Microarray Data Analysis Research Articles

An Investigation of the Effect of the Traditional Naxi Herbal Formula Against Liver Cancer Through Network Pharmacology, Molecular Docking, and In Vitro Experiments

Background/Objectives: The formula Chong-Lou-Yao-Fang (CLYF) is an herbal medicinal formulation developed by the indigenous Naxi people for treating liver cancer. This study was to reveal the biological activity, potential targets, and molecular mechanisms of CLYF for cancer treatment. Methods: Network pharmacology, microarray data analysis, survival analysis, and molecular docking were employed to predict potential compounds, targets, and pathways for the treatment of liver cancer. In vitro experiments and Western blot validation were conducted to confirm these predictions. Results: 35 key compounds and 20 core targets were screened from CLYF, involving signaling pathways for PI3K–Akt, MAPK, hepatitis B and C, which were effective for liver cancer treatment. Microarray data analysis and survival analysis indicated that EGFR and TP53 serve as promising biomarkers for diagnosis and prognosis in liver cancer. Molecular docking revealed stable binding between EGFR, TP53, and AKT1 with active ingredients. Cell experiments confirmed that CLYF-A suppressed cell proliferation, induced apoptosis, and caused cell cycle arrest in HepG2 cells, which were associated with a loss of mitochondrial membrane potential. Compared to the control group, the relative protein expression levels of EGFR and AKT1 significantly decreased following treatment with CLYF-A, while TP53 levels increased significantly. Conclusions: Verification of the anticancer activity of CLYF and its potential mechanisms may have important implications for anticancer therapies. Our results may provide a scientific basis for the clinical use of CLYF for cancer treatment and have important implications for developing pharmaceutical preparations, which also need more pharmacological experiments, clinical experiments, and in vivo experiments.

Identification of Specific microRNAs in Adipose Tissue Affected by Lipedema

Lipedema is a chronic disorder affecting women with a 10% incidence worldwide. It is often confused with obesity. This study was undertaken to study microRNAs in lipedema tissue assessed by direct hybridization using the robust n-counter flex DX CE-IVD platform. The mean age of the subjects participating in the study was 40.29 (±12.17). The mean body weight and BMI were 67.37 (±10.02) and 25.75 (±4.10), respectively. The lipedema stages included were I and II. The differential expressed human (hsa)-miRNAs were determined according to a log2 fold-change (LFC) of 0.5 and p value < 0.05. To these, increased expression of hsa-let-7g-5p was evident, as well as reduced levels of hsa-miR-371a-5p, -4454+7975, -365a+b-3p, -205-5p, -196a-5p, -4488, -2116-5p, -141-3p, -208a-3p, -302b-3p, 374a-5p, and -1297. Then, several bioinformatics tools were used to analyze microarray data focusing on validated target genes in silico. KEGG and Gene Ontology (GO) pathway enrichment analysis was conducted. Furthermore, the protein–protein interaction and co-expression network were analyzed using STRING and Cytoscape, respectively. The most upregulated miRNA mainly affected genes related to cell cycle, oocyte meiosis, and inflammatory bowel disease. The downregulated microRNAs were related to endocrine resistance, insulin resistance, hypersensitivity to AGE-RAGEs, and focal adhesion. Finally, we validated by RT-PCR the upregulated hsa-let-7g-5p and two down-regulated ones, hsa-miR-205-5p and hsa-miR-302b-3p, confirming microarray results. In addition, three mRNA target miRNAs were monitored, SMAD2, the target of the hsa-let-7g-5p, and ESR1 and VEGFA, the target of hsa-miR-205-5p and hsa-miR-302b-3p, respectively. Our results open a new direction for comprehending biochemical mechanisms related with the pathogenesis of lipedema, shedding light on this intricate pathophysiological condition that could bring to light possible biomarkers in the future.

PhenoMetaboDiff: R Package for Analysis and Visualization of Phenotype Microarray Data

PhenoMetaboDiff: R Package for Analysis and Visualization of Phenotype Microarray Data

CTSD is the key therapeutic target of Jinshui Liujun decoction in treating chronic bronchitis

This study used network pharmacology, bioinformatics, molecular docking and molecular dynamics simulations to evaluate the pharmacological mechanism of Jinshui Liujun decoction in treating chronic bronchitis. The network pharmacology constructed and analysed the drug-disease targets network. Microarray data analysis revealed CTSD as a key therapeutic target gene. Molecular docking and molecular dynamics simulations results indicated CTSD, can bind with β-sitosterol, cerevisterol, stigmasterol effectively. This study identifies the mechanism of action and gene expression of the key therapeutic target CTSD of Jinshui Liujun decoction in the treatment of chronic bronchitis, and verifies its binding stability with the key active components, aiming to provide new targets and research directions for the clinical treatment of chronic bronchitis.

