The LncRNA MIAT is identified as a regulator of stemness-associated transcript in glioma

MIAT: A pivotal oncogenic long noncoding RNA tunning the hallmarks of solid malignancies

Long non-coding RNAs (LncRNAs) have emerged as intriguing players in cellular regulation, challenging the traditional view of non-coding RNAs as mere "dark genome". Non-coding DNA makes up most of the human genome and plays a pivotal role in cancer development. These RNA molecules, which do not code for proteins, have captivated researchers with their diverse and crucial roles in gene regulation, chromatin dynamics, and other cellular processes. In several physiological and pathological circumstances, lncRNAs serve critical functions. This review will tackle the complex function of the lncRNA myocardial infarction-associated transcript (MIAT) in various solid malignancies. A special emphasis would be directed on the correlation between cancer patients' clinicopathological features and the expression profile of MIAT. MIAT is a oncogenic regulator in many malignant tumors, where it can control the growth, invasion, metastasis, and resistance to death of cells. As a result, MIAT is thought to be a possible biomarker and therapeutic target for cancer patients. The biological functions, mechanisms and potential clinical implications of MIAT during carcinogenesis and finally the current possible therapeutic approaches targeting MIAT are also outlined in this review.

Prognostic modeling of disulfidptosis gene-associated lncRNAs aids in identifying the tumor microenvironment and guiding the selection of therapy

INTRODUCTION

Gliomas, a type of malignant tumor, are marked by a short survival period and an unfavorable prognosis. Disulfide stress, which arises from an overabundance of intracellular cystine, can initiate disulfidoptosis, an emerging form of cell death. The link between gliomas and disulfidoptosis has not been extensively explored. This study breaks new ground by investigating the correlation between glioma prognosis and lncRNAs associated with disulfidoptosis, with the aim of improving glioma treatment strategies.

METHODS

We analyzed 10 long non-coding RNAs (lncRNAs) co-expressed with disulfidoptosis genes, retrieved clinical information and gene expression profiles from glioma and normal groups in the TCGA database, and developed a prognostic model for lncRNAs based on this data. The receiver operating characteristic curve (ROC) was used to evaluate and validate the model's reliability. Furthermore, the Kaplan-Meier survival curve was employed to assess the disparity in overall survival (OS) among patients with varying risk scores. We also examined the tumor microenvironment (TME), immune cell infiltration, immune-related functions, tumor mutational burden (TMB), and OncoPredict in samples with differing risk scores. To confirm the expression variations of genes associated with prognostic models in cell lines, quantitative polymerase chain reaction (qPCR) was employed.

RESULTS

Eleven long non-coding RNAs (lncRNAs) were identified for constructing prognostic models by analyzing lncRNAs associated with disulfidoptosis genes using Cox regression and LASSO regression analyses. The study's findings indicate that these 11 key lncRNAs serve as independent predictors of overall survival (OS) in glioma patients. Moreover, the frequency with which patients of varying risk scores opt for immune checkpoint blockade (ICB) therapy and chemotherapy not only differs but also their responses to these treatments are significantly distinct, suggesting that the risk score could be a predictive factor for treatment response.

CONCLUSIONS

This research sheds light on the characteristics of disulfidoptosis in glioma, revealing that patterns of disulfidoptosis in patients can be effectively assessed using a risk score. Consequently, the judicious application of this prognostic model can significantly inform clinical treatment strategies and precision medicine for glioma, potentially improving patient outcomes.

Deciphering the role of LOC124905135-related non-coding RNA cluster in human cancers: A comprehensive review

Non-coding RNAs (ncRNAs), especially microRNAs (miRNAs) and long ncRNAs (lncRNAs), are essential regulators of processes, such as the cell cycle and apoptosis. In addition to interacting with intracellular complexes and participating in diverse molecular pathways, ncRNAs can be used as clinical diagnostic biomarkers and therapeutic targets for fighting cancer. Studying ncRNA gene clusters is crucial for understanding their role in cancer and developing new treatments. LOC124905135 is a protein-coding gene encoding a collagen alpha-1(III) chain-like protein, and also acts as a gene for several ncRNAs, including miR-3619, PRR34 antisense RNA 1 (PRR34-AS1), PRR34, long intergenic ncRNA 2939 (LINC02939), LOC112268288, and MIRLET7BHG. It also serves as a host gene for three miRNAs (hsa-let7-A3, hsa-miR-4763, and hsa-let-7b). Notably, the ncRNAs derived from this particular genomic region significantly affect various cell functions, including the cell cycle and apoptosis. This cluster of ncRNAs is dysregulated in several types of cancer, exhibiting mutations, alterations in copy number, and being subject to DNA methylation and histone modification. In summary, the ncRNAs derived from the LOC124905135 cluster could be used as targets for diagnosis, therapy monitoring, and drug discovery in human cancers.

