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Purpose: Liver and lung metastases demonstrate distinct biological, particularly immunological, characteristics. We investigated whether preoperative complete blood count (CBC) parameters, which may reflect the immune system condition, predict early dissemination to the liver and lungs in colorectal cancer (CRC). Methods: In this retrospective single-centre study, we included 268 resected CRC cases with complete 2-year follow-up and analysed preoperative CBC for association with early liver or lung metastasis development. Next, selected CBC and clinicopathological parameters were analysed with uni- and multivariable Cox regression. Independent factors affecting liver or lung metastasis-free survival were incorporated into composite scores, which were further evaluated with receiver operating characteristic (ROC) curves and dichotomised using a modified, specificity-focused, Youden approach to identify particularly high-risk patients. Results: Compared to metastasis-free patients, early liver metastases were related to decreases in red blood cells, haematocrit, lymphocytes and elevated monocyte-to-lymphocyte ratio, while lung metastases to lower eosinophil counts. A composite score of independent factors (erythrocytopenia, lower lymphocyte count and pN) yielded HR of 8.01 (95% CI 3.45–18.57, p < 0.001) for liver-specific metastasis-free survival (MFS). For lung-specific MFS, the combination of eosinopenia, pN and primary tumour location showed HR of 13.69 (95% CI 4.34–43.20, p < 0.001). Conclusion: Early CRC metastases to the liver and lungs are associated with partially divergent clinicopathological and peripheral blood features. We propose simple, clinically implementable scores, based on routinely assessed parameters, to identify patients with an increased risk of early dissemination to the liver or lungs. After validation in independent cohorts, these scores may provide easily available prognostic information. [ABSTRACT FROM AUTHOR]

Although previous studies have shown that preoperative pulmonary rehabilitation training may improve postoperative prognosis in patients with lung cancer, the literature included in the existing meta-analysis is highly heterogeneous and lacks effective subgroup analysis. Therefore, an updated meta-analysis is needed to integrate the latest published randomized controlled clinical trials (RCT). This updated analysis was performed to identify the clinical effects of preoperative pulmonary rehabilitation on physical rehabilitation (lung function, activity endurance, and dyspnea), psychological rehabilitation, quality of life, length of hospital stay, and postoperative pulmonary complications in patients with lung cancer. The PubMed, Embase, Cochrane Library, and Web of Science database were searched since inception up to March 2024. A random-effects model was used to pool data, and sensitivity and subgroup analyses were performed to explore the stability of outcomes and potential sources of heterogeneity. All analyses were conducted via Review Manager 5.4.1 and STATA 15.0. The final analysis included 11 RCTs with 1250 patients. The results of meta-analysis suggest that preoperative pulmonary rehabilitation can significantly improve the quality of life of patients with lung cancer after surgery (SMD: 0.16; 95% CI: 0.01, 0.32; P = 0.04) and significantly reduce the risk of postoperative pulmonary complications (PPCs) (RR: 0.39; 95% CI: 0.25, 0.60; P < 0.0001). The results of subgroup analysis suggested that the effect of combined preoperative and postoperative rehabilitation was significantly better than that of preoperative rehabilitation alone, and the effect of short-term preoperative pulmonary rehabilitation (≤ 3 weeks) was significantly better than that of long-term rehabilitation. Preoperative pulmonary rehabilitation for patients with lung cancer can significantly improve their postoperative quality of life and reduce postoperative complications, but factors such as intervention time and intervention method may affect the rehabilitation effect. [ABSTRACT FROM AUTHOR]

Next-generation sequencing (NGS) offers a promising approach for differentiating multiple primary lung cancers (MPLC) from intrapulmonary metastasis (IPM), though panel selection and clonal interpretation remain challenging. Whole-exome sequencing (WES) data from 80 lung cancer samples were utilized to simulate MPLC and IPM, with various sequenced panels constructed through gene subsampling. Two clonal interpretation approaches primarily applied in clinical practice, MoleA (based on shared mutation comparison) and MoleB (based on probability calculation), were subsequently evaluated. ROC analysis highlighted MoleB's superior performance, especially with the NCCNplus panel (AUC = 0.950 ± 0.002) and pancancer MoleA (AUC = 0.792 ± 0.004). In two independent cohorts (WES cohort, N = 42 and non-WES cohort, N = 94), NGS-based methodologies effectively stratified disease-free survival, with NCCNplus MoleB further predicting prognosis. Phylogenetic analysis further revealed evolutionary distinctions between MPLC and IPM, establishing an optimized NGS-based framework for differentiating multiple lung cancers. [ABSTRACT FROM AUTHOR]

Lung cancer is one of the major causes of cancer morbidity and mortality. Subtyping of non-small cell lung cancer is necessary owing to different treatment options. This study is to evaluate the value of immunohistochemical expression of glypican-1 in the diagnosis of lung squamous cell carcinoma (SCC). This retrospective study included a total of 68 cases, of which 36 were diagnosed as SCC and 32 as adenocarcinoma (ADC). Furthermore, glypican-1 expression was compared with the expressions of p63, thyroid transcription factor-1 (TTF-1), and napsin A. All cases of SCC except one showed positive immunostaining to glypican-1; 35/36 (97.2%) cases, and predominantly scored 3 +. While only 5 cases of ADC showed positive immunostaining to glypican-1, having a score of 1 + or 2 +. The difference between glypican-1 expression of the two tumor types was highly significant (p value < 0.001). The sensitivity, specificity, and overall accuracy of glypican-1 expression for differentiating lung SCC from ADC were 97.2%, 84.4%, and 91.2%, respectively. The sensitivity of glypican-1 is more than p63 in the diagnosis of lung SCC. Glypican-1 can be added as a new diagnostic marker to help in the accurate discrimination between poorly differentiated lung SCC and solid predominant adenocarcinoma cases. [ABSTRACT FROM AUTHOR]

Lung cancer, particularly adenocarcinoma, ranks high in morbidity and mortality rates worldwide, with a relatively low five-year survival rate. To achieve precise prognostic assessment and clinical intervention for patients, thereby enhancing their survival prospects, there is an urgent need for more accurate stratification schemes. Currently, the TNM staging system is predominantly used in clinical practice for prognostic evaluation, but its accuracy is constrained by the reliance on physician experience. Although biomarker discovery based on molecular pathology offers a new perspective for prognostic assessment, its dependence on expensive gene panel testing limits its widespread clinical application. Pathological images contain abundant diagnostic information, providing a new avenue for prognostic evaluation. In this study, we employed advanced Hover-Net technology to accurately quantify the abundance of epithelial cells, lymphocytes, macrophages, and neutrophils from pathological images, and delved into the clinical and biological significance of these cellular abundances. Our research findings reveal that, in contrast to patients classified as N0 stage, those belonging to the N1 stage demonstrated a marked elevation in the infiltration of epithelial cells, lymphocytes, macrophages, and neutrophils. Notably, the infiltration patterns of lymphocytes and neutrophils exhibited an inverse relationship with the activation status of numerous pivotal gene pathways, including the HALLMARK_HEME_METABOLISM pathway. Furthermore, our analysis distinguished FABP7 as a prognostic biomarker, exhibiting pronounced differential expression between patients with high and low levels of neutrophil infiltration, indicate that cellular abundance analysis based on pathological images can provide a more accurate and cost-effective prognostic evaluation, offering new strategies for the clinical management of lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Deep learning (DL) methods have demonstrated remarkable effectiveness in assisting with lung cancer risk prediction tasks using computed tomography (CT) scans. However, the lack of comprehensive comparison and validation of state-of-the-art (SOTA) models in practical settings limits their clinical application. This study aims to review and analyze current SOTA deep learning models for lung cancer risk prediction (malignant-benign classification). To evaluate our model's general performance, we selected 253 out of 467 patients from a subset of the National Lung Screening Trial (NLST) who had CT scans without contrast, which are the most commonly used, and divided them into training and test cohorts. The CT scans were preprocessed into 2D-image and 3D-volume formats according to their nodule annotations. We evaluated ten 3D and eleven 2D SOTA deep learning models, which were pretrained on large-scale general-purpose datasets (Kinetics and ImageNet) and radiological datasets (3DSeg-8, nnUnet and RadImageNet), for their lung cancer risk prediction performance. Our results showed that 3D-based deep learning models generally perform better than 2D models. On the test cohort, the best-performing 3D model achieved an AUROC of 0.86, while the best 2D model reached 0.79. The lowest AUROCs for the 3D and 2D models were 0.70 and 0.62, respectively. Furthermore, pretraining on large-scale radiological image datasets did not show the expected performance advantage over pretraining on general-purpose datasets. Both 2D and 3D deep learning models can handle lung cancer risk prediction tasks effectively, although 3D models generally have superior performance than their 2D competitors. Our findings highlight the importance of carefully selecting pretrained datasets and model architectures for lung cancer risk prediction. Overall, these results have important implications for the development and clinical integration of DL-based tools in lung cancer screening. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer (NSCLC), half of which are lung adenocarcinoma (LUAD), is one of the most widely spread cancers in the world. Telomerase, which maintains telomere length and chromosomal integrity, enables cancer cells to avoid replicative senescence. When telomerase is inhibited, cancer cells' senescence began, preventing them from growing indefinitely. Cellular senescence and telomeres are intrinsically linked. As of yet, still laking a systematic study of the involvement of telomere-senescence related genes in lung adenocarcinoma development. In this study, myeloid cells were identified as the cell type which are most correlated with cellular senescence based on its highest telomere-related gene activity. GO, KEGG, GSEA and GSVA analyses were used to explore the biological function of telomere-senescence related genes in LUAD. The combined analysis of single-cell RNA-sequencing and bulk-RNA sequencing identified a gene signature composed of 14 genes which can accurately predict the prognosis of patients with LUAD. In one training and four validation sets, patients with higher Telomere Related Gene Signature (TRGS) had a worse prognosis than those with lower TRGS. Different TRGS patient groups showed varying degrees of immune cell infiltration, frequency of gene missense mutation, sensitivity to different drugs, and tumor mutation burden (TMB). Collectively, we developed a brand new signature composed of telomere-senescence related genes that can accurately predicts patients' prognosis in LUAD, which provides new insights for future research into the role of cellular senescence in LUAD. [ABSTRACT FROM AUTHOR]

