Bioinform Adv. 2025 Apr 4;5(1):vbaf073. doi: 10.1093/bioadv/vbaf073. eCollection 2025.

ABSTRACT

MOTIVATION: The increasing use of big data and optimized prediction methods in metabolomics requires techniques aligned with biological assumptions to improve early symptom diagnosis. One major challenge in predictive data analysis is handling confounding factors-variables influencing predictions but not directly included in the analysis.

RESULTS: Detecting and correcting confounding factors enhances prediction accuracy, reducing false negatives that contribute to diagnostic errors. This study reviews concept drift detection methods in metabolomic predictions and selects the most appropriate ones. We introduce a new implementation of concept drift analysis in predictive classifiers using metabolomics data. Known confounding factors were confirmed, validating our approach and aligning it with conventional methods. Additionally, we identified potential confounding factors that may influence biomarker analysis, which could introduce bias and impact model performance.

AVAILABILITY AND IMPLEMENTATION: Based on biological assumptions supported by detected concept drift, these confounding factors were incorporated into correction of prediction algorithms to enhance their accuracy. The proposed methodology has been implemented in Semi-Automated Pipeline using Concept Drift Analysis for improving Metabolomic Predictions (SAPCDAMP), an open-source workflow available at https://github.com/JanaSchwarzerova/SAPCDAMP.

PMID:40297776 | PMC:PMC12037104 | DOI:10.1093/bioadv/vbaf073

Oncol Res. 2025 Apr 18;33(5):1229-1248. doi: 10.32604/or.2025.059411. eCollection 2025.

ABSTRACT

OBJECTIVES: Currently, there exist two approaches to the treatment of malignant neoplasms: the Karanahan technology and in situ vaccination, which are based on chronometric delivery of therapeutic agents to the tumor depending on the characteristics of tumor cells, as well as the immune status. The main purpose of this study was to experimentally prove the feasibility of combining the Karanahan technology and in situ vaccination with αOX40 antibodies into a single therapeutic platform to achieve a potent additive antitumor therapeutic effect.

METHODS: BALB/c mice grafted with B-cellular lymphoma A20 were treated using the Karanahan technology consisting of intraperitoneal cyclophosphamide administrations and intratumoral DNA injections according to an individually determined therapeutic regimen, together with in situ vaccination with αOX40. A pathomorphological analysis of the organs of experimental animals that died during the initial attempt to combine the two technologies was carried out. An analysis of blood cell populations was performed to determine the safe time for antibody administration: the number of immune cells capable of activating systemic inflammation (CD11b+Ly-6C+, CD11b+Ly-6G+, CD3-NKp46+CD11b+), the presence of Fc receptor and OX40 on the surface of these cells, and the number of neutrophils activated to NETosis were analyzed. Based on the analysis results, the antitumor efficacy of various modes of combining the Karanahan technology and in situ vaccination was studied.

RESULTS: When αOX40 was administered 5 h after each treatment using the Karanahan technology, mass death of mice caused by systemic inflammation and multiple organ failure was observed. The state of blood cells after the treatment using the Karanahan technology at the time points corresponding to antibody injections was analyzed to elucidate the reasons for this effect. It was found that at some time points, there occurs activation of the immune system and a powerful release (up to 16%) of monocytes and granulocytes carrying Fc receptor and OX40 on their surface into blood; when interacting with αOX40, they can activate the lytic potential of these cells. Activation of neutrophils to NETosis was also observed. Based on these findings, a study was carried out in different time regimes to combine the Karanahan technology and αOX40 injections. When αOX40 was injected into the points of minimal release of myeloid cells into the blood, increased survival rate and the greatest antitumor efficacy were observed: 37% of animals survived without relapses on day 100 after experiment initiation. Conclusions: The results obtained indicate that it is possible to combine the Karanahan technology and in situ vaccination with αOX40, with obligatory constant monitoring of the number of myeloid cells in peripheral blood to determine the safe time for antibody injection.

PMID:40296901 | PMC:PMC12034020 | DOI:10.32604/or.2025.059411

Front Toxicol. 2025 Apr 14;7:1605402. doi: 10.3389/ftox.2025.1605402. eCollection 2025.

