Design, synthesis and bioevaluation of dual EGFR-PI3Kα inhibitors for potential treatment of NSCLC.

Aberrant activation or mutation of the EGFR-PI3K-Akt-mTOR signaling pathway has been implicated in a wide range of human cancers, especially non-small-cell lung cancer (NSCLC). Thus, dual inhibition of EGFR and PI3K has been investigated as a promising strategy to address acquired drug resistance resulting from the use of tyrosine kinase inhibitors. A series of dual EGFR/PI3Kα inhibitors was synthesized using pharmacophore hybridization of the third-generation EGFR inhibitor olmutinib and the PI3Kα selective inhibitor TAK-117. The optimal compound 30k showed potent kinase inhibitory activities with IC50 values of 3.6 and 30.0 nM against EGFRL858R/T790M and PI3Kα, respectively. Compound 30k exhibited a significant antiproliferative effect in NCI-H1975 cells with a higher selectivity profile than olmutinib. The potential antitumor mechanism, molecular binding modes, and in vitro metabolic stability of compound 30k were also clarified.

Identification of novel PD-1/PD-L1 small molecule inhibitors: virtual screening, synthesis and in vitro characterisation.

The PD-1/PD-L1 pathway is considered as one of the most promising immune checkpoints in tumour immunotherapy. However, researchers are faced with the inherent limitations of antibodies, driving them to pursue PD-L1 small molecule inhibitors. Virtual screening followed by experimental validation is a proven approach to discover active compounds. In this study, we employed multistage virtual screening methods to screen multiple compound databases to predict new PD-1/PD-L1 ligands. 35 compounds were proposed by combined analysis of fitness scores, interaction pattern and MM-GBSA binding affinities. Enzymatic assay confirmed that 10 out of 35 ligands were potential PD-L1 inhibitors, with inhibitory rate higher than 50% at the concentration of 30 µM. Among them, ZDS20 was identified as the most effective inhibitor with low micromolar activity (IC50 = 3.27 µM). Altogether, ZDS20 carrying novel scaffold was identified and could serve as a lead for the development of new classes of PD-L1 inhibitors.

UPLC-MS/MS method for the determination of voriconazole plasma concentration from pediatric patients with hematologic tumors: An application toward personalized therapy.

Untreated invasive fungal infection is one of the important risk factors affecting the prognosis of pediatric patients with hematologic tumors. Voriconazole (VOR) is the first-line antifungal drug for the treatment of Aspergillus infections. In order to reduce the risk of adverse drug reactions while producing an ideal antifungal effect, therapeutic drug monitoring was performed to maintain the VOR plasma concentration in a range of 1,000-5,500 ng/ml. In the present study, a reliable, accurate, sensitive and quick ultra-high performance liquid chromatograph-tandem mass spectrometry (UPLC-MS/MS) method was developed for the determination of the VOR level. Protein precipitation was performed using acetonitrile, and then the chromatographic separation was carried out by UPLC using a C18 column with the gradient mobile phases comprising 0.1% methanoic acid in acetonitrile (A) and 0.1% methanoic acid in water (B). In the selective reaction monitor mode, the mass spectrometric detection was carried out using an TSQ Endura triple quadruple mass spectrometer. The performance of this UPLC-MS/MS method was validated as per the National Medical Products Administration for Bioanalytical Method Validation. Additionally, the plasma concentrations of VOR in pediatric patients with hematologic tumors were detected using this method, and the analyzed results were used for personalized therapy.

Synthesis and biological evaluation of cajanonic acid A derivatives as potential PPARγ antagonists.

Four series of cajanonic acid A (CAA) derivatives have been designed and synthesized. The newly prepared compounds have been screened for glucose consumption activity in HepG2 cell lines and PPARγ antagonistic activity in HEK293 cell lines. Compound 26g bearing a tetrahydroisoquinolinone scaffold showed the most potent PPARγ antagonistic and hypoglycemic activities. An oral glucose tolerance test (OGTT) was performed and the results further confirmed that 26g was a potent hypoglycemic agent. In addition, the possible binding modes for compound 26g in the PPARγ protein have been investigated in this study.

Licochalcone A suppresses the proliferation of sarcoma HT-1080 cells, as a selective R132C mutant IDH1 inhibitor.

