Endometrial cancer (EC) is the most common malignancy of the female genital tract, with an estimated incidence of 63,230 new cases in 2018 in the United States (1). With the increasing prevalence of major EC risk factors, such as obesity, diabetes and hypertension, a rising trend has also been recognized in younger women (2). EC is generally classified into two subtypes, defined as type I or endometrioid endometrial cancer (EEC) and type II or non-endometrioid endometrial cancer (NEEC) (3,4). This dualistic classification underlies different patterns of molecular alterations, pathogenesis and clinical outcome (4).

Type I EC, which is the most frequent uterine malignancy (80% of all cases), is an estrogen-dependent lesion, often seen in conjunction with endometrial hyperplasia, usually developed in peri- and early postmenopausal women (4). Type II EC affects older patients, is not preceded by hyperplasia and comprises more aggressive histologic subtypes, such as papillary serous, clear cell carcinomas and carcinosarcomas (3,5). In general, type I EC has a good prognosis, with a 10-year overall survival rate exceeding 80% (6,7). Surprisingly, despite optimal risk-adapted treatment, a small but substantial number of patients exhibits recurrence and poor survival. In such cases available risk factors or biological markers are not able to reliably predict the poor clinical course. Indeed, it is currently established that a classification only based on morphologic features is inconsistent and that molecular-based classification is desirable for optimal treatment and prognosis of such cancers. Nevertheless, although several genetic alterations have been associated with increased risk of EC (8–10) and mutations in genes such as ATR have been established to be associated with poor clinical outcomes in EEC (11), new molecular markers need to be identified for early diagnosis and treatment purposes.

In 2013, researchers at The Cancer Genome Atlas (TCGA) performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas by applying array- and sequencing-based technologies, thus drawing a new classification of endometrial cancers according to four main molecular categories according to their genomic features (12). This may guide post-surgical therapy in patients affected with aggressive tumors. Yet, since taking these results into clinical practice is currently cost-prohibitive, molecular surrogates corresponding to each of the subgroups (13), able to successfully classify all patients in the TCGA cohort and to minimize false negatives in the CN-high poor prognosticator group, were identified.

The Encyclopedia of DNA Elements (ENCODE) project estimates that almost 62–75% of the DNA is transcribed into RNA, but only 2% of the transcriptome is finally translated into proteins (14). However, this non-coding part of the genome plays many key roles in several biological processes and diseases such as in cancers (15). Thus, the landscape of non-coding RNAs (ncRNAs) is increasing day by day and has emerged as a major source of biomarkers (16,17), being considered as priority transcripts to be monitored for functional significance in both pathogenesis and progression of ECs. Based on their size, ncRNAs are divided in two main categories: Small ncRNAs [sncRNAs (<200 nt)] and long ncRNAs [lncRNAs (>200 nt)]. Moreover, they are connected to each other, with some lncRNAs acting on post-transcriptional regulation through the modulation of certain sncRNA subgroups (18).

Among sncRNAs, four major functional groups have been identified in mammals: microRNAs (miRNAs), PIWI-interacting-RNAs (piRNAs), small nucleolar-RNAs (snoRNAs) and endogenous small interfering-RNAs (endo-siRNAs) (19). sncRNAs can exert large-scale and diverse effects on cellular processes by regulating gene expression, protein translation and genomic organization. In particular, lncRNAs may contain also miRNA-binding sites and can compete with miRNAs for interaction with their target mRNAs and thereby block their effects on these mRNAs.

The classification of lncRNAs is more complex than that of sncRNAs, as they can be divided on the basis of their size, association with annotated protein-coding genes, or with other DNA elements of known function (18,20). Thus, lncRNAs represent a heterogeneous group of RNAs, which have been identified as important molecules in several biological processes, performing tumor suppression and oncogenic functions in various types of cancer (18).

Using small RNA sequencing and microarrays, we previously determined significant differences in sncRNA expression patterns between normal, hyperplastic and neoplastic endometrium of patients affected with EEC (21). This led to the definition of a sncRNA signature (129 miRNAs, 2 of which were not previously described, 10 piRNAs and 3 snoRNAs) recapitulating neoplastic transformation.

In the present study, we aimed to analyze the role of lncRNAs in EEC and to examine a possible connection with the sncRNAs previously observed. To this aim, we first performed lncRNA profiling in a set of EEC samples and paired normal tissues, to identify lncRNA molecules more likely to be associated with the cancerous state. These were also confirmed in a set of 20 paired cancer-normal profiles deposited in the TCGA database. The 80 more highly differentially expressed were found to be significantly associated with different tumor grade among 405 EEC RNA profiles in TCGA. Finally, we identified a small/long RNA functional core whose deregulation was predicted to be strongly associated with endometrial neoplastic transformation. Indeed, computational analysis identified, among the most affected functional pathways, focal adhesion, MAPK and Wnt signaling, confirming previously published data (21).