NO ABSTRACT

PMID:40296895 | PMC:PMC12034682 | DOI:10.3389/ftox.2025.1605402

J Agric Food Chem. 2025 Apr 29. doi: 10.1021/acs.jafc.5c02722. Online ahead of print.

ABSTRACT

Mycoprotein, a filamentous fungi-based protein substitute for traditional meat products, plays a crucial role in ensuring global food security. While genetic manipulation of mycoprotein-producing fungi holds promise for improving key traits, such as higher protein content and biomass yield, substantial progress has yet to be made. In this study, we investigated the function of genes related to conidiogenesis to identify valuable genetic elements for increasing fungal biomass yields in Fusarium venenatum. In the FvFLBD knockout mutant of F. venenatum, fungal biomass increased compared to the wild-type strain, with conidia formation completely abolished. Nutrient profiling further revealed elevated amino acid content in this mutant, likely due to metabolic changes. Additionally, we observed synergistic effects on biomass yield in the FvFLBD and FvUBQ14 double knockout, suggesting that this approach could serve as a comprehensive strategy for enhancing fungal food production. Our findings provide valuable genetic insights and broaden the horizon of mycoprotein applications in the food industry.

PMID:40296655 | DOI:10.1021/acs.jafc.5c02722

Front Pharmacol. 2025 Apr 14;16:1579633. doi: 10.3389/fphar.2025.1579633. eCollection 2025.

ABSTRACT

BACKGROUND: Postoperative pain following cesarean section can cause maternal anxiety, limited ambulation, and even postpartum depression. In this study, we aimed to investigate the effects of esketamine for postoperative patient-controlled intravenous analgesia in women following cesarean section.

METHODS: One hundred women were randomly assigned to two groups. The esketamine group received 1 mg⋅kg-1⋅d-1 of esketamine +1 µg⋅kg-1⋅d-1 of sufentanil for intravenous postoperative analgesia, and the control group received 1 µg⋅kg-1⋅d-1 of sufentanil for intravenous analgesia. The primary outcome was the pain intensity during the postoperative 24 h, and it was assessed using a visual analog scale (VAS). The secondary outcomes included hemodynamic parameters, total consumption of analgesics, blood loss, and drug-related side effects (hypotension, hypertension, bradycardia, nausea, and vomiting).

RESULTS: The VAS scores at rest were lower in the esketamine group than in the control group during the postoperative 6 h-24 h (p < 0.05), and the VAS scores at cough in the esketamine group were lower during the postoperative 4 h-24 h (p < 0.05). There were significant differences at blood loss during the postoperative 24 h (137.6 ± 33.0 vs 159.6 ± 41.3 mL, p = 0.004). Blood pressure and heart rate were greater in the esketamine group than in the control group during the postoperative 8 h-24 h (p < 0.05). The incidence of nausea and vomiting was significantly lower in the esketamine group than in the control group (4% vs 18%, p = 0.025).

CONCLUSION: This study indicated that esketamine not only improved postoperative pain but also reduced postpartum blood loss and the incidence of nausea and vomiting in women undergoing cesarean section (registration number: ChiCTR2400082094).

SYSTEMATIC REVIEW REGISTRATION: https://www.chictr.org.cn, Identifier ChiCTR2400082094.

PMID:40297147 | PMC:PMC12034930 | DOI:10.3389/fphar.2025.1579633

Cureus. 2025 Mar 28;17(3):e81392. doi: 10.7759/cureus.81392. eCollection 2025 Mar.

