Lung Cancer Research Articles

Lung cancer in females: Military cancer center experience in Jordan

Objective: to evaluate the clinical properties, pathological properties and the survival data for 80 lung cancer female patients who were managed in our center. Methods: this retrospective study included 80 female patients with lung cancer that were treated in The Military Cancer Center of the Jordanian Royal Medical services between January 2022 and January 2024, the patients pathological, clinical and survival data will be reviewed and analyzed. Results: group age was between 41 to 82 years (mean of 60.18 ± 11.72). 82.5% of patients were diagnosed with non-small cell lung cancer (NSCLC), 17.5% of patients had small cell lung cancer (SCLC), 30% of patients were smokers. Significant weight loss was observed in 40% of patients. Comorbidity was present in 43.75% of patients with hypertension being the most common one 36.25%. Adenocarcinoma was the most common histological subtype 56%. The one-year survival rate was 70% and the two-year survival rate was 37.5%. Conclusion: our study showed that advanced stage, weight loss, poor ECOG score and NSCLC subtype were a main prognostic factors in females with lung cancer in Jordan.

Object Detection & Analysis with Deep CNN and Yolov8 in Soft Computing Frameworks

Object detection is one of the major roles in deep learning and soft computing which contributes to many real time cases in healthcare, agriculture etc. This study proposes a deep learning-based approach for object detection to detect lung cancer and diagnosis by utilizing deep Convolutional Neural Networks (CNN) and the YOLOv8 model, with DICOM (Digital Imaging and Communications in Medicine) images for robust image analysis. Lung cancer remains one of the leading causes of mortality worldwide, necessitating early and accurate detection to improve patient outcomes. The primary objective of the research is to enhance the accuracy, precision, and recall rates in lung cancer detection, while reducing false positives and false negatives, through advanced machine learning techniques. In the proposed work, CNN is employed for feature extraction, enabling the model to capture the intricate patterns present in the DICOM images. YOLOv8, a cutting-edge object detection algorithm, is integrated to detect cancerous regions with high efficiency and speed. A comparative analysis is conducted with traditional machine learning classifiers such as Support Vector Machine (SVM), AdaBoost, Random Forest, and K-Nearest Neighbors (KNN), demonstrating the superior performance of the proposed deep learning models. The experimental results reveal that the CNN-YOLOv8 model achieves remarkable accuracy of 94 Parsant, with a precision of 93.56 Parsant, recall of 92 Parsant, ROC score of 93 Parsant, and an F-score of 94.60 Parsant. These findings underscore the effectiveness of deep learning in lung cancer detection, significantly outperforming conventional models in terms of accuracy and reliability. The novelty of this research lies in the integration of CNN with YOLOv8, specifically optimized for medical DICOM images, which allows for real-time, accurate identification of lung cancer while maintaining computational efficiency.

Utilizing Raspberry Pi and Internet of Things (IoT) Frameworks for Comprehensive Monitoring of Urban Pollutants and Climate Variables

Global warming is the effect of a rise in Earth's climate temperature due to air pollution. Urban areas have higher levels of air pollution than rural areas due to increased traffic and rapid development. In addition to brief health problems like headaches, eye infections, and throat in-factions, pollution also has lengthy health repercussions like lung cancer and heart disease. As a result, it's important to keep an eye on the many climatic and pollution indicators, including light intensity, temperature, humidity, air pressure, oxygen and carbon dioxide level and camera. Using suitable equipment and Internet of Things (IoT) technologies, a pollution and climate monitoring system is constructed in the proposed paper that can measure the parameters above at regular intervals. The system then uploads the data to a webpage in the Thing Speak. The IoT analytics platform service Thing Speak enables the collection, visualization, and analysis of real-time data streams. The sensors are used to feed data to Thing Speak, which instantly visualizes the data in a graph. The main tool for gathering data from the sensors and sending parameters to the website is the Raspberry Pi3 computer. The software code is developed using Python. By logging on to the website from any location in the world, one can view the submitted pollution and climate parameters of a specific location.

Monotropein represses the proliferation and angiogenesis via the AKT/NF-κB pathway in lung cancer.

