Search Results (442)

The core perturbome is defined as a central response to multiple disturbances, functioning as a complex molecular network to overcome the disruption of homeostasis under stress conditions, thereby promoting tolerance and survival under stress conditions. Based on the biological and clinical relevance of Escherichia coli and Staphylococcus aureus, we characterized their molecular responses to multiple perturbations. Gene expression data from E. coli (8815 target genes—based on a pangenome—across 132 samples) and S. aureus (3312 target genes across 156 samples) were used. Accordingly, this study aimed to identify and describe the functionality of the core perturbome of these two prokaryotic models using a machine learning approach. For this purpose, feature selection and classification algorithms (KNN, RF and SVM) were implemented to identify a subset of genes as core molecular signatures, distinguishing control and perturbation conditions. After verifying effective dimensional reduction (with median accuracies of 82.6% and 85.1% for E. coli and S. aureus, respectively), a model of molecular interactions and functional enrichment analyses was performed to characterize the selected genes. The core perturbome was composed of 55 genes (including nine hubs) for E. coli and 46 (eight hubs) for S. aureus. Well-defined interactomes were predicted for each model, which are jointly associated with enriched pathways, including energy and macromolecule metabolism, DNA/RNA and protein synthesis and degradation, transcription regulation, virulence factors, and other signaling processes. Taken together, these results may support the identification of potential therapeutic targets and biomarkers of stress responses in future studies. Full article

Background: Patients with resected stage IIB and IIC melanoma are at high risk of recurrence and distant metastasis, despite surgical treatment. The recent emergence of immune checkpoint inhibitors (ICIs) has led to their evaluation in the adjuvant setting for early-stage disease. This review aims to synthesize current evidence regarding adjuvant immunotherapy for stage IIB/IIC melanoma, explore emerging strategies, and highlight key challenges and future directions. Methods: We conducted a comprehensive literature review of randomized clinical trials, observational studies, and relevant mechanistic and biomarker research on adjuvant therapy in stage IIB/IIC melanoma. Particular focus was placed on pivotal trials evaluating PD-1 inhibitors (KEYNOTE-716 and CheckMate 76K), novel vaccine and targeted therapy trials, mechanisms of resistance, immune-related toxicity, and biomarker development. Results: KEYNOTE-716 and CheckMate 76K demonstrated significant improvements in recurrence-free survival (RFS) and distant metastasis-free survival (DMFS) with pembrolizumab and nivolumab, respectively, compared to placebo. However, no definitive overall survival benefit has yet been shown. Adjuvant immunotherapy is linked to immune-related adverse events, including permanent endocrinopathies. Emerging personalized approaches, such as circulating tumor DNA monitoring and gene expression profiling, may enhance patient selection, but remain investigational. Conclusions: Adjuvant PD-1 blockade offers clear RFS benefits in high-risk stage II melanoma, but optimal patient selection remains challenging, due to uncertain overall survival benefit and toxicity concerns. Future trials should integrate biomarker-driven approaches to refine therapeutic decisions and minimize overtreatment. Full article

Posterior capsule opacification (PCO), a frequent complication of cataract surgery, arises from dysregulated wound healing and fibrotic transformation of residual lens epithelial cells. While transcriptomic and machine learning (ML) approaches have elucidated fibrosis-related pathways in other tissues, the molecular divergence between regenerative and fibrotic outcomes in the lens remains unclear. Here, we used an ex vivo chick lens injury model to simulate post-surgical conditions, collecting RNA from lenses undergoing either regenerative wound healing or fibrosis between days 1–3 post-injury. Bulk RNA sequencing data were normalized, log-transformed, and subjected to univariate filtering prior to training LASSO, SVM, and RF ML models to identify discriminatory gene signatures. Each model was independently validated using a held-out test set. Distinct gene sets were identified, including fibrosis-associated genes (VGLL3, CEBPD, MXRA7, LMNA, gga-miR-143, RF00072) and wound-healing-associated genes (HS3ST2, ID1), with several achieving perfect classification. Gene Set Enrichment Analysis revealed divergent pathway activation, including extracellular matrix remodeling, DNA replication, and spliceosome associated with fibrosis. RT-PCR in independent explants confirmed key differential expression levels. These findings demonstrate the utility of supervised ML for discovering lens-specific fibrotic and regenerative gene features and nominate biomarkers for targeted intervention to mitigate PCO. Full article

