LncRNA RCAT1 promotes tumor progression and metastasis via miR-214-5p/E2F2 axis in renal cell carcinoma

The crosstalk between non-coding RNAs and cell-cycle events: A new frontier in cancer therapy

The cell cycle comprises sequential events during which a cell duplicates its genome and divides it into two daughter cells. This process is tightly regulated to ensure that the daughter cell receives identical copied chromosomal DNA and that any errors in the DNA during replication are correctly repaired. Cyclins and their enzyme partners, cyclin-dependent kinases (CDKs), are critical regulators of G- to M-phase transitions during the cell cycle. Mitogenic signals induce the formation of the cyclin/CDK complexes, resulting in phosphorylation and activation of the CDKs. Once activated, cyclin/CDK complexes phosphorylate specific substrates that drive the cell cycle forward. The sequential activation and inactivation of cyclin-CDK complexes are tightly controlled by activating and inactivating phosphorylation events induced by cell-cycle proteins. The non-coding RNAs (ncRNAs), which do not code for proteins, regulate cell-cycle proteins at the transcriptional and translational levels, thereby controlling their expression at different cell-cycle phases. Deregulation of ncRNAs can cause abnormal expression patterns of cell-cycle-regulating proteins, resulting in abnormalities in cell-cycle regulation and cancer development. This review explores how ncRNA dysregulation can disrupt cell division balance and discusses potential therapeutic approaches targeting these ncRNAs to control cell-cycle events in cancer treatment.

In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data

MicroRNAs (miRNAs) are promising biomarkers for the early detection of disease, and many miRNA-based diagnostic models have been constructed to distinguish patients and healthy individuals. To thoroughly utilize the miRNA-profiling data across different sequencing platforms or multiple centers, the models accounting the batch effects were demanded for the generalization of medical application. We conducted transcription factor (TF)-mediated miRNA-miRNA interaction network analysis and adopted the within-sample expression ratios of miRNA pairs as predictive markers. The ratio of the expression values between each miRNA pair turned out to be stable across multiple data sources. A genetic algorithm-based classifier was constructed to quantify risk scores of the probability of disease and discriminate disease states from normal states in discovery, with a validation dataset for COVID-19, renal cell carcinoma, and lung adenocarcinoma. The predictive models based on the expression ratio of interacting miRNA pairs demonstrated good performances in the discovery and validation datasets, and the classifier may be used accurately for the early detection of disease.

Established and emerging biomarkers of immunotherapy in renal cell carcinoma

Immunotherapies, such as immune checkpoint inhibitors, have heralded impressive progress for patient care in renal cell carcinoma (RCC). Despite this success, some patients' disease fails to respond, and other patients experience significant side effects. Thus, development of biomarkers is needed to ensure that patients can be selected to maximize benefit from immunotherapies. Improving clinicians' ability to predict which patients will respond to immunotherapy and which are most at risk of adverse events - namely through clinical biomarkers - is indispensable for patient safety and therapeutic efficacy. Accordingly, an evolving suite of therapeutic biomarkers continues to be investigated. This review discusses biomarkers for immunotherapy in RCC, highlighting current practices and emerging innovations, aiming to contribute to improved outcomes for patients with RCC.

Exploring the Therapeutic Significance of microRNAs and lncRNAs in Kidney Diseases

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are two crucial classes of transcripts that belong to the major group of non-coding RNAs (ncRNAs). These RNA molecules have significant influence over diverse molecular processes due to their crucial role as regulators of gene expression. However, the dysregulated expression of these ncRNAs constitutes a fundamental factor in the etiology and progression of a wide variety of multifaceted human diseases, including kidney diseases. In this context, over the past years, compelling evidence has shown that miRNAs and lncRNAs could be prospective targets for the development of next-generation drugs against kidney diseases as they participate in a number of disease-associated processes, such as podocyte and nephron death, renal fibrosis, inflammation, transition from acute kidney injury to chronic kidney disease, renal vascular changes, sepsis, pyroptosis, and apoptosis. Hence, in this current review, we critically analyze the recent findings concerning the therapeutic inferences of miRNAs and lncRNAs in the pathophysiological context of kidney diseases. Additionally, with the aim of driving advances in the formulation of ncRNA-based drugs tailored for the management of kidney diseases, we discuss some of the key challenges and future prospects that should be addressed in forthcoming investigations.

DNM3OS Enhances the Apoptosis and Senescence of Spermatogonia Associated with Nonobstructive Azoospermia by Providing miR-214-5p and Decreasing E2F2 Expression

Background

Nonobstructive azoospermia (NOA) is a complex disease characterized by the spermatogenic dysfunction of testicular tissues. The roles played by long noncoding RNAs (lncRNAs) in NOA pathogenesis have not been extensively studied.

