miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology

Identification and characterization of lncRNA-miRNA-mRNA tripartite network of sulfur mustard exposed patients

BACKGROUND

Alkylating cellular DNA, sulfur mustard (SM) is a chemical warfare agent that causes severe damage to the skin, eyes, and respiratory tract. Exposure can result in painful burns, chronic lung disease, immune system suppression, and an increased chance of developing cancer. The symptoms of itching, redness, and blistering are frequently followed by long-term genetic and psychological damage. By exploring the interaction between microRNA (miRNA), mRNA, and long non-coding RNA (lncRNA) in these patients, it is possible to identify gene expression patterns that could reduce cancer risk or improve treatment outcomes.

METHODS

The purpose of this study is to examine transcriptome data from PBMC samples obtained from sulfur mustard exposed patients (Mild, Moderate, Severe) and healthy Control, separated into six groups (SC, SMo, SMi, MoMi, MoC, and MiC). miRNA, lncRNA, and mRNA interactions were explored using miRNA, lncRNA, and mRNA tools and databases, such as miRTarBase, miRDB, miRNET, miRcode, and DIANA. A tripartite mRNA-miRNA-lncRNA network was modeled with the aid of Cytoscape software, and functional analyses were performed to gain an understanding of molecular pathways using GO and KEGG functional analyses.

RESULTS

By extracting miRNAs shared between lncRNAs and mRNAs, six groups were identified and Cytoscape software was used to visualize the lncRNA-miRNA-mRNA network. Betweenness, closeness, and degree filters identified key genes, with INO80D and lncRNAs MINCR, LINC00662, NEAT1, and DHRS4-AS1, along with miRNAs hsa-miR-1-3p, hsa-miR-124-3p, and hsa-let-7b-5p as the main players in all groups.

CONCLUSION

The interaction between key genes involved in chemical injuries and their association with genes implicated in lung cancer is highlighted in this study. By targeting these genes and their proteins, we can improve treatment strategies for sulfur mustard exposed patients and potentially reduce lung cancer risk.

Association Between Altered Microbiota Composition and Immune System-Related Genes in COVID-19 Infection

Microbiota and immunity affect the host's susceptibility to SARS-CoV-2 infection and the severity of COVID-19. This study aimed to identify significant alterations in the microbiota composition, immune signaling pathways, their potential association, and candidate microRNA in COVID-19 patients using an in silico study model. Enrichment online databases and Python programming were utilized to analyze GSE164805, GSE180594, and GSE182279, as well as NGS data of microbiota composition (PRJNA650244 and PRJNA660302) associated with COVID-19, employing amplicon-based/marker gene sequencing methods. C1, TNF, C2, IL1, and CFH genes were found to have a significant impact on immune signaling pathways. Additionally, we observed a notable decrease in Bacteroides spp. and Faecalibacterium sp., while Escherichia coli, Streptococcus spp., and Akkermansia muciniphila showed increased abundance in COVID-19. Notably, A. muciniphila demonstrated an association with immunity through C1 and TNF, while Faecalibacterium sp. was linked to C2 and IL1. The correlation between E. coli and CFH, as well as IL1 and Streptococcus spp. with C2, was identified. hsa-let-7b-5p was identified as a potential candidate that may be involved in the interaction between the microbiota composition, immune response, and COVID-19. In conclusion, integrative in silico analysis shows that these microbiota members are potentially crucial in the immune responses against COVID-19.

Comprehensive transcriptome, miRNA and kinome profiling identifies new treatment options for personalized lung cancer therapy

BACKGROUND

Basic research identified oncogenic driver mutations in lung cancer (LC). However, <10% of patients carry driver mutations. Thus, most patients are not recommended for first-line kinase inhibitor (KI)-based therapies. Through enabling technologies and bioinformatics, we gained deep insight into patient-specific signalling networks which permitted novel KI-based treatment options in LC.

METHODS

We performed molecular pathology, transcriptomics and miRNA profiling across 95 well-characterized LC patients. We confirmed results based on cross-linked immunoprecipitation-sequencing data, and used N = 524 adeno- and 497 squamous cell carcinomas as validation sets. We employed the PamGene platform to identify aberrant kinases, validated the results by evaluating independent siRNA and CRISPR-mediated mRNA knockdown studies in human LC cell lines.

RESULTS

Transcriptomics revealed 439, 1240, 383 and 320 significantly upregulated genes, respectively, for adeno-, squamous, neuroendocrine and metastatic cases, and there are 1092, 1477, 609 and 1267 downregulated DEGs. Based on gene enrichment analysis and experimentally validated miRNA-gene interactions, we constructed regulatory networks specific for adeno-, squamous, neuroendocrine and metastatic LC. Molecular profiling discovered 137 significantly upregulated kinases (range 2-26-fold) of which 65 and 72, respectively, are tyrosine and serine-threonine kinases while 6 kinases carry driver mutations. Meanwhile, there are 21 kinases commonly upregulated irrespective of the histological type of LC. Bioinformatics decoded networks in which kinases function as master regulators. Typically, the networks consisted of 14, 9, 16 and 19 highly regulated kinases in adeno-, squamous, neuroendocrine and metastatic LC. Inhibition of kinases which function as master regulators disrupted the signalling networks, and their gene knock-down studies confirmed inhibition of cell proliferation in a panel of human LC cell lines. Additionally, the proposed molecular profiling enables KI-based therapies in patients with acquired drug resistance.

CONCLUSIONS

Our study broadens the perspective of KI-based therapies in LC, and we propose a framework to overcome acquired drug resistance.

Screening of biomarkers for diagnosing chronic kidney disease and heart failure with preserved ejection fraction through bioinformatics analysis

Background

Previous research has established that chronic kidney disease (CKD) and heart failure with preserved ejection fraction (HFpEF) often coexist. Although we have a preliminary understanding of the potential correlation between HFpEF and CKD, the underlying pathophysiological mechanisms remain unclear. This study aimed to elucidate the molecular mechanisms associated with CKD and HFpEF through bioinformatics analysis.

Methods

Datasets for HFpEF and CKD were obtained from the Gene Expression Omnibus (GEO) database. The R software package "limma" was employed to conduct differential expression analysis. Functional annotation was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). We conducted weighted gene co-expression network analysis (WGCNA), correlation analysis with autophagy, ferroptosis, and immune-related processes, as well as transcriptional regulation analysis, immune infiltration analysis, and diagnostic performance evaluation. Finally, the diagnostic potential of the identified hub genes for CKD and HFpEF was assessed using ROC curve analysis (GSE37171).

Results

Differential expression analysis revealed 58 overlapping genes, comprised of 40 up-regulated and 18 down-regulated genes. Both GO and KEGG analyses indicated enriched pathways relevant to both disorders. WGCNA identified 4086 genes associated with CKD. Further comparison with differentially expressed genes (DEGs) identified three hub genes (KLF4, SCD, and SEL1L3) that were linked to autophagy, ferroptosis, and immune processes in both conditions. Additionally, a miRNA-mRNA regulatory network involving 376 miRNAs and 12 transcription factors (TFs) was constructed. ROC curve analysis was performed to evaluate the diagnostic utility of the hub genes for CKD and HFpEF.

Conclusion

This study elucidated shared pathogenic mechanisms and identified diagnostic markers common to both HFpEF and CKD. The identified hub genes show promise as potential tools for early diagnosis and treatment strategies for these conditions.

mir-188-5p emerges as an oncomir to promote chronic myeloid leukemia via upregulation of BUB3 and SUMO2

BACKGROUND

Chronic myeloid leukemia (CML) is an aggressive malignancy originating from hematopoietic stem cells. miRNAs play a role in physiological and developmental processes, including cellular proliferation, apoptosis, angiogenesis, and differentiation, and in CML's prognosis, diagnosis, and treatment. This study aimed to investigate the function and possible mechanisms of action of miR-188-5p in the development and progression of chronic myeloid leukemia.

METHODS AND RESULTS

miRNA expression profiles were obtained from the GSE90773 dataset in the Gene Expression Omnibus (GEO). GEO2R was used to identify differentially expressed miRNAs. miRNET, miRDB, CancerSEA, GeneMANIA, and BioGRID databases were applied to assess the biological function of miRNA and target molecules in CML. RT-PCR performed validation analyses of miRNA and target molecules in CML. To determine the power of miR-188-5p expression levels to distinguish patients with CML from control, the ROC analysis was performed. miR-188-5p is significantly increased in K-562 cells, and overexpression of miR-188-5p was associated with clinicopathological features. miR-188-5p showed significantly higher AUC values (AUC = 1.0, p = 0.0001). The cut-off of miR-188-5p was 6.74. miRDB and mirNET predicted BUB3 and SUMO2 as a potential target gene of miR-188-5p. Additionally, increased expression of BUB3 and SUMO2 was observed in the K-562 cell. Bub3 is implicated in apoptosis and the cell cycle, whereas Sumo2 protein sumoylation and DNA binding are believed to contribute to catabolic processes.

CONCLUSIONS

Our results suggest that miR-188-5p acts as an oncomiRNA in CML pathogenesis and may be a promising therapeutic target for CML.

Pan-cancer analysis of Methyltransferase-like 16 (METTL16) and validated in colorectal cancer

Human Methyltransferase-like 16(METTL16) is an independent N6-methyladenosine (m6A) methyltransferase. Previous studies have proven METTL16 been linked with some types of cancers. However, comparative studies of the relevance of METTL16 across diverse tumors remain sparse. We comprehensively investigated the effect of METTL16 expression on tumor prognosis across human malignancies by analyzing multiple cancer-related databases like Tumor Immune Estimation Resource (TIMER) and human protein atlas (HPA). Bioinformatics data indicated that METTL16 was overexpressed in most of these human malignancies and was significantly associated with the prognosis of patients with cancer, especially in colorectal cancer (CRC). Subsequently, In vitro experiments, the utility of METTL16 that downregulation of its expression could result in reduced proliferation and migration of CRC cells. Our findings reveal novel insights into METTL16 expression and its biological functions in diverse cancer types, indicating that METTL16 could serve as a prognostic biomarker and plays an important role in colorectal cancer.

Role of miRNAs in the pathogenesis of psoriasis and psoriatic arthritis: a genome-wide Mendelian randomization study

BACKGROUND

MicroRNAs (miRNAs) are critical in the onset and treatment of skin diseases, but the miRNAs causally associated with psoriasis (PSO) and psoriatic arthritis (PsA) remain unclear. This study aims to identify miRNAs with causal associations with PSO and PsA.

