AIMC Topic: Gene Expression Profiling

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Identification and analysis of metabolic reprogramming-related genes in triple-negative breast cancer.

Clinical and experimental medicine
Triple-negative breast cancer (TNBC) is notorious for its rapid progression, tendency to metastasize, high recurrence rates, dismal outcomes, and limited treatment options, underscoring the urgent need to uncover new biomarkers and molecular pathways...

Ligand-receptor interaction profiling as a predictive biomarker for anti-PD-1 therapy response in melanoma.

Clinical and experimental medicine
Cell-to-cell communication through ligand-receptor (LR) interactions can fundamentally shape the tumor microenvironment and immune responses, but the full spectrum of these interactions in anti-PD-1 therapy remains unexplored. We developed a predicti...

Machine learning identifies exosome related gene signatures for early prediction of non-small cell lung cancer.

Scientific reports
Non-small cell lung cancer (NSCLC) remains a major health challenge worldwide, mainly due to the lack of effective early diagnostic biomarkers. Exosome-related genes have recently emerged as potential diagnostic markers due to their roles in tumor pr...

The impact of PANoptosis-related genes on immune profiles and subtype classification in ischemic stroke.

Scientific reports
Ischemic stroke (IS) is an acute neurological disorder causing brain dysfunction, with high mortality and disability. PANoptosis is a synchronized sort of regulated cell demise that combines the characteristics of pyroptosis, apoptosis, and necroptos...

Programmed cell death-related genes define distinct molecular subtypes and risk profiles in hepatocellular carcinoma.

Scientific reports
Hepatocellular carcinoma (HCC) is a biologically and clinically heterogeneous malignancy, whose initiation and progression are increasingly recognized to be driven by the aberrant regulation of programmed cell death (PCD) pathways. To elucidate this ...

Alterations of multilayer network correlated with cognitive impairment and gene expression profiles in children with idiopathic generalized epilepsy.

Scientific reports
This study investigated dynamic brain network changes and their genetic correlations in children with idiopathic generalized epilepsy (IGE). We included 26 children with IGE and 35 healthy controls, all participants underwent resting-state functional...

Machine learning and multi-omics integration reveal TRPV2 as a central regulator in bicuspid aortic valve calcification.

Biochemical and biophysical research communications
BACKGROUND: Bicuspid aortic valve (BAV), the most common congenital heart defect, is strongly predisposed to early calcification, yet the molecular drivers remain poorly defined. This study aims to identify the functional role of transient receptor p...

Integrative transcriptomic analysis identifies shared EndMT-related gene signatures in endometriosis and recurrent miscarriage.

Scientific reports
Endometriosis (EMs) and recurrent miscarriage (RM) represent major reproductive health challenges. This study investigates the involvement of endothelial-mesenchymal transition (EndMT) in these conditions through integrative bioinformatics analysis, ...

TRIumph in nanotoxicology: simplifying transcriptomics into a single predictive variable.

Nanoscale horizons
The primary aim of our study was to address the problem of transcriptomic data complexity by introducing a novel transcriptomic response index (TRI), compressing the entire transcriptomic space into a single variable, and linking it with the inhaled ...

Investigation into the molecular mechanism of obesity: an integrated approach of multi-omics analysis, machine learning and experimental validation.

Journal of translational medicine
BACKGROUND: Obesity has emerged as a major global public health challenge and poses a significant threat to human health. Despite extensive research, the mechanisms underlying its pathological progression remain elusive.