An integrative analysis of consortium-based multi-omics QTL and genome-wide association study data uncovers new biomarkers for lung cancer DOI Open Access
Yanru Wang, Angela Yee‐Moon Wang, Ning Xie

et al.

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

Published: Dec. 16, 2024

Abstract The role of molecular traits (e.g., gene expression and protein abundance) in the occurrence, development, prognosis lung cancer has been extensively studied. However, biomarkers other layers connections among various that influence risk remain largely underexplored. We conducted first comprehensive assessment associations between (i.e., DNA methylation, expression, metabolite) through epigenome-wide association study (EWAS), transcriptome-wide (TWAS), proteome-wide (PWAS) metabolome-wide (MWAS), then we synthesized all omics to reveal potential regulatory mechanisms across layers. Our analysis identified 61 CpG sites, 62 genes, 6 proteins, 5 metabolites, yielding 123 novel biomarkers. These highlighted 90 relevant genes for cancer, 83 them were established our study. Multi-omics integrative revealed 12 these overlapped layers, suggesting cross-omics interactions. Moreover, 106 cross-layer pathways, indicating cell proliferation, differentiation, immunity, protein-catalyzed metabolite reaction interact risk. Further subgroup analyses biomarker distributions differ patient subgroups. To share signals different with community, released a free online platform, LungCancer-xWAS, which can be accessed at http://bigdata.njmu.edu.cn/LungCancer-xWAS/ . findings underscore importance xWAS integrating types quantitative trait loci (xQTL) data genome-wide (GWAS) deepen understanding pathophysiology, may provide valuable insights into therapeutic targets disease.

Language: Английский

circ0066187 promotes pulmonary fibrogenesis through targeting STAT3-mediated metabolism signal pathway DOI Creative Commons
Bo Liu, Weili Liu, Hongbo Li

et al.

Cellular and Molecular Life Sciences, Journal Year: 2025, Volume and Issue: 82(1)

Published: Feb. 19, 2025

Language: Английский

Citations

1
Cancer and the Microbiome of the Human Body DOI Open Access
Lourdes Herrera‐Quintana, Héctor Vázquez‐Lorente, María López-Garzón

et al.

Nutrients, Journal Year: 2024, Volume and Issue: 16(16), P. 2790 - 2790

Published: Aug. 21, 2024

Cancer remains a public health concern worldwide, with its incidence increasing worldwide and expected to continue growing during the next decades. The microbiome has emerged as central factor in human disease, demonstrating an intricate relationship between cancer. Although some microbiomes present within local tissues have been shown restrict cancer development, mainly by interacting cells or host immune system, microorganisms are harmful risk factors for development. This review summarizes recent evidence concerning of most common types (i.e., lung, head neck, breast, gastric, colorectal, prostate, cervix cancers), providing general overview future clinical approaches perspectives.

Language: Английский

Citations

4
Metabolomics for early-stage lung adenocarcinoma: diagnostic biomarker screening DOI Creative Commons
Danxiong Sun,

Yanhong Du,

Rufang Li

et al.

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: March 11, 2025

Objective This study aimed to identify specific metabolic markers in the blood that can diagnose early-stage lung adenocarcinoma. Methods An untargeted metabolomics was performed, and participants were divided into four groups: adenocarcinoma group (E-LUAD; n = 21), healthy control (HC, 17), non-cancerous disease (NCC; advanced (A-LUAD; 25). Plasma metabolite levels differed E-LUAD compared other three groups identified via liquid chromatography–mass spectrometry (LC–MS). Principal component analysis (PCA) partial least squares discriminant (PLS-DA) performed at metaX for statistical analysis. A Venn diagram constructed overlapping differential metabolites of class comparisons. The data randomly a training set validation set. Based on metabolites, diagnostic model constructed. discrimination evaluated using area under curve (AUC). Results total 527 tentatively positive ion mode 286 negative mode. Compared with HC group, 121 identified. NCC 67 A-LUAD 54 showed 29 distinguish from HC, NCC, A-LUAD. feature selected establish E-LUAD. AUC value 0.918, it 0.983 Conclusion Blood has potential More medical studies are needed verify whether current research be applied clinical practice.

Language: Английский

Citations

0
Development of a miRNA-Based Model for Lung Cancer Detection DOI Open Access

Kai Chin Poh,

Tao Ren, Liuh Ling Goh

et al.