METHODS

Five Mendelian randomization (MR) methods were employed, using miRNA expression quantitative trait loci (mirQTL) data as exposure variables and PSO and PsA as outcome variables. This approach was used to uncover the causal links of miRNAs with both PSO and PsA, with robust sensitivity analyses ensuring the stability of our findings. Finally, miRNet and enrichment analyses were used to predict target genes of the causal miRNAs and their potential biological roles.

RESULTS

Our robust findings indicated that miR-27b-3p, miR-204-5p, and miR-6891-3p were notably associated with an enhanced risk of PSO. Additionally, miR-6891-3p was greatly associated with an enhanced risk of PsA. Conversely, miR-29c-3p, miR-181a-3p, miR-181a-5p, miR-181b-5p, and miR-199a-3p were substantially associated with a reduced risk of both PSO and PsA. Enrichment analyses revealed that the target genes of these causal miRNAs were markedly enriched in biological pathways such as apoptosis, Wnt, and PI3K-AKT signaling.

CONCLUSION

This study identifies eight miRNAs causally associated with PSO and five miRNAs associated with PsA, with no observed heterogeneity or pleiotropy. These findings offer potential biomarkers for the diagnosis and treatment of PSO and PsA. Key Points • We conducted the first genome-wide MR study to explore the causal relationships between miRNAs and PSO and PsA. • The study found stable and reliable causal effects of 8 miRNAs on PSO and 5 miRNAs on PsA. • These miRNAs provide important insights into elucidating the pathophysiological mechanisms of PSO and PsA and developing new therapeutic approaches.

Identification of differentially expressed MiRNA clusters in cervical cancer

BACKGROUND

Aberrant miRNA expression has been associated with cervical cancer (CC) progression. The present study aimed to identify the miRNA clusters (MCs) altered in CC, identify their clinical utility, and understand their biological functions via computational analysis.

METHODS

We used small RNA sequencing and qRT‒PCR to identify and validate abnormally expressed MCs in cervical squamous cell carcinoma (CSCC) samples. We compared our data with publicly available CC datasets to identify the differentially expressed MCs in CC. The potential targets, pathways, biological functions, and clinical utility of abnormally expressed MCs were predicted via several computational tools.

RESULTS

Small RNA sequencing revealed that 229 miRNAs belonging to 48 MCs were significantly differentially expressed in CSCC (p-value ≤ 0.05). Validation by qRT‒PCR confirmed the downregulation of members of the miR-379/656, namely, hsa-miR-376c-3p (2.8-fold; p-value 0.03), hsa-miR-494-3p (3.4-fold; p-value 0.02), hsa-miR-495-3p (eightfold; p-value 0.01), and hsa-miR-409-3p (fivefold; p-value 0.03), in CSCC samples compared with normal samples. The prognostic model generated via miRNA expression and random forest analysis showed robust sensitivity and specificity (0.88 to 0.92) in predicting overall survival. In addition, we report 22 prognostically important miRNAs in CC. Pathway analysis revealed the enrichment of several cancer-related pathways, notably p53, the cell cycle, viral infection and MAPK signalling. CDC25A, CCNE1, E2F1, CCNE2, RBL1, E2F3, CDK2, RBL2, E2F2 and CCND2 were identified as the top ten gene targets of MC. Drug‒gene interaction analysis revealed enrichment of 548 approved drugs and 62 unique genes.

CONCLUSION

Our study identified MCs, their target genes, their prognostic utility, and their potential functions in CC and recommended their usefulness in CC management.

Integrative analysis of m7G methylation-associated genes prognostic signature with immunotherapy and identification of LARP1 as a key oncogene in head and neck squamous cell carcinoma

Background

N7-methylguanosine (m7G) methylation is an RNA modification associated with cancer progression, but its specific role in head and neck squamous cell carcinoma (HNSCC) remains unclear.

Methods

This study analyzed the differential expression of m7G-related genes (m7GRGs) in HNSCC using the TCGA-HNSCC dataset, identifying key pathways associated with the cell cycle, DNA replication, and focal adhesion. A LASSO-Cox regression model was constructed based on four m7GRGs (EIF3D, EIF1, LARP1, and METTL1) and validated with GEO datasets and clinical samples. Further validation of gene upregulation in HNSCC tissues was conducted using RT-qPCR and immunohistochemistry, while the role of LARP1 in HNSCC cells was assessed via knockout experiments.

Results

The constructed model demonstrated strong predictive performance, with the risk score significantly correlating with prognosis, immune infiltration, and drug sensitivity. An external dataset and clinical specimens further confirmed the model's predictive accuracy for immunotherapy response. Additionally, two regulatory axes-LINC00707/hsa-miR-30b-5p/LARP1 and SNHG16/hsa-miR-30b-5p/LARP1-were identified. LARP1 knockout experiments revealed that suppressing LARP1 markedly inhibited HNSCC cell proliferation, migration, and invasion.

Conclusion

The m7GRG-based prognostic model developed in this study holds strong clinical potential for predicting prognosis and therapeutic responses in HNSCC. The identification of LARP1 and its related regulatory pathways offers new avenues for targeted therapy in HNSCC.

CDCA genes as prognostic and therapeutic targets in Colon adenocarcinoma

OBJECTIVES

The study investigates the role of Cell Division Cycle Associated (CDCA) genes in colorectal cancer (COAD) by analyzing their differential expression, epigenetic alterations, prognostic significance, and functional associations.

METHODOLOGY

This study employed a detailed in silico and in vitro experiments-based methodology.

RESULTS

RT-qPCR assays reveal significantly elevated mRNA levels of CDCA2, CDCA3, CDCA4, CDCA5, CDCA7, and CDCA8 genes in COAD cell lines compared to controls. Bisulfite sequencing indicates reduced promoter methylation of CDCA gene promoters in COAD cell lines, suggesting an epigenetic regulatory mechanism. Analysis of large TCGA datasets confirms increased CDCA gene expression in COAD tissues. Survival analysis using cSurvival database demonstrates negative correlations between CDCA gene expression and patient overall survival. Additionally, Lasso regression-based models of CDCA genes predict survival outcomes in COAD patients. Investigating immune modulation, CDCA gene expression inversely correlates with immune cell infiltration and immune modulators. miRNA-mRNA network analysis identifies regulatory miRNAs targeting CDCA genes, validated by RT-qPCR showing up-regulation of has-mir-10a-5p and has-mir-20a-5p in COAD cell lines and tissues. Drug sensitivity analysis suggests resistance to specific drugs in COAD patients with elevated CDCA gene expression. Furthermore, CDCA gene expression correlates with crucial functional states in COAD, including "angiogenesis, apoptosis, differentiation, hypoxia, inflammation, and metastasis." Additional in vitro experiments revealed that CDCA2 and CDCA3 knockdown in SW480 and SW629 cells significantly reduced cell proliferation and colony formation while enhancing cell migration.

CONCLUSION

Overall, the study elucidates the multifaceted role of CDCA genes in COAD progression, providing insights into potential diagnostic, prognostic, and therapeutic implications.

Identification of a functional CircRNA-miRNA-mRNA network and inhibitory effect of Hsa_circ_0001681 on gliomas

OBJECTIVE

Gliomas pose a significant global health challenge due to high rates of morbidity and mortality. Recent research has indicated that circular RNAs (circRNAs) may play a crucial role in gliomas. However, the specific impacts of circRNAs on gliomas development is poorly understood. Therefore, the present study aimed to explore the roles of circRNAs in gliomas by analyzing their interactions with microRNAs (miRNAs) and messenger RNAs (mRNAs).

METHODS

Datasets were extracted from the Gene Expression Omnibus (GEO) database to investigate differentially expressed circRNAs in gliomas. Using the Circular RNA Interactome, we predicted interactions between the identified circRNAs and 125 target miRNAs, focusing on 15 key miRNAs selected by intersection analysis. The miRNet database was applied to predict 2635 target mRNAs, constructing a comprehensive circRNA-miRNA-mRNA network, while functional enrichment analyses were conducted to determine the roles of this network.

RESULTS

Four circRNAs with significant differential expression in glioma samples were identified. The constructed network indicated the substantial involvement of transcriptional regulation and cancer-related pathways. Notably, hsa_circ_0001681 was highlighted as a key circRNA, which was further validated through Sanger sequencing and quantitative reverse transcription PCR (qRT-PCR). Functional assays, including cellular assays and animal xenograft experiments, demonstrated that hsa_circ_0001681 inhibits glioma carcinogenesis in vitro and in vivo.

CONCLUSION

Our investigation highlights the significant role of the circRNA-miRNA-mRNA network in the pathophysiology of gliomas, and supports the potential of hsa_circ_0001681 as a diagnostic and therapeutic biomarker. These findings present new opportunities for understanding the molecular mechanisms underlying glioma and developing targeted treatments.

Non-Coding RNAs in Cancer: Structure, Function, and Clinical Application

We are on the brink of a paradigm shift in both theoretical and clinical oncology. Genomic and transcriptomic profiling, alongside personalized approaches that account for individual patient variability, are increasingly shaping discourse. Discussions on the future of personalized cancer medicine are mainly dominated by the potential of non-coding RNAs (ncRNAs), which play a prominent role in cancer progression and metastasis formation by regulating the expression of oncogenic or tumor suppressor proteins at transcriptional and post-transcriptional levels; furthermore, their cell-free counterparts might be involved in intercellular communication. Non-coding RNAs are considered to be promising biomarker candidates for early diagnosis of cancer as well as potential therapeutic agents. This review aims to provide clarity amidst the vast body of literature by focusing on diverse species of ncRNAs, exploring the structure, origin, function, and potential clinical applications of miRNAs, siRNAs, lncRNAs, circRNAs, snRNAs, snoRNAs, eRNAs, paRNAs, YRNAs, vtRNAs, and piRNAs. We discuss molecular methods used for their detection or functional studies both in vitro and in vivo. We also address the challenges that must be overcome to enter a new era of cancer diagnosis and therapy that will reshape the future of oncology.

Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach

BACKGROUND

Screening tests, particularly liquid biopsy with circulating miRNAs, hold significant potential for non-invasive cancer detection before symptoms manifest.

METHODS

This study aimed to identify biomarkers with high sensitivity and specificity for multiple and specific cancer screening. 972 Serum miRNA profiles were compared across thirteen cancer types and healthy individuals using weighted miRNA co-expression network analysis. To prioritize miRNAs, module membership measure and miRNA trait significance were employed. Subsequently, for specific cancer screening, gastric cancer was focused on, using a similar strategy and a further step of preservation analysis. Machine learning techniques were then applied to evaluate two distinct miRNA panels: one for multi-cancer screening and another for gastric cancer classification.

