Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

Computational and Structural Biotechnology Journal, Journal Year: 2024, Volume and Issue: 23, P. 1154 - 1168

Published: March 1, 2024

In recent years, the role of bioinformatics and computational biology together with omics techniques transcriptomics has gained tremendous importance in biomedicine healthcare, particularly for identification biomarkers precision medicine drug discovery. Differential gene expression (DGE) analysis is one most used RNA-sequencing (RNA-seq) data analysis. This tool, which typically various RNA-seq processing applications, allows differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate contextualize resulting lists. These studies provide valuable information about disease-causing biological processes help identifying molecular targets novel therapies. review focuses on differential pipelines commonly identify specific discuss advantages disadvantages these techniques.

Language: Английский

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Early-stage idiopathic Parkinson’s disease is associated with reduced circular RNA expression

npj Parkinson s Disease, Journal Year: 2024, Volume and Issue: 10(1)

Published: Jan. 20, 2024

Language: Английский

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USP3 promotes gastric cancer progression and metastasis by deubiquitination-dependent COL9A3/COL6A5 stabilisation

Cell Death and Disease, Journal Year: 2021, Volume and Issue: 13(1)

Published: Dec. 20, 2021

As an important regulator of intracellular protein degradation, the mechanism deubiquitinating enzyme family in tumour metastasis has received increasing attention. Our previous study revealed that USP3 promotes progression and is highly expressed gastric cancer (GC). Herein, we report two critical targets, COL9A3 COL6A5, downstream USP3, via isobaric tags for relative absolute quantification technique. Mechanistically, observed interacted with stabilised COL6A5 deubiquitination GC. Importantly, found were essential mediators USP3-modulated oncogenic activity vitro vivo. Examination clinical samples confirmed elevated expression concomitant increased abundance, correlates human GC progression. These data suggest by COL6A5. findings identify a regarding USP3-mediated potential therapeutic targets management.

Language: Английский

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Analysis of environmental pollutant Bisphenol F elicited prostate injury targets and underlying mechanisms through network toxicology, molecular docking, and multi-level bioinformatics data integration

Toxicology, Journal Year: 2024, Volume and Issue: 506, P. 153847 - 153847

Published: June 2, 2024

Language: Английский

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Lift the Veil of Breast Cancers Using 4 or Fewer Critical Genes

Cancer Informatics, Journal Year: 2022, Volume and Issue: 21

Published: Jan. 1, 2022

Known genes in the breast cancer study literature could not be confirmed whether they are vital to formations due lack of convincing accuracy, although may biologically directly related based on present biological knowledge. It is hoped can identified with highest possible for example, 100% accuracy and causal patterns beyond what has been known cancer. One hope that finding gene-gene interaction signatures functional effects solve puzzle. This research uses a recently developed competing linear factor analysis method differentially expressed gene detection advance formation. Surprisingly, 3 detected TNBC non-TNBC (Her2, Luminal A, B) samples sensitivity specificity 1 triple-negative cancers (TNBC, 54 675 265 samples). These show clear signature pattern how patients grouped. For another (with 673 66 samples), 4 bring same specificity. Four found have 121 an 96.5% fourth 60 483 1217 results 4-gene-based classifiers robust accurate. The naturally classify into subtypes, 7 subtypes. findings demonstrate clearest smallest numbers compared reported literature. considered essential studies practice. They provide focused, targeted researches precision medicine each subtype New disease types using classified hence new effective therapies developed.

Language: Английский

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Comprehensive analysis of autophagy‐related prognostic genes in breast cancer

Journal of Cellular and Molecular Medicine, Journal Year: 2020, Volume and Issue: 24(16), P. 9145 - 9153

Published: July 2, 2020

Abstract Accumulating evidence revealed that autophagy played vital roles in breast cancer (BC) progression. Thus, the aim of this study was to investigate prognostic value autophagy‐related genes (ARGs) and develop a ARG‐based model evaluate 5‐year overall survival (OS) BC patients. We acquired ARG expression profiling large cohort (N = 1007) from The Cancer Genome Atlas (TCGA) database. correlation between ARGs OS confirmed by LASSO Cox regression analyses. A predictive established based on independent variables. time‐dependent receiver operating curve (ROC), calibration plot, decision subgroup analysis were conducted determine performance model. Four (ATG4A, IFNG, NRG1 SERPINA1) identified using multivariate constructed four two clinicopathological risk factors (age TNM stage), dividing patients into high‐risk low‐risk groups. group higher than ( P < 0.0001). Time‐dependent ROC at 5 years indicated ARG–based tool had better accuracy stage training (AUC: 0.731 vs 0.640, 0.01) validation 0.804 0.671, 0.01). mutation frequencies 0.9%, 2.8%, 8% 1.3%, respectively. built verified novel nomogram, credible approach predict BC, which can assist oncologists determining effective therapeutic strategies.

