Biomarker Potential of Plasma MicroRNA-150-5p in Prostate Cancer

Paunescu, Ionut Andrei; Bardan, Răzvan; Marcu, Anca; Nițușcă, Diana; Dema, Alis; Negru, Șerban; Bălăcescu, Ovidiu; Bălăcescu, Loredana; Cumpanas, A.; Sîrbu, Ioan Ovidiu; Petruț, Bogdan; Șeclăman, Edward; Marian, Cătălin

doi:10.3390/medicina55090564

Cited by 28 publications

(19 citation statements)

References 29 publications

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“…miRNAs are non-coding RNAs ranging from 18 to 24 nucleotides in length that negatively regulate gene expression at the post-transcriptional level [ 55 ]. Their expression may be either contributory or inhibitory to various types of cancers, including GBM [ 110 , 160 ]. One of the miRNAs found critical for mesenchymal transition in GBM is miR-23a, which was found to induce the expression of invasion- and PMT-related molecules, including RhoA, RhoC, Snail, Slug, and MMP9 [ 168 ].…”

Section: Biomarkers and Therapeutic Targets For Mesenchymal Glioblastmentioning

confidence: 99%

Perspective of mesenchymal transformation in glioblastoma

Kim

Varn

Park

et al. 2021

acta neuropathol commun

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Despite aggressive multimodal treatment, glioblastoma (GBM), a grade IV primary brain tumor, still portends a poor prognosis with a median overall survival of 12–16 months. The complexity of GBM treatment mainly lies in the inter- and intra-tumoral heterogeneity, which largely contributes to the treatment-refractory and recurrent nature of GBM. By paving the road towards the development of personalized medicine for GBM patients, the cancer genome atlas classification scheme of GBM into distinct transcriptional subtypes has been considered an invaluable approach to overcoming this heterogeneity. Among the identified transcriptional subtypes, the mesenchymal subtype has been found associated with more aggressive, invasive, angiogenic, hypoxic, necrotic, inflammatory, and multitherapy-resistant features than other transcriptional subtypes. Accordingly, mesenchymal GBM patients were found to exhibit worse prognosis than other subtypes when patients with high transcriptional heterogeneity were excluded. Furthermore, identification of the master mesenchymal regulators and their downstream signaling pathways has not only increased our understanding of the complex regulatory transcriptional networks of mesenchymal GBM, but also has generated a list of potent inhibitors for clinical trials. Importantly, the mesenchymal transition of GBM has been found to be tightly associated with treatment-induced phenotypic changes in recurrence. Together, these findings indicate that elucidating the governing and plastic transcriptomic natures of mesenchymal GBM is critical in order to develop novel and selective therapeutic strategies that can improve both patient care and clinical outcomes. Thus, the focus of our review will be on the recent advances in the understanding of the transcriptome of mesenchymal GBM and discuss microenvironmental, metabolic, and treatment-related factors as critical components through which the mesenchymal signature may be acquired. We also take into consideration the transcriptomic plasticity of GBM to discuss the future perspectives in employing selective therapeutic strategies against mesenchymal GBM.

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Section: Biomarkers and Therapeutic Targets For Mesenchymal Glioblastmentioning

confidence: 99%

Perspective of mesenchymal transformation in glioblastoma

Kim

Varn

Park

et al. 2021

acta neuropathol commun

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“…In the three GEO datasets, the performance . In conclusion, the 3-miRNA panel selected in this study is superior to other miRNA biomarkers in the diagnosis of PC (Porzycki et al, 2018;Moltzahn et al, 2011;Chen et al, 2012;Bryant et al, 2012;Yaman Agaoglu et al, 2011;Paunescu et al, 2019).…”

