Search Results (10,761)

The present research aimed to assess the anti-cancer effects of the polysaccharide fraction (SJP) isolated from Saccharina japonica. The release of immune-activating cytokines, including IL-6, IL-12, and TNF-α, was markedly stimulated by the SJP in a concentration-dependent manner within the range of 1 to 100 µg/mL. Furthermore, the prophylactic intravenous (p.i.v.) and per os (p.p.o.) injection of SJP boosted the cytolytic activity mediated by NK cells and CTLs against tumor cells. In a study involving Colon26-M3.1 carcinoma as a lung cancer model, both p.i.v. and p.p.o. exhibited significant anti-lung-cancer effects. Notably, p.i.v. and p.p.o. administration of SJP at a dose of 50 mg/kg reduced tumor colonies by 84% and 40%, respectively, compared to the control. Moreover, the anti-lung-cancer effects of SJP remained substantial, even when NK cell function was inhibited using anti-asialo-GM1. Fractionation with CaCl₂ suggested that SJP is a mixture of alginate and fucoidan. The fucoidan fraction stimulated the immune response of macrophages more strongly than the alginate fraction. Consequently, this finding suggested that SJP from S. japonica possesses remarkable anti-cancer effects through the activation of various immunocytes. In addition, this finding indicates that the potent biological activity of SJP may be attributed to fucoidan. Full article

The expression level of Programmed Death-Ligand 1 (PD-L1) determined by the immunohistochemical method is currently approved to test the potential efficacy of immune-checkpoint inhibitors and to candidate patients with Non-Small Cell Lung Cancer (NSCLC) for treatment with immunotherapeutic drugs. As part of the CORELAB (New prediCtivebiOmaRkers of activity and Efficacy of immune checkpoint inhibitors in advanced non-small cell Lung cArcinoma) project, aimed at identifying new predictive and prognostic biomarkers in NSCLC patients receiving immunotherapeutic drugs, we investigated the role of circulating tumor DNA (ctDNA) molecular characterization as an additional predictive biomarker. We analyzed plasma ctDNA by targeted Next Generation Sequencing in a subset of 50 patients at different time points. ctDNA content was inversely correlated with the clinical outcome both at a baseline and after 2 months of treatment. OS was significantly higher in patients with ≥50% ctDNA reduction. TP53 and KRAS were the most frequently mutated genes, and patients with KRAS and/or TP53 mutations showed worse outcomes than patients without detectable variants or with mutations in other genes. Fewer common variants were found in BRAF, EGFR, MAP2K1, MET, NRAS, and PIK3CA genes. Our data demonstrated that molecular characterization of ctDNA and also its quantitative evaluation could serve as a dynamic, real-time prognostic, and predictive biomarker, enabling regular molecular monitoring of therapy efficacy in support of other medical examinations. Full article

Background: Although higher-generation TKIs are associated with improved progression-free survival in advanced NSCLC patients with EGFR mutations, the optimal selection of TKI treatment remains uncertain. To address this gap, we developed a web application powered by a reinforcement learning (RL) algorithm to assist in guiding initial TKI treatment decisions. Methods: Clinical and mutational data from advanced NSCLC patients were retrospectively collected from 14 medical centers. Only patients with complete data and sufficient follow-up were included. Multiple supervised machine learning models were tested, with the Extra Trees Classifier (ETC) identified as the most effective for predicting progression-free survival. Feature importance scores were calculated by the ETC, and features were then integrated into a Deep Q-Network (DQN) RL algorithm. The RL model was designed to select optimal TKI generation and a treatment line for each patient and was embedded into an open-source web application for experimental clinical use. Results: In total, 318 cases of EGFR-mutant advanced NSCLC were analyzed, with a median patient age of 63. A total of 52.2% of patients were female, and 83.3% had ECOG scores of 0 or 1. The top three most influential features identified were neutrophil-to-lymphocyte ratio (log-transformed), age (log-transformed), and the treatment line of TKI administration, as tested by the ETC algorithm, with an area under curve (AUC) value of 0.73, whereas the DQN RL algorithm achieved a higher AUC value of 0.80, assigning distinct Q-values across four TKI treatment categories. This supports the decision-making process in the web-based ‘EGFR Mutant NSCLC Treatment Advisory System’, where clinicians can input patient-specific data to receive tailored recommendations. Conclusions: The RL-based web application shows promise in assisting TKI treatment selection for EGFR-mutant advanced NSCLC patients, underscoring the potential for reinforcement learning to enhance decision-making in oncology care. Full article

