Search Results (402)

We propose an advanced electronic nose based on SE-RelationNet for COPD diagnosis with limited breath samples. The model integrates residual blocks, BiGRU layers, and squeeze–excitation attention mechanisms to enhance feature-extraction efficiency. Experimental results demonstrate exceptional performance with minimal samples: in 4-way 1-shot tasks, the model achieves 85.8% mean accuracy (F1-score = 0.852), scaling to 93.3% accuracy (F1-score = 0.931) with four samples per class. Ablation studies confirm that the 5-layer residual structure and single-hidden-layer BiGRU optimize stability (h_F1-score ≤ 0.011). Compared to SiameseNet and ProtoNet, SE-RelationNet shows superior accuracy (>15% improvement in 1-shot tasks). This technology enables COPD detection with as few as one breath sample, facilitating early intervention to mitigate lung cancer risks in COPD patients. Full article

Natural products, characterized by their structural novelty, multi-target capabilities, and favorable toxicity profiles, represent a prominent reservoir for the discovery of innovative anticancer therapeutics. In the current investigation, we identified ajuforrestin A, a diterpenoid compound extracted from Ajuga lupulina Maxim, as a potent agent against lung cancer. In vitro, this compound markedly curtailed the proliferation of A549 cells. Mechanistic explorations revealed that ajuforrestin A could arrest A549 cells in the G0/G1 phase of the cell cycle, provoke apoptosis in cancer cells, and impede their migration by modulating the STAT3 and FAK signaling cascades. Angiogenesis is indispensable for tumor formation, progression, and metastatic dissemination. Vascular endothelial growth factor (VEGF) and its receptor VEGFR-2 are established as crucial mediators in tumor neovascularization, a process fundamental to both the expansion of tumor cells and the development of new blood vessels within the tumor milieu. Through the combined application of a Tg(fli1:EGFP) zebrafish model and SPR experimentation, we furnished strong evidence for the ability of ajuforrestin A to obstruct tumor angiogenesis via selective engagement with VEGFR-2. Finally, a zebrafish xenograft tumor model demonstrated that ajuforrestin A could effectively restrain tumor growth and metastasis in vivo. Ajuforrestin A therefore shows considerable promise as a lead compound for the future development of therapies against non-small cell lung cancer (NSCLC). Full article

Genetic factors play an important role in the risk of developing lung cancer, a disease that disproportionately affects African American (AA) individuals who smoke. Accumulating evidence suggests that specific ancestry-informative genetic markers are predictive of lung cancer risk in AA individuals who smoke. Although testing for, and communication of, genetic risk to patients should impact health and screening, results are mixed. The goal of this study was to evaluate the effects of genetic risk communication that also included ancestry-specific risk information among African American individuals who smoke. Using an experimental design, African American individuals who smoke (n = 166) were assigned randomly to receive hypothetical genetic test results that indicated (1) low vs. high genetic risk for lung cancer (“Risk”) and (2) European vs. African Ancestry (“Ancestry”). We hypothesized that participants who had been told that they were both at high risk for lung cancer based on genetic markers prominent in African persons at risk of lung cancer, and that they have African ancestry, would exhibit increases in cognitive (perceived lung cancer risk), emotional (cancer worry and psychological distress), and motivational (motivation to quit smoking) factors shown to predict longer-term health behavior change. Results revealed significant and moderate-to-large effects of Risk for all outcomes. There was also a significant Ancestry effect on perceived lung cancer risk: increased risk perceptions among participants who learned that they have high African genetic heritage. Path analytic modeling revealed that cognitive and emotional factors mediated the effects of both Risk and Ancestry feedback on motivation to quit smoking. Findings further highlight the importance of incorporating ancestry-specific genetic risk information into genetic counseling sessions, especially in underserved populations, as doing so may impact key cognitive, emotional, and motivational factors critical to behavior change. Full article

