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Cancer Research Mar 2024FLT3 internal tandem duplication (FLT3-ITD) mutations are one of the most prevalent somatic alterations associated with poor prognosis in patients with acute myeloid...
UNLABELLED
FLT3 internal tandem duplication (FLT3-ITD) mutations are one of the most prevalent somatic alterations associated with poor prognosis in patients with acute myeloid leukemia (AML). The clinically approved FLT3 kinase inhibitors gilteritinib and quizartinib improve the survival of patients with AML with FLT3-ITD mutations, but their long-term efficacy is limited by acquisition of secondary drug-resistant mutations. In this study, we conducted virtual screening of a library of 60,411 small molecules and identified foretinib as a potent FLT3 inhibitor. An integrated analysis of the BeatAML database showed that foretinib had a lower IC50 value than other existing FLT3 inhibitors in patients with FLT3-ITD AML. Foretinib directly bound to FLT3 and effectively inhibited FLT3 signaling. Foretinib potently inhibited proliferation and promoted apoptosis in human AML cell lines and primary AML cells with FLT3-ITD mutations. Foretinib also significantly extended the survival of mice bearing cell-derived and patient-derived FLT3-ITD xenografts, exhibiting stronger efficacy than clinically approved FLT3 inhibitors in treating FLT3-ITD AML. Moreover, foretinib showed potent activity against secondary mutations of FLT3-ITD that confer resistance to quizartinib and gilteritinib. These findings support the potential of foretinib for treating patients with AML with FLT3-ITD mutations, especially for those carrying secondary mutations after treatment failure with other FLT3 inhibitors.
SIGNIFICANCE
Foretinib exhibits superior efficacy to approved drugs in AML with FLT3-ITD mutations and retains activity in AML with secondary FLT3 mutations that mediate resistance to clinical FLT3 inhibitors.
Topics: Humans; Mice; Animals; Mutation; Protein Kinase Inhibitors; Leukemia, Myeloid, Acute; fms-Like Tyrosine Kinase 3; Pyrazines; Quinolines; Anilides; Aniline Compounds; Benzothiazoles; Phenylurea Compounds
PubMed: 38231480
DOI: 10.1158/0008-5472.CAN-23-1534 -
Frontiers in Molecular Biosciences 2023More people are being diagnosed with resistant breast cancer, increasing the urgency of developing new effective treatments. Several lines of evidence suggest that...
More people are being diagnosed with resistant breast cancer, increasing the urgency of developing new effective treatments. Several lines of evidence suggest that blocking the kinase activity of VEGFR-2 reduces angiogenesis and slows tumor growth. In this study, we developed novel VEGFR-2 inhibitors based on the triazolopyrazine template by using comparative molecular field analysis (CoMFA) and molecular similarity indices (CoMSIA) models for 3D-QSAR analysis of 23 triazolopyrazine-based compounds against breast cancer cell lines (MCF -7). Both CoMFA (Q = 0.575; = 0.936, R = 0.956) and CoMSIA/SE (Q = 0.575; = 0.936, R = 0.847) results demonstrate the robustness and stability of the constructed model. Six novel compounds with potent inhibitory activity were carefully designed, and screening of ADMET properties revealed their good oral bioavailability and ability to diffuse through various biological barriers. When compared with the most active molecule in the data set and with Foretinib (breast cancer drug), molecular docking revealed that the six designed compounds had strengthened affinity (-8.9 to -10 kcal/mol) to VEGFR-2. Molecular Dynamics Simulations and MMPBSA calculations were applied to the selected compound T01 with the highest predicted inhibitory activity, confirming its stability in the active pocket of VEGFR-2 over 100 ns. The present results provided the basis for the chemical synthesis of new compounds with improved inhibitory properties against the breast cancer cell line (MCF -7).