Gallic Acid Alleviates Glucolipotoxicity-Induced Nephropathy by miR-709-NFE2L2 Pathway in db/db Mice on a High-Fat Diet.

Type 2 diabetes mellitus (T2DM) has become a major global issue, with diabetic nephropathy (DN) ranking as one of its most serious complications. The involvement of microRNAs (miRNAs) in the progression of T2DM and DN is an area of active research, yet the molecular mechanisms remain only partially elucidated. Gallic acid (GA), a naturally occurring polyphenolic compound found in various plants such as bearberry leaves, pomegranate root bark, tea leaves, and oak bark, has demonstrated antioxidant properties that may offer therapeutic benefits in DN. The study aimed to investigate the therapeutic potential of GA in mitigating kidney fibrosis, oxidative stress and inflammation, within a glucolipotoxicity-induced diabetic model using db/db mice. The mice were subjected to a high-fat diet to induce glucolipotoxicity, a condition that mimics the metabolic stress experienced in T2DM. Through microarray data analysis, we identified a significant upregulation of renal miR-709a-5p in the diabetic mice, linking this miRNA to the pathological processes underlying DN. GA treatment was shown to boost the activity of including catalase, essential antioxidant enzymes, glutathione peroxidase and superoxide dismutase, while also reducing lipid accumulation in the kidneys, indicating a protective effect against HFD-induced steatosis. In vitro experiments further revealed that silencing miR-709a-5p in MES-13 renal cells led to a reduction in oxidative stress markers, notably lowering lipid peroxidation markers, and significantly boosting the activity of antioxidant defenses. Additionally, NFE2L2, a crucial transcription factor involved in the antioxidant response, was identified as a direct target of miR-709a-5p. The downregulation of miR-709a-5p by GA suggests that this polyphenol mitigates glucolipotoxicity-induced lipogenesis and oxidative stress, potentially offering a novel therapeutic avenue for managing diabetic fatty liver disease and DN. Our findings indicate that GA exerts a protective effect in DN by downregulating miR-709a-5p, thereby alleviating oxidative stress through the suppression of NFE2L2. The results highlight the potential of GA and NFE2L2-activating agents as promising therapeutic strategies in the treatment of DN.

Comprehensive analysis of chromosomal breakpoints and candidate genes associated with male infertility: insights from cytogenetic studies and expression analyses.

The study aimed to investigate prevalent chromosomal breakpoints identified in balanced structural chromosomal anomalies and to pinpoint potential candidate genes linked with male infertility. This was acchieved through a comprehensive approach combining RNA-seq and microarray data analysis, enabling precise identification of candidate genes. The Cytogenetics data from 2,500 infertile males referred to Royan Research Institute between 2009 and 2022 were analyzed, with 391 cases meeting the inclusion criteria of balanced chromosomal rearrangement. Of these, 193 cases exhibited normal variations and were excluded from the analysis. By examining the breakpoints, potential candidate genes were suggested. Among the remaining 198 cases, reciprocal translocations were the most frequent anomaly (129 cases), followed by Robertsonian translocations (43 cases), inversions (34 cases), and insertions (3 cases).Some patients had more than one chromosomal abnormality. Chromosomal anomalies were most frequently observed in chromosomes 13 (21.1%), 14 (20.1%), and 1 (16.3%) with 13q12, 14q12, and 1p36.3 being the most prevalent breakpoints, respectively. Chromosome 1 contributed the most to reciprocal translocations (20.2%) and inversions (17.6%), while chromosome 14 was the most involved in the Robertsonian translocations (82.2%). The findings suggested that breakpoints at 1p36.3 and 14q12 might be associated with pregestational infertility, whereas breakpoints at 13q12 could be linked to both gestational and pregestational infertility. Several candidate genes located on common breakpoints were proposed as potentially involved in male infertility. Bioinformatics analyses utilizing three databases were conducted to examine the expression patterns of 78 candidate genes implicated in various causes of infertility.‏ In azoospermic individuals, significant differential expression was observed in 19 genes: 15 were downregulated (TSSK2, SPINK2, TSSK4, CDY1, CFAP70, BPY2, BTG4, FKBP6, PPP2R1B, SPECC1L, CENPJ, ‏SKA3, FGF9, NODAL, CLOCK), while four genes were upregulated ‏(‏HSPB1, MIF, PRF1, ENTPD6). In the case of Asthenozoospermia, seven genes showed significant upregulation (PRF1, DDX21, KIT, SRD5A3, MTCH1, DDX50, NODAL). Though RNA-seq data for Teratozoospermia were unavailable, microarray data revealed differential expression insix genes: three downregulated (BUB1, KLK4, PIWIL2) and three upregulated (AURKC, NPM2, RANBP2). These findings enhance our understanding of the molecular basis of male infertility and could provide valuable insights for future diagnostic and therapeutic strategies.

