RNA Network Research Articles

Exploring the ceRNA network involving AGAP2-AS1 as a novel biomarker for preeclampsia

Preeclampsia (PE) is an important research subject in obstetrics. Nevertheless, the underlying mechanisms of PE remain elusive. PE-related expression datasets (GSE96983, GSE96984 and GSE24129) were downloaded from the Gene Expression Omnibus (GEO) database. Firstly, the differentially expressed messenger RNAs (DE-mRNAs), DE-microRNA (DE-miRNAs) and DE-long non-coding RNA (DE-lncRNAs) between PE and control cohorts were identified, and the ceRNA network was constructed. Then candidate hub genes were obtained through five algorithms by the protein-protein intersection (PPI) network of the mRNAs. Further, five hub genes were identified by receiver operating characteristic (ROC) curve and gene expression profiles: DAXX, EFNB1, NCOR2, RBBP4 and SOCS1. The function of 5 hub genes was analyzed and the interaction between drugs and hub genes was predicted. A total of 5 small molecule drugs were predicted, namely benzbromarone, 9,10-phenanthrenequinone, chembl312032, insulin and aldesleukin. AGAP2-AS1 was mainly located in exosome and cytoplasm. Agap2-as1-related regulatory subnetworks were extracted from ceRNA networks which included 41 mRNAs, 2 miRNAs and 1 lncRNA, including the regulated relationship pairs AGAP2-AS1-hsa-miR-497-5p-SRPRB, and AGAP2-AS1-hsa-miR-195-5p-RPL36. In summary, we constructed a competitive endogenous RNA (ceRNA) network to identify five potential biomarkers (DAXX, EFNB1, NCOR2, SOCS1 and RBBP4) of PE. The in-depth analysis of the AGAP2-AS1 regulatory network will help to uncover more important molecules closely related to PE and provide a scientific Reference.

Whole transcriptome sequencing of testis and epididymis reveals genes associated with sperm development in roosters

BackgroundChickens play a crucial role as the primary global source of eggs and poultry, and the quality of rooster semen significantly impacts poultry reproductive efficiency. Therefore, it is imperative to comprehend the regulatory mechanisms underlying sperm development.ResultsIn this study, we established transcriptome profiles of lncRNAs, miRNAs, and mRNAs in 3 testis tissues and 3 epididymis tissues from “Jing Hong No.1” roosters at 24, 35, and 64 weeks of age. Using the data, we conducted whole transcriptome analysis and constructed a ceRNA network. We detected 10 differentially expressed mRNAs (DEmRNAs), 33 differentially expressed lncRNAs (DElncRNAs), and 10 differentially expressed miRNAs (DEmiRNAs) in the testis, as well as 149 DEmRNAs, 12 DElncRNAs, and 10 DEmiRNAs in the epididymis. These genes were found to be involved in cell differentiation and development, as well as various signaling pathways such as GnRH, MAPK, TGF-β, mTOR, VEGF, and calcium ion pathways. Subsequently, we constructed two competing endogenous RNA (ceRNA) networks comprising DEmRNAs, DElncRNAs, and DEmiRNAs. Furthermore, we identified four crucial lncRNA-mRNA-miRNA interactions that govern specific biological processes in the chicken reproductive system: MSTRG.2423.1-gga-miR-1563-PPP3CA and MSTRG.10064.2-gga-miR-32-5p-GPR12 regulating sperm motility in the testis; MSTRG.152556.1-gga-miR-9-3p-GREM1/THYN1 governing immunomodulation in the epididymis; and MSTRG.124708.1-gga-miR-375-NDUFB9/YBX1 controlling epididymal sperm maturation and motility.ConclusionsWhole transcriptome sequencing of chicken testis and epididymis screened several key genes and ceRNA regulatory networks, which may be involved in the regulation of epididymal immunity, spermatogenesis and sperm viability through the pathways of MAPK, TGF-β, mTOR, and calcium ion. These findings contribute to our comprehensive understanding of the intricate molecular processes underlying rooster spermatogenesis, maturation and motility.