Methods

Microarray assays were performed on samples of testicular biopsy tissue obtained from patients with NOA for the purpose of identifying differentially expressed lncRNAs and messenger RNA (mRNA) transcripts, and the results were verified by quantitative real-time polymerase chain reaction. Mouse-derived GC-1 spermatogonia (spg) cells undergoing treatment with Adriamycin (ADR) were used to investigate the biological functions of the selected lncRNAs in vitro. The target microRNAs (miRNAs) of lncRNAs and the target mRNAs of miRNAs were predicted by a bioinformatics analysis. Functional studies performed using the CCK-8 assay, EdU incorporation assay, apoptosis detection, and senescence-associated β-galactosidase (SA-β-Gal) staining were conducted using GC-1 spg cells.

Results

Totals of 2,652 lncRNAs and 2,625 mRNAs were found to be differentially expressed in the testicular tissue of NOA patients when compared with patients in a control group. Dynamin 3 opposite strand (DNM3OS) was a provider of pe-miR-214-5p that positively regulates miR-214-5p expression in GC-1 spg cells. The E2 factor (E2F) family of transcription factor 2 (E2F2) was initially predicted and subsequently verified to be a downstream gene of miR-214-5p. E2F2 expression was upregulated after DNM3OS knockdown in ADR-treated GC-1 spg cells. Moreover, knockdown of either DNM3OS or miR-214-5p significantly alleviated ADR-induced decreases in cellular activity and proliferation, as well as increases in apoptosis and senescence of mouse spermatogonial GC-1 spg cells.

Conclusions

DNM3OS was found to regulate the apoptosis and senescence of spermatogonia by providing miR-214-5p and decreasing E2F2 expression, suggesting it as a novel target for gene therapy of male infertility.

Circadian rhythm-associated lncRNA RP11-414H17.5 as a key therapeutic target in osteosarcoma affects the tumor immune microenvironment and enhances malignancy

BACKGROUND

It has previously been proven that circadian rhythm disruption is associated with the incidence and deterioration of several tumors, which potentially leads to increased tumor susceptibility and a worse prognosis for tumor-bearing patients. However, their potential role in osteosarcoma has yet to be sufficiently investigated.

METHODS

Transcriptomic and clinical data of 84 osteosarcoma samples and 70 normal bone tissue samples were obtained from the TARGET and GTEx databases, circadian rhythm-related genes were obtained from Genecards, and circadian rhythm-related lncRNAs (CRLs) were obtained by Pearson correlation analysis, differential expression analysis, and protein-protein interaction (PPI) analysis. COX regression and LASSO regression were performed on the CRLs in order to construct a circadian rhythm-related prognostic prediction signature (CRPS). CRPS reliability was verified by Kaplan-Meier (KM), principal component analysis (PCA), nomogram, and receiver operating characteristic (ROC) curve. CRPS effects on the immune microenvironment of osteosarcoma were explored by enrichment analysis and immune infiltration analysis, and the effect of critical gene RP11-414H17.5 on osteosarcoma was experimentally verified.

RESULT

CRPS consisting of three CRLs was constructed and its area under the curve (AUC) values predicted that osteosarcoma prognosis reached 0.892 in the training group and 0.843 in the test group, with a p value of < 0.05 for the KM curve and stable performance across different clinical subgroups. PCA analysis found that CRPS could significantly distinguish between different risk subgroups, and exhibited excellent performance in the prediction of the immune microenvironment. The experiment verified that RP11-414H17.5 can promote metastasis and inhibit apoptosis of osteosarcoma cells.

CONCLUSION

The study revealed that circadian rhythm plays a crucial role in osteosarcoma progression and identified the impact of the key gene RP11-414H17.5 on osteosarcoma, which provides novel insights into osteosarcoma diagnosis and therapy.

Identification and verification of a novel anoikis-related gene signature with prognostic significance in clear cell renal cell carcinoma

PURPOSE

Clear cell renal cell carcinomas (ccRCCs) are the most common form of renal cancer in the world. The loss of extracellular matrix (ECM) stimulates cell apoptosis, known as anoikis. A resistance to anoikis in cancer cells is believed to contribute to tumor malignancy, particularly metastasis; however, the potential influence of anoikis on the prognosis of ccRCC patients is not fully understood.

METHODS

In this study, anoikis-related genes (ARGs) with discrepant expression were selected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The anoikis-related gene signature (ARS) was built using a combination of the univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. ARS was also evaluated for their prognostic value. We explored the tumor microenvironment and enrichment pathways between different clusters of ccRCC. We also examined differences in clinical characteristics, immune cell infiltration and drug sensitivity between the high- and low-risk sets. In addition, we utilized three external databases and quantitative real-time polymerase chain reaction (qRT-PCR) to validate the expression and prognosis of ARGs.

