Lung Cancer Research Articles

Equity of access to pathological diagnosis and bronchoscopy for lung cancer in Aotearoa New Zealand

background: Māori are less likely to survive their lung cancer once diagnosed, but it remains unclear whether this is partially driven by poorer access to best-practice diagnostic services. methods: We examined all lung cancer registrations in Aotearoa New Zealand between 2007–2019 (n=27,869) linked to national administrative health datasets and further stratified by ethnicity, tumour type and stage of disease. Using descriptive and regression analyses, we compared ethnic groups in terms of the basis of diagnosis (e.g., histology, cytology), receipt of bronchoscopy and travel distance and time to access bronchoscopy. results: We found no differences in access to a pathological diagnosis between ethnic groups regardless of cancer type or stage. We found that Māori within the cohort were marginally more likely to access bronchoscopy than the majority European group; however, we also found that Māori had a lower odds of living close to the location of their bronchoscopy, and a correspondingly higher odds of living 100–200km (adjusted odds ratio [adj. OR] 1.46, 95% confidence interval [CI] 1.26–1.69) or more than 200km away (1.36, 95% CI 1.15–1.61) than Europeans. conclusion: Interventions that aim to further support Māori to overcome the systematic and cumulative disadvantages in access to cancer care should be broadly supported and resourced.

KI-gestützte Atemgasanalyse (E-Nose) zur Früherkennung von Lungenkarzinomen

Volatile organic compounds (VOCs) are an increasingly meaningful method for the early detection of various types of cancers, including lung cancer, through non-invasive methods. Traditional cancer detection techniques such as biopsies, imaging, and blood tests, though effective, often involve invasive procedures or are costly, time consuming, and painful. Recent advancements in technology have led to the exploration of VOC detection as a promising non-invasive and comfortable alternative. VOCs are organic chemicals that have a high vapor pressure at room temperature, making them readily detectable in breath, urine, and skin. The present study leverages artificial intelligence (AI) and machine learning algorithms to enhance classification accuracy and efficiency in detecting lung cancer through VOC analysis collected from exhaled breath air. Unlike other studies that primarily focus on identifying specific compounds, this study takes an agnostic approach, maximizing detection efficiency over the identification of specific compounds focusing on the overall compositional profiles and their differences across groups of patients. The results reported hereby uphold the potential of AI-driven techniques in revolutionizing early cancer detection methodologies towards their implementation in a clinical setting.

Morbidität und Mortalität nach NSCLC-Operationen bei älteren Patienten: Individualisierte Risikobewertung notwendig

Background: Reports from case series suggest that operative outcomes are comparable amongst different age groups following surgery with curative intent for non-small cell lung cancer (NSCLC). The purpose of this study was to compare morbidity and mortality after NSCLC surgery in older patients (≥ 75 years) versus younger patients (< 75 years) and identify independent predictive risk factors. Methods: We identified 2015 patients with postoperative stages IA to IIIA according to AJCC/UICC 7th edition who had undergone NSCLC surgery with curative intent at a single specialized lung cancer center from January 2010 to December 2015. A matched-pair analysis was performed on 227 older patients and corresponding 227 younger patients. Short-term surgical outcomes were postoperative morbidity, length of hospital stay, 30-day and 90-day mortality. Long-term operative outcomes were disease-free and overall survival. Results: 454 patients were included in the matched-pair analysis. 36% of younger patients developed postoperative complications versus 42% in older patients (p = 0.163). Age was not significantly associated with the occurrence of postoperative complications. Median length of hospital stay was 14 days in older patients and 13 days in younger patients (p = 0.185). 90-day mortality was 2.2% in younger patients compared to 4% in older patients (p = 0.424). In patients aged 75 and older impaired performance status (ECOG ≥ 1) was associated with decreased overall survival (HR = 2.15, CI 1.34–3.46), as were preoperative serum C-reactive protein / albumin ratio ≥ 0.3 (HR = 1.95, CI 1.23–3.11) and elevated preoperative serum creatinine levels ≥ 1.1 mg/dl (HR = 1.84, CI 1.15–2.95). In the younger cohort male sex (HR = 2.26, CI 1.17–4.36), postoperative stage III disease (HR 4.61, CI 2.23–9.54) and preoperative anemia (hemoglobin < 12 g/dl) (HR 2.09, CI 1.10–3.96) were associated with decreased overall survival.