Shared and specific competing endogenous RNAs network mining in four digestive system tumors

BackgroundDigestive system malignancies, including esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), liver hepatocellular carcinoma (LIHC), and colon adenocarcinoma (COAD), pose significant global health challenges. Identifying shared and distinct regulatory mechanisms across these cancers can lead to improved therapies. This study aims to construct and compare competing endogenous RNA (ceRNA) networks across ESCA, STAD, LIHC, and COAD to identify RNA biomarkers that could serve as precision therapeutic targets to enhance clinical outcomes and advance personalized cancer care. MethodsClinical and transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to predict differentially expressed RNAs using edgeR package. The ceRNA networks were constructed using the miRcode and ENCORI databases. Functional enrichment analysis and prognostic RNA screening were performed with ConsensusPathDB and univariate Cox regression analysis. Resultswe identified 6, 88, 55, and 41 RNA biomarkers in ESCA, STAD, LIHC, and COAD, respectively. Network analysis revealed shared and specific elements, with shared nodes enriched in cell cycle and mitotic processes. Several biomarkers, including HMGB3 and RGS16 (ESCA), COL4A1 and COL6A3 (STAD), CDCA5 and CDCA8 (LIHC), and LIMK1 and OSBPL3 (COAD), were consistent with prior studies, while novel biomarkers, such as C3P1 (ESCA), P2RY6 (STAD), and N4BP2L1 and PPP1R3B (LIHC), were discovered. Based on RNA correlation analysis, 1, 23, and 2 potential ceRNA regulatory axes were identified in STAD (PVT1/miR-490-3p/HMGA2), LIHC (DLX6-AS1/miR-139-5p/TOP2A, etc.), and COAD (STRCP1 & LINC00488/miR-142-3p/GAB1), respectively. ConclusionsThis study advances the understanding of ceRNA networks in digestive cancers, highlighting RNA biomarkers with potential as therapeutic targets for personalized treatment strategies.

GUCA2A dysregulation as a promising biomarker for accurate diagnosis and prognosis of colorectal cancer

Colorectal cancer is a leading cause of global mortality and presents a significant barrier to improving life expectancy. The primary objective of this study was to discern a unique differentially expressed gene (DEG) that exhibits a strong association with colorectal cancer. By achieving this goal, the research aims to contribute valuable insights to the field of translational medicine. We performed analysis of colorectal cancer microarray and the TCGA colon adenoma carcinoma (COAD) datasets to identify DEGs associated with COAD and common DEGs were selected. Furthermore, a pan-cancer analysis encompassing 33 different cancer types was performed to identify differential genes significantly expressed only in COAD. Then, comprehensively in-silico analysis including gene set enrichment analysis, constructing Protein–Protein interaction, co-expression, and competing endogenous RNA (ceRNA) networks, investigating the correlation between tumor-immune signatures in distinct tumor microenvironment and also the potential interactions between the identified gene and various drugs was executed. Further, the candidate gene was experimentally validated in tumoral colorectal tissues and colorectal adenomatous polyps by qRael-Time PCR. GUCA2A emerged as a significant DEG specific to colorectal cancer (|log2FC|> 1 and adjusted q-value < 0.05). Importantly, GUCA2A exhibited excellent diagnostic performance for COAD, with a 99.6% and 78% area under the curve (AUC) based on TCGA-COAD and colon cancer patients. In addition, GUCA2A expression in adenomatous polyps equal to or larger than 5 mm was significantly lower compared to smaller than 5 mm. Moreover, low expression of GUCA2A significantly impacted overall patient survival. Significant correlations were observed between tumor-immune signatures and GUCA2A expression. The ceRNA constructed included GUCA2A, 8 shared miRNAs, and 61 circRNAs. This study identifies GUCA2A as a promising prognostic and diagnostic biomarker for colorectal cancer. Further investigations are warranted to explore the potential of GUCA2A as a therapeutic biomarker.