Purpose: Nano-drug delivery systems (NDDS) have become a promising alternative and adjunctive strategy for lung cancer (LC) treatment. However, comprehensive bibliometric analyses examining global research efforts on NDDS in LC are scarce. This study aims to fill this gap by identifying key research trends, emerging hotspots, and collaboration networks within the field of NDDS and LC. Methods: A total of 2452 publications, spanning from 1998 to 2024, were extracted from the Web of Science Core Collection. The data were analyzed using tools such as VOSviewer, CiteSpace, and the R package 'bibliometrix'. Results: The analysis covered contributions from 12,539 researchers affiliated with 2689 institutions across 55 countries, with their work published in 551 different journals. Research output has increased steadily, with China and the United States leading in both publication volume and impact. Major contributors include the Chinese Academy of Sciences and Shanghai Jiao Tong University. The International Journal of Nanomedicine published the most articles, while Journal of Controlled Release ranked highest in co-citations. Kamal Dua authored the most papers, and Maeda, H. was the most frequently co-cited author. Key research areas encompass "active targeting", "drug delivery optimization", "overcoming drug resistance", "nanocarriers", and "pulmonary drug delivery". Emerging hotspots include "epithelial mesenchymal transition", "mucus penetration", "lipid nanoparticles", "hydrogels", and "immune checkpoint inhibitors". Conclusion: This bibliometric analysis, the first comprehensive study on NDDS in LC, identifies China and the United States as leading contributors in publication volume and impact. Key research areas include "active targeting" and "drug delivery optimization", with emerging hotspots such as "lipid nanoparticles" and "immune checkpoint inhibitors". These findings provide essential insights to guide future research and optimize treatment strategies. [ABSTRACT FROM AUTHOR]

Lung cancer (LC) is a crucial rapidly developing disease. In Egypt, it is one of the five most frequent cancers. Little is known about the impact of deleted mismatch repair genes and its correlation to clinicopathological characteristics. This study evaluates immunohistochemical expression of the mismatch repair genes (PMS2), (MSH2), (MLH1) & (MSH6) & its correlation with clinicopathologic parameters & prognosis of LC. Age was higher with lost MLH1 & PMS2 but HTN was higher with lost four markers. Smoking was associated with expression of MLH1 & PMS2. A progressive course was associated with lost MSH2 & MSH6. Suprarenal metastasis was associated with lost all markers but bone metastasis was associated with lost MSH2 & MSH6. All the markers were significantly correlated with each other, with perfect correlations between MSH6 & MSH2 and between MLH & PMS2. Median overall survival among cases with lost markers was significantly lower than patients with preserved markers. We recommend evaluation of the four proteins as a biomarker that could guide LC therapy. In-depth biological research is imperative to elucidate the precise roles and mechanisms of these markers. This will advance management strategies and even guide immune checkpoint inhibitor therapy for LC. [ABSTRACT FROM AUTHOR]

Tumor genomic profiling is often limited to one or two timepoints due to the invasiveness of tissue biopsies, but longitudinal profiling may provide deeper clinical insights. Using ctDNA data from IMpower150 study, we examined genetic changes in metastatic non-squamous NSCLC post-first-line immunotherapy. Mutations were most frequently detected in TP53, KRAS, SPTA1, FAT3, and LRP1B at baseline and during treatment. Mutation levels rose prior to radiographic progression in most progressing patients, with specific mutations (SPTA1, STK11, KEAP1, SMARCA4, TBX3, CDH2, and MLL3) significantly enriched in those with progression or nondurable response. However, ctDNA's role in detecting hyperprogression and pseudoprogression remains uncertain. STK11, SMARCA4, KRAS, SLT2, and KEAP1 mutations showed the strongest correlation with poorer overall survival, while SMARCA4, STK11, SPTA1, TBX3, and KEAP1 mutations correlated with shorter progression-free survival. Overall, longitudinal liquid biopsy profiling provided valuable insights into lung cancer biology post-immunotherapy, potentially guiding personalized therapies and future drug development. [ABSTRACT FROM AUTHOR]

The number of lung cancer survivors is rapidly growing in China, and their experiences are becoming increasingly complex. However, there is limited research on the experiences of Chinese lung cancer survivors. This study aimed to examine the post-diagnosis experiences of these survivors, using their blog entries as the primary data source. Qualitative content analysis was adopted to investigate the post-diagnosis experiences of Chinese lung cancer survivors. Data were collected from the public media site Xiaohongshu and involved a total of 417 blog entries posted by 15 lung cancer survivors. Each sentence in the eligible blog entries was determined as a unit of analysis and divided into meaning units, which were then coded and analyzed iteratively to generate subthemes and themes. The content analysis yielded five themes: (1) reasons for reluctance to accept their diagnosis; (2) treatment and its side effects; (3) emotional responses to their illness; (4) emotional support; (5) lung cancer disease management. This study has implications for healthcare professionals, highlighting the need for patient-centered care and emotional support for lung cancer survivors. Additionally, it also provides qualitative evidence that blogs are an accessible and valuable tool for studying the perspectives and experiences of lung cancer survivors. [ABSTRACT FROM AUTHOR]

Introduction: Silver nanoparticles (AgNPs) derived from natural sources have garnered significant attention due to their unique properties and eco-friendly production methods. With lung cancer remaining a major global health issue, there is a continuous need for novel and effective therapeutic approaches beyond conventional treatments such as chemotherapy, immunotherapy, and targeted therapies. Objective: This study aims to synthesize AgNPs using plant extracts from Gymnema sylvestre, Moringa oleifera, and Azadirachta indica and to evaluate their anticancer activity, particularly their effects on gene expression in A549 lung cancer cells. Methods: AgNPs were synthesized using green chemistry techniques and characterized by X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR). Gene expression studies were performed to assess the impact of AgNPs on cancer-related genes such as VEGF and CYCLIN-D1. Cytotoxicity assays were conducted on A549 cells to determine the anticancer potential of the synthesized AgNPs compared to plant extracts alone. Results: XRD confirmed the formation of crystalline AgNPs, while FTIR indicated the presence of bioactive compounds interacting with the nanoparticles. Gene expression analysis revealed significant downregulation of VEGF and CYCLIN-D1, suggesting inhibitory effects on angiogenesis and cell cycle progression. The synthesized AgNPs exhibited potent cytotoxic activity against A549 cells, with enhanced efficacy compared to the leaf extracts alone. Conclusion: The study highlights the potential of AgNPs synthesized from medicinal plant extracts as promising candidates for lung cancer therapy. Their environmentally sustainable production, combined with their ability to target key cancer pathways, positions them as innovative and affordable therapeutic agents in the field of nanomedicine. [ABSTRACT FROM AUTHOR]

The prominence of circular RNAs (circRNAs) has surged in cancer research due to their distinctive properties and impact on cancer development. This review delves into the role of circRNAs in four key cancer types: colorectal cancer (CRC), gastric cancer (GC), liver cancer (HCC), and lung cancer (LUAD). The focus lies on their potential as cancer biomarkers and drug targets. Our study analyses the reported circRNAs in the mentioned malignancies, examining their nature, functions, targets, origins, and contributions as tumor enhancers or suppressors. The approach involved assessing full-text reports on PMC, utilizing keywords such as "CircRNA" and "Cancer types," coupled with bioinformatics, experimental assays, or clinical investigations. Exclusions encompassed non-English publications, conference abstracts, letters, and expert opinions. The findings unveil 577 identified circRNAs across these cancer types: 124 in CRC, 177 in GC, 93 in HCC, and 183 in LUAD. Mechanistic insights into how circRNAs modulate gene expression in cancer are explored, particularly their interactions with microRNAs and RNA-binding proteins. Dysregulation of circRNAs across various cancers and their potential as diagnostic and prognostic indicators are synthesized. The exploration extends to the potential of targeting circRNAs as a novel cancer therapy strategy, either through inhibiting oncogenic circRNAs or reinstating tumor-suppressive ones. This article discusses the challenges and prospects in harnessing circRNAs for cancer diagnostics and therapies. These comprehensive analyses hold promise for advancing cancer research and fostering the development of innovative therapies and diagnostics. [ABSTRACT FROM AUTHOR]