Background: In the past decade, immunotherapy has become a major choice for the treatment of lung cancer, yet its therapeutic efficacy is still relatively limited due to the various immune escape mechanisms of tumors. Based on this, we introduce Neo-BCV, a novel bacterial composite vaccine designed to enhance immune responses against lung cancer. Methods: We investigated the immune enhancing effect of Neo-BCV through in vivo and in vitro experiments, including flow cytometry, RNA-seq, and Western blot. Results: We have demonstrated that Neo-BCV can promote Dendritic cells (DCs) maturation and induce DCs differentiation into pro-inflammatory subgroups, significantly enhancing cytotoxic T lymphocyte (CTL)-mediated anti-tumor responses. Transcriptome sequencing revealed that Neo-BCV exerts its effects by specifically inhibiting the JAK2-STAT3 signaling pathway, a crucial regulator of cancer progression, metabolism, and inflammation. Moreover, Neo-BCV significantly improved the immune microenvironment in both tumor and spleen tissues without inducing notable toxic effects in major organs. Conclusions: These findings highlight Neo-BCV’s potential as a safe and effective therapeutic strategy, offering a novel avenue for clinical translation in lung cancer immunotherapy. Full article

Background/Objectives: Platycodon grandiflorus (PG) has been widely researched as a conductant drug for the treatment of lung diseases by ancient and modern traditional Chinese medicine (TCM) practitioners. Inspired by the mechanism and our previous finding about fructans and fructooligosaccharides from Platycodon grandiflorus (FFPG), we developed a nano drug delivery system (NDDS) targeting lung cancer. The aim was to improve the efficiency of the liposomal delivery of Paclitaxel (PTX) and enhance the anti-tumor efficacy. Methods: The FFPG-Lip-PTX NDDS was prepared by electrostatic adsorption. Dynamic light scattering, zeta potential, and transmission electron microscopy were used for physical characterization. The release behavior of the NDDS was simulated by dialysis. The uptake of the NDDS was observed by confocal microscopy and flow cytometry. Cytotoxicity, apoptosis, migration, and invasion experiments were used to evaluate the anti-tumor ability of the NDDS in vitro. The penetration and inhibition of tumor proliferation were further analyzed via a 3D tumor sphere model. Finally, in vivo biological distribution and pharmacodynamic experiments verified the targeting and anti-tumor ability of the FFPG-Lip-PTX NDDS. Results: FFPG-Lip-PTX possessed a homogeneous particle size distribution, high encapsulation efficiency, and stability. In vitro experiments confirmed that FFPG promoted the uptake of the NNDS by tumor cells and enhanced cytotoxicity. It also increased the anti-tumor effect by promoting cell apoptosis and inhibiting invasion and metastasis. The same conclusion was obtained in 3D tumor spheres. In vivo experiments exhibited that FFPG-lips-PTX showed more significant lung cancer-targeting activity and anti-tumor effects. Conclusions: In this study, a novel lung-targeted NDDS is proposed to enhance the therapeutic effect of chemotherapy drugs on lung cancer. Full article

Predicting drug–target interactions (DTIs) is a crucial step in the development of new drugs and drug repurposing. In this paper, we propose a novel drug–target prediction model called MCF-DTI. The model utilizes the SMILES representation of drugs and the sequence features of targets, employing a multi-scale convolutional neural network (MSCNN) with parallel shared-weight modules to extract features from the drug side. For the target side, it combines MSCNN with Transformer modules to capture both local and global features effectively. The extracted features are then weighted and fused, enabling comprehensive feature representation to enhance the predictive power of the model. Experimental results on the Davis dataset demonstrate that MCF-DTI achieves an AUC of 0.9746 and an AUPR of 0.9542, outperforming other state-of-the-art models. Our case study demonstrates that our model effectively validated several known drug–target relationships in lung cancer and predicted the therapeutic potential of certain preclinical compounds in treating lung cancer. These findings contribute valuable insights for subsequent drug repurposing efforts and novel drug development. Full article

