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Hydrogen sulfide (H₂S), a metabolite of the transsulfuration pathway, has been implicated in ferroptosis, a unique form of cell death caused by lipid peroxidation. While the exact mechanisms controlling ferroptosis remain unclear, our study reveals that H₂S sensitizes human non-small cell lung cancer (NSCLC) cells to this process, particularly when cysteine levels are low. Combining H₂S with cystine depletion significantly enhances the effectiveness of ferroptosis-based cancer therapy. Mechanistically, H₂S persulfidates the 195 th cysteine on S-adenosyl homocysteine hydrolase (SAHH), reducing its enzymatic activity. This leads to decreased homocysteine levels, subsequently lowering cysteine and glutathione concentrations under cystine depletion conditions. These changes ultimately increase the vulnerability of NSCLC cells to ferroptosis. Our findings establish H₂S as a key regulator of homocysteine metabolism and a critical factor in determining NSCLC cell susceptibility to ferroptosis. These results highlight the potential of H₂S-based therapies to improve the efficacy of ferroptosis-targeted cancer treatments for NSCLC., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: This study analyzes symptoms in lung cancer patients undergoing immunotherapy to identify core symptom clusters through network analysis and lay a foundation for effective symptom management programs., Methods: The sample comprised 240 lung cancer patients receiving immunotherapy. Participants were assessed using the Memorial Symptom Assessment Scale. Exploratory factor analysis was used to extract symptom clusters, and network analysis using JASP 0.17.3 was performed to explore the centrality indices and density of the symptom network., Results: Five symptom clusters were identified, i.e., emotion-related, lung cancer-related, physical, skin, and neural symptom clusters, with a cumulative variance contribution rate of 55.819%. Network analysis revealed that sadness was the most intense symptom (r s  = 2.189), dizziness was the most central symptom (r c  = 1.388), and fatigue was the most significant bridging symptom (r b  = 2.575)., Conclusion: This study identified five symptom clusters and a symptom network among lung cancer patients during immunotherapy. The network analysis's centrality indices and network density results can assist healthcare professionals in devising more precise symptom management strategies., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: A Two-sample Mendelian randomization (MR) Analysis was used to assess the causal relationship between non-small cell lung cancer (NSCLC) and sepsis., Method: Single nucleotide polymorphisms (SNPs) closely associated with NSCLC were utilized as instrumental variables (IVs) in this study. The Inverse Variance Weighted (IVW) method was used as the primary method for MR analysis, supplemented by the Weighted median, Weighted model, and MR-Egger regression method. Sensitivity analysis was conducted to improve result robustness, and data from various sources were validated and integrated. Bonferroni tests were applied to adjust for multiple comparisons., Results: After Bonferroni tests correcting the combined results, MR analysis revealed a significant association between genetically predicted NSCLC and an increased susceptibility to sepsis (odds ratios [OR]: 1.140, 95% confidence interval [CI]: 1.085-1.199, P = 2.61 × 10 - 7 ). The combined results demonstrated that NSCLC is associated with a heightened risk of sepsis in patients under 75 years of age (OR: 1.085, 95%CI: 1.037-1.353, P = 3.84 × 10 - 4 ). Furthermore, lung adenocarcinoma (LUAD) was found to be potentially associated with an increased susceptibility to sepsis (OR: 1.040, 95% CI: 1.009-1.073, P = 1.16 × 10 - 2 ). These results withstood multiple sensitivity analyses, demonstrating their robustness., Conclusion: This study confirms that NSCLC can significantly increase susceptibility to sepsis at the genetic level, providing valuable insights for the early identification of individuals at risk for sepsis., (© 2024. The Author(s).)

Background: Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine tumor with high mortality, and only a limited subset of extensive-stage SCLC (ES-SCLC) patients demonstrate prolonged survival under chemoimmunotherapy, which warrants the exploration of reliable biomarkers. Herein, we built a machine learning-based model using pathomics features extracted from hematoxylin and eosin (H&E)-stained images to classify prognosis and explore its potential association with genomics and TIME., Methods: We retrospectively recruited ES-SCLC patients receiving first-line chemoimmunotherapy at Nanjing Jinling Hospital between April 2020 and August 2023. Digital H&E-stained whole-slide images were acquired, and targeted next-generation sequencing, programmed death ligand-1 staining, and multiplex immunohistochemical staining for immune cells were performed on a subset of patients. A random survival forest (RSF) model encompassing clinical and pathomics features was established to predict overall survival. The function of putative genes was assessed via single-cell RNA sequencing., Results and Conclusion: During the median follow-up period of 12.12 months, 118 ES-SCLC patients receiving first-line immunotherapy were recruited. The RSF model utilizing three pathomics features and liver metastases, bone metastases, smoking status, and lactate dehydrogenase, could predict the survival of first-line chemoimmunotherapy in patients with ES-SCLC with favorable discrimination and calibration. Underlyingly, the higher RSF-Score potentially indicated more infiltration of CD8 + T cells in the stroma as well as a greater probability of MCL-1 amplification and EP300 mutation. At the single-cell level, MCL-1 was associated with TNFA-NFKB signaling and apoptosis-related processes. Hopefully, this noninvasive model could act as a biomarker for immunotherapy, potentially facilitating precision medicine in the management of ES-SCLC., (© 2024. The Author(s).)

Importance: The impact of patient-specific, disease-related, and social factors on outcomes in limited-stage small cell lung cancer (LS-SCLC) is not well defined. A post hoc secondary analysis of such factors from the Cancer and Leukemia Group B (CALGB) 30610-Radiation Therapy Oncology Group (RTOG) 0538 trial may impact future trial design., Objective: To assess the comprehensive demographic, disease-related, treatment-related, and social factors for potential associations with survival outcomes and understand whether specific subpopulations may benefit from radiotherapy (RT) dose escalation in LS-SCLC., Design, Setting, and Participants: This post hoc secondary analysis of a randomized clinical trial included 638 adults with LS-SCLC treated at 186 unique treatment sites with at least 1 accrual for all patients from March 15, 2008, to December 1, 2019; 313 patients were randomized to receive RT twice daily to a dosage of 45 Gy for 3 weeks and 325 to receive RT once daily to a dosage of 70 Gy for 7 weeks. Data were locked February 28, 2022, and analyzed from November 28, 2022, to June 4, 2024., Interventions: Twice-daily RT or once-daily RT., Main Outcomes and Measures: Multivariable Cox proportional hazards models evaluated the association of treatment groups and other risk factors with progression-free survival (PFS) and overall survival (OS). Patient-specific factors included age, sex, and Eastern Cooperative Oncology Group performance status. Disease-related factors included tumor, nodal, and overall cancer stages. Treatment-related factors included type of chemotherapy, timing of concurrent RT, RT technique, and prophylactic cranial irradiation. Social factors included marital status and treatment center accrual volume., Results: Among 507 patients (260 [51.3%] female and 247 [48.7%] male; mean [SD] age, 62.6 [7.9] years) included in the multivariate survival analysis, with a median follow-up of 4.7 (IQR, 3.7-7.1) years, female sex was associated with improved OS (hazard ratio [HR], 0.73 [95% CI, 0.58-0.91]; P = .006), while being 70 years or older was associated with decreased OS (HR, 1.50 [95% CI, 1.14-1.98]; P = .004). Neither age nor sex was associated with PFS. When compared with those with N1 disease, OS and PFS were worse in patients with N2 (HRs, 1.64 [95% CI, 1.19-2.26]; P = .002 and 1.36 [95% CI, 1.02-1.81]; P = .04, respectively) and N3 (HRs, 2.03 [95% CI, 1.40-2.93]; P < .001 and 1.63 [95% CI, 1.17-2.26]; P = .004) disease. Compared with stage II cancer, OS was worse for stage IIIA (HR, 1.65 [95% CI, 1.17-2.31]; P = .004) and stage IIIB (HR, 1.94 [95% CI, 1.34-2.83]; P < .001). Compared with high-volume accrual centers, treatment at low- or middle-volume accrual centers was associated with worse PFS (HRs, 1.94 [95% CI, 1.33-2.82; P < .001] and 1.44 [95% CI, 1.15-1.82; P = .002], respectively) and worse OS (HRs, 1.55 [95% CI, 1.03-2.32; P = .03] and 1.33 [95% CI, 1.04-1.70; P = .02], respectively)., Conclusions and Relevance: This secondary analysis of the CALGB 30610-RTOG 0538 randomized clinical trial of patients with LS-SCLC found associations between female sex or being younger than 70 years and improved overall survival and between advanced nodal stage or treatment at low- or middle-volume accrual centers and worse outcomes. These findings suggest that stratification by nodal stage, clinical stage, and age should be considered in future randomized trials., Trial Registration: ClinicalTrials.gov Identifier: NCT00632853.