Background: To overcome the limitations of conventional CRC (colorectal cancer) mouse models in replicating metastasis and enabling efficient therapeutic evaluation, we developed a novel implantation method using tissue adhesive to establish reproducible orthotopic and metastatic tumors. Conventional models using injection or suturing techniques often suffer from technical complexity, inconsistent tumor establishment, and limited metastatic reliability. Methods: We developed and validated a novel orthotopic and metastatic CRC model utilizing tissue adhesive for tumor transplantation. Uniform tumor fragments derived from bioluminescent HCT116/Luc xenografts were affixed to the cecum of nude mice. Tumor growth and metastasis were monitored through bioluminescence imaging and confirmed by the results of histological analysis of metastatic lesions. The model’s utility for therapeutic testing was evaluated using MK801, an NMDA receptor antagonist. Results: The biological-based model demonstrated rapid and reproducible tumor implantation (<5 min), consistent primary tumor growth, and robust metastasis to the liver and lungs. The biological-based approach achieved 80% tumor engraftment (4/5), with consistent metastasis to the liver and lungs in all mice, compared with lower and variable metastasis rates in injection (0%, 0/5) and suturing (20%, 1/5) methods. MK801 treatment significantly suppressed both primary tumor growth and metastasis, validating the model’s suitability for preclinical drug evaluation. Conclusions: By enabling rapid, reproducible, and spontaneous formation of metastatic lesions using a minimally invasive tissue adhesive technique, our model represents a significant methodological advancement that supports high-throughput therapeutic screening and bridges the gap between experimental modeling and clinical relevance in colorectal cancer research. Full article

Background: Lung cancer, predominantly NSCLC (80%), has a poor prognosis due to late diagnosis and limited treatment efficacy. DMRTA2 (DMRT5), a transcription factor linked to neural/germ cell development, is overexpressed in NSCLC per TCGA data, indicating its potential role in tumorigenesis and as a therapeutic target. Methods: Conduct a comprehensive search of the relevant theoretical foundations. Based on this, differential expression analysis will be performed using the DESeq2 package in R on RNA-seq data from lung adenocarcinoma and lung squamous cell carcinoma in the TCGA database. The research will then employ various methods, including CRISPR genome editing, MTS assay, flow cytometry, Western blot, co-immunoprecipitation, immunofluorescence, and qRT-PCR. Results: Through experimental validation, we found that DMRTA2 mRNA is highly expressed in non-small-cell lung cancer (NSCLC) tissues and is negatively correlated with poor prognosis. DMRTA2 binds to HSP90β, inhibiting the interaction between HSP90β and p53, thereby suppressing p53 ubiquitination and nuclear export. This activates the p53 pathway, inhibiting the proliferation and invasion of lung cancer cells. Conclusions: In NSCLC, DMRTA2 acts as a context-dependent regulator, stabilizing wild-type p53 through competitive HSP90β binding to suppress tumors, while in p53-compromised cells, potentially engaging HSP90β or alternative pathways to promote malignancy. Its dual localization and transport interactions reveal multifunctional, stress-responsive roles beyond transcription. Full article

The human genome has a profound impact on human health and disease detection. Carcinoma (cancer) is one of the prominent diseases that majorly affect human health and requires the development of different treatment strategies and targeted therapies based on effective disease detection. Therefore, our research aims to identify biomarkers associated with distinct cancer types (gastric, lung, and breast) using machine learning. In the current study, we have analyzed the human genomic data of gastric cancer, breast cancer, and lung cancer patients using XGB-BIF (i.e., XGBoost-Driven Biomarker Identification Framework for detecting cancer). The proposed framework utilizes feature selection via XGBoost (eXtreme Gradient Boosting), which captures feature interactions efficiently and takes care of the non-linear effects in the genomic data. The research progressed by training XGBoost on the full dataset, ranking the features based on the Gain measure (importance), followed by the classification phase, which employed support vector machines (SVM), logistic regression (LR), and random forest (RF) models for classifying cancer-diseased and non-diseased states. To ensure interpretability and transparency, we also applied SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), enabling the identification of high-impact biomarkers contributing to risk stratification. Biomarker significance is discussed primarily via pathway enrichment and by studying survival analysis (Kaplan–Meier curves, Cox regression) for identified biomarkers to strengthen translational value. Our models achieved high predictive performance, with an accuracy of more than 90%, to classify and link genomic data into diseased (cancer) and non-diseased states. Furthermore, we evaluated the models using Cohen’s Kappa statistic, which confirmed strong agreement between predicted and actual risk categories, with Kappa scores ranging from 0.80 to 0.99. Our proposed framework also achieved strong predictions on the METABRIC dataset during external validation, attaining an AUC-ROC of 93%, accuracy of 0.79%, and Kappa of 74%. Through extensive experimentation, XGB-BIF identified the top biomarker genes for different cancer datasets (gastric, lung, and breast). CBX2, CLDN1, SDC2, PGF, FOXS1, ADAMTS18, POLR1B, and PYCR3 were identified as important biomarkers to identify diseased and non-diseased states of gastric cancer; CAVIN2, ADAMTS5, SCARA5, CD300LG, and GIPC2 were identified as important biomarkers for breast cancer; and CLDN18, MYBL2, ASPA, AQP4, FOLR1, and SLC39A8 were identified as important biomarkers for lung cancer. XGB-BIF could be utilized for identifying biomarkers of different cancer types using genetic data, which can further help clinicians in developing targeted therapies for cancer patients. Full article