Occult Non-small Cell Lung Cancer Presenting as Paraneoplastic Gastroparesis: A Case Report and Literature Review

Occult Non-small Cell Lung Cancer Presenting as Paraneoplastic Gastroparesis: A Case Report and Literature Review

The relationship between obstructive sleep apnea, dyspnea, and health-related quality of life in lung cancer survivors: a cross-sectional study in the Republic of Korea

The relationship between obstructive sleep apnea, dyspnea, and health-related quality of life in lung cancer survivors: a cross-sectional study in the Republic of Korea

Repurposing of sericin combined with dactolisib or vitamin D to combat non-small lung cancer cells through computational and biological investigations.

This study aims to repurpose sericin in combating non-small lung cancer cells (A549 and H460) by combining it with dactolisib or vitamin D to reduce the dose of dactolisib and boost the anticancer effectiveness of dactolisib and vitamin D. Therefore, the binding affinities of individual and combined drugs were examined using in silico and protein-protein interaction studies, targeting NF-κB, Cyclin D1, p-AKT, and VEGF1 proteins. The findings manifested remarkable affinities for combinatorial drugs compared to individual compounds. To substantiate these findings, the combined IC50 for each combination (sericin + dactolisib and sericin + vitamin D) were determined, reporting 31.9 and 41.8µg/ml, respectively, against A549 cells and 47.9 and 55.3µg/ml, respectively, against H460 cells. Furthermore, combination indices were assessed to lower the doses of each drug. Interestingly, in vitro results exhibited marked diminutions in NF-κB, Cyclin D1, p-AKT, and VEGF1 after treatment with sericin + dactolisib and sericin + vitamin D compared to control lung cancer cells and those treated with a single drug. Moreover, A549 and H460 cells treated with both combinations demonstrated augmented caspase-3 levels, implying substantial apoptotic activity. Altogether, these results accentuated the prospective implementation of sericin in combination with dactolisib and vitamin D at low doses to preclude lung cancer cell proliferation.

Epoxymicheliolide Reduces Radiation-Induced Senescence and Extracellular Matrix Formation by Disrupting NF-κB and TGF-β/SMAD Pathways in Lung Cancer.

Lung cancer is a major cause of cancer-related mortality, and radiotherapy is often limited by tumor resistance and side effects. This study explores whether epoxymicheliolide (ECL), a compound from feverfew, can enhance radiotherapy efficacy in lung cancer. We tested ECL on A549 and PC-9 lung cancer cell lines to evaluate its effect on x-ray irradiation. We measured apoptosis, NF-κB pathway inhibition, TGF-β secretion reduction, and epithelial-mesenchymal transition suppression. Invivo, C57BL/6 mice with lung tumors received ECL and radiotherapy. ECL enhanced the antiproliferative effects of x-ray irradiation, induced apoptosis in senescent cells, inhibited the NF-κB pathway, reduced TGF-β levels, and suppressed epithelial-mesenchymal transition. ECL also inhibited tumor growth and improved survival in mice. ECL is a promising adjunct to radiotherapy for lung cancer, improving treatment outcomes by targeting multiple tumor progression mechanisms. It offers potential for enhanced management of lung cancer.

Mechanisms of microRNA Regulation of the Epithelial–Mesenchymal Transition (EMT) in Lung Cancer

Lung cancer remains the cancer with the highest mortality worldwide, largely due to a limited understanding of the precise molecular mechanisms that drive its progression. microRNAs (miRNAs) have emerged as crucial regulators of lung cancer progression by influencing key cellular processes, notably the epithelial–mesenchymal transition (EMT). EMT is a complex and potentially reversible process where epithelial cells lose their polarity and adhesion, reorganize their cytoskeleton, and transition to a mesenchymal phenotype, enhancing their migratory and invasive capacities. While EMT plays an essential role in normal physiological contexts such as tissue development and wound healing, it is also a critical mechanism underlying the progression and metastasis of lung cancer. This review aims to summarize the latest research findings on the role of endogenous and exosome-derived microRNAs in regulating EMT in lung cancer, focusing on studies conducted over the past five years. It also provides an overview of EMT’s essential molecular mechanisms to better understand how miRNAs regulate EMT in lung cancer.