Language: Английский

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Coexpression Network Analysis of Genes Related to the Characteristics of Tumor Stemness in Triple-Negative Breast Cancer

BioMed Research International, Journal Year: 2020, Volume and Issue: 2020, P. 1 - 14

Published: July 13, 2020

Cancer stem cells (CSCs) are subsets of with the ability self-renewal and differentiation in neoplasm, which considered to be related tumor heterogeneity. It has been reported that CSCs act on tumorigenesis biology triple-negative breast cancer (TNBC). However, key genes cause TNBC showing cell characteristics still unclear. We combined RNA sequencing (RNA-seq) data from The Genome Atlas (TCGA) database mRNA expression-based stemness index (mRNAsi) further analyze mRNAsi regard molecular subtypes, depth, pathological staging (BC). Secondly, we extract differential gene expression vs. normal group other subtypes BC group, respectively, intersect them achieve precise results. used a weighted coexpression network analysis (WGCNA) screen significant modules functions selected including BIRC5, CDC25A, KIF18B, KIF2C, ORC1, RAD54L, TPX2 were carried out through ontology (GO) functional annotation. Oncomine, bc-GenExMiner v4.4, GeneMANIA, Kaplan-Meier Plotter (KM-plotter), GEPIA verify level genes. In this study, found had highest compared subtypes. lower score, better overall survival treatment outcome. Seven screened annotation indicated there strong correlations between them, relating nuclear division, organelle fission, mitotic events determine fate. Among these genes, four highly associated adverse events. identified study closely maintenance stemness, overexpression showed earlier recurrence. (OS) curves all crossed at around nine-year follow-up, was consistent trend OS curve mRNAsi. These findings may provide new ideas for screening therapeutic targets order depress stemness.

Language: Английский

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IQGAP3 Overexpression Correlates With Poor Prognosis and Radiation Therapy Resistance in Breast Cancer

Frontiers in Pharmacology, Journal Year: 2021, Volume and Issue: 11

Published: Jan. 14, 2021

Background: IQ motif-containing GTPase activating protein 3 (IQGAP3), the latest identified member of IQGAP family, may act as a crucial factor in cancer development and progression; however, its clinical value breast remains unestablished. We explored correlation between IQGAP3 expression profile clinicopathological features cancer. Methods: mRNA levels were detected cell lines tumor tissues by real-time PCR western blotting compared to normal control groups. Protein was also evaluated immunohistochemically archived paraffin-embedded specimens from 257 patients, associations level, characteristics, prognosis analyzed. assessed relationship sensitivity radiation therapy which determined subgroup analysis. Results: significantly upregulated human at both level controls. Additionally, high 110/257 (42.8%) specimens. High related stage ( p = 0.001), T category 0.002), N locoregional recurrence distant metastasis vital status 0.001). Univariate multivariate statistical analysis showed that an independent prognostic among all patients our cohort 0.003, Subgroup revealed correlated with radioresistance predictor radiotherapy outcome. Conclusion: Our findings suggest predicts poor Therefore, be reliable biomarker could used identify who benefit radiotherapy.

Language: Английский

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Integrating Somatic Mutations for Breast Cancer Survival Prediction Using Machine Learning Methods

Frontiers in Genetics, Journal Year: 2021, Volume and Issue: 11

Published: Jan. 18, 2021

Breast cancer is the most common malignancy in women, and because it has a high mortality rate, urgent to develop computational methods increase accuracy of breast survival predictive models. Although multi-omics data such as gene expression have been extensively used recent studies, accurate prognosis remains challenge. Somatic mutations are another important promising source for studying development, its effect on be further explored. Meanwhile, these omics datasets high-dimensional redundant. Therefore, we adopted multiple kernel learning (MKL) efficiently integrate somatic mutation currently molecular including expression, copy number variation (CNV), methylation, protein prediction survival. Before integration, maximum relevance minimum redundancy (mRMR) feature selection method was utilized select features that present low among themselves each type data. The experimental results demonstrated proposed achieved optimal performance there remarkable improvement when were included, indicating critical improving predictions. Moreover, mRMR superior other previous studies. Furthermore, MKL outperformed traditional classifiers integration. Our analysis indicated through employing harnessing power proper effective integration frameworks, can increased, thereby providing more clinical diagnosis treatment patients.

Language: Английский

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GATA3 somatic mutations are associated with clinicopathological features and expression profile in TCGA breast cancer patients

Scientific Reports, Journal Year: 2021, Volume and Issue: 11(1)

Published: Jan. 18, 2021

Abstract The effect of somatic mutations and the gene expression profiles on prognosis is well documented in cancer research. This study was conducted to evaluate association GATA3 with tumor features, survival, breast cancer. Clinicopathological information compared between TCGA-BRCA patients -mutant non-mutant tumors all as ER-positive subgroup. Cox-regression method used mutation status overall survival time. Differential expression, functional annotation, protein–protein interaction analyses were performed using edgeR, Metascape, DAVID, STRING CytoNCA. samples had significantly different clinicopathological features ( p < 0.05). While not associated entire cohort adj = 0.52), GATA3- wild type cases a better than mutant ones 0.04). higher normal tissues. Several pathways groups Interleukin-6 found highest scored both comparisons (normal vs. groups) patient subgroup, suggesting IL6 tumorigenesis. These findings suggest that can be several characteristics influence pattern expression. However, seems prognostic factor for disease only patients.

Language: Английский

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