Background/Objectives: Nucleic acid-based anticancer vaccines are becoming a very active field in the fight against cancer. Here, our goal was to generate an oral DNA vaccine targeting the angiogenic peptide, proadrenomedullin N-terminal 20 peptide (PAMP). Methods: An expression plasmid (PcPAMP) was generated by fusing the tetanus toxin epitopes P2 and P30 to the mouse PAMP sequence to counteract self-tolerance, and the empty plasmid was used as a negative control (PcNeg). The plasmids were introduced into Salmonella typhimurium bacteria that were then transformed into bacterial ghosts. C57BL/6J mice were orally immunized with the ghosts five times at 2-week intervals. Then, B16-F10 melanoma cells were injected into the tail vein to generate lung metastases. Furthermore, naïve CD4⁺ T cells were exposed to PAMP, and their secretome was analyzed by proximity extension assays. Results: Significant levels of anti-PAMP immunoglobulins were detected in the blood of PcPAMP-vaccinated mice and their levels of spleen CD8⁺ T cells were significantly higher than in those treated with PcNeg, indicating that self-tolerance was effectively broken. Although the number and size of lung metastases was similar between both experimental groups, there was a significant reduction in intratumoral angiogenesis and in cancer cell proliferation index in the PcPAMP group. Furthermore, these animals showed an intense infiltration of lymphocytes, including regulatory T cells, and M2-like macrophages into the metastases, that was not evident in the PcNeg group. In addition, PAMP induced upregulation of IL1β, IL6, IL7, IL12, IL27, TNFα, and FGF21, and downregulation of IL16 in naïve CD4⁺ T cells. Conclusions: Although the vaccine was not effective in reducing tumor growth, new proliferative and immune functions have been described for PAMP. These new functions include induction of melanoma proliferation and modulation of lymphocyte and macrophage tumor infiltration dynamics. Full article

Background/Objectives: Breast cancer remains a leading cause of cancer-related mortality among women worldwide, necessitating novel therapeutic strategies. This study aimed to investigate the synergistic antitumor effects of caerin peptides (F1/F3) combined with dendritic cell (DC) vaccines in a 4T-1 murine breast cancer model, providing new insights for breast cancer immunotherapy. Methods: In vitro experiments evaluated the effects of F1/F3 on 4T-1 cell proliferation and apoptosis. A 4T-1 breast cancer mouse model was established, and treatments included F1/F3 alone, DC vaccines (DCV₁: loaded with whole tumor antigens; DCV₂: loaded with F1/F3-induced apoptotic antigens), or combination therapy. Flow cytometry analyzed immune cell subsets in the tumor microenvironment and lymph nodes, while ELISA measured cytokine levels. Results: F1/F3 significantly inhibited 4T-1 cell proliferation and induced apoptosis while suppressing tumor growth and lung metastasis in vivo. Flow cytometry revealed increased infiltration of CD4⁺ T cells and cDC₁ in tumors, along with reduced PD-L1 expression. DCV₂ exhibited stronger T-cell proliferation induction and lower IL-10 secretion in vitro. Combination therapy with DCV₂ and F1/F3 demonstrated superior tumor suppression compared to monotherapy. Conclusions: F1/F3 enhances antitumor immunity by modulating the tumor microenvironment, and its combination with DCV₂ yields synergistic effects. This study provides experimental evidence for combination immunotherapy in breast cancer, with potential for further optimization of DC vaccine design to improve efficacy. Full article

The genus Pistacia from the Anacardiaceae family contains species of wild flowering plants. The only species that produces edible nuts large enough for commercial sale is P. vera L. (pistachio). Other species, such as P. terebinthus L., P. atlantica L., and P. khinjuk, are used as pistachio rootstocks. Pistacia species include phenolic compounds, such as flavonoids, essential oils, and tannins, which are responsible for a number of pharmacological properties. The species most commonly investigated for their anticancer and/or cytotoxic activities against cancer cells in experimental studies include P. lentiscus, P. atlantica subspecies, and P. chinensis subsp. integerrima. However, no review exists that evaluates the phenolic compounds of three other Pistacia species (P. vera L., P. terebinthus L., and P. khinjuk) and their anticancer and cytotoxic effects. Thus, this review aims to thoroughly assess the phenolic compounds that were isolated from these species and investigate any potential anticancer or cytotoxic effects on cancer cells. The findings show that pistacia species and their isolated phenolic compounds (phenolic acids, flavonoids, and essential oils) from different plant parts have anticancer activity against lung, cervical, prostate, gastric, colon, liver, renal, skin, and breast cancer cells. Additionally, certain phenolic compounds from pistacia species have cytotoxic activity; however, the degree of toxicity may vary based on the dosage and duration of use. Further experiments are required to fully understand the possible mechanisms underlying the anticancer and cytotoxic effects of pistacia species and their phenolic compounds on cancer cells. Full article