Cancers, Journal Year: 2025, Volume and Issue: 17(6), P. 942 - 942

Published: March 10, 2025

Background: Lung cancer is the leading cause of cancer-related mortality globally, with late-stage diagnoses contributing to poor survival rates. While lung screening low-dose computed tomography (LDCT) has proven effective in reducing among heavy smokers, its limitations, including high false-positive rates and resource intensiveness, restrict widespread use. Liquid biopsy, particularly using microRNA (miRNA) biomarkers, offers a promising adjunct current strategies. This study aimed evaluate predictive power panel serum miRNA biomarkers for detection. Patients Methods: A case-control was conducted at two tertiary hospitals, enrolling 82 cases 123 controls. We performed an extensive literature review shortlist 25 candidate miRNAs, which 16 showed significant two-fold increase expression compared Machine learning techniques, Random Forest, K-Nearest Neighbors, Neural Networks, Support Vector Machines, were employed identify top six miRNAs. then evaluated models, incorporating these nodule characteristics on LDCT. Results: prediction model utilising (mir-196a, mir-1268, mir-130b, mir-1290, mir-106b mir-1246) alone achieved area under curve (AUC) values ranging from 0.78 0.86, sensitivities 70–78% specificities 73–85%. Incorporating size significantly improved performance, yielding AUC between 0.96 0.99, 92–98% 93–98%. Conclusions: combining cancer. Integration into protocols may improve patient outcomes.

Language: Английский

Citations

0
The rising influence of lipid metabolism in lung cancer: a global research perspective DOI Creative Commons
Chaoqun Wang, Ming Lei, Wei Wang

et al.

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: March 31, 2025

Lung cancer is a prevalent malignant neoplasm globally and the leading cause of cancer-related mortality, posing significant threat to human health imposing considerable societal burden. Researchers have recently focused more on lipid metabolism in lung cancer. However, date, there has been no bibliometric analysis relation metabolism. This study used methods analyze link between Publications from 1995 2024 were sourced Web Science Core Collection (WoSCC). The Microsoft Excel, R-bibliometrix, CiteSpace, VOSviewer software visualize data. In this study, total 535 publications identified, with marked increase number observed post-2016. Both China United States exerted substantial influence domain. Notably, Chinese Academy Sciences Huazhong University Technology demonstrated leadership various aspects research related Professor Ana Ramirez de Molina Frontiers Oncology most productive authors journals respectively. Besides, keywords like "lipid metabolism", "lung cancer", "expression", "metabolism" "growth" central current are expected continue driving future trends studies. Research relationship was still its early stages. Targeting represented promising therapeutic strategy, as inhibiting key enzymes involved biosynthesis uptake potential impede progression mitigate drug resistance. first thoroughly summarize developments area over past thirty years, providing scholars updated insights identifying directions.

Language: Английский

Citations

0
Lipidomic signatures as predictive biomarkers for early-onset lung cancer: Identification and development of a risk prediction model DOI Creative Commons
Fei Wang,

Zeming Guo,

Wei Tang

et al.

Journal of Advanced Research, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

Citations

0
Gut Escherichia coli promotes lung cancer by increasing circulating STAMBP production. DOI Creative Commons
Xinpei Li, You Mo,

Shijie Shang

et al.

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1), P. 459 - 459

Published: April 3, 2025

Language: Английский

Citations

0
Lipid-lowering drugs affect lung cancer risk via sphingolipid metabolism: a drug-target Mendelian randomization study DOI Creative Commons
Honglin Li, Lei Zhang, Feiran Yang

et al.

Frontiers in Genetics, Journal Year: 2023, Volume and Issue: 14

Published: Nov. 16, 2023

The causal relationship between lipid-lowering drug (LLD) use and lung cancer risk is controversial, the role of sphingolipid metabolism in this effect remains unclear.

Language: Английский

Citations

7
Comparative Metabolomics DOI
İdil Yet

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

Citations

0
Metabolomics Signatures of Exposure to Ambient Air Pollution: A Large-Scale Metabolome-Wide Association Study in the Cancer Prevention Study-II Nutrition Cohort DOI Creative Commons
Donghai Liang, Ziyin Tang, W. Ryan Diver

et al.

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

Existing air pollution metabolomics studies showed inconsistent results, often limited by small sample size and individual pollutants effects. We conducted a metabolome-wide association study among 1096 women (68.2 ± 5.7 years) who provided blood samples (1998–2001) within the Cancer Prevention Study-II Nutrition Cohort. Annual average exposures to particulate matter, nitrogen dioxide, ozone, sulfur carbon monoxide in year of draw were used. Metabolomics profiling was on serum Metabolon. evaluated effects using multiple linear regression mixture effect quantile g-computation, adjusting for confounders false discovery rate (FDR). Ninety-five metabolites significantly associated with at least one pollutant or (FDR < 0.05). These enriched pathways related oxidative stress, systemic inflammation, energy metabolism, signals transduction, nucleic acid damage repair, xenobiotics. Sixty confirmed level 1 2 evidence, which 21 have been previously linked exposure, including taurine, creatinine, sebacate. Overall, our results replicate prior findings large provide novel insights into biological responses long-term exposure analysis.

Language: Английский

Citations

0