Molecular classification of ECs represents an objective that clinicians are trying to achieve in order to provide independent prognostic information beyond established risk factors.

In the past few years, pragmatic molecular classifiers have been developed, able to identify four prognostically distinct molecular subgroups that may change the current risk stratification systems (12,13,32). Indeed, the evolution of genomic classification in ECs has the potential to be used routinely in therapeutic protocol selection and in stratifying cases in future clinical trials (13).

Nevertheless, mounting evidence has emphasized the roles and clinical significance of non-coding RNAs and, in particular lncRNAs, among others in endometrial cancer (33,34).

Several studies have shown the potential of lncRNAs as therapeutic targets and investigated their involvement in cancer pathogenesis (35,36). Indeed, limited information is available on EC (37–44). Clarification of their role in the onset, progression and follow-up of this tumor is warranted to help molecular classification and targeted therapy of this cancer histotype.

In the present study, we first evaluated the differential expression of lncRNAs between endometrial tumor samples and paired normal tissues of six EEC patients and then we compared and validated our results with different EEC datasets present in TCGA database. In this way, we identified a set of lncRNAs discriminating between normal and cancerous endometrium, common between those described here and publicly available data. Moreover, deep investigation of this lncRNAs dataset among a group of 405 EEC RNA-Seq profiles in TGCA revealed that 80 lncRNAs, differentially expressed with a higher fold, were statistically distributed in five clusters, reflecting tumor grade stratification and associated with different survival trends.

A number of studies have demonstrated that a large number of miRNA-binding sites are present on lncRNAs, suggesting how these transcripts can serve also as competing endogenous RNAs controlling ‘free’ miRNA levels and functions (45,46). Importantly, lncRNAs could compete with mRNAs for miRNAs, and thereby regulate miRNA-mediated transcript repression (45,46). Therefore, we built a ceRNA network, depicting key interactions occurring among differentially expressed mRNAs, lncRNAs and miRNAs in our EEC samples and determining a functional impact within crucial pathways in EC, which may represent potential core regulators to be monitored for early diagnosis and therapeutic purposes. Indeed, understanding molecular interactions has becoming a common tool especially in cancer research, given the limited information provided to date by studies focusing on a single molecule (47–49).

In this regard, our results strengthen and integrate the current knowledge concerning EEC molecular markers, thus providing novel details about their functional correlations. In this way, a functional multi-molecule core has been identified, showing miRNA members mostly deregulated in EEC and the corresponding mRNA and lncRNA targets inversely correlated with miRNA expression. From this snapshot it emerges, for example, the coexistence between downregulation of miR-10b that has been also proved to be downregulated in other types of cancer, such as gastric and cervical ones (50,51) and upregulation of its long-RNA targets. Moreover, we confirmed upregulation of almost the entire miR-200 family (miR-200a/b/c and miR-141), an event already well documented in EEC, where these RNAs target mainly genes involved in tissue transformation responsible for epithelial-to-mesenchymal transition (EMT) (52,53). In this context, we observed an inverse correlation, among others, with the well known miR-200 targets ZEB1 and ZEB2, transcriptional repressors of E-cadherin whose expression is restored in EMT (53) and KLF9, whose downregulation in EEC has been previously demonstrated (54,55). Downregulation was also retrieved for TIMP2 representing, together with the above mentioned mRNAs, a key gene involved in the differentiation of EEC and proposed as a potential therapeutic target (56–58). More interestingly, an inverse correlation was also found with several downregulated lncRNAs, including ADAMTS9-AS2, MEG3 and HAND2-AS1, already demonstrated to act as tumor suppressors. Indeed, ADAMTS9-AS2 has been associated with the inhibition of cancer progression and migration in lung and glioma cells; its expression has been correlated with poor prognosis through a mechanism involving the interaction with DNMT1 (59,60). In addition, a role of MEG3 in EEC tumorigenesis and progression through the modulation of Notch and PI3K pathways has been proved (40,61). In several cancer types, MEG3 has been shown to sequester various microRNAs from protein and/or target mRNAs resulting in altered protein activity, translation and degradation; in particular involvement of this lncRNA in the regulation of the miR-200 family has been demonstrated, confirming what was revealed by the ceRNA model constructed here (Fig. 3) (62). Finally, HAND2-AS1 has been shown to be involved in inhibition of EEC invasion and metastasis, through the downregulation of neuromedin U (63), and it has been proposed to play a role in the tumorigenesis of muscle-invasive bladder cancer through the interaction with many several miRNAs (including, of note, also miR-183) (64).

In conclusion, in the present study we identified a functional core, constituted by a specific combination of miRNAs-mRNAs-lncRNAs expression, which represents a molecular signature of potential usefulness to monitor EEC progression, for follow-up and prognosis of this disease.