RESULTS

The first panel (hsa-miR-8073, hsa-miR-614, hsa-miR-548ah-5p, hsa-miR-1258) achieved 96.1% accuracy, 96% specificity, and 98.6% sensitivity in multi-cancer screening. The second panel (hsa-miR-1228-5p, hsa-miR-1343-3p, hsa-miR-6765-5p, hsa-miR-6787-5p) showed promise in detecting gastric cancer with 87% accuracy, 90% specificity, and 89% sensitivity.

CONCLUSIONS

Both panels exhibit potential for patient classification in diagnostic and prognostic applications, highlighting the significance of liquid biopsy in advancing cancer screening methodologies.

The role of FTO in m6A RNA methylation and immune regulation in Staphylococcus aureus infection-related osteomyelitis

Background

Regulators of n6-methyladenosine (m6A) RNA modification play important roles in many diseases; however, their involvement in Staphylococcus aureus (S. aureus)-related osteomyelitis remains inadequately explored. Therefore, this study aims to investigate the role of m6A in S. aureus infection-related osteomyelitis and elucidate its underlying mechanisms.

Methods

We downloaded the S. aureus infection-related osteomyelitis infection dataset GSE30119 from the Gene Expression Omnibus database. Initially, we constructed a diagnostic model based on m6A genes and predicted the hub node miRNAs and transcription factors by constructing a protein-protein interaction network. Subsequently, a prognostic model was built using LASSO regression, the receiver operating characteristic curve of the model was plotted, and the predictive performance of the diagnostic model was validated. Further, unsupervised clustering analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were employed to assess immune cell infiltration. Additionally, we validated the expression of fat mass and obesity-associated protein (FTO) in S. aureus-infected Raw264.7 macrophages using qPCR and western blotting. Moreover, we conducted si-FTO experiments on mouse Raw264.7 macrophages to investigate the anti-inflammatory regulatory role of si-FTO during S. aureus infection.

Results

We identified 19 co-expressed genes closely related to FTO were identified, along with 206 related transcription factor regulatory genes and 589 miRNAs. Enrichment analyses suggested that these genes were involved in pathways related to the proliferation and oxidation of various immune cells, cellular senescence, and various tumors and immune cells, as well as cell cycle-related functions. GSEA revealed that PD-1, TH1, TH2, CTLA4, and other pathways were significantly enriched in patients with high FTO expression. GSVA indicated that the differentially enriched pathways were related to included amino acid metabolism, immunity, and infection. Correlation analysis of immune infiltration revealed that monocytes, M2 macrophages, resting mast cells, and neutrophils were present in normal and diseased samples. Differences in expression were observed between the groups. The western blotting and qPCR analyses confirmed that the protein expression of FTO was reduced in macrophages after infection with S. aureus, consistent with the observed changes in mRNA expression. Furthermore, we validated that FTO may influence the regulation of inflammation through the FoxO1/NF-kB pathway.

Conclusion

The m6A RNA methylation regulator FTO may serve as a potential diagnostic marker and therapeutic target, involved in the pathogenesis of S. aureus infection-related osteomyelitis. This finding provides new insights into the relationship between FTO-mediated m6A RNA methylation and osteomyelitis.

Exploring MAP3K genes in gastric cancer: biomarkers, tumor microenvironment dynamics, and chemotherapy resistance

BACKGROUND

Gastric cancer (GC) presents a significant global health burden, necessitating a deeper understanding of its molecular underpinnings for improved diagnostics and therapeutics.

METHODS

In this study, we investigated the expression profiles and clinical implications of MAP3K genes in GC using in silico and in vitro experiments.

RESULTS

Utilizing RT-qPCR analysis, we observed significant up-regulation of MAP3K1, MAP3K4, MAP3K5, MAP3K6, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 in GC cell lines, while MAP3K2, MAP3K3, MAP3K11, MAP3K12, MAP3K13, MAP3K14, and MAP3K15 exhibited down-regulation. Prognostic evaluation revealed that elevated expression of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 was associated with shorter overall survival (OS), emphasizing their clinical significance. Furthermore, the diagnostic potential was demonstrated through robust Receiver operating characteristics (ROC) curve analysis, indicating the strong discriminatory power of these genes in distinguishing GC patients. Proteomic analysis further confirmed the higher expression of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 genes in GC. Methylation profiling further supported the idea that promoter hypomethylation of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 genes was associated with their up-regulation. Single-cell functional analysis elucidated the involvement of MAP3K genes in shaping the tumor microenvironment. miRNA-mRNA network analysis revealed intricate regulatory mechanisms, with hsa-mir-200b-3p emerging as a key regulator. Finally, the MAP3K1 knockdown has shown significant impacts on the cellular behavior of the BGC823 cells.

CONCLUSION

This comprehensive assessment provides valuable insights into the role of MAP3K genes in GC, offering avenues for further research and therapeutic exploration.

Synergistic Anti-Aging Effects of Adipose-Derived Stem Cell Extracellular Vesicles Loaded With Natural Compounds

BACKGROUND

Small extracellular vesicles from adipose-derived stem cells (ASC-sEVs) are gaining attentions rapidly for inherent therapeutic values in skin care and cosmetics. However, the optimal combinations of ASC-sEVs and certain natural compounds for synergistic anti-aging effects have not been systematically studied.

METHODS

Human ASC-sEVs were purified from culture supernatant of ASCs and multi-omics datasets of miRNAs, proteins and lipids of ASC-sEVs were analyzed for pathways regulating skin homeostasis. ASC-sEVs were then loaded with nicotinamide riboside (NR), resveratrol (RES), vitamin C (VITC), retinol (RET) and arbutin (ARB) at different concentrations by the sonication-incubation method. Their anti-oxidant, anti-wrinkle and anti-melanogenic effects were tested in vitro using the human keratinocyte HaCaT cells exposed to UVB radiation and human melanocyte B16F10 cells.

RESULTS

Multi-omics data analysis of ASC-sEVs identified key bioactive molecules regulating collagen formation, pigmentation, oxidative stress and inflammation. In the in vitro screenings for anti-aging effects, the compound-loaded ASC-sEVs outperformed the sEV- and compound-only treatments. Specifically in UVB-exposed HaCaT cells, 2 μg/mL sEVs loaded with 20 μg/mL NR, 2 μg/mL RES, 5 μg/mL VITC reduced reactive oxygen species level by 22.0%; while combination of sEVs and 2 μg/mL RES, 2.8 μg/mL RET significantly reduced MMP3 and upregulated PLOD1 expressions. B16F10 cells incubated with 2 μg/mL sEVs loaded with 2 μg/mL RES, 0.5 mM ARB had intracellular and extracellular melanin content lowered by 21.4% and 22.4% respectively. All the combinations caused no cytotoxicity.

CONCLUSION

Our study demonstrated the superiority of ASC-sEVs to deliver both endogenous biocargos and exogenous compounds to achieve synergistic skin anti-aging effects.

Identification and Analysis of Autophagy-Related Genes as Diagnostic Markers and Potential Therapeutic Targets for Tuberculosis Through Bioinformatics

According to the World Health Organization, Mycobacterium tuberculosis infections affect approximately 25% of the world's population. There is mounting evidence linking autophagy and immunological dysregulation to tuberculosis (TB). As a result, this research set out to discover TB-related autophagy-related biomarkers and prospective treatment targets. We used five autophagy databases to get genes linked to autophagy and Gene Expression Omnibus databases to get genes connected to TB. Then, functional modules associated with autophagy were obtained by analyzing them using weighted gene co-expression network analysis. Both Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to examine the autophagy-related genes (ATGs) of important modules. Limma was used to identify differentially expressed ATGs (DE-ATGs), and the external datasets were used to further confirm their identification. We used DE-ATGs and a protein-protein interaction network to search the hub genes. CIBERSORT was used to estimate the kinds and amounts of immune cells. After that, we built a drug-gene interaction network and a network that included messenger RNA, small RNA, and DNA. At last, the differential expression of hub ATGs was confirmed by RT-qPCR, immunohistochemistry, and western blotting. The diagnostic usefulness of hub ATGs was evaluated using receiver operating characteristic curve analysis. Including 508 ATGs, four of the nine modules strongly linked with TB were deemed essential. Interleukin 1B (IL1B), CAPS1, and signal transducer and activator of transcription 1 (STAT1) were identified by intersection out of 22 DE-ATGs discovered by differential expression analysis. Research into immune cell infiltration found that patients with TB had an increased proportion of plasma cells, CD8 T cells, and M0 macrophages. A competitive endogenous RNA network utilized 10 long non-coding RNAs and 2 miRNAs. Then, the IL1B-targeted drug Cankinumad was assessed using this network. During bioinformatics analysis, three hub genes were validated in mouse and macrophage infection models. We found that IL1B, CASP1, and STAT1 are important biomarkers for TB. As a result, these crucial hub genes may hold promise as TB treatment targets.

Integrated analysis of gene expressions and targeted mirnas for explaining crosstalk between oral and esophageal squamous cell carcinomas through an interpretable machine learning approach

This study explores the bidirectional relation of esophageal squamous cell carcinoma (ESCC) and oral squamous cell carcinoma (OSCC), examining shared risk factors and underlying molecular mechanisms. By employing random forest (RF) classifier, enhanced with interpretable machine learning (IML) through SHapley Additive exPlanations (SHAP), we analyzed gene expression from two GEO datasets (GSE30784 and GSE44021). The GSE30784 dataset comprises 167 OSCC samples and 45 control group, whereas the GSE44021 dataset encompasses 113 ESCC samples and 113 control group. Our analysis led to identification of 20 key genes, such as XBP1, VGLL1, and RAD1, which are significantly associated with development of ESCC and OSCC. Further investigations were conducted using tools like NetworkAnalyst 3.0, Single Cell Portal, and miRNET 2.0, which highlighted complex interactions between these genes and specific miRNA targets including hsa-mir-124-3p and hsa-mir-1-3p. Our model achieved high precision in identifying genes linked to crucial processes like programmed cell death and cancer pathways, suggesting new avenues for diagnosis and treatment. This study confirms the bidirectional relationship between OSCC and ESCC, laying groundwork for targeted therapeutic approaches. This study helps to identify shared biological pathways and genetic factors of these conditions for designing personalized medicine strategies and to improve disease management.

Extracellular Vesicles Derived From Lipopolysaccharide-Challenged Gingival Fibroblast Reveal Distinct miRNA Expression Patterns Associated With Reduced Cancer Survival

OBJECTIVES

Periodontitis is a prevalent inflammatory disease with established systemic implications. Extracellular vesicles (EVs) have emerged as key mediators of intercellular communication, potentially linking periodontitis to systemic diseases. However, the molecular cargo of EVs from inflamed periodontal cells remains poorly characterized. This study investigates the EV cargo of human gingival fibroblasts (hGF-hTERT) following lipopolysaccharide (LPS) stimulation and explores their potential role in cancer progression.

