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Rapid detection of drug-resistant leukemia played a crucial role in formulating appropriate treatment plans for patients and improving their prognosis. In this research, an integrated optofluidic platform was developed to detect and analyze leukemia and drug-resistant leukemia cell. The detection technique was designed by embedding optical fibers coupled with photosensors and a laser source into optofluidic chip. The scattered light signals were detected when the cells pass through the detecting area. The platform was first validated by classifying 1 μm polystyrene microparticles and 1 μm polystyrene microparticles coated with spherical 10 nm Fe3O4 nanoparticles. After validation, the method was applied to classify leukemia and drug-resistant leukemia cells by injecting the testing sample and obtaining. The SVM classifier demonstrated the highest classification accuracy of 91.1% compared with LR, RF, and KNN classifiers for analyzing leukemia cells and drug-resistant leukemia cells. The proposed method can perform detection within 10 min with a total experimental timeframe of 20 min. The presented results demonstrate the feasibility of applying microfluidics and machine learning approaches to detect and classify biological entities with slight variations based on scattered light signals. This platform holds significant potential for clinical diagnostics, offering a rapid, cost-effective, and efficient method for detecting drug-resistant leukemia cells, potentially aiding in personalized treatment strategies.

Indoleamine 2,3-dioxygenase 1 (IDO1) is a key immunoregulatory enzyme and a prospective target for cancer immunotherapy, while triggering cell death through apoptosis is a complementary anticancer strategy. As a result, a number of triazole analogues were developed, synthesized, and tested as promising dual immunomodulatory and apoptosis-inducing agents. Among the compounds, 3b emerged as the most potent with a GI50 of 0.72 μM against HepG2, compared to Imatinib (GI50 = 1.92 μM). It also showed higher cytotoxicity against HepG2 (liver) than non-cancerous Vero cells, with a selectivity index of 121.58. In the enzymatic experiment, 3b demonstrated higher affinity against IDO1, with a submicromolar IC50 of 0.093 μM. Further, it exhibited 199.13-fold and 313-fold selectivity against IDO1 compared to IDO2 and TDO. It also significantly and dose-dependently restored IDO1-mediated immune suppression by lowering kynurenine production and activating IL-2. In addition, 3b significantly and dose-dependently increased total apoptosis in the Annexin V assay. Furthermore, the mechanism of cytotoxicity was studied through apoptosis, as evidenced by increased levels of cytochrome c, caspase-3, caspase-9, caspase-8 (excluding), and PARP-1 in HepG2 cells. Consistent with this, higher expression of cleaved apoptotic markers (except caspase-8) in Western blots at various concentrations validated the activation of the intrinsic mitochondrial apoptotic pathway. Moreover, docking, MD simulation, and DFT also suggest IDO1 as the molecular target responsible for the observed immunomodulatory effects. Collectively, these results suggest further biological investigation to explore the translational potential of compound 3b.

Given the high incidence of hepatocellular carcinoma (HCC) and its limited therapeutic options, and building on our previous work on anti-HCC sesquiterpenoid dimers, a series of natural product-like guaianolide-eudesmanolide dimers were designed and synthesized as potential anti-HCC agents in this study. Among them, compound 1 showed significantly antihepatoma effects on HepG2, Huh-7, and SK-Hep-1 cells with IC50 values of 5.6, 4.8, and 4.6 μM, respectively; induced cell cycle arrest and apoptosis; and inhibited the migration of HCC cells. Bioinformatic analysis and experimental validation indicated that compound 1 directly targeted NEURL1B, which was further established as a critical regulator of HCC proliferation and migration. Mechanistically, compound 1 bound to Arg422 within the NHR2 domain of NEURL1B, triggering its autoubiquitination and degradation, which stabilized DLL1 by suppressing its ubiquitination and ultimately attenuated the Notch signaling pathway. In vivo experiments showed that compound 1 (60 mg/kg) inhibited tumor weight up to 69% in SK-Hep-1 xenograft nude mice, which was comparable to that of sorafenib (67%) at the same dose. This study revealed that the previously unrecognized oncogenic role of NEURL1B acted as upstream of DLL1 in HCC, and suggested that compound 1 might be an antihepatoma candidate that inhibited Notch signaling by disrupting the NEURL1B-DLL1 interaction.