Introduction: There is an urgent clinical need to accurately predict the risk for disease progression in post-treatment NSCLC patients, yet current ctDNA mutation profiling approaches are limited by low sensitivity. We represent a non-invasive liquid biopsy assay utilizing cfDNA neomer profiling for predicting disease progression in 44 inoperable localized NSCLC patients., Methods: A total of 97 plasma samples were collected at various time points during or post-treatments (TP1: 39, TP2: 33, TP3: 25). cfDNA neomer profiling, generated based on target sequencing data, was used to fit survival support vector machine models for each time point. Leave-one-out cross-validation (LOOCV) was performed to evaluate the models' predictive performances., Results: Our cfDNA neomer profiling assay showed excellent performance in detecting patients with a high risk for disease progression. At TP1, the high-risk patients detected by our model showed an increased risk of 3.62 times (hazard ratio [HR] = 3.62, p = 0.0026) for disease progression, compared to 3.91 times (HR = 3.91, p = 0.0022) and 4.00 times (HR = 4.00, p = 0.019) for TP2 and TP3. These neomer profiling determined HRs were higher than the ctDNA mutation-based results (HR = 2.08, p = 0.074; HR = 1.49, p&#x02009;=&#x02009;0.61) at TP1 and TP3. At TP1, the predictive model reached 40% sensitivity at 92.9% specificity, outperforming the mutation-based method (40% sensitivity at 78.6% specificity), while the combination results reached a higher sensitivity (60%). Finally, the longitudinal analysis showed that the combination of neomer and ctDNA mutation-based results could predict disease progression with an excellent sensitivity of 88.9% at 80% specificity., Conclusion: In conclusion, we developed a cfDNA neomer profiling assay for predicting disease progression in inoperable NSCLC patients. This assay showed increased predicting power during and post-treatment compared to the ctDNA mutation-based method, thus illustrating a great clinical potential to guide treatment decisions in inoperable NSCLC patients., Trial Registration: ClinicalTrials.gov: NCT04014465., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Randomized controlled trials (RCTs) have unequivocally established the therapeutic advantages of combining immune checkpoint inhibitors (ICIs) with chemotherapy in the treatment of early-stage non-small cell lung cancer (NSCLC). Presently, numerous perioperative immunotherapy regimens centered around the integration of ICIs and chemotherapy have undergone clinical trials. Nonetheless, due to the absence of direct comparative RCTs among these treatment regimens, this study aims to employ Bayesian network meta-analysis to ascertain the optimal combination of ICIs and chemotherapy., Methods: A systematic literature search was conducted in PubMed, EMBASE, Cochrane Library, Web of Science databases, and major international conference publications up to April 10, 2024. This comprehensive search yielded a total of 1434 studies. Following a rigorous screening process that involved evaluating the studies for relevance, methodological quality, and alignment with our research objectives, 8 studies were carefully selected for inclusion in the final analysis. Based on these curated search results, a systematic review and network meta-analysis were conducted., Results: 8 RCTs were included, encompassing 7 treatments and involving 3699 operable NSCLC patients at stages I-III. Compared to chemotherapy alone, perioperative immunotherapy demonstrated higher efficacy. The combination of toripalimab and chemotherapy showed the most significant improvement in event-free survival (EFS) (HR= 0.40; 95% CI, 0.28-0.58). The regimen that most notably enhanced overall survival (OS) was Nivolumab combined with chemotherapy (HR = 0.62; 95% CI, 0.36-1.07). In terms of pathological complete response (pCR), the combination of Toripalimab and chemotherapy exhibited the highest benefit (OR = 32.89; 95% CI, 7.88-137.32). Regarding the improvement in R0 resection, Pembrolizumab plus chemotherapy performed most prominently(OR=2.15; 95% CI, 1.30-3.56). In terms of the incidence of grade 3 or higher adverse events, durvalumab combined with chemotherapy had the lowest incidence (OR = 1.05; 95% CI, 0.79-1.38), while the incidence for other regimens was higher than chemotherapy alone., Conclusion: The efficacy of perioperative immunotherapy plus chemotherapy in patients with early NSCLC is significantly improved compared to chemotherapy alone. Although there is a certain risk of adverse events, the safety is within a controllable range. After a comprehensive evaluation of five endpoints in this study, it is believed that the combination of Toripalimab or Nivolumab with chemotherapy may be the optimal immunotherapy regimen for the treatment of stage Ib-IIIb NSCLC. These findings will help guide the design of clinical treatment plans and ICIs selection., Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier CRD42024536799., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Chen, Wang, Yue, Chen, Zhu, Cui, Zhang, Jin and Xiao.)

Non-small cell lung cancer (NSCLC) is a lethal malignancy. There is mounting evidence indicating that lncRNAs are crucial players with dual roles as both biomarkers and regulators across various cancers. It was reported that LINC00941 plays a cancer-promoting role in NSCLC. However, its impact on tumour autophagy remains poorly understood. In this study, we developed a risk assessment model and identified an autophagy-related lncRNA LINC00941, which has independent predictive and early diagnostic potential. Using RT-qPCR analysis, we confirmed the upregulation of LINC00941 in tumour tissues and cell lines of human lung adenocarcinoma (LUAD). Functional assays, such as CCK8, colony formation and xenograft models, demonstrated the cancer-promoting activity of LINC00941 both in vitro and in vivo. Further analysis using Western blotting analysis, mRFP-GFP-LC3 double fluorescence lentivirus vector and transmission electron microscopy (TEM) confirmed that the knockdown of LINC00941 triggered autophagy. These results indicate that knockdown of LINC00941 induces autophagy and impairs the proliferation of LUAD. Therefore, we propose LINC00941 as an independent biomarker for early diagnosis as well as a therapeutic target in LUAD., (© 2024 The Author(s). Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.)

Objectives: The goal was to explore clinical factors and build a predictive model for the disease-free and overall survival of patients with non-small cell lung cancer (NSCLC) receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors., Methods: Inclusion criteria for patients in this multicentre study were as follows: (i) Patients who were diagnosed with stages I-III NSCLC after a bronchoscopy biopsy or puncture; (ii) patients who were examined with computed tomography/positron emission tomography-computed tomography before treatment and surgery; (iii) patients who received neoadjuvant chemotherapy combined with immune checkpoint inhibitors for 2 to 6 cycles preoperatively; (iv) patients whose peripheral blood indicators and tumour markers were assessed before treatment and preoperatively; (v) patients who underwent radical lung cancer surgery after neoadjuvant therapy. Cases were divided into high- and low-risk groups according to 78 clinical indicators based on a 10-fold Least Absolute Shrinkage and Selection Operator selection. We used Cox proportional hazards models to predict disease-free and overall survival. Then, we used time-dependent area under the curve and decision curve analyses to examine the accuracy of the results., Results: Data were collected continuously, and 212 and 85 cases were randomly assigned to training and testing sets, respectively. The area under the curve for the prediction of disease-free survival (training: 1 year, 0.83; 2 years, 0.81; 3 years, 0.83 versus testing: 1 year, 0.65; 2 years, 0.66; 3 years, 0.70), overall survival (training: 1 year, 0.86; 2 years, 0.85; 3 years, 0.86 versus testing: 1 year, 0.66; 2 years, 0.57; 3 years, 0.70) were determined. The coefficient factors including pathological response; preoperative tumour maximum diameter; preoperative lymph shorter diameter; preoperative tumour and lymph maximum standardized uptake value; change in tumour standardized uptake value preoperatively; and blood-related risk factors were favourably associated with prognosis (P < 0.001)., Conclusions: Our prediction model, which integrated data from preoperative positron emission tomography-CT, preoperative blood parameters and pathological response, was able to make highly accurate predictions for disease-free and overall survival in patients with NSCLC receiving neoadjuvant immunity with chemical therapy., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)

Scope: The association between a planetary and sustainable EAT-Lancet diet and lung cancer remains inconclusive, with limited exploration of the role of genetic susceptibility and inflammation., Methods and Results: The study includes 175 214 cancer-free participants in the UK Biobank. Fourteen food components are collected from a 24-h dietary recall questionnaire. A polygenic risk score is constructed through capturing the overall risk variants for lung cancer. Sixteen inflammatory biomarkers are assayed in blood samples. Participants with the highest EAT-Lancet diet scores (≥12) have a lower risk of lung cancer incidence (hazard ratio [HR] = 0.64, 95% confidence interval [CI]: 0.51-0.80) and mortality (HR = 0.65, 95% CI: 0.48-0.88), compared to those with the lowest EAT-Lancet diet scores (≤8). Interestingly, there is a significantly protective trend against both lung adenocarcinoma and lung squamous cell carcinoma with higher EAT-Lancet diet scores. Despite no significant interactions, a risk reduction trend for lung cancer is observed with increasing EAT-Lancet diet scores and decreasing genetic risk. Ten inflammatory biomarkers partially mediate the association between the EAT-Lancet diet and lung cancer risk., Conclusion: The study depicts a lower risk of lung cancer conferred by the EAT-Lancet diet associated with lower inflammation levels among individuals with diverse genetic predispositions., (© 2024 Wiley‐VCH GmbH.)

Purpose: Despite the generally favourable prognoses observed in patients with ALK-positive non-small cell lung cancer (NSCLC), there remains significant variability in clinical outcomes. The objective of this study is to enhance patient stratification by examining both the specific sites of gene fusion and the presence of co-occurring mutations., Methods: We collected retrospective clinical and pathological data on ALK-positive patients with locally advanced or metastatic disease. ALK fusion variants and concomitant mutations were identified through next-generation sequencing technology. We then assessed treatment efficacy via tumor response and survival metrics., Results: This study included a total of 59 patients, with 49 harboring echinoderm microtubule-associated protein-like 4 (EML4)-ALK fusions and 10 presenting with rare fusions. The median follow-up period was 33 months. Clinical outcomes between non-EML4-ALK and EML4-ALK patients were comparable. Among the EML4-ALK cohort, patients with longer variants (v1, v2, v8) demonstrated superior progression-free survival (PFS) (median PFS: 34 months vs. 11 months; hazard ratio [HR]: 2.28; P = 0.05) compared to those with shorter variants (v3, v5). Furthermore, patients treated with second-generation ALK inhibitors (ALKi) displayed a progression-free survival advantage (median PFS: not reached [NR] vs. 9 months; HR: 5.37; P = 0.013). Baseline TP53 co-mutation were linked with a substantially shorter OS (median OS,37 months vs. NR; HR 2.74; P = 0.047)., Conclusions: In ALK+ NSCLC, longer EML4-ALK variants correlate with improved prognosis and enhanced response to second-generation ALKi, while TP53 co-mutations indicate a negative prognosis., (© 2024. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).)