Identification of RBM15 as a prognostic biomarker in prostate cancer involving the regulation of prognostic m6A-related lncRNAs

BACKGROUND

Long noncoding RNAs (lncRNAs) and N6-methyladenosine (m6A) modification of RNA play pivotal roles in tumorigenesis and cancer progression. However, knowledge regarding the expression patterns of m6A-related lncRNAs and their corresponding m6A regulators in prostate cancer (PCa) is limited. This study aimed to delineate the landscape of m6A-related lncRNAs, develop a predictive model, and identify the critical m6A regulators of prognostic lncRNAs in PCa.

METHODS

Clinical and transcriptome data of PCa patients were downloaded from The Cancer Genome Atlas (TCGA) database. Prognostic m6A-related lncRNAs were subsequently identified through Pearson correlation and univariate Cox regression analyses. The prognostic lncRNAs were clustered into two groups by consensus clustering analysis, and a risk signature model was constructed using least absolute shrinkage and selection operator (LASSO) regression analysis of the lncRNAs. This model was evaluated using survival, clinicopathological, and immunological analyses. Furthermore, based on the constructed lncRNA-m6A regulatory network and RT-qPCR results, RBM15 was identified as a critical regulator of m6A-related lncRNAs. The biological roles of RBM15 in PCa were explored through bioinformatics analysis and biological experiments.

RESULTS

Thirty-four prognostic m6A-related lncRNAs were identified and categorized into two clusters with different expression patterns and survival outcomes in PCa patients. Seven m6A lncRNAs (AC105345.1, AL354989.1, AC138028.4, AC022211.1, AC020558.2, AC004076.2, and LINC02666) were selected to construct a risk signature with robust predictive ability for overall survival and were correlated with clinicopathological characteristics and the immune microenvironment of PCa patients. Among them, LINC02666 and AC022211.1 were regulated by RBM15. In addition, RBM15 expression correlated with PCa progression, survival, and the immune response. Patients with elevated RBM15 expression were more susceptible to the drug AMG-232. Moreover, silencing RBM15 decreased the viability of PCa cells and promoted apoptosis.

CONCLUSION

RBM15 is involved in the regulation of prognostic lncRNAs in the risk signature and has a robust predictive ability for PCa, making it a promising biomarker in PCa.

Long non-coding RNA MIAT serves as a biomarker of fragility fracture and promotes fracture healing

BACKGROUND

Fragility fracture is common in the elderly. Osteoblast differentiation is essential for bone healing and regeneration. Expression pattern of long non-coding RNA MIAT during fracture healing was examined, and its role in osteoblast differentiation was investigated.

METHODS

90 women with simple osteoporosis and 90 women with fragility fractures were included. Another 90 age-matched women were set as the control group. mRNA levels were tested using RT-qPCR. Cell viability was detected via CCK-8, and osteoblastic biomarkers, including ALP, OCN, Collagen I, and RUNX2 were tested via ELISA. The downstream miRNAs and genes targeted by MIAT were predicted by bioinformatics analysis, whose functions and pathways were annotated via GO and KEGG analysis.

RESULTS

Serum MIAT was upregulated in osteoporosis women with high accuracy of diagnostic efficacy. Serum MIAT was even elevated in the fragility fracture group, but decreased in a time manner after operation. MIAT knockdown promoted osteogenic proliferation and differentiation of MC3T3-E1, but the influences were reversed by miR-181a-5p inhibitor. A total of 137 overlapping target genes of miR-181a-5p were predicted based on the miRDB, TargetScan and microT datasets, which were mainly enriched for terms related to signaling pathways regulating pluripotency of stem cells, cellular senescence, and osteoclast differentiation.

CONCLUSIONS

LncRNA MIAT serves as a promising biomarker for osteoporosis, and promotes osteogenic differentiation via targeting miR-181a-5p.

Puzzling out the role of MIAT LncRNA in hepatocellular carcinoma

A non-negligible part of our DNA has been proven to be transcribed into non-protein coding RNA and its intricate involvement in several physiological processes has been highly evidenced. The significant biological role of non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) has been variously reported. In the current review, the authors highlight the multifaceted role of myocardial infarction-associated transcript (MIAT), a well-known lncRNA, in hepatocellular carcinoma (HCC). Since its discovery, MIAT has been described as a regulator of carcinogenesis in several malignant tumors and its overexpression predicts poor prognosis in most of them. At the molecular level, MIAT is closely linked to the initiation of metastasis, invasion, cellular migration, and proliferation, as evidenced by several in-vitro and in-vivo models. Thus, MIAT is considered a possible theranostic agent and therapeutic target in several malignancies. In this review, the authors provide a comprehensive overview of the underlying molecular mechanisms of MIAT in terms of its downstream target genes, interaction with other classes of ncRNAs, and potential clinical implications as a diagnostic and/or prognostic biomarker in HCC.