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. The discovery of specific driver mutations has revolutionized the treatment landscape of oncogene-addicted NSCLC through targeted therapies, significantly improving patient outcomes. However, immune checkpoint inhibitors (ICIs) have demonstrated limited effectiveness in this context. Emerging evidence, though, reveals significant heterogeneity among different driver mutation subgroups, suggesting that certain patient subsets may benefit from ICIs, particularly when combined with other therapeutic modalities. In this review, we comprehensively examine the current evidence on the efficacy of immunotherapy in oncogene-addicted NSCLC. By analyzing recent clinical trials and preclinical studies, along with an overview of mechanisms that may reduce immunotherapy efficacy, we explored potential strategies to address these challenges, to provide insights that could optimize immunotherapy approaches and integrate them effectively into the treatment algorithm for oncogene-addicted NSCLC. Full article

Kirsten Rat Sarcoma viral oncogene homolog (KRAS) is a frequently occurring mutation in non-small-cell lung cancer (NSCLC) and influences cancer treatment and disease progression. In this study, a machine learning (ML) pipeline was applied to radiomic features extracted from public and internal CT images to identify KRAS mutations in NSCLC patients. Both datasets were analyzed using parametric (ttest) and non-parametric statistical tests (Mann–Whitney U test) and dimensionality reduction techniques. Afterwards, the proposed ML pipeline was applied to both datasets using a five-fold cross-validation on the training set (70/30 train/test split) before being validated on the other dataset. The results show that the radiomic features are significantly different (Mann–Whitney U test; p < 0.05) between the two datasets, despite the use of identical feature extraction methods. Model transferability is therefore difficult to achieve, which became evident during external testing (F1 score = 0.41). Oversampling, undersampling, clustering and harmonization techniques were applied to balance and harmonize the datasets, but did not improve the classification of KRAS mutation presence. In general, due to only a single moderate result (highest test F1 score = 0.67), the accuracy of KRAS prediction is not sufficient for clinical application. In future work, the complexity of KRAS mutation might be addressed by taking submutations into consideration. Larger multicentric datasets with balanced tumor stages, including multi-scanner datasets, seem to be necessary for building robust predictive models. Full article

Background/Objectives: A significant breakthrough in non-small-cell lung cancer (NSCLC) treatment has occurred with the introduction of targeted therapies and immunotherapy. However, not all patients treated with these therapies would respond to treatment, and patients who respond to treatment would acquire resistance at some time point. This is why we need new biomarkers that can predict response to therapy. The aim of this study was to investigate whether soluble programmed cell death-ligand 1 (sPD-L1) could be a predictive biomarker in patients with epidermal growth factor receptor (EGFR)-positive NSCLC. Materials and Methods: Blood samples from 35 patients with EGFR-mutated (EGFRmut) adenocarcinoma who achieved disease control with EGFR tyrosine kinase inhibitor (EGFR TKI) therapy were collected for sPD-L1 analysis. We analyzed sPD-L1 concentrations in 30 healthy middle-aged subjects, as a control population, to determine the reference range. Adenocarcinoma patients were divided into two groups, i.e., a group with low sPD-L1 (≤182.5 ng/L) and a group with high sPD-L1 (>182.5 ng/L). Results: We found that progression-free survival (PFS) was 18 months, 95% CI (11.1–24.9), for patients with low sPD-L1 and 25 months, 95% CI (8.3–41.7), for patients with high sPD-L1. There was no statistically significant difference in PFS between the groups (p = 0.100). Overall survival (OS) was 34.4 months, 95% CI (26.6–42.2), for patients with low sPD-L1 and 84.1 months, 95% CI (50.6–117.6), for patients with high sPD-L1; there was also no statistically significant difference between the groups (p = 0.114). Conclusion: In our study, we found that patients with high sPD-L1 had numerically better PFS and OS, but this has no statistical significance. Further studies with a larger number of patients are needed to evaluate the role of sPD-L1 as a predictive biomarker in patients with EGFRmut NSCLC. Full article

Background/Objectives: Improved survival due to advances in medical therapy has resulted in increasing numbers of cancer patients living with bone metastases; however, our understanding of the prognostic implications of bone metastases requires larger population-based studies outlining their incidence and prevalence in different primary cancer types, including those with lower incidence. This study aimed to evaluate the incidence and prevalence of bone metastases in solid organ tumors by analyzing reports of staging CT studies with natural language processing (NLP). Methods: In this retrospective study, 639,470 reports representing 129,326 unique patients were analyzed; 6279 randomly selected reports were manually annotated and labeled for the presence or absence of bone metastases. From these data, a BERT-based NLP model was developed and applied to the patient database. The cumulative incidence at 5 years and prevalence of bone metastases in each cancer type were calculated. Results: The accuracy of the NLP model on a validation set was 97.1%, with a positive predictive value (precision) of 88.0% and a sensitivity (recall) of 86.3%. The 5-year incidence rate of bone metastases was highest in prostate, breast, head and neck, and lung cancer (52%, 41%, 36%, 33%). Incidence was lowest in central nervous system cancer and testicular cancer (8%, 5%). Prevalence was highest in prostate, breast, and lung cancer (32%, 25% and 23%), and lowest in central nervous system cancer and testicular cancer (4%, 4%). Conclusions: NLP was utilized to demonstrate patterns of bone metastases in a broad range of cancer types and is a valuable tool in population-based assessment of bone metastases. Full article