Integrating multiomics sequencing analyses uncover the key mechanisms related to oxidative stress, mitochondria, and immune cells in keloid

BackgroundThis study aimed to investigate the key molecular mechanisms underlying keloid pathogenesis by integrating oxidative stress, mitochondria, and immune cells. MethodsTranscriptome sequencing (mRNA, lncRNA, and circRNA expression data), proteomic sequencing, and small RNA sequencing analyses of lesional and non-lesional skin of patients with keloids and healthy control (normal) skin were conducted. By integrating mRNA and publicly available gene expression data (GSE158395), differentially expressed genes related to oxidative stress and mitochondrial function in keloids were identified. Hub genes were identified using various bioinformatics analyses such as immune infiltration analysis, weighted gene co-expression network analysis, machine learning, and expression validation using proteomics sequencing data. Moreover, a competing endogenous RNA (ceRNA) network of hub genes was constructed by combining miRNA, lncRNA, and circRNA expression data. Five hub genes were identified: MGST1, DHCR24, ALDH3A2, ADH1B, and FKBP5. ResultsThese hub genes had a high diagnostic value for keloids, with an AUC value > 0.8 each. In addition, five hub genes were associated with the infiltration of multiple immune cells. The immune cells with the strongest positive and negative correlations with hub genes were M0 and M1 macrophages. A ceRNA network was constructed, and several ceRNAs, such as AC005062.1/miR-134-5p/FKBP5 and BASP1-AS1/miR-503-5p/ADH1B, were identified. These five hub genes may contribute to keloid pathogenesis. ConclusionThese genes and their related ceRNAs may serve as diagnostic biomarkers and therapeutic targets for keloids.

Combining single-cell RNA sequencing and network pharmacology to explore the target of cangfu daotan decoction in the treatment of obese polycystic ovary syndrome from an immune perspective

BackgroundPolycystic ovary syndrome (PCOS) is a heterogeneous gynecological endocrine disorder linked to immunity. Cangfu Daotan Decoction (CFDT), a classic Chinese medicine prescription, is particularly effective in treating PCOS, specifically in patients with obesity; however, its specific mechanism remains unclear.MethodsPart 1: Peripheral blood mononuclear cells were collected on egg retrieval day from obese and normal-weight patients with PCOS and healthy women undergoing in vitro fertilization (IVF)-embryo transfer. Next, scRNA-seq was performed to screen the key genes of bese patients with PCOS. Part 2: Active ingredients of CFDT and obesity-related PCOS targets were identified based on public databases, and the binding ability between the active ingredients and targets was analyzed. Part 3: This part was a monocentric, randomized controlled trial. The obese women with PCOS were randomized to CFDT (6 packets/day) or placebo, and the healthy women were included in the blank control group (43 cases per group). The clinical manifestations and laboratory outcomes among the three groups were compared.ResultsBased on the scRNA-seq data from Part 1, CYLD, ARPC3, CXCR4, RORA, JUN, FGL2, ZEB2, GNLY, FTL, SMAD3, IL7R, KIR2DL1, CTSD, BTG2, CCL5, HLA, RETN, CTSZ, and NCF2 were potential key genes associated with obese PCOS were identified. The proportions of T, B, and natural killer cells were higher in patients with PCOS compared to healthy women, with even higher proportions observed in obese patients with PCOS. Gene ontology and the Kyoto encyclopedia of genes and genomes analysis depicted that the differentially expressed genes were related to immune regulation pathways. Network pharmacology analysis identified that the key active components in CFDT were quercetin, carvacrol, β-sitosterol, cholesterol, and nobiletin, and TP53, AKT1, STAT3, JUN, SRC, etc. were the core targets. The core targets and their enrichment pathways overlapped with those in Part 1. Clinical trials in Part 3 found that CFDT reduced the dosage of gonadotropins use in patients with PCOS, increased the number of high-quality embryos, and improved the ongoing pregnancy rate.ConclusionCFDT can improve the immune microenvironment of patients to some extent, reduce their economic burden, and enhance IVF outcomes. The improvement in the immune microenvironment in obese patients with PCOS may be linked to targets such as JUN and AKT.

LnCeCell 2.0: an updated resource for lncRNA-associated ceRNA networks and web tools based on single-cell and spatial transcriptomics sequencing data.