ABSTRACT

Fluoxetine, a selective serotonin reuptake inhibitor (SSRI), is widely prescribed to treat depressive episodes but is rarely associated with hematological side effects such as thrombocytopenia. This report presents the case of a 26-year-old Omani man with bipolar disorder and chronic idiopathic thrombocytopenia who developed a significant decline in platelet count while being treated with fluoxetine during a depressive episode. Thrombocytopenia, defined as a platelet count below 150 × 10³/µL, can result from various factors, including immune dysregulation, infections, or drug-induced effects. Prior to initiating fluoxetine, the patient's platelet levels had been stable. However, it progressively declined during treatment, eventually reaching a critical level of 34 × 10³/µL. Extensive investigations ruled out other causes, implicating fluoxetine as the primary contributor. Discontinuing the medication led to a gradual improvement in the patient's platelet count. This case underscores the importance of promptly recognizing platelet decline and the need for healthcare providers to remain vigilant about SSRI-induced hematological side effects, especially in patients with pre-existing thrombocytopenia.

PMID:40296929 | PMC:PMC12035503 | DOI:10.7759/cureus.81392

Ther Adv Psychopharmacol. 2025 Apr 25;15:20451253251332275. doi: 10.1177/20451253251332275. eCollection 2025.

ABSTRACT

BACKGROUND: Despite the therapeutic benefits, non-adherence to lithium is common. One recent study showed that most patients discontinue lithium due to adverse effects. Little is known about individuals starting and discontinuing lithium repeatedly.

OBJECTIVES: We aimed to determine reasons for discontinuing and restarting lithium multiple times in patients with bipolar or schizoaffective disorder.

DESIGN: Retrospective cohort study based on psychiatric case records of the SLaM Biomedical Research Centre Case Register (SLaM BRC case register).

METHOD: Anonymised clinical data were extracted via the Clinical Record Interactive Search (CRIS) application. Patients with at least three events of lithium discontinuation between 2012 and 2022 were included.

RESULTS: Of 2888 eligible patients, 123 patients had discontinued lithium on at least three occasions. Psychiatric reasons, such as suspected lack of insight, feeling subjectively well or disagreeing with diagnosis, were the most common reasons for lithium discontinuations. They accounted for 77.2% of cases in the first event of discontinuation, 73.2% in the second and 72.3% in the third event. Adverse physical effects accounted for 19.5% of cases in the first event of discontinuation, 25.2% in the second and 26.0% in the third event. Relapse into the underlying affective disorder accounted for 83.7% each of reinstatements in the first and second events and 82.1% in the third event.

DISCUSSION: In our sample, lithium was discontinued due to adverse effects in only a minority of patients. In most cases, the reasons for lithium discontinuation were considered psychiatric. Lithium was mainly restarted due to relapse. This warrants a better understanding of the reasons for repeatedly discontinuing lithium and the best way to promote lithium adherence to prevent a perpetual cycle of remitting when on lithium and relapsing when off lithium.

PMID:40296869 | PMC:PMC12035018 | DOI:10.1177/20451253251332275

Clin Pharmacol Drug Dev. 2025 Apr 29. doi: 10.1002/cpdd.1538. Online ahead of print.

ABSTRACT

Long-acting (LA) cabotegravir 200-mg/mL (CAB200) injections are approved for HIV-1 prevention and as a complete LA HIV-1 treatment regimen with rilpivirine. A high-concentration suspension formulation, cabotegravir 400 mg/mL (CAB400-D), was developed to enable less frequent dosing and self-administration. This phase 1, double-blind, randomized study (NCT04484337) evaluated intramuscular (IM) gluteal, subcutaneous (SC) abdominal, and IM thigh CAB400-D injections (200-800 mg [0.5-2.0 mL]) in adults without HIV, using CAB200 injections as active control. Co-administration with recombinant human hyaluronidase (rHuPH20), topical nonsteroidal anti-inflammatory drug, or topical steroid was evaluated for some SC injections. Pharmacokinetics, adverse events (AEs), and participant-reported outcomes were assessed. Overall, 138 participants were enrolled. Absorption was faster with CAB400-D versus CAB200. Within 4 weeks, CAB400-D plasma exposures were similar across administration routes and higher than those of CAB200. Co-administration with rHuPH20 increased the spontaneous absorption rate of CAB400-D but not CAB200. No deaths or drug-related serious AEs were observed. Five (4%) participants discontinued treatment due to AEs (injection-site reactions [ISRs], n = 3 discontinuations). Most (99%) participants experienced ≥ 1 ISR. Participants reported good acceptability of injections. Although CAB400-D injections demonstrated acceptable safety/tolerability, faster absorption than CAB200 limited potential dosing intervals to monthly dosing. Alternative cabotegravir formulations with longer dosing intervals are under clinical evaluation.