Lung cancer is the most diagnosed cancer and the primary cause of cancer-related mortality worldwide, with lung adenocarcinoma (LUAD) becoming the prevalent histological subtype. Rac GTPase activating protein 1 (RacGAP1) has been found to be upregulated in several cancers, where it acts as an oncogene; nevertheless, its role in lung adenocarcinoma is largely unknown. The present study investigated the clinical relevance, the oncogenic function and the underlying molecular mechanisms of RacGAP1 in LUAD. Analyses of five patient cohorts’ datasets revealed that RacGAP1 was upregulated in adenocarcinoma tissues compared to normal lung tissues, and its overexpression was associated with unfavorable prognostic factors and poor survival; intriguingly, RacGAP1 expression was related to tobacco smoke, a well-known risk factor for LUAD. Then, experimental analyses demonstrated that RacGAP1 knockdown inhibited cell proliferation, migration and invasion, thus highlighting its role in promoting LUAD. Finally, the finding of significant correlations between RacGAP1 and Wnt-altered status or β-catenin in patients led to experiments demonstrating that silencing of RacGAP1 reduced β-catenin transcriptional activity, thereby downregulating the expression of Wnt-related genes, i.e., LGR5, Wnt2B and Wnt5A. Overall, our findings indicate that RacGAP1 plays an oncogenic role in adenocarcinoma, contributing to the abnormal activation of the Wnt/β-catenin signaling pathway. These findings may pave the way for innovative therapeutic strategies and the development of advanced diagnostic panels. Full article

Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy characterized by rapid progression, high metastatic potential, and limited therapeutic options. Lysine-specific demethylase 1 (LSD1) has been identified as a promising epigenetic target in SCLC. RG6016 (ORY-1001) is a selective LSD1 inhibitor currently under clinical investigation for its antitumor activity. In this study, publicly available RNA-Seq datasets from SCLC patient-derived xenograft (PDX) models treated with RG6016 were reanalyzed using bioinformatic approaches. Differential gene expression analysis was conducted to identify genes responsive to LSD1 inhibition. Candidate genes showing significant downregulation were further evaluated by molecular docking to assess their potential interaction with RG6016. The analysis identified a set of differentially expressed genes following RG6016 treatment, including notable downregulation of MYC, UCHL1, and TSPAN8. In silico molecular docking revealed favorable docking poses between RG6016 and the proteins encoded by these genes, suggesting potential direct or indirect targeting. These findings support a broader mechanism of action for RG6016 beyond its known interaction with LSD1. This study demonstrates that RG6016 may exert its antitumor effects through the modulation of additional molecular targets such as MYC, UCHL1, and TSPAN8 in SCLC. The combined bioinformatic and molecular docking analyses provide new insights into the potential multi-target profile of RG6016 and indicate the need for further experimental validation. Full article

Programmed death-ligand 1 (PD-L1) is a crucial immune checkpoint protein that tumors often exploit to evade immune surveillance. This study systematically screened a library of 1031 FDA-approved drugs using a high-throughput molecular dynamics approach to identify potential inhibitors targeting PD-L1. From this screening, five promising compounds—vorapaxar, delafloxacin, tenofovir disoproxil, pivmecillinam, and fursultiamine—showed significant binding affinities to PD-L1 and demonstrated cytotoxic activity against A549 lung tumor cells. These candidates were further evaluated through extended molecular dynamics simulations lasting up to 150 ns to assess their structural stability, residue fluctuations, and binding free energy. Among the identified compounds, pivmecillinam demonstrated the most favorable results, exhibiting stable binding interactions and a binding free energy of −18.01 kcal/mol, comparable to that of the known PD-L1 inhibitor BMS-1. These findings suggest that pivmecillinam has promising immunomodulatory potential and could serve as a candidate for further development in cancer immunotherapy. Overall, this study underscores the value of integrating high-throughput MD and experimental approaches for drug repositioning to identify novel therapeutic agents. Full article