RESULTS

Eight ARGs (PLAUR, HMCN1, CDKN2A, BID, GLI2, PLG, PRKCQ and IRF6) were identified as anoikis-related prognostic factors. According to Kaplan-Meier (KM) analysis, ccRCC patients with high-risk ARGs have a worse prognosis. The risk score was found to be a significant independent prognostic indicator. According to tumor microenvironment (TME) scores, stromal score, immune score, and estimated score of the high-risk group were superior to those of the low-risk group. There were significant differences between the two groups regarding the amount of infiltrated immune cells, immune checkpoint expression as well as drug sensitivity. A nomogram was constructed using ccRCC clinical features and risk scores. The signature and the nomogram both performed well in predicting overall survival (OS) for ccRCC patients. According to a decision curve analysis (DCA), clinical treatment options for patients with ccRCC could be improved using this model.

CONCLUSION

The results of validation from external databases and qRT-PCR were basically agreement with findings in TCGA and GEO databases. The ARS serving as biomarkers may provide an important reference for individual therapy of ccRCC patients.

Deep Learning Approaches for lncRNA-Mediated Mechanisms: A Comprehensive Review of Recent Developments

This review paper provides an extensive analysis of the rapidly evolving convergence of deep learning and long non-coding RNAs (lncRNAs). Considering the recent advancements in deep learning and the increasing recognition of lncRNAs as crucial components in various biological processes, this review aims to offer a comprehensive examination of these intertwined research areas. The remarkable progress in deep learning necessitates thoroughly exploring its latest applications in the study of lncRNAs. Therefore, this review provides insights into the growing significance of incorporating deep learning methodologies to unravel the intricate roles of lncRNAs. By scrutinizing the most recent research spanning from 2021 to 2023, this paper provides a comprehensive understanding of how deep learning techniques are employed in investigating lncRNAs, thereby contributing valuable insights to this rapidly evolving field. The review is aimed at researchers and practitioners looking to integrate deep learning advancements into their lncRNA studies.

E2F2 serves as an essential prognostic biomarker and therapeutic target for human renal cell carcinoma by presenting "E2F2/miR-16-5p/SPTLC1" schema

BACKGROUND

Renal cell carcinoma (RCC) is a common malignant tumor of the urinary system with high mortality and morbidity. Although E2F2, a classical transcription factor implicated in cell cycle, has been shown to foster tumorigenesis in several human cancers, it could not draw a satisfy answer referring to precise downstream signaling axis in RCC development yet.

METHODS

Based on the publicly available data from TCGA database, expression patterns of E2F2, SPTLC1 and miR-16-5p were identified, either with the ability to predict the prognosis of patients with RCC, which was further validated in 38 paired RCC tissues and matched adjacent tissues by RT-qPCR and Western blot, respectively. Their cellular biofunctions were evaluated using MTT, EdU, Colony formation and transwell assays. Chromatin immunoprecipitation (ChIP) and luciferase reporter assay were employed to certain the exquisite core transcription regulatory circuitry of E2F2/miR-16-5p/SPTLC1 in RCC progression, which was also determined in xenograft tumor model.

RESULTS

Consistent with the public TCGA database, E2F2 was significantly increased in RCC tissues and cells, indicating shorter overall survival. Mechanistically, E2F2 served as a transcriptional activator of miR-16-5p, thus accounting for its negative regulation on SPTLC1 expression. E2F2 knockdown-mediated suppressive biofunctions on RCC cells were rescued by miR-16-5p mimics, while this effect was abolished again by SPTLC1 overexpression. Role of E2F2 on RCC tumorigenesis via the miR-16-5p/SPTLC1 axis was verified both in vitro and in vivo.

CONCLUSION

E2F2 promoted RCC progression via the miR-16-5p/SPTLC1 axis, which may represent a novel prognostic and therapeutic biomarker for RCC.

LINC00886 Facilitates Hepatocellular Carcinoma Tumorigenesis by Sequestering microRNA-409-3p and microRNA-214-5p

Purpose

As the major subtype of liver cancer, hepatocellular carcinoma (HCC) suffers from high mortality and is prone to recurrence. Long non-coding RNAs (lncRNAs) are well characterized to be pivotal players contributing to HCC pathogenesis and progression. Therefore, this study intended to probe the biological functions of LINC00886 in hepatocarcinogenesis.

Patients and Methods

Quantitative real-time polymerase chain reaction (qRT-PCR) was applied to analysis of LINC00886, microRNA-409-3p (miR-409-3p), microRNA-214-5p (miR-214-5p), RAB10 and E2F2 expression. Subcellular localization of LINC00886 was identified through a fluorescent in situ hybridization (FISH) kit and a subcellular assay. Additionally, proliferated cells were determined with EdU as well as cell counting kit-8 (CCK-8) assays. Scratch and Transwell assays were applied to detect migratory and invasive cells. Apoptotic cells were measured via TUNEL staining assay. Furthermore, targeted binding between LINC00886 and miR-409-3p or miR-214-5p was validated utilizing dual-luciferase reporter assays. RAB10, E2F2 and NF-κB signaling-associated protein levels were evaluated utilizing Western blot.