Monotropein (Mon) is an iridoid glycosides extracted from Morinda officinalis F.C. How. (Rubiaceae) that shows anticancer effects on colorectal cancer. This study aimed to investigate the therapeutic effect of Mon on lung cancer. The viability, apoptosis, invasion, and tube formation of A549 and H1299 were determined by CCK8 assay, flow cytometry, transwell assay, and tube formation assay. NF-κB expression in the nucleus was detected by immunofluorescent staining. In vivo assay, BALB/c nude mice were divided into a sham group and a 2mg/kg Mon group. For the Mon group, mice were orally administered with 2mg/kg Mon. The duration of the animal study was 35days, and the tumor formation and angiogenesis were investigated. Compared with the control (Mon 0μM) group, Mon dramatically repressed the viability, invasion, tube formation, proliferation marker Ki67, N-cadherin, and VEGFA expressions in A549 cells (Mon of 25, 50, and 100µM) and H1299 cells (Mon of 50 and 100µM). Mon dramatically promoted cell apoptosis, cleaved caspase 3, and E-cadherin expressions. Besides, Mon remarkably downregulated p-AKT and p-NF-κB protein expressions. Moreover, AKT agonist SC79 reversed the anticancer effects of 100µM Mon on A549 cells. Furthermore, Mon markedly suppressed tumor growth, decreased N-cadherin, VEGFA, p-AKT, and p-NF-κB expressions, increased apoptosis and E-cadherin expression, and SC79 reversed the inhibition effects of Mon in vivo. Thus, Mon is a potential antitumor natural drug, and more signaling pathways involved in Mon-modulated lung cancer progression are worth testing for further investigation.

Retraction: Down-regulation of lncRNA XIST inhibits cell proliferation via regulating miR-744/RING1 axis in non-small cell lung cancer.

Retraction: Down-regulation of lncRNA XIST inhibits cell proliferation via regulating miR-744/RING1 axis in non-small cell lung cancer.

Investigation into drug resistance to cisplatin in cancer stem cell-enriched population in non-small cell lung cancer

Investigation into drug resistance to cisplatin in cancer stem cell-enriched population in non-small cell lung cancer

Age-standardized mortality-to-incidence ratio for lung cancer in the world.

Age-standardized mortality-to-incidence ratio for lung cancer in the world.

Association between airway microbiota and systemic inflammation markers in non-small cell lung cancer patients

Growing evidences have suggested the airway microbiota may participate in lung cancer progression. However, little was known about the relationship between airway microbiota and lung cancer associated systemic inflammation. Here we aimed to explore the association between sputum microbiota and systemic inflammation in lung cancer. The microbiota of spontaneous sputum samples from 51 non-small cell lung cancer (NSCLC) patients and 6 patients with lung benign nodules were sequenced via 16 S rRNA sequencing. Neutrophil-lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR) and C reactive protein (CRP) were used to represent systemic inflammation. Patients were divided into 2 groups based on level of inflammatory biomarkers respectively (CRP_low versus CRP_high; NLR_low versus NLR_high; PLR_low versus PLR_high). α-diversity was significantly decreased in CRP_high and NLR_high patients. β diversity analysis based on weighted unifrac distance indicated that microbial community structure differed significantly between patients with different inflammation status. Lefse identified genera Porphyromonas, Selenomonas, Moryella, Megasphaera, Corynebacterium were enriched in CRP_low group. Compared with NLR_high, genera Veillonella, Neisseria, Bulleidia, Moryella were enriched in NLR_low group. For patients with different PLR level, genera Veillonella, Prevotella, Moryella, Selenomonas were increased in PLR_ low patients. Function analysis identified propionate metabolism pathway was significantly enriched in CRP_low and PLR_low groups. Moreover, RDA analysis showed that compared with PLR, NLR and CRP had strongest association with microbial community. Airway microbial structure differed between lung cancer with different systemic inflammation status. Patients with relative high inflammation status were associated with alteration of specific airway genera and microbial metabolic function.

Diagnostic utility of chest wall vessel involvement sign on ultra-high-resolution CT for primary lung cancer infiltrating the chest wall.