PMID:40296638 | DOI:10.1002/cpdd.1538

BMC Cardiovasc Disord. 2025 Apr 28;25(1):330. doi: 10.1186/s12872-025-04768-8.

ABSTRACT

BACKGROUND: Genetic variations in the CYP2C19 gene, which encodes the major enzyme responsible for activating clopidogrel, may influence response to Clopidogrel antiplatelet therapy. This study aimed to assess the prevalence of CYP2C19 variants in Syrian patients with coronary artery disease (CAD) and evaluate the impact of these variants on the clinical efficacy of a doubled maintenance dose of clopidogrel following percutaneous coronary intervention (PCI).

METHODS: This study included 50 Syrian CAD patients on dual antiplatelet therapy (DAPT) with a doubled maintenance dose of clopidogrel. CYP2C19 genotypes were determined by PCR, followed by Sanger sequencing. Clinical outcomes, including major acute cardiovascular events (MACE) and bleeding events, were monitored over 18-24 months.

RESULTS: The allele frequencies were 8% for CYP2C19*2, 0% for CYP2C19*3, and 17% for CYP2C19*17. The distribution of our study population by CYP2C19 genotype-predicted metabolizer phenotypes was 56% for normal metabolizers (NMs), 26% for intermediate metabolizers (IMs), 12% for rapid metabolizers (RMs), and 2% for ultra-rapid metabolizers (UMs). No association was found between the CYP2C19*2 allele and recurrent ischemic events or between the CYP2C19*17 allele and bleeding complications in patients treated with a doubled maintenance dose of clopidogrel.

CONCLUSIONS: In Syrian patients undergoing PCI, a doubled maintenance dose of clopidogrel (150 mg/day) may help mitigate variability in response due to CYP2C19*2 carrier status, offering potential benefits in optimizing antiplatelet therapy. However, given the study's limited sample size, these findings should be interpreted with caution, and larger studies are needed to confirm this potential benefit.

PMID:40295977 | DOI:10.1186/s12872-025-04768-8

BMC Cancer. 2025 Apr 28;25(1):799. doi: 10.1186/s12885-025-14218-5.

ABSTRACT

OBJECTIVE: While PD-L1 expression serves as a predictive biomarker for programmed cell death 1 and its ligand (PD-1/PD-L1) inhibitor efficacy in patients with non-small cell lung cancer (NSCLC), its association with treatment-related adverse events (TRAEs) has yet to be fully elucidated. This study systematically evaluated the correlation between PD-L1 expression status and TRAEs in patients with NSCLC.

METHODS: We systematically searched the Cochrane Library, Embase, and PubMed databases from inception to June 30, 2024, to identify prospective clinical trials examining PD-1/PD-L1 inhibitors among NSCLC patients that reported treatment-related toxicity data stratified by PD-L1 expression.

RESULTS: Twenty-six prospective trials (N = 5,453) were analyzed. At the 1%, 25%, and 50% PD-L1 cutoffs, PD-L1-negative patients presented significantly reduced risks of grade 3-4 TRAEs (OR = 0.37, 0.53, 0.41; 95% CI = 0.18-0.77, 0.31-0.90, 0.19-0.97; P < 0.01, 0.02, 0.04). Similarly, PD-L1-negative patients had significantly reduced risks of AEs leading to treatment discontinuation at the 1% and 25% PD-L1 cutoffs (OR = 0.25, 0.38; 95% CI = 0.08-0.76, 0.16-0.89; P = 0.01, 0.03) but not at the 50% PD-L1 cutoff (OR 0.28, 95% CI 0.07-1.12, P = 0.07). Subgroup analyses revealed elevated all-grade TRAEs with the 22C3 immunohistochemistry assay (P < 0.001), whereas first-line therapy recipients (P = 0.006) and open-label trial participants (P = 0.002) presented increased grade 3-4 TRAEs.