DNA damage is one of the primary mechanisms underlying cancer and other chronic degenerative diseases. Early evaluation of this damage in the affected cells and tissues is crucial for understanding pathogenesis and implementing effective prevention strategies. However, isolating target cells from affected organs, such as the lungs, can be challenging. Therefore, an alternative approach is to evaluate genotoxic damage in surrogate cells. Pulmonary alveolar macrophages are ideally suited for this purpose because they are in close contact with the target cells of the bronchial and alveolar epithelium, share the exact mechanisms and levels of exposure, and are easily recoverable in large numbers. This review comprehensively lists all studies using alveolar macrophages as surrogate cells to show genotoxic lung damage in humans or laboratory animals. These investigations provide fundamental information on the mechanisms of DNA damage in the lung and allow for better assessment and management of risk following exposure to inhalable genotoxic agents. Furthermore, they may be a valuable tool in cancer chemoprevention, helping the right choice of agents for clinical trials. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to assess the efficiency of artificial intelligence (AI) in the detection of visceral pleural invasion (VPI) of lung cancer using high-resolution computed tomography (HRCT) images, which is challenging for experts because of its significance in T-classification and lymph node metastasis prediction. Methods: This retrospective analysis was conducted on preoperative HRCT images of 472 patients with stage I non-small cell lung cancer (NSCLC), focusing on lesions adjacent to the pleura to predict VPI. YOLOv4.0 was utilized for tumor localization, and EfficientNetv2 was applied for VPI prediction with HRCT images meticulously annotated for AI model training and validation. Results: Of the 472 lung cancer cases (500 CT images) studied, the AI algorithm successfully identified tumors, with YOLOv4.0 accurately localizing tumors in 98% of the test images. In the EfficientNet v2-M analysis, the receiver operating characteristic curve exhibited an area under the curve of 0.78. It demonstrated powerful diagnostic performance with a sensitivity, specificity, and precision of 76.4% in VPI prediction. Conclusion: AI is a promising tool for improving the diagnostic accuracy of VPI for NSCLC. Furthermore, incorporating AI into the diagnostic workflow is advocated because of its potential to improve the accuracy of preoperative diagnosis and patient outcomes in NSCLC. [ABSTRACT FROM AUTHOR]

Elevated cancer incidence has been reported among World Trade Center (WTC)-exposed responders, with some incidence rate ratios (IRRs) varying over time. This study describes the influence that different reference populations have on relative cancer incidence and temporal trends. Participants from the WTC Combined Rescue/Recovery Cohort (n = 65,691) were observed between 1/1/2002 and 12/31/2015 using data obtained from 13 state cancer registries. Poisson regression was used to estimate IRRs controlling for age, race/ethnicity, and calendar year. IRRs and change-points were estimated using three reference populations (New York City (NYC), New York State (NYS), and a US population). IRRs for each cancer site varied in magnitude. Prostate and thyroid cancer IRRs were significantly greater in WTC-exposed responders, while colon and lung cancer IRRs were significantly lower compared with NYC, NYS, and US population reference groups. The range of IRRs varied by reference population. Mixed findings were observed for other cancers, as results were dependent on the reference group used. A significant change-point was found only for prostate cancer, and only when compared to a US population. Our findings suggest that reference population selection will influence the IRR, timing, and statistical significance of change-point estimation, varying with follow-up length. [ABSTRACT FROM AUTHOR]

Background: Cluster of differentiation 155 (CD155) is expressed in many tumor types. CD155 is involved in the immune avoidance of tumor cells and contributes to tumor development and progression. Therefore, CD155 is a novel target for cancer immunotherapy. The clinical significance of CD155 expression in lung squamous cell carcinoma (LUSC) has not been fully elucidated. Materials and methods: We performed a retrospective analysis of 264 patients with surgically resected LUSC. Immunohistochemistry was used to evaluate CD155 expression. The association of CD155 expression with clinicopathological features and clinical outcomes was assessed. We also analyzed the relationship between CD155 expression and programmed cell death-ligand 1 (PD-L1) expression and tumor-infiltrating lymphocytes. Results: Among the 264 patients, 137 patients (51.9%) were classified in the high CD155 expression group. High CD155 expression was significantly associated with pleural invasion, vascular invasion, PD-L1 positivity, and high CD3, CD4, and CD8 expressions. In multivariate analysis, the presence of pleural invasion and PD-L1 positivity were independent predictors of high CD155 expression. Kaplan–Meier curve analysis showed that high CD155 expression was significantly associated with shorter disease-free survival and overall survival. In multivariate analysis, high CD155 expression was an independent poor prognostic factor for overall survival, but not for disease-free survival. Subgroup analyses revealed that the prognostic effect of CD155 expression was observed in the PD-L1 positive group but not the PD-L1 negative group. Conclusion: Our analysis revealed that high CD155 expression significantly predicted poor prognosis in patients with surgically resected LUSC, especially in patients with PD-L1-positive tumors. [ABSTRACT FROM AUTHOR]

Purpose: Early and accurate identification of the risk of psychological distress allows for timely intervention and improved prognosis. Current methods for predicting psychological distress among lung cancer patients using readily available data are limited. This study aimed to develop a robust machine learning (ML) model for determining the risk of psychological distress among lung cancer patients. Methods: A cross-sectional study was designed to collect data from 342 lung cancer patients. Least Absolute Shrinkage and Selection Operator (LASSO) was used for feature selection. Model training and validation were conducted with bootstrap resampling method. Fivefold cross-validation evaluated and optimized the model with parameter tuning. Feature importance was assessed using SHapley additive exPlanations (SHAP) method. Results: The model identified seven independent risk factors of psychological distress: residence (β = 0.141), diagnosis duration (β = 0.055), TNM stage (β = 0.098), pain severity (β = 0.067), perceived stigma (β = 0.052), illness perception (β = 0.100), and coping style (β = 0.097). Among the eight ML algorithms evaluated, the extreme gradient boosting (XGBoost) algorithm demonstrated the highest performance with AUROC values of 0.988, 0.945, and 0.922 for the training, validation, and test sets, respectively. The model’s results were further explained using SHAP, which revealed the importance and contribution of each risk factor to the overall distress risk. A web-based tool was developed based on this model to facilitate clinical use. Conclusion: The XGBoost classifier demonstrated exceptional performance, and clinical implementation of the web-based risk calculator can serve as an easy-to-use tool for health practitioners to formulate early prevention and intervention strategies. [ABSTRACT FROM AUTHOR]

Purpose: Lung cancer remains one of the most diagnosed cancers in Canada and continues to be the leading cause of cancer deaths in Canada, responsible for 25% of all cancer deaths. Prior studies consistently report poor experiences of people with lung cancers. The study purpose was to explore the reasons for consistently poorer reported experience of people with lung cancer compared to people with gastrointestinal cancers, who previously have reported positive cancer care experiences within the same context, and to better understand key differences that influence patient experience. Methods: This qualitative study used semi-structured interviews of people living with lung cancer (LC) and gastrointestinal cancers (GIC) undergoing radiotherapy at a tertiary cancer centre. Thematic content analysis was conducted to analyse interview transcripts. A person-centred care framework was used to guide the development of the interview guide and data analysis. Results: We interviewed 16 participants (10 LC and 6 GIC). Participants with LC reported poor experience leading to and at the time of their cancer diagnosis, including delays in their diagnosis and anxiety related to their diagnosis. Most participants in both groups reported severe symptoms prior to their radiotherapy. However, the symptoms of people living with LC further worsened during the radiation therapy with the addition of treatment side effects, while the symptoms of people living with GIC were better controlled during treatment. Participants living with LC noted poor communication, gaps in coordination and uncertainty. They acknowledged awareness of support services and other resources, but they reported no interest in accessing them. Conclusion: This study identified gaps in patient experience of people living with LC compared to GIC and proposed ideas for quality improvement projects, including expediting the diagnosis process, enhancing communication with patients around their lung cancer diagnosis, improved symptom management, and timing of supportive care services. [ABSTRACT FROM AUTHOR]