MATERIALS AND METHODS

EVs were isolated from LPS-treated and untreated fibroblasts via ultracentrifugation. Dynamic light scattering and scanning electron microscopy characterized EV size and morphology. RNA sequencing identified differentially expressed miRNAs, validated by qPCR. Functional pathway enrichment and in-silico analyses using The Cancer Genome Atlas (TCGA) were performed to assess EV-associated miRNA impact on tumorigenesis.

RESULTS

EV size and concentration remained unchanged after LPS stimulation. However, LPS-derived EVs exhibited a 2.6-fold increase in miRNA content, with three significantly upregulated miRNAs: miR-146a-5p, miR-486-5p, and miR-451a. Functional enrichment analysis revealed their involvement in inflammation, immune modulation, and cancer pathways. In vitro, LPS-derived EVs significantly enhanced prostate cancer (LnCap) cell proliferation. TCGA analysis linked the upregulated miRNAs to poor cancer prognosis.

CONCLUSIONS

LPS stimulation alters the miRNA cargo of gingival fibroblast-derived EVs, enhancing pathways associated with inflammation and cancer progression. These findings suggest a mechanistic role for periodontal EVs in systemic disease pathogenesis, warranting further investigation into their diagnostic and therapeutic potential.

Identification of EARS2 as a Potential Biomarker with Diagnostic, Prognostic, and Therapeutic Implications in Colorectal Cancer

Purpose

Colorectal cancer (CRC) is a prevalent malignancy, and lactate metabolism significantly influences tumorigenesis and progression. This study identifies key genes associated with lactic acid metabolism and explore their impact on CRC.

Patients and Methods

This study utilized data from The Cancer Genome Atlas, Gene Expression Omnibus, other public databases, and our institutional resources. Machine learning identified key lactate metabolism-related genes. Receiver Operating Characteristic analysis, Kaplan-Meier analysis, and the construction of a nomogram model were conducted to assess the diagnostic and prognostic significance of the key lactate metabolism-related gene EARS2. EARS2 expression in colorectal tissue was validated using both publicly available external data and samples from our institution. To investigate the mechanisms underlying EARS2 in CRC, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Gene Set Enrichment Analysis, and Protein-Protein Interaction analyses were performed, alongside the construction of miRNA-mRNA interaction networks. Additionally, the relationships between EARS2 and immune cell infiltration, as well as responses to drug therapy, were examined. Following the knockdown of EARS2, we assessed cell proliferation, migration capabilities, and apoptosis. Statistical analyses were conducted using R and GraphPad Prism software.

Results

ERAS2 was overexpressed in CRC tissues compared to normal and adenoma tissues, with higher expression levels correlating with aberrant lactate metabolism and poorer patient prognosis. EARS2 was involved in pathways such as neuroactive ligand-receptor interactions, protein digestion, and cholesterol metabolism, and it was associated with immune cell infiltration and responses to drug treatment. Additionally, the knockdown of EARS2 inhibited the proliferation, migration, and invasion of CRC cells while enhancing their apoptosis.

Conclusion

Elevated expression of EARS2 is associated with abnormal lactate metabolism, immune cell infiltration, altered therapeutic sensitivity, and poorer survival outcomes in CRC. This correlation suggests that EARS2 may serve as a potential target for the diagnosis, prognosis, and therapeutic intervention in CRC.

Investigating the miRNA-mRNA interactome of human trabecular meshwork cells treated with TGF-β1 provides insights into the pathogenesis of pseudoexfoliation glaucoma

Pseudoexfoliation glaucoma is a severe form of secondary open angle glaucoma and is associated with activation of the TGF-β pathway by TGF-β1. MicroRNAs (miRNAs) are small non-coding RNA species that are involved in regulation of mRNA expression and translation. To investigate what glaucomatous changes occur in the trabecular meshwork and how these changes may be regulated by miRNAs, we performed a bioinformatics analysis resulting in a miRNA-mRNA interactome. Primary human trabecular meshwork cells originating from normal donors were treated with TGF-β1 at 5 ng/mL for 24h; total RNA was extracted followed by RNA-Seq and miRNA-Seq. For both mRNA and miRNA species, differential expression was determined using a bioinformatics pipeline consisting of FastQC, STAR, FeatureCounts, edgeR (for miRNA) and DESeq2 (for mRNA). Putative mRNA-miRNA interactions between differentially expressed mRNA and miRNA species were determined using interaction databases miRWalk, miRTarBase, TarBase and TargetScan. To classify mRNA species by function and pathway, gene enrichment was performed using Enrichr. The resulting miRNA-mRNA interactome consisted of 1202 interactions. Some highly connected microRNAs were hsa-let-7e-5p, hsa-miR-20a-5p, hsa-miR-122-5p, and hsa-miR-29c-3p. Most differentially expressed genes were indicated to be regulated by miRNAs. The sub-interactomes of genes involved in specific pseudoexfoliation glaucoma related enrichment terms such as oxidative stress, unfolded protein response, signal molecules and ECM remodelling were determined. This is the first study to present a genome-wide microRNA-mRNA regulatory network for human trabecular meshwork cells treated with TGF-β1 and may serve to generate unbiased hypotheses about regulatory functions and mRNA targets of miRNAs in pseudoexfoliation glaucoma and may help to develop miRNA-based therapeutics.

Peripheral blood miRNAs are associated with airflow below threshold in children with asthma

BACKGROUND

MicroRNAs (miRNAs) are crucial post-transcriptional regulators involved in inflammatory diseases, such as asthma. Poor lung function and airflow issues in childhood are linked to the development of chronic obstructive pulmonary disease (COPD) in adulthood.

METHODS

We analyzed small RNA-Seq data from 365 peripheral whole blood samples from the Genetics of Asthma in Costa Rica Study (GACRS) for association with airflow levels measured by FEV1/FVC. Differentially expressed (DE) miRNAs were identified using DESeq2 in R, adjusting for covariates and applying a 10% false discovery rate (FDR). The analysis included 361 samples and 649 miRNAs. The two DE miRNAs were further tested for association with airflow obstruction in a study of adult former smokers with and without COPD.

RESULTS

We found 1 upregulated and 1 downregulated miRNA in participants with airflow below the threshold compared to those above it. In the adult study, the same miRNAs were upregulated and downregulated in individuals with FEV1/FVC < 0.7 versus those with FEV1/FVC > 0.7, showing suggestive statistical evidence. The target genes of these miRNAs were enriched for PI3K-Akt, Hippo, WNT, MAPK, and focal adhesion pathways.

CONCLUSIONS

Two differentially expressed miRNAs were associated with airflow levels in children with asthma and airflow obstruction in adults with COPD. This suggests that shared genetic regulatory systems may influence childhood airflow and contribute to adulthood airflow obstruction.

Unveiling cell-type-specific microRNA networks through alternative polyadenylation in glioblastoma

BACKGROUND

Glioblastoma multiforme (GBM) is characterized by its cellular complexity, with a microenvironment consisting of diverse cell types, including oligodendrocyte precursor cells (OPCs) and neoplastic CD133 + radial glia-like cells. This study focuses on exploring the distinct cellular transitions in GBM, emphasizing the role of alternative polyadenylation (APA) in modulating microRNA-binding and post-transcriptional regulation.

RESULTS

Our research identified unique APA profiles that signify the transitional phases between neoplastic cells and OPCs, underscoring the importance of APA in cellular identity and transformation in GBM. A significant finding was the disconnection between differential APA events and gene expression alterations, indicating that APA operates as an independent regulatory mechanism. We also highlighted the specific genes in neoplastic cells and OPCs that lose microRNA-binding sites due to APA, which are crucial for maintaining stem cell characteristics and DNA repair, respectively. The constructed networks of microRNA-transcription factor-target genes provide insights into the cellular mechanisms influencing cancer cell survival and therapeutic resistance.

CONCLUSIONS

This study elucidates the APA-driven regulatory framework within GBM, spotlighting its influence on cell state transitions and microRNA network dynamics. Our comprehensive analysis using single-cell RNA sequencing data to investigate the microRNA-binding sites altered by APA profiles offers a robust foundation for future research, presenting a novel approach to understanding and potentially targeting the complex molecular interplay in GBM.

Disulfidptosis-related gene signatures as prognostic biomarkers and predictors of immunotherapy response in HNSCC

Background

Disulfidptosis is a newly discovered form of cell death associated with tumorigenesis, particularly under oxidative stress and metabolic disorder conditions. Currently, the biological mechanisms of disulfidptosis-related genes (DRGs) in head and neck squamous cell carcinoma (HNSCC) remain unclear.

Methods

The study includes sections on methodologies, data sources, clinical data collection, subtype establishment, identification and analysis of differentially expressed genes, genetic variation, and the construction and validation of a DRG prognostic model. Various analyses are conducted, including the relationship between the risk scores model and clinicopathological features, immune status, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), ESTIMATE, mRNAsi, and drug sensitivity. The study also covers single-cell analysis and DNA methylation analysis of DRGs, and the prediction of potential microRNA and long non-coding RNA target genes. Prognostic DRGs expression in HNSCC is validated through RT-qPCR and immunohistochemistry. The model's predictive capability is confirmed using external validation cohorts from GEO datasets and clinical tissue samples. The role of DSTN in HNSCC is further validated through gene knockout experiments.

Results

We identified four valuable genes (SLC3A2, NUBPL, ACTB, DSTN) and constructed a prognostic model, along with identifying two DRG-related subtypes. Analysis of the DRG risk score revealed that the low-risk group had a better prognosis compared to the high-risk group. Significant correlations were found between the DRG risk score and clinical features, immunotherapy response, drug sensitivity, and genes related to RNA epigenetic modifications. Low-risk HNSCC patients were identified as potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. A regulatory axis involving DSTN, hsa-miR-181c-5p, LUCAT1, and IGFL2-AS1 was constructed for HNSCC. RT-qPCR and IHC data further validated the upregulation of prognostic DRGs in HNSCC. The prognostic model demonstrated excellent predictive performance for the prognosis of HNSCC patients. Additionally, DSTN was significantly overexpressed in tumor cells; its knockdown inhibited tumor cell proliferation, migration, and invasion.

Conclusion

The prognostic model effectively predicts HNSCC outcomes, with better prognosis in the low-risk group. DSTN upregulation promotes tumor growth, and its knockout inhibits proliferation, migration, and invasion.