IDH1 mutations are closely related to the development and progression of various human cancers, such as glioblastoma, sarcoma, and acute myeloid leukemia. By screening dozens of reported natural compounds using both wild-type and mutant IDH1 enzymatic assays, we discovered Licochalcone A is a selective inhibitor to the R132C-mutant IDH1 with an IC50 value of 5.176 µM, and inhibits the proliferation of sarcoma HT-1080 cells with an IC50 value of 10.75 µM. Suggested by the molecular docking results, Licochalcone A might occupy the allosteric pocket between the two monomers of IDH1 homodimer, and the R132H mutation was unfavorable for the binding of Licochalcone A with the IDH1 protein, as compared to the R132C mutation. Revealed by the RNA-Seq data analysis, the Cell Cycle pathway was the most over-represented pathway for HT-1080 cells treated with Licochalcone A. Consistent with these results, Licochalcone A induced apoptosis and cell cycle arrest of HT-1080 cells, while it showed minimal effect against the proliferation of normal RCTEC cells. The discovery of Licochalcone A as a mutation-selective IDH1 inhibitor can serve as a promising starting point for the development of mutation-selective anti-tumor lead compounds targeting IDH1.

Breast Cancer Prediction Based on Multiple Machine Learning Algorithms.

INTRODUCTION: The incidence of breast cancer has steadily risen over the years owing to changes in lifestyle and environment. Presently, breast cancer is one of the primary causes of cancer-related deaths among women, making it a crucial global public health concern. Thus, the creation of an automated diagnostic system for breast cancer bears great importance in the medical community. OBJECTIVES: This study analyses the Wisconsin breast cancer dataset and develops a machine learning algorithm for accurately classifying breast cancer as benign or malignant. METHODS: Our research is a retrospective study, and the main purpose is to develop a high-precision classification algorithm for benign and malignant breast cancer. To achieve this, we first preprocessed the dataset using standard techniques such as feature scaling and handling missing values. We assessed the normality of the data distribution initially, after which we opted for Spearman correlation analysis to examine the relationship between the feature subset data and the labeled data, considering the normality test results. We subsequently employed the Wilcoxon rank sum test to investigate the dissimilarities in distribution among various breast cancer feature data. We constructed the feature subset based on statistical results and trained 7 machine learning algorithms, specifically the decision tree, stochastic gradient descent algorithm, random forest algorithm, support vector machine algorithm, logistics algorithm, and AdaBoost algorithm. RESULTS: The results of the evaluation indicated that the AdaBoost-Logistic algorithm achieved an accuracy of 99.12%, outperforming the other 6 algorithms and previous techniques. CONCLUSION: The constructed AdaBoost-Logistic algorithm exhibits significant precision with the Wisconsin breast cancer dataset, achieving commendable classification performance for both benign and malignant breast cancer cases.

Predicting the prognosis of glioma patients with TERT promoter mutations and guiding the specific immune profile of immune checkpoint blockade therapy.

The telomerase reverse transcriptase promoter (TERTp) is frequently mutated in gliomas. This study sought to identify immune biomarkers of gliomas with TERTp mutations. Data from TCGA were used to identify and validate survival-associated gene signatures, and immune and stromal scores were calculated using the ESTIMATE algorithm. High stromal or immune scores in patients with TERTp-mutant gliomas correlated with shorter overall survival compared to cases with low stromal or immune scores. Among TERTp-mutant gliomas with both high immune and high stromal scores, 213 commonly shared DEGs were identified. Among 71 interacting DEGs representing candidate hub genes in a PPI network, HOXC6, WT1, CD70, and OTP showed significant ability in establishing subgroups of high- and low-risk patients. A risk model based on these 4 genes showed strong prognostic potential for gliomas with mutated TERTp, but was inapplicable for TERTp-wild-type gliomas. TERTp-mutant gliomas with high-risk scores displayed a greater percentage of naïve B cells, plasma cells, naïve CD4 T cells, and activated mast cells than low-risk score gliomas. TIDE analysis indicated that immune checkpoint blockade (ICB) therapy may benefit glioma patients with TERTp mutations. The present risk model can help predict prognosis of glioma patients with TERTp mutations and aid ICB treatment options.

HDAC6-dependent deacetylation of NGF dictates its ubiquitination and maintains primordial follicle dormancy.