Objectives: To establish and validate a technetium 99m sestamibi ( 99m Tc-MIBI) single-photon emission computed tomography/computed tomography (SPECT/CT) nomogram for predicting non-small cell lung cancer (NSCLC). Comparing the diagnostic performance of early and delayed SPECT/CT nomogram, and compare the diagnostic performance of SPECT/CT radiomics models with single SPECT and CT radiomics models., Methods: This prospective study included 119 lesions (NSCLC: n = 92, benign pulmonary lesions: n = 27) from 103 patients (mean age: 59.68 ± 8.94 years). Patients underwent dual-phase 99m Tc-MIBI SPECT/CT imaging. They were divided into the training (n = 83) and validation (n = 36) cohorts. Logistic regression, support vector machine, random forest, and light-gradient boosting machine were applied to train and determine the optimal machine learning model. Then, combining radiomics score and clinical factors, establish nomograms for diagnosing NSCLC., Result: CYFRA21-1 was selected for constructing the clinical model. In early imaging, the areas under the curve (AUCs) of the clinical model, radiomics model, and nomogram were 0.571, 0.830, and 0.875, respectively. The nomogram performed better than the clinical model and similarly to the radiomics model (P=0.020, P=0.216), and there are no statistically significant differences in the predictive performance between the radiomics model and the clinical model (P=0.103). In delayed imaging, the AUC was 0.643, 0.888, and 0.893, respectively. The predictive performance of the nomogram was superior compared to the clinical model and comparable to the radiomics model (P=0.042, P=0.480), and the radiomics model also demonstrated superior diagnostic performance compared to the clinical model (P=0.049). Compared to early SPECT/CT results, the AUC values of the nomogram and radiomics models in the delayed phase were higher, although no statistical differences were found (P=0.831, P=0.568). In delayed imaging, the AUC of the radiomics models for CT and SPECT was 0.696 and 0.768, respectively, SPECT/CT radiomics exhibited significant differences compared with CT and SPECT alone (P=0.042, P=0.038)., Conclusion: Dual-phase 99m Tc-MIBI SPECT/CT nomograms and radiomics models can effectively predict NSCLC, providing an economically and non-invasive imaging method for diagnosing NSCLC, moreover, these findings provide a basis for early diagnosis and treatment strategies in NSCLC patients. Delayed-phase SPECT/CT imaging may offer greater practical value than early-phase imaging for diagnosing NSCLC. However, this novel approach necessitates further validation in larger, multi-center cohorts., Clinical Relevance: Radiomics nomogram based on SPECT/CT for discriminating NSCLC from benign lung lesions helps to aid early diagnosis and guide treatment., Key Points: Nomograms, based on dual-phase SPECT/CT, was constructed to discriminate between non-small cell lung cancer and benign lesions. SPECT/CT radiomics model has better predictive performance than SPECT and CT radiomics model., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: To evaluate the potential of whole-body dynamic (WBD) 2-deoxy-2-[ 18 F]fluoro-D-glucose positron emission tomography/computed tomography ([ 18 F]FDG PET/CT) multiparametric imaging in the differential diagnosis between benign and malignant lung lesions., Procedures: We retrospectively analyzed WBD PET/CT scans from patients with lung lesions performed between April 2020 and March 2023. Multiparametric images including standardized uptake value (SUV), metabolic rate (MR FDG ) and distribution volume (DV FDG ) were visually interpreted and compared. We adopted SUV max , metabolic tumor volume (MTV) and total lesion glycolysis (TLG) for semi-quantitative analysis, MR max and DV max values for quantitative analysis. We also collected the patients' clinical characteristics. The variables above with P-value < 0.05 in the univariate analysis were entered into a multivariate logistic regression. The statistically significant metrics were plotted on receiver-operating characteristic (ROC) curves., Results: A total of 60 patients were included for data evaluation. We found that most malignant lesions showed high uptake on MR FDG and SUV images, and low or absent uptake on DV FDG images, while benign lesions showed low uptake on MR FDG images and high uptake on DV FDG images. Most malignant lesions showed a characteristic pattern of gradually increasing FDG uptake, whereas benign lesions presented an initial rise with rapid fall, then kept stable at a low level. The AUC values of MR max and SUV max are 0.874 (95% CI: 0.763-0.946) and 0.792 (95% CI: 0.667-0.886), respectively. DeLong's test showed the difference between the areas is statistically significant (P < 0.001)., Conclusions: Our study demonstrated that dynamic [ 18 F]FDG PET/CT imaging based on the Patlak analysis was a more accurate method of distinguishing malignancies from benign lesions than conventional static PET/CT scans., (© 2024. The Author(s), under exclusive licence to World Molecular Imaging Society.)

Background: Programmed death receptor ligand 1 (PD-L1) tumor proportion score (TPS) and tumor mutational burden (TMB) are key predictive biomarkers for immune checkpoint inhibitor (ICI) efficacy in non-small-cell lung cancer (NSCLC). Data on their variation across multiple samples are limited., Patients and Methods: Patients with NSCLC and multiple PD-L1 TPS and/or TMB assessments were included. Clinicopathologic and genomic data were analyzed according to PD-L1 and TMB variation., Results: In total, 402 PD-L1 sample pairs and 413 TMB sample pairs were included. Concordance between pairs was moderate for PD-L1 (ρ = 0.53, P < 0.0001) and high for TMB (ρ = 0.80, P < 0.0001). Shorter time between biopsies correlated with higher concordance in PD-L1, but not in TMB. Major increases (ΔTPS ≥ +50%) and decreases (ΔTPS ≤ -50%) in PD-L1 were observed in 9.7% and 8.0% of cases, respectively. PD-L1, but not TMB, decreased with intervening ICI (P = 0.02). Acquired copy number loss of CD274, PDCD1LG2, and JAK2 were associated with major decrease in PD-L1 (q < 0.05). Among patients with multiple PD-L1 assessments before ICI, cases where all samples had a PD-L1 ≥1%, compared to cases with at least one sample with PD-L1 <1% and another with PD-L1 ≥1%, achieved improved objective response rate and progression-free survival (PFS). Among patients with at least one PD-L1 <1% and one ≥1% before ICI, cases where the most proximal sample was PD-L1 ≥1% had longer median PFS compared to cases where the most proximal PD-L1 was <1%. Among patients with multiple TMB assessments before ICI, patients with a TMB ≥10 mut/Mb based on the most recent assessment, as compared to those with a TMB <10 mut/Mb, achieved improved PFS and overall survival to ICI; instead, no differences were observed when patients were categorized using the oldest TMB assessment., Conclusions: Despite intrapatient concordance in PD-L1 and TMB, variation in these biomarkers can influence ICI outcomes, warranting consideration for reassessment before ICI initiation when feasible., (Copyright © 2024 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved.)

This study aimed to investigate the expression of SF3B1 in non-small cell lung cancer, and its clinical significance, biological function, and molecular mechanisms. SF3B1 mRNA and protein levels were elevated in both lung squamous cell carcinoma and lung adenocarcinoma (LUAD) tissues based on TCGA data and immunohistochemistry. Notably, high SF3B1 expression in LUAD was significantly associated with increased lymph node metastasis. Functional experiments involving SF3B1 knockdown and overexpression demonstrated that SF3B1 facilitated the proliferation, invasion, and migration of LUAD cells. Additionally, the SF3B1 inhibitor pladienolide-B attenuated the aggressive behavior of LUAD cells both in vitro and in vivo. RNA sequencing analysis indicated that differentially expressed genes in the SF3B1 knockdown and SF3B1 inhibitor groups were enriched in ferroptosis-related pathways compared to their respective control groups. The antiferroptotic role of SF3B1 in LUAD cells was validated by detecting glutathione depletion, lipid peroxidation, and observing morphological changes using transmission electron microscopy. This process was confirmed to be independent of apoptosis and autophagy, as evidenced by the effects of the ferroptosis inducer erastin, the apoptosis inhibitor Z-VAD-FMK, and the autophagy inhibitor 3-methyladenine. Rescue experiments indicated that the antiferroptotic role of SF3B1 in LUAD is partially mediated by upregulating the expression of SLC7A11., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: For the past 20 years, twice-daily thoracic radiotherapy with concurrent chemotherapy has been the treatment of choice for limited-stage small-cell lung cancer (LS-SCLC), which has a poor prognosis. We aimed to assess the efficacy and safety of high-dose, accelerated, hyperfractionated, twice-daily thoracic radiotherapy (54 Gy in 30 fractions) versus standard-dose radiotherapy (45 Gy in 30 fractions) as a first-line treatment for LS-SCLC., Methods: This open-label, randomised, phase 3 trial was performed at 16 public hospitals in China. The key inclusion criteria were patients aged 18-70 years, with histologically or cytologically confirmed LS-SCLC, who had an Eastern Cooperative Oncology Group (ECOG) performance status of 0-1, and who were previously untreated or had received one course of cisplatin or carboplatin and etoposide. Eligible patients were randomly assigned (1:1) to receive volumetric-modulated arc radiotherapy (VMAT) of 45 Gy in 30 fractions to the gross tumour volume or VMAT with a simultaneous integrated boost of 54 Gy in 30 fractions to the gross tumour volume starting 0-42 days after the first chemotherapy course. Both groups received 10 fractions of twice-daily thoracic radiotherapy per week. The planning target volume was 45 Gy in 30 fractions in both groups. Patients with responsive disease received prophylactic cranial radiotherapy (25 Gy in 10 fractions). Randomisation was performed using a centralised interactive web response system, stratified by ECOG performance status, disease stage, previous chemotherapy course, and chemotherapy choice. The primary outcome was overall survival in the intention-to-treat population. Safety was analysed in the as-treated population. This study was registered at ClinicalTrials.gov, NCT03214003., Findings: From June 30, 2017, to April 6, 2021, 224 patients (102 [46%] females and 122 [54%] males; median age 64 years [IQR 58-68]) were enrolled and randomly assigned to the 54 Gy group (n=108) or 45 Gy (n=116) group. The median follow-up was 46 months (IQR 33-56). The median overall survival was significantly longer in the 54 Gy group (60·7 months [95% CI 49·2-62·0]) than in the 45 Gy group (39·5 months [27·5-51·4]; hazard ratio 0·55 [95% CI 0·37-0·72]; p=0·003). Treatment was tolerable, and the chemotherapy-related and radiotherapy-related toxicities were similar between the groups. The grade 3-4 radiotherapy toxicities were oesophagitis (14 [13%] of 108 patients in the 54 Gy group vs 14 [12%] of 116 patients in the 45 Gy group; p=0·84) and pneumonitis (five [5%] of 108 patients vs seven [6%] of 116 patients; p=0·663). Only one treatment-related death occurred in the 54 Gy group (myocardial infarction). The study was prematurely terminated by an independent data safety monitoring board on April 30, 2021, based on evidence of sufficient clinical benefit., Interpretation: Compared with standard-dose thoracic radiotherapy (45 Gy), high-dose radiotherapy (54 Gy) improved overall survival without increasing toxicity in a cohort of patients aged 18-70 years with LS-SCLC. Our results support the use of twice-daily accelerated thoracic radiotherapy (54 Gy) with concurrent chemotherapy as an alternative first-line LS-SCLC treatment option., Funding: Chinese Society of Clinical Oncology-Linghang Cancer Research, the Wu Jieping Medical Foundation, and Clinical Research Fund For Distinguished Young Scholars of Peking University Cancer Hospital and Beijing Municipal Administration of Hospitals Incubating Program., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Though the heparin-protamine complex (HP complex) is a crucial system utilized in clinical settings, the metabolic pathways of this complex remain inadequately understood. Herein, the enzymatic degradation of the heparin-protamine complex by trypsin and its broader implications were investigated. By utilizing fluorescent gold nanoclusters liganded with the HP complex (AuNCs-HP complex), we observed significant morphological and spectral changes during enzymatic degradation. Experiments showed that AuNCs-HP complex could be degraded and cleaved into small fragments by trypsin. Moreover, the AuNCs-HP complex demonstrated its potential as a highly sensitive spectral sensing platform, enabling precise measurement of trypsin activity with an outstanding detection limit (0.34 ng mL -1 ). Additionally, we explored its utility for specific tumor cell detection, focusing on lung adenocarcinoma cells, and successfully identified their presence through distinctive fluorescence changes. These remarkable findings not only contribute valuable insights into targeted degradation systems but also offer promising opportunities for cancer biomarker detection. The AuNCs-HP complex serves as an innovative tool for real-time trypsin activity monitoring, paving the way for advanced biomedical applications., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Lung adenocarcinoma (LUAC) as the most common lung cancer, and its incidence is increasing. Complement factor B (CFB) is an important factor in the alternative complement pathway. CFB has been reported to be involved in the progression of many cancers, including in pancreatic cancer, cutaneous squamous cell carcinoma, and nasopharyngeal carcinoma, but the function and molecular mechanism of CFB in LUAC remains unclear. The present study aimed to explore the role of CFB in LUAC malignant progression. In our previous study, we found that CFB was downregulated expression in LUAC clinical samples. Here, we firstly detected the cell function in vitro. Cell proliferation and migration were increased, while cell apoptosis and cell cycle arrest were suppressed after CFB knockdown. Overexpression of CFB repressed the malignant progression of LUAC in vitro. Besides, in vivo experiments revealed that upregulation of CFB inhibited tumor growth and Ki67 expression. Additionally, our data indicated that CFB negatively regulated Ras/mitogen-activated protein kinase (MAPK) signaling pathway. Furthermore, upregulation of CFB inhibited the progression of LUAC was reversed by Ras/MAPK pathway activators (ML-098 or C16-PAF). Our study uncovered that CFB acts as a tumor suppressor repressed tumorigenesis of LUAC through inhibiting the Ras/MAPK pathway, suggesting that CFB may be a potential biomarker and therapeutic target for LUAC., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Environmentally persistent free radicals (EPFRs) are generated in the combustion processes of solid waste and can cause adverse influences on human health, especially lung diseases. Lung cancer is one of the most serious malignancies in recent years, which the global deaths rate is about 1.6 million every year. Methods and Results: In this study, we verified that ZnO/MCB EPFRs promote cell proliferation and migration, impedes cell apoptosis in lung cancer. Furthermore, we found that ZnO/MCB could influence the expression of miRNAs (miR-18a and miR-34a). In vivo , ZnO/MCB and ZnO EPFRs can reduce the weight and survival rate of BALB/c male mice more than that of BALB/c female mice. In the ZnO/MCB exposed group, male mice lung became even smaller, while the female mice the lung increased significantly. Taken together, our results provide evidence for assessing the potential health risks of persistent free radicals on fine particles. Conclusions: This study linked toxicity of EPFRs with miRNAs revealed the potential health hazard to human lung cancer.

