Clinical Value of lncRNA MEG3 in High-Grade Serous Ovarian Cancer

Abstract

Long non-coding RNAs (lncRNAs) are emerging as regulators in cancer development and progression, and aberrant lncRNA profiles have been reported in several cancers. Here, we evaluated the potential of using the maternally expressed gene 3 (MEG3) tissue level as a prognostic marker in high-grade serous ovarian cancer (HGSOC), the most common and deadliest gynecologic malignancy. To the aim of the study, we measured MEG3 transcript levels in 90 pre-treatment peritoneal biopsies. We also investigated MEG3 function in ovarian cancer biology. We found that high MEG3 expression was independently associated with better progression-free (p = 0.002) and overall survival (p = 0.01). In vitro and in vivo preclinical studies supported a role for MEG3 as a tumor suppressor in HGSOC, possibly through modulation of the phosphatase and tensin homologue (PTEN) network. Overall, results from this study demonstrated that decreased MEG3 is a hallmark for malignancy and tumor progression in HGSOC.

Comprehensive analysis of ceRNA network related to lincRNA in glioblastoma and prediction of clinical prognosis

“…MEG3 , also known as gene trap locus 2, is an imprinted gene located at 14q32 [ 36 ]. It is a new type of tumour suppressor that plays a role in various tumours, such as ovarian and bladder cancers [ 37 , 38 ]. Studies have shown that MEG3 is under-expressed in gliomas, and its over-expression has a significant inhibitory effect on the proliferation and migration of glioma cells, while promoting its apoptosis and autophagy, and inhibiting the PI3K/AKT/mTOR signalling pathway [ 39 , 40 ].…”

Construction and Validation of a Novel Glycometabolism-Related Gene Signature Predicting Survival in Patients With Ovarian Cancer

“…In recent years, features such as age, pathological stage, lymph node metastasis and distant metastasis have been commonly used in clinical work to predict the prognosis of patients with OC (Mittermeyer et al, 2013;Yuan et al, 2017;Zwakman et al, 2017;Hua et al, 2019), but the accuracy of these factors is insufficient. With the development of high-throughput sequencing technology, an increasing number of mRNAs have been discovered as biomarkers that can be used to evaluate and predict the prognosis of OC (Buttarelli et al, 2020;Nash and Menon, 2020;Zhang et al, 2020;Zhou et al, 2020). For instance, some scholars found that the high expression of TET3 was related to the progression of OC and the poor prognosis of patients (Cao et al, 2019).…”

“…With the development of high-throughput sequencing, several patient genome databases have been established, which have enabled us to gain a more systematic and comprehensive understanding of patients' genome changes. By mining databases, we identified a number of biomarkers associated with clinical outcomes (Buttarelli et al, 2020;Nash and Menon, 2020;Zhang et al, 2020;Zhou et al, 2020). However, a single gene cannot accurately predict the outcomes of OC.…”

miR‐181a overexpression predicts the poor treatment response and early‐progression of serous ovarian cancer patients

“…Apart from the protein-based CA125 and HE4 that are currently utilized to diagnose and/or monitor OC patients, 36 [39][40][41] Evidently, the focus of research on defining new molecular markers and their further large-scale evaluation could explicitly become substantial for the improvement of disease management.…”

“…Noteworthy, copy‐number alteration (CNA) profiling in cell‐free DNA has emerged as powerful marker for the discrimination of ovarian tumors from benign lesions in patients presenting with an adnexal mass, 37 while HOXA9 promoter methylation in circulating tumor DNA has been strongly associated with poor disease outcome 38 . Likewise, loss of MEG3 long noncoding RNA, miR‐150‐5p overexpression and elevated miR‐622 serum levels have been reported recently to predict patients’ unfavorable outcome 39‐41 . Evidently, the focus of research on defining new molecular markers and their further large‐scale evaluation could explicitly become substantial for the improvement of disease management.…”