Vaccination has been considered the most crucial defence against viral infections, including SARS-CoV-2. Numerous reports have demonstrated the effectiveness of the above vaccines in oncological patients. It has also been proven that, apart from vaccinations and oncological therapy, the course of the cancer process itself influences the magnitude of the humoral response, especially in people after infection with SARS-CoV-2. The phenomenon we observe seems to confirm the presence of a "natural" defence potential in a cancer patient's body, in this case, directed against infection with a viral pathogen. A "stronger" antiviral response also explains the asymptomatic course of SARS-CoV-2 infection in some of the above patients. To what extent the SARS-CoV-2 infection weakened the "natural" potential of the anticancer response in these patients remains an open question. Objective: This study aimed to answer the question about the impact of the cancer process on the humoral response in oncological patients vaccinated against SARS-CoV-2 infection and in patients after COVID-19. Material and methods: One thousand six hundred and sixty-eight people were observed. Over 2 years, 5,082 SARS-CoV-2 IgG and IgM antibody samples were determined. The concentration of antibodies was assessed in groups of oncological patients: those undergoing anticancer therapy after contracting COVID-19 and those after vaccination against the SARS-CoV-2 infection. Results: The obtained results indicate a naturally more significant humoral response in oncological patients who have not been vaccinated and have not undergone anticancer therapy, such as radiotherapy, chemotherapy, or surgical intervention. The above observation applies to patients with breast, lung, colon, kidney, and testicular cancer, although the response varies significantly depending on the type of cancer. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the role of POU Class 4 Homeobox 1 (POU4F1) in regulating gemcitabine (GEM) resistance in lung cancer cells. The mRNA and protein expressions were assessed using RT-qPCR, western blot, immunofluorescence, and immunohistochemistry. Cell viability and proliferation were assessed by CCK-8 assay and EdU assay. TUNEL staining and flow cytometry were employed to detect cell apoptosis. The m6A modification of TWF1 was detected using MeRIP assay. The interactions between molecules were validated using dual luciferase reporter gene, ChIP, and RIP assays. POU4F1 knockdown inhibited GEM resistance and autophagy in lung cancer cells. Mechanistically, POU4F1 transcriptionally activated methyltransferase-like protein 3 (METTL3) in GEM-resistant cells by binding to the METTL3 promoter. METTL3 promoted the N6-methyladenosine (m6A) modification and expression level of twinfilin-1 (TWF1). Overexpression of METTL3 and TWF1 weakened the effects of POU4F1 knockdown on GEM resistance and autophagy. Moreover, knockdown POU4F1 also enhanced GEM anti-tumor sensitivity in vivo. In conclusion, POU4F1 upregulation promoted GEM resistance in lung cancer cells by promoting autophagy through increasing METTL3-mediated TWF1 m6A modification. [ABSTRACT FROM AUTHOR]

Background: This qualitative study aims to deeply understand the emotional experiences of mutuality relationships between lung cancer patients undergoing chemotherapy and their caregivers, providing insights for developing cancer-related mutuality interventions. Methods: Using a qualitative research method with semi-structured interviews, 15 pairs of patients and their caregivers from the Department of Respiratory Medicine at the Affiliated People’s Hospital of Xuzhou Medical University were selected as subjects. Data were qualitatively and inductively analyzed using Braun and Clarke’s thematic analysis method. Results: Five themes and fourteen sub-themes were extracted from the experiences and interactions between patients and caregivers: reciprocity and mutual support (support provided by patients to caregivers, support provided by caregivers to patients), challenges (lack of communication, difficulty in adaptation, role changes, economic burdens), change and adaptation (living with the disease, social support), negative outcomes (increased burden on caregivers, disruption of social activities and family relationships), and intervention needs (need for disease knowledge, humanistic care, communication skills). Conclusion: The findings of this study provide healthcare professionals with information on the mutual support and challenges faced by chemotherapy patients and their caregivers in coping with cancer. This information aims to facilitate culturally-based psychological interventions, enhance mutuality, improve quality of life, and promote the entire family’s adaptation to the disease. [ABSTRACT FROM AUTHOR]

Objectives: To estimate the pooled prevalence and progression rate of ILAs and identify the risk factors for radiological progression. Materials and methods: An EMBASE and PubMed search was undertaken, identifying all studies meeting the inclusion criteria performed before May 10, 2023. Random effect models were used to estimate pooled prevalence, ILA progression rates, and odds ratio for radiological progression based on radiological subtype. Subgroup analyses were performed to compare the general and high-risk populations for lung cancer. The quality of the included studies was evaluated using the risk of bias assessment tool for non-randomized studies. Results: We analyzed 19 studies (241,541 patients) and 10 studies (1317 patients) for the pooled prevalence and progression rate of ILA, respectively. The pooled ILA prevalence was 9.7% (95% CI, 6.1–13.9%). The pooled prevalence was 6.8% (95% CI, 3.1–11.6%) and 7.1% (95% CI, 2.2–14.4%) in the general (six studies) and high-risk population for lung cancer (six studies), respectively. The pooled progression rate was 47.1% (95% CI, 29.1–65.5%). The pooled progression rate was 64.2% (95% CI, 45.0–81.2%, five studies) and 31.0% (95% CI, 8.2–60.5%, five studies) for longer (≥ 4.5 years) and shorter follow-up periods (< 4.5 years), respectively (p = 0.009). Fibrotic ILAs were significantly associated with a higher progression probability (combined OR, 5.55; 95% CI, 1.95–15.82). Conclusions: The prevalence of ILAs was approximately 9.7%. Approximately half of the patients exhibited radiological progression, with the rate increasing over a longer follow-up period. Fibrotic ILA was a significant risk factor for radiological progression. Clinical relevance statement: The prevalence of interstitial lung abnormalities (ILAs) is approximately 9.7%, with about half exhibiting progression; a longer follow-up duration and fibrotic ILAs are associated with a higher progression rate. Key Points: ILAs are increasingly recognized as important, but few population data are available. ILAs exhibited a pooled prevalence of 9.7% with a progression rate of 47.1%. Fibrotic ILAs were associated with increased progression likelihood. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer-related death. The use of computational methods to quantify changes that are not perceptible to the human eye is increasing in digital pathology imaging and has quickly improved detection rates at a low cost. Therefore, the present study aims to use complex computational shape markers as tools for automated analysis of the spatial distribution of cells in microscopy images of squamous cell lung carcinoma (SqCC). Photomicrographs from pathology glass slides in the LC25000 dataset were used in this study. Compared with those of the control, the fractal dimension (28%) and lacunarity (41%) of the cell nuclei changed in SqCC. The multifractal analysis revealed a significant difference in parameters Dq, α, and f(α) for all values of q (−10 to + 10), with a greater increase for more positive q values. The values at q + 10 increased by 34% for Dq, 36% for α, and 53% for f(α) in the SqCC images. The circularity, area, and perimeter also changed in the SqCC images. However, the parameters of aspect ratio, roundness, and solidity did not significantly differ between SqCC and benign tissue. The complex shape markers with the greatest changes in this study were the f(α) values for multifractality (53%) and lacunarity (41%). In conclusion, automated quantification of the spatial distribution of cell nuclei can be a fast, low-cost tool for evaluating the microscopic characteristics of SqCC; therefore, complex shape markers could be useful tools for software and artificial intelligence to detect lung carcinoma. [ABSTRACT FROM AUTHOR]

We investigated the combined effects of ataxia telangiectasia and Rad3-related (ATR) inhibition, ablative radiotherapy, and immune checkpoint inhibitor (ICI) therapy against lung cancer. ATR inhibitor was administered combined with ablative radiotherapy to assess its radiosensitizing effect on lung cancer cells. Treatment response and survival were evaluated in vivo using A549 xenograft flank tumor and synchronous LLC lung and flank tumor mouse models. Mice received ablative radiotherapy (12 Gy/d for 2 d), ATR inhibitor, and ICI. The tumor microenvironment was assessed in irradiated flank and non-irradiated lung tumors. Programmed death-ligand 1 expression was upregulated after irradiation. ATR inhibition attenuated this upregulation. ATR inhibitor pretreatment decreased cell survival after irradiation by inhibiting DNA double-strand break repair, inducing mitotic cell death, and altering cell cycle progression. ATR inhibition enhanced radiation-induced damage-associated molecular patterns determined by high mobility group box 1 quantification and activated the cyclic GMP-AMP synthase-stimulator of interferon genes pathway. Combined ATR inhibition and ablative radiotherapy inhibited tumor growth and improved survival in mice. Adding ICI therapy further enhanced local antitumor effects, reducing the metastatic lung tumor burden and remodeling the tumor microenvironment through immunogenic cell death induction and enhanced immune cell infiltration. Triple therapy increased immune cell infiltration in distant non-irradiated lung tumors and stimulated the generation of protective T-cell immunity in splenocytes. Safety analysis showed minimal toxicity. ATR inhibition enhanced the efficacy of ablative radiotherapy and immunotherapy in lung cancer. These findings underscore the importance of combination therapies for enhancing systemic antitumor immune responses and outcomes. [ABSTRACT FROM AUTHOR]

Objectives: The impact of cGAS/STING tumor expression on PD-1/L1 inhibitor efficacy and the tumor microenvironment remain to be elucidated. Methods: In a post-hoc analysis of a prospective biomarker study with 106 advanced NSCLC patients treated with PD-1/L1 inhibitors from December 2015 to September 2018, tumor tissue before treatment from 68 patients was analyzed. cGAS and STING expression were measured using immunohistochemical staining and H-scores. Additionally, 40 serum proteins were quantified before and 4–6 weeks after treatment initiation. Results: Median cGAS and STING H-scores were 220 (range, 5–300) and 190 (range, 0–300), respectively. There were no differences in cGAS or STING H-scores between the high (tumor proportion score [TPS] ≥ 50) and low (TPS < 50) PD-L1groups (p = 0.990 and 0.283, respectively). Unexpectedly, patients with high cGAS (H-score ≥ 220) demonstrated significantly shorter progression-free survival (PFS) of PD-1/L1 inhibitors when the PD-L1 TPS was high (median PFS: 143 days vs. not reached; p = 0.028); PFS at 18 months was 7% and 53% in the high and low cGAS groups, respectively while STING expression did not impact PFS. In serum protein analyses, high cGAS H-score was associated with significantly higher TGF-β1 and TGF-β2 before PD-1/L1 inhibition (47.5 vs. 22.3 ng/l, p = 0.023; 2118 vs. 882 pg/ml, p = 0.037); additionally, the cGAS H-score significantly correlated with TGF-β1 (r = 0.451, p = 0.009) and TGF-β2 (r = 0.375, p = 0.031) basal levels. Conclusion: cGAS expression, but not STING, predicts poor PD-1/L1 inhibitor efficacy in NSCLC with high PD-L1, potentially due to a TGF-β-mediated immunosuppressive environment (UMIN000024414). [ABSTRACT FROM AUTHOR]