Genome-wide investigation of lncRNAs revealed their tight association with gastric cancer

BACKGROUND

Gastric cancer (GC) is a significant health issue globally, ranking as the fifth most common cancer with over 10,000 new cases reported annually. Long non-coding RNA (lncRNA) has emerged as a critical player in cellular functions, influencing GC's development, growth, metastasis, and prognosis. However, our understanding of lncRNA's role in the pathogenesis of GC remains limited. Therefore, it is particularly important to explore the relationship between lncRNA and gastric cancer.

METHODS

we conducted a comprehensive analysis of RNA sequencing data from the GEO database and stomach adenocarcinoma (STAD) data from the TCGA database to identify lncRNAs that exhibit altered expression levels in GC and the mechanisms underlying lncRNA-mediated transcription and post-transcriptional regulation were explored.

RESULTS

This study uncovered 94 lncRNAs with differential expression and, through co-expression analysis, linked these to 1508 differentially expressed genes (DEGs). GO functional enrichment analysis highlighted that these DEGs are involved in critical pathways, such as cell adhesion and the positive regulation of cell migration. By establishing a lncRNA-miRNA-mRNA regulatory network, we found that the ceRNA mechanism, particularly involving RP11-357H14.17 and CTD-2377D24.4, could play a role in GC progression. Experimental validation of selected differentially expressed lncRNAs and mRNAs (including RP11-357H14.17-CLDN1, BBOX1, TRPM2-AS, CLDN1, PLAU, HOXB7) confirmed the RNA-seq results.

CONCLUSIONS

Overall, our findings highlight the critical role of the lncRNA-mRNA regulatory network in the development and progression of GC, offering potential biomarkers for diagnosis and targets for innovative treatment strategies.

lncRNA Biomarkers of Glioblastoma Multiforme

Long noncoding RNAs (lncRNAs) are RNA molecules of 200 nucleotides or more in length that are not translated into proteins. Their expression is tissue-specific, with the vast majority involved in the regulation of cellular processes and functions. Many human diseases, including cancer, have been shown to be associated with deregulated lncRNAs, rendering them potential therapeutic targets and biomarkers for differential diagnosis. The expression of lncRNAs in the nervous system varies in different cell types, implicated in mechanisms of neurons and glia, with effects on the development and functioning of the brain. Reports have also shown a link between changes in lncRNA molecules and the etiopathogenesis of brain neoplasia, including glioblastoma multiforme (GBM). GBM is an aggressive variant of brain cancer with an unfavourable prognosis and a median survival of 14-16 months. It is considered a brain-specific disease with the highly invasive malignant cells spreading throughout the neural tissue, impeding the complete resection, and leading to post-surgery recurrences, which are the prime cause of mortality. The early diagnosis of GBM could improve the treatment and extend survival, with the lncRNA profiling of biological fluids promising the detection of neoplastic changes at their initial stages and more effective therapeutic interventions. This review presents a systematic overview of GBM-associated deregulation of lncRNAs with a focus on lncRNA fingerprints in patients' blood.

Integrated analysis reveals the regulatory mechanism of the neddylation inhibitor MLN4924 on the metabolic dysregulation in rabbit granulosa cells

BACKGROUND

Neddylation, an important post-translational modification (PTM) of proteins, plays a crucial role in follicular development. MLN4924 is a small-molecule inhibitor of the neddylation-activating enzyme (NAE) that regulates various biological processes. However, the regulatory mechanisms of neddylation in rabbit ovarian cells have not been emphasized. Here, the transcriptome and metabolome profiles in granulosa cells (GCs) treated with MLN4924 were utilized to identify differentially expressed genes, followed by pathway analysis to precisely define the altered metabolisms.

RESULTS

The results showed that 563 upregulated and 910 downregulated differentially expressed genes (DEGs) were mainly enriched in pathways related to cancer, cell cycle, PI3K-AKT, progesterone-mediated oocyte maturation, and PPAR signaling pathway. Furthermore, we characterized that MLN4924 inhibits PPAR-mediated lipid metabolism, and disrupts the cell cycle by promoting the apoptosis and proliferation of GCs. Importantly, we found the reduction of several metabolites in the MLN4924 treated GCs, including glycerophosphocholine, arachidic acid, and palmitic acid, which was consistent with the deregulation of PPAR signaling pathways. Furthermore, the increased metabolites included 6-Deoxy-6-sulfo-D-glucono-1,5-lactone and N-Acetyl-D-glucosaminyldiphosphodolichol. Combined with transcriptome data analyses, we identified genes that strongly correlate with metabolic dysregulation, particularly those related to glucose and lipid metabolism. Therefore, neddylation inhibition may disrupt the energy metabolism of GCs.

CONCLUSIONS

These results provide a foundation for in-depth research into the role and molecular mechanism of neddylation in ovary development.