Long-Chain Non-Coding RNA SNHG3 Promotes the Growth of Ovarian Cancer Cells by Targeting miR-339-5p/TRPC3 Axis

Role of TRP channels in carcinogenesis and metastasis: Pathophysiology and regulation by non-coding RNAs

In 2021, David Julius and Ardem Patapoutian received Nobel Prize in Physiology or Medicine for their ground-breaking discoveries in the functional characterization of receptors for temperature and touch. Transient receptor potential (TRP) channels have captivated tremendous appreciation as promising drug targets over the past few years because of central involvement in different cancers. Based on the insights gleaned from decades of high-quality research, basic and clinical scientists have unveiled how Transient receptor potential channels regulated cancer onset and progression. Pioneering studies have sparked renewed interest and researchers have started to scratch the surface of mechanistic role of these channels in wide variety of cancers. In this review we have attempted to provide a summary of most recent updates and advancements made in the biology of these channels in context of cancers. We have partitioned this review into different subsections on the basis of emerging evidence about characteristically distinct role of TRPV (TRPV1, TRPV5), TRPM (TRPM3, TRPM7) and TRPC in cancers. Regulation of TRP channels by non-coding RNAs is also a very exciting area of research which will be helpful in developing a sharper understanding of the multi-step aspects of cancers.

Calcium signals and potential therapy targets in ovarian cancer (Review)

Ovarian cancer (OC) is a deadly disease. The poor prognosis and high lethality of OC are attributed to its high degrees of aggressiveness, resistance to chemotherapy and recurrence rates. Calcium ion (Ca2+) signaling has received attention in recent years, as it appears to form an essential part of various aspects of cancer pathophysiology and is a potential therapeutic target for OC treatment. Disruption of normal Ca2+ signaling pathways can induce changes in cell cycle progression, apoptosis, proliferation and migration and invasion, leading to the development of the malignant phenotype of tumors. In the present review, the main roles of ion channel/receptor/pump‑triggered Ca2+ signaling pathways located at the plasma membrane and organelle Ca2+ transport in OC are summarized. In addition, the potential of Ca2+ signaling as a novel target for the development of effective treatment strategies for OC was discussed. Furthering the understanding into the role of Ca2+ signaling in OC is expected to facilitated the identification of novel therapeutic targets and improved clinical outcomes for patients.

Extra Trees Method for Predicting LncRNA-Disease Association Based On Multi-Layer Graph Embedding Aggregation

Lots of experimental studies have revealed the significant associations between lncRNAs and diseases. Identifying accurate associations will provide a new perspective for disease therapy. Calculation-based methods have been developed to solve these problems, but these methods have some limitations. In this paper, we proposed an accurate method, named MLGCNET, to discover potential lncRNA-disease associations. Firstly, we reconstructed similarity networks for both lncRNAs and diseases using top k similar information, and constructed a lncRNA-disease heterogeneous network (LDN). Then, we applied Multi-Layer Graph Convolutional Network on LDN to obtain latent feature representations of nodes. Finally, the Extra Trees was used to calculate the probability of association between disease and lncRNA. The results of extensive 5-fold cross-validation experiments show that MLGCNET has superior prediction performance compared to the state-of-the-art methods. Case studies confirm the performance of our model on specific diseases. All the experiment results prove the effectiveness and practicality of MLGCNET in predicting potential lncRNA-disease associations.

Small nucleolar RNA host gene 3 functions as a novel biomarker in liver cancer and other tumour progression

Cancer has become the most life-threatening disease in the world. Mutations in and aberrant expression of genes encoding proteins and mutations in noncoding RNAs, especially long noncoding RNAs (lncRNAs), have significant effects in human cancers. LncRNAs have no protein-coding ability but function extensively in numerous physiological and pathological processes. Small nucleolar RNA host gene 3 (SNHG3) is a novel lncRNA and has been reported to be differentially expressed in various tumors, such as liver cancer, gastric cancer, and glioma. However, the interaction mechanisms for the regulation between SNHG3 and tumor progression are poorly understood. In this review, we summarize the results of SNHG3 studies in humans, animal models, and cells to underline the expression and role of SNHG3 in cancer. SNHG3 expression is upregulated in most tumors and is detrimental to patient prognosis. SNHG3 expression in lung adenocarcinoma remains controversial. Concurrently, SNHG3 affects oncogenes and tumor suppressor genes through various mechanisms, including competing endogenous RNA effects. A deeper understanding of the contribution of SNHG3 in clinical applications and tumor development may provide a new target for cancer diagnosis and treatment.