PubMed: 38074087
DOI: 10.3389/fmolb.2023.1288652 -
Journal of Cellular and Molecular... Oct 2023Mucosal melanoma (MM) is a very rare and aggressive type of cancer for which immunotherapy or targeted therapy such as BRAF/MEK inhibitors, used in cutaneous melanoma,...
Mucosal melanoma (MM) is a very rare and aggressive type of cancer for which immunotherapy or targeted therapy such as BRAF/MEK inhibitors, used in cutaneous melanoma, usually fail. Due to our earlier experience showing the high effectiveness of epidermal growth factor receptor (EGFR) and hepatocyte growth factor receptor (MET) inhibitors in reducing the activation of the MAPK and PI3K/AKT signalling pathways, we aim to test whether these drugs would also be effective for mucosal melanoma. Cells representing two commercially available mucosal melanoma cell lines (GAK and HMVII) and one cell line obtained from a patient's vaginal melanoma were treated with MET or EGFR inhibitors, or combinations of these agents. The dual-inhibitor treatment strategy resulted in a decrease of cell proliferation, migration and invasion. Moreover, combinations of inhibitors led to reduction of pEGFR/EGFR and pMET/MET ratio and downregulation of PI3K/AKT and MEK/ERK1/2-based signalling pathways. Our findings indicate a potential therapeutic strategy based on EGFR and MET inhibitors in mucosal melanoma, which should be further evaluated in vivo and in clinical experiments. They also suggest that targeting multiple receptor tyrosine kinases may block signalling crosstalk and possibly delay the appearance of resistance to kinase inhibitors in mucosal melanoma cells.
PubMed: 37679999
DOI: 10.1111/jcmm.17935 -
Acta Biomaterialia Oct 2023Gastric cancer (GC) is the fourth leading cause of cancer-related deaths worldwide and, therefore, it is urgent to develop new and more efficient therapeutic approaches....
Gastric cancer (GC) is the fourth leading cause of cancer-related deaths worldwide and, therefore, it is urgent to develop new and more efficient therapeutic approaches. Foretinib (FRT) is an oral multikinase inhibitor targeting MET (hepatocyte growth factor receptor) and RON (recepteur d'origine nantais) receptor tyrosine kinases (RTKs) that has been used in clinical trials for several solid tumors. Targeted uptake of therapeutic polymeric nanoparticles (NPs) represents a powerful approach in cancer cell drug delivery. Previously, a nanodelivery system composed of polymeric NPs functionalized with B72.3 antibody, which targets the tumor-associated antigen Sialyl-Tn (STn), has been developed. Herein, these NPs were loaded with FRT to evaluate its capacity in delivering the drug to multicellular tumors spheroids (MCTS) and mouse models. The data indicated that B72.3 functionalized FRT-loaded PLGA-PEG-COOH NPs (NFB72.3) specifically target gastric MCTS expressing the STn glycan (MKN45 SimpleCell (SC) cells), leading to a decrease in phospho-RTKs activation and reduced cell viability. In vivo evaluation using MKN45 SC xenograft mice revealed that NFB72.3 were able to decrease tumor growth, reduce cell proliferation and tumor necrosis. NFB72.3-treated tumors also showed inactivation of phospho-MET and phospho-RON. This study demonstrates the value of using NPs targeting STn for FRT delivery, highlighting its potential as a therapeutic application in GC. STATEMENT OF SIGNIFICANCE: Despite the advances in gastric cancer therapeutics, it remains one of the diseases with the highest incidence and mortality in the world. Combining targeted therapies with a controlled drug release is an attractive strategy to reduce drug cytotoxic effects and improve specific drug delivery efficiency to the cancer cells. Thus, we developed nanoparticles loaded with a tyrosine kinase inhibitor and targeting a specific tumor glycan exclusive of cancer cells. In in vivo gastric cancer xenograft mice models, these nanoparticles efficiently reduced tumor growth, cell proliferation and tumor necrosis area and inactivated phosphorylation of targeting receptors. This approach represents an innovative therapeutic strategy with high impact in gastric cancer.