Comprehensive investigation of matrix metalloproteinases in skin cutaneous melanoma: diagnostic, prognostic, and therapeutic insights

The dysregulation of matrix metalloproteinases (MMPs) in skin cutaneous melanoma (SKCM) represents a critical aspect of tumorigenesis. In this study, we investigated the diagnostic, prognostic, and therapeutic aspects of the MMPs in SKCM. Thirteen SKCM cell lines and seven normal skin cell lines were cultured under standard conditions for experimental analyses. RNA and DNA were extracted, followed by RT-qPCR to assess MMP expression and promoter methylation analysis to determine methylation levels. Functional assays, including cell proliferation, colony formation, and wound healing, were conducted post-MMP7 knockdown using siRNA in A375 cells. Databases like GEPIA2, HPA, MEXPRESS, and miRNet were employed for expression, survival, methylation, and miRNA-mRNA network analyses. We investigated the expression and promoter methylation landscape of MMPs in SKCM cell lines, revealing significant (p-value < 0.05) up-regulation of MMP1, MMP7, MMP9, MMP10, MMP11, MMP12, MMP13, MMP14, and MMP25, alongside down-regulation of MMP2, MMP3, and MMP21. Furthermore, our analysis demonstrated a significant (p-value < 0.05) inverse correlation between MMP expression levels and promoter methylation status, suggesting a potential regulatory role of DNA methylation in MMP dysregulation. Notably, MMP7, MMP11, and MMP14 exhibited significant (p-value < 0.05) associations with the overall survival of SKCM patients, emphasizing their prognostic significance. Additionally, Receiver operating characteristic (ROC) curve analysis highlighted the significant (p-value < 0.05) diagnostic potential of MMP7, MMP11, and MMP14 in distinguishing SKCM from normal individuals. Subsequent validation across multiple cohorts confirmed significant (p-value < 0.05) elevated MMP expression levels in SKCM tissues, particularly in advanced disease stages, further emphasizing their role in tumor progression. Furthermore, we elucidated potential regulatory pathways involving miR-22-3p, which targets MMP7, MMP11, and MMP14 genes in SKCM. Our findings also revealed associations between MMP expression and immune modulation, drug sensitivity, and functional states of SKCM cells. Lastly, MMP7 knockdown in A375 cells significantly significant (p-value < 0.05) impacted several characteristics, including cell proliferation, colony formation, and wound healing. Our findings highlight the diagnostic, prognostic, and therapeutic potential of MMP7, MMP11, and MMP14 in SKCM. These MMPs could serve as biomarkers for early detection and targets for therapy. Future efforts should focus on preclinical and clinical validation to translate these insights into personalized diagnostic and therapeutic strategies.

Olaparib Combined with DDR Inhibitors Effectively Prevents EMT and Affects miRNA Regulation in TP53-Mutated Epithelial Ovarian Cancer Cell Lines

Epithelial ovarian cancer (EOC) remains a leading cause of gynecologic cancer mortality. Despite advances in treatment, metastatic progression and resistance to standard therapies significantly worsen patient outcomes. Epithelial-mesenchymal transition (EMT) is a critical process in metastasis, enabling cancer cells to gain invasive and migratory capabilities, often driven by changing miRNA expression involved in the regulation of pathological processes like drug resistance. Targeted therapies like PARP inhibitors (PARPi) have improved outcomes, particularly in BRCA-mutated and DNA repair-deficient tumors; however, resistance and limited efficacy in advanced stages remain challenges. Recent studies highlight the potential synergy of PARPi with DNA damage response (DDR) inhibitors, such as ATR and CHK1 inhibitors, which disrupt cancer cell survival pathways under stress. This study investigated the combined effects of olaparib with ATR and CHK1 inhibitors (ATRi and CHK1i) on migration, invasion, and EMT-related protein expression and miRNA expression in ovarian cancer cell lines OV-90 and SKOV-3. The results demonstrated enhanced cytotoxicity, inhibition of migration and invasion, and modulation of miRNAs linked to metastasis. These findings suggest that combination therapies targeting DNA repair and cell cycle pathways may offer a novel, more effective approach to managing advanced EOC and reducing metastatic spread.

MicroRNAs signatures as potential molecular markers in mild cognitive impairment: a meta-analysis

Mild cognitive impairment (MCI) is characterized by a decline in cognitive functioning without significant interference in daily activities. Its high heterogeneity and elevated conversion rate to dementia pose challenges for accurate diagnosis and monitoring, highlighting the urgent need to identify methodologies focused on the early detection and intervention of MCI. Due to their biological characteristics, microRNAs (miRNAs) are potential candidates as non-invasive molecular markers for the identification and assessment of MCI progression. Therefore, in this study, we conducted a meta-analysis to identify the miRNAs commonly deregulated in MCI, focusing on expression profiles in plasma, serum, and extracellular vesicle samples. Our analysis identified eight upregulated miRNAs, including hsa-miR-149-3p, and four downregulated miRNAs, such as Let-7f-5p. Notably, hsa-miR-149-3p emerged as a central node in interaction networks, suggesting its crucial role in regulating cellular processes relevant to MCI. Additionally, pathway analysis revealed significant enrichment in biological processes associated with transcriptional regulation and neurodegeneration. Our results underscore the potential of circulating miRNAs as non-invasive molecular markers for MCI and open the possibility for new methodologies that enable more accurate diagnosis and monitoring of disease progression. Validating the expression of miRNAs such as hsa-miR-149-3p and Let-7f-5p, along with identifying their functional role in the specific context of MCI, is essential to establish their biological relevance. This work contributes to the understanding of the miRNA profile in mild cognitive impairment using easily accessible samples, which could be useful for the development of various strategies aimed at preventing or delaying MCI in individuals at risk of developing dementia, including Alzheimer's disease.

Characterizing Circulating microRNA Signatures of Type 2 Diabetes Subtypes

Type 2 diabetes (T2D) is a heterogeneous disease influenced by both genetic and environmental factors. Recent studies suggest that T2D subtypes may exhibit distinct gene expression profiles. In this study, we aimed to identify T2D cluster-specific miRNA expression signatures for the previously reported five clinical subtypes that characterize the underlying pathophysiology of long-standing T2D: severe insulin-resistant diabetes (SIRD), severe insulin-deficient diabetes (SIDD), mild age-related diabetes (MARD), mild obesity-related diabetes (MOD), and mild early-onset diabetes (MEOD). We analyzed the circulating microRNAs (miRNAs) in 45 subjects representing the five T2D clusters and 7 non-T2D healthy controls by single-end small RNA sequencing. Bioinformatic analyses identified a total of 430 known circulating miRNAs and 13 previously unreported novel miRNAs. Of these, 71 were upregulated and 37 were downregulated in either controls or individual clusters. Each T2D subtype was associated with a specific dysregulated miRNA profile, distinct from that of healthy controls. Specifically, 3 upregulated miRNAs were unique to SIRD, 1 to MARD, 9 to MOD, and 18 to MEOD. Among the downregulated miRNAs, 11 were specific to SIRD, 9 to SIDD, 2 to MARD, and 1 to MEOD. Our study confirms the heterogeneity of T2D, represented by distinguishable subtypes both clinically and epigenetically and highlights the potential of miRNAs as markers for distinguishing the pathophysiology of T2D subtypes.

Let-7b-5p sensitizes breast cancer cells to doxorubicin through Aurora Kinase B

MicroRNAs (miRNAs) are small, non-coding RNAs that regulate the expression level of the target genes in the cell. Breast cancer is responsible for the majority of cancer-related deaths among women globally. It has been proven that deregulated miRNAs may play an essential role in the progression of breast cancer. It has been shown in many cancers, including breast cancer, that aberrant expression of miRNAs may be associated with drug resistance. This study investigated the effect of let-7b-5p, detected by bioinformatics methods, on Dox resistance through the Aurora Kinase B (AURKB) gene. In silico analysis using publicly available miRNA expression, GEO datasets revealed that let-7b-5p significantly downregulated in BC. Further in silico studies revealed that of the genes among the potential targets of let-7b-5p, AURKB was the most negatively correlated and may be closely associated with Dox resistance. Expression analysis via quantitative PCR confirmed that let-7b-5p was downregulated and AURKB was upregulated in breast cancer tissue samples. Later, functional studies conducted with MCF-10A, MCF-7, and MDA-MB-231 cell lines demonstrated that let-7b-5p inhibits cancer cells through AURKB and sensitizes them to Dox resistance. In conclusion, it has been shown that the let-7b-5p/AURKB axis may be significant in breast cancer progression and the disruption in this axis may contribute to the trigger of Dox resistance.

Transcriptomic profiling and machine learning reveal novel RNA signatures for enhanced molecular characterization of Hashimoto's thyroiditis

While ultrasonography effectively diagnoses Hashimoto's thyroiditis (HT), exploring its transcriptomic landscape could reveal valuable insights into disease mechanisms. This study aimed to identify HT-associated RNA signatures and investigate their potential for enhanced molecular characterization. Samples comprising 31 HT patients and 30 healthy controls underwent RNA sequencing of peripheral blood. Differential expression analysis identified transcriptomic features, which were integrated using multi-omics factor analysis. Pathway enrichment, co-expression, and regulatory network analyses were performed. A novel machine-learning model was developed for HT molecular characterization using stacking techniques. HT patients exhibited increased thyroid volume, elevated tissue hardness, and higher antibody levels despite being in the early subclinical stage. Analysis identified 79 HT-associated transcriptomic features (3 mRNA, 6 miRNA, 64 lncRNA, 6 circRNA). Co-expression (77 nodes, 266 edges) and regulatory (18 nodes, 45 edges) networks revealed significant hub genes and modules associated with HT. Enrichment analysis highlighted dysregulation in immune system, cell adhesion and migration, and RNA/protein regulation pathways. The novel stacking-model achieved 95% accuracy and 97% AUC for HT molecular characterization. This study demonstrates the value of transcriptome analysis in uncovering HT-associated signatures, providing insights into molecular changes and potentially guiding future research on disease mechanisms and therapeutic strategies.

Non-coding RNAs secreted by renal cancer include piR_004153 that promotes migration of mesenchymal stromal cells

BACKGROUND

Renal cell cancer (RCC) is the most common and highly malignant subtype of kidney cancer. Mesenchymal stromal cells (MSCs) are components of tumor microenvironment (TME) that influence RCC progression. The impact of RCC-secreted small non-coding RNAs (sncRNAs) on TME is largely underexplored. Here, we comprehensively analysed the composition of exosomal sncRNAs secreted by RCC cells to identify those that influence MSCs.

