Machine learning models reveal ARHGAP11A's impact on lymph node metastasis and stemness in NSCLC DOI

Xiaoli Wang,

Yan Zhou,

Xiaomin Lu

et al.

BioFactors, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 31, 2024

Abstract Most patients with non‐small cell lung cancer (NSCLC) are diagnosed at an advanced stage of the disease, which complicates treatment due to a heightened risk metastasis. Consequently, timely identification biomarkers associated lymph node metastasis is essential for improving clinical management NSCLC patients. In this research, WGCNA algorithm was utilized pinpoint genes linked in NSCLC. A cluster analysis carried out investigate how these correlate prognosis and outcomes immunotherapy Following this, diagnostic prognostic models were created validated through various machine learning methodologies. The random forest technique highlighted importance ARHGAP11A, leading in‐depth examination its role By analyzing 78 tissue chip samples from patients, study confirmed association between ARHGAP11A expression, patient prognosis, Finally, influence on cells assessed function experiments. This research identify 25 that related metastasis, clarifying their connections tumor invasion, growth, activation stemness pathways. Cluster revealed significant associations NSCLC, especially concerning targeted treatments. system combines approaches demonstrated strong efficacy forecasting both diagnosis Importantly, identified as key gene Molecular docking analyses suggested has affinity therapies within Additionally, immunohistochemical assessments higher levels expression unfavorable Experiments showed reducing can hinder proliferation, traits cells. investigation reveals novel insight may potential biomarker connected Moreover, ability diminish characteristics, presenting promising opportunity strategies condition.

Language: Английский

Nervous system–gut microbiota–immune system axis: future directions for preventing tumor DOI Creative Commons
Juanjuan Wang,

Wenyue Cheng,

Rongcun Yang

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: May 1, 2025

Tumor is one of the leading causes death worldwide. The occurrence and development tumors are related to multiple systems factors such as immune system, gut microbiota, nervous system. system plays a critical role in tumor development. Studies have also found that microbiota can directly or indirectly affect tumorigenesis With increasing attention on microenvironment recent years, has emerged novel regulator Some therapies based been tested clinical trials. However, not only interact with cells but through microbiota. system-mediated regulate tumorigenesis, growth, invasion, metastasis Here, we mainly explore potential effects system-gut microbiota-immune axis involve regulating which prevent Meanwhile, direct regulation by development, reviewed.

Language: Английский

Citations

0
Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy DOI Creative Commons

Suyin Feng,

Long Zhu, Yan Qin

et al.

Biology Direct, Journal Year: 2024, Volume and Issue: 19(1)

Published: Nov. 12, 2024

Gliomas represent a highly aggressive class of tumors located in the brain. Despite availability multiple treatment modalities, prognosis for patients diagnosed with glioma remains unfavorable. Therefore, further exploration new biomarkers is crucial to enhance prognostic assessment and investigate more effective options. In this research, we utilized machine learning techniques assess significance genes related angiogenesis epithelial-mesenchymal transition (EMT) context patients. The random forest algorithm highlighted CALU, analysis indicated that effect CALU on progression may be regulated by MYC. Different approaches were employed our investigation uncover associated EMT glioma. Our findings verify connection between these glioma, as well results immunotherapeutic interventions. Notably, through experimental verification, identified marker inhibiting expression can impede

Language: Английский

Citations

2
OSBPL10‐CNBP axis mediates hypoxia‐induced pancreatic cancer development DOI Creative Commons
Yishu Huang, Ronghao Zhang,

Shuyang Fan

et al.

BioFactors, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 27, 2024

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of malignancies with worst outcomes among digestive system tumors. Identification novel biomarkers great significance for treatment researches and prognosis prediction pancreatic cancer patients. Due to OSBPL10 known involvement in oncogenic activity other tumors, we elucidated the mechanism underlying its contribution progression. We employed data from Gene Expression Omnibus database detect expression normal tissues. A series assays were conducted assess impact on proliferation metastatic capacities cells influence macrophages evaluated by Flow cytometry. In addition, Co‐immunoprecipitation, mass spectrometry, western blot utilized investigate potential mechanisms activity. From our study, revealed be upregulated cancer, poor prognosis. The overexpression promotes malignant behaviors has an tumor immune microenvironment stimulating transformation M1 into M2 macrophages. Mechanistically, hypoxia induces through interaction between hypoxia‐inducible factor 1‐α promoter region OSBPL10. Additionally, directly bound CNBP, mediating CNBP ultimately regulating metastasis capacity cells, as well influencing macrophage polarization. research emphasized role uncovering key involving hypoxia, HIF‐1α, CNBP. finding suggests that a biomarker making it therapeutic target intervention this malignancy.

Language: Английский

Citations

1
Integrated Blood Transcriptome and Multi-Tissue Trace Mineral Analyses of Healthy Stocker Cattle Fed Complexed or Inorganic Trace Mineral Supplement DOI Creative Commons
Matthew A. Scott, Kelsey M Harvey, Brandi B. Karisch

et al.

Animals, Journal Year: 2024, Volume and Issue: 14(15), P. 2186 - 2186

Published: July 26, 2024

Supplementing trace minerals is common in managing bovine respiratory disease (BRD) post-weaned cattle; however, its influence on host immunity and metabolism high-risk cattle remains unclear. We aimed to assess the impact of three supplementation programs liver serum element concentrations blood gene expression. Fifty-six beef steers were randomly assigned one groups over 60 days: (1) sulfate-sourced Cu, Co, Mn, Zn (INR), (2) amino acid-complexed (AAC), or (3) AAC plus mineral vitamin drench (COMBO). Serum biopsies for at d0, d28, d60 analyzed from free BRD (n = 9 INR; n 6 AAC; 10 COMBO). Differences correlations via generalized linear mixed models Spearman's rank coefficients, respectively (

Language: Английский

Citations

0
Machine learning models reveal ARHGAP11A's impact on lymph node metastasis and stemness in NSCLC DOI

Xiaoli Wang,

Yan Zhou,

Xiaomin Lu

et al.

BioFactors, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 31, 2024

Abstract Most patients with non‐small cell lung cancer (NSCLC) are diagnosed at an advanced stage of the disease, which complicates treatment due to a heightened risk metastasis. Consequently, timely identification biomarkers associated lymph node metastasis is essential for improving clinical management NSCLC patients. In this research, WGCNA algorithm was utilized pinpoint genes linked in NSCLC. A cluster analysis carried out investigate how these correlate prognosis and outcomes immunotherapy Following this, diagnostic prognostic models were created validated through various machine learning methodologies. The random forest technique highlighted importance ARHGAP11A, leading in‐depth examination its role By analyzing 78 tissue chip samples from patients, study confirmed association between ARHGAP11A expression, patient prognosis, Finally, influence on cells assessed function experiments. This research identify 25 that related metastasis, clarifying their connections tumor invasion, growth, activation stemness pathways. Cluster revealed significant associations NSCLC, especially concerning targeted treatments. system combines approaches demonstrated strong efficacy forecasting both diagnosis Importantly, identified as key gene Molecular docking analyses suggested has affinity therapies within Additionally, immunohistochemical assessments higher levels expression unfavorable Experiments showed reducing can hinder proliferation, traits cells. investigation reveals novel insight may potential biomarker connected Moreover, ability diminish characteristics, presenting promising opportunity strategies condition.

Language: Английский

Citations

0