Rationale: Primordial follicles are limited in number and cannot be regenerated, dormant primordial follicles cannot be reversed once they enter a growth state. Therefore, the length of the female reproductive lifespan depends on the orderly progression and selective activation of primordial follicles, the mechanism of which remains unclear. Methods: We used human ovarian cortical biopsy specimens, granulosa cells from diminished ovarian reserve (DOR) patients, Hdac6-overexpressing transgenic mouse model, and RNA sequencing to analyze the crucial roles of histone deacetylase 6 (HDAC6) in fertility preservation and primordial follicle activation. Results: In the present study, we found that HDAC6 was highly expressed in most dormant primordial follicles. The HDAC6 expression was reduced accompanying reproductive senescence in human and mouse ovaries. Overexpression of Hdac6 delayed the rate of primordial follicle activation, thereby prolonging the mouse reproductive lifespan. Short-term inhibition of HDAC6 promoted primordial follicle activation and follicular development in humans and mice. Mechanism studies revealed that HDAC6 directly interacted with NGF, reducing acetylation modification of NGF and thereby accelerating its ubiquitination degradation. Consequently, the reduced NGF protein level maintained the dormancy of primordial follicles. Conclusions: The physiological significance of the high expression of HDAC6 in most primordial follicles is to reduce NGF expression and prevent primordial follicle activation to maintain female fertility. Reduced HDAC6 expression increases NGF expression in primordial follicles, activating their development and contributing to reproduction. Our study provides a clinical reference value for fertility preservation.

Reconsideration of interferon treatment for viral diseases: Lessons from SARS, MERS, and COVID-19.

Periodic pandemics of coronavirus (CoV)-related pneumonia have been a major challenging issue since the outbreak of severe acute respiratory syndrome (SARS) in 2002 and Middle East respiratory syndrome (MERS) in 2012. The ongoing pandemic of CoV disease (COVID-19) poses a substantial threat to public health. As for the treatment options, only limited antiviral agents have been approved hitherto, and clinicians mainly focus on currently available drugs including the conventional antiviral interferons (IFNs). In clinical practice, IFNs, when used either alone or in combination with ribavirin and/or lopinavir/ritonavir, have shown promising outcomes, to some extent, in SARS-CoV or MERS-CoV treatment. Although the efficacy and safety of IFNs in COVID-19 treatment remain unclear, their possible use merits further evaluation. We present a review that summarizes current evidence of IFN treatment for COVID-19 and elaborates on other challenges in terms of the timing of IFN treatment initiation, treatment duration, and IFN type to be used. The review findings suggested that IFN acts by directly inhibiting viral replication and activating immune cell subsets. However, there is a lack of well-designed and controlled clinical trials providing firm evidence for the efficacy or safety of IFN therapy for CoVs. Additionally, critically ill patients with multiple immunosuppression-associated comorbidities may not benefit from IFN therapy, necessitating screening of those patients who would most benefit from IFN treatment.

Integrated investigation and experimental validation of PPARG as an oncogenic driver: implications for prognostic assessment and therapeutic targeting in hepatocellular carcinoma.

Peroxisome proliferator-activated receptor gamma (PPARG), a key transcription factor involved in lipid metabolism and glucose homeostasis, has been implicated in various types of cancer. However, its precise role in cancer remains unclear. In this study, we conducted a comprehensive pan-cancer analysis of PPARG expression using various types of cancer obtained from public databases. We observed significant heterogeneity in PPARG expression across different types of cancer. The association between PPARG expression and patient prognosis was investigated using Cox proportional hazards regression models and survival analysis. Clinical features and protein expression levels in the cohort showed that PPARG expression was strongly associated, suggesting its potential as a therapeutic target. We also evaluated the prognostic potential of PPARG by analyzing immune infiltration and genomic stability. We experimentally validated the potential of PPARG as a therapeutic target by analyzing drug sensitivity profiles, molecular docking simulations, and in vitro cell proliferation assays associated with PPARG expression. We identified common expression patterns of PPARG with other genes involved in key carcinogenic pathways. This provides deeper insights into the molecular mechanisms underlying its carcinogenic role. Additionally, functional enrichment analysis revealed significant enrichment of genes related to drug metabolism, cell proliferation, and immune response pathways associated with PPARG. Our findings highlight the importance of PPARG in the broader biology of cancer and suggest its potential as a diagnostic and therapeutic target for specific types of cancer. The results of our study provide strong support for the potential role of PPARG as a promising prognostic biomarker and immunotherapeutic target across various types of cancer.