Microarray gene expression meta-analysis

Gene expression profiling is a powerful tool that has been extensively used to investigate the underlying biology and etiology of diseases, including cancer. Microarray gene expression analysis enables simultaneous measurement of thousands of mRNA levels. Sophisticated computational approaches have evolved in parallel with the rapid progress in bioassay technologies, enabling more effective analysis of the large and complex datasets that these technologies produce. In this study, we utilized systems biology approaches to examine gene expression profiles across different grades of breast cancer progression...

One of the greatest challenges of humanity for deep space exploration is to fully understand how altered gravitational conditions affect human physiology. It is evident that the spaceflight environment causes multiple alterations to musculoskeletal, cardiovascular, immune and central nervous systems, to name a few known effects. To better characterize these biological effects, we compare gene expression datasets from microarray studies found in NASA GeneLab, part of the NASA Open Science Data Repository. In this review, we summarize these archived results for various tissues, emphasizing key genes which are highly reproducible in different mice or human experiments...

Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. We developed NetActivity, a machine learning framework that generates GSAS based on a sparsely-connected autoencoder, where each neuron in the inner layer represents a gene set. We proposed a three-tier training that yielded representative, robust, and interpretable GSAS. NetActivity model was trained with 1518 GO biological processes terms and KEGG pathways and all GTEx samples...

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its progressive form, metabolic dysfunction-associated steatohepatitis (MASH), pose significant risks of severe fibrosis, cirrhosis, and hepatocellular carcinoma. Despite their widespread prevalence, the molecular mechanisms underlying the development and progression of these common chronic hepatic conditions are not fully understood. Here, we conducted the most extensive meta-analysis of hepatic gene expression datasets from liver biopsy samples to date, integrating 10 RNA-sequencing and microarray datasets (1,058 samples)...

Abiotic stresses limit the quantity and quality of rice grain production, which is considered a strategic crop in many countries. In this study, a meta-analysis of different microarray data at seedling stage was performed to investigate the effects of multiple abiotic stresses (drought, salinity, cold situation, high temperature, alkali condition, iron, aluminum, and heavy metal toxicity, nitrogen, phosphorus, and potassium deficiency) on rice. Comparative analysis between multiple abiotic stress groups and their control groups indicated 561 differentially expressed genes (DEGs), among which 422 and 139 genes were up-regulated and down-regulated, respectively...

High-throughput sequencing has created an exponential increase in the amount of gene expression data, much of which is freely, publicly available in repositories such as NCBI's Gene Expression Omnibus (GEO). Querying this data for patterns such as similarity and distance, however, becomes increasingly challenging as the total amount of data increases. Furthermore, vectorization of the data is commonly required in Artificial Intelligence and Machine Learning (AI/ML) approaches. We present BioVDB, a vector database for storage and analysis of gene expression data, which enhances the potential for integrating biological studies with AI/ML tools...

Papillary thyroid cancer (PTC) is a prevalent kind of thyroid cancer (TC), with the risk of metastasis increasing faster than any other malignancy. So, understanding the role of PTC in pathogenesis requires studying the various gene expressions to find out which particular molecular biomarkers will be helpful. The authors conducted a comprehensive search on the PubMed microarray database and a meta-analysis approach on the remaining ones to determine the differentially expressed genes between PTC and normal tissues, along with the analyses of overall survival (OS) and recurrence-free survival (RFS) rates in patients with PTC...

BACKGROUND: Lung cancer is a major cause of cancer-related mortality worldwide, with a 5-year survival rate of approximately 22%. Cisplatin is one of the standard first-line chemotherapeutic agents for non-small cell lung cancer (NSCLC), but its efficacy is often limited by the development of resistance. Despite extensive research on the molecular mechanisms of chemoresistance, the underlying causes remain elusive and complex. AIMS: We analyzed three microarray datasets to find the gene signature and key pathways related to cisplatin resistance in NSCLC...

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) has a five-year survival rate of less than 5%. Absence of symptoms at primary tumor stages, as well as high aggressiveness of the tumor can lead to high mortality in cancer patients. Most patients are recognized at the advanced or metastatic stage without surgical symptom, because of the lack of reliable early diagnostic biomarkers. The objective of this work was to identify potential cancer biomarkers by integrating transcriptome data...

The intestine is a barrier organ that plays an important role in the immune system of Atlantic salmon. The immune functions are distributed among the diffuse gut lymphoid tissue containing diverse immune cells, and other cell types. Comparison of intestinal transcriptomes with those of other organs and tissues offers an opportunity to elucidate the specific roles of the intestine and its relationship with other parts of the body. In this work, a meta-analysis was performed on a large volume of data obtained using a genome-wide DNA oligonucleotide microarray...