Results

LINC00886, RAB10 and E2F2 levels were aberrantly increased, with the abnormal expressed decline of miR-409-3p and miR-214-5p, in HCC tissues, cells and peripheral blood mononuclear cells (PBMCs). Silencing LINC00886 attenuated the proliferative, migratory, invasive, and anti-apoptotic potential of HCC cells, while LINC00886 overexpression proceeded in the contrary direction. Mechanistically, miR-409-3p and miR-214-5p were validated as binding targets for LINC00886 and inverted the biological functions of LINC00886 during HCC progression. Furthermore, the LINC00886-miR-409-3p/miR-214-5p axis could regulate RAB10 and E2F2 expression via mediating NF-κB pathway activation in hepatocarcinogenesis.

Conclusion

Our findings indicated that LINC00886 facilitated HCC progression via absorbing miR-409-3p or miR-214-5p to upregulate RAB10 and E2F2 through activation of NF-κB pathway, offering a promising novel target for HCC therapy.

Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application

Renal cell carcinoma (RCC) is a major pathological type of kidney cancer and is one of the most common malignancies worldwide. The unremarkable symptoms of early stages, proneness to postoperative metastasis or recurrence, and low sensitivity to radiotherapy and chemotherapy pose a challenge for the diagnosis and treatment of RCC. Liquid biopsy is an emerging test that measures patient biomarkers, including circulating tumor cells, cell-free DNA/cell-free tumor DNA, cell-free RNA, exosomes, and tumor-derived metabolites and proteins. Owing to its non-invasiveness, liquid biopsy enables continuous and real-time collection of patient information for diagnosis, prognostic assessment, treatment monitoring, and response evaluation. Therefore, the selection of appropriate biomarkers for liquid biopsy is crucial for identifying high-risk patients, developing personalized therapeutic plans, and practicing precision medicine. In recent years, owing to the rapid development and iteration of extraction and analysis technologies, liquid biopsy has emerged as a low cost, high efficiency, and high accuracy clinical detection method. Here, we comprehensively review liquid biopsy components and their clinical applications over the past 5 years. Additionally, we discuss its limitations and predict its future prospects.

A review on the role of long non-coding RNA and microRNA network in clear cell renal cell carcinoma and its tumor microenvironment

Renal cell carcinoma (RCC) is the second lethal urogenital malignancy with the increasing incidence and mortality in the world. Clear cell renal cell carcinoma (ccRCC) is one major subtype of RCC, which accounts for about 70 to 80% of all RCC cases. Although many innovative therapeutic options have emerged during the last few decades, the efficacy of these treatments for ccRCC patients is very limited. To date, the prognosis of patients with advanced or metastatic ccRCC is still poor. The 5-year survival rate of these patients remains less than 10%, which mainly attributes to the complexity and heterogeneity of the tumor microenvironment (TME). It has been demonstrated that long non-coding RNAs (lncRNAs) perform an indispensable role in the initiation and progression of various tumors. They mostly function as sponges for microRNAs (miRNAs) to regulate the expression of target genes, finally influence the growth, metastasis, apoptosis, drug resistance and TME of tumor cells. However, the role of lncRNA/miRNA/mRNA axis in the TME of ccRCC remains poorly understood. In this review, we summarized the biological function of lncRNA/miRNA/mRNA axis in the pathogenesis of ccRCC, then discussed how lncRNA/miRNA/mRNA axis regulate the TME, finally highlighted their potential application as novel biomarkers and therapeutic targets for ccRCC.

CDKN2B-AS1 is overexpressed in polycystic ovary syndrome and sponges miR-181a to promote granulosa cell proliferation

MiR-181a suppresses the proliferation of mouse granulosa cells, which participate in polycystic ovary syndrome (PCOS), suggesting the potential role of miR-181a in PCOS. Our bioinformatics analysis revealed that miR-181a could bind CDKN2B-AS1, a lncRNA regulates ovarian endometriosis. This research was, therefore, conducted to explore the potential crosstalk between CDKN2B-AS1 and miR-181a in PCOS. Expression analysis of CDKN2B-AS1 and miR-181a in follicular fluid from 60 PCOS patients and 60 controls was done with reverse transcriptions-quantitative PCRs. The direct interaction between CDKN2B-AS1 and miR-181a was predicted by IntaRNA and confirmed by RNA pull-down assay. CDKN2B-AS1 in nuclear and cytoplasm of granulosa cells was detected by cellular fractionation assay. The role of CDKN2B-AS1 and miR-181a in granulosa cell proliferation was analyzed by 5-bromodeoxyuridinc assay. In this study, CDKN2B-AS1 was expressed in high amounts in PCOS, whereas miR-181a was downregulated in PCOS, CDKN2B-AS1 was detected in both nucleus and cytoplasm. Although CDKN2B-AS1 and miR-181a were not closely correlated, CDKN2B-AS1 directly interacted with miR-181a. CDKN2B-AS1 and miR-181a overexpression failed to affect the expression of each other. In addition, the inhibitory effect of miR-181a on granulosa cell proliferation was attenuated by CDKN2B-AS1. CDKN2B-AS1 is overexpressed in PCOS and may sponge miR-181a to promote granulosa cell proliferation. Our study characterized a novel CDKN2B-AS1/miR-181a pathway in PCOS. This novel pathway may serve as a potential target to treat PCOS.