We describe LnCeCell 2.0 (http://bio-bigdata.hrbmu.edu.cn/LnCeCell), an updated resource for lncRNA-associated competing endogenous RNA (ceRNA) networks and web tools based on single-cell and spatial transcriptomics sequencing(stRNA-seq)data. We have updated the LnCeCell 2.0 database with significantly expanded data and improved features, including(i) 257 single-cell RNA sequencingandstRNA-seqdatasets across 86 diseases/phenotypes and 80 human normal tissues, (ii) 836581 cell-specific and spatial spot-specific ceRNA interactions and functional networks for 1002988 cells and 367971 spatial spots, (iii) 15489 experimentally supported lncRNA biomarkers related to disease pathology, diagnosis and treatment, (iv) detailed annotation of cell type, cell state, subcellular and extracellular locations of ceRNAs through manual curationand (v) ceRNA expression profiles and follow-up clinical information of 20326 cancer patients. Further, a panel of 24 flexible tools (including 8 comprehensive and 16 mini-analysis tools) was developed to investigate ceRNA-regulated mechanisms at single-cell/spot resolution. The CeCellTraject tool, for example, illustrates the detailed ceRNA distribution of different cell populations and explores the dynamic change of the ceRNA network along the developmental trajectory. LnCeCell 2.0 will facilitate the study of fine-tuned lncRNA-ceRNA networks with single-cell and spatial spot resolution, helping us to understand the regulatory mechanisms behind complex microbial ecosystems.

Dynamic Landscapes of Long Noncoding RNAs During Early Root Development and Differentiation in Glycine max and Glycine soja.

Soybean (Glycine max) is an important crop for its nutritional value. Its wild relative, Glycine soja, provides a valuable genetic resource for improving soybean productivity. Root development and differentiation are essential for soybean plants to take up water and nutrients, store energy and anchor themselves. Long noncoding RNAs (lncRNAs) have been reported to play critical roles in various biological processes. However, the spatiotemporal landscape of lncRNAs during early root development and differentiation in soybeans is scarcely characterized. Using RNA sequencing and transcriptome assembly, we identified 1578 lncRNAs in G. max and 1454 in G. soja, spanning various root portions and time points. Differential expression analysis revealed 82 and 69 lncRNAs exhibiting spatiotemporally differential expression patterns in G. max and G. soja, respectively, indicating their involvement in the early stage of root architecture formation. By elucidating multiple competitive endogenous RNA (ceRNA) networks involving lncRNAs, microRNAs and protein-coding RNAs, we unveiled intricate regulatory mechanisms of lncRNA in early root development and differentiation. Our efforts significantly expand the transcriptome annotations of soybeans, unravel the dynamic landscapes of lncRNAs during early root development and differentiation, and provide valuable resources into the field of soybean root research.

Identification of lncRNA dual targeting PD-L1 and PD-L2 as a novel prognostic predictor for gastric cancer

BackgroundAlthough breakthroughs have been achieved in gastric cancer (GC) therapy with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1), the acquisition of high response rate remains a huge challenge for clinicians. It is imperative to identify novel biomarkers for predicting response to immunotherapy and explore alternative therapeutic strategy for GC.MethodsThe transcriptomic profiles and clinical information of GC patients from The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) database was used to screen differentially expressed lncRNAs between the tumor specimens and the paracancerous tissues. The TargetScan, miRDB and miRcode database were then utilized to construct competing endogenous RNA (ceRNA) networks and identify pivotal lncRNAs. An independent dataset from GEO (GSE70880) and 23 pairs of GC specimens of our cohort were subsequently performed for external validity. The relationship between clinical variables and gene expression were evaluated by Kruskal–wallis test and Wilcoxon signed-rank. The prognostic value of the candidate genes was assessed using Kaplan-Meier analysis and Cox regression models. CIBERSORT and Gene set enrichment analysis (GSEA) were used to determine immune cell infiltration. Gastric adenocarcinoma AGS cells and human embryonic kidney 293T (HEK293T) cells with knockdown of LINC01094 were generated by siRNA transfection, followed by detecting the alteration of the target miRNA and PD-L1/PD-L2 by RT-qPCR. Besides, the interaction between lncRNA and the miRNA–PD-L1/PD-L2 axis were verified by dual luciferase reporter assay.ResultsTwenty-two intersecting lncRNAs were identified to be PD-L1/PD-L2-related lncRNAs and LINC01094–miR-17-5p–PD-L1/PD-L2 was constructed as a potential ceRNA network. LINC01094 was increased in tumor specimens than adjacent normal samples and was positively associated with advanced tumor stages and EBV and MSI status. Furthermore, LINC01094 expression was an independent risk factor for poor overall survival (OS) in GC patients. CD8+ T cell exhaustion-related genes were enriched in high-LINC01094 tissues and high-PD-L2 group. A strong positive association of LINC01094 expression was established with M2 macrophages, IL-10+ TAM, as well as PD-L1 and PD-L2 levels, therefore a LINC01094–miR-17-5p–IL-10 network was proposed in macrophages. Using the exoRBase database, LINC01094 was assumed in blood exosomes of GC patients The results of knockdown experiments and luciferase reporter assays revealed that LINC01094 interacted with miR-17-5p and served as a miRNA sponge to regulate the expression of PD-L1 and PD-L2.ConclusionLINC01094 dually regulates the expression of PD-L1 and PD-L2 and shapes the immunosuppressive tumor microenvironment via sponging miR-17-5p. LINC01094 may serve as a potential prognostic predictor and therapeutic target in GC.