Background: TSPX is an X-linked tumor suppressor that was initially identified in non-small cell lung cancer (NSCLC) cell lines. However, its expression patterns and downstream mechanisms in NSCLC remain unclear. This study aims to investigate the functions of TSPX in NSCLC by identifying its potential downstream targets and their correlation with clinical outcomes. Methods: RNA-seq transcriptome and pathway enrichment analyses were conducted on the TSPX-overexpressing NSCLC cell lines, A549 and SK-MES-1, originating from lung adenocarcinoma and squamous cell carcinoma subtypes, respectively. In addition, comparative analyses were performed using the data from clinical NSCLC specimens (515 lung adenocarcinomas and 502 lung squamous cell carcinomas) in the Cancer Genome Atlas (TCGA) database. Results: TCGA data analysis revealed significant downregulation of TSPX in NSCLC tumors compared to adjacent non-cancerous tissues (Wilcoxon matched pairs signed rank test p < 0.0001). Notably, the TSPX expression levels were inversely correlated with the cancer stage, and higher TSPX levels were associated with better clinical outcomes and improved survival in lung adenocarcinoma, a subtype of NSCLC (median survival extended by 510 days; log-rank test, p = 0.0025). RNA-seq analysis of the TSPX-overexpressing NSCLC cell lines revealed that TSPX regulates various genes involved in the cancer-related signaling pathways and cell viability, consistent with the suppression of cell proliferation in cell culture assays. Notably, various potential downstream targets of TSPX that correlated with patient survival (log-rank test, p = 0.016 to 4.3 × 10⁻¹⁰) were identified, including EGFR pathway-related genes AREG, EREG, FOSL1, and MYC, which were downregulated. Conclusions: Our results suggest that TSPX plays a critical role in suppressing NSCLC progression by downregulating pro-oncogenic genes, particularly those in the EGFR signaling pathway, and upregulating the tumor suppressors, especially in lung adenocarcinoma. These findings suggest that TSPX is a potential biomarker and therapeutic target for NSCLC management. Full article

Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths globally, with a persistently low five-year survival rate of only 14–17%. High rates of metastasis contribute significantly to the poor prognosis of NSCLC, in which inflammation plays an important role by enhancing tumor growth, angiogenesis, and metastasis. Targeting inflammatory pathways within cancer cells may thus represent a promising strategy for inhibiting NSCLC metastasis. This study evaluated the anti-inflammatory and anti-metastatic properties of morin, a bioactive compound derived from a Thai medicinal herb, focusing on its effects on NLRP3 inflammasome-mediated pathways in an in vitro NSCLC model. The A549 and H1299 cell lines were stimulated with lipopolysaccharide (LPS) and adenosine triphosphate (ATP) to activate the NLRP3 pathway. The inhibition effects exhibited by morin in reducing pro-inflammatory secretion in LPS- and ATP-stimulated NSCLC cells were assessed by ELISA, while wound healing and trans-well invasion assays evaluated its impact on cell migration and invasion. RT-qPCR measurement quantified the expression of inflammatory genes, and zymography and Western blotting were used to examine changes in invasive protein levels, epithelial-to-mesenchymal transition (EMT) markers, and underlying molecular mechanisms. Our findings demonstrated the significant ability of morin to decrease the production of IL-1β, IL-18, and IL-6 in a dose-dependent manner (p < 0.05), as well as suppress NSCLC cell migration and invasion. Morin downregulated invasive proteins (MMP-2, MMP-9, u-PAR, u-PA, MT1-MMP) and EMT markers (fibronectin, N-cadherin, vimentin) (p < 0.01) while also reducing the mRNA levels of NLRP3, IL-1β, IL-18, and IL-6. Mechanistic investigations revealed that morin suppressed NLRP3 inflammasome activity and inactivated MAPK pathways. Specifically, it decreased the expression of NLRP3 and ASC proteins and reduced caspase-1 activity, while reducing the phosphorylation of ERK, JNK, and p38 proteins. Collectively, these findings suggest that morin’s inactivation of the NLRP3 inflammasome pathway could offer a novel therapeutic strategy for counteracting pro-tumorigenic inflammation and metastatic progression in NSCLC. Full article