Of breast cancers, the triple-negative subtype (TNBC) is characterized by aggressive behavior, poor prognosis and limited treatment options due to its high molecular heterogeneity. Since insufficient programmed cell death response is a major hallmark of cancer, here we searched for apoptosis-related biomarkers of prognostic potential in TNBC. The expression of the pro-apoptotic caspase 8, cytochrome c, caspase 3, the anti-apoptotic BCL2 and the caspase-independent mediator, apoptosis-inducing factor-1 (AIF1; gene AIFM1) was tested in TNBC both in silico at transcript and protein level using KM-Plotter, and in situ in our clinical TNBC cohort of 103 cases using immunohistochemistry. Expression data were correlated with overall survival (OS), recurrence-free survival (RFS) and distant metastasis-free survival (DMFS). We found that elevated expression of the executioner apoptotic factors AIF1 and caspase 3, and of BCL2, grants significant OS advantage within TNBC, both at the mRNA and protein level, particularly for chemotherapy-treated vs untreated patients. The dominantly cytoplasmic localization of AIF1 and cleaved-caspase 3 proteins in primary TNBC suggests that chemotherapy may recruit them from the cytoplasmic/mitochondrial stocks to contribute to improved patient survival in proportion to their expression. Our results suggest that testing for the expression of AIF1, caspase 3 and BCL2 may identify partly overlapping TNBC subgroups with favorable prognosis, warranting further research into the potential relevance of apoptosis-targeting treatment strategies. Full article

Background: Glioblastoma (GBM) is one of the most challenging malignancies in all of neoplasms. These malignancies are associated with unfavorable clinical outcomes and significantly compromised patient wellbeing. The immunological landscape within the tumor microenvironment (TME) plays a critical role in determining GBM prognosis. By mining data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and correlating them with immune responses in the TME, genes associated with the immune microenvironment with potential prognostic value were obtained. Method: We selected GSE16011 as the training set. Gene expression profiles were substrates scored by both ESTIMATE and xCell, and immune cell subpopulations in GBM were analyzed by CIBERSORT. Gene expression profiles associated with low immune scores were performed by lasso regression, Cox analysis and random forest (RF) to identify a prognostic model for the multiple genes associated with immune infiltration in GBM. Then we constructed a nomogram to optimize the prognostic model using GSE7696 and TCGA-GBM as validation sets and evaluated these data for gene mutation and gene enrichment analysis. Result: The prognostic correlation between the six genes (MEOX2, PHYHIP, RBBP8, ST18, TCF12, and THRB) and GBM was finally found by lasso regression, Cox regression, and RF, and the online database obtained that all six genes were differentially expressed in GBM. Therefore, a prognostic correlation model was constructed based on the six genes. Kaplan–Meier (KM) survival analysis showed that this prognostic model had excellent prognostic ability. Conclusions: Prognostic models based on tumor microenvironment and immune score stratification and the construction of related genes have potential applications for prognostic analysis of GBM patients. Full article

