Construction a six-gene prognostic model for hepatocellular carcinoma based on WGCNA co-expression network DOI Creative Commons
Tian Wang,

Yu-Chun Fan,

Linli Zhang

et al.

Journal of Holistic Integrative Pharmacy, Journal Year: 2024, Volume and Issue: 5(2), P. 90 - 102

Published: June 1, 2024

Currently, the incidence of hepatocellular carcinoma remains high, and prognosis patients is poor. Prognostic biomarkers are still worth exploring. Based on The Cancer Genome Atlas (TCGA) database, differentially expressed genes (DEGs) were screened. Subsequently, a modular analysis these DEGs was performed using weighted gene co-expression network (WGCNA). A prognostic model for liver cancer constructed employing Cox proportional hazards model. Through univariate multivariate regression analyses, we developed proportional-hazards specifically carcinoma. International Consortium (ICGC) cohort data used to validate accuracy Following this, conducted further analyses genes, encompassing functional enrichment survival analysis. Additionally, utilized BBcancer database investigate whether have potential serve as blood markers. Notably, in this six-gene model, also analyzed genes' drug susceptibility. Leveraging candidate identified from WGCNA analysis, with an AUC value greater than 0.7. This incorporates HMMR, E2F2, WDR62, KIF11, MSH4, KCNF1, revealing that low expression levels had significantly better compared those high (P ​< ​0.05). revealed enriched pathways related hepatitis B, C, Furthermore, observed strong association between KCNF1 overall (OS) (HCC) patients, among which WDR62 KIF11 extracellular vesicles. demonstrated sensitivity drugs such VX-680, TAE684, Sunitinib, S-Trityl-L-cysteine, Paclitaxel, CGP-60474. risk based represents valuable tool predicting HCC may target development. In particular, carcinoma, though their precise biological functions require exploration.

Language: Английский

Hyaluronic acid-conjugated methotrexate and 5-fluorouracil for targeted drug delivery DOI

Wanfei Shao,

Yanfang Yang,

Weidong Shen

et al.

International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 273, P. 132671 - 132671

Published: May 31, 2024

Language: Английский

Citations

11
Emerging therapeutic drug monitoring technologies: considerations and opportunities in precision medicine DOI Creative Commons
Winnie S. Liang, Brett K. Beaulieu‐Jones, Susan L. Smalley

et al.

Frontiers in Pharmacology, Journal Year: 2024, Volume and Issue: 15

Published: March 13, 2024

In recent years, the development of sensor and wearable technologies have led to their increased adoption in clinical health monitoring settings. One area that is early, but promising, stages use biosensors for therapeutic drug (TDM). Traditionally, TDM could only be performed certified laboratories was used specific scenarios optimize dosage based on measurement plasma/blood concentrations. Although has been typically pursued settings involving medications are challenging manage, basic approach useful characterizing activity. idea there likely a clear relationship between concentration (or other matrices) efficacy. However, these relationships may vary across individuals affected by genetic factors, comorbidities, lifestyle, diet. will valuable enabling precision medicine strategies determine efficacy drugs individuals, as well optimizing personalized dosing, especially since windows inter-individually. this mini-review, we discuss emerging applications, factors influence including interactions, polypharmacy, supplement use. We also how using within single subject (N-of-1) aggregated N-of-1 trial designs provides opportunities better capture response activity at individual level. Individualized solutions potential help treatment selection dosing regimens so right dose matched person context.

Language: Английский

Citations

10
Organoids and spheroids: advanced in vitro models for liver cancer research DOI Creative Commons
Mirella Pastore,

A. Giachi,

Elena Spínola-Lasso

et al.