Cuproptosis-Related LncRNA-Based Prediction of the Prognosis and Immunotherapy Response in Papillary Renal Cell Carcinoma

Cuproptosis, a new cell death pattern, is promising as an intervention target to treat tumors. Abnormal long non-coding RNA (lncRNA) expression is closely associated with the occurrence and development of papillary renal cell carcinoma (pRCC). However, cuproptosis-related lncRNAs (CRLs) remain largely unknown as prognostic markers for pRCC. We aimed to forecast the prognosis of pRCC patients by constructing models according to CRLs and to examine the correlation between the signatures and the inflammatory microenvironment. From the Cancer Genome Atlas (TCGA), RNA sequencing, genomic mutations and clinical data of TCGA-KIRP (Kidney renal papillary cell carcinoma) were analyzed. Randomly selected pRCC patients were allotted to the training and testing sets. To determine the independent prognostic impact of the training characteristic, the least absolute shrinkage and selection operator (LASSO) algorithm was utilized, together with univariate and multivariate Cox regression models. Further validation was performed in the testing and whole cohorts. External datasets were utilized to verify the prognostic value of CRLs as well. The CRLs prognostic features in pRCC were established based on the five CRLs (AC244033.2, LINC00886, AP000866.1, MRPS9-AS1 and CKMT2-AS1). The utility of CRLs was evaluated and validated in training, testing and all sets on the basis of the Kaplan-Meier (KM) survival analysis. The risk score could be a robust prognostic factor to forecast clinical outcomes for pRCC patients by the LASSO algorithm and univariate and multivariate Cox regression. Analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) data demonstrated that differentially expressed genes (DEGs) are primarily important for immune responses and the PI3K-Akt pathway. Arachidonic acid metabolism was enriched in the high-risk set by Gene Set Enrichment Analysis (GSEA). In addition, Tumor Immune Dysfunction and Exclusion (TIDE) analysis suggested that there was a high risk of immune escape in the high-risk cohort. The immune functions of the low- and high-risk sets differed significantly based on immune microenvironment analysis. Finally, four drugs were screened with a higher sensitivity to the high-risk set. Taken together, a novel model according to five CRLs was set up to forecast the prognosis of pRCC patients, which provides a potential strategy to treat pRCC by a combination of cuproptosis and immunotherapy.

The Role of Long Noncoding RNA (lncRNAs) Biomarkers in Renal Cell Carcinoma

Renal cell carcinoma is one of the common cancers whose incidence and mortality are continuously growing worldwide. Initially, this type of tumour is usually asymptomatic. Due to the lack of reliable diagnostic markers, one-third of ccRCC patients already have distant metastases at the time of diagnosis. This underlines the importance of establishing biomarkers that would enable the prediction of the disease's course and the risk of metastasis. LncRNA, which modulates genes at the epigenetic, transcriptional, and post-transcriptional levels, appears promising. The actions of lncRNA involve sponging and sequestering target miRNAs, thus affecting numerous biological processes. Studies have confirmed the involvement of RNAs in various diseases, including RCC. In this review, we focused on MALAT1 (a marker of serious pathological changes and a factor in the promotion of tumorigenesis), RCAT1 (tumour promoter in RCC), DUXAP9 (a plausible marker of localized ccRCC), TCL6 (exerting tumour-suppressive effects in renal cancer), LINC00342 (acting as an oncogene), AGAP2 Antisense1 (plausible predictor of RCC progression), DLEU2 (factor promoting tumours growth via the regulation of epithelial-mesenchymal transition), NNT-AS1 (sponge of miR-22 contributing to tumour progression), LINC00460 (favouring ccRCC development and progression) and Lnc-LSG1 (a factor that may stimulate ccRCC metastasis).

LINC00536 Promotes Breast Cancer Progression by Regulating ROCK1 via Sponging of miR-214-5p