Background/Objectives: The resistance mutations EGFR^{L858R/T790M/C797S} in epidermal growth factor receptor (EGFR) are key factors in the reduced efficacy of Osimertinib. Predicting the inhibitory effects of Osimertinib derivatives against these mutations is crucial for the development of more effective inhibitors. This study aims to predict the inhibitory effects of Osimertinib derivatives against EGFR^{L858R/T790M/C797S} mutations. Methods: Six models were established using heuristic method (HM), random forest (RF), gene expression programming (GEP), gradient boosting decision tree (GBDT), polynomial kernel function support vector machine (SVM), and mixed kernel function SVM (MIX-SVM). The descriptors for these models were selected by the heuristic method or XGBoost. Comprehensive learning particle swarm optimizer was adopted to optimize hyperparameters. Additionally, the internal and external validation were performed by leave-one-out cross-validation ($Q_{LOO}^2$), 5-fold cross validation ($Q_{5-fold}^2$) and concordance correlation coefficient (CCC), $Q_{F1}^2$, and $Q_{F2}^2$. The properties of novel EGFR inhibitors were explored through molecular docking analysis. Results: The model established by MIX-SVM whose kernel function is a convex combination of three regular kernel functions is best: $R^2$ and RMSE for training set and test set are 0.9445, 0.1659 and 0.9490, 0.1814, respectively; $Q_{LOO}^2$, $Q_{5-fold}^2$, CCC, $Q_{F1}^2$, and $Q_{F2}^2$ are 0.9107, 0.8621, 0.9835, 0.9689, and 0.9680. Based on these results, the IC₅₀ values of 162 newly designed compounds were predicted using the HM model, and the top four candidates with the most favorable physicochemical properties were subsequently validated through PEA. Conclusions: The MIX-SVM method will provide useful guidance for the design and screening of novel EGFR^{L858R/T790M/C797S} inhibitors. Full article

Breast cancer is a leading cause of central nervous system (CNS) metastases in women, often associated with poor prognosis and limited therapeutic options. However, molecular differences between primary tumors and CNS metastases remain underexplored. We aimed to characterize transcriptomic differences between primary breast tumors and matched CNS metastases and identify immune-related biomarkers associated with metastatic progression and patient outcomes. Transcriptomic profiling was based on 11 matched FFPE sample pairs (primary tumor and CNS metastasis). Paired formalin-fixed paraffin-embedded (FFPE) samples from primary tumors (T1) and CNS metastases (T2) were analyzed using the NanoString nCounter^® platform and the PanCancer IO 360™ Gene Expression Panel. Differential gene expression, Z-score transformation, and heatmap visualization were performed in R. In silico survival analyses for overall survival (OS) and recurrence-free survival (RFS) were conducted using publicly available TCGA and GEO datasets. Forty-five genes were significantly differentially expressed between the T1 and T2 samples. Immune-related genes such as CXCL9, IL7R, CD79A, and CTSW showed consistent downregulation in CNS metastases. High expression of CXCL9 and CD79A was associated with improved OS and RFS, whereas high IL7R and CTSW expression correlated with worse outcomes. These findings indicate immune suppression as a hallmark of CNS colonization. Comparative transcriptomic analysis further underscored the distinct molecular landscapes between primary and metastatic tumors. This study highlights transcriptional signatures associated with breast cancer CNS metastases, emphasizing the role of immune modulation in metastatic progression. The identified genes have potential as prognostic biomarkers and therapeutic targets, supporting the need for site-specific molecular profiling in metastatic breast cancer management. Full article

Skeletal muscle atrophy is a debilitating condition characterized by the loss of muscle mass and function. It is commonly associated with aging, chronic diseases, disuse, and prolonged glucocorticoid therapy. Oxidative stress and catabolic signaling pathways play significant roles in the progression of muscle degradation. Despite its clinical relevance, few effective therapeutic options are currently available. In this study, we investigated the protective effects of an ethanolic extract of Glycine Semen Preparata (GSP), i.e., fermented black soybeans, using in vitro and in vivo models of dexamethasone (Dexa)-induced muscle atrophy. In C2C12 myoblasts and myotubes, GSP significantly attenuated both oxidative stress-induced and Dexa-induced damages by reducing reactive oxygen species levels and by suppressing the expression of the muscle-specific E3 ubiquitin ligases MuRF1 and Atrogin-1. Moreover, GSP upregulated key genes involved in muscle regeneration (Myod1 and Myog) and mitochondrial biogenesis (PGC1α), indicating its dual role in muscle protection and regeneration. Oral administration of GSP to mice with Dexa-induced muscle atrophy resulted in improved muscle fiber integrity, increased proportion of large cross-sectional area fibers, and partial recovery of motor function. Isoflavone aglycones, such as daidzein and genistein, were identified as active compounds that contribute to the beneficial effects of GSP through antioxidant activity and gene promoter enhancement. Thus, GSP is a promising nutraceutical that prevents or mitigates muscle atrophy by targeting oxidative stress and promoting myogenesis and mitochondrial function. Further studies are warranted to standardize the bioactive components and explore their clinical applications. Full article