The clinical pathway in China county for lung cancer diagnosis and treatment (2024 edition)

Standardizing the diagnosis and treatment of lung cancer is a key measure to improve the survival rate of lung cancer patients and reduce the mortality rate. However, county hospitals generally face the problem of inaccessibility to advanced diagnostic and treatment technologies. Therefore, when developing quality control standards and clinical diagnosis and treatment specifications, it is necessary to combine the actual situation of county hospitals and formulate specific recommendations. The recommendations of treatment measures also need to consider the approval status of indications and whether it is included in the National Reimbursement Drug List (NRDL), to ensure the access to medicines. To address the above issues, based on the existing guidelines at home and abroad and the clinical work characteristics of county hospitals, the " the clinical pathway in China county for lung cancer diagnosis and treatment (2024 edition)" has been updated on the basis of the first edition. This pathway elaborated on the imaging diagnosis, pathological diagnosis, molecular testing, precision medicine, and developed different diagnosis and treatment processes for different types of lung cancer patients. Consistent with the first pathway, this update still divides the recommendations for diagnosis and treatment of clinical scenarios into basic strategies and optional strategies for elaboration. The basic strategies are the standards that county hospitals must meet, while the optional strategies provide more choices for hospitals, which are convenient for county doctors to put into clinical practice. All the recommended diagnostic and treatment plans strictly refer to existing guidelines and consensus. Compared to the first edition, based on the latest high-level evidence-based medicine and the approval status of indications, the pathway has updated the diagnosis and treatment recommendations for lung cancer under different pathological types, TNM classification, and molecular classification in basic and optional strategies.

Cardiotoxicity following thoracic radiotherapy for lung cancer.

Radiotherapy is the standard of care treatment for unresectable NSCLC, combined with concurrent chemotherapy and adjuvant immunotherapy. Despite technological advances in radiotherapy planning and delivery, the risk of damage to surrounding thoracic tissues remains high. Cardiac problems, including arrhythmia, heart failure and ischaemic events, occur in 20% of patients with lung cancer who undergo radiotherapy. As survival rates improve incrementally for this cohort, minimising the cardiovascular morbidity of RT is increasingly important. Problematically, the reporting of cardiac endpoints has been poor in thoracic radiotherapy clinical trials, and retrospective studies have been limited by the lack of standardisation of nomenclature and endpoints. How baseline cardiovascular profile and cardiac substructure radiation dose distribution impact the risk of cardiotoxicity is incompletely understood. As Thoracic Oncology departments seek to expand the indications for radiotherapy, and as the patient cohort becomes older and more comorbid, there is a pressing need for cardiotoxicity to be comprehensively characterised with sophisticated oncology, physics and cardio-oncology evaluations. This review synthesises the evidence base for cardiotoxicity in conventional radiotherapy, focusing on lung cancer, including current data, unmet clinical needs, and future scientific directions.

The association between breast cancer and lung cancer: a bidirectional Mendelian randomization study.

With increasing life spans, breast cancer (BC) survivors may face the possibility of developing second primary cancer (SPC), which can considerably shorten survival. Lung cancer (LC) is a common SPC among BC survivors. This study explored the association between these two cancers through Mendelian randomization (MR) analysis. A bidirectional two-sample MR analysis was conducted with BC genome-wide association study (GWAS) data from the Breast Cancer Association Consortium (BCAC) included 228,951 individuals and the GWAS summary statistics from the Transdisciplinary Research in Cancer of the Lung (TRICL) of LC included 112,781 individuals. The IVW method and MR-RAPS method showed a causal effect of overall BC on lung adenocarcinoma (LUAD) (IVW: OR = 1.060, 95% CI = 1.008-1.116, P = 0.024; MR-RAPS: OR = 1.059, 95% CI = 1.005-1.116, P = 0.033), which indicated that patients with BC had an increased risk of LUAD. However, there is no strong evidence for a causal effect of LUAD on BC. Our study revealed a causal effect of BC on second primary LUAD, suggesting that we should intensify screening for second primary LC in BC survivors. Early intervention and treatment for patients with second primary LC are needed to reduce mortality in BC survivors.

Non-small cell lung cancer detection through knowledge distillation approach with teaching assistant.

Non-small cell lung cancer (NSCLC) exhibits a comparatively slower rate of metastasis in contrast to small cell lung cancer, contributing to approximately 85% of the global patient population. In this work, leveraging CT scan images, we deploy a knowledge distillation technique within teaching assistant (TA) and student frameworks for NSCLC classification. We employed various deep learning models, CNN, VGG19, ResNet152v2, Swin, CCT, and ViT, and assigned roles as teacher, teaching assistant and student. Evaluation underscores exceptional model performance in performance metrics achieved via cost-sensitive learning and precise hyperparameter (alpha and temperature) fine-tuning, highlighting the model's efficiency in lung cancer tumor prediction and classification. The applied TA (ResNet152) and student (CNN) models achieved 90.99% and 94.53% test accuracies, respectively, with optimal hyperparameters (alpha = 0.7 and temperature = 7). The implementation of the TA framework improves the overall performance of the student model. After obtaining Shapley values, explainable AI is applied with a partition explainer to check each class's contribution, further enhancing the transparency of the implemented deep learning techniques. Finally, a web application designed to make it user-friendly and classify lung types in recently captured images. The execution of the three-stage knowledge distillation technique proved efficient with significantly reduced trainable parameters and training time applicable for memory-constrained edge devices.