CONCLUSIONS: PD-L1 positivity may predict increased risks of grade 3-4 TRAEs and AEs leading to treatment discontinuation in NSCLC patients receiving PD-1/PD-L1 blockade. Furthermore, PD-L1 expression might be a useful biomarker for toxicity management in patients with NSCLC after PD-1/PD-L1 inhibitor treatment.

PMID:40295968 | DOI:10.1186/s12885-025-14218-5

In Vivo. 2025 May-Jun;39(3):1458-1469. doi: 10.21873/invivo.13947.

ABSTRACT

BACKGROUND/AIM: The concurrent use of vascular endothelial growth factor (VEGF) inhibitors and nonsteroidal anti-inflammatory drugs (NSAIDs) raises concerns regarding the increased risk of adverse drug reactions (ADRs) due to potential pharmacodynamic interactions. However, no studies have specifically addressed this issue. The objective of this study was to investigate whether the combination of these drugs increased the risk of ADRs.

PATIENTS AND METHODS: Disproportionality analysis was conducted on ADR reports from the Japanese Adverse Drug Event Report (JADER) and FDA Adverse Event Reporting System (FAERS) databases. The concomitant signal score and Ω shrinkage measure were used to identify safety signals associated with the drug combination. Additionally, logistic regression analysis focused on reports of ADRs related to cancer treatment and assessed the significance of the adjusted reporting odds ratio (aROR) for the interaction between these drugs.

RESULTS: Disproportionality analysis included ADR data from the JADER (n=1,509,399) and FAERS (n=38,610,433) databases. The concomitant signal score and Ω shrinkage measure identified a signal for gastrointestinal perforation in both databases. Logistic regression on cancer treatment-related ADRs (JADER: n=255,177; FAERS: n=1,167,941) showed a synergistic increase in gastrointestinal perforation risk with the drug combination [aROR for interaction term: JADER: 1.74 (95% confidence interval (CI)=1.45-2.07); FAERS: 1.49 (95% CI=1.29-1.72)].

CONCLUSION: The combination of VEGF inhibitors and NSAIDs is associated with an increased risk of gastrointestinal perforation, a serious and potentially fatal ADR. Therefore, caution is warranted when prescribing a combination of these drugs.

PMID:40294980 | DOI:10.21873/invivo.13947

Sci Rep. 2025 Apr 28;15(1):14903. doi: 10.1038/s41598-025-98399-w.

ABSTRACT

Alzheimer's disease (AD) is characterized by a progressive spread of neurofibrillary tangles (NFT), beginning in the medial perirhinal cortex (mPRC), advancing to the entorhinal cortex (ERC), and subsequently involving the hippocampus, lateral perirhinal cortex (lPRC), and the rest of the brain. Given the close relationship between NFT accumulation and neuronal loss, the mPRC reflects a promising structural marker for early diagnosis of AD. However, only limited tools that automatically measure the cortical thickness of the mPRC are currently available. Utilizing the nnU-Net framework, we trained models on structural MRI of 126 adults, with manually segmented labels as ground truth. These models were then applied to an independent dataset of 103 adults (comprising patients with Alzheimer's dementia, amnestic mild cognitive impairment (aMCI), and healthy controls). High agreement was observed between manual and automated measurements of cortical thickness. Furthermore, we found significant atrophy in the Alzheimer's dementia group in the mPRC, ERC, and lPRC compared to healthy controls. Comparison of the aMCI group and healthy controls revealed significant differences in the ERC only. The results underscore the utility of our automated segmentation tool in advancing Alzheimer's research.

PMID:40295570 | DOI:10.1038/s41598-025-98399-w

Sci Rep. 2025 Apr 28;15(1):14876. doi: 10.1038/s41598-025-95803-3.