To support the national goals of carbon peaking and carbon neutrality, this study proposes a household carbon emission prediction model based on Gene Expression Programming (GEP) for low-carbon retrofitting of aging residential areas in arid-cold regions. Focusing on 15 typical aging communities in Kundulun District, Baotou City, a 17-dimensional dataset encompassing building characteristics, demographic structure, and energy consumption patterns was collected through field surveys. Key influencing factors (e.g., electricity usage and heating energy consumption) were selected using Pearson correlation analysis and the Random Forest (RF) algorithm. Subsequently, a hybrid prediction model was constructed, with its parameters optimized by minimizing the root mean square error (RMSE) as the fitness function. Experimental results demonstrated that the model achieved an R² value of 0.81, reducing RMSE by 77.1% compared to conventional GEP models and by 60.4% compared to BP neural networks, while significantly improving stability. By combining data dimensionality reduction with adaptive evolutionary algorithms, this model overcomes the limitations of traditional methods in capturing complex nonlinear relationships. It provides a reliable tool for precision-based low-carbon retrofits in aging residential areas of arid-cold regions and offers a methodological advance for research on building carbon emission prediction driven by urban renewal. Full article

The combination of Chinsurah Boro II (BT)-type cytoplasmic male sterility (CMS) and Rf1, the main fertility restorer gene (Rf) for CMS-BT, has been extensively utilized for the production of three-line commercial japonica hybrid seeds. The identification of new Rf genes holds significance for the breeding of BT-type restorer lines, aiming to enhance the heterosis level of BT-type japonica hybrids. In the present study, ‘02428’, a wide-compatibility japonica variety, was observed to partially restore fertility to BT-type CMS lines. Genetic analysis revealed that ‘02428’ carries a dominant Rf gene, Rf21(t), responsible for the fertility restoration of BT-type CMS lines. Leveraging bulked segregant analysis (BSA) resequencing technology and molecular markers, the Rf21(t) locus was identified, and mapped within a candidate interval of 6–12.5 Mb on chromosome 2. Using the iso-cytoplasmic restorer populations, Rf21(t) was ultimately mapped to an interval of approximately 77 kb, encompassing 12 predicted genes, including LOC_Os02g17360, encoding a PPR-domain-containing protein and LOC_Os02g17380 (Rf2), a cloned Rf for Lead-rice-type CMS. A comparative sequence analysis, gene expression profiling and gene knockout experiments confirmed that LOC_Os02g17360 and LOC_Os02g17380 are the most likely candidates of Rf21(t). Furthermore, Rf21(t) showed the dosage effect on the fertility restoration of BT-type CMS lines. This newly identified Rf21(t) represents a valuable genetic resource for the breeding of BT-type japonica restorer lines. Our findings offer practical insights for breeders interested in advancing BT-type japonica hybrid development. Full article

Muscle aging and atrophy in the elderly are closely associated with increased oxidative stress in muscle tissue. Bioactive peptides derived from protein hydrolysates have emerged as promising functional ingredients for alleviating sarcopenia due to their antioxidant properties and enrichment in essential amino acids. In a preliminary screening, mackerel protein hydrolysate (MPH) showed notable protective effects in a myotube atrophy model. This study evaluated the anti-atrophic potential of MPHs produced using different enzymes in H₂O₂-treated C2C12 myotubes. Among five hydrolysates, the alcalase-derived hydrolysate (MHA) demonstrated the most potent effects in maintaining myotube diameter, restoring myosin heavy chain (MYH) expression, and downregulating the atrophy-related genes MAFbx and MuRF1. Mechanistically, MHA activated the Akt/FoxO signaling pathway and inhibited NF-κB activation, thereby reducing muscle protein degradation. Additionally, MHA significantly lowered intracellular ROS levels and showed strong direct antioxidant activity. Amino acid and molecular weight profiling revealed high levels of essential amino acids and low-molecular-weight peptides, suggesting a synergistic contribution to its bioactivity. These findings suggest that MHA is a promising food-derived functional material with anti-atrophic and antioxidant properties and may be useful in preventing or managing age-related muscle loss such as sarcopenia, warranting further preclinical validation. Full article