Transcriptome analysis of liver and ileum reveals potential regulation of long non-coding RNA in pigs with divergent feed efficiency.

LncRNA plays a significant role in regulating feed efficiency. This study aims to explore the key long non-coding RNAs, associated genes, and pathways in pigs with extreme feed efficiencies. We screened pigs with extremely high and low RFI through a 12-week animal growth trial and then conducted transcriptome analysis on their liver and ileum tissues. We analyzed the differential expressed lncRNAs, miRNAs, and mRNAs through target gene prediction and functional analysis. And we identified key lncRNAs and their potential regulatory genes associated with feed efficiency through the construction of competitive endogenous RNA network. Differentially expressed lncRNAs were pinpointed in the liver, revealing 23 crucial target genes primarily associated with GTP metabolism and glycolipid biosynthesis. In the ileum, a screening identified 92 pivotal target genes, mainly linked to lipid and small molecule metabolism. Moreover, LOC106504303 and LOC102160805 emerged as potentially significant lncRNAs respectively, playing roles in mitochondrial oxidative phosphorylation in the liver, and lipid and cholesterol metabolism in the ileum. The lncRNAs regulate energy metabolism and biosynthesis in the liver, and the digestive absorption capacity in the small intestine, affecting the feed efficiency of pigs.

Identification of exosomal ceRNA networks as prognostic markers in clear cell renal cell carcinoma.

Aggressive clear cell renal cell carcinoma (ccRCC) has a bad prognosis. We seek new ccRCC biomarkers for diagnosis and treatment. We used exoRBase and The Cancer Genome Atlas Database to compare DEmRNAs, DEmiRNAs, DElncRNAs, and DEcircRNAs in ccRCC and normal renal tissues. CircRNAs and circRNAs targeting microRNAs (miRNAs) were anticipated and taken intersections, and several databases assessed the targeted link between common miRNAs and messenger RNAs (mRNAs). The Cancer Genome Atlas database was used to create a predictive mRNA signature that was validated in E-MTAB-1980. Finally, we examined competing endogenous RNA network miRNAs and long noncoding RNAs for ccRCC predictive biomarkers using overall survival analysis. We built the first competing endogenous RNA regulation network of circRNA-lncRNA-miRNA-mRNA and found that it substantially correlates with ccRCC prognosis. We unveiled ccRCC's posttranscriptional regulation mechanism in greater detail. Our findings identified novel biomarkers for ccRCC diagnosis, therapy, and prognosis.

Network-based modelling reveals cell-type enriched patterns of non-coding RNA regulation during human skeletal muscle remodelling

Abstract A majority of human genes produce non-protein-coding RNA (ncRNA), and some have roles in development and disease. Neither ncRNA nor human skeletal muscle is ideally studied using short-read sequencing, so we used a customised RNA pipeline and network modelling to study cell-type specific ncRNA responses during muscle growth at scale. We completed five human resistance-training studies (n = 144 subjects), identifying 61% who successfully accrued muscle-mass. We produced 288 transcriptome-wide profiles and found 110 ncRNAs linked to muscle growth in vivo, while a transcriptome-driven network model demonstrated interactions via a number of discrete functional pathways and single-cell types. This analysis included established hypertrophy-related ncRNAs, including CYTOR – which was leukocyte-associated (FDR = 4.9×10−7). Novel hypertrophy-linked ncRNAs included PPP1CB-DT (myofibril assembly genes, FDR = 8.15×10−8), and EEF1A1P24 and TMSB4XP8 (vascular remodelling and angiogenesis genes, FDR = 2.77×10−5). We also discovered that hypertrophy lncRNA MYREM shows a specific myonuclear expression pattern in vivo. Our multi-layered analyses established that single-cell-associated ncRNA are identifiable from bulk muscle transcriptomic data and that hypertrophy-linked ncRNA genes mediate their association with muscle growth via multiple cell types and a set of interacting pathways.

