Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer DOI Creative Commons

Sisi Gong,

Rongfu Huang,

Meie Wang

et al.

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: Nov. 11, 2024

Triple-negative breast cancer (TNBC) is known for its aggressive nature, lack of effective diagnostic tools and treatments, generally poor prognosis. The objective this study was to investigate metabolic changes in TNBC using metabolomics approaches explore the underlying mechanisms through integrated analysis with transcriptomics. In study, serum untargeted profiles were first examined between 18 patients 21 healthy control (HC) subjects liquid chromatography-mass spectrometry (LC-MS), identifying a total 22 significantly differential metabolites (DMs). Subsequently, receiver operating characteristic revealed that 7-methylguanine could serve as potential biomarker both discovery validation sets. Additionally, transcriptomic datasets retrieved from GEO database identify differentially expressed genes (DEGs) normal tissues. An integrative DMs DEGs conducted, uncovering molecular TNBC. Notably, three pathways—tyrosine metabolism, phenylalanine glycolysis/gluconeogenesis—were enriched, providing insight into energy metabolism disorders Within these pathways, two (4-hydroxyphenylacetaldehyde oxaloacetic acid) six (MAOA, ADH1B, ADH1C, AOC3, TAT, PCK1) identified key components. summary, highlights biomarkers potentially be used diagnosis screening comprehensive transcriptomics data offers validated in-depth understanding metabolism.

Language: Английский

Fructose-1,6-bisphosphatase 1 in cancer: Dual roles, mechanistic insights, and therapeutic potential – A comprehensive review DOI

Qinghang Song,

Jiehe Sui,

Yuxuan Yang

et al.

International Journal of Biological Macromolecules, Journal Year: 2025, Volume and Issue: unknown, P. 139273 - 139273

Published: Jan. 1, 2025

Language: Английский

Citations

1
Exploring Aerobic Energy Metabolism in Breast Cancer: A Mutational Profile of Glycolysis and Oxidative Phosphorylation DOI Open Access
Ricardo Cunha de Oliveira, Giovanna C. Cavalcante, Giordano B. Soares‐Souza

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(23), P. 12585 - 12585

Published: Nov. 23, 2024

Energy metabolism is a fundamental aspect of the aggressiveness and invasiveness breast cancer (BC), neoplasm that most affects women worldwide. Nonetheless, impact genetic somatic mutations on glycolysis oxidative phosphorylation (OXPHOS) genes in BC remains unclear. To fill these gaps, mutational profiles 205 screened related to OXPHOS 968 individuals with from The Cancer Genome Atlas (TCGA) project were performed. We carried out analyses characterize profile BC, assess clonality tumors, identify mutation co-occurrence, predict pathogenicity alterations. In total, 408 132 pathways detected.

Language: Английский

Citations

2
PMAIP1-mediated glucose metabolism and its impact on the tumor microenvironment in breast cancer: Integration of multi-omics analysis and experimental validation DOI
Yidong Zhang, Hang Xu,

Xuedan Han

et al.

Translational Oncology, Journal Year: 2024, Volume and Issue: 52, P. 102267 - 102267

Published: Dec. 30, 2024

Language: Английский

Citations

2
Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer DOI Creative Commons

Sisi Gong,

Zhijun Liao, Meie Wang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: June 7, 2024

Abstract Triple-negative breast cancer (TNBC) is recognized for its aggressive nature, lack of effective diagnosis and treatment, generally poor prognosis. The objective this study was to investigate the metabolic changes in TNBC using metabolomics approaches explore underlying mechanisms through integrated analysis with transcriptomics. In study, serum untargeted profiles were firstly explored between 18 21 healthy controls (HC) by liquid chromatography-mass spectrometry (LC-MS), identifying a total 22 significantly altered metabolites (DMs). Subsequently, receiver operating characteristic revealed that 7-methylguanine could serve as potential biomarker both discovery validation sets. Additionally, transcriptomic datasets retrieved from GEO database identify differentially expressed genes (DEGs) normal tissues. An integrative DMs DEGs subsequently conducted, uncovering molecular TNBC. Notably, three pathways—tyrosine metabolism, phenylalanine glycolysis/gluconeogenesis—were enriched, explaining energy metabolism disorders Within these pathways, two (4-hydroxyphenylacetaldehyde oxaloacetic acid) six (MAOA, ADH1B, ADH1C, AOC3, TAT, PCK1) identified critical components. summary, highlights biomarkers potentially be utilized screening comprehensive transcriptomics data provides validated in-depth understanding metabolism.

Language: Английский

Citations

1
PMAIP1-Mediated Glucose Metabolism and its Impact on the Tumor Microenvironment in Breast Cancer: Integration of Multi-Omics Analysis and Experimental Validation DOI Open Access
Yidong Zhang,

Xuedan Han,

Qiyi Yu

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Abstract Background Glucose metabolism in breast cancer has a potential effect on tumor progression and is related to the immune microenvironment. Thus, this study aimed develop glucose metabolism– microenvironment score provide new perspectives treatment. Method Data were acquired from Gene Expression Omnibus UCSC Xena databases, glucose-metabolism-related genes Set Enrichment Analysis database. Genes with significant prognostic value identified, infiltration analysis was conducted, model constructed based results of these analyses. The validated by vitro experiments MCF-7 MCF-10A cell lines, including expression validation, functional experiments, bulk sequencing. Single-cell also conducted explore role specific clusters cancer, Bayes deconvolution used further investigate associations between phenotypes cancer. Results Four (PMAIP1, PGK1, SIRT7, SORBS1) and, through analysis, combined established. classify clinical subtypes PMAIP1 identified as critical gene jointly confirmed protective PMAIP1+ luminal cluster.

Language: Английский

Citations

0
Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer DOI Creative Commons

Sisi Gong,

Rongfu Huang,

Meie Wang

et al.

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: Nov. 11, 2024

Triple-negative breast cancer (TNBC) is known for its aggressive nature, lack of effective diagnostic tools and treatments, generally poor prognosis. The objective this study was to investigate metabolic changes in TNBC using metabolomics approaches explore the underlying mechanisms through integrated analysis with transcriptomics. In study, serum untargeted profiles were first examined between 18 patients 21 healthy control (HC) subjects liquid chromatography-mass spectrometry (LC-MS), identifying a total 22 significantly differential metabolites (DMs). Subsequently, receiver operating characteristic revealed that 7-methylguanine could serve as potential biomarker both discovery validation sets. Additionally, transcriptomic datasets retrieved from GEO database identify differentially expressed genes (DEGs) normal tissues. An integrative DMs DEGs conducted, uncovering molecular TNBC. Notably, three pathways—tyrosine metabolism, phenylalanine glycolysis/gluconeogenesis—were enriched, providing insight into energy metabolism disorders Within these pathways, two (4-hydroxyphenylacetaldehyde oxaloacetic acid) six (MAOA, ADH1B, ADH1C, AOC3, TAT, PCK1) identified key components. summary, highlights biomarkers potentially be used diagnosis screening comprehensive transcriptomics data offers validated in-depth understanding metabolism.

Language: Английский

Citations

0