Abnormal metabolism has emerged as a prominent hallmark of cancer and plays a pivotal role in carcinogenesis and progression of lung adenocarcinoma (LUAD). In this study, single-cell sequencing revealed that the metabolic enzyme 6-phosphogluconate dehydrogenase (PGD), which is a critical regulator of the pentose phosphate pathway (PPP), is significantly upregulated in the malignant epithelial cell subpopulation during malignant progression. However, the precise functional significance of PGD in LUAD and its underlying mechanisms remain elusive. Through the integration of TCGA database analysis and LUAD tissue microarray data, it was found that PGD expression was significantly upregulated in LUAD and closely correlated with a poor prognosis in LUAD patients. Moreover, in vitro and in vivo analyses demonstrated that PGD knockout and inhibition of its activity mitigated the proliferation, migration, and invasion of LUAD cells. Mechanistically, immunoprecipitation-mass spectrometry (IP-MS) revealed for the first time that IQGAP1 is a robust novel interacting protein of PGD. PGD decreased p-AMPK levels by competitively interacting with the IQ domain of the known AMPKα binding partner IQGAP1, which promoted glycolysis and fatty acid synthesis in LUAD cells. Furthermore, we demonstrated that the combination of Physcion (a PGD-specific inhibitor) and metformin (an AMPK agonist) could inhibit tumor growth more effectively both in vivo and in vitro. Collectively, these findings suggest that PGD is a potential prognostic biomarker and therapeutic target for LUAD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Objectives: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Understanding the molecular mechanisms underlying tumor progression is of great clinical significance. This study aims to identify novel molecular markers associated with LUAD subtypes, with the goal of improving the precision of LUAD subtype classification. Additionally, optimization efforts are directed towards enhancing insights from the perspective of patient survival analysis., Materials and Methods: We propose an innovative feature-selection approach that focuses on LUAD classification, which is comprehensive and robust. The proposed method integrates multi-omics data from The Cancer Genome Atlas (TCGA) and leverages a synergistic combination of max-relevance and min-redundancy, least absolute shrinkage and selection operator, and Boruta algorithms. These selected features were deployed in six machine-learning classifiers: logistic regression, random forest, support vector machine, naive Bayes, k-Nearest Neighbor, and XGBoost., Results: The proposed approach achieved an area under the receiver operating characteristic curve (AUC) of 0.9958 for LR. Notably, the accuracy and AUC of a composite model incorporating copy number, methylation, as well as RNA- sequencing data for expression of exons, genes, and miRNA mature strands surpassed the accuracy and AUC metrics of models with single-omics data or other multi-omics combinations. Survival analyses, revealed the SVM classifier to elicit optimal classification, outperforming that achieved by TCGA. To enhance model interpretability, SHapley Additive exPlanations (SHAP) values were utilized to elucidate the impact of each feature on the predictions. Gene Ontology (GO) enrichment analysis identified significant biological processes, molecular functions, and cellular components associated with LUAD subtypes., Conclusion: In summary, our feature selection process, based on TCGA multi-omics data and combined with multiple machine learning classifiers, proficiently identifies molecular subtypes of lung adenocarcinoma and their corresponding significant genes. Our method could enhance the early detection and diagnosis of LUAD, expedite the development of targeted therapies and, ultimately, lengthen patient survival., Competing Interests: Declaration of Competing Interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled “Subclassification of Lung Adenocarcinoma through Comprehensive Multi-omics Data to Benefit Survival Outcomes”., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Gefitinib is an epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), which serves the critical pillar for the treatment of non-small cell lung cancer (NSCLC). However, the acquired resistance remains a challenge for its clinical application, for which, practical strategies to reverse gefitinib resistance in NSCLC are necessary. Ferroptosis, a programmed cell death driven by ferritin-dependent lipid peroxidation, involves in NSCLC progression and related chemoresistance. In our previous work, the self-synthesised EGFR inhibitor Yfq07 (N4, N6-disubstituted pyrimidine-4,6-diamine derivatives) displayed a considerable inhibitory effect on NSCLC both in vitro and in vivo. Herein, we observed that Yfq07 suppressed the proliferation of PC-9GR and HCC827GR cells, two gefitinib resistance NSCLC cell lines. Mechanically, Yfq07 inhibited the phosphorylation of the Discoidin Domain Receptor 1 (DDR1), a receptor tyrosine kinase (RTK) highly expressed in multiple cancers, accompanied by downregulated miR-3648 and upregulated SOCS2. Inhibition or knockdown of DDR1 suppressed the proliferation, migration, and invasion of gefitinib-resistant NSCLC cells, and on the other hand, also downregulated miR-3648 and promoted SOCS2 expression. More specifically, miR-3648 targeted the 3'UTR segment of SOCS2 mRNA and thus affecting the P-ERK signalling pathway to regulate the malignant behaviors of gefitinib-resistant NSCLC cells. Furthermore, Yfq07 also indirectly induced the ferroptosis of gefitinib-resistant NSCLC cells via SOCS2 triggered inhibition of xCT-GPX4 pathway. In conclusion, our study indicates that DDR1 inhibitor Yfq07 promotes ferroptosis and reverses gefitinib-resistance of NSCLC through DDR1-miR-3648-SOCS2 signalling pathway, which provides insights for targeted therapy of gefitinib-resistant NSCLC and drug developments targeting ferroptosis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: The main adjuvant therapies for anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer include ALK tyrosine kinase inhibitors (TKI) and chemotherapy. We aimed to compare differences in the incidence of thromboembolism (TE) among different treatment options., Design: Using a systematic review and Bayesian network meta-analysis (NMA)., Data Sources: We searched PubMed, Embase, Cochrane Library, ClinicalTrials.gov and Web of Science databases before 10 June 2023., Eligibility Criteria: We included published randomised controlled trials (RCT) involving comparisons of treatments between chemotherapy and ALK-TKI drugs., Data Extraction and Synthesis: Assessed risk bias with Cochrane tool. Conducted NMA with GEMTC in R, we evaluate the model fit using the deviation information criteria. Estimated posterior distribution using Markov Chain Monte Carlo, 4 chains, 10 fine-tuned iterations, 10 000 iterations per chain, total 50 000 iterations. Monitored potential scale reduction factor for convergence. And checked convergence with Gelman-Rubin statistics and trace plot. Provided surface under the cumulative ranking, lower values indicate less TE event probability., Results: Analysis of eight RCTs showed that, compared with that for crizotinib, there was a lower risk of total TE with chemotherapy (OR, 0.28; 95% credible intervals (CrI) 0.11 to 0.63), brigatinib (OR 0.31; 95% CrI 0.11 to 0.79) and ceritinib (OR 0.13; 95% CrI 0.03 to 0.45). In addition, analysis of venous TE (VTE) showed similar results, with a lower occurrence for chemotherapy (OR 0.27; 95% CrI 0.1 to 0.62), brigatinib (OR 0.18; 95% CrI 0.04 to 0.6) and ceritinib (OR 0.1; 95% CrI 0.02 to 0.43) compared with that for crizotinib. There were no significant differences in the occurrence of arterial TE among the different treatment options., Conclusion: Compared with chemotherapy, alectinib, lorlatinib, brigatinib and ceritinib, crizotinib significantly increased the risk of TE and VTE., Prospero Registration Number: CRD42023373307., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Circulating genetically abnormal cells (CACs) have emerged as a promising biomarker for the early diagnosis of lung cancer, particularly in patients with pulmonary nodules. However, their performance may be suboptimal in certain patient populations. This study aimed to refine patient selection to improve the detection of CACs in pulmonary nodules. A retrospective analysis was conducted on 241 patients with pulmonary nodules who had undergone pathological diagnosis through surgical tissue specimens. Utilizing consensus clustering analysis, the patients were categorized into three distinct clusters. Cluster 1 was characterized by older age, larger nodule size, and a higher prevalence of hypertension and diabetes. Notably, the diagnostic efficacy of CACs in Cluster 1 surpassed that of the overall patient population (AUC: 0.855 vs. 0.689, P = 0.044). Moreover, for Cluster 1, an integrated diagnostic model was developed, incorporating CACs, sex, maximum nodule type, and maximum nodule size, resulting in a further improved AUC of 0.925 (95% CI 0.846-1.000). In conclusion, our study demonstrates that CACs detection shows better diagnostic performance in aiding the differentiation between benign and malignant nodules in older patients with larger pulmonary nodules and comorbidities such as diabetes and hypertension. Further research and validation are needed to explore how to better integrate CACs detection into clinical practice., (© 2024. The Author(s).)