Radiotherapy is a primary treatment method for lung cancer, and radiation-induced lung injury has been widely studied. However, the lung and intestines are closely related, and patients receiving lung radiotherapy often experience gastrointestinal reactions. Huanglian Decoction has proven effective in treating intestinal diseases, but its role in radiation-induced intestinal injury in lung cancer has not yet been demonstrated. The study investigated the potential protective mechanisms of Huanglian Decoction against radiation-induced intestinal injury in lung cancer. In vivo experiments were conducted to examine the morphological changes. Changes in endoplasmic reticulum stress-related proteins were assessed using electron microscopy, immunohistochemistry, immunofluorescence, and Western blotting. In vitro studies involved the overexpression of TRPA1 protein in NCM460 cells via lentiviral vectors. Tumor-bearing mice exhibited severe damage to both lung and colon tissues following radiotherapy, with elevated levels of IL-33, increased expression of ST2L and TRPA1 in colon tissues, higher levels of endoplasmic reticulum stress-related proteins, and the presence of apoptosis and inflammatory responses. Huanglian Decoction reduced radiation-induced intestinal injury by lowering IL-33 levels, which in turn reduced endoplasmic reticulum stress response in colon tissues. In TRPA1-overexpressing NCM460 cells, Huanglian Decoction decreased TRPA1 expression levels and significantly alleviated endoplasmic reticulum stress response. Conclusively, the results indicate that Huanglian Decoction alleviates radiation-induced intestinal endoplasmic reticulum stress by reducing IL-33 levels, subsequently inhibiting the expression of ST2L and TRPA1 in colon tissues. This demonstrates the protective effect of Huanglian Decoction on the intestines during lung cancer radiotherapy, highlighting its promising clinical application in radiation protection. [ABSTRACT FROM AUTHOR]

Background: This study examines lung cancer incidence in Spain (1990–2019) through age–period–cohort (A–P–C) analysis and Global Burden of Diseases (GBD) data, unravelling the complex interplay of age, period, and birth cohort in shaping these trends. Methods: Utilizing GBD and Spanish population data, the study calculates age-standardized incidence rates (ASIRs) and employs Joinpoint analysis to identify significant trends. A–P–C analysis dissects the individual effects of age, calendar period, and birth cohort on incidence patterns. Results: Between 1990 and 2019, almost 738,000 cases of lung cancer were diagnosed in Spain, with an average annual increase of 1.7%. The ASIR of lung cancer in Spain from 1990 to 2019 showed a sustained upward trend in women (Average Annual Per cent Change: 2.5%, P < 0.05), reaching 23.3 cases per 100,000 in 2019, whilst men experienced a significant decrease in incidence rates (AAPC: −0.6%, P < 0.05), falling to 108.9 in 2019. The male-to-female incidence ratio decreased from 12.2 in 1992 to 4.9 in 2019. Joinpoint analysis identified distinct periods for both sexes, with men showing stability, decline and then a significant decrease, whereas women showed an initial increase followed by a decrease. The longitudinal age curves showed a consistently higher incidence risk in men, peaking in the 80–84 age group. Male cohorts since the 1920s showed a decreasing relative risk, whereas women showed fluctuations in risk over time. Conclusion: Lung cancer rates are falling in Spain, especially amongst men, due to lower smoking rates. The gender gap is closing, but prevention targeted at women is needed. Tighter tobacco control and research into other risk factors are essential. Understanding the long-term effects of smoking and early exposure is key to better prevention and treatment in Spain. [ABSTRACT FROM AUTHOR]

ZIF-8 (Zn, Fe) bimetal–organic framework (BMOF) is used for encapsulation of the doxorubicin (DOX). The BMOF surface is coated by chitosan-grafted- polycaprolactone (Cs-g-PCL) to obtain a pH-sensitive nanocarrier. Curcumin (Cur) was loaded into the Cs-g-PCL, and the surface of nanoparticles coated by transactivating transcriptional factor (TAT) peptide. The capability of TAT peptide-coated Cs-g-PCL/Cur/BMOF/DOX was investigated for lung cancer treatment. More than 95% DOX release from Cs-g-PCL/Cur/BMOF/DOX and TAT peptide-coated Cs-g-PCL/Cur/BMOF/DOX under pH values of 5.5 & 6.8 & 7.4 occurred within 72 ± 0.25 & 120 ± 0.3 & 144 ± 0.3 h and 96 ± 0.2 & 144 ± 0.3 & 168 ± 0.5 h, respectively. MTT assay results indicated that the co-delivery of DOX and Cur resulted in decreasing the cell viability of A549 lung cancer cell up to 22.7 ± 0.2%, and the maximum A549 cancer cells death percentage was 93.5 ± 0.1% using TAT peptide-coated Cs-g-PCL/Cur/BMOF/DOX BMOFs. The flowcytometry and confocal images results demonstrated the synergistic effect of TAT peptide and DOX-Cur anticancer drugs on the apoptosis of A549 cancer cells. The in vivo results indicated the maximum tumor inhibition (relative tumor volume: 0.25 after 20 days) for the tumor-bearing mice treated with TAT peptide-coated Cs-g-PCL/Cur/ZIF-8 (Zn, Fe) /DOX BMOF. Overall, results revealed that the co-delivery of anticancer agents and peptides increase the therapeutic efficacy. [ABSTRACT FROM AUTHOR]

Liquid biopsy using circulating tumor DNA (ctDNA) has been reported to be less invasive and effective for comprehensive genetic analysis of heterogeneous solid tumors, including decision-making for therapeutic strategies, predicting recurrence, and detecting genetic factors related to treatment resistance in various types of cancers. Breast cancer, colorectal cancer, and lung cancer are among the most prevalent malignancies worldwide, and clinical studies of liquid biopsy for these cancers are ongoing. Liquid biopsy has been used as a companion diagnostic tool in clinical settings, and research findings have accumulated, especially in cases of colorectal cancer after curative resection and non-small cell lung cancer (NSCLC) after curative chemoradiotherapy, in which ctDNA detection helps predict eligibility for adjuvant chemotherapy. Liquid biopsy using ctDNA shows promise across a wide range of cancer types, including breast cancer, and its clinical applications are expected to expand further through ongoing research. In this article, studies on liquid biopsy in breast cancer, colorectal cancer, and NSCLC are compared focusing on ctDNA. [ABSTRACT FROM AUTHOR]

Purpose: Lung cancer is one of the leading causes of death worldwide. Recent studies have shown that circular RNAs are dysregulated in a variety of cancers, but the mechanism in lung cancer is still indistinct. In our work, we explored the action mechanism of circLDLRAD3 in lung cancer. Methods: The abundance of circLDLRAD3, microRNA-497-5p (miR-497-5p) and platelet-type PFK (PFKP) was measured by real-time quantitative polymerase chain reaction (RT-qPCR) in lung cancer. Meanwhile, the level of PFKP was quantified by western blot. Cell counting kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine (EdU) assay, transwell assay, wound healing assay, flow cytometry, western blot, immunohistochemical (IHC) assay and glycolysis metabolism analysis were performed for functional analyses. Furthermore, the interplay between miR-497-5p and circLDLRAD3 or FKPF was detected by the dual-luciferase reporter and RNA Immunoprecipitation (RIP) assays. Eventually, the in vivo experiments were applied to measure the role of circLDLRAD3. Result: The levels of circLDLRAD3 and PFKP were increased. Silencing circLDLRAD3 inhibited cell viability, proliferation, migration, invasion and glycolysis metabolism and promoted cell apoptosis in lung cancer cells. In mechanism, circLDLRAD3 regulated PFKP level as a miR-497-5p sponge. MiR-497-5p suppressed the progression of lung cancer by inhibiting PFKP. In addition, circLDLRAD3 knockdown also inhibited tumor growth in vivo. Conclusion: CircLDLRAD3 promoted the development of lung cancer through increasing PFKP expression by regulating miR-497-5p, which also provided a potential targeted therapy for lung cancer treatment. [ABSTRACT FROM AUTHOR]