Key Genes Involved in the Beneficial Mechanism of Hyperbaric Oxygen for Glioblastoma and Predictive Indicators of Hyperbaric Oxygen Prolonging Survival in Glioblastoma Patients.

The prognosis of glioblastoma is poor, and therapy-resistance is largely attributed to intratumor hypoxia. Hyperbaric oxygen (HBO) effectively alleviates hypoxia. However, the sole role of HBO in glioblastoma remains controversial. We previously reported that HBO can promote apoptosis, shorten protrusions, and delay growth of glioblastoma, but the molecular mechanism is unclear. We aimed to test candidate genes in HBO-exposed glioblastoma cells and to analyze their correlation with the survival of glioblastoma patients. Glioblastoma cell lines exposed to repetitive HBO or normobaric air (NBA) were collected for RNA isolation and microarray data analysis. GO analysis, KEGG pathway analysis and survival analysis of the differentially expressed genes (DEGs) were performed. HBO not only inhibited hypoxia-inducing genes including CA9, FGF11, PPFIA4, TCAF2 and SLC2A12, but also regulated vascularization by downregulating the expression of COL1A1, COL8A1, COL12A1, RHOJ and FILIP1L, ultimately attenuated hypoxic microenvironment of glioblastoma. HBO attenuated inflammatory microenvironment by reducing the expression of NLRP2, CARD8, MYD88 and CD180. HBO prevented metastasis by downregulating the expression of NTM, CXCL12, CXCL13, CXCR4, CXCR5, CDC42, IGFBP3, IGFBP5, GPC6, MMP19, ADAMTS1, EFEMP1, PTBP3, NF1 and PDCD1. HBO upregulated the expression of BAK1, PPIF, DDIT3, TP53I11 and FAS, whereas downregulated the expression of MDM4 and SIVA1, thus promoting apoptosis. HBO upregulated the expression of CDC25A, MCM2, PCNA, RFC33, DSCC1 and CDC14A, whereas downregulated the expression of ASNS, CDK6, CDKN1B, PTBP3 and MAD2L1, thus inhibiting cell cycle progression. Among these DEGs, 17 indicator-genes of HBO prolonging survival were detected. HBO is beneficial for glioblastoma. Glioblastoma patients with these predictive indicators may prolong survival with HBO therapy. These potential therapeutic targets especially COL1A1, ADAMTS1 and PTBP3 deserve further validation.

An approach based on clustering for detecting differentially expressed genes in microarray data analysis

An approach based on clustering for detecting differentially expressed genes in microarray data analysis

Reference gene panel for urinary exosome-based molecular diagnostics in patients with kidney disease.

Kidney disease is a severe complication of diabetes that often leads to end-stage renal disease. Early diagnosis is crucial for prevention or delay. However, the current diagnostic methods, with their limitations in detecting the disease in its early stages, underscore the urgency and importance of finding new solutions. miRNAs encapsulated inside urinary exosomes (UEs) have potential as early biomarkers for kidney diseases. The need for reference miRNAs for accurate interpretation currently limits their translational potential. To identify consistently expressing reference miRNAs from UEs of controls and patients with type 2 diabetesmellitus (T2DM) and biopsy-confirmed kidney diseases. miRNA profiling was performed on UEs from 31 human urine samples using a rigorous and unbiased method. The UEs were isolated from urine samples collected from healthy individuals (n = 6), patients with T2DM (n = 13), and T2DM patients who also had kidney diseases (including diabetic nephropathy, n = 5; membranous nephropathy, n = 5; and IgA nephropathy, n = 2) through differential ultracentrifugation. After characterizing the UEs, miRNA expression profiling using microarray technology was conducted. Microarray data analysis identified 14 miRNAs that were consistently expressed in UEs from 31 human samples, representing various kidney conditions: diabetic controls, diabetic nephropathy, membrane nephropathy, IgA nephropathy, and healthy controls. Through in silico analysis, we determined that 10 of these miRNAs had significant potential to serve as reference genes in UEs. We identified uniformly expressing UE miRNAs that could serve as reference genes kidney disease biomarkers.