Background: Post-translational modification pathway of protein ubiquitination is intricately associated with tumorigenesis. We previously reported elevated ubiquitin-conjugating enzyme 2T (UBE2T) as an independent risk factor in stage I lung adenocarcinoma and promoting cellular proliferation. However, its underlying mechanisms needed further investigation., Methods: Immunohistochemistry was used to assess the expression of UBE2T and retinoic acid receptor-related orphan receptor α (RORA) in stage I LUAD. Cell proliferation, migration, and invasion of LUAD cell lines were measured by Cell Counting Kit-8 assay (CCK-8), Colony-forming assay and Transwell assay, respectively. Western blot analysis was performed to determine the expression of epithelial-mesenchymal transition (EMT) markers. A xenograft model was established to evaluate the proliferative capacity of UBE2T and its interaction with RORA in promoting LUAD. Mechanistic insights into the promotion of early-stage LUAD by UBE2T were obtained through luciferase reporter assay, chromatin immunoprecipitation and co-immunoprecipitation., Results: UBE2T and RORA expression was significantly up- and down-regulated in early-stage LUAD patients which's proved to be associated with unfavorable outcomes, strengthened cell proliferation, migration, EMT and invasion through its interaction with RORA both in vivo and in vitro. The growth NSCLC xenografts was reduced by down-expression of UBE2T but was suppressed by RORA knockout. Mechanistically, UBE2T mediated the ubiquitination of the intermediate transcription factor PBX1, which played a transcriptional role in downstream regulation of RORA., Conclusion: The oncogenic role of UBE2T and the UBE2T-PBX1-RORA axis in driving malignant progression in Stage I LUAD had been established. UBE2T might be a novel and promising therapeutic target for LUAD treatment., (© 2024. The Author(s).)

Background: Severe endoplasmic reticulum (ER) stress elicits apoptosis to suppress lung cancer. Our previous research identified that Cepharanthine (CEP), a kind of phytomedicine, possessed powerful anti-cancer efficacy, for which the underlying mechanism was still uncovered. Herein, we investigated how CEP induced ER stress and worked against lung cancer., Methods: The differential expression genes (DEGs) and enrichment were detected by RNA-sequence. The affinity of CEP and NRF2 was analyzed by cellular thermal shift assay (CETSA) and molecular docking. The function assay of lung cancer cells was measured by western blots, flow cytometry, immunofluorescence staining, and ferroptosis inhibitors., Results: CEP treatment enriched DEGs in ferroptosis and ER stress. Further analysis demonstrated the target was NRF2. In vitro and in vivo experiments showed that CEP induced obvious ferroptosis, as characterized by the elevated iron ions, ROS, COX-2 expression, down-regulation of GPX4, and atrophic mitochondria. Moreover, enhanced Grp78, CHOP expression, β-amyloid mass, and disappearing parallel stacked structures of ER were observed in CEP group, suggesting ER stress was aroused. CEP exhibited excellent anti-lung cancer efficacy, as evidenced by the increased apoptosis, reduced proliferation, diminished cell stemness, and prominent inhibition of tumor grafts in animal models. Furthermore, the addition of ferroptosis inhibitors weakened CEP-induced ER stress and apoptosis., Conclusion: In summary, our findings proved CEP drives ferroptosis through inhibition of NRF2 for induction of robust ER stress, thereby leading to apoptosis and attenuated stemness of lung cancer cells. The current work presents a novel mechanism for the anti-tumor efficacy of the natural compound CEP., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: The programmed cell death (PCD) plays a key role in the development and progression of lung adenocarcinoma. In addition, immune-related genes also play a crucial role in cancer progression and patient prognosis. However, further studies are needed to investigate the prognostic significance of the interaction between immune-related genes and cell death in LUAD., Methods: In this study, 10 clustering algorithms were applied to perform molecular typing based on cell death-related genes, immune-related genes, methylation data and somatic mutation data. And a powerful computational framework was used to investigate the relationship between immune genes and cell death patterns in LUAD patients. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations, and we constructed an immune-associated programmed cell death model (PIGRS) using the machine learning model that exhibited the best performance. Finally, based on a series of in vitro experiments used to explore the role of PSME3 in LUAD., Results: We used 10 clustering algorithms and multi-omics data to categorize TCGA-LUAD patients into three subtypes. patients with the CS3 subtype had the best prognosis, whereas patients with the CS1 and CS2 subtypes had a poorer prognosis. PIGRS, a combination of 15 high-impact genes, showed strong prognostic performance for LUAD patients. PIGRS has a very strong prognostic efficacy compared to our collection. In conclusion, we found that PSME3 has been little studied in lung adenocarcinoma and may be a novel prognostic factor in lung adenocarcinoma., Discussion: Three LUAD subtypes with different molecular features and clinical significance were successfully identified by bioinformatic analysis, and PIGRS was constructed using a powerful machine learning framework. and investigated PSME3, which may affect apoptosis in lung adenocarcinoma cells through the PI3K/AKT/Bcl-2 signaling pathway., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xie, Chen, Tian, Wang, Wang, Zhang, Wang and Lian.)

Background: To explore the abnormal metabolism-related genes that affect the prognosis of patients with lung adenocarcinoma (LUAD), and analyze the relationship with immune infiltration and competing endogenous RNA (ceRNA) network., Methods: Transcriptome data of LUAD were downloaded from the Cancer Genome Atlas database. Abnormal metabolism-related differentially expressed genes in LUAD were screened by the R language. Cox analysis was used to construct LUAD prognostic risk model. Kaplan-Meier test, ROC curve and nomograms were used to evaluate the predictive ability of metabolic related gene prognostic model. CIBERSORT algorithm was used to analyze the relationship between risk score and immune infiltration. The starBase database constructed a regulatory network consistent with the ceRNA hypothesis. IHC experiments were performed to verify the differential expression of ALG3 in LUAD and paracancerous samples., Results: In this study, 42 abnormal metabolism-related differential genes were screened. After survival analysis, the final 5 metabolism-related genes were used as the construction of prognosis model, including ALG3, COL7A1, KL, MST1, and SLC52A1. In the model, the survival rate of LUAD patients in the high-risk subgroup was lower than that in the low-risk group. In addition, the risk score of the constructed LUAD prognostic model can be used as an independent prognostic factor for patients. According to the analysis of CIBERSORT algorithm, the risk score is related to the infiltration of multiple immune cells. The potential ceRNA network of model genes in LUAD was constructed through the starBase database. IHC experiments revealed that ALG3 expression was upregulated in LUAD., Conclusion: The prognostic model of LUAD reveals the relationship between metabolism and prognosis of LUAD, and provides a novel perspective for diagnosis and research of LUAD., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

The advent of immunotherapy has greatly improved the prognosis of non-small cell lung (NSCLC) patients. However, given its low response rate and high cost of treatment, the search for valuable predictive markers of treatment efficacy is necessary. Considering the complexity and heterogeneity of the tumour and tumour microenvironment, the construction of a multi-dimensional prediction model is necessary. Therefore, we aimed to integrate clinical parameters, radiomic features, and immune signature data from NSCLC patients receiving immunotherapy to construct a multi-dimensional prediction model to better predict the efficacy of immunotherapy. The current study enrolled 137 NSCLC patients who received immunotherapy. We collected baseline clinical information, CT images, and tumour tissue specimens. Using 3D-Slicer software, radiomic features were extracted from patient CT images, and tumor tissue samples obtained before immunotherapy were subjected to immunohistochemical staining. Then, the least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to downscale the data, and the radiomic features and immune signatures associated with the prognosis of immunotherapy patients were identified. The modified lung immune predictive index (mLIPI), radiomics score (Radioscore), immune score and multi-dimensional model nomogram were constructed. The C-index and area under the curve (AUC) were applied to evaluate the predictive efficacy of the models. Three radiomic features and three immune signatures that could predict the efficacy of immunotherapy were eventually screened. Multivariate analysis showed that the mLIPI, Radioscore, and immune score were independent predictive factors for PFS and OS (P < 0.05 for all models). The multi-dimensional model combining the three models showed better predictive efficacy than the mLIPI, Radioscore, and immune score (PFS: 0.721 vs. 0.662 vs. 0.610 vs. 0.610; OS: 0.727 vs. 0.661 vs. 0.601 vs. 0.602 respectively). The multi-dimensional model showed the best predictive efficacy, with C-index for PFS and OS higher than mLIPI, radioscore and immune score: 0.721 vs. 0.662 vs. 0.610 vs. 0.610 for PFS and 0.727 vs. 0.661 vs. 0.601 vs. 0.602 for OS, respectively. The AUC for the multi-dimensional model also performed better than those of the individual models: 0.771 vs. 0.684 vs. 0.715 vs. 0.711 for PFS and 0.768 vs. 0.662 vs. 0.661 vs. 0.658 for OS, respectively. The multi-dimensional model combining the three models had better predictive efficacy than any single model and was more likely to help provide patients personalized and precision medicine., (© 2024. The Author(s).)

