Circular RNA circCLK3 promotes the progression of tongue squamous cell carcinoma via miR-455-5p/PARVA axis

Emerging cell cycle related non-coding RNA biomarkers from saliva and blood for oral squamous cell carcinoma

The unnotified or undifferentiable early stages of oral squamous cell carcinoma (OSCC) progression are the prime reasons for late-stage detection and poor survival outcomes of oral cancer. This review summarizes the prior research and recent advancements on the influence of dysregulated non-coding RNA (ncRNA) on cell cycle and their employability as diagnostic and prognostic biomarkers of oral cancer. The literature search was performed using the following keywords: 'serum/saliva non-coding RNAs' and 'serum/saliva non-coding RNAs and cell cycle', 'serum/saliva dysregulated ncRNAs and cell cycle', 'Cdk/CKI and ncRNAs', 'tissue ncRNAs' concerning 'oral cancer''. The compiled data focuses mainly on the diagnostic and prognostic significance of MicroRNAs (miRNAs), Circular RNAs (circRNAs), and Long noncoding RNAs (lncRNAs) on oral cancer and all other cancers as well as subject-relevant articles published in languages other than English are beyond the scope of this review and excluded from the study. Moreover, articles focusing on DNA, protein, and metabolite markers are eliminated from the study. While there exist various potential biomolecules such as DNA, RNA, proteins, metabolites, and specific antigens representing predictive biomarkers in body fluids for oral cancer, this review completely focuses on non-coding RNAs restricted to saliva and blood, picking out a few of the reliable ones amongst the recent investigations based on the sophisticated techniques, cohort, and sensitivity as well as specificity, i.e., salivary miR-1307-5p, miR-3928, hsa_circ_0001874 and ENST00000412740, NR_131012, ENST00000588803, NR_038323, miR-21 in circulation. Thus, further studies are required to clinically confirm the usage of these non-invasive biomarkers in oral cancer.

Non-Coding RNAs in Oral Cancer: Emerging Roles and Clinical Applications

Oral cancer (OC) is among the most prevalent cancers in the world. Certain geographical areas are disproportionately affected by OC cases due to the regional differences in dietary habits, tobacco and alcohol consumption. However, conventional therapeutic methods do not yield satisfying treatment outcomes. Thus, there is an urgent need to understand the disease process and to develop diagnostic and therapeutic strategies for OC. In this review, we discuss the role of various types of ncRNAs in OC, and their promising clinical implications as prognostic or diagnostic markers and therapeutic targets. MicroRNA (miRNA), long ncRNA (lncRNA), circular RNA (circRNA), PIWI-interacting RNA (piRNA), and small nucleolar RNA (snoRNA) are the major ncRNA types whose involvement in OC are emerging. Dysregulated expression of ncRNAs, particularly miRNAs, lncRNAs, and circRNAs, are linked with the initiation, progression, as well as therapy resistance of OC via modulation in a series of cellular pathways through epigenetic, transcriptional, post-transcriptional, and translational modifications. Differential expressions of miRNAs and lncRNAs in blood, saliva or extracellular vesicles have indicated potential diagnostic and prognostic importance. In this review, we have summarized all the promising aspects of ncRNAs in the management of OC.

circCLK3 regulates colorectal cancer SW620 cell proliferation, migration, and invasion by targeting miR-654-5p

BACKGROUND

Recent studies have investigated the role of circular RNAs (circRNAs) as significant regulatory factors in the progression of multiple cancers, containing colorectal cancer (CRC). Nevertheless, the biological functions of circCLK3 in CRC and the underlying mechanisms by which it regulates CRC progression remain unclear.

AIM

To clarify the mechanism of circCLK3 regulating colorectal cancer SW620 cell proliferation, migration, and invasion.

METHODS

CRC tissues and adjacent tissues were collected, and the expression of circCLK3 and miR-654-5p was detected by qRT-PCR. SW620 cells were cultured in vitro and divided into the following groups: si-circCLK3 group, pcDNA-circCLK3 group, miR-654-5p group, si-circCLK3 + anti-miR-654-5p group, and corresponding negative control groups (si-NC group, pcDNA group, miR-NC group, and si-circCLK3 + anti-miR-NC group). CCK8 assay, colony formation test, scratch test, and Transwell test were used to detect cell proliferation, migration, and invasion. The interaction between circCLK3 and miR-654-5p was confirmed by dual-luciferase reporter assay. The protein expression of MMP-2 and MMP-9 was detected by Western blot.

RESULTS

circCLK3 expression was increased (P < 0.05), while miR-654-5p expression was decreased (P < 0.05) in CRC tissues. Cell viability, scratch healing rate, the protein levels of matrix metalloproteinase-2 (MMP-2) and MMP-9, the number of cell clones formed, and the number of invasive cells were decreased (P < 0.05) in the si-circCLK3 group. circCLK3 could negatively regulate the expression of miR-654-5p. Cell viability, scratch healing rate, the protein levels of MMP-2 and MMP-9, the number of cell clones formed and the number of invasive cells were decreased (P < 0.05) in the miR-654-5p group. Cell viability, scratch healing rate, the protein levels of MMP-2 and MMP-9, the number of cell clones formed, and the number of invasive cells were increased (P < 0.05) in the si-circCLK3 + anti-miR-654-5p group.

CONCLUSION

circCLK3 promotes CRC cell proliferation, migration, and invasion by targeting miR-654-5p.

Circular RNA-Related CeRNA Network and Prognostic Signature for Patients with Osteosarcoma

Introduction

Osteosarcoma (OSA) is characterized by its relatively high morbidity in children and adolescents. Patients usually have advanced disease at the time of diagnosis, resulting in poor outcomes. This study focused on building a circular RNA-based ceRNA network to develop a reliable model for OSA risk prediction.

Methods

We used the Gene Expression Omnibus (GEO) datasets to explore the expression patterns of circRNA, miRNA, and mRNA in OSA. The prognostic value of circRNA host genes was assessed with data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database using Kaplan–Meier survival analysis. We established a circRNA-related ceRNA network and annotated its biological functions. Next, we developed a prognostic risk signature based on mRNAs extracted from the ceRNA network. We also developed a prognostic model and constructed a nomogram to enhance the prediction of OSA prognosis.

Results

We identified 166 DEcircRNAs, 233 DEmiRNAs, and 1317 DEmRNAs and used them to create a circRNA-related ceRNA network. We then established a prognostic risk model consisting of four genes (MLLT11, TNFRSF11B, SLC7A7, and PARVA). Moreover, we found that inhibition of MLLT11 and SLC7A7 blocked OSA cell proliferation and migration in in vitro experiments.

Conclusion

Our study identifies crucial prognostic genes and provides a circRNA-related ceRNA network for OSA, which will contribute to the elucidation of the molecular mechanisms underlying the oncogenesis and development of OSA.