METHODS

Exosomal sncRNAs secreted by RCC cells and normal kidney cells were analyzed using RNAseq, followed by qPCR validation. MSCs were treated by conditioned media (CM) derived from RCC cells and transfected with piRNA, followed by the analysis of proliferation, viability, migration and immunocytochemical detection of piRNA. Expression of MSCs genes was evaluated using microarray and qPCR. TCGA data were analyzed to explore the expression of sncRNAs in RCC tumors.

RESULTS

RNAseq revealed 40 miRNAs, 71 tRNAs and four piRNAs that were consistently secreted by RCC cells. qPCR validation using five independent RCC cell lines confirmed that expressions of miR-10b-3p and miR-125a-5p were suppressed, while miR-365b-3p was upregulated in exosomes from RCC cells when compared with normal kidney proximal tubules. The expression of miR-10b-3p and miR-125a-5p was decreased, whereas the expression of miR-365b-3p was increased in RCC tumors and correlated with poor survival of patients. Expressions of tRNA-Glu, tRNA-Gly, and tRNA-Val were the most increased, while tRNA-Gln, tRNA-Leu, and tRNA-Lys were top decreased in RCC exosomes when compared with normal kidney cells. Moreover, hsa_piR_004153, hsa_piR_016735, hsa_piR_019521, and hsa_piR_020365 were consistently upregulated in RCC exosomes. piR_004153 (DQ575660.1; aliases: hsa_piRNA_18299, piR-43772, piR-hsa-5938) was the most highly expressed in exosomes from RCC cells when compared with normal kidney cells. Treatment of MSCs with RCC CM resulted in upregulation of piR_004153 expression. Transfection of MSCs with piR_004153 stimulated their migration and viability, and altered expression of 35 genes, including downregulation of FGF2, SLC7A5, and WISP1. Immunocytochemistry confirmed the nuclear localization of piR_004153 transfected in MSCs.

CONCLUSION

RCC cells secrete multiple sncRNAs, including piR_004153 which targets MSCs, alters expression of FGF2, SLC7A5, and WISP1, and stimulates their motility and viability. To our knowledge, this is the first study showing that cancer-derived piRNA can enhance MSC migration.

Temporal Expression Analysis to Unravel Gene Regulatory Dynamics by microRNAs

MicroRNAs (miRNAs) are a class of small non-coding RNAs (sncRNAs) of length 21-25 nucleotides. These sncRNAs hybridize to repress their target genes and inhibit protein translation, thereby controlling regulatory functions in the cell. Integration of time-series matched small and RNA-seq data enables investigation of dynamic gene regulation through miRNAs during development or in response to a stimulus, such as stress. Here we summarize analysis strategies, such as probabilistic and regression-based models, that take advantage of the temporal dimension to investigate the complexity of miRNA regulation.

Identification of Potential Genes in Rheumatoid Arthritis-Associated Interstitial Lung Disease Using RNA-seq and In Vitro Analyses

Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is an increasingly recognized extra-articular manifestations (EAMs) in the RA, with highly morbidity and mortality. The identification of key molecules involved in RA-ILD has a high requirement in clinic, and the role of their transcriptional regulation in the etiology of RA-ILD is great significant for investigation. In this study, we collected the whole peripheral blood samples of RA-ILD and RA only patients to bulk RNA-sequence. Differential gene expression analysis was employed to identify key genes, common pathways, and potential drug targets for RA-ILD. Furthermore, RT-qPCR was conducted to verify potential biomarkers in RA-ILD. Four hundred seventy-eight differentially expressed genes (DEGs) were identified that related to chromatin-modifying enzymes. A robust correlation with immune and inflammation biological processes and pathways was indicated through enrichment analyses of these shared DEGs, like B cell receptor signaling pathway, complement activation, NF-kappa B signaling pathway. Protein-protein interaction network analysis further emphasized the significance of 12 hub genes, including CHD4, MUS81, CXCL8, NSUN6, RAD9A, CCL4, B3GAT1, KAT2A, TBX21, HDAC2, ERBB2, and ITGAL. Notably, NSUN6 expression was statistically significant in RA-ILD by the machine learning LASSO regression analysis and RT-qPCR. Our study provides novel insights into the molecular mechanisms of RA-ILD, identifies potential biomarkers, and lays the groundwork for future therapeutic strategies.

Screening miRNAs to Hinder the Tumorigenesis of Renal Clear Cell Carcinoma Associated with KDR Expression

INTRODUCTION

This study delved to understand the role of Kinase Insert Domain Receptor (KDR) and its associated miRNAs in renal cell carcinoma through an extensive computational analysis. The potential of our findings to guide future research in this area is significant.

METHODS

Our methods, which included the use of UALCAN and GEPIA2 databases, as well as miRDB, MirDIP, miRNet v2.0, miRTargetLink, MiEAA v2.1, TarBase v8.0, INTERNET, and miRTarBase, were instrumental in identifying the regulation of miRNA associated with KDR expression. The predicted miRNA was validated with the TCGA-KIRC patients' samples by implementing CancerMIRNome. The TargetScanHuman v8.0 was implemented to identify the associations between human miRNAs and KDR. A Patch Dock server analyzed the interactions between hsa-miR-200c-3p and KDR.

RESULTS

The KDR expression rate was investigated in the Kidney Renal Cell Carcinoma (KIRC) samples, and adjacent normal tissues revealed that the expression rate was significantly higher than the normal samples, which was evident from the strong statistical significance (P = 1.63e-12). Likely, the KDR expression rate was estimated as high at tumor grade 1 and gradually decreased till the metastasis grade, reducing the survival rate of the KIRC patients. To identify these signals early, we predicted a miRNA that could alter the expression of KDR. Furthermore, we uncovered the potential associations between miR-200c-3p expressions by regulating KDR towards the progression of KIRC.

DISCUSSION

Upon examining the outcome, it became evident that miR-200c-3p was significantly downregulated in KIRC compared to the normal samples. Moreover, the negative correlation was obtained for hsa-miR-200c-3p (R = - 0.276) along with the KDR expression describing that the increased rate of hsamiR- 200c-3p might reduce the KDR expression rate, which may suppress the KIRC initiation or progression.

CONCLUSION

The in-silico analysis indicated that the significant increase in KDR expression during the initiation of KIRC could serve as an early diagnostic marker. Moreover, KDR could be utilized to identify advancements in KIRC stages. Additionally, hsa-miR-200c-3p was identified as a potential regulator capable of downregulating and upregulating KDR expression among the 24 miRNAs screened. This finding holds promise for future research endeavors. Concurrent administration of the FDA-approved 5- fluorouracil with KIRC drugs, such as sorafenib, zidovudine, and everolimus, may have the potential to enhance the therapeutic efficacy in downregulating hsa-miR-200c-3p. However, further in vitro studies are imperative to validate these findings and gain a comprehensive understanding of the intricate regulatory interplay involving hsa-miR-200c-3p, KDR, 5-fluorouracil, and other FDA-approved drugs for the treatment of KIRC. This will facilitate the identification of KIRC stage progression and its underlying preventative mechanisms.

A Network Biology-Guided Investigation of the Long Noncoding RNAs' Role in Glaucoma

Glaucoma is a group of eye diseases characterized by progressive harm to the optic nerve that often results in loss of vision and blindness. Recent studies suggest that deregulation in the expression of a particular type of RNAs named long noncoding RNAs (lncRNAs) can impact the development of glaucoma and, hence, are promising targets for drug discovery. LncRNAs are transcripts with a length longer than 200 nucleotides that are not translated into proteins. Their extended length differentiates them from other non-coding RNAs such as microRNAs. Furthermore, lncRNAs exhibit diverse and often unpredictable regulatory functions within gene networks, unlike the well-defined gene silencing role of microRNAs. This chapter aims to discuss the role of lncRNAs in the pathogenesis of glaucoma. We will discuss and investigate lncRNAs linked to glaucoma, examine their functional regulation mechanisms in (glaucoma) gene networks, the extent of their (abnormal) expression in the disease, and their prospective as therapeutic targets. To this end, we performed lncRNA expression analysis from publicly available datasets and utilized this information to investigate their role in key pathways and biological mechanisms contributing to glaucoma progression. We employed a computational pipeline to construct glaucoma-associated lncRNA-miRNA, miRNA-TFs, gene-miRNA, protein-TF, and TF-TFs gene networks and used them to identify lncRNAs biomarkers for early diagnosis and disease progression monitoring. We identified lncRNA-enriched regulatory clusters and explored the potential of some of these lncRNA-gene clusters as targets for new therapies for glaucoma. Using this approach, we expect to give initial steps towards the elucidation of lncRNAs' role in glaucoma onset and progression.

Computational Prediction of Gene Regulation by lncRNAs

High-throughput sequencing technologies and innovative bioinformatics tools discovered that most of the genome is transcribed into RNA. However, only a fraction of the RNAs in cell translates into proteins, while the majority of them are categorized as noncoding RNAs (ncRNAs). The ncRNAs with more than 200 nt without protein-coding ability are termed long noncoding RNAs (lncRNAs). Hundreds of studies established that lncRNAs are a crucial RNA family regulating gene expression. Regulatory RNAs, including lncRNAs, modulate gene expression by interacting with RNA, DNA, and proteins. Several databases and computational tools have been developed to explore the functions of lncRNAs in cellular physiology. This chapter discusses the tools available for lncRNA functional analysis and provides a detailed workflow for the computational analysis of lncRNAs.

Multiplexed Molecular Endophenotypes Help Identify Hub Genes in Non-Small Cell Lung Cancer: Unlocking Next-Generation Cancer Phenomics

Next-generation cancer phenomics by deployment of multiple molecular endophenotypes coupled with high-throughput analyses of gene expression offer veritable opportunities for triangulation of discovery findings in non-small cell lung cancer (NSCLC) research. This study reports differentially expressed genes in NSCLC using publicly available datasets (GSE18842 and GSE229253), uncovering 130 common genes that may potentially represent crucial molecular signatures of NSCLC. Additionally, network analyses by GeneMANIA and STRING revealed significant coexpression and interaction patterns among these genes, with four notable hub genes-GRK5, CAV1, PPARG, and CXCR2-identified as pivotal in NSCLC progression. Validation of these hub genes indicated their consistent downregulation in tumor tissues compared to normal counterparts. Gene expression across the endophenotypes representing pathological stages revealed distinct downregulation trends, emphasizing their putative roles as biomarkers for cancer progression. Moreover, three miRNAs (hsa-miR-429, hsa-miR-335-5p, and hsa-miR-126-3p) showed strong associations with these hub genes, while SREBF1 emerged as a relevant transcription factor. Pathway enrichment analysis identified the chemokine signaling pathway as significantly associated with these genes, highlighting its role in tumor progression and immune evasion. Cell-type enrichment analysis indicated that endothelial cells may play a significant role in NSCLC pathogenesis. Finally, survival analysis demonstrated that GRK5 is a potential oncogenic marker, whereas CAV1 may have a protective effect. These findings collectively underscore the critical molecular interactions in NSCLC and suggest novel paths for translational research, targeted therapies, and prognostic markers in clinical settings. They also attest to the promises of next-generation cancer phenomics using multiple endophenotypes for discovery and triangulation of novel findings.