The analysis of streaming time-to-event cohorts has garnered significant research attention. Most existing methods require observed cohorts from a study sequence to be independent and identically sampled from a common model. This assumption may be easily violated in practice. Our methodology operates within the framework of online data updating, where risk estimates for each cohort of interest are continuously refreshed using the latest observations and historical summary statistics. At each streaming stage, we introduce parameters to quantify the potential discrepancy between batch-specific effects from adjacent cohorts. We then employ penalized estimation techniques to identify nonzero discrepancy parameters, allowing us to adaptively adjust risk estimates based on current data and historical trends. We illustrate our proposed method through extensive empirical simulations and a lung cancer data analysis., (© 2024 John Wiley & Sons Ltd.)

Stratification strategies for chemotherapy plus PD-1 inhibitors in advanced non-small-cell lung cancer (NSCLC) are critically demanded. We performed high-throughput panel-based deep next-generation sequencing and low-pass whole genome sequencing on prospectively collected circulating tumor DNA (ctDNA) specimens from 460 patients in the phase 3 CHOICE-01 study at different time points. We identified predictive markers for chemotherapy plus PD-1 inhibitor, including ctDNA status and genomic features such as blood-based tumor mutational burden, intratumor heterogeneity, and chromosomal instability. Furthermore, we established an integrated ctDNA-based stratification strategy, blood-based genomic immune subtypes (bGIS) scheme, to distinguish patients who benefit from the addition of PD-1 inhibitor to first-line chemotherapy. Moreover, we demonstrated potential applications for the dynamic monitoring of ctDNA. Overall, we proposed a potential therapeutic algorithm based on the ctDNA-based stratification strategy, shedding light on the individualized management of immune-chemotherapies for patients with advanced NSCLC., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Batroxobin, isolated from Bothrops moojeni, is a defibrinogenating agent used as a thrombin-like serine protease against fibrinogen for improving microcirculation. Here, we investigated whether, and if so, how batroxobin acts in concert with NK cells in terms of anti-tumor effects. CD3+/CD56+ NK cells were isolated and cultured from C57BL/6 mouse spleen. NK cells' viability was tested via Lactate dehydrogenase (LDH) assay. Lewis lung cancer cell (1*107 cell/ml) was used to build animal models. All animals were divided into five groups and treated with Batroxobin and NK cells respectively. HE staining was used to detect the pathological morphology of tumor tissue. The contents of fibrinogen and TNF-α in serum were determined by ELISA. The protein expression levels of MMP2, MMP9, VEGF and CD44 in tumor tissues were detected by Western Blot or immunohistochemistry. Compared with Control group, Tumor growth was not significantly affected in the group treated with Batroxobin or NK cells alone, However, tumor growth was significantly inhibited in the NK cell combined with the Batroxobin group. Serum levels of Fbg and TNF-αin mice treated with Batroxobin combined with NK cells dropped significantly, bringing them closer to normal levels. WB results showed that the expression levels of MMP2/9, VEGF and CD44 in Batroxobin combined with NK cell group also significantly decreased. Batroxobin combined with adoptive immunotherapy with NK cells significantly inhibited the growth of Lewis lung cancer in mice.

With the outbreak of the coronavirus disease 2019 (COVID-19), reductions in T-cell function and exhaustion have been observed in patients post-infection of COVID-19. T cells are key mediators of anti-infection and antitumor, and their exhaustion increases the risk of compromised immune function and elevated susceptibility to cancer. Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer with high incidence and mortality. Although the survival rate after standard treatment such as surgical treatment and chemotherapy has improved, the therapeutic effect is still limited due to drug resistance, side effects, and recurrence. Recent advances in molecular biology and immunology enable the development of highly targeted therapy and immunotherapy for cancer, which has driven cancer therapies into individualized treatments and gradually entered clinicians' views for treating NSCLC. Currently, with the development of photosensitizer materials, phototherapy has been gradually applied to the treatment of NSCLC. This review provides an overview of recent advancements and limitations in different treatment strategies for NSCLC under the background of COVID-19. We discuss the latest advances in phototherapy as a promising treatment method for NSCLC. After critically examining the successes, challenges, and prospects associated with these treatment modalities, their profound prospects were portrayed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Si, Bai, Wang, Wang and Qin.)

Purpose: To investigate the value of multi-parametric MRI-based radiomics for preoperative prediction of lung metastases from soft tissue sarcoma (STS)., Methods: In total, 122 patients with clinicopathologically confirmed STS who underwent pretreatment T1-weighted contrast-enhanced (T1-CE) and T2-weighted fat-suppressed (T2FS) MRI scans were enrolled between Jul. 2017 and Mar. 2021. Radiomics signatures were established by calculating and selecting radiomics features from the two sequences. Clinical independent predictors were evaluated by statistical analysis. The radiomics nomogram was constructed from margin and radiomics features by multivariable logistic regression. Finally, the study used receiver operating characteristic (ROC) and calibration curves to evaluate performance of radiomics models. Decision curve analyses (DCA) were performed to evaluate clinical usefulness of the models., Results: The margin was considered as an independent predictor (p < 0.05). A total of 4 MRI features were selected and used to develop the radiomics signature. By incorporating the margin and radiomics signature, the developed nomogram showed the best prediction performance in the training (AUCs, margin vs. radiomics signature vs. nomogram, 0.609 vs. 0.909 vs. 0.910) and validation (AUCs, margin vs. radiomics signature vs. nomogram, 0.666 vs. 0.841 vs. 0.894) cohorts. DCA indicated potential usefulness of the nomogram model., Conclusions: This feasibility study evaluated predictive values of multi-parametric MRI for the prediction of lung metastasis, and proposed a nomogram model to potentially facilitate the individualized treatment decision-making for STSs., (© 2024. The Author(s).)

The spatial arrangement of immune cells within the tumor microenvironment (TME) and their interactions play critical roles in the initiation and development of cancer. Several advanced technologies such as imaging mass cytometry (IMC) providing the immunological landscape of the TME with single-cell resolution. In this study, we develop a new method to quantify the spatial proximity between different cell types based on single-cell spatial data. Using this method on IMC data from 416 lung adenocarcinoma patients, we show that the proximity between different cell types is more correlated with patient prognosis compared to the traditional features such immune cell density and fractions. Consistent with previous reports, our results validate that proximity of T helper (Th) and B cells to cancer cells is associated with survival benefits. More importantly, we discover that the proximity of M2 macrophages to multiple immune cells is associated with poor prognosis. When Th/B cells are stratified into M2-distal and M2-proximal, the abundance of the former but not the latter category of Th/B cells is correlated with enhanced patient survival. Additionally, the abundance of M2-distal and M2-proximal cytotoxic T cells (Tc) is respectively associated with good and poor prognosis. Our results indicate that the prognostic effect of Th, Tc, and B cells in the tumor microenvironment is modulated by the nearby M2 macrophages. The proposed new method proposed can be readily applied to all single-cell spatial data for revealing functional impact of immune cell interactions., (© 2024. The Author(s).)

Acquired resistance is inevitable in the treatment of non-small cell lung cancer (NSCLC) with osimertinib, and one of the primary mechanisms responsible for this resistance is the epithelial-mesenchymal transition (EMT). We identify upregulation of the proviral integration site for Moloney murine leukemia virus 1 (PIM1) and functional inactivation of glycogen synthase kinase 3β (GSK3β) as drivers of EMT-associated osimertinib resistance. Upregulation of PIM1 promotes the growth, invasion, and resistance of osimertinib-resistant cells and is significantly correlated with EMT molecules expression. Functionally, PIM1 suppresses the ubiquitin-proteasome degradation of snail family transcriptional repressor 1 (SNAIL) and snail family transcriptional repressor 2 (SLUG) by deactivating GSK3β through phosphorylation. The stability and accumulation of SNAIL and SLUG facilitate EMT and encourage osimertinib resistance. Furthermore, treatment with PIM1 inhibitors prevents EMT progression and re-sensitizes osimertinib-resistant NSCLC cells to osimertinib. PIM1/GSK3β signaling is activated in clinical samples of osimertinib-resistant NSCLC, and dual epidermal growth factor receptor (EGFR)/PIM1 blockade synergistically reverse osimertinib-resistant NSCLC in vivo. These data identify PIM1 as a driver of EMT-associated osimertinib-resistant NSCLC cells and predict that PIM1 inhibitors and osimertinib combination therapy will provide clinical benefit in patients with EGFR-mutant NSCLC., (© 2024. The Author(s).)