ABSTRACT

A brain tumor is a serious medical condition characterized by the abnormal growth of cells within the brain. It can cause a range of symptoms, including headaches, seizures, cognitive impairment, and changes in behavior. Brain tumors pose a significant health concern, imposing a substantial burden on patients. Timely diagnosis is crucial for effective treatment and patient health. Brain tumors can be either benign or malignant, and their symptoms often overlap with those of other neurological conditions, leading to delays in diagnosis. Early detection and diagnosis allow for timely intervention, potentially preventing the tumor from reaching an advanced stage. This reduces the risk of complications and increases the rate of recovery. Early detection is also significant in the selection of the most suitable treatment. In recent years, Smart IoT devices and deep learning techniques have brought remarkable success in various medical imaging applications. This study proposes a smart monitoring system for the early and timely detection, classification, and prediction of brain tumors. The proposed research employs a custom CNN model and two pre-trained models, specifically Inception-v4 and EfficientNet-B4, for classification of brain tumor cases into ten categories: Meningioma, Pituitary, No tumor, Astrocytoma, Ependymoma, Glioblastoma, Oligodendroglioma, Medulloblastoma, Germinoma, and Schwannoma. The custom CNN model is designed specifically to focus on computational efficiency and adaptability to address the unique challenges of brain tumor classification. Its adaptability to new challenges makes it a key component in the proposed smart monitoring system for brain tumor detection. Extensive experimentation is conducted to study a diverse set of brain MRI datasets and to evaluate the performance of the developed model. The model's precision, sensitivity, accuracy, f1-score, error rate, specificity, Y-index, balanced accuracy, geometric mean, and ROC are considered as performance metrics. The average classification accuracy for CNN, Inception-v4, and EfficientNet-B4 is 97.58%, 99.56%, and 99.76%, respectively. The results demonstrate the excellent accuracy and performance of the previous proposed approaches. Furthermore, the trained models maintain accurate performance after deployment. The method predicts accuracy of 96.5% for CNN, 99.3% for Inception-v4, and 99.7% for EfficientNet-B4 on a test dataset of 1000 brain tumor images.

PMID:40295548 | DOI:10.1038/s41598-025-95803-3

J Neurooncol. 2025 Apr 28. doi: 10.1007/s11060-025-05063-4. Online ahead of print.

ABSTRACT

PURPOSE: Chordomas and chondrosarcomas are rare, aggressive spinal bone tumors with distinct origins, biological behavior, and treatment challenges, primarily due to their resistance to conventional chemotherapy and radiation. This study aimed to compare clinical characteristics, treatment strategies, and long-term outcomes between spinal chordoma and chondrosarcoma, and to develop a robust machine learning-based model for individualized survival prediction.

METHODS: We conducted a retrospective analysis using the National Cancer Database (NCDB) to identify patients diagnosed with spinal chordoma or chondrosarcoma from 2004 to 2017. Demographics, tumor characteristics, comorbidity indices, treatment modalities (surgery, radiation, chemotherapy), and outcomes were extracted. Kaplan-Meier and weighted log-rank analyses assessed overall survival (OS) at predefined intervals (30-day, 90-day, 1-year, 5-year, 10-year). Twelve machine learning and deep learning models were trained to predict 10-year OS. Model performance was evaluated using AUC, Brier Score, and Concordance Index (C-index). A web-based risk calculator was developed using the best-performing ensemble model.

RESULTS: A total of 3175 patients were included (chordoma: n = 1204; chondrosarcoma: n = 1971). Chordoma patients were significantly older, travelled farther for treatment, and had smaller tumors with lower rates of metastatic disease at presentation. Chondrosarcoma patients more frequently underwent gross total resection, while chordoma patients received more radiation therapy, often with higher doses and more frequent use of proton therapy. Kaplan-Meier analysis revealed that chordoma patients had superior 10-year OS compared to chondrosarcoma patients (p < 0.0001). Among those receiving radiation, chondrosarcoma patients treated with radiation alone had the poorest survival. DeepSurv achieved the highest C-index (0.83) and lowest Brier Score (0.14), while ensemble models integrating Gradient Boosting and CatBoost also demonstrated strong performance (AUC > 0.80). Age, tumor type, and radiation therapy were identified as the most influential predictors using SHAP analysis. A publicly accessible, web-based calculator was developed for individualized survival prediction.