Construction of competitive endogenous RNA network and identification of potential regulatory axis in vascular calcification.

Competitive endogenous RNAs (ceRNA) theory has been proved in numerous biological processes. Nevertheless, there is a lack of research applying the ceRNA theory to the study of vascular calcification (VC) in chronic kidney diseases (CKD). In the present study, a ceRNA network was constructed after conducting transcriptome sequencing of differentially expressed genes, followed by experimental validation to identify a new target for the diagnosis and treatment of vascular calcification. Total RNA was extracted from β-glycerophosphate (β-GP) cultured vascular smooth muscle cells (VSMCs) on Day 7. Illumina HiSeq platform was utilized to build sequencing libraries. GO and KEGG analysis was conducted to identify the function of the differentially expressed genes. Protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. A ceRNA network was established based on TargetScan, miRDB, miRWALK, and miRanda database. Western blot and qRT-PCR were used to explore the expression level of protein and RNA, respectively. The direct binding sites were confirmed by dual-luciferase reporter assay. In total, 647 differentially expressed lncRNAs and 289 differentially expressed mRNAs were identified (|log2FC| ≥ 1, p < .05). The function of differentially expressed mRNAs was mainly enriched in negative regulation of osteoblast differentiation, regulation of RNA metabolic process, and other typical pathways. The ceRNA network was generated with a total of 107 interaction pairs. The lncRNA Prrc2c/miR-145-5p/Smad3 axis was considered a potential regulatory pathway within the ceRNA network. The regulatory relationship and targets of this ceRNA axis were validated via invitro experiments. For the first time, we found that lncRNA Prrc2c was highly expressed and promoted calcification of VSMCs. Luciferase reporter assay showed that lncRNA Prrc2c could bind miR-145-5p at site 1755-1761. Similarly, luciferase reporter assay showed that miR-145-5p inhibited Smad3 expression by binding to its 3'UTR. Our findings provide a comprehensive examination of the ceRNA networks in vascular smooth muscle cells (VSMCs) treated with high phosphorate. Specifically, we have identified the role of lncRNA Prrc2c in promoting VSMC calcification through the miR-145-5p/Smad3 axis.

Transcriptome-wide N6-methyladenosine modification profiling of long non-coding RNAs in patients with recurrent implantation failure

N6-methyladenosine (m6A) is involved in most biological processes and actively participates in the regulation of reproduction. According to recent research, long non-coding RNAs (lncRNAs) and their m6A modifications are involved in reproductive diseases. In the present study, using m6A-modified RNA immunoprecipitation sequencing (m6A-seq), we established the m6A methylation transcription profiles in patients with recurrent implantation failure (RIF) for the first time. There were 1443 significantly upregulated m6A peaks and 425 significantly downregulated m6A peaks in RIF. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that genes associated with differentially methylated lncRNAs are involved in the p53 signalling pathway and amino acid metabolism. The competing endogenous RNA network revealed a regulatory relationship between lncRNAs, microRNAs and messenger RNAs. We verified the m6A methylation abundances of lncRNAs by using m6A-RNA immunoprecipitation (MeRIP)–real-time polymerase chain reaction. This study lays a foundation for further exploration of the potential role of m6A modification in the pathogenesis of RIF.

Dysregulation of the DRAIC/SBK1 Axis Promotes Lung Cancer Progression

Background: Long non-coding RNAs (lncRNAs) are key regulators of cellular processes that underpin cancer development and progression. DRAIC is a migration inhibitor that has been linked with lung adenocarcinoma progression; however, its mechanisms remain to be studied. Methods: Several bioinformatics tools were used to explore the role of DRAIC in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Results: Our bioinformatics analysis illustrates that patients with low expression of DRAIC have poor overall survival outcomes. In addition, the mRNA of SH3 domain-binding kinase 1 (SBK1) was downregulated in this cohort of patients. Mechanistic analysis showed that SBK1 is under the DRAIC competing endogenous RNAs network, potentially through sponging of miRNA-92a. Conclusion: Consistent dysregulation of the DRAIC-SBK1 axis was linked to poor survival outcome in both LUAD and LUSC, suggesting a tumour inhibitor role and providing potential for new diagnostics and therapeutic approaches.