Application of CT-based foundational AI and radiomics models for prediction of outcome for non-small-cell lung cancer patients treated on the NRG/RTOG 0617 clinical trial

Abstract Objectives To apply CT-based foundational artificial intelligence (AI) and radiomics models for predicting overall survival (OS) for patients with locally advanced non-small cell lung cancer (NSCLC). Methods Data for 449 patients retrospectively treated on the NRG Oncology/Radiation Therapy Oncology Group (RTOG) 0617 clinical trial were analyzed. Foundational AI, radiomics and clinical features were evaluated using univariate cox regression and correlational analyses to determine independent predictors of survival. Several models were fit using these predictors and model performance was evaluated using nested cross-validation and unseen independent test datasets via area under receiver-operator-characteristic curves, AUC’s. Results For all patients, the combined foundational AI and clinical models achieved AUCs of 0.67 for the Random Forest (RF) model. The combined radiomics and clinical models achieved RF AUCs of 0.66. In the low-dose arm, foundational AI alone achieved AUC of 0.67, while AUC for the ensemble radiomics and clinical models was 0.65 for the support vector machine (SVM). In the high-dose arm, AUC values were 0.67 for combined radiomics and clinical models and 0.66 for the foundational AI model. Conclusions This study demonstrated encouraging results for application of foundational AI and radiomics models for prediction of outcomes. More research is warranted to understand the value of ensemble models toward improving performance via complementary information. Advances in knowledge Using foundational AI and radiomics-based models we were able to identify significant signatures of outcomes for NSCLC patients retrospectively treated on a national cooperative group clinical trial. Associated models will be important for application toward prospective patients.

A study protocol for a mixed-method environmental scan of contextual factors that influence lung cancer screening adherence.

The efficacy of lung cancer screening (LCS) to reduce lung cancer specific mortality is heavily dependent on adherence to recommended screening guidelines, with real-world adherence rates reported to be drastically lower than rates described in clinical trials. There is a dearth in the literature on reminder processes and clinical workflows used to address adherence and robust data is needed to fully understand which clinical set-ups, processes, and context enhance and increase continued LCS participation. This paper describes a protocol for an environmental scan of adherence and reminder processes that are currently used in LCS programs across the United States. This study will triangulate data using a 3-step explanatory sequential mixed methods design to describe mechanisms of current adherence and reminder systems within academic and community LCS programs to pinpoint clinic or system barrier and facilitator combinations that contribute to increased adherence. In step 1, surveys from a nationally representative sample of LCS programs will yield quantitative data about program structure, volume, and tracking/reminder processes and messages. After completion of the survey, interested LCS program personnel will be invited to participate in an in-depth interview (step 2) to explore current processes and interventions used for adherence at the participant and program level. Finally, in step 3, triangulation of quantitative and qualitative data will be completed through qualitative comparative analysis to identify combinations of components that affect higher or lower adherence. This research advances the state of the science by filling a gap in knowledge about LCS program characteristics and processes associated with better adherence which can inform the development and implementation of interventions that are scalable and sustainable across a wide variety of clinical practice settings.

Ultrasensitive In2O3-Based Nanoflakes for Lung Cancer Diagnosis and the Sensing Mechanism Investigated by Operando Spectroscopy.

Rapid gas sensing with high sensitivity and selectivity is pivotal in advanced production, in smart living, and increasingly in medical health applications. This study presents a novel Pt@InNiOx nanoflake isoprene sensor that achieves an exceptionally low limit of detection (LOD) at 2 ppb, the lowest reported for isoprene sensors to date. Notably, it exhibits high selectivity and remarkable antihumidity capacity, thus meeting the stringent requirements for lung cancer screening. To unravel the sensing mechanism, we fabricate an operando DRIFTS-Raman cell coupled to online electrical measurements. It reveals that the ultrasensitive performance of Pt@InNiOx nanoflakes stems from the activated conjugated structure of isoprene by Pt nanoclusters and from the enhanced isoprene adsorption and electron interaction due to the nanoflake morphology. The p-n junction constructed by doping Ni maintains Fermi level equilibrium, shielding it from humidity interference. Practically, we integrate these ultrasensitive Pt@InNiOx nanoflakes into a miniaturized portable electronic device that successfully distinguishes lung cancer patients with expiratory isoprene below 40 ppb, from the healthy population with isoprene above 60 ppb, enabling an accurate diagnosis in clinics. Our work not only provides a breakthrough in low-cost, noninvasive cancer screening through breath analysis but also advances the rational design of cutting-edge gas sensing materials.