CONCLUSION: Spinal chordoma and chondrosarcoma differ significantly in clinical features and outcomes, with chordoma showing more favorable long-term survival. The findings highlight the importance of GTR and individualized radiation therapy in optimizing outcomes. The predictive model employing complicated machine learning models provides a valuable tool for estimating long-term survival and guiding personalized treatment strategies, though external validation is needed to strengthen its generalizability and clinical utility.

PMID:40295452 | DOI:10.1007/s11060-025-05063-4

J Comput Biol. 2025 Apr 28. doi: 10.1089/cmb.2024.0884. Online ahead of print.

ABSTRACT

Predicting the survival outcomes and assessing the risk of patients play a pivotal role in comprehending the microbial composition across various stages of cancer. With the ongoing advancements in deep learning, it has been substantiated that deep learning holds the potential to analyze patient survival risks based on microbial data. However, confronting a common challenge in individual cancer datasets involves the limited sample size and the high dimensionality of the feature space. This predicament often leads to overfitting issues in deep learning models, hindering their ability to effectively extract profound data representations and resulting in suboptimal model performance. To overcome these challenges, we advocate the utilization of pretraining and fine-tuning strategies, which have proven effective in addressing the constraint of having a smaller sample size in individual cancer datasets. In this study, we propose a deep learning model that amalgamates Transformer encoder and variational autoencoder (VAE), VTrans, employing both pre-training and fine-tuning strategies to predict the survival risk of cancer patients using microbial data. Furthermore, we highlight the potential of extending VTrans to integrate microbial multi-omics data. Our method is assessed on three distinct cancer datasets from The Cancer Genome Atlas Program, and the research findings demonstrated that (1) VTrans excels in terms of performance compared to conventional machine learning and other deep learning models. (2) The utilization of pretraning significantly enhances its performance. (3) In contrast to positional encoding, employing VAE encoding proves to be more effective in enriching data representation. (4) Using the idea of saliency map, it is possible to observe which microbes have a high contribution to the classification results. These results demonstrate the effectiveness of VTrans in prediting patient survival risk. Source code and all datasets used in this paper are available at https://github.com/wenwenmin/VTrans and https://doi.org/10.5281/zenodo.14166580.

PMID:40295093 | DOI:10.1089/cmb.2024.0884

Anticancer Res. 2025 May;45(5):1953-1964. doi: 10.21873/anticanres.17572.

ABSTRACT

BACKGROUND/AIM: Bladder cancer (BCa) is associated with high recurrence rates, emphasizing the importance of early and accurate detection. This study aimed to develop a lightweight and fast deep learning model, Light-Bladder-Net (LBN), for non-invasive BCa detection using conventional urine data.

MATERIALS AND METHODS: We improved LBN's generalization by applying data transformations, adding uniform noise, and employing feature selection methods (mRMR, PCA, SVD, t-SNE) to extract key vectors from its fully connected layer. These vectors were integrated into the original dataset, and multiple machine learning models were trained to enhance classification accuracy. Lastly, weighted voting was used to assign importance across these models.

RESULTS: Our approach achieved an accuracy of 0.83, a sensitivity of 0.85, a specificity of 0.80, and a precision of 0.81, indicating robust performance in detecting BCa from urine data.

CONCLUSION: This non-invasive diagnostic method offers rapid, cost-effective predictions. A free online tool is available for clinicians and patients to conveniently detect BCa using standard urine samples at http://merlin.nchu.edu.tw/LBN/.

PMID:40295062 | DOI:10.21873/anticanres.17572

Anticancer Res. 2025 May;45(5):1981-1995. doi: 10.21873/anticanres.17574.

ABSTRACT

BACKGROUND/AIM: SH003, a novel herbal mixture consisting of Astragalus membranaceus, Angelica gigas, and Trichosanthes kirilowii Maximowicz, has shown promising anti-cancer effects in various cancers, including non-small cell lung cancer (NSCLC), which comprises approximately 85% of all lung cancer cases. Characterized by high mortality rates due to late-stage diagnosis and frequent development of resistance to traditional therapies, NSCLC is a significant clinical challenge. This study investigated the anti-cancer effects of SH003 on NSCLC cells, focusing on its role in modulating receptor tyrosine kinase (RTK) signaling pathways.