Frontiers in Cell and Developmental Biology, Journal Year: 2025, Volume and Issue: 12

Published: Jan. 9, 2025

Liver cancer is a leading cause of cancer-related deaths worldwide, highlighting the need for innovative approaches to understand its complex biology and develop effective treatments. While traditional in vivo animal models have played vital role liver research, ethical concerns demand more human-relevant systems driven development advanced vitro models. Spheroids organoids emerged as powerful tools due their ability replicate tumor microenvironment facilitate preclinical drug development. are simpler 3D culture that partially recreate structure cell interactions. They can be used penetration studies high-throughput screening. Organoids derived from stem cells or patient tissues accurately emulate complexity functionality tissue. generated pluripotent adult cells, well specimens, providing personalized studying behavior responses. retain genetic variability original offer robust platform screening treatment strategies. However, both spheroids limitations, such absence functional vasculature immune components, which essential growth therapeutic The field modeling evolving, with ongoing efforts predictive reflect complexities human cancer. By integrating these tools, researchers gain deeper insights into accelerate novel

Language: Английский

Citations

1
Organoids: development and applications in disease models, drug discovery, precision medicine, and regenerative medicine DOI Creative Commons
Qigu Yao, Sheng Cheng, Qiaoling Pan

et al.

MedComm, Journal Year: 2024, Volume and Issue: 5(10)

Published: Sept. 21, 2024

Organoids are miniature, highly accurate representations of organs that capture the structure and unique functions specific organs. Although field organoids has experienced exponential growth, driven by advances in artificial intelligence, gene editing, bioinstrumentation, a comprehensive overview organoid applications remains necessary. This review offers detailed exploration historical origins characteristics various types, their applications-including disease modeling, drug toxicity efficacy assessments, precision medicine, regenerative medicine-as well as current challenges future directions research. have proven instrumental elucidating genetic cell fate hereditary diseases, infectious metabolic disorders, malignancies, study processes such embryonic development, molecular mechanisms, host-microbe interactions. Furthermore, integration technology with intelligence microfluidics significantly advanced large-scale, rapid, cost-effective thereby propelling progress medicine. Finally, advent high-performance materials, three-dimensional printing technology, also gaining prominence Our insights predictions aim to provide valuable guidance researchers support continued advancement this rapidly developing field.

Language: Английский

Citations

8
HDAC Inhibition Sensitize Hepatocellular Carcinoma to Lenvatinib via Suppressing AKT Activation DOI Creative Commons
Shuai Yan, Lu Chen, Hao Zhuang

et al.

International Journal of Biological Sciences, Journal Year: 2024, Volume and Issue: 20(8), P. 3046 - 3060

Published: Jan. 1, 2024

Hepatocellular carcinoma (HCC) is a deadly malignancy with limited treatment options.As first-line for advanced HCC, Lenvatinib has been applicated in clinic since 2018.Resistance to Lenvatinib, however, severely restricted the clinical benefits of this drug.Therefore, it urgent explore potential resistance mechanisms and identify appropriate methods reduce HCC.We identified SAHA, HDAC inhibitor, have effective anti-tumor activity against Lenvatinib-resistant HCC organoids by screening customized drug library.Mechanism analysis revealed that SAHA upregulates PTEN expression suppresses AKT signaling, which contributes reversing liver cancer cells.Furthermore, combinational application inhibitor or synergistically inhibits cell proliferation induces apoptosis.Finally, we confirmed synergistic effects AZD5363 primary patient derived organoids.Collectively, these findings may enable development combination therapies HCC.

Language: Английский

Citations

6
Rationally Designed Cell Membrane Biomimetic Biosensing Platform for the Binding Analysis of Drugs with Intracellular Kinase Domain of Epidermal Growth Factor Receptor DOI
Xia Liu, Quan Feng, Qi Hu

et al.

Analytical Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 4, 2025

Biosensing technologies have demonstrated significant potential in exploring the binding of drugs to receptor tyrosine kinases (RTKs). As a typical transmembrane receptor, there are still several shortcomings utilization intracellular kinase domain RTKs, primary action site small-molecule inhibitors, resulting insufficient and unclear sites, which impair efficiency accuracy biosensing. Herein, using epidermal growth factor (EGFR) as an example, we reported biosensing platform based on cell membrane camouflage technology for evaluating EGFR. The azide-functionalized membranes modified through glucose metabolism were reverse-coated onto alkyne-functionalized magnetic nanoparticles via bioorthogonal reaction (CMRMNPs), therefore effectively exposing EGFR without damage. To construct platform, fluorescent probe derived from gefitinib pharmacophore (GN probe) was further synthesized incubated with CMRMNPs. This strategy facilitated efficient localization GN within Ultimately, this approach successfully implemented evaluate three inhibitors study provides viable constructing biomimetic biosensors defined orientation offers novel insights methodologies drug regions RTKs.