CIRCULATING miR-1-3p, miR-96-5p, miR-148a-3p, and miR-375-3p Support Differentiation Between Prostate Cancer and Benign Prostate Lesions

INTRODUCTION

microRNAs (miRNAs) are small noncoding RNAs and promising cancer biomarkers. Prostate-specific antigen (PSA) testing revolutionized prostate cancer (PCa) diagnostics and monitoring. However, PSA testing also contributes to PCa overdiagnoses that are detrimental on patients' health and may lead to overtreatment. Here, we searched for circulating miRNAs that could serve as biomarkers facilitating differentiation between PCa and benign prostate hyperplasia (BPH).

PATIENTS

66 patients with PCa or BPH were investigated (33 patients in each cohort). Men with PCa underwent minimally invasive radical prostectomy (RP), whereas men with BPH underwent either holmium laser enucleation of the prostate (HOLEP), transurethral resection of the prostate (TURP) or simple prostatectomy.

METHODS

We performed RNAseq of PCa and BPH serum samples, integrated our data with TCGA-PRAD cohort, followed by qPCR validation using independent cohort of PCa and BPH patients.

RESULTS

RNAseq detected 295 miRNAs in serum samples, including 283 miRNAs that were both expressed by PCa tissues and present in PCa sera. 10 miRNAs were selected for qPCR validation. Expression of serum miR-1-3p, miR-96-5p, miR-148a-3p, and miR-375-3p was decreased in PCa patients when compared to BPH samples. Diagnostic accuracy of combinations of PSA with geometric means of [miR-1-3p, miR-148a-3p], [miR-148a-3p, miR-375-3p], and [miR-375-3p, miR-96-5p] exceed diagnostic value of PSA alone, with the top AUC 0.97 for [miR-1-3p, miR-148a-3p]/PSA (cut-off < 0.002893, sensitivity 95.83 %, specificity 91.30 %).

CONCLUSIONS

In conclusion, we found a miRNAs that can support PCa diagnosis.

Integrative analysis of anoikis-related genes prognostic signature with immunotherapy and identification of CDKN3 as a key oncogene in lung adenocarcinoma

Anoikis, a form of programmed cell death induced by loss of cell contact, is closely associated with tumor invasion and metastasis, making it highly significant in lung cancer research. We examined the expression patterns and prognostic relevance of Anoikis-related genes (ARGs) in lung adenocarcinoma (LUAD) using the TCGA-LUAD database. This study identified molecular subtypes associated with Anoikis in LUAD and conducted functional enrichment analyses. We constructed an ARG risk score using univariate least absolute shrinkage and selection operator (LASSO) Cox regression, validated externally with GEO datasets and clinical samples. The clinical applicability of the prognostic model was evaluated using nomograms, calibration curves, decision curve analysis (DCA), and time-dependent AUC assessments. We identified four prognostically significant genes (PLK1, SLC2A1, CDKN3, PHLDA2) and two ARG-related molecular subtypes. ARGs were generally upregulated in LUAD and correlated with multiple pathways including the cell cycle and DNA replication. The prognostic model indicated that the low-risk group had better outcomes and significant correlations with clinicopathological features, tumor microenvironment, immune therapy responses, drug sensitivity, and pan-RNA epigenetic modification-related genes. Patients with low-risk LUAD were potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. Prognostic ARGs' distribution and expression across various immune cell types were further analyzed using single-cell RNA sequencing. The pivotal role of CDKN3 in LUAD was confirmed through qRT-PCR and gene knockout experiments, demonstrating that CDKN3 knockdown inhibits tumor cell proliferation, migration, and invasion. Additionally, we constructed a ceRNA network involving CDKN3/hsa-miR-26a-5p/SNHG6, LINC00665, DUXAP8, and SLC2A1/hsa-miR-218-5p/RNASEH1-AS1, providing new insights for personalized and immune therapy decisions in LUAD patients.

Non-Invasive miRNA Profiling for Differential Diagnosis and Prognostic Stratification of Testicular Germ Cell Tumors

BACKGROUND/OBJECTIVES

Testicular germ cell tumors (TGCT) are common in young adult men and have high cure rates. Conventional serum tumor markers and imaging are not able to differentiate between histologic subtypes of the disease, which portend different prognoses and require distinct therapeutic strategies. Micro-RNAs (miRNAs) are small non-coding transcripts involved in the post-transcriptional regulation of gene expression, which have emerged as promising biomarkers in a variety of tumors. This study aimed to assess the potential of differentially expressed miRNAs in differential diagnosis and prognostication among TGCT patients with various histologic subtypes.

METHODS

Transcriptomic analysis of 134 patients from The Cancer Genome Atlas (TCGA)-TGCT database was conducted. miRNA differential expression analysis among seminomatous, embryonal carcinoma, mixed GCT, and teratoma was performed, followed by ROC curve analysis of the most significantly up- and downregulated miRNAs, respectively. Statistical associations of miRNA expression with AJCC stage were also investigated along with miRNA target network analysis and evaluation of miRNA detection in patients' fluids.

RESULTS

Upregulation of seven miRNAs (hsa-mir-135a-1, hsa-mir-135a-2, hsa-mir-200a, hsa-mir-200b, hsa-mir-203b, hsa-mir-375, hsa-mir-582) and downregulation of seven additional miRNAs (hsa-mir-105-1, hsa-mir-105-2, hsa-mir-4433a, hsa-mir-548x, hsa-mir-5708, hsa-mir-6715a, hsa-mir-767) were identified. miRNAs displayed a high sensitivity/specificity of 0.94/1.0 (AUC = 0.98) for the upregulated and 0.97/0.94 (AUC = 0.96) for the downregulated signature. Deregulated expression of these miRNAs was significantly associated with AJCC stage and distant organ metastasis (p < 0.001), overall supporting their prognostic strength. Both signatures were detectable in body fluids, particularly urine. miRNA target network analysis supported the functional role of these miRNAs in the regulation of cancer-related processes such as cell proliferation via deregulation of pivotal oncogenes.

CONCLUSIONS

These findings support the clinical value of two novel miRNA signatures in differential diagnosis and prognostic stratification of various histologic subtypes of TGCT, with potential treatment implications.

Identifying Hub Genes and miRNAs Associated with Alzheimer's Disease: A Bioinformatics Pathway to Novel Therapeutic Strategies

Alzheimer's disease (AD) is a neurodegenerative disorder that mainly affects the elderly population. It is characterized by cognitive impairment and dementia due to abnormal levels of amyloid beta peptide (Aβ) and axonal Tau protein in the brain. However, the complex underlying mechanisms affecting this disease are not yet known, and there is a lack of standardized biomarkers and therapeutic targets. Therefore, in this study, by means of bioinformatics analysis, AD-affected brain tissue was analyzed using the GSE138260 dataset, identifying 612 differentially expressed genes (DEGs). Functional analysis revealed 388 upregulated DEGs associated with sensory perception and 224 downregulated DEGs linked to the regulation and modulation of synaptic processes. Protein-protein interaction network analysis identified 20 hub genes. Furthermore, miRNA target gene networks revealed 1767 miRNAs linked to hub genes, among which hsa-mir-106a-5p, hsa-mir-17-5p, hsa-mir-26a-5p, hsa-mir-27a-3p and hsa-mir-34a-5p were the most relevant. This study presents novel biomarkers and therapeutic targets for AD by analyzing the information obtained with a comprehensive literature review, providing new potential targets to study their role in AD.

miR-542-3p/PIK3R1 axis is involved in hsa_circ_0087104-mediated inhibition of esophageal squamous cell carcinoma metastasis

Esophageal squamous cell carcinoma (ESCC), the most predominant subtype of esophageal cancer, is notorious for its high lymph node metastatic potential and poor prognosis. Growing evidence has demonstrated crucial function of circRNAs in human malignancies. However, the knowledge of circRNAs in lymph node metastasis of ESCC is still inadequate. In this study, a series of bioinformatic analyses and experimental validation were performed. By performing differential expression analysis and selection for GEO dataset GSE150476, a total of 8 circRNAs associated with lymph node metastasis of ESCC were identified. Expression analysis confirmed their low expression in ESCC tissues (relative to normal tissues) or metastatic sites (relative to primary sites). By combination of binding miRNAs from CSCD and starBase databases, six potential miRNAs (miR-532-5p, miR-2681-5p, miR-670-5p, miR-1252-5p, miR-382-3p and miR-542-3p) were predicted and a circRNA-miRNA regulatory network was constructed. Next, 695 target genes were predicted to bind to the 6 miRNAs. After conducting protein-protein interaction (PPI) network analysis, hub gene identification and expression analysis, a hub gene PIK3R1 was identified as the most potential downstream target gene of hsa_circ_0087104/miR-542-3p in ESCC. Hsa_circ_0087104 and PIK3R1 were decreased while miR-542-3p was increased in ESCC cells compared with normal esophageal epithelial cell line. Luciferase reporter and MS2-RIP assays confirmed the direct bind of miR-542-3p to hsa_circ_0087104 or PIK3R1. Hsa_circ_0087104 increased PIK3R1 expression but ectopic expression of miR-542-3p reversed hsa_circ_0087104-mediated PIK3R1 overexpression in ESCC. Overexpression of hsa_circ_0087104 suppressed in vitro migration and invasion of ESCC cells and this suppressive effect could be weakened by upregulation of miR-542-3p. Collectively, the current findings elucidated a potential hsa_circ_0087104/miR-542-3p/PIK3R1 axis that might be involved in suppression of lymph node metastasis of ESCC.

A Molecular Signature of the Ubiquitin-Proteasome System for Forecasting Prognosis in Thyroid Carcinoma Patients

Background

The ubiquitin-proteasome system (UPS) is vital for protein quality control and its dysregulation is linked to diseases, including cancer. Targeting the UPS is becoming a promising approach in cancer therapy. However, the role of UPS modulation in thyroid carcinoma (THCA) remains to be fully elucidated.

Methods

Initially, we utilized data from The Cancer Genome Atlas (TCGA) database to employ weighted gene co-expression network analysis (WGCNA) with LASSO regression to develop a prognostic model for core UPS genes implicated in THCA. Subsequently, we stratified the THCA training set into two distinct subtypes based on ubiquitin-proteasome system prognostic model score (UPS-PMS) characteristics. Key genes within the model were then subjected to functional analysis, immunotherapy evaluation, and drug sensitivity studies.