Identification of ferroptosis-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches

Ferroptosis has emerged as a critical mechanism in the development and progression of various tumors, particularly diffuse large B-cell lymphoma (DLBCL). However, the thorough characterization of ferroptosis-related genes in DLBCL remains inadequately explored. We retrieved datasets associated with DLBCL and ferroptosis gene sets from the Gene Expression Omnibus (GEO) database and the Ferroptosis Database (FerrDb), resulting in the identification of 27 differentially expressed ferroptosis-related genes (DE-FRGs) linked to DLBCL. Utilizing the LASSO and Support Vector Machine Recursive Feature Elimination (SVW-RFE) algorithms, we identified 10 genes—MT1G, MTOR, BRD4, ACO1, SAT1, PEBP1, LPIN1, ATM, SRXN1, and PRDX1—as key biomarker candidates with significant diagnostic potential. Functional enrichment analyses revealed that these biomarker genes are likely involved in regulating several critical biological pathways implicated in DLBCL pathogenesis, including immune response, oxidative phosphorylation, and cell cycle regulation. Moreover, we identified 246 potential therapeutic agents targeting these 10 biomarker genes. Concurrently, competitive endogenous RNA (ceRNA) network analysis uncovered a complex regulatory network centered on the identified biomarker genes. Additionally, CIBERSORT analysis highlighted notable alterations in the immune microenvironment of DLBCL patients. We propose a diagnostic strategy that provides novel insights into the molecular mechanisms underlying DLBCL. Nevertheless, further validation of the practical value of this strategy for DLBCL diagnosis is necessary before its clinical application.

Exploring Potential Biomarkers and Molecular Mechanisms of Cutaneous Squamous Cell Carcinoma Based on Bioinformatics.

Cutaneous squamous cell carcinoma (cSCC) ranks as the second most common malignancy in clinical practice and poses a significant threat to public health due to its high malignancy. In this study, we aimed to explore potential biomarkers and molecular mechanisms of cSCC. Differentially expressed genes (DEGs) from GSE66359 and GSE117247 datasets were identified using R software. We conducted enrichment analyses and screened hub genes through protein-protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA). To assess the diagnostic performance of these genes, we generated ROC curves using both internal and external datasets (GSE45164) and validated the expression levels of these genes in cSCC tissues through immunohistochemistry. Subsequently, we predicted the target miRNAs and lncRNAs for hub genes using online databases and constructed competing endogenous RNA (ceRNA) networks. In total, we identified 505 upregulated DEGs and 522 downregulated DEGs. Through PPI and WGCNA analyses, we identified four hub genes exhibiting robust diagnostic performance in internal and external datasets (AUC > 0.9) and selected three previously unreported genes for further analysis. Immunohistochemistry demonstrated significantly elevated CCNA2, CCNB2, and UBE2C expression in cSCC tissues compared to normal skin tissues. Finally, we constructed three ceRNA networks, namely NEAT1/H19-hsa-miR-148a-3p-CCNA2 and NEAT1-hsa-miR-140-3p-UBE2C. In conclusion, we have identified CCNA2, CCNB2, and UBE2C as novel biomarkers for cSCC, and the NEAT1/H19-hsa-miR-148a-3p-CCNA2 and NEAT1-hsa-miR-140-3p-UBE2C ceRNA networks may represent molecular mechanisms under-lying cSCC progression. The findings of this study offer new diagnostic and therapeutic options for cSCC patients.

Comprehensive Bioinformatics Analysis Reveals the Potential Role of the hsa_circ_0001081/miR-26b-5p Axis in Regulating COL15A1 and TRIB3 within Hypoxia-Induced miRNA/mRNA Networks in Glioblastoma Cells.