Background/Objectives: The role of KDM6A gene mutations in acute myeloid leukemia (AML) remains poorly understood. This study aimed to evaluate the impact of KDM6A mutations on relapse risk, cumulative incidence of relapse (CIR), relapse-free survival (RFS), and overall survival (OS) in adult AML patients, with a particular focus on those with RUNX1::RUNX1T1 fusion. Methods: the retrospective analysis was conducted on 1970 adult AML patients treated at Peking University People’s Hospital. Of these, 1676 patients who achieved complete remission (CR) were included. Among them, 27 harbored KDM6A mutations. Propensity score matching (PSM) was used (1:10 ratio) to compare outcomes between patients with and without KDM6A mutations. Further analysis focused on 207 patients with RUNX1::RUNX1T1 fusion, among whom 13 had KDM6A mutations (PSM 1:5). Results: In the overall cohort, KDM6A variants (n = 27) had a higher 2-year CIR (45.7% vs. 28.6%, p = 0.04). Fine–Gray analysis showed KDM6A variants independently increased relapse risk (HR = 1.98 [1.08–3.63], p = 0.03). KDM6A mutations were associated with inferior 2-year RFS (36.3% vs. 60.9%, p = 0.044). Multivariable analysis confirmed KDM6A mutations as independent predictors of poor RFS (HR = 3.08 [1.56–6.08], p = 0.001). Among RUNX1::RUNX1T1 patients, KDM6A mutations significantly increased relapse risk (75.0% vs. 21.7%, p < 0.001), raised 2-year CIR (46.9% vs. 24.0%, p = 0.05), worsened 2-year RFS (31.3% vs. 71.9%, p < 0.001), and lowered 2-year OS (63.3% vs. 86.4%, p = 0.002). They were also independent predictors of CIR (HR = 2.46 [1.11–5.47], p = 0.03), RFS (HR = 5.1, [2.5–10.5], p < 0.001) and OS (HR = 12.9, [4.3–38.7], p < 0.001). Conclusions: KDM6A mutations are significantly associated with increased relapse risk and poor prognosis in AML, especially in patients with RUNX1::RUNX1T1 fusion, and may serve as a valuable prognostic biomarker. Full article

Background/Objectives: Glioblastoma multiforme (GBM) is an aggressive and heterogeneous brain tumor with poor prognosis, emphasizing the need for reliable molecular biomarkers to improve patient stratification and treatment planning. This study aimed to identify key genes associated with overall survival in GBM by employing and comparing machine learning (ML) and deep learning (DL) approaches using RNA-Seq gene expression data. Methods: RNA-Seq expression and clinical data for primary GBM tumors were obtained from The Cancer Genome Atlas (TCGA). A univariate Cox proportional hazards regression was used to identify survival-associated genes. For survival prediction, ML-based feature selection techniques—RF, GB, SVM-RFE, RF-RFE, and PCA—were used to construct multivariate Cox models. Separately, DeepSurv, a DL-based survival model, was trained using the significant genes from the univariate analysis. Gradient-based importance scoring was applied to determine key genes from the DeepSurv model. Results: Univariate analysis yielded 694 survival-associated genes. The best ML-based Cox model (RF-RFE with 90% training data) achieved a c-index of 0.725. In comparison, DeepSurv demonstrated superior performance with a c-index of 0.822. The top 10 genes were identified from the DeepSurv analysis, including CMTR1, GMPR, and PPY. Kaplan–Meier survival curves confirmed their prognostic significance, and network analysis highlighted their roles in processes such as purine metabolism, RNA processing, and neuroendocrine signaling. Conclusions: This study demonstrates the effectiveness of combining ML and DL models to identify prognostic gene expression biomarkers in GBM, with DeepSurv providing higher predictive accuracy. The findings offer valuable insights into GBM biology and highlight candidate biomarkers for further validation and therapeutic development. Full article

