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

Combinatorial Biosynthesis Creates a Novel Aglycone Polyether with High Potency and Low Side Effects Against Bladder Cancer DOI Creative Commons

Pan Yan,

Gang Wang, Minjian Huang

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: 11(32)

Published: June 27, 2024

Abstract Polyethers play a crucial role in the development of anticancer drugs. To enhance efficacy and reduce toxicity these compounds, thereby advancing their application cancer treatment, herein, guided by structure‐activity relationships aglycone polyethers, novel polyethers are rationally redesigned with potentially improved reduced against tumors. realize biosynthesis gene clusters post‐polyketide synthase tailoring pathways for endusamycin lenoremycin identified subjected to combinatorial studies, resulting creation polyether termed End‐16, which demonstrates significant potential treating bladder (BLCA). End‐16 ability suppress proliferation, migration, invasion, cellular protrusions formation BLCA cells, as well induce cell cycle arrest G1 phase vitro. Notably, exhibits superior inhibitory activity fewer side effects compared frontline anti‐BLCA drug cisplatin vivo, warranting further preclinical studies. This study highlights integrating strategies rational design create unnatural products enhanced pharmacological properties.

Language: Английский

Citations

4
Mechanistic Study of Purple Sweet Potato Anthocyanins: Multifaceted Anti-Fibrotic Effects and Targeting of PDGFRβ in Liver Fibrosis DOI
Jun Dai,

Huansong Li,

Lingshan Gou

et al.

Journal of Agricultural and Food Chemistry, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 3, 2024

The purple sweet potato anthocyanins (PSPA) are known for their diverse health benefits, yet hepatoprotective effects and the mechanisms by which they combat liver fibrosis have not been thoroughly investigated. This study aimed to elucidate these employing a carbon tetrachloride (CCl

Language: Английский

Citations

2
New finding based on Comparative Toxicogenomics Database: Hepatic YY1 mediates drug-induced liver injury DOI

Jin‐Quan Zhao,

Yuan Sun, Lulu Yang

et al.

Phytomedicine, Journal Year: 2024, Volume and Issue: 135, P. 156102 - 156102

Published: Sept. 27, 2024

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