Background/Objectives: The intrinsic molecular heterogeneity of glioblastoma (GBM) is one of the main reasons for its resistance to conventional treatment. Mesenchymal GBM niches are associated with hypoxic signatures and a negative influence on patients' prognosis. To date, competing endogenous RNA (ceRNA) networks have been shown to have a broad impact on the progression of various cancers. In this study, we decided to construct hypoxia-specific microRNA/ messengerRNA (miRNA/mRNA) networks with a putative circular RNA (circRNA) regulatory component using available bioinformatics tools. Methods: For ceRNA network construction, we combined publicly available data deposited in the Gene Expression Omnibus (GEO) and interaction pairs obtained from miRTarBase and circBank; a differential expression analysis of GBM cells was performed with limma and deseq2. For the gene ontology (GO) enrichment analysis, we utilized clusterProfiler; GBM molecular subtype analysis was performed in the Glioma Bio Discovery Portal (Glioma-BioDP). Results: We observed that miR-26b-5p, generally considered a tumor suppressor, was upregulated under hypoxic conditions in U-87 MG cells. Moreover, miR-26b-5p could potentially inhibit TRIB3, a gene associated with tumor proliferation. Protein-protein interaction (PPI) network and GO enrichment analyses identified a hypoxia-specific subcluster enriched in collagen-associated terms, with six genes highly expressed in the mesenchymal glioma group. This subcluster included hsa_circ_0001081/miR-26b-5p-affected COL15A1, a gene downregulated in hypoxic U-87 MG cells yet highly expressed in the mesenchymal GBM subtype. Conclusions: The interplay between miR-26b-5p, COL15A1, and TRIB3 suggests a complex regulatory mechanism that may influence the extracellular matrix composition and the mesenchymal transformation in GBM. However, the precise impact of the hsa_circ_0001081/miR-26b-5p axis on collagen-associated processes in hypoxia-induced GBM cells remains unclear and warrants further investigation.

LINC00668 silencing retards tumorigenesis via sponging miR-518c-3p to regulating WDR1 in triple negative breast cancer

The emergence of long noncoding RNAs (lncRNAs) was proved to be crucial to the aggravation of triple negative breast cancer (TNBC), a fatal female malignancy. LINC00668 was unveiled as an overexpressed lncRNA in TNBC previously. However, its exact function and whether it functioned in TNBC development needs to be ascertained. To explore this, qRT-PCR was used to detect its dysregulation in TNBC cells. Biological functions of LINC00668 were determined through loss-of-function experiments. Bioinformatics analysis was utilized to predict the downstream modulatory genes of LINC00668. Dual-luciferase reporter assay plus RNA immunoprecipitation analysis, quantitative PCR analysis, and rescue assays were employed for the exploration of potential action of mode in competitive endogenous RNA (ceRNA) network. It was revealed that LINC00668 was upregulated and its depletion resulted in impeded proliferation and migration of TNBC cells. Bioinformatics analysis and mechanical assays uncovered that LINC00668 sponged miR-518c-3p to facilitate WDR1 level in TNBC. Furthermore, rescue experiments demonstrated that LINC00668/miR-518c-3p pathway contributed to TNBC cell proliferation and migration in the form of WDR1 dependency. Overall our study might discover a vital clue for the cure of lncRNA-directed treatment for TNBC patients.

Transparent sparse graph pathway network for analyzing the internal relationship of lung cancer.

While it is important to find the key biomarkers and improve the accuracy of disease models, it is equally important to understand their interaction relationships. In this study, a transparent sparse graph pathway network (TSGPN) is proposed based on the structure of graph neural networks. This network simulates the action of genes in vivo, adds to prior knowledge, and improves the model's accuracy. First, the graph connection was constructed according to protein-protein interaction networks and competing endogenous RNA (ceRNA) networks, from which some noise or unimportant connections were spontaneously removed based on the graph attention mechanism and hard concrete estimation. This realized the reconstruction of the ceRNA network representing the influence of other genes in the disease on mRNA. Next, the gene-based interpretation was transformed into a pathway-based interpretation based on the pathway database, and the hidden layer was added to realize the high-dimensional analysis of the pathway. Finally, the experimental results showed that the proposed TSGPN method is superior to other comparison methods in F1 score and AUC, and more importantly, it can effectively display the role of genes. Through data analysis applied to lung cancer prognosis, ten pathways related to LUSC prognosis were found, as well as the key biomarkers closely related to these pathways, such as HOXA10, hsa-mir-182, and LINC02544. The relationship between them was also reconstructed to better explain the internal mechanism of the disease.