The short metabolic half-life of conventional tobacco biomarkers often limits their ability to reflect cumulative toxicological damage, which may complicate risk stratification for urothelial carcinoma (UC). This study explored an explainable artificial intelligence (XAI) framework to integrate epigenetic, environmental, and clinical factors for more refined UC risk assessment. We conducted a medical center-based case-control study of 351 UC cases and 373 controls. Data on demographics, comorbidities, and biomarkers including AHRR (cg05575921) DNA methylation, urinary cotinine, 8-OHdG, and urinary heavy metals were collected and analyzed. We used LASSO regression to manage multicollinearity of metals. Eight ML models, including XGBoost, were trained and evaluated using 5-fold cross-validation. SHAP (SHapley Additive exPlanations) and mediation analyses were employed to interpret feature importance and biological pathways. Logistic regression confirmed associations between UC risk and urinary cotinine, several metals (Cr, Co, Ni, Pb), and lower AHRR methylation (all p < 0.05). Eight supervised learning algorithms were compared, with XGBoost providing the highest discriminative performance (AUC = 0.752). SHAP analysis identified chronic kidney disease and age as primary determinants, while AHRR methylation and selected metals (Ni, Cr) contributed significant independent discriminative value. Mediation analysis suggested that AHRR methylation mediated 43.74% of the effect of long-term smoking history, whereas the influence of urinary cotinine on risk was primarily mediated through increased urinary 8-OHdG. Decision tree analysis further identified a high-risk subgroup of former smokers with persistent AHRR hypomethylation despite low cotinine levels. In conclusion, by combining clinical factors with epigenetic and environmental biomarkers, our explainable machine learning framework offers robust UC risk stratification. AHRR methylation, selected metals, and CKD status provide critical information beyond standard risk factors, supporting more effective targeted surveillance for high-risk individuals.

Ovarian cancer is a leading gynecological malignancy with a poor patient survival rate. The current therapeutic regimen primarily relies on chemotherapy. However, most patients experience relapse and develop chemoresistance. Therefore, there is an urgent need to develop new anti-ovarian cancer compounds and scalable production processes. Dimethyl bisphenolate (DMB), a novel compound that we synthesized, is a phenolic acid derivative based on the neolignan backbone. The compound was produced by degrading and esterifying salvianolic acid B, the primary active ingredient in Salvia miltiorrhiza Bge. This study evaluated the anti-ovarian cancer activity of DMB through in vitro and in vivo experiments. DMB effectively inhibited the proliferation and migration of ovarian cancer cells in vitro. Mechanistic studies demonstrated that DMB suppresses ovarian cancer cell growth by regulating the PI3K/AKT/mTOR signaling pathway, impairing energy metabolism, and inducing cell cycle arrest and apoptosis. In vivo experiments further confirmed DMB significantly inhibited tumor growth in a human ovarian cancer nude mouse xenograft model. Overall, the significant anti-ovarian cancer effect demonstrated, the underlying mechanisms elucidated, and the scalable preparation technology established indicate that DMB is a promising therapeutic candidate for treating ovarian cancer.

Non-small cell lung cancer (NSCLC) is a common type of lung cancer with poor prognosis and high mortality in advanced stages. Although secreted phosphoprotein 1 (SPP1) is associated with the progression of NSCLC, its specific mechanisms remain to be explored. Through integrated bioinformatics analysis combining weighted gene co-expression network analysis (WGCNA), differential expression analysis, gene enrichment analysis with the Kyoto Encyclopedia of Genes and Genomes (KEGG)/Gene Ontology (GO), and machine learning techniques incorporating database predictions, core genes were identified. Experimental validation was conducted using Western blot, co-immunoprecipitation (Co-IP), cycloheximide (CHX) chase assay, Ubiquitin Immunoprecipitation (Ub-IP), colony formation, flow cytometry, transwell assay, reactive oxygen species (ROS) detection, and quantitative real-time PCR (qRT-PCR). The functional impact of SPP1 on tumor growth was further confirmed through mouse models and immunohistochemistry (IHC). Based on WGCNA and machine learning, SPP1 was identified as a core gene. SMURF2 ubiquitinated and degraded SPP1. Rescue experiments confirmed that SMURF2 inhibited proliferation and invasion, and promoted apoptosis in NSCLC cells, which were reversed by SPP1 overexpression. Furthermore, SMURF2 enhanced ferroptosis and modulated macrophage polarization via the same ubiquitination mechanism. Animal studies verified that SMURF2-mediated ubiquitination and degradation of SPP1 suppressed tumor growth. This study aims to investigate the role of SMURF2-mediated ubiquitination of SPP1 in inhibiting malignant progression, promoting ferroptosis, and modulating macrophage polarization in NSCLC, thereby providing a theoretical foundation and new insights for understanding and targeting NSCLC.

Lysine-specific demethylase 1 (LSD1), a key epigenetic regulator mediating histone modification, has been a potential therapeutic target for acute myeloid leukemia (AML) due to its critical role in disease pathogenesis. In this work, we designed and synthesized novel LSD1 inhibitors with the scaffold of tranylcypromine-pyrimidine. The representative compound 7a was a highly effective LSD1 inhibitor (IC50 = 7.87 nM) with excellent selectivity over MAO-A and MAO-B (>127-fold over MAO-A and > 1270-fold over MAO-B). Meanwhile, compound 7a also showed effective inhibitory activity against MV-4-11 with IC50 values of 0.36 μM. Mechanistic studies demonstrated that 7a could directly targeted LSD1, thereby promoting a significant increase of H3K4me1/2 histone methylation levels in MV-4-11 cells. 7a induced apoptosis while upregulating the differentiation marker CD86 and downregulating the stem cell-associated proteins SOX2 and CD44. Collectively, these findings establish compound 7a, a tranylcypromine-pyrimidine derivative, provides the structural foundation for the development of LSD1 inhibitors for the treatment of AML.