Background and Objectives: Due to the progress made in all areas of research, pediatric patients diagnosed with acute lymphoblastic leukemia (ALL) now have an average overall survival rate of 90%. There are still discrepancies between high-income countries and limited-resource centers. The aim of this study was to analyze prognostic factors and outcome parameters in a 223-patient cohort from a single center in Romania, treated with two adapted BFM protocols. Materials and Methods: The patients diagnosed with ALL in our center were enrolled in this study from January 2016 to December 2022 and subsequently followed up until December 2024. The patients were treated first according to the ALL IC BFM 2009 protocol until June 2019 and afterwards with the ALL AIEOP BFM 2017 protocol starting with July 2019. The prognostic factors were analyzed in both subgroups and the outcomes were measured: event-free survival (EFS), overall survival (OS), cumulative incidence of relapse (CIR), relapse-free survival (RFS) and non-relapse mortality (NRM). Results: The comparison between the two subgroups revealed that every parameter improved over time: complete remission after induction (87.75% vs. 80.7%), early deaths (3.92% vs. 5.78%), deaths in remission (4.08% vs. 5.26%), 5-year EFS (73.79% vs. 70.22%), 5-year CIR (18.36% vs. 19.04%), 5-year RFS (81.76% vs. 80.97%), 5-year NRM (7.85% vs. 10.77%), and 5-year OS (88.18% vs. 82.54%). Whereas for the standard-risk group, events such as relapse or death were isolated, for intermediate-risk patients, the events were limited to a small number and did not significantly influence the overall results, and for high-risk children, the results improved significantly between the two subgroups. The worst outcomes were observed in patients with the BCR::ABL1 fusion gene, T-cell phenotype, and in teenagers, compared to the ETV6::RUNX1 fusion gene, B precursor ALL, and in smaller children, respectively. Conclusions: The 5-year OS increased in our center from 82.54% to almost 90%, with the most substantial finding being the survival rate for high-risk patients, now reaching up to 80%. The prognostic factors were age at diagnosis, genetic characteristics, and response to treatment, especially prednisone sensibility. Full article

Background: Quasipaa spinosa crude extract (QSce), a natural source rich in proteins such as parvalbumin (PV), has been traditionally used to promote physical recovery. However, its mechanisms in mitigating exercise-induced fatigue remain unclear. Methods: Using a murine treadmill exhaustion model, we evaluated the effects of QS-derived Parvalbumin (QsPV) (30 and 150 mg/kg/day) on endurance capacity, oxidative stress, tissue injury, and muscle function. Indicators measured included time to exhaustion, intracellular calcium levels, antioxidant enzymes [superoxide dismutase (SOD), glutathione peroxidase (GSH-Px)], lipid peroxidation (malondialdehyde, MDA), injury markers [creatine kinase (CK), lactate dehydrogenase (LDH), cardiac troponin I (cTnI)], renal function (blood urea), and muscle force. Results: QsPV-150 significantly increased time to exhaustion by 34.6% compared to the exercise-only group (p < 0.01). It reduced MDA by 41.2% in skeletal muscle and increased SOD and GSH-Px levels by 35.4% and 28.1%, respectively. Serum CK, LDH, and cTnI were reduced by 39.5%, 31.7%, and 26.8%, respectively, indicating protection against muscle and cardiac injury. QsPV also decreased blood urea by 22.3% and improved renal histology, with reduced glomerular damage and tubular lesions. At the molecular level, QsPV restored calcium balance and downregulated calpain-1/2 and atrophy-related genes (MuRF-1, MAFbx-32). Muscle contractile force (GAS and SOL) improved by 12.2–20.3%. Conclusions: QsPV attenuates exercise-induced fatigue through multi-organ protection involving calcium buffering, oxidative stress reduction, and anti-atrophy effects. These findings support its potential as a natural recovery-enhancing supplement, pending further clinical and pharmacokinetic studies. Full article