNA in Epithelial Ovarian Cancer—A Scoping Review. Cells, 14(7), 555. https://doi.org/10.3390/cells14070555

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