Analysis of chromatin accessibility in peripheral blood mononuclear cells from patients with early-stage breast cancer.

Objective: This study was aimed at exploring a specific open region of chromatin in the peripheral blood mononuclear cells (PBMCs) of patients with breast cancer and evaluating its feasibility as a biomarker for diagnosing and predicting breast cancer prognosis. Methods: We obtained PBMCs from breast cancer patients and healthy people for the assay for transposase-accessible chromatin (ATAC) sequencing (n = 3) and obtained the GSE27562 chip sequencing data for secondary analyses. Through bioinformatics analysis, we mined the pattern changes for chromatin accessibility in the PBMCs of breast cancer patients. Results: A total of 1,906 differentially accessible regions (DARs) and 1,632 differentially expressed genes (DEGs) were identified via ATAC sequencing. The upregulated DEGs in the disease group were mainly distributed in the cells, organelles, and cell-intima-related structures and were mainly responsible for biological functions such as cell nitrogen complex metabolism, macromolecular metabolism, and cell communication, in addition to functions such as nucleic acid binding, enzyme binding, hydrolase reaction, and transferase activity. Combined with microarray data analysis, the following set of nine DEGs showed intersection between the ATAC and microarray data: JUN, MSL2, CDC42, TRIB1, SERTAD3, RAB14, RHOB, RAB40B, and PRKDC. HOMER predicted and identified five transcription factors that could potentially bind to these peak sites, namely NFY, Sp 2, GFY, NRF, and ELK 1. Conclusion: Chromatin accessibility analysis of the PBMCs from patients with early-stage breast cancer underscores its potential as a significant avenue for biomarker discovery in breast cancer diagnostics and treatment. By screening the transcription factors and DEGs related to breast cancer, this study provides a comprehensive theoretical foundation that is expected to guide future clinical applications and therapeutic developments.

Exploring Mitochondrial Autophagy Dysregulation in Osteosarcoma: Its Implications for Prognosis and Targeted Therapy

Objective: This study aimed to investigate the differential expression of mitophagyrelated genes in osteosarcoma patients with distinct prognostic outcomes and explore potential molecular regulatory mechanisms. Methods: We analyzed microarray data from metastatic and nonmetastatic osteosarcoma patients using the UCSC dataset. Differential gene screening and intersection of mitophagy-related genes were performed using NetworkAnalyst. Random forest and LASSO regression were employed to screen selected genes and establish a risk prediction model. Functional enrichment analysis, protein- protein interaction (PPI) networks, immunoassays, and in vitro experiments were conducted to validate the findings. Results: Seven differentially expressed genes were identified, and a robust risk prediction model was developed (AUC=0.886). PPI and functional enrichment analyses provided insights into relevant molecules and regulatory pathways. The immunoassay results revealed differences in the immune environment between the metastatic and nonmetastatic groups. Immunohistochemistry demonstrated significant downregulation of EPHA3 expression in the metastatic group, and in vitro experiments indicated that inhibiting EPHA3 increased the proliferative activity and migration ability of osteosarcoma cells. Conclusion: Our study suggests that the downregulation of EPHA3 may contribute to mitochondrial autophagy dysfunction, thereby increasing the risk of osteosarcoma metastasis.