Chest wall infiltration in primary lung cancer affects the surgical and therapeutic strategies. This study evaluates the efficacy of the chest wall vessel involvement in subpleural lung cancer (CWVI) on ultra-high-resolution CT (UHR-CT) for detecting chest wall invasion. A retrospective analysis of lung cancer cases with confirmed pleural and chest wall invasion was conducted from November 2019 to April 2022. Seventy-seven patients (mean ± standard deviation age 70 ± 8 years, 64 males) who underwent preoperative contrast-enhanced UHR-CT were included. They were grouped into 51 non-chest wall infiltration (pl1 and pl2) and 26 chest wall infiltration (pl3). Clinical, histopathological, and UHR-CT findings were reviewed. Upper lobe tumors exhibited a higher chest wall invasion rate (p < 0.001). Rib destruction was evident in five patients with chest wall invasion but none with pleural invasion (p < 0.001). CWVI was present in 19 of 26 patients with chest wall invasion and 2 of 51 patients with pleural invasion (p < 0.001). The maximum tumor diameter (Dmax), arch distance which means the interface length between the primary tumor and the chest wall (Adist), and the ratio of Dmax to Adist were higher in chest wall invasion cases (all p < 0.001). After excluding patients with rib destruction, in multivariate logistic regression analysis, only CWVI was a significant predictor for chest wall invasion (odds ratio 29.22 (95% confidence interval 9.13-262.90), p < 0.001). CWVI on UHR-CT can help diagnose lung cancer infiltrating the chest wall, offering a potential tool for clinical decision-making. Question Chest wall infiltration in primary lung cancer has implications for the treatment plan, but diagnosis is often difficult with conventional CT. Findings Chest wall vessel involvement in subpleural lung cancer on ultra-high-resolution CT is a valuable predictor for diagnosing chest wall infiltration. Clinical relevance The delineation of chest wall vessels with contrast-enhanced ultra-high-resolution CT may improve the diagnosis of chest wall infiltration and allow accurate staging and optimal treatment options for subpleural primary lung cancer.

Epidemiology of Cancer in the Fiji Islands: 2010 to 2018.

Cancer is a global public health concern with increasing incidence and mortality rates, particularly in low- and middle-income countries (LMICs) like the Pacific Island Countries and Territories (PICTs). Among the PICTs, Fiji faces a growing burden of cancer. This study aimed to analyze cancer incidence and mortality data in Fiji from 2010 to 2018 to identify trends and provide an update on the current cancer-related statistics in the Fiji Islands. The top three cancer incidence rates among women were breast, cervical, and endometrial cancer, whereas prostate, liver, and lung cancer were the most prevalent among men. Notably, the central division had higher cancer incidence rates, whereas the northern division had a disproportionately higher mortality rate. Factors contributing to these trends may include lifestyle behaviors, limited access to health care in certain regions, and low awareness. Although this study has limitations due to data quality, it emphasizes the need for targeted interventions, accurate data reporting, and improved cancer treatment delivery to reduce the burden of cancer in Fiji.

Remote symptom monitoring with patient-reported outcomes and nudges during lung cancer immunotherapy in China (PRO-NET): protocol for a randomised controlled trial

IntroductionLung cancer is the leading cause of cancer-related mortality globally, with non-small cell lung cancer (NSCLC) comprising the majority of cases. For advanced NSCLC, immunotherapy offers substantial survival benefits but...

Risk of second primary malignancies among survivors of cutaneous melanoma: A nationwide population-based study in the Republic of Korea

There is limited data on the risk of second primary malignancies (SPMs) in Asian melanoma survivors. This study aimed to identify the risk of SPMs in Asian melanoma survivors. Standardized incidence ratios (SIRs) were calculated for overall and specific SPMs. The risk factor for overall SPM development was analyzed using a multivariable Cox regression model. A total of 10,070 patients with melanoma were included in the study. Melanoma survivors exhibited an increased risk of overall SPM (SIR, 1.51; 95% confidence interval [CI], 1.34–1.70). Additionally, specific SPMs were more common among melanoma survivors, including nonmelanoma skin cancer, oral cavity and pharyngeal cancer, renal cancer, female breast cancer, lung cancer, pancreatic cancer, and liver cancer. Independent risk factors for overall SPM development included a Charlson Comorbidity Index ≥ 1 (adjusted hazard ratio [aHR], 1.41; 95% CI, 1.07–1.87), and a body mass index ≥ 25 kg/m2 (aHR, 1.47; 95% CI, 1.04–2.08). Inherent uncertainty related to diagnostic codes may exist. The risk of overall and specific SPMs was significantly elevated in Asian melanoma survivors, particularly among those with invasive melanoma. Among modifiable factors, a high body mass index (BMI) was associated with an increased risk of SPM.

Design, Structure Optimization, and Preclinical Characterization of JAB-21822, a Covalent Inhibitor of KRASG12C.

KRAS is the most frequently mutated driver oncogene in human cancer, and KRASG12C mutation is commonly found in non-small-cell lung cancer (NSCLC), colorectal cancer (CRC), and pancreatic ductal adenocarcinoma (PDAC). Inhibitors that covalently modify the mutated codon 12 cysteine have completed proof-of-concept studies in the clinic. Here, we describe structure-based design and cocrystal-aided drug optimization of a series of compounds with the 1,8-naphthyridine-3-carbonitrile scaffold. Biopharmaceutical optimization of the resulting leads to improve the solubility of the compounds and block the possible metabolic hotspots led to the identification of JAB-21822, a covalent KRASG12C inhibitor with high potency and excellent cross-species pharmacokinetic properties. JAB-21822 has finished the pivotal Phase II clinical trials in NSCLC, and a new drug application was submitted to the National Medical Products Administration in 2024.