Accumulating evidence has shown that long noncoding RNAs (lncRNAs) play a significant role in regulating gene expression and participating in the progression of various malignancies. In our study, by analyzing data from The Cancer Genome Atlas (TCGA), LINC00536 was found to be highly expressed in breast cancer (BC) tissues, but its function and clinical significance in BC are still unknown. Therefore, we aimed to explore the role and molecular mechanism of LINC00536 in BC. We collected human BC tissue specimens and validated that LINC00536 was overexpressed in BC tissues. Increased LINC00536 expression was associated with advanced TNM stage, larger tumor diameter, lymph node metastasis and poor prognosis in patients with BC. Univariate and multivariate Cox regression analyses showed that high LINC00536 expression was an independent prognostic risk factor for overall survival in BC patients. Furthermore, quantitative reverse transcription PCR (qRT-PCR) showed that LINC00536 was upregulated in BC cell lines. Then, we confirmed that LINC00536 silencing-inhibited BC cell proliferation, migration, and invasion and led to cell cycle arrest in vitro. Animal experiments showed that knockdown of LINC00536 expression suppressed tumorigenesis in vivo. Mechanistically, LINC00536 serves as a ceRNA for miR-214-5p, increasing the expression of ROCK1, which acts as a tumor promoter in BC. Rescue assays revealed that miR-214-5p inhibition or ROCK1 overexpression could neutralize the suppressive effects of LINC00536 knockdown on cell proliferation, migration and invasion. Our data indicated that LINC00536 accelerates BC progression by regulating the miR-214-5p/ROCK1 pathway, which might provide a new perspective to investigate the development process of BC.

lncRNA MIR4435-2HG Accelerates the Development of Bladder Cancer through Enhancing IQGAP3 and CDCA5 Expression

Background. Bladder cancer (BCa) is one of the most prevalent cancers occurring in the urinary system. Long noncoding RNAs (lncRNAs), in recent years, have emerged as crucial regulators in various biological processes of tumors. Aim. To identify the role of MIR4435-2 host gene (MIR4435-2HG) and uncover its molecular mechanism in BCa. Methods. Firstly, quantitative real-time PCR (RT-qPCR) analysis was used to examine MIR4435-2HG expression in BCa cells. Cell Counting Kit-8 (CCK-8), 5-ethynyl-2 $\prime$ -deoxyuridine (EdU), wound healing, and transwell assays were implemented to identify the role of MIR4435-2HG in BCa. RNA-binding protein immunoprecipitation (RIP), RNA pull down, and luciferase reporter assays were applied to explore the potential mechanism of MIR4435-2HG in BCa. Results. MIR4435-2HG was highly expressed in BCa. Moreover, MIR4435-2HG silencing abrogated BCa cell proliferation, migration, and invasion. In terms of underlying mechanism, MIR44352HG acted as a microRNA-2467-3p (miR-2467-3p) sponge to control the expression of IQ motif containing GTPase activating protein 3 (IQGAP3) and cell division cycle associated 5 (CDCA5), resulting in activation of the rat sarcoma virus (Ras)/rapidly accelerated fibrosarcoma (Raf)/mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) and PI3K/AKT/mTOR signaling pathways. Conclusion. MIR4435-2HG involves in the progression of BCa, which might provide novel insights for BCa treatment.

MicroRNAs as Potential Tools for Predicting Cancer Patients’ Susceptibility to SARS-CoV-2 Infection and Vaccination Response

Coronavirus disease (COVID-19) is an infectious disease that is caused by a highly contagious and severe acute respiratory syndrome—coronavirus 2 (SARS-CoV-2). This infection started to spread across the world in 2019 and rapidly turned into a global pandemic, causing an urgent necessity for treatment strategies development. The mRNA vaccines against SARS-CoV-2 can trigger an immune response, providing genetic information that allows the production of spike glycoproteins. MiRNAs play a crucial role in diverse key cellular processes, including antiviral defense. Several miRNAs are described as key factors in SARS-CoV-2 human infection through the regulation of ACE2 levels and by the inhibition of SARS-CoV-2 replication and spike expression. Consequently, these molecules have been considered as highly promising biomarkers. In numerous human malignancies, it has been recognized that miRNAs expression is dysregulated. Since miRNAs can target SARS-CoV-2-associated mRNAs, in cancer patients, the deregulation of these molecules can impair the immune response to the vaccines. Therefore, in this review, we propose a miRNA profile of seven SARS-CoV-2-related miRNAs, namely miR-214, miR-98-5p, miR-7-5p, miR-24-3p, miR-145-5p, miR-223-3p and miR-15b-5p, that are deregulated in a high number of cancers and have the potential to be used as prognostic biomarkers to stratify cancer patients.

A Novel Machine Learning 13-Gene Signature: Improving Risk Analysis and Survival Prediction for Clear Cell Renal Cell Carcinoma Patients

Simple Summary

Clear cell renal cell carcinoma is a type of kidney cancer which comprises the majority of all renal cell carcinomas. Many efforts have been made to identify biomarkers which could help healthcare professionals better treat this kind of cancer. With extensive public data available, we conducted a machine learning study to determine a gene signature that could indicate patient survival with high accuracy. Through the min-Redundancy and Max-Relevance algorithm we generated a signature of 13 genes highly correlated with patient outcomes. These findings reveal potential strategies for personalized medicine in the clinical practice.