Linking gut microbiota dysbiosis to molecular pathways in Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by cognitive decline and synaptic dysfunction. Emerging evidence suggests a significant relationship between gut microbiota and brain health, mediated through the gut-brain axis. Alterations in gut microbiota composition may influence AD progression by affecting molecular pathways and miRNA interactions. MethodsWe retrieved and analyzed microarray data from 34 tissue samples of AD patients and controls (GEO accession number GSE110298). Differentially expressed genes (DEGs) with the GCS score package in R, considering a p-value < 0.05 and logFC<-1 and logFC>1 to isolate significant gene clusters. Enrichment analysis of signaling pathways and gene ontology was conducted using Enrichr, KEGG, Panther, DAVID, and shiny GO databases. Protein-protein interactions were visualized with Networkanalyst and CytoScape. Gut microbiota in 200 CE patients was analyzed using next-generation sequencing (NGS) data from gutMDisorder and GMrepo databases. miRNA interactions were evaluated using miEAA, Targetscan, MienTurnet, and miRnet databases. ResultsSignificant reductions in microbial taxa, including Clostridia (LDA score −4.878208), Firmicutes (LDA score −4.817032), and Faecalibacterium (LDA score −4.40714), were observed in AD patients. Pathway analysis highlighted the involvement of Axon guidance, ErbB, and MAPK signaling pathways in AD. Venn diagram analysis identified 619 intersecting genes in brain and gut tissues, emphasizing pathways such as Axon Guidance and Cell Cycle. miRNA analysis revealed important regulatory miRNAs, including hsa-let-7c, hsa-mir-125b-2, and hsa-mir-145, which target key transcription factors involved in AD pathology. ConclusionThe study demonstrates significant dysbiosis in the gut microbiota of AD patients and underscores the potential role of gut microbiota in AD progression through altered signaling pathways and miRNA interactions. These findings highlight the need for further research into microbiota-based interventions as potential therapeutic strategies for AD.

Potential brain biomarkers in patients with Autism spectrum syndrome

Autism spectrum disorder (ASD) is referred as a cluster of neurodevelopmental disorders with relatively high incidence. ASD is believed to be a multifactorial condition, and genetics is one of the most important factors in its formation. Therefore, profiling gene expression in ASD patients can lead to the identification of new molecular insights. To evaluate gene expression patterns, we have utilized NCBI GEO microarray data. The dataset of ASD patients (GSE28475, GSE28521, GSE38322 and GSE113834) were defined as two meta-data, Total brain meta-data and Lobe specified meta-data. Meta-analysis and batch effect removal was conducted by the SVA package. Microarray data analysis was performed using the LIMMA package under R 4.2.1 software. Total Meta-Analysis (TMA) identified 525 significantly differentially expressed genes (DEGs) in ASD patient’s brain. The temporal and frontal lobes of ASD patients showed 96 and 23 DEGs respectively. Among the mentioned DEGs, there were 11 common DEGs between the temporal and frontal lobes that were also dysregulated in TMA except for UTP4 which was only dysregulated in the temporal and frontal lobes. However, the occipital and cerebellum lobes did not show any significant DEGs. Enrichment analysis pointed out the vital roles of identified DEGs in transmembrane transportation, ATP production, and cellular respiration. According to our findings, gene expression profile in the temporal and frontal lobes of ASD patients are significantly different than a control group. This aberrant gene expression potentially leads to crucial complications in nerve signal transmission and defects energy production in neurons. Therefore, potential therapeutic targets may be suggested based on these findings.

Initial Evaluation of lncRNA A2M-AS1 Gene Expression in Multiple Sclerosis Patients.

Multiple sclerosis (MS) is one of the three leading neurodegenerative diseases worldwide. Gene expression profile studies play an important role in recognizing and preventing disease. Considering the inherent ability of biomarkers to diagnose and prognose the occurrence of a disease, with the aim of gene therapy and changing gene expression, it can be helped to treat it. In this study, by examining the gene interaction and expression of non-coding genes in patients with MS, using bioinformatics analyses, laboratory research and potential non-coding diagnostic biomarkers of MS were selected for further investigations. First, by using micro-array data analysis of the GEO database, the expression status of the long non-coding ribonucleic acid (RNA) (lncRNA) A2M-AS1 gene was investigated in patients with MS. lncRNA-mRNA interaction analysis was performed in the lncRRisearch database. After sample collection, the total RNA extracted using the RNA extraction kit from 20 patient samples and 20 healthy samples was synthesized into cDNA with the synthesis kit. The quantitative reverse transcriptase polymerase chain reaction experiment was performed for the final validation of expression change. Based on bioinformatic and laboratory analysis, the expression of the A2M-AS1 gene in MS samples showed a significant decrease in expression compared to healthy samples. Also, based on the receiver operating characteristic analysis, lncRNA A2M-AS1 can be introduced as an acceptable diagnostic biomarker to distinguish MS samples from healthy samples. lncRNA A2M-AS1, by reducing its expression as an acceptable diagnostic biomarker, can increase the risk of developing MS.