A TRP Family Based Signature for Prognosis Prediction in Head and Neck Squamous Cell Carcinoma

Purpose

Head and neck squamous cell carcinoma (HNSCC) is a classical type of head and neck cancers, with heterogeneous clinical outcome. This project is set out to create a robust risk signature based on TRP family genes (TFGs) for prognosis evaluation in HNSCC.

Methods

Based on the HNSCC sample data from the TCGA website, we integrated expression profile of TFGs for 490 HNSCC cases. We explore the interactions among TFGs using STRING tool. The TFGs-based signature (TFBS) was created by Cox relative analyses. In addition, we conducted GSEA to identify the underlying signaling pathways of the specific TFGs in HNSCC. The immune landscape of HNSCC patients was analyzed by CIBERSORT and ssGSEA algorithms.

Results

A total of 6 TFGs (TRPC1, TRPC3, TRPC6, TRPV2, TRPV4, and TRPM8) closely associated with prognosis of HNSCC cases were screened to create TFBS. TFBS predicted that the TFBS-high group presented dismal patient outcome. Cox regression revealed the favorable independent value of TFBS. ROC analysis showed the robust power of TFBS for prognosis forecasting. GSEA determined several crucial pathways related with HNSCC, which are the p53 pathway, TNF-alpha signaling via NFKB, and hypoxia. Moreover, immune-related analysis showed that patients in the TFBS-high group were more likely in immunosuppressive status.

Conclusion

Our proposed TFBS could serve as a favorable indicator to forecast the survival outcome of HNSCC cases and offer prominent therapy guidance.

A diagnostic and prognostic value of blood-based circulating long non-coding RNAs in Thyroid, Pancreatic and Ovarian Cancer

Several studies have demonstrated the potential of circulating long non-coding RNAs (lncRNAs) as promising cancer biomarkers. Herein, we addressed the regulatory role of circulating lncRNAs and their potential value as diagnostic/prognostic markers for thyroid, pancreatic and ovarian cancers. Furthermore, we analyzed and measured the clinical implications and association of lncRNAs with sensitivity, specificity, and area under the ROC curve (AUC). Based on our meta-analysis, we found that GAS8-AS1 could discriminate thyroid cancer from non-cancer and other cancers with higher accuracy (AUC = 0.746; sensitivity = 61.70%, and specificity = 90.00%). Similarly, for ovarian cancer, lncRNA RP5-837J1.2 was found to have ideal diagnostic potential with critical clinical specifications of AUC = 0.996; sensitivity = 97.30% and specificity = 94.60%. Whereas we could not find any lncRNA having high diagnostic/prognostic efficiency in pancreatic cancer. We believe that lncRNAs mentioned above may explore clinical settings for the diagnosis and prognosis of cancer patients.

Small RNA sequencing reveals distinct nuclear microRNAs in pig granulosa cells during ovarian follicle growth

Nuclear small RNAs have emerged as an important subset of non-coding RNA species that are capable of regulating gene expression. A type of small RNA, microRNA (miRNA) have been shown to regulate development of the ovarian follicle via canonical targeting and translational repression. Little has been done to study these molecules at a subcellular level. Using cell fractionation and high throughput sequencing, we surveyed cytoplasmic and nuclear small RNA found in the granulosa cells of the pig ovarian antral preovulatory follicle. Bioinformatics analysis revealed a diverse network of small RNA that differ in their subcellular distribution and implied function. We identified predicted genomic DNA binding sites for nucleus-enriched miRNAs that may potentially be involved in transcriptional regulation. The small nucleolar RNA (snoRNA) SNORA73, known to be involved in steroid synthesis, was also found to be highly enriched in the cytoplasm, suggesting a role for snoRNA species in ovarian function. Taken together, these data provide an important resource to study the small RNAome in ovarian follicles and how they may impact fertility.