Abstract

Patients with clear cell renal cell carcinoma (ccRCC) have poor survival outcomes, especially if it has metastasized. It is of paramount importance to identify biomarkers in genomic data that could help predict the aggressiveness of ccRCC and its resistance to drugs. Thus, we conducted a study with the aims of evaluating gene signatures and proposing a novel one with higher predictive power and generalization in comparison to the former signatures. Using ccRCC cohorts of the Cancer Genome Atlas (TCGA-KIRC) and International Cancer Genome Consortium (ICGC-RECA), we evaluated linear survival models of Cox regression with 14 signatures and six methods of feature selection, and performed functional analysis and differential gene expression approaches. In this study, we established a 13-gene signature (AR, AL353637.1, DPP6, FOXJ1, GNB3, HHLA2, IL4, LIMCH1, LINC01732, OTX1, SAA1, SEMA3G, ZIC2) whose expression levels are able to predict distinct outcomes of patients with ccRCC. Moreover, we performed a comparison between our signature and others from the literature. The best-performing gene signature was achieved using the ensemble method Min-Redundancy and Max-Relevance (mRMR). This signature comprises unique features in comparison to the others, such as generalization through different cohorts and being functionally enriched in significant pathways: Urothelial Carcinoma, Chronic Kidney disease, and Transitional cell carcinoma, Nephrolithiasis. From the 13 genes in our signature, eight are known to be correlated with ccRCC patient survival and four are immune-related. Our model showed a performance of 0.82 using the Receiver Operator Characteristic (ROC) Area Under Curve (AUC) metric and it generalized well between the cohorts. Our findings revealed two clusters of genes with high expression (SAA1, OTX1, ZIC2, LINC01732, GNB3 and IL4) and low expression (AL353637.1, AR, HHLA2, LIMCH1, SEMA3G, DPP6, and FOXJ1) which are both correlated with poor prognosis. This signature can potentially be used in clinical practice to support patient treatment care and follow-up.

Actinidia chinensis Planch Root extract suppresses the growth and metastasis of hypopharyngeal carcinoma by inhibiting E2F Transcription Factor 1-mediated MNX1 antisense RNA 1

Increasing evidence has shown that traditional Chinese medicines and their bioactive components exert an anti-tumor effect, representing a novel treatment strategy. Actinidia chinensis Planch Root extracts (acRoots) have been reported to repress cancer cell proliferation and metastasis. The effect of acRoots on hypopharyngeal carcinoma progression was explored in this study. Firstly, data from MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) and colony formation assays showed that incubation with accRoots reduced cell proliferation of hypopharyngeal carcinoma cells. Moreover, acRoots promoted the cell apoptosis of hypopharyngeal carcinoma. Secondly, cell migration and invasion of hypopharyngeal carcinoma cells were suppressed by acRoots. Thirdly, E2F1 (E2F Transcription Factor 1) and lncRNA MNX1-AS1 (MNX1 antisense RNA 1) were up-regulated in hypopharyngeal carcinoma tissues, and reduced in hypopharyngeal carcinoma cells post acRoots incubation. Overexpression of E2F1 attenuated acRoots-induced decrease in MNX1-AS1 in hypopharyngeal carcinoma cells. Lastly, administration with acRoots retarded in vivo hypopharyngeal carcinoma growth through down-regulation of E2F1-mediated MNX1-AS1. In conclusion, acRoots exerted tumor-suppressive role in hypopharyngeal carcinoma through inhibition of E2F1-mediated MNX1-AS1.

Identification of the Expression and Clinical Significance of E2F Family in Clear Cell Renal Cell Carcinoma

Background

Multiple studies have identified that E2F transcriptions act as important regulators for the tumorigenesis and progression of several human cancers. However, little is known about the function of E2Fs in clear cell renal cell carcinoma (ccRCC).

Methods

We firstly investigated the expression levels, genetic alteration, and biological function of E2Fs in patients with ccRCC and the connections between the immune cell infiltration and the overall survivals of ccRCC patients with the E2Fs expression levels based on UALCAN, The Cancer Genome Atlas database, Gene Expression Profiling Interactive Analysis, TIMER, STRING, GSCALite and cBioPortal databases.

Results

Results revealed that the expression levels of E2F1/2/3/4/6/7/8 were markedly upregulated in patients with ccRCC, while the expression of E2F5 displayed an opposite trend. We also experimentally validated the overexpression of E2F3/4/7 in human ccRCC tissues and ccRCC cell lines. Furthermore, the high E2F1/2/3/4/7/8 expression levels were clearly associated with worse pathological characteristics of ccRCC, including high pathological stage, poor molecular subtypes and high tumor grade. Meanwhile, high expression levels of E2F1/2/4/7/8 were evidently associated with worse overall survivals (OSs) and progression-free survivals (PFSs) of patients harboring ccRCC. Univariate and multivariate analyses illustrated that the expressions of E2F4/5/7 were independent factors associated with the OSs and PFSs of patients with ccRCC. Meanwhile, the mutations in E2Fs were also significantly related to poor OSs and PFSs of patients with ccRCC. Mechanically, the E2Fs genes synergistically promoted the progression of ccRCC by accelerating the cell cycle and inhibiting DNA damage response and apoptosis after performing the protein structure, functional enrichment, and PPI network analyses. In addition, E2Fs genes were also significantly associated with tumor immune cells infiltration and the drug sensitivity in ccRCC.