The Yes-associated protein (YAP) oncoprotein has been linked to both metastases and resistance to targeted therapy of lung cancer cells. We aimed to investigate the effect of YAP pharmacological inhibition, using YAP/TEA domain (TEAD) transcription factor interaction inhibitors in chemo-resistant lung cancer cells. YAP subcellular localization, as a readout for YAP activation, cell migration, and TEAD transcription factor functional transcriptional activity were investigated in cancer cell lines with up-regulated YAP, with and without YAP/TEAD interaction inhibitors. Parental (A549) and paclitaxel-resistant (A549R) cell transcriptomes were analyzed. The half-maximal inhibitory concentration (IC50) of paclitaxel or trametinib, which are Mitogen-Activated protein kinase and Erk Kinase (MEK) inhibitors, combined with a YAP/TEAD inhibitor (IV#6), was determined. A three-dimensional (3D) microfluidic culture device enabled us to study the effect of IV#6/paclitaxel combination on cancer cells isolated from fresh resected lung cancer samples. YAP activity was significantly higher in paclitaxel-resistant cell lines. The YAP/TEAD inhibitor induced a decreased YAP activity in A549, PC9, and H2052 cells, with reduced YAP nuclear staining. Wound healing assays upon YAP inhibition revealed impaired cell motility of lung cancer A549 and mesothelioma H2052 cells. Combining YAP pharmacological inhibition with trametinib in K-Ras mutated A549 cells recapitulated synthetic lethality, thereby sensitizing these cells to MEK inhibition. The YAP/TEAD inhibitor lowered the IC50 of paclitaxel in A549R cells. Differential transcriptomic analysis of parental and A549R cells revealed an increased YAP/TEAD transcriptomic signature in resistant cells, downregulated upon YAP inhibition. The YAP/TEAD inhibitor restored paclitaxel sensitivity of A549R cells cultured in a 3D microfluidic system, with lung cancer cells from a fresh tumor efficiently killed by YAP/TEAD inhibitor/paclitaxel doublet. Evidence of the YAP/TEAD transcriptional program's role in chemotherapy resistance paves the way for YAP therapeutic targeting. [ABSTRACT FROM AUTHOR]

The combination of shikonin (SKN) and gefitinib (GFB) can reverse the drug resistance of lung cancer cells by affecting energy metabolism. However, the poor solubility of SKN and GFB limits their clinical application because of low bioavailability. Wheat germ agglutinin (WGA) can selectively bind to sialic acid and N-acetylglucosamine on the surfaces of microfold cells and enterocytes, and is a targeted biocompatible material. Therefore, we created a co-delivery micelle system called SKN/GFB@WGA-micelles with the intestinal targeting functions to enhance the oral absorption of SKN and GFB by promoting mucus penetration for nanoparticles via oral administration. In this study, Caco-2/HT29-MTX-E12 co-cultured cells were used to simulate a mucus/enterocyte dual-barrier environment, and HCC827/GR cells were used as a model of drug-resistant lung cancer. We aimed to evaluate the oral bioavailability and anti-tumor effect of SKN and GFB using the SKN/GFB@WGA-micelles system. In vitro and in vivo experimental results showed that WGA promoted the mucus penetration ability of micelles, significantly enhanced the uptake efficiency of enterocytes, improved the oral bioavailability of SKN and GFB, and exhibited good anti-tumor effects by reversing drug resistance. The SKN/GFB@WGA-micelles were stable in the gastrointestinal tract and provided a novel safe and effective drug delivery strategy. [ABSTRACT FROM AUTHOR]

Purpose of review: Bone morphogenetic protein 2 (BMP2) belongs to the transforming growth factor-β (TGF-β) superfamily and plays an important role in regulating embryonic development, angiogenesis, osteogenic differentiation, tissue homeostasis, and cancer invasion. Increasing studies suggest BMP2 is involved in several respiratory diseases. This study aimed to review the role and mechanisms of BMP2 in respiratory diseases. Recent findings: BMP2 signaling pathway includes the canonical and non-canonical signaling pathway. The canonical signaling pathway is the BMP2-SMAD pathway, and the non-canonical signaling pathway includes mitogen-activated protein kinase (MAPK) pathway and phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathway. The BMP2 is related to pulmonary hypertension (PH), lung cancer, pulmonary fibrosis (PF), asthma, and chronic obstructive pulmonary disease (COPD). BMP2 inhibits the proliferation of pulmonary artery smooth muscle cells (PASMCs), promotes the apoptosis of PASMCs to reduce pulmonary vascular remodeling in PH, which is closely related to the canonical and non-canonical pathway. In addition, BMP2 stimulates the proliferation and migration of cells to promote the occurrence, colonization, and metastasis of lung cancer through the canonical and the non-canonical pathway. Meanwhile, BMP2 exert anti-fibrotic function in PF through canonical signaling pathway. Moreover, BMP2 inhibits airway inflammation to maintain airway homeostasis in asthma. However, the signaling pathways involved in asthma are poorly understood. BMP2 inhibits the expression of ciliary protein and promotes squamous metaplasia of airway epithelial cells to accelerate the development of COPD. Summary: In conclusion, BMP2 may be a therapeutic target for several respiratory diseases. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) play essential roles as oncogenic factors in cancer progression by influencing cell proliferation, apoptosis, and metastasis pathways. This study aims to investigate the expression changes of LINC01615 in prevalent cancers, explore its correlation with patient mortality rates, and introduce a novel therapeutic approach to reduce LINC01615 expression. Using The Cancer Genome Atlas (TCGA) data, the expression changes of LINC01615 in various cancers were analyzed, and its relationship with patient survival rates through Cox regression analysis weas assessed. Co-expressed pathways related to LINC01615 were identified via network analysis. Potential drugs to decrease LINC01615 expression were identified using the GSE38376 study. Besides, chitosan-coated nanoparticles were fabricated and functionalized with the identified drug, Lapatinib, to examine their effect on lung cancer cell lines and changes in LINC01615 expression. Our results indicated elevated LINC01615 expression in various common cancers, particularly in lung cancer, which was associated with poor prognosis in lung, breast, and kidney cancers. Co-expression network analysis suggested links to metastasis-related genes. Lapatinib, identified through GEO data, was found to modulate LINC01615 expression effectively. Chitosan-gold nanoparticles conjugated with Lapatinib significantly reduced LINC01615 expression in lung cancer cell lines while enhancing apoptosis rates. Therefore, these nanoparticles could be considered a promising therapeutic candidate for treating cancers with overexpression of LINC01615. [ABSTRACT FROM AUTHOR]

Lung cancer is one of the most common malignant tumors in the world, with high incidence rate and mortality. Monocarboxylate transporter (MCT) 1 has been found to be widely expressed in various tumors and plays a crucial role in regulating energy metabolism. Emodin, as an important traditional Chinese medicine in China, has been reported to inhibit the progression of lung cancer. However, its potential mechanism has not been fully elucidated. The effects of emodin and MCT1 inhibitor AZD3965 on the proliferation, migration, and invasion of lung cancer cells were detected using cell counting kit-8 (CCK-8) assay, wound-healing assay, and transwell small chamber assay. The content of glucose, lactate, and pyruvate in the cell culture medium was detected using a glucose, lactate, and pyruvate detection kit, and also detected protein expression using western blotting. In addition, to investigate the effects of emodin and AZD3965 on lung cancer in vivo, we constructed nude mice subcutaneous transplant tumor model by subcutaneous injection of lung cancer cells. The results showed that emodin and AZD3965 could inhibit the proliferation, migration, and invasion of lung cancer cells. At the same time, they could inhibit the expression of MCT1 in lung cancer cells and promote the release of lactate, but did not affect the content of glucose and pyruvate. In vivo experiments had shown that emodin and AZD3965 could effectively inhibit the growth of lung cancer and inhibit the expression of MCT1. All in all, our data suggested that emodin inhibited the proliferation, migration, and invasion of lung cancer cells, possibly by inhibiting MCT1, providing important theoretical basis for elucidating the mechanism of emodin in treating lung cancer.Highlights: Emodin could inhibit proliferation, migration, and invasion of lung cancer cells. Emodin could inhibit the expression of monocarboxylate transporter 1, a key mediator of lactate shuttle. Emodin could inhibit the expression of oncogenes in lung cancer cells. Emodin and AZD3965 could inhibit the growth of subcutaneous transplanted tumors in nude mice. [ABSTRACT FROM AUTHOR]

This retrospective study developed an automated algorithm for 3D segmentation of adipose tissue and paravertebral muscle on chest CT using artificial intelligence (AI) and assessed its feasibility. The study included patients from the Boston Lung Cancer Study (2000–2011). For adipose tissue quantification, 77 patients were included, while 245 were used for muscle quantification. The data were split into training and test sets, with manual segmentation as the ground truth. Subcutaneous and visceral adipose tissues (SAT and VAT) were segmented separately. Muscle area, mean attenuation value, and intermuscular adipose tissue percentage (IMAT%) were calculated in the paravertebral muscle segmentation. The AI algorithm was trained on the training sets, and its performance was evaluated on the test sets. The AI achieved Dice scores above 0.87 and showed excellent correlations for VAT/SAT ratios, muscle attenuation value, and IMAT% (correlation coefficients > 0.98, p < 0.001). The mean differences between the AI and ground truth were minimal (VAT/SAT ratio: 0.7%; muscle attenuation value: 1 HU; IMAT%: <1%). In conclusion, we developed a feasible AI algorithm for automated 3D segmentation of adipose tissue and paravertebral muscle on chest CT. [ABSTRACT FROM AUTHOR]