Identification of the molecular link: STAT3 is a shared key gene linking postmenopausal osteoporosis and sarcopenia.

This study explored the shared genetic traits and molecular interactions between postmenopausal osteoporosis (POMP) and sarcopenia, both of which substantially degrade elderly health and quality of life. We hypothesized that these motor system diseases overlap in pathophysiology and regulatory mechanisms. We analyzed microarray data from the Gene Expression Omnibus (GEO) database using weighted gene co-expression network analysis (WGCNA), machine learning, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify common genetic factors between POMP and sarcopenia. Further validation was done via differential gene expression in a new cohort. Single-cell analysis identified high expression cell subsets, with mononuclear macrophages in osteoporosis and muscle stem cells in sarcopenia, among others. A competitive endogenous RNA network suggested regulatory elements for these genes. Signal transducer and activator of transcription 3 (STAT3) was notably expressed in both conditions. Single-cell analysis pinpointed specific cells with high STAT3 expression, and microRNA (miRNA)-125a-5p emerged as a potential regulator. Experiments confirmed the crucial role of STAT3 in osteoclast differentiation and muscle proliferation. STAT3 has emerged as a key gene in both POMP and sarcopenia. This insight positions STAT3 as a potential common therapeutic target, possibly improving management strategies for these age-related diseases.

Investigation roles of Adamts1 and Adamts5 in scleral fibroblasts under hypoxia and mice with form-deprived myopia

Scleral hypoxia is considered a trigger in scleral remodeling-induced myopia. Identifying differentially expressed molecules within the sclera is essential for understanding the mechanism of myopia. We developed a scleral fibroblast hypoxia model and conducted RNA sequencing and bioinformatic analysis. RNA interference technology was then applied to knock down targeted genes with upregulated expression, followed by an analysis of COLLAGEN I protein level. Microarray data analysis showed that the expression of Adamts1 and Adamts5 were upregulated in fibroblasts under hypoxia (t-test, p < 0.05). Western blot analysis confirmed increased protein levels of ADAMTS1 and ADAMTS5, and a concurrent decrease in COLLAGEN I in hypoxic fibroblasts. The knockdown of either Adamts1 or Adamts5 in scleral fibroblasts under hypoxia resulted in an upregulation of COLLAGEN I. Moreover, a form-deprivation myopia (FDM) mouse model was established for validation. The sclera tissue from FDM mice exhibited increased levels of ADAMTS1 and ADAMTS5 protein and a decrease in COLLAGEN I, compared to controls. The study suggests that Adamts1 and Adamts5 may be involved in scleral remodeling induced by hypoxia and the development of myopia.

A Droplet Digital Polymerase Chain Reaction-Based Tool to Aid in Melanoma Diagnosis.

Detecting copy number variations (CNVs) at certain loci can aid in the diagnosis of histologically ambiguous melanocytic neoplasms. Droplet digital polymerase chain reaction (ddPCR) is a rapid, automated, and inexpensive method for CNV detection in other cancers, but not yet melanoma. To evaluate the performance of a 4-gene ddPCR panel that simultaneously tests for ras responsive binding element protein 1 (RREB1) gain; cyclin-dependent kinase inhibitor 2A (CDKN2A) loss; MYC proto-oncogene, bHLH transcription factor (MYC) gain; and MYB proto-oncogene, transcription factor (MYB) loss in melanocytic neoplasms. One hundred sixty-four formalin-fixed, paraffin-embedded skin samples were used to develop the assay, of which 65 were used to evaluate its performance. Chromosomal microarray analysis (CMA) data were used as the gold standard. ddPCR demonstrated high concordance with CMA in detecting RREB1 gain (sensitivity, 86.7%; specificity, 88.9%), CDKN2A loss (sensitivity, 80%; specificity, 100%), MYC gain (sensitivity, 70%; specificity, 100%), and MYB loss (sensitivity, 71.4%; specificity, 100%). When one CNV was required to designate the test as positive, the 4-gene ddPCR panel distinguished nevi from melanomas with a sensitivity of 78.4% and a specificity of 71.4%. For reference, CMA had a sensitivity of 86.2% and a specificity of 78.6%. Our data also revealed interesting relationships with histology, namely (1) a positive correlation between RREB1 ddPCR copy number and degree of tumor progression; (2) a statistically significant correlation between MYC gain and nodular growth; and (3) a statistically significant correlation between MYB loss and a sheetlike pattern of growth. With further validation, ddPCR may aid both in our understanding of melanomagenesis and in the diagnosis of challenging melanocytic neoplasms.

