Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Comprehensive Analysis of Metabolic Genes in Breast Cancer Based on Multi-Omics Data.

Pathology oncology research : POR - 1 Jan 2021

Hua Yu, Gao Lihong, Li Xiaobo

Abstract excerpt

Background: Reprogramming of cell metabolism is one of the most important hallmarks of breast cancer. This study aimed to comprehensively analyze metabolic genes in the initiation, progression, and prognosis of breast cancer. Materials and Methods: Data from The Cancer Genome Atlas (TCGA) in breast cancer were downloaded including RNA-seq, copy number variation, mutation, and DNA methylation. A gene co-expression...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biomarkers, Tumor
Share to Breast Neoplasms
Share to Gene Expression Profiling

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene Expression Regulation, Neoplastic

Share to Gene Regulatory Networks

Share to Genome, Human

Share to Mutation

Share to Prognosis

Source

Open in PubMed Open full text

Identifiers

PMID: 34408553
DOI: 10.3389/pore.2021.1609789
PMCID: PMC8366497

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Comprehensive Analysis of Metabolic Genes in Breast Cancer Based on Multi-Omics Data.PMID 34408553Read ↗

Single-cell sequencing and transcriptome analysis identified a comprehensive risk score model based on immune-related metabolic genes for improving the prediction of sensitivity in breast cancer immunotherapySemantic proximity Read ↗

Exploring the role of metabolic pathways in TNBC immunotherapy: insights from single-cell and spatial transcriptomicsSemantic proximity Read ↗

Integrative Transcriptomic Analysis Identifies ADIPOQ, LIPE, LEP, SLC2A4, and LPL as Prognostic Metabolic Markers in Breast CancerSemantic proximity Read ↗

Bulk and single-cell transcriptome profiling reveal the metabolic heterogeneity in human breast cancersSemantic proximity Read ↗

A Single-Cell Network Approach to Decode Metabolic Regulation in Gynecologic and Breast CancersSemantic proximity Read ↗

Identification of a Novel Lipid Metabolic-Related Gene Signature with the Tumor Immune Microenvironment for Breast CancerSemantic proximity Read ↗

Identifying personalized metabolic signatures in breast cancerSemantic proximity Read ↗

Identification of a novel lipid metabolism-related gene signature within the tumour immune microenvironment for breast cancerSemantic proximity Read ↗

Metabolism and Tumor Microenvironment-Associated Molecular Classification of NeuroblastomaSemantic proximity Read ↗

Characterization of metabolic phenotypes in breast cancer through the integration of genome-scale metabolic models and machine learningSemantic proximity Read ↗

Identification and validation of a metabolic-related gene risk model predicting the prognosis of Lung, Colon, and Breast cancersSemantic proximity Read ↗

Correlation between metabolic characteristics and breast cancer subtypes and prognosisSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.