Long-term survival from a randomized controlled trial of lobectomy by video-assisted thoracoscopic surgery versus thoracotomy for early-stage lung cancer.

We previously did a randomized clinical trial of lobectomy by VATS or thoracotomy for early-stage lung cancer and found that patients who underwent VATS had less postoperative pain and better quality of life compared with thoracotomy. VATS has since been regarded the preferred surgical method for early-stage lung cancer. It is assumed that long-term survival is not influenced by surgical approach, but this assumption primarily rests on non-randomized comparative studies. We decided to do a long-term follow-up of patients who entered our previous randomized trial. Between 2008 and 2014 we randomly assigned 206 patients to VATS (n = 103) or anterolateral thoracotomy (n = 103) for proven or suspected early-stage NSCLC. Records from patients with NSCLC on final pathology were identified in the national electronic patient-record system and the Danish Lung Cancer Registry. Overall, disease-free, and cancer-specific survival were estimated using the Kaplan-Meier method and log-rank test was used to compare the two interventions. A total of 196 patients had NSCLC on final histopathology. Four patients were lost to follow-up and the remaining 192 were included in this follow-up study with 128 events used for overall survival analysis, 100 events for disease-free survival analysis and 79 events for cancer-specific survival analysis. VATS was used in 99 patients versus 93 by thoracotomy. Median age at time of surgery was 66 years (range 41-85 years). After a median follow-up time of 12.8 years (range 9.9-15.8 years), 33% of patients were alive. Overall, disease-free, and cancer-specific survival were not significantly different between VATS and thoracotomy: Overall survival (p = 0.29), disease-free survival (p = 0.17) and cancer-specific survival (p = 0.31). We did not find any statistically significant differences in overall, disease-free, or cancer-specific survival between VATS and thoracotomy. However, larger trials with better power for survival analysis are needed to fully explore if there are differences. Alternatively, differences in survival between thoracotomy and VATS for early-stage NSCLC could be investigated by pooling survival data from two similar randomized trials that have since been published.

Inhibition of Kinase Activity and In Vitro Downregulation of the Protein Kinases in Lung Cancer and Cervical Cancer Cell Lines and the Identified Known Anticancer Compounds of Ziziphus mucronata

Inhibition of Kinase Activity and In Vitro Downregulation of the Protein Kinases in Lung Cancer and Cervical Cancer Cell Lines and the Identified Known Anticancer Compounds of Ziziphus mucronata

A Non-invasive Lung Disease Study of Exhaled Breath Nitric Oxide Based on Ultraviolet Differential Absorption Spectroscopy Techniques.

In this study, a non-invasive device based on ultraviolet differential absorption spectroscopy (UV-DOAS) technology for detecting fractional exhaled nitric oxide (FeNO)was developed and clinically validated in patients with various lung diseases. The diagnostic potential of FeNO was explored by analysing subgroups of patients with lung cancer, nodules, and other disease. The results showed that FeNO concentrations were significantly higher in patients with malignant tumours than in healthy controls (p < 0.01). The diagnostic efficacy of FeNO in different lung diseases was confirmed by ROC analysis: the AUC values were 0.925 for malignant tumours, 0.925 for suspected malignant/benign tumours, 0.792 for benign lesions, and 0.938 for infectious/inflammatory diseases. The significant postoperative FeNO level decrease supports the diagnostic use of FeNO in different stages of the disease. Compared with conventional electrochemical, chemiluminescent and fluorescent probe methods, the UV-DOAS technique has significant advantages regarding sensitivity and portability, suggesting its potential for clinical application.

Global Burden of Tracheal, Bronchus, and Lung Cancer in Adults Over 55 Years Old Based on Socio demographic Status and Geographical and Gender Differences from 2010-2021

Global Burden of Tracheal, Bronchus, and Lung Cancer in Adults Over 55 Years Old Based on Socio demographic Status and Geographical and Gender Differences from 2010-2021

Lidocaine Inhibits the Proliferation of Non-Small Cell Lung Cancer and Exerts Anti-Inflammatory Effects Through the TLR-9/MyD88/NF-κB Pathway.