Introduction: Several observational or retrospective studies have previously been conducted to explore the possible association between lung cancer and human papillomavirus (HPV) infection. However, there may be inconsistencies in the data and conclusions due to differences in study design and HPV testing methods. There are currently no studies that provide conclusive evidence to support the involvement of HPV in the occurrence and development of lung cancer. Therefore, the relationship between HPV and lung cancer remains controversial and uncertain. This study aimed to explore whether HPV infection is causally related to lung cancer risk by systematically performing a two-way Two-Sample Mendelian Randomization (TSMR) analysis., Methods: In the International Lung Cancer Consortium (ILCCO) genome-wide association study dataset, we included 11,348 lung cancer (LUCA) cases, including 3275 squamous cell carcinoma (LUSC) cases, 3442 adenocarcinoma (LUAD) cases, and 15,861 cases of control. Using genetic variants associated with the HPV E7 protein as instrumental variables, we summarized statistics associated with HPV infection in the MRC IEU OpenGWAS database, which included the HPV-16 E7 protein and the HPV-18 E7 protein. Two-sample Mendelian randomization (MR) results are expressed as odds ratios (OR) and 95% confidence intervals (CI)., Results: Based on a comprehensive analysis of genome-wide association study (GWAS) data from public databases, we mainly used inverse-variance weighted (IVW) to estimate causal relationships, while using MR-Egger, weighted median, simple mode, and weighted mode, and other four methods as supplements. Two-sample MR Analysis revealed no causal relationship between exposure factors (HPV-16 E7 protein and HPV-18 E7 protein) and outcome factors (lung cancer (LUCA) and its subtypes squamous cell carcinoma (LUSC) and adenocarcinoma (LUAD)) in forward MR Analysis using the IVW approach.HPV-16 E7 protein and LUCA and its subtypes LUSC and LUAD by IVW method results: [OR] = 1.002; 95% [CI]: 0.961 - 1.045; p = 0.920; [OR] = 1.023; 95% [CI]: 0.966 - 1.084; p = 0.438; [OR] = 0.994; 95% [CI]: 0.927 - 1.066; p = 0.872); HPV-18 E7 protein and LUCA and its subtypes LUSC and LUAD by IVW method results: [OR] = 0.965; 95% [CI]: 0.914 - 1.019; p = 0.197; [OR] = 0.933; 95% [CI]: 0.834 - 1.043; p = 0.222; [OR] = 1.028; 95% [CI]: 0.945 - 1.118; p = 0.524. It was observed through reverse MR that LUCA and its subtypes LUSC and LUAD were used as exposure factors, and HPV infection (HPV-16 E7 protein and HPV-18 E7 protein) was used as the outcome factors, the results of the IVW method are also invalid.LUCA and HPV-16 E7 protein and HPV-18 E7 protein by IVW method results: [OR] = 1.036; 95% [CI]: 0.761 - 1.411; p = 0.82; [OR] = 1.318; 95% [CI]: 0.949 - 1.830; p = 0.099; LUSC and HPV-16 E7 protein and HPV-18 E7 protein by IVW method results: [OR] = 1.123; 95% [CI]0.847 - 1.489; p = 0.421; [OR] = 0.931; 95% [CI]: 0.660 - 1.313; p = 0.682; LUAD and HPV-16 E7 protein and HPV-18 E7 protein by IVW method results: [OR] = 1.182; 95% [CI] 0.983 - 1.421; p = 0.075; [OR] = 1.017; 95% [CI]: 0.817 - 1.267; p = 0.877.Our results indicate that there is no causal relationship between genetically predicted HPV infection and LUCA and its subtypes LUSC and LUAD. In addition, in the reverse MR analysis, we did not observe a significant causal relationship between LUCA and its subtypes LUSC and LUAD on HPV infection., Conclusions: Our findings do not support a genetic association between HPV infection and lung cancer., (© 2024. The Author(s).)

Objective: To summarize and analyze the clinical characteristics and prognosis of thoracic SMARCA4-deficient undifferentiated tumor (SMARCA4-UT). Methods: A retrospective analysis was conducted on the clinical data of 51 patients with SMARCA4-UT who were diagnosed in the First Affiliated Hospital of Zhengzhou University from January 2018 to December 2023, and 52 patients with SMARCA4-intact non-small cell lung cancer (SMARCA4-iNSCLC) expression admitted during the same period were used as controls. The Kaplan-Meier survival analysis and log-rank test were used to analyze the survival difference between the two groups of patients, and the Cox regression model was used to explore the factors influencing the prognosis of the two groups of patients. Results: In the SMARCA4-UT group, there were 50 males and 1 female, with the age of (63.8±9.7) years. Compared to the SMARCA4-iNSCLC group, the SMARCA4-UT group exhibited a higher proportion of male patients and smokers, as well as a higher Ki-67 level (all P <0.05). SMARCA4-UT is mainly characterized by solid lesions with poor adhesion, and some of them exhibit rhabdomyoid morphology. Immunohistochemistry revealed negative results for BRG1, thyroid transcription factor-1, P40, NapsinA, and others were mostly negative, while some patients were positive for spalt-like transcription factor 4. There were a relatively large number of cases with Ki-67≥30% (47/51, 92%). Among the 10 patients in the SMARCA4-UT group who underwent next-generation sequencing genetic testing, 6 patients were found to have SMARCA4 mutations, often accompanied by TP53 (8/10, 80%), STK 11(3/10, 30%), KRAS(2/10, 20%), with fewer common driver gene mutations. The average tumor mutation burden was 16.12 mutations/Mb. Compared with SMARCA4-iNSCLC patients, the median overall survival of SMARCA4-UT patients was significantly shorter (12 months vs 45 months, P <0.001), and the median overall survival of patients with stage Ⅲ-Ⅳ SMARCA4-UT treated with immunotherapy was longer than that of patients without immunotherapy (23 months vs 7 months, P =0.027). The results of the multivariate Cox regression model analysis indicated that SMARCA4 deficiency is a risk factor for prognosis in patients with SMARCA4-UT and SMARCA4-iNSCLC [ HR =7.954(95% CI： 2.764-22.890), P <0.001]. Conclusions: SMARCA4-UT is a rare undifferentiated tumour distinct from SMARCA4-iNSCLC, which is prevalent among elderly male smokers. It possesses high invasiveness and poor prognosis. The typical pathological characteristic is negative BRG1. Immunotherapy demonstrates a certain effect.

Background It is increasingly recognized that interstitial lung abnormalities (ILAs) detected at CT have potential clinical implications, but automated identification of ILAs has not yet been fully established. Purpose To develop and test automated ILA probability prediction models using machine learning techniques on CT images. Materials and Methods This secondary analysis of a retrospective study included CT scans from patients in the Boston Lung Cancer Study collected between February 2004 and June 2017. Visual assessment of ILAs by two radiologists and a pulmonologist served as the ground truth. Automated ILA probability prediction models were developed that used a stepwise approach involving section inference and case inference models. The section inference model produced an ILA probability for each CT section, and the case inference model integrated these probabilities to generate the case-level ILA probability. For indeterminate sections and cases, both two- and three-label methods were evaluated. For the case inference model, we tested three machine learning classifiers (support vector machine [SVM], random forest [RF], and convolutional neural network [CNN]). Receiver operating characteristic analysis was performed to calculate the area under the receiver operating characteristic curve (AUC). Results A total of 1382 CT scans (mean patient age, 67 years ± 11 [SD]; 759 women) were included. Of the 1382 CT scans, 104 (8%) were assessed as having ILA, 492 (36%) as indeterminate for ILA, and 786 (57%) as without ILA according to ground-truth labeling. The cohort was divided into a training set ( n = 96; ILA, n = 48), a validation set ( n = 24; ILA, n = 12), and a test set ( n = 1262; ILA, n = 44). Among the models evaluated (two- and three-label section inference models; two- and three-label SVM, RF, and CNN case inference models), the model using the three-label method in the section inference model and the two-label method and RF in the case inference model achieved the highest AUC, at 0.87. Conclusion The model demonstrated substantial performance in estimating ILA probability, indicating its potential utility in clinical settings. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Zagurovskaya in this issue.

Background: Lung cancer is a prevalent and severe form of malignant tumors worldwide. tRF-Leu-CAG, a recently discovered non-coding single-stranded small RNA derived from transfer RNA, has sparked interest in exploring its biological functions and potential molecular mechanisms in lung cancer., Methods: The abundance of tRF-Leu-CAG was measured via quantitative real-time polymerase chain reaction (qRT-PCR) in 96 sets of lung cancer tissue samples obtained from clinical patients. Subsequently, both in vivo and in vitro experiments were conducted to validate the biological functions of tRF-Leu-CAG in lung cancer. Furthermore, an exploration of the potential target genes of tRF-Leu-CAG and its association with autophagy and drug resistance in lung cancer was undertaken., Results: Our analysis revealed a significant upregulation of tRF-Leu-CAG in non-small cell lung cancer (NSCLC) tissues. Additionally, we observed that heightened expression of tRF-Leu-CAG significantly augmented the proliferation and migration of NSCLC cells, facilitated cell cycle progression, and suppressed apoptosis. Furthermore, we identified transcription elongation factor A3 (TCEA3) as a direct target gene of tRF-Leu-CAG. TCEA3 inhibited the proliferation and migration of NSCLC, and tRF-Leu-CAG promoted the proliferation and migration of NSCLC by mediating the silencing of TCEA3. Moreover, we demonstrated that the augmentation of paclitaxel resistance by tRF-Leu-CAG was contingent on autophagy. Finally, tRF-Leu-CAG notably accelerated tumor growth and promoted the process of epithelial-mesenchymal transition (EMT) in vivo., Conclusions: tRF-Leu-CAG promotes NSCLC tumor growth and metastasis by targeting TCEA3 and promotes paclitaxel resistance by enhancing cellular autophagy. These results provide potentially effective targets and therapeutic options for the clinical treatment of NSCLC., (© 2024 John Wiley & Sons Ltd.)

Interleukin (IL)-4 and IL-13 are the main effectors of innate lymphoid cells (ILC2) of the type 2 innate immune response, which can carry out specific signal transmission between multiple cells in the tumor immune microenvironment. IL-4 and IL-13 mediate signal transduction and regulate cellular functions in a variety of solid tumors through their shared receptor chain, the transmembrane heterodimer interleukin-4 receptor alpha/interleukin-13 receptor alpha-1 (type II IL-4 receptor). IL-4, IL-13, and their receptors can induce the formation of a variety of malignant tumors and play an important role in their progression, growth, and tumor immunity. In order to explore possible targets for lung cancer prediction and treatment, this review summarizes the characteristics and signal transduction pathways of IL-4 and IL-13, and their respective receptors, and discusses in depth their possible role in the occurrence and development of lung cancer.