Topics: Humans; Animals; Mice; Stomach Neoplasms; Tyrosine Kinase Inhibitors; Protein Kinase Inhibitors; Polymers; Nanoparticles; Polysaccharides; Necrosis; Cell Line, Tumor
PubMed: 37586448
DOI: 10.1016/j.actbio.2023.08.014 -
BMC Cancer Aug 2023Glioblastoma (GBM) is a type of highly malignant brain tumor that is known for its significant intratumoral heterogeneity, meaning that there can be a high degree of...
BACKGROUND
Glioblastoma (GBM) is a type of highly malignant brain tumor that is known for its significant intratumoral heterogeneity, meaning that there can be a high degree of variability within the tumor tissue. Despite the identification of several subtypes of GBM in recent years, there remains to explore a classification based on genes related to proliferation and growth.
METHODS
The growth-related genes of GBM were identified by CRISPR-Cas9 and univariate Cox regression analysis. The expression of these genes in the Cancer Genome Atlas cohort (TCGA) was used to construct growth-related genes subtypes (GGSs) via consensus clustering. Validation of this subtyping was performed using the nearest template prediction (NTP) algorithm in two independent Gene Expression Omnibus (GEO) cohorts and the ZZ cohort. Additionally, copy number variations, biological functions, and potential drugs were analyzed for each of the different subtypes separately.
RESULTS
Our research established multicenter-validated GGSs. GGS1 exhibits the poorest prognosis, with the highest frequency of chr 7 gain & chr 10 loss, and the lowest frequency of chr 19 & 20 co-gain. Additionally, GGS1 displays the highest expression of EGFR. Furthermore, it is significantly enriched in metabolic, stemness, proliferation, and signaling pathways. Besides we showed that Foretinib may be a potential therapeutic agent for GGS1, the worst prognostic subtype, through data screening and in vitro experiments. GGS2 has a moderate prognosis, with a slightly higher proportion of chr 7 gain & chr 10 loss, and the highest proportion of chr 19 & 20 co-gain. The prognosis of GGS3 is the best, with the least chr 7 gain & 10 loss and EGFR expression.
CONCLUSIONS
These results enhance our understanding of the heterogeneity of GBM and offer insights for stratified management and precise treatment of GBM patients.
Topics: Humans; Glioblastoma; DNA Copy Number Variations; CRISPR-Cas Systems; Brain Neoplasms; Cell Line; ErbB Receptors; Prognosis
PubMed: 37580710
DOI: 10.1186/s12885-023-11131-7 -
Aging Jun 2023Clear cell renal cell carcinoma (ccRCC) is the most common solid renal tumor. NSUN5, a gene encoding cytosine-5 RNA methyltransferase, has rarely been reported...
Clear cell renal cell carcinoma (ccRCC) is the most common solid renal tumor. NSUN5, a gene encoding cytosine-5 RNA methyltransferase, has rarely been reported associated with cancer. A bioinformatics analysis revealed that NSUN5 was overexpressed in ccRCC. Gene Ontology and gene set variation analyses showed that NSUN5 was associated with tumor immunity in ccRCC. The effect of immunosuppressive treatment was superior in the low-risk group compared to the high-risk group, and higher stromal score in the high-risk group relative to the low-risk group. A drug sensitivity analysis revealed that the high-risk group was more sensitive to 5-fluorouracil, mitomycin C, methotrexate, and 17-AAG, whereas the low-risk group was more sensitive to crizotinib, sorafenib, foretinib, and ivozanib. NSUN5 knockout decreased ccRCC cell proliferation. The migration speed and number of invasive cells further decreased. The percentage of apoptotic cells increased. In NSUN5-knockout cells, the levels of BAX, caspase-8, caspase-9, and p53 increased significantly, whereas those of Bcl2, CCND1, CCND3, and MMP9 decreased significantly. NSUN5 is highly expressed in ccRCC and inhibits cancer cell invasion, proliferation, and migration while promoting apoptosis by activating the p53 signaling pathway. This study provides insights into the mechanisms of action of NSUN5 in urological tumors and may contribute to improving ccRCC treatment options.