Accurate lung nodule segmentation is fundamental for the early detection of lung cancer. With the rapid development of deep learning, lung nodule segmentation models based on the encoder-decoder structure have become the mainstream research approach. However, during the encoding process, most models have limitations in extracting edge and semantic information and in capturing long-range dependencies. To address these problems, we propose a new lung nodule segmentation model, abbreviated as MCAT-Net. In this model, we construct a multi-threshold feature separation module to capture edge and texture features from different levels and specified intensities of the input image. Secondly, we introduce the coordinate attention mechanism, which allows the model to better recognize and utilize spatial information when handling long-range dependencies, enabling the deep network to maintain its sensitivity to nodule positions. Thirdly, we use the transformer to fully capture the long-range dependencies, further enhancing the global information integration of the network. The proposed method was verified on the LIDC-IDRI and LNDb datasets. The Dice similarity coefficient (DSC) values achieved were 88.29% and 78.51%, and the sensitivities were 86.33% and 75.05%, respectively. The experimental results demonstrated its high practical value for the early diagnosis of lung cancer. [ABSTRACT FROM AUTHOR]

Using Fourier Transform Infrared spectroscopy (FTIR), it is possible to show chemical composition of materials and / or profile chemical changes occurring in tissues, cells, and body fluids during onset and progression of diseases. For diagnostic application, the use of blood would be the most appropriate in biospectroscopy studies since, (i) it is easily accessible and, (ii) enables frequent analyses of biochemical changes occurring in pathological states. At present, different studies have investigated potential of serum, plasma and sputum being alternative biofluids for lung cancer detection using FTIR. However, until now, it has not been shown which biofluid; among serum and plasma, that can serve as the best material medium for detecting lung cancer with highest levels of accuracy. In this study, plasma and serum isolated from blood consenting participants without lung cancer symptoms (controls) and lung cancer patients. The samples were measured using FTIR and subsequently analyzed by machine learning (ML) algorithms in order to show which fluids (serum or plasma) would better enhance detection of lung cancer. Higher absorbances values of PO2−, CH2, CH3 and amides vibrations in FTIR spectra of both serum and plasma samples, collected from lung cancer patients were observed in comparison to individuals without lung cancer symptoms (controls). Principal component analysis (PCA) of FTIR spectra showed plasma and serum samples collected from lung cancer patients and individuals without lung cancer symptoms were better differentiated in fingerprinting region (from 800 to 1800 cm− 1) when compared to lipid region (2800–3000 cm− 1). Moreover, also sensitivity specificity and accuracy calculated by logistic regression (LR) and receive operating characteristic (ROC) showed higher values for fingerprint range (800–1800 cm− 1) in comparison with lipids (2800–3000 cm− 1) one for both, serum and plasma. However, using these methods differences between serum and plasma were not existed. From the all obtained results, it was visible, that both fluids could be used in detected lung cancer using FTIR. Moreover, it was also showed that fingerprint range gave a better distinction between the studied patient groups than the lipid range. This was noticeable for both serum and plasma. [ABSTRACT FROM AUTHOR]

Lung cancer ranks as the most prevalent malignant neoplasm worldwide, contributing significantly to cancer-related mortality. Stemness is a well-recognized factor underlying radiotherapy resistance, recurrence and metastasis in non-small-cell lung cancer (NSCLC) patients. Our prior investigations have established the role of IQ motif containing GTPase-activating protein 3 (IQGAP3) in mediating radiotherapy resistance in lung cancer, but its impact on lung cancer stemness remains unexplored. Our bioinformatics analysis results revealed a significant correlation between IQGAP3 and lung cancer stemness. Moreover, we found that IQGAP3 depletion in lung cancer cells resulted in reduced migration, invasion and sphere-forming capabilities. Through RNA sequencing, we identified GLI1 as a pivotal downstream effector of IQGAP3. The knockdown of IQGAP3 led to the downregulation of GLI1 mRNA and protein levels, which impeded the activation of the Hedgehog-GLI1 signaling pathway. Further, our results also indicated that GLI1 is the primary effector mediating IQGAP3's biological functions in lung cancer. These findings elucidate the role of IQGAP3 in promoting lung cancer stemness and metastasis through the Hedgehog pathway, facilitated by GLI1, highlighting the potential of IQGAP3 as a promising therapeutic target for lung cancer treatment. [ABSTRACT FROM AUTHOR]

Many conditions, such as pulmonary edema, bleeding, atelectasis or collapse, lung cancer, and shadow formation after radiotherapy or surgical changes, cause Lung Opacity. An unsupervised cross-domain Lung Opacity detection method is proposed to help surgeons quickly locate Lung Opacity without additional manual annotations. This study proposes a novel method based on adversarial learning to detect Lung Opacity on chest X-rays. Focal loss, GIoU loss, and WBF (weighted boxes fusion) were used in training. We conducted extensive experiments on Chest X-rays from RSNA (Radiological Society of North America) and Vingroup Big Data Institute to verify the performance of cross-domain detection. The results indicate that our method has superior performance. The AP reached 34.30% and 36.55%, while the AR10 reached 74.11% and 75.91% in two cross-domain detection tasks. The visualization results show that the randomly selected samples were more accurately detected for Lung Opacity after applying our method. Compared with other excellent detection frameworks, our method achieved competitive results without additional annotations, making it suitable for assisting in Lung Opacity detection. [ABSTRACT FROM AUTHOR]

Radon (222Rn) and thoron (220Rn) were reported as the highest contributors to natural radiation received by humans. Furthermore, radon has been stated as the second-highest cause of lung cancer. The concentrations of 238U and 232Th (the parent nuclide of radon and thoron, respectively) in nature vary with geological conditions and can be enhanced by human activities. Bangka Island in Indonesia is one such case with tin mining, where the environment contains a high amount of 232Th due to the island's granite bedrock. This study assesses the public's exposure to radon and thoron inhalation on Bangka Island by conducting measurements using a continuous radon-thoron monitor and a time-integrated monitor for radon, thoron, and thoron progeny concentrations. From those measurements, their diurnal and seasonal variation in the dwellings on Bangka Island were analyzed. From 135 dwellings on Bangka Island, the estimated annual effective dose derived from the inhalation of radon, thoron, and their progenies reaches 4.3 mSv at the highest and a mean of 1.7 ± 0.8 mSv in which thoron contributes more than two times higher than radon. Note that the public exposure to radon and thoron inhalation in Bangka was within the reference level for the existing exposure situation. [ABSTRACT FROM AUTHOR]

Lung cancer (LC) remains the primary cause of cancer-related mortality, largely due to late-stage diagnoses. Effective strategies for early detection are therefore of paramount importance. In recent years, machine learning (ML) has demonstrated considerable potential in healthcare by facilitating the detection of various diseases. In this retrospective development and validation study, we developed an ML model based on dynamic ensemble selection (DES) for LC detection. The model leverages standard blood sample analysis and smoking history data from a large population at risk in Denmark. The study includes all patients examined on suspicion of LC in the Region of Southern Denmark from 2009 to 2018. We validated and compared the predictions by the DES model with diagnoses provided by five pulmonologists. Among the 38,944 patients, 9,940 had complete data of which 2,505 (25%) had LC. The DES model achieved an area under the roc curve of 0.77±0.01, sensitivity of 76.2%±2.04%, specificity of 63.8%±2.3%, positive predictive value of 41.6%±1.2%, and F1-score of 53.8%±1.0%. The DES model outperformed all five pulmonologists, achieving a sensitivity 6.5% higher than their average. The model identified smoking status, lactate dehydrogenase, age, total calcium levels, low values of sodium, leucocytes, neutrophil count, and C-reactive protein as the most important factors for LC detection. The results highlight the successful application of the ML approach in detecting LC, surpassing pulmonologists' performance. Incorporating clinical and laboratory data in future risk assessment models can improve decision-making and facilitate timely referrals. [ABSTRACT FROM AUTHOR]