Resveratrol (RSV) has been found to have a cancer-suppressing effect in a variety of cancers, including non-small cell lung cancer (NSCLC). Studies have shown that sine oculis homeobox 4 (SIX4) and sphingosine kinase 2 (SPHK2) are tumour promoters of NSCLC. However, whether RSV regulates SIX4 and SPHK2 to mediate NSCLC cell functions remains unclear. NSCLC cell functions were assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay, 5-ethynyl-2'-deoxyuridine (EdU) assay, flow cytometry, transwell assay and wound healing assay. Protein expression levels were detected by western blot. SIX4 and SPHK2 mRNA levels in NSCLC tumour tissues were examined using quantitative real-time PCR. In addition, mice xenograft models were built to explore the impact of RSV on NSCLC tumour growth. RSV inhibited NSCLC cell proliferation, invasion and migration, while facilitated apoptosis. SIX4 and SPHK2 were up-regulated in NSCLC tissues and cells, and their expression was reduced by RSV. Knockdown of SIX4 and SPHK2 suppressed NSCLC cell growth, invasion and migration, and the regulation of RSV on NSCLC cell functions could be reversed by SIX4 and SPHK2 overexpression. RSV inactivated Wnt/β-catenin pathway via decreasing SIX4 and SPHK2 levels. In animal experiments, RSV reduced NSCLC tumour growth in vivo . RSV repressed NSCLC malignant process by decreasing SIX4 and SPHK2 levels to restrain the activity of Wnt/β-catenin pathway.

Background: The International Association for the Study of Lung Cancer (IASLC) Pathology Committee introduced a histologic grading system for invasive lung adenocarcinoma (LUAD) in 2020. The IASLC grading system, hinging on the evaluation of predominant and high-grade histologic patterns, has proven to be practical and prognostic for invasive LUAD. However, there are still limitations in evaluating the prognosis of stage IA LUAD. Radiomics may serve as a valuable complement., Purpose: To establish a model that integrates IASLC grading and radiomics, aimed at predicting the prognosis of stage IA LUAD., Methods: We conducted a retrospective analysis of 628 patients diagnosed with stage IA LUAD who underwent surgical resection between January 2015 and December 2018 at our institution. The patients were randomly divided into the training set (n = 439) and testing set (n = 189) at a ratio of 7:3. Overall survival (OS) and disease-free survival (DFS) were taken as the end points. Radiomics features were obtained by PyRadiomics. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO). The prediction models for OS and DFS were developed using multivariate Cox regression analysis, and the models were visualized through nomogram plots. The model's performance was evaluated using area under the curves (AUC), concordance index (C-index), calibration curves, and survival decision curve analysis (DCA)., Results: In total, nine radiomics features were selected for the OS prediction model, and 15 radiomics features were selected for the DFS prediction model. Patients with high radiomics scores were associated with a worse prognosis (p < 0.001). We built separate prediction models using radiomics or IASLC alone, as well as a combined prediction model. In the prediction of OS, we observed that the combined model (C-index: 0.812 ± 0.024, 3 years AUC: 0.692, 5 years AUC: 0.792) achieved superior predictive performance than the radiomics (C-index: 0.743 ± 0.038, 3 years AUC: 0.633, 5 years AUC: 0.768) and IASLC grading (C-index: 0.765 ± 0.042, 3 years AUC: 0.658, 5 years AUC: 0.743) models alone. Similar results were obtained in the models for DFS., Conclusion: The combination of radiomics and IASLC pathological grading proves to be an effective approach for predicting the prognosis of stage IA LUAD. This has substantial clinical relevance in guiding treatment decisions for early-stage LUAD., (© 2024 American Association of Physicists in Medicine.)

Objective: The objective of this study is to evaluate the correlation between tumor proportionality scores (TPS) and the effectiveness of immune checkpoint inhibitors (ICIs) as the second or subsequent line therapies for individuals who received diagnoses of advanced non-small cell lung cancer (NSCLC)., Methods: The retrospective analysis was conducted on the medical records of a total of 143 patients who received diagnoses of stage IIIB/IV NSCLC and were admitted to our hospital from the beginning of 2019 to the end of September 2022. The follow-up period ended on 01 January 2023. The study used Kaplan-Meier survival curves to assess the progression-free survival (PFS) and overall survival (OS) of patients. Univariate and multivariate Cox proportional risk models were used to analyze the factors associated with the PFS and OS of advanced-stage NSCLC patients who received ICIs as the second or subsequent lines., Results: Patients diagnosed with NSCLC who had a TPS ≥1% and got treatment with ICIs exhibit notably elevated rates of partial response, objective response rate, disease control rate and extended PFS in comparison to NSCLC patients with a TPS of <1% ( P  < 0.05). NSCLC patients with TPS within 1-49% [hazard ratio (HR) = 0.372; 95% confidence interval (CI), 0.140-0.993; P  = 0.048] or ≥50% (HR = 0.276; 95% CI, 0.095-0.796; P  = 0.017) were significantly associated with prolonged PFS, which were conducted by multivariate Cox regression analysis., Conclusion: Programmed death protein-1 expression status may be predictive markers of the effectiveness of ICIs as the second or subsequent lines of therapies in advanced NSCLC are influenced by TPS., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: The prognostic analysis of lung invasive mucinous adenocarcinoma (IMA) is deficient due to the lack of a universally recommended histological grading system, leading to unregulated treatment approaches., Objective: We aimed to examine the clinical trajectory of IMA and assess the viability of utilizing the existing grading system for lung invasive non-mucinous adenocarcinoma in the context of IMA., Methods: We retrospectively collected clinicopathological data from 265 IMA patients. Each case re-evaluated the tumor grade using the following three classification systems: the 4th Edition of the World Health Organization classification system, the International Association for the Study of Lung Cancer (IASLC) grading system, and a two-tier grading system. We performed a comparative analysis of these grading systems and identified the most effective grading system for IMA., Results: The study comprised a total of 214 patients with pure IMA and 51 patients with mixed IMA. The 5-year overall survival (OS) rates for pure IMA and mixed IMA were 86.7% and 57.8%, respectively. All three grading systems proved to be effective prognostic classifiers for IMA. The value of area under the curve at 1-, 3-, and 5-year OS was highest for the IASLC grading system compared with the other grade systems and the clinical stage. The IASLC classification system was an independent prognostic predictor (p = 0.009, hazard ratio 2.243, 95% confidence interval 1.219-4.127)., Conclusion: Mixed IMA is more aggressive than pure IMA, with an OS rate on par with that of high-grade pure IMA. The IASLC grading system can better indicate prognosis and is recommended for lung IMA., (© 2024. Society of Surgical Oncology.)

Sinensetin is a product isolated from Orthosiphon aristatus, and its antitumor activities have been well established. This study focused on the role and mechanism of sinensetin in lung adenocarcinoma (LUAD). LUAD cells were treated with various concentrations of sinensetin. The proliferation, migration, invasion, and angiogenesis of LUAD cells were detected using colony formation, transwell, and tube formation assays, respectively. The protein levels of VEGF-A, VEGFR-2, and phosphorylated AKT (ser473) were measured by western blotting. The targeted relationship between VEGF-A and miR-374c-5p was verified by luciferase reporter assay. BALB/c nude mice inoculated with A549 cells were treated with sinensetin (40 mg/kg/day) by gavage for 21 days to investigate the effect of sinensetin on tumor growth and angiogenesis in vivo. We found that sinensetin reduced proliferation, migration, invasion, angiogenesis, and cancer stem characteristics of LUAD cells. Sinensetin also suppressed LUAD tumor growth and angiogenesis in vivo. Sinensetin downregulated VEGF-A expression in LUAD cells by enhancing miR-374c-5p expression. MiR-374c-5p inhibited the VEGF-A/VEGFR-2/AKT pathway in LUAD cells. The antitumor effect of sinensetin was reversed by overexpression of VEGF-A or inhibition of miR-374c-5p. Overall, sinensetin upregulates miR-374c-5p to inhibit the VEGF-A/VEGFR-2/AKT pathway, thereby exerting antitumor effect on LUAD., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Rationale and Objectives: To explore and externally validate habitat-based radiomics for preoperative prediction of epidermal growth factor receptor (EGFR) mutations in exon 19 and 21 from MRI imaging of non-small cell lung cancer (NSCLC)-originated brain metastasis (BM)., Methods: A total of 170, 62 and 61 patients from center 1, center 2 and center 3, respectively were included. All patients underwent contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) MRI scans. Radiomics features were extracted from the tumor active (TA) and peritumoral edema (PE) regions in each MRI slice. The most important features were selected by the least absolute shrinkage and selection operator regression to develop radiomics signatures based on TA (RS-TA), PE (RS-PE) and their combination (RS-Com). Receiver operating characteristic (ROC) curve analysis was performed to access performance of radiomics models for both internal and external validation cohorts., Results: 10, four and six most predictive features were identified to be strongly associated with the EGFR mutation status, exon 19 and exon 21, respectively. The RSs derived from the PE region outperformed those from the TA region for predicting the EGFR mutation, exon 19 and exon 21. The RS-Coms generated the highest performance in the primary training (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.955 vs. 0.946 vs. 0.928), internal validation (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.879 vs. 0.819 vs. 0.882), external validation 1 (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.830 vs. 0.825 vs. 0.822), and external validation 2 (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.812 vs. 0.818 vs. 0.800) cohort., Conclusion: The developed habitat-based radiomics model can be used to accurately predict the EGFR mutation subtypes, which may potentially guide personalized treatments for NSCLC patients with BM., Competing Interests: Declaration of Competing Interest On behalf of all authors, the corresponding author states that there is no conflict of interest., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Segmentation in medical images is inherently ambiguous. It is crucial to capture the uncertainty in lesion segmentations to assist cancer diagnosis and further interventions. Recent works have made great progress in generating multiple plausible segmentation results as diversified references to account for the uncertainty in lesion segmentations. However, the efficiency of existing models is limited, and the uncertainty information lying in multi-annotated datasets remains to be fully utilized. In this study, we propose a series of methods to corporately deal with the above limitation and leverage the abundant information in multi-annotated datasets: (1) Customized T-time Inner Sampling Network to promote the modeling flexibility and efficiently generate