Results

We delineated a prognostic model of the UPS comprising six genes, which we subsequently demonstrated was capable of forecasting patient prognosis. Moreover, our findings indicated a substantial correlation between UPS-PMS and immune microenvironmental factors, notably a negative correlation with myeloid immune cells and a potential influence on the Th1 to Th2 cells ratio. Especially, we observed a significant association between high UPS-PMS and an immunosuppressive microenvironment. Then, we elucidated the biological distinctions among various THCA sample subtypes, highlighting that the cluster_1 subtype is associated with an unfavorable prognosis. Of note, KCNA1 was identified as a pivotal prognostic gene within the UPS-PMS framework. We constructed a three-tiered regulatory network centered on KCNA1-related competing endogenous RNA (ceRNA). Furthermore, our results suggested that KCNA1 has potential as a target for immunotherapeutic strategies. Concurrently, drug sensitivity analyses demonstrated that high KCNA1 expression promoted gemcitabine resistance in patients, while KCNA1 knockdown increased sensitivity to gemcitabine.

Conclusion

In conclusion, we developed a novel UPS-based prognostic model for THCA, identified key gene KCNA1, and assessed immunotherapy and drug sensitivity, revealing new therapeutic targets.

Effective data visualization strategies in untargeted metabolomics

Covering: 2014 to 2023 for metabolomics, 2002 to 2023 for information visualizationLC-MS/MS-based untargeted metabolomics is a rapidly developing research field spawning increasing numbers of computational metabolomics tools assisting researchers with their complex data processing, analysis, and interpretation tasks. In this article, we review the entire untargeted metabolomics workflow from the perspective of information visualization, visual analytics and visual data integration. Data visualization is a crucial step at every stage of the metabolomics workflow, where it provides core components of data inspection, evaluation, and sharing capabilities. However, due to the large number of available data analysis tools and corresponding visualization components, it is hard for both users and developers to get an overview of what is already available and which tools are suitable for their analysis. In addition, there is little cross-pollination between the fields of data visualization and metabolomics, leaving visual tools to be designed in a secondary and mostly ad hoc fashion. With this review, we aim to bridge the gap between the fields of untargeted metabolomics and data visualization. First, we introduce data visualization to the untargeted metabolomics field as a topic worthy of its own dedicated research, and provide a primer on cutting-edge visualization research into data visualization for both researchers as well as developers active in metabolomics. We extend this primer with a discussion of best practices for data visualization as they have emerged from data visualization studies. Second, we provide a practical roadmap to the visual tool landscape and its use within the untargeted metabolomics field. Here, for several computational analysis stages within the untargeted metabolomics workflow, we provide an overview of commonly used visual strategies with practical examples. In this context, we will also outline promising areas for further research and development. We end the review with a set of recommendations for developers and users on how to make the best use of visualizations for more effective and transparent communication of results.

Integration of miRNA expression analysis of purified leukocytes and whole blood reveals blood-borne candidate biomarkers for lung cancer

Changes in leukocyte populations may confound the disease-associated miRNA signals in the blood of cancer patients. We aimed to develop a method to detect differentially expressed miRNAs from lung cancer whole blood samples that are not influenced by variations in leukocyte proportions. The Ref-miREO method identifies differential miRNAs unaffected by changes in leukocyte populations by comparing the within-sample relative expression orderings (REOs) of miRNAs from healthy leukocyte subtypes and those from lung cancer blood samples. Over 77% of the differential miRNAs observed between lung cancer and healthy blood samples overlapped with those between myeloid-derived and lymphoid-derived leukocytes, suggesting the potential impact of changes in leukocyte populations on miRNA profile. Ref-miREO identified 16 differential miRNAs that target 19 lung adenocarcinoma-related genes previously linked to leukocytes. These miRNAs showed enrichment in cancer-related pathways and demonstrated high potential as diagnostic biomarkers, with the LASSO regression models effectively distinguishing between healthy and lung cancer blood or serum samples (all AUC > 0.85). Additionally, 12 of these miRNAs exhibited significant prognostic correlations. The Ref-miREO method offers valuable candidates for circulating biomarker detection in cancer that are not affected by changes in leukocyte populations.

Identification of prostate cancer associated genes for diagnosis and prognosis: a modernized in silico approach

Prostate cancer (PCa) ranks as the second leading cause of cancer-related deaths in men. Diagnosing PCa relies on molecular markers known as diagnostic biomarkers, while prognostic biomarkers are used to identify key proteins involved in PCa treatments. This study aims to gather PCa-associated genes and assess their potential as either diagnostic or prognostic biomarkers for PCa. A corpus of 152,064 PCa-related data from PubMed, spanning from May 1936 to December 2020, was compiled. Additionally, 4199 genes associated with PCa terms were collected from the National Center of Biotechnology Information (NCBI) database. The PubMed corpus data was extracted using pubmed.mineR to identify PCa-associated genes. Network and pathway analyses were conducted using various tools, such as STRING, DAVID, KEGG, MCODE 2.0, cytoHubba app, CluePedia, and ClueGO app. Significant marker genes were identified using Random Forest, Support Vector Machines, Neural Network algorithms, and the Cox Proportional Hazard model. This study reports 3062 unique PCa-associated genes along with 2518 corresponding unique PMIDs. Diagnostic markers such as IL6, MAPK3, JUN, FOS, ACTB, MYC, and TGFB1 were identified, while prognostic markers like ACTB and HDAC1 were highlighted in PubMed. This suggests that the potential target genes provided by PubMed data outweigh those in the NCBI database.

Integrative analysis of FADS3 as a marker for prognosis and immunity in head and neck squamous cell carcinoma

BACKGROUND

Long-chain polyunsaturated fatty acid formation requires fatty acid desaturase (FADS), which is strongly linked to cancer progression. Nevertheless, it's unclear how FADS3 functions in head and neck squamous cell carcinoma (HNSCC).

METHODS

HNSCC cases were retrieved from TCGA and GEO databases, and FADS members with transcriptionally differential expression were identified. Clinical survival, tumor microenvironment (TME), and potential pathogenic mechanism in HNSCC were also investigated. These results were validated using tissue staining, flow cytometry and functional studies in HNSCC cell lines.

RESULTS

When comparing HNSCC to normal epithelial tissues, FADS3 expression was much higher in the former. FADS3 upregulation was correlated with poor clinical outcomes. FADS3 was an independent prognostic factor for poor overall survival in HNSCC patients. KEGG, GO, and GSEA revealed that FADS3 expression correlated with several immune-related pathways and the epithelial-mesenchymal transition (EMT). Knocking down FADS3 restrained HNSCC cell proliferation, migration, invasion, and EMT. Single-cell dataset analysis showed an association between FADS3 and TME features. Further investigation revealed that FADS3high tumor was accompanied with less CD8+ T cells in situ tissue and peripheral blood. FADS3 was positively correlated with immune-related molecules and could predict the adverse efficacy of immunotherapy. Finally, we constructed a CYTOR/hsa-let-7c-5p axis regulating FADS3 expression in HNSCC progression.

CONCLUSIONS

FADS3 may represent a target for treatment in HNSCC, which is linked to prognosis, EMT, immune infiltration, and ceRNA regulatory network of HNSCC.

The emerging role of TIM-3 in colorectal cancer: a promising target for immunotherapy

INTRODUCTION

Colorectal cancer (CRC) imposes a substantial worldwide health burden, necessitating innovative strategies to enhance therapeutic outcomes. T cell immunoglobulin-3 (Tim-3), an immune checkpoint, enhances immunological tolerance. Tim-3's role in CRC surpasses its conventional function as an indicator of dysfunction in T lymphocytes.

AREAS COVERED

This review provides an all-inclusive summary of the structural and functional attributes of Tim-3's involvement in the case of CRC. It explores the implications of Tim-3 expression in CRC with regard to tumor progression, clinical characteristics, and therapeutic approaches. Furthermore, it delves into the intricate signaling pathways and molecular mechanisms through which Tim-3 exerts its dual function in both immunity against tumors and immune evasion.

EXPERT OPINION

Understanding Tim-3's complicated network of interactions in CRC has significant consequences for the development of novel immunotherapeutic strategies targeted toward restoring anti-tumor immune responses and improving patient survival. Tim-3 is an important and valuable target for CRC patient risk classification and treatment because it regulates a complex network of strategies for suppressing immune responses, including causing T cell exhaustion, increasing Treg (regulatory T-cell) proliferation, and altering antigen-presenting cell activity.

Investigating gene expression datasets of hippocampus tissue to discover Alzheimer's disease-associated molecular markers

BACKGROUND

Alzheimer's disease (AD) is an advancing neurodegenerative disorder distinguished by the formation of amyloid plaques and neurofibrillary tangles in the human brain. Nevertheless, the lack of peripheral biomarkers that can detect the development of AD remains a significant limitation.

OBJECTIVE

The main aim of this work was to discover the molecular markers associated with AD.

METHODS

We conducted a comprehensive microarray analysis of gene expression data from hippocampus tissue in AD patients and control samples using three microarray datasets (GSE1297, GSE28146, and GSE29378) collected from Gene Expression Omnibus (GEO). The datasets were pre-processed and normalized, revealing 346 significant genes, 103 of which were upregulated and 243 downregulated. The PPI network of significant genes was constructed to detect the top 50 hub genes, which were then further analyzed using Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes pathway (KEGG), and GSEA, revealing 47 key genes involved in AD-related pathways. These key genes were then subjected to feed forward loop (FFL) motif analysis for the prediction of transcriptional factors (TFs) and microRNAs (miRNAs) mediated gene regulatory networks.

RESULTS

The interaction of AD-associated TFs HNF4A, SPI1, EGR1, STAT3, and MYC and miRNAs hsa-miR-155-5p and hsa-miR-16-5p in the transcriptional and post-transcriptional events of 3 upregulated and 10 downregulated genes: H2AFZ, MCM3, MYO1C, AXIN1, CCND1, ETS2, MYH9, RELA, RHEB, SOCS3, TBL1X, TBP, TXNIP, and YWHAZ, respectively, has been identified. The miRNA/TF-mediated three types of the FFL motifs, i.e., miRNA-FFL, TF-FFL, and composite-FFL, were constructed, and seven common genes among these FFL were identified: CCND1, MYH9, SOCS3, RHEB, MYO1C, TXNIP, AXIN1, and TXNIP.

CONCLUSIONS

These findings may provide insights into the development of potential molecular markers for therapeutic management of AD.