BACKGROUND: Carcinoma of the breast, a prevailing factor in female mortality worldwide, involves dysregulation of lncRNAs and microRNAs. AIM: The main goal of this research was to predict and experimentally examine the LINC01405 expression status in breast cancer subtypes, along with investigation of its interaction with miR-29b and miR-497-5p that results in regulating PI3-Kinase, WNT, and TGF-beta signaling pathways. METHODS AND RESULTS: We performed a meta-analysis of five GEO datasets, encompassing microarray and RNA-seq data, to identify differentially expressed genes...

Wound healing is a complex process involving the coordinated interaction of various genes and molecular<br />pathways. The study aimed to uncover novel therapeutic targets, biomarkers and candidate genes for drug development<br />to improve successful wound repair interventions.<br />Materials and Methods: This study is a network-meta analysis study. Nine wound healing microarray datasets obtained<br />from the Gene Expression Omnibus (GEO) database were used for this study. Differentially expressed genes (DEGs)<br />were described using the Limma package and shared genes were used as input for weighted gene co-expression<br />network analysis...

Almost all non-small cell lung cancer (NSCLC) patients initially responding to EGFR tyrosine kinase inhibitors (TKIs) develop acquired resistance. Since KCa 3.1 channels, expressed in mitochondria and plasma membrane, regulate similar behavioral traits of NSCLC cells as EGFR, we hypothesized that their blockade contributes to overcoming EGFR-TKI resistance. Meta-analysis of microarray data revealed that KCa 3.1 channel expression in erlotinib-resistant NSCLC cells correlates with that of genes of integrin and apoptosis pathways...

Abiotic stresses are major limiting factors for maize growth. Therefore, exploration of the mechanisms underlying the response to abiotic stress in maize is of great interest. Toward this end, we performed integration of the feature selection method into the meta-analysis of microarray gene expression. Following extraction of raw data, normalization, and batch effect removal, the data were merged into one expression profile. Differentially expressed genes (DEGs) between control and abiotic conditions were used for the feature selection algorithm to find the minimum features for high-performance classification...

Duchenne muscular dystrophy (DMD) is a genetic disorder that causes muscle weakness and degeneration. In this study, we identified potential biomarkers and drug targets for DMD through a comprehensive meta-analysis of mRNA profiles. We conducted an in-depth analysis of three microarray datasets from the GEO database, utilizing the Affymetrix platform. A rigorous data pre-processing pipeline encompassed background correction, normalization, log2 transformation and probe-to-gene symbol mapping. Robust multi-array average method followed by Limma package in R was employed to ensure differential expression analysis within individual datasets, yielding gene-specific p-values...

Abstract . Maize may be exposed to several abiotic stresses in the field. Therefore, identifying the tolerance mechanisms of natural field stress is mandatory. Gene expression data of maize upon abiotic stress were collected, and 560 differentially expressed genes (DEGs) were identified through meta-analysis. The most significant gene ontology terms in up-regulated genes were 'response to abiotic stress' and 'chitinase activity'. 'Phosphorelay signal transduction system' was the most significant enriched biological process in down-regulated DEGs...

OBJECTIVES: Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart defect in the United States. We aimed to identify genetic variations associated with TOF using meta-analysis of publicly available digital samples to spotlight targets for prevention, screening, and treatment strategies. METHODS: We used the Search Tag Analyze Resource for Gene Expression Omnibus (STARGEO) platform to identify 39 TOF and 19 non-TOF right ventricle tissue samples from microarray data and identified upregulated and downregulated genes...

BACKGROUND: Breast cancer is a multifaceted disease characterized by genetic and epigenetic changes that lead to uncontrolled cell growth and metastasis. Early detection and treatment are crucial for managing diseases. OBJECTIVES: The objective of this study is to investigate the potential of chimeric peptides for drug delivery and to identify biomarkers associated with breast cancer. Recent studies have shown that the low-density lipoprotein receptor-related protein 1 (LRP-1) receptor has a significant impact on the development of breast cancer...

BACKGROUND: Dengue is a major arthropod-borne viral disease spreading rapidly across the globe. The absence of vaccines and inadequate vector control measures leads to further expansion of dengue in many regions globally. Hence, the identification of genes involved in the pathogenesis of dengue will help to understand the molecular basis of the disease and the genes responsible for the disease progression. METHODS: In the present study, a meta-analysis was carried out using dengue gene expression data obtained from Gene Expression Omnibus repository...

Cardiometabolic disorders (CMD) are a growing public health problem across the world. Among the known cardiometabolic risk factors are compounds that induce endocrine and metabolic dysfunctions, such as endocrine disrupting chemicals (EDCs). To date, how EDCs influence molecular programs and cardiometabolic risks has yet to be fully elucidated, especially considering the complexity contributed by species-, chemical-, and dose-specific effects. Moreover, different experimental and analytical methodologies employed by different studies pose challenges when comparing findings across studies...