Evaluation of the expression of LINCOO475 and FOXO1 genes as tumor suppressor genes in breast cancer: Correlation of bioinformatics tools and experimental approaches

Breast cancer is one of the most prevalent forms of malignancy in humans and is considered the most important life-threatening factor among women worldwide. Long non-coding RNAs (LncRNAs) are thought to be potential transcripts that regulate the expression of important genes in vital processes such as cell proliferation, apoptosis, survival, and oxidative stress. LINC00475 is an important lncRNA and is located on 9q22.31 and its expression is regulated by p53. FOXO1 gene is an important regulator in physiological processes such as cell maintenance and differentiation, stimulation of cell cycle arrest, and apoptosis. In this study, we focused on identifying a possible association between FOXO1 and LINC00475 expression levels in breast cancer. Bioinformatics expression and Microarray data analysis were utilized to find their potential role as novel biomarkers in breast cancer. The correlation of gene expression levels with the survival rate of patients was determined using GEPIA. LINC00475 and FOXO1 expression levels were validated using quantitative reverse transcription PCR (qRT-PCR) in 55 tumors and 40 normal tissues. Our experiments indicated a significant decrease in the expression level of LINC00475 and FOXO1 genes in tumor tissues compared to normal samples. Moreover, the specificity and sensitivity of all statistical criteria were significant between the two groups. Also, we revealed a positive relationship between LINC00475 and FOXO1 expression in tumor samples. Based on gene expression analysis and lncRNA data, it was shown that LINC00475 and FOXO1 could represent as potential diagnostic biomarkers for early diagnosis of breast cancer.

Effective Cancer Diagnosis through High-Dimensional Microarray Data Analysis by Integrating DCT and UFS

Cancer remains a global health challenge, with various types such as lung, breast, and colon cancer posing significant threats. Timely and accurate diagnosis is crucial for effective treatment and improved survival rates. Genetic research offers promising avenues in the fight against cancer, as identifying gene mutations and expression levels enables the development of targeted therapies and a deeper understanding of disease subtypes and progression. This study explores an innovative hybrid approach to enhance cancer diagnosis and classification. By combining Discrete Cosine Transformation (DCT) and Univariate Feature Selection (UFS) methods, the feature selection process is optimized for the dataset. The extracted features are then rigorously tested using established classifiers to assess their effectiveness in cancer classification. The proposed method's performance was evaluated using eight distinct datasets, and metrics such as MF1, K-score, and sensitivity were calculated and compared with various methods in the literature. Empirical evidence demonstrates that the proposed method outperforms others on 5 out of 8 datasets in terms of both accuracy and computational efficiency. The introduced method represents a reliable tool for cancer diagnosis and classification.

Insights into Co-Expression Network Analysis of MicroProteins and their Target Transcription Factors in Plant Embryo Development

Background: Gene expression is regulated in a spatiotemporal manner, and the roles of microProteins (MiPs) in this concept have started to become clear in plants. Methods: Here, a microarray data analysis was carried out to decipher the spatiotemporal role of MiPs in embryo development. The guilt-by-association method was used to determine the corresponding regulatory factors. Results: Module network analyses and protein-protein interaction (PPI) assays suggested 13 modules for embryo development in the Arabidopsis model plant. Various biological processes such as metabolite biosynthesis, hormone transition and regulation, fatty acid and storage protein biosynthesis, and photosynthesis-related processes were prevalent. Different transcription factors (TFs) at different stages of embryo development were found and reviewed. Furthermore, 106 putative MiPs were identified that might be involved in the regulation of embryo development. Candidate hub MiPs (15) at embryo developmental stages were identified by PPI network analysis and their putative regulatory roles were discussed. Previously reported MiPs, AT1G14760 (KNOX), AT5G39860 (PRE1), and AT2G46410 (CPC), were noted to be present in modules M3 and M8. Conclusion: Molecular comprehension of regulatory factors including MiPs and TFs during embryo development allows targeted breeding of the corresponding traits and genome-based engineering of value-added new varieties.