Section: Comparison With Previously Identified Signaturesmentioning

confidence: 73%

MicroRNA panel in serum reveals novel diagnostic biomarkers for prostate cancer

Zhang

Liu

Zou

et al. 2021

PeerJ

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Purpose MicroRNAs (miRNAs), which could be stably preserved and detected in serum or plasma, could act as biomarkers in cancer diagnosis. Prostate cancer is the second cancer in males for incidence. This study aimed to establish a miRNA panel in peripheral serum which could act as a non-invasive biomarker helping diagnosing PC. Methods A total of 86 PC patients and 86 normal control serum samples were analyzed through a four-stage experimental process using quantitative real-time polymerase chain reaction. Logistic regression method was used to construct a diagnostic model based on the differentially expressed miRNAs in serum. Receiver operating characteristic curves were constructed to evaluate the diagnostic accuracy. We also compared the 3-miRNA panel with previously reported biomarkers and verified in four public datasets. In addition, the expression characteristics of the identified miRNAs were further explored in tissue and serum exosomes samples. Results We identified a 3-miRNA signature including up-regulated miR-146a-5p, miR-24-3p and miR-93-5p for PC detection. Areas under the receiver operating characteristic curve of the 3-miRNA panel for the training, testing and external validation phase were 0.819, 0.831 and 0.814, respectively. The identified signature has a very stable diagnostic performance in the large cohorts of four public datasets. Compared with previously identified miRNA biomarkers, the 3-miRNA signature in this study has superior performance in diagnosing PC. What’s more, the expression level of miR-93-5p was also elevated in exosomes from PC samples. However, in PC tissues, none of the three miRNAs showed significantly dysregulated expression. Conclusions We established a three-miRNA panel (miR-146a-5p, miR-24-3p and miR-93-5p) in peripheral serum which could act as a non-invasive biomarker helping diagnosing PC.

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“…All subjects included in this study provided informed consent for the use of their biological samples. The study was approved by the Ethics Committee of the participating institutions, in accordance with the Declaration of Helsinki, and venous blood was collected in EDTA-containing tubes, as previously described [ 26 ]. Patients’ characteristics are briefly summarized in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

“…Eleven-year-old FFPE tissue samples of PCa from the Department of Pathology, University of Medicine and Pharmacy “Victor Babes” Timisoara, were sectioned (10 µm in size), mounted on MMI RNAse-free slides (MMI, Zurich, Switzerland), and microdissected using LCM technology, as previously described [ 26 , 27 ].…”

Section: Methodsmentioning

confidence: 99%

Long Noncoding RNA NEAT1 as a Potential Candidate Biomarker for Prostate Cancer

Nițușcă

Marcu

Dema

et al. 2021

Life

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Background: Prostate cancer (PCa) remains one of the leading causes of cancer-related mortality in men worldwide, mainly due to unsatisfactory diagnostic methods used at present, which lead to overdiagnosis, unnecessary biopsies and treatment, or misdiagnosis in early asymptomatic stages. New diagnostic biomarkers are needed for a correct and early diagnosis. Long noncoding RNAs (lncRNAs) have been broadly studied for their involvement in PCa biology, as well as for their potential role as diagnostic biomarkers. Methods: We conducted lncRNA profiling in plasma and microdissected formalin-fixed paraffin-embedded (FFPE) tissues of PCa patients and attempted validation for commonly dysregulated individual lncRNAs. Results: Plasma profiling revealed eight dysregulated lncRNAs, while microarray analysis revealed 717 significantly dysregulated lncRNAs, out of which only nuclear-enriched abundant transcript 1 (NEAT1) was commonly upregulated in plasma samples and FFPE tissues. NEAT1’s individual validation revealed statistically significant upregulation (FC = 2.101, p = 0.009). Receiver operating characteristic (ROC) analysis showed an area under the curve (AUC) value of 0.7298 for NEAT1 (95% CI = 0.5812–0.8785), suggesting a relatively high diagnostic value, thus having a potential biomarker role for this malignancy. Conclusions: We present herein data suggesting that NEAT1 could serve as a diagnostic biomarker for PCa. Additional studies of larger cohorts are needed to confirm our findings, as well as the oncogenic mechanism of NEAT1 in the development of PCa.

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Biomarker Potential of Plasma MicroRNA-150-5p in Prostate Cancer

Cited by 28 publications

References 29 publications

Perspective of mesenchymal transformation in glioblastoma

Perspective of mesenchymal transformation in glioblastoma

MicroRNA panel in serum reveals novel diagnostic biomarkers for prostate cancer

Long Noncoding RNA NEAT1 as a Potential Candidate Biomarker for Prostate Cancer

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