Conclusion

As a result, E2F4/7 were highly expressed in ccRCC and significantly associated with worse pathological characteristics of ccRCC, including high pathological stage, poor molecular subtypes and high tumor grade, tumor immune cell infiltration, and drug sensitivity, consequently translating into poor OSs and PFSs of patients with ccRCC. Our results indicated that E2F4/7 could be potential biomarkers and therapeutic targets of ccRCC patients.

Current Research Progress of the Role of LncRNA LEF1-AS1 in a Variety of Tumors

Long non-coding RNAs (lncRNA), as key regulators of cell proliferation and death, are involved in the regulation of various processes in the nucleus and cytoplasm, involving biological developmental processes in the fields of immunology, neurobiology, cancer, and stress. There is great scientific interest in exploring the relationship between lncRNA and tumors. Many researches revealed that lymph enhancer-binding factor 1-antisense RNA 1 (LEF1-AS1), a recently discovered lncRNA, is downregulated in myeloid malignancy, acting mainly as a tumor suppressor, while it is highly expressed and carcinogenic in glioblastoma (GBM), lung cancer, hepatocellular carcinoma (HCC), osteosarcoma, colorectal cancer (CRC), oral squamous cell carcinoma (OSCC), prostatic carcinoma, retinoblastoma, and other malignant tumors. Furthermore, abnormal LEF1-AS1 expression was associated with tumorigenesis, development, survival, and prognosis via the regulation of target genes and signaling pathways. This review summarizes the existing data on the expression, functions, underlying mechanism, relevant signaling pathways, and clinical significance of LEF1-AS1 in cancer. It is concluded that LEF1-AS1 can serve as a novel biomarker for the diagnosis and prognosis of various tumors, thus deserves further attention in the future.

Identification of N6-methylandenosine related LncRNAs biomarkers associated with the overall survival of osteosarcoma

PURPOSE

Osteosarcoma (OS) is a differentiation disease caused by the genetic and epigenetic differentiation of mesenchymal stem cells into osteoblasts. OS is a common, highly malignant tumor in children and adolescents. Fifteen to 20 % of the patients find distant metastases at their first visit. The purpose of our study was to identify biomarkers for tracking the prognosis and treatment of OS to improve the survival rate of patients.

MATERIALS AND METHODS

In this study, which was based on Therapeutically Applicable Research to Generate Effective Treatments (TARGET), we searched for m6A related lncRNAs in OS. We constructed a network between lncRNA and m6A, and built an OS prognostic risk model.

RESULTS

We identified 14,581 lncRNAs by using the dataset from TARGET. We obtained 111 m6A-related lncRNAs through a Pearson correlation analysis. A network was built between lncRNA and m6A genes. Eight m6A-related lncRNAs associated with survival were identified through a univariate Cox analysis. A selection operator (LASSO) Cox regression was used to construct a prognostic risk model with six genes (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) obtained through least absolute shrinkage. We also discovered upregulated levels of DLGAP1-AS2 and m6A methylation in osteosarcoma tissues/cells compared with normal tissues/osteoblasts cells.

CONCLUSION

We constructed a risk score prognosis model of m6A-related lncRNAs (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) using the dataset downloaded from TRAGET. We verified the value of the model by dividing all samples into test groups and training groups. However, the role of m6A-related lncRNAs in osteosarcoma needs to be further researched by cell and in vivo studies.

Long noncoding RNA SNHG4: a novel target in human diseases

Recently, long noncoding RNAs (lncRNAs) have attracted great attention from researchers. LncRNAs are non-protein-coding RNAs of more than 200 nucleotides in length. Multiple studies have been published on the relationship between lncRNA expression and the progression of human diseases. LncRNA small nucleolar RNA host gene 4 (SNHG4), a member of the lncRNA SNHG family, is abnormally expressed in a variety of human diseases, including gastric cancer, renal cell carcinoma, glioblastoma, neuroblastoma, prostate cancer, colorectal cancer, osteosarcoma, cervical cancer, liver cancer, lung cancer, non-small-cell lung cancer, neonatal pneumonia, diabetic retinopathy, neuropathic pain, acute cerebral infarction, acute myeloid leukaemia, and endometriosis. In this paper, the structure of SNHG4 is first introduced, and then studies in humans, animal models and cells are summarized to highlight the expression and function of SNHG4 in the above diseases. In addition, the specific mechanism of SNHG4 as a competing endogenous RNA (ceRNA) is discussed. The findings indicate that SNHG4 can be used as a biomarker for disease prognosis evaluation and as a potential target for disease diagnosis and treatment.