Air pollution is a significant and widespread issue that presents serious challenges for both human health and the environment because of the presence of a variety of harmful substances in the air, such as tropospheric ozone (O₃), particulate matter (PM₁₀), nitrogen oxides (NOx), sulfur dioxide (SO₂), and carbon monoxide (CO). In this research, the aim is to evaluate the current evidence for the harmful effects of air pollution on human health, focusing on tropospheric ozone, and to highlight the need for further research in the future. The objective is to evaluate recent data on the respiratory and cardiovascular risks caused by air pollution, the potential association between climate change due to air pollution and human disorders, and the subsequent economic burden. A systematic search of the literature is conducted using PubMed, Scopus, Web of Science, and regulatory reports (EPA), focusing on peer-reviewed studies, epidemiological analyses, and clinical and experimental studies. The key findings indicate that O₃ exposure contributes to inflammatory lung injury and to the worsening of preexisting conditions like asthma and COPD, is associated with cancer, and also has numerous negative impacts on neurological, metabolic, and reproductive health, combined with increased healthcare costs. These findings highlight the significance of O₃ pollution as a major public health concern, emphasizing the need for immediate measures to decrease emissions and effective policies to protect the climate and the health of the individuals. Full article

Background:Taraxacum officinale(commonly known as dandelion) is a medicinal and edible plant, with the entire plant being used for therapeutic purposes. Studies have demonstrated that dandelion exhibits inhibitory effects against various types of cancer. However, research on its potential for lung cancer (LC) treatment is limited, and the specific compounds responsible for its anticancer effects, as well as the underlying mechanisms, remain unclear. Methods: This study aimed to elucidate the underlying pharmacological mechanisms by which dandelion exerts therapeutic effects against LC. Initially, active compounds of dandelion and their corresponding targets were retrieved from public databases. Subsequently, network pharmacology approaches were applied to identify LC-associated disease targets. By integrating drug-specific targets and disease-related targets, a comprehensive dandelion–lung cancer interaction network was established. Protein–protein interaction (PPI) analyses and functional enrichment studies were further performed to uncover potential molecular mechanisms. Additionally, molecular docking and molecular dynamics (MD) simulations were conducted to evaluate binding interactions between critical active constituents and core targets. To experimentally validate these findings, in vitro cellular assays combined with scanning electron microscopy (SEM) were employed to investigate the anticancer effects of taraxasterol, a key bioactive sterol compound isolated from dandelion, on LC cells. Results: Our analyses identified 58 active compounds in dandelion linked to 614 potential targets, of which 228 targets were associated with LC. The PPI network highlighted 16 core targets, notably TP53, CASP3 and EGFR. Functional enrichment analysis suggested that dandelion might exert its anticancer effects by modulating the tumor microenvironment through the regulation of these critical targets. Molecular docking results demonstrated stable binding interactions between major active compounds and the identified core targets. Furthermore, the anticancer activity of taraxasterol was experimentally validated through in vitro assays and SEM-based morphological assessments, confirming its inhibitory effects on A549 lung cancer cells. Conclusions: Collectively, our findings reveal a multi-targeted therapeutic mechanism of dandelion against LC and support its potential development as a novel natural candidate for lung cancer treatment. Full article

Cancer is the second leading cause of mortality worldwide. Despite the available treatment options, a majority of cancer patients develop drug resistance, indicating the need for alternative approaches. Repurposed drugs, such as antiglycolytic and anti-microbial agents, have gained substantial attention as potential alternative strategies against different disease pathophysiologies, including lung cancer. To that end, multiple studies have suggested that the antiglycolytic dichloroacetate (DCA) and the antibiotic salinomycin (SAL) possess promising anticarcinogenic activity, attributed to their abilities to target the key metabolic enzymes, ion transport, and oncogenic signaling pathways involved in regulating cancer cell behavior, including cell survival and proliferation. We used the following searches and selection criteria. (1) Biosis and PubMed were used with the search terms dichloroacetate; salinomycin; dichloroacetate as an anticancer agent; salinomycin as an anticancer agent; dichloroacetate side effects; salinomycin side effects; salinomycin combination therapy; dichloroacetate combination therapy; and dichloroacetate or salinomycin in combination with other agents, including chemotherapy and tyrosine kinase inhibitors. (2) The exclusion criteria included not being related to the mechanisms of DCA and SAL or not focusing on their anticancer properties. (3) All the literature was sourced from peer-reviewed journals within a timeframe of 1989 to 2024. Importantly, experimental studies have demonstrated that both DCA and SAL exert promising anticarcinogenic properties, as well as having synergistic effects in combination with other therapeutic agents, against multiple cancer models. The goal of this review is to highlight the mechanistic workings and efficacy of DCA and SAL as monotherapies, and their combination with other therapeutic agents in various cancer models, with a major emphasis on non-small-cell lung cancer (NSCLC) treatment. Full article