Language: Английский

Citations

0
Adaptive-weighted federated graph convolutional networks with multi-sensor data fusion for drug response prediction DOI

Yu Hui,

Qingyong Wang, Xiaobo Zhou

et al.

Information Fusion, Journal Year: 2025, Volume and Issue: unknown, P. 103147 - 103147

Published: April 1, 2025

Language: Английский

Citations

0
Ara-C suppresses H3 K27–altered spinal cord diffuse midline glioma growth and enhances immune checkpoint blockade sensitivity DOI Creative Commons

Baoxing Pang,

Yilin Wu,

Song‐Yuan An

et al.

Science Advances, Journal Year: 2025, Volume and Issue: 11(16)

Published: April 16, 2025

H3 K27–altered spinal cord diffuse midline glioma (H3-SCDMG) poses therapeutic challenges. Analysis of 73 clinical samples revealed heightened proliferation in H3-SCDMG versus wild-type tumors, suggesting vulnerabilities. Drug screening identified cytarabine (Ara-C) as highly effective inhibiting K27M cell models, recently established patient-derived cells, and xenograft models. Mechanistically, Ara-C can suppress tumor growth through DNA damage, cell-cycle arrest, apoptosis. An investigator-initiated trial involving four patients showed benefits three cases. In addition, a subset cells exhibited senescence senescence-associated secretory phenotype post–Ara-C treatment, accompanied by several immune checkpoint ligands’ up-regulation more infiltration. Combining with dual Programmed death protein 1 (PD-1) TIGIT blockade emerged promising strategy to disrupt evasion senescent enhancing antitumor responses. These findings highlight Ara-C’s potential monotherapy synergy immunotherapy for H3-SCDMG, offering strategies management.

Language: Английский

Citations

0
Clinical potential and experimental validation of prognostic genes in hepatocellular carcinoma revealed by risk modeling utilizing single cell and transcriptome constructs DOI Creative Commons
Hang Deng, Xu Wang, Zhenzhen Jiang

et al.

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

Published: April 4, 2025

Background Hepatocellular carcinoma (HCC) is the leading cause of tumor-related mortality worldwide. There an urgent need for predictive biomarkers to guide treatment decisions. This study aimed identify robust prognostic genes HCC and establish a theoretical foundation clinical interventions. Methods The datasets were obtained from public databases then differential expression analysis used obtain significant gene profiles. Subsequently, univariate Cox regression PH assumption test performed, risk model was developed using optimal algorithm 101 combinations on TCGA-LIHC dataset pinpoint genes. Immune infiltration drug sensitivity analyses conducted assess impact these explore potential chemotherapeutic agents HCC. Additionally, single-cell employed key cellular players their interactions within tumor microenvironment. Finally, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) utilized validate roles in Results A total eight identified (MCM10, CEP55, KIF18A, ORC6, KIF23, CDC45, CDT1, PLK4). model, constructed based genes, effective predicting survival outcomes patients. CEP55 exhibited strongest positive correlation with activated CD4 T cells. top 10 drugs showed increased low-risk group. B cells as components highest interaction numbers strengths macrophages both control groups. Prognostic more highly expressed initial state cell differentiation. RT-qPCR confirmed upregulation MCM10, PLK4 tissues (p&lt; 0.05). Conclusion successfully PLK4), which provided new directions exploring pathogenesis research

Language: Английский

Citations

0
Immune organoid for cancer immunotherapy DOI Creative Commons
Xiaohe Wang, Wuyin Wang, Zhi‐Jun Sun

et al.

Acta Pharmaceutica Sinica B, Journal Year: 2025, Volume and Issue: unknown

Published: May 1, 2025

Language: Английский

Citations

0