MATERIALS AND METHODS: NSCLC cell lines (A549, H460, HCC827) were treated with SH003 to evaluate cell viability (MTT assay), colony formation, apoptosis (Annexin V/7-AAD staining, western blot), and cell cycle distribution (PI staining). Phosphorylation of RTKs and related signaling molecules was analyzed using a phospho-RTK array and western blot. In vivo anti-tumor effects were assessed using an A549 xenograft mouse model treated orally with SH003.

RESULTS: NSCLC cell lines A549, H460, and HCC827 treated with SH003 showed significant, dose-dependent cell viability and colony formation reductions. SH003 induced apoptosis, evidenced by increased cleaved PARP and caspase-8 levels, and caused G1/S cell cycle arrest. Additionally, SH003 treatment decreased phosphorylation of multiple receptor tyrosine kinases (RTKs), including ErbB4, FGFR1, FGFR3, and PDGFRβ, as confirmed by an RTK array. In an A549 xenograft mouse model, SH003 inhibited tumor growth without affecting body weight, indicating low systemic toxicity.

CONCLUSION: SH003 is a promising multi-target therapeutic agent for NSCLC, offering a novel strategy to improve patient outcomes.

PMID:40295074 | DOI:10.21873/anticanres.17574

Anticancer Res. 2025 May;45(5):1965-1980. doi: 10.21873/anticanres.17573.

ABSTRACT

BACKGROUND/AIM: Colon cancer is the most prevalent type of gastrointestinal cancer, characterized by high incidence and mortality rates despite advancements in diagnosis and treatment. Although chemotherapy is the standard treatment for advanced cases, survival benefits are often limited, highlighting the need for innovative therapeutic strategies. SH003, an herbal mixture composed of Astragalus membranaceus, Angelica gigas, and Trichosanthes kirilowii Maximowicz, has demonstrated anticancer properties across various cancer types. This study aimed to explore the anticancer effects of SH003 on colon cancer through in vitro and in vivo experiments.

MATERIALS AND METHODS: In vitro studies were conducted using human colon cancer cell lines, including HCT116, HT29, SW480, SW620, LoVo, LS174T, H508, and LS1034. Cell viability assays were performed to determine IC50 values over time. Apoptosis induction was assessed through Western blot analysis. Cell cycle progression was analyzed by examining the expression of cell cycle-related proteins. The disruption of the RTK-STAT3 signaling pathway was evaluated by measuring the phosphorylation of ALK using RTK-array. In vivo experiments involved establishing an HCT116 xenograft mouse model to assess tumor growth inhibition and systemic toxicity following SH003 administration.

RESULTS: SH003 significantly reduced cell viability in all tested colon cancer cell lines, with IC50 values decreasing over time, indicating a time-dependent cytotoxic effect. Apoptosis induction was confirmed by increased levels of cleaved PARP, caspase-3, caspase-8, and caspase-9. SH003 also induced G1/S phase cell cycle arrest, as evidenced by decreased expression of p-Rb, CDK2, CDK4, and Cyclin D1. Furthermore, SH003 disrupted the RTK-STAT3 signaling pathway by reducing ALK phosphorylation and decreasing the levels of p-STAT3, c-Myc, and cyclin D1. In vivo, SH003 significantly suppressed tumor growth in the HCT116 xenograft mouse model, reducing tumor volumes without causing notable systemic toxicity.

CONCLUSION: These findings suggest that SH003 possesses robust anticancer effects against colon cancer by inducing apoptosis, causing cell cycle arrest, and disrupting RTK-STAT3 signaling. The in vivo results further confirm SH003's efficacy and safety, supporting its potential as a promising therapeutic option for colon cancer treatment. Further studies are warranted to elucidate its mechanisms and clinical applicability.

PMID:40295067 | DOI:10.21873/anticanres.17573