Topics: Humans; Carcinoma, Renal Cell; Tumor Suppressor Protein p53; Cell Line, Tumor; Kidney Neoplasms; Kidney; Cell Proliferation; Gene Expression Regulation, Neoplastic; Methyltransferases; Muscle Proteins
PubMed: 37263638
DOI: 10.18632/aging.204761 -
Bioinformatics Advances 2023The application of machine learning (ML) techniques in the medical field has demonstrated both successes and challenges in the precision medicine era. The ability to...
MOTIVATION
The application of machine learning (ML) techniques in the medical field has demonstrated both successes and challenges in the precision medicine era. The ability to accurately classify a subject as a potential responder versus a nonresponder to a given therapy is still an active area of research pushing the field to create new approaches for applying machine-learning techniques. In this study, we leveraged publicly available data through the BeatAML initiative. Specifically, we used gene count data, generated via RNA-seq, from 451 individuals matched with data generated from treatment with RTK-type-III inhibitors. Three feature selection techniques were tested, principal component analysis, Shapley Additive Explanation (SHAP) technique and differential gene expression analysis, with three different classifiers, XGBoost, LightGBM and random forest (RF). Sensitivity versus specificity was analyzed using the area under the curve (AUC)-receiver operating curves (ROCs) for every model developed.
RESULTS
Our work demonstrated that feature selection technique, rather than the classifier, had the greatest impact on model performance. The SHAP technique outperformed the other feature selection techniques and was able to with high accuracy predict outcome response, with the highest performing model: Foretinib with 89% AUC using the SHAP technique and RF classifier. Our ML pipelines demonstrate that at the time of diagnosis, a transcriptomics signature exists that can potentially predict response to treatment, demonstrating the potential of using ML applications in precision medicine efforts.
AVAILABILITY AND IMPLEMENTATION
https://github.com/UD-CRPL/RCDML.
SUPPLEMENTARY INFORMATION
Supplementary data are available at online.
PubMed: 37250111
DOI: 10.1093/bioadv/vbad034 -
ACS Omega Jan 2023The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer...
The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave the way for the development of a new cancer therapeutic pathway. Using multiple linear regression (MLR)-quantitative structure-activity relationship (QSAR) and artificial neural network (ANN)-QSAR modeling techniques, we look at the quantitative relationship between the biological inhibitory activity of 40 small molecules derived from cyclohexane-1,3-dione and their topological, physicochemical, and electronic properties against NSCLC cells. In this regard, screening methods based on QSAR modeling with density-functional theory (DFT) computations, in silico pharmacokinetic/pharmacodynamic (ADME-Tox) modeling, and molecular docking with molecular electrostatic potential (MEP) and molecular mechanics-generalized Born surface area (MM-GBSA) computations were used. Using physicochemical (stretch-bend, hydrogen bond acceptor, Connolly molecular area, polar surface area, total connectivity) and electronic (total energy, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels) molecular descriptors, compound is identified as the optimal scaffold for drug design based on in silico screening tests. The computer-aided modeling developed in this study allowed us to design, optimize, and screen a new class of 36 small molecules based on cyclohexane-1,3-dione as potential c-Met inhibitors against NSCLC cell growth. The in silico rational drug design approach used in this study led to the identification of nine lead compounds for NSCLC therapy via c-Met protein targeting. Finally, the findings are validated using a 100 ns series of molecular dynamics simulations in an aqueous environment on c-Met free and complexed with samples of the proposed lead compounds and Foretinib drug.
PubMed: 36743017
DOI: 10.1021/acsomega.2c07585 -
Aging Jan 2023Pancreatic ductal adenocarcinoma (PADA) represents a devastating type of pancreatic cancer with high mortality. Defining a prognostic gene signature that can stratify...