Case report: A golden tail of immunotherapy: significant tail effect in a chemotherapy-resistant advanced pulmonary sarcomatoid carcinoma patient treated by Sintilimab combined with Anlotinib

Tail effect is a unique phenomenon in immunotherapy characterized by the prolonged maintenance of therapeutic efficacy. It can be observable even after treatment cessation. Immunotherapy has gradually become a vital regimen for the treatment of advanced lung cancer patients, among which immune-combined therapies based on immune checkpoint inhibitors (ICIs) have been applied clinically and demonstrates considerable clinical efficacy. In this case report, the patient was pathologically diagnosed with pulmonary sarcomatoid carcinoma (PSC), a rare and highly aggressive subtype of non-small cell lung cancer (NSCLC) known for its poor prognosis due to high invasiveness and metastatic potential. After developing resistance to chemotherapy, the patient was treated with a combined regimen of sintilimab and anlotinib, leading to initial clinical improvement. Following just three cycles of this regimen, treatment was discontinued, and the patient was discharged. Remarkably, over the subsequent months, the patient exhibited a significant tail effect, evidenced by sustained therapeutic stability, continuous tumor regression, stable low levels of serum carcinoembryonic antigen (CEA), and further improvement in clinical symptoms. Tail effect is a golden tail of immunotherapy. This case illustrates that the tail effect of immunotherapy can offer substantial survival benefits for patients with unresectable advanced lung cancer who have failed chemotherapy.

Complex shape markers can detect alterations in the spatial distribution of cell nuclei in human lung squamous cell carcinoma: a useful tool for automatic analysis?

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.

Imbalance of redox homeostasis and altered cellular signaling induced by the metal complexes of terpyridine.

Compounds that can induce oxidative stress in cancer cells while remaining nontoxic to healthy cells are extremely promising for potential anticancer drugs. 2,2':6',2''-terpyridine-metal complexes possess these properties. The high level of activity (IC50 = 0.605 µM) of 2,2':6',2''-terpyridine-metal complexes on lung, breast, pancreatic, and glioblastoma multiforme cancer lines and their selectivity (SI > 41.32) on human normal fibroblasts were confirmed and presented in this paper. The mechanism of action of these compounds is associated with the generation of reactive oxygen species, which affects several cellular pathways and signals. The results demonstrate that 2,2':6',2''-terpyridine-metal complexes affect cell cycle inhibition in the G0/G1 phase as well as the activation of apoptosis and autophagy cell death. These results were confirmed in several independent studies, including experiments measuring the fluorescence levels of reactive oxygen species, flow cytometry, and gene and protein analysis.

SARS-CoV-2 nucleocapsid protein interaction with YBX1 displays oncolytic properties through PKM mRNA destabilization.

SARS-CoV-2, a highly contagious coronavirus, is responsible for the global pandemic of COVID-19 in 2019. Currently, it remains uncertain whether SARS-CoV-2 possesses oncogenic or oncolytic potential in influencing tumor progression. Therefore, it is important to evaluate the clinical and functional role of SARS-CoV-2 on tumor progression. Here, we integrated bioinformatic analysis of COVID-19 RNA-seq data from the GEO database and performed functional studies to explore the regulatory role of SARS-CoV-2 in solid tumor progression, including lung, colon, kidney and liver cancer. Our results demonstrate that infection with SARS-CoV-2 is associated with a decreased expression of genes associated with cancer proliferation and metastasis in lung tissues from patients diagnosed with COVID-19. Several cancer proliferation or metastasis related genes were frequently downregulated in SARS-CoV-2 infected intestinal organoids and human colon carcinoma cells.In vivo and in vitro studies revealed that SARS-CoV-2 nucleocapsid (N) protein inhibits colon and kidney tumor growth and metastasis through the N-terminal (NTD) and the C-terminal domain (CTD). The molecular mechanism indicates that the N protein of SARS-CoV-2 interacts with YBX1, resulting in the recruitment of PKM mRNA into stress granules mediated by G3BP1. This process ultimately destabilizes PKM expression and suppresses glycolysis. Our study reveals a new function of SARS-CoV-2nucleocapsid protein on tumor progression.

Ensemble learning based lung and colon cancer classification with pre-trained deep neural networks

Ensemble learning based lung and colon cancer classification with pre-trained deep neural networks