The treatment of Non Small Cell Lung Cancer (NSCLC) has been revolutionised by the introduction of targeted therapies. With the improvement of response and frequently of overall survival, however, a whole new set of adverse events emerged. In fact, due to the peculiar mechanism of action of each one of the tyrosine kinase inhibitors and other targeted therapies, every drug has its own specific safety profile. In addition, this safety profile could not fully emerge from clinical trials data, as patients in clinical practice usually have more comorbidities and frailties. Cardiotoxicity is a well-known and established adverse event of anti-cancer therapies. However, only recently it has become a central topic for targeted therapies in NSCLC, due to the unknown real range and frequency. Management of this toxicity begins with prevention, and must balance the need of continuing an effective anticancer treatment versus low risk of even fatal events and the preservation of long-term quality of life. The aim of this review is to summarise the current knowledge focusing on currently used targeted therapies in NSCLC. Full article

Background/Objectives: Lung cancer is the primary cause of cancer-related deaths. Most patients are typically diagnosed at advanced stages. Low-dose computed tomography (LDCT) has been proven to reduce lung cancer mortality, but screening programs using LDCT are associated with a high number of false positives and unnecessary thoracotomies. It is therefore imperative that a certain diagnosis is refined, especially in cases of solitary pulmonary nodules that are difficult to technically access for an accurate preoperative diagnosis. Extracellular vesicles (EVs) involved in intercellular communication may be an innovative biomarker for diagnosis and therapeutic strategies in lung cancer, regarding their ability to carry tumor-specific cargo. The aim of the LUCEx study is to determine if extracellular vesicle cargoes from both lung tissue and blood could provide complementary information to screen lung cancer patients and enable personalized follow-up after the surgery. Methods: The LUCEx study is a prospective study aiming to recruit 600 patients with lung cancer and 50 control subjects (false positives) undergoing surgery after diagnostic imaging for suspected pulmonary nodules using computed tomography (CT) scans. These patients will undergo curative surgery at the Department of Thoracic Surgery of the Miguel Servet Hospital in Zaragoza, Spain, and will be followed-up for at least 5 years. At baseline, samples from both tumor distal lung tissue and preoperative peripheral blood will be collected and processed to compare the quantity and content of EVs, particularly their micro-RNA (miRNA) cargo. At the third and fifth years of follow-up, CT scans, functional respiratory tests, and blood extractions will be performed. Discussion: Extracellular vesicles and their miRNA have emerged as promising tools for the diagnosis and prognosis of several diseases, including cancer. The LUCEx study, based on an observational clinical cohort, aims to understand the role of these vesicles and their translational potential as complementary tools for imaging diagnosis and prognosis. Full article

We demonstrate that natural killer (NK) cells induce a higher cytotoxicity against lung cancer stem-like cells (hA549) compared to differentiated lung cancer cell lines (H292). The supernatants from split-anergized NK cells (IL-2 and anti-CD16 mAb-treated NK cells) induced differentiation in hA549. Differentiated lung cancer cell line (H292) and NK cells differentiated hA549 expressed reduced NK cell-mediated cytotoxicity but expressed higher sensitivity to chemotherapeutic drugs. This finding validated our previous reports demonstrating that the levels of tumor killing by NK cells and by chemotherapeutic drugs correlate directly and indirectly, respectively, with the stage and levels of tumor differentiation. We also demonstrate the role of IFN-γ and TNF-α in inducing tumor differentiation. NK cells’ supernatants or IFN-γ and TNF-α-induced tumor differentiation was blocked when we used antibodies against IFN-γ and TNF-α. Therefore, IFN-γ and TNF-α released from NK cells play a significant role in differentiating tumors, resulting in increased susceptibility of tumors to chemotherapeutic drugs. We also observed the different effects of MHC-class I antibodies in CSCs vs. differentiated tumors. Treatment with anti-MHC-class I decreased NK cell-mediated cytotoxicity in hA549 tumors, whereas it increased NK cell-mediated cytotoxicity when differentiated tumors were treated with antibodies against MHC-class I. Full article