Activating mutations in FLT3 occur in 30% of acute myeloid leukemia (AML) cases. The AML patient-derived MV4-11 cell line contains a genetic alteration in FLT3 ("FLT3-ITD"), causing constitutive FLT3 activation. From screening, we identified compound 1 with unprecedently high anti-MV4-11 effects, with IC50 = 0.0021 ± 0.0003 nM. From the dose response curve, the effects of compound 1 are gradual and may have biphasic characteristics. Further studies identified compound 1 as a type-I FLT3 inhibitor with comparable potency to quizartinib and gilteritinib; however, compound 1 is much more potent against MV4-11 cells, indicating that it may have a second molecular mechanism of action independent of FLT3 inhibition. Interestingly, compound 1's high potency is uniquely toward MV4-11 cells, and distinct from other cell lines either with or without FLT3 mutations. Preliminary efforts to unravel this mechanism were undertaken. The results of apoptosis assay and cell cycle analysis showed that the effects of compound 1 on MV4-11 may be biphasic, with an immediate cell cycle stabilizing effect at low picomolar concentrations, and a stronger effect to arrest cell cycle and induce apoptosis at low nanomolar concentrations. However, kinase selectivity profiling demonstrates that other than FLT3, compound 1 lacks strong binding affinities with other kinases. Therefore, the high inhibitory potency of compound 1 on MV4-11 cells appear unlikely to be due to synergism of co-inhibition of FLT3 and any other kinases. Altogether, compound 1 may serve as a promising lead compound for further optimization and research on a potentially new molecular antiproliferative mechanism.

Exportin 1 (XPO1), a nuclear export protein frequently overexpressed in multiple myeloma (MM), represents a validated therapeutic target. However, noninvasive imaging approaches capable of assessing XPO1 engagement and pharmacodynamic modulation during therapy remain limited. Here, we present the radiosynthesis and preclinical evaluation of [18F]selinexor, an XPO1-targeted positron emission tomography (PET) radiotracer derived from the clinically used drug selinexor via an 18F/19F isotope exchange method. This labeling approach preserves the parent drug's molecular structure and pharmacological characteristics, enabling in vivo tracking of selinexor. [18F]Selinexor was synthesized with a radiochemical yield of 23.9 ± 4.1% and molar activity of 0.41 ± 0.08 GBq/μmol. The tracer exhibited favorable stability, XPO1-specific binding, and tumor retention. PET imaging and pharmacokinetic analysis demonstrated rapid systemic distribution followed by slow elimination, closely consistent with known pharmacokinetics of selinexor. Predominant hepatobiliary clearance and prolonged blood retention supported optimal tumor uptake at delayed imaging time points, with tracer uptake peaking at 3 h post-injection in MM.1S (2.92 ± 0.30% ID/g) and NCI-H929 (2.50 ± 0.18% ID/g) xenografts. Uptake was markedly reduced upon blocking, confirming the tracer's in vivo specificity. During therapeutic intervention, repeated selinexor administration effectively suppressed tumor growth and was accompanied by a progressive reduction in tumor uptake from 3.03 ± 0.25% ID/g (day 0) to 0.93 ± 0.13% ID/g (day 15). Notably, this reduction in uptake occurred independently of changes in tumor volume and correlated with decreased XPO1 expression by immunohistochemistry. Conversely, doxorubicin reduced tumor size without affecting uptake, indicating preserved XPO1-associated signal. Together, these findings demonstrate that [18F]selinexor PET functions as a noninvasive imaging tool for evaluating the in vivo pharmacokinetics and pharmacodynamic behavior of selinexor, and capturing treatment-induced alterations in XPO1 engagement, although further structural optimization will be required prior to potential translation.

The serine/threonine kinase UNC-51-like autophagy-activating kinase 1 (ULK1) has emerged as a promising target for cancer treatment. This study utilized an integrative approach combining computational and experimental methods to discover novel ULK1 inhibitors. Through molecular fingerprint similarity and shape-based screenings of the ChEMBL database, along with fragment growth modifications of DCC-3116, three datasets comprising a total of 1.5 million compounds were generated. A multi-level molecular docking workflow shortlisted 1520 compounds, from which 9 promising candidates (SX1-SX3, D1-D5, and CL130) were identified based on their strong binding modes, favorable binding free energies, and desirable ADMET properties. These candidate compounds were synthesized and demonstrated nanomolar inhibitory activity in the ULK1 ADP-Glo kinase assay. Notably, D1-D3 exhibited significantly higher inhibitory potency compared to the reference SBI-0206965 (IC50 = 38.19 nM), with IC50 values of 14.91 nM, 0.74 nM, and 1.06 nM, respectively. The anti-proliferation assay of D1 was conducted on HeLa cells, yielding an IC50 value of 0.83 μM. Molecular dynamics simulations further confirmed the stability of these compounds within the ULK1 binding pocket, while principal component analysis and dynamic cross-correlation matrix analyses revealed distinct conformational and binding behaviors. Binding free energy calculations indicated that the interactions between the candidate compounds and ULK1 were either stronger or comparable to those of SBI-0206965. Overall, these results suggest that SX1-SX3, and D1-D5 were promising ULK1 inhibitors, providing a solid foundation for further development as potential anticancer drugs.