Lung cancer represents a significant global health burden, with non-small cell lung cancer (NSCLC) being the most common subtype. The current standard of care for NSCLC has limited efficacy, highlighting the necessity for innovative treatment options. Lidocaine, traditionally recognized as a local anesthetic, has emerged as a compound with potential antitumor and anti-inflammatory capabilities. This study was designed to explore the impact of lidocaine on NSCLC cell proliferation and inflammation, particularly focusing on the Toll-like receptor 9 (TLR)-9/MyD88/NF-κB signaling pathway. A nude mice model of NSCLC was employed, with animals receiving lidocaine at different concentrations. In vitro experiments on A549 cells involved exposure to lidocaine, followed by assessment of cell viability, cytokine expression, and TLR-9 levels using the 3-(4,5-Dimethylthiazol-2-Yl)-2,5-Diphenyltetrazolium Bromide (MTT) assay, enzyme-linked immunosorbent assay, and Quantitative Real-time polymerase chain reaction (qPCR). Protein levels were evaluated via Western blot analysis. Additionally, A549 cells were transfected with a TLR-9-overexpressing lentivirus to dissect the role of TLR-9 in lidocaine's mechanism of action. Treatment with lidocaine led to a significant reduction in tumor dimensions and a decrease in inflammatory marker expression in the NSCLC mouse model. In cellular assays, lidocaine effectively suppressed A549 cell proliferation and the expression of inflammatory cytokines. The overexpression of TLR-9 partially negated the suppressive effects of lidocaine, underscoring the significance of the TLR-9/MyD88/NF-κB pathway in mediating lidocaine's effects. Lidocaine's inhibitory effects on NSCLC cell proliferation and its anti-inflammatory mechanisms are mediated through the TLR-9/MyD88/NF-κB pathway. The study's results offer promising insights into the therapeutic potential of lidocaine in NSCLC and pave the way for future investigations into its application in cancer therapy.

Isolation and spectroscopic characterization of anticancer phytochemicals from Artemisia laciniata: a combined experimental and theoretical investigation using ADMET analysis and in silico molecular docking simulation against key cancer targets.

Artemisia laciniata, a high-altitude medicinal herb, possesses diverse therapeutic properties. This study conducted a comprehensive phytochemical analysis of the whole plant, leading to the isolation of 15 secondary metabolites (1-15) across various classes: flavonoids (1-6), triterpenoids (7, 8), sesquiterpenoid lactones (9, 10) and furanocoumarins (11, 12) along with three steroids (13-15). These compounds were characterized using NMR (1HNMR,13C NMR, 2D NMR), IR, HRMS and UV-VIS. All were reported for the first time from this plant, with compound 10 being a novel natural product. In-vitro antitumor activity was evaluated against lung (A549), colon (HCT116), prostate (PC3) and breast (T47D) cancer cell lines.Compounds 3, 4, 6, 7, 8 and 10demonstrated significant antitumor activity, with compounds 3, 7 and 8 exhibiting IC50 values 8 and 28 µM. In silico molecular docking and ADMET analysis were conducted to assess pharmacokinetics and pharmacodynamics, revealing strong binding affinities of compounds 3, 6, and 7, particularly with PD-L1, highlighting their potential to target multiple cancer-related pathways. This study concludes that A. laciniata contains potent anticancer phytochemicals that target key proteins involved in cancer development, as demonstrated by MTT assay results.

A human metabolic map of pharmacological perturbations reveals drug modes of action.

Understanding a small molecule's mode of action (MoA) is essential to guide the selection, optimization and clinical development of lead compounds. In this study, we used high-throughput non-targeted metabolomics to profile changes in 2,269 putative metabolites induced by 1,520 drugs in A549 lung cancer cells. Although only 26% of the drugs inhibited cell growth, 86% caused intracellular metabolic changes, which were largely conserved in two additional cancer cell lines. By testing more than 3.4 million drug-metabolite dependencies, we generated a lookup table of drug interference with metabolism, enabling high-throughput characterization of compounds across drug therapeutic classes in a single-pass screen. The identified metabolic changes revealed previously unknown effects of drugs, expanding their MoA annotations and potential therapeutic applications. We confirmed metabolome-based predictions for four new glucocorticoid receptor agonists, two unconventional 3-hydroxy-3-methylglutaryl-CoA (HMGCR) inhibitors and two dihydroorotate dehydrogenase (DHODH) inhibitors. Furthermore, we demonstrated that metabolome profiling complements other phenotypic and molecular profiling technologies, opening opportunities to increase the efficiency, scale and accuracy of preclinical drug discovery.