Cancer, a leading cause of death worldwide, is projected to increase by 76.6% in new cases and 89.7% in mortality by 2050 (WHO 2022). Among various types, lung cancer is the most prevalent with high morbidity, while breast, colorectal, and pancreatic cancers also show high mortality rates. Cancer progression often involves disruption in cell cycle regulation and signaling pathways, with mutations in genes like TP53, EGFR, and K-RAS playing significant roles. In this study, we analyzed gene expression datasets to identify common molecular signatures across breast, colorectal, lung and pancreatic cancers. Our focus was on genes related to cell cycle regulation and p53 signaling pathway, intending to discover potential biomarkers for improved diagnosis and treatment strategies. The study analyzed GEO datasets; GSE45827, GSE9348, GSE30219, and GSE62165 for breast, colorectal, lung, and pancreatic cancers respectively. Differentially expressed genes (DEGs) were identified using GEO2R, and functional annotation and pathway analysis were performed using WebGestalt. Common cell cycle and p53 signaling genes were acquired from MSigDB using GSEA. A protein–protein interaction network was constructed using STRING and Cytoscape, identifying top hub genes. Validation of hub genes at mRNA and protein levels was done via GEPIA2 and Human Protein Atlas. Survival analysis was conducted using TCGA data by GEPIA2 and LASSO, and drug sensitivity was analyzed with the GSCA drug bank database, highlighting potential therapeutic targets. The study identified 411 common DEGs among these four cancers. Pathway and functional enrichment revealed key biological processes and pathways like p53 signaling, and cell cycle. The intersection of these DEGs with genes involved in cell cycle and p53 signaling, identified 23 common genes that were used for constructing a PPI network. The top 10 hub genes were validated both for mRNA and protein expression, revealing they are significantly overexpressed in all studied cancers. Prognostic relevance showed that MCM4, MCM6, CCNA2, CDC20, and CHEK1 are associated with survival. Additionally, drug sensitivity analysis highlighted key gene-drug interactions, suggesting potential targets for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Background: Lung cancer is a form of cancer that is responsible for the largest incidence of deaths attributed to cancer worldwide. Non-small cell lung cancer (NSCLC) is the most prevalent of all the subtypes of the disease. Treatment with tyrosine kinase inhibitors (TKI) may help some people who have been diagnosed with non-small cell lung cancer. The presence of actionable mutations in the epidermal growth factor receptor (EGFR) gene is a key predictor of how a patient will respond to a TKI. Thus, the frequency of identification of mutations in EGFR gene in patients with NSCLC can facilitate personalized treatment. Objective: The objective of this study was to screen for mutations in the EGFR gene and to investigate whether there is a correlation between the screened mutations and various clinical and pathological factors, such as gender, smoking history, and age, in tissue samples from patients with NSCLC. Methods: The study comprised 333 NSCLC tissue samples from 230 males and 103 females with an average age of 50 years. Exons 18–21 of the EGFR gene have been examined using real-time PCR. Using SPSS, correlations between clinical and demographic variables were examined, and EGFR mutation and clinical features associations were studied. Results: The study's findings revealed that the incidence rate of EGFR mutation was 24.32% (81/333), with partial deletion of exon 19 (19-Del) and a point mutation of L858R in exon 21 accounting for 66.67% (P < 0.001) and 28.40% (P < 0.001) of the mutant cases, respectively. Patients who had the T790M mutation represent 4.94% (P = 0.004) of total number of patients. Females harbored EGFR mutations (54.32%) with higher frequency than men (45.68%) (P < 0.001), while nonsmokers had EGFR mutations (70.37%) more frequently than current smokers (29.63%) (P < 0.001). Conclusion: The screening study conducted in Egypt reported that the EGFR mutations prevalence was 24.32% among Egyptians with NSCLC. The study also found a slight gender bias, with females having an incidence rate of these mutations higher than males. Additionally, nonsmokers had higher rates of mutations in EGFR gene compared to smokers. According to the findings, somatic EGFR mutations can be employed as a diagnostic tool for non-small cell lung cancer in Egypt, and they can be implemented in conjunction with clinical criteria to identify which patients are more likely to respond favorably to TKIs. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) is the most predominant histological subtype of lung cancer characterized by driver mutations detected in a substantial proportion of the cases. Tyrosine kinase inhibitors (TKIs) are standard care for the patients with these mutations. In this study, we evaluated the efficiency of an NGS-based 8-gene test in selecting TKIs-sensitive patients in a cohort of treatment-naive Chinese LUAD patients and evaluated the sensitivity of rare compound mutations to different EGFR-TKIs in vitro. Material and methods: Targeted sequencing covering the hotspot regions of eight LUAD driver genes was performed across 853 treatment-naive LUAD patients admitted in Henan Cancer Hospital (HNCH cohort). The mutational landscape of HNCH patients was compared with TCGA patients. Logistic regression analysis was used to determine the factors associated with presence of these mutations. Genetically modified LUAD PC9 cells were established to evaluate the sensitivity of selected EGFR rare compound mutations to different EGFR-TKIs. Results: A total of 574 single nucleotide variants (SNVs), 270 indels, 88 amplifications, and 87 rearrangements were identified in this study, with EGFR and KRAS being the most frequently mutated genes. Females, mostly life-long non-smokers, had significantly higher EGFR mutation rates than males. Males, primarily smokers, more frequently had KRAS mutations. HNCH patients in general had a higher mutation count than TCGA patients (1.09 vs 0.93 mutations per patient (m/p)), in consistent with its higher proportion of patients with advanced disease. Rare EGFR compound mutations identified in this study, including Exon19del plus L747S/I744V and L858R plus V843I/T854A/G873, conferred genetically modified PC9 cells more sensitive to second-generation EGFR-TKI afatinib in-vivo. Conclusion: This NGS-based 8-gene test efficiently identified over 70% of Chinese treatment-naive LUAD patients who are targetable for TKIs. Patients with rare EGFR compound mutations might consider second-generation EGFR-TKIs for treatment. [ABSTRACT FROM AUTHOR]

In recent years, the incidence of ground-glass nodular lung adenocarcinoma has gradually increased. Preoperative evaluation of the tumor invasiveness is very important, but there is a lack of effective methods. Plasma samples of ground-glass nodular lung adenocarcinoma and healthy volunteers were collected. Pulmonary nodules with different densities were compared by metabolomics. Different invasive degrees of lung adenocarcinoma were contrasted as well. Multivariate statistical methods were applied to search for significant metabolites from comparisons between two groups. The common metabolites among the different comparisons were selected and then assessed by various indices. Five metabolites were discovered for lung adenocarcinoma with different invasive degrees. Significant metabolites were selected for pulmonary nodules with different densities as well. When these metabolites were cross-compared, only the level of lysoPC(18:3) was significantly lower in ground-glass nodular lung adenocarcinoma than healthy population, as opposed to other metabolites. After identifying the invasive degree of pulmonary ground-glass nodules, lysoPC(18:3) showed a satisfactory sensitivity and specificity, both greater than 0.85. Metabolomics analysis has favorable advantages in the study of ground-glass nodular lung adenocarcinoma. LysoPC(18:3) may have the potential to differentiate precancerous lesions from invasive lung cancer, which could help clinicians to make proper judgment before surgery. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer-related death globally. Metastasis is the most common reason of mortality in which hypoxia is suggested to have a pivotal role. However, the effect of hypoxia on the metastatic potential and migratory activity of cancer cells is largely unexplored and warrants detailed scientific investigations. Accordingly, we analyzed changes on cell proliferation and migratory activity both in single-cell migration and invasion under normoxic and hypoxic conditions in lung adenocarcinoma cell lines. Alterations in crucial genes and proteins associated with cellular response to hypoxia, epithelial-mesenchymal transition, proliferation and apoptosis were also analyzed. Generally, we observed no change in proliferation upon hypoxic conditions and no detectable induction of apoptosis. Interestingly, we observed that single-cell motility was generally reduced while invasion under confluent conditions using scratch assay was enhanced by hypoxia in most of the cell lines. Furthermore, we detected changes in the expression of EMT markers that are consistent with enhanced motility and metastasis-promoting effect of hypoxia. In summary, our study indicated cell line-, time of exposure- and migrational type-dependent effects of hypoxia in cellular proliferation, motility and gene expression. Our results contribute to better understanding and tackling cancer metastasis. [ABSTRACT FROM AUTHOR]

Spread through air spaces (STAS) is a distinct invasion pattern in lung cancer, crucial for prognosis assessment and guiding surgical decisions. Histopathology is the gold standard for STAS detection, yet traditional methods are subjective, time-consuming, and prone to misdiagnosis, limiting large-scale applications. We present VERN, an image analysis model utilizing a feature-interactive Siamese graph encoder to predict STAS from lung cancer histopathological images. VERN captures spatial topological features with feature sharing and skip connections to enhance model training. Using 1,546 histopathology slides, we built a large single-cohort STAS lung cancer dataset. VERN achieved an AUC of 0.9215 in internal validation and AUCs of 0.8275 and 0.8829 in frozen and paraffin-embedded test sections, respectively, demonstrating clinical-grade performance. Validated on a single-cohort and three external datasets, VERN showed robust predictive performance and generalizability, providing an open platform (http://plr.20210706.xyz:5000/) to enhance STAS diagnosis efficiency and accuracy. [ABSTRACT FROM AUTHOR]

One of the world's deadliest diseases is lung cancer. Based on a few features, machine learning techniques can help in the diagnosis of lung cancer. The performance of several classifiers: support vector machine (SVM), logistic regression (LR), Naïve Bayes (NB), random forest (RF), and K-nearest neighbor (KNN), was evaluated by the authors using the dataset available on Kaggle to create a systematic approach for the diagnosis of lung cancer disease based on readily observable signs and historical medical data without the requirement of CT scan images. The authors have proposed a novel approach for classification called Pearson correlation weighted KNN (PCWKNN), which is a modified version of KNN and uses Pearson correlation coefficient values to determine weights in a weighted KNN. The performance of the classifiers was evaluated using the hold-out validation method. SVM, LR, and RF were 96.77% accurate. NB obtained 95.16% accuracy. KNN achieved 91.93% accuracy. PCWKNN outperformed the employed classifiers and obtained an accuracy of 98.39%. Addressing the imperative for improved model generalization, the researchers utilized PCWKNN on an alternative, more extensive lung cancer dataset and subsequently broadened its application to diverse diseases, including the brain stroke dataset. The encouraging outcomes underscore PCWKNN's resilience and adaptability, suggesting its viability for real-world implementation. [ABSTRACT FROM AUTHOR]