BACKGROUND
Pancreatic ductal adenocarcinoma (PADA) represents a devastating type of pancreatic cancer with high mortality. Defining a prognostic gene signature that can stratify patients with different risk will benefit cancer treatment strategies.
METHODS
Gene expression profiles of PADA patients were acquired from the Cancer Genome Atlas and Gene Expression Omnibus, including GSE62452 and GSE28735. Differential expression analysis was carried out using the package edgeR in R. Intro-tumor immune infiltrates were quantified by six different computational algorithms XCELL, TIMER, QUANTISEQ, MCPCOUNTER, EPIC, and CIBERSORT. Biological processes were investigated based on R package "clusterProfiler".
RESULTS
13 genes () were eligible for the development of a prognostic gene signature. Performance of the prognostic gene signature was assessed in the discovery set (n = 210), validation set (n = 52), and two external data set (GSE62452, n = 65, and GSE28735, n = 84). Area under the curve (AUC) for predicting 3-year overall survival was 0.727, 0.732, 0.700, and 0.658 in the training set, the validation set, and the two test sets, respectively. KM curve revealed that the low-risk group had an improved prognosis than the high-risk group in all four datasets. PCA analysis demonstrated that the low-risk group was apparently separated from the high-risk group. CD8 T cell and B cell were significantly reduced in the high-risk group than in the low-risk group, while neutrophils were significantly augmented in the high-risk group than in the low-risk group. BMS-536924, Foretinib, Linsitinib, and Sabutoclax were more sensitive in the low-risk group, whereas Erlotinib was more effective in the high-risk group.
CONCLUSIONS
We successfully established and verified a novel circadian clock-related gene signature, which could stratify patients with different risk and be reflective of the therapeutic effect of molecular targeted therapy. Our findings could incorporate the pharmacological modulation of circadian clock into future therapeutic strategies.
Topics: Humans; Prognosis; Molecular Targeted Therapy; Circadian Clocks; Pancreatic Neoplasms; Carcinoma, Pancreatic Ductal; Immunity; RNA-Binding Proteins; Adaptor Proteins, Signal Transducing
PubMed: 36626244
DOI: 10.18632/aging.204462 -
International Journal of Molecular... Jan 2023This study investigated the antitumor effects of foretinib on triple-negative breast cancer cells MDA-MB-231 xenograft tumors in vivo underlying phosphorylated...
This study investigated the antitumor effects of foretinib on triple-negative breast cancer cells MDA-MB-231 xenograft tumors in vivo underlying phosphorylated mesenchymal to epithelial transition (p-MET)/ hepatocyte growth factor (HGF)-related mechanism, as well as its pharmacokinetic characteristics. The MDA-MB-231 human breast cancer cell line was used for in vitro experiments, and the tumor xenograft model was established for in vivo experiments. MDA-MB-231 xenograft mice received oral foretinib (15 or 50 mg/kg/day) or vehicle for 18 days. The xenograft tumors were collected. Protein expressions of p-MET and HGF were examined with Western blotting and immunohistochemical staining. The mRNA expression of was examined with real-time PCR. Blood samples were collected from the mice treated with foretinib under different doses of 2, 10, and 50 mg/kg, and the pharmacokinetic profiles of foretinib were evaluated. We found that foretinib treatment caused a significant inhibition in tumor growth in a dose-dependent manner, whereas the continuous administration did not result in weight loss in treated nude mice. In both MDA-MB-231 cells and xenograft tumors, foretinib suppressed the expression of p-MET and HGF. These findings reveal that the decrease of p-MET and HGF may play an important role in the anti-breast cancer properties of foretinib.
Topics: Humans; Animals; Mice; Female; Hepatocyte Growth Factor; Triple Negative Breast Neoplasms; Mice, Nude; Cell Line, Tumor; Breast Neoplasms; Xenograft Model Antitumor Assays; Cell Proliferation
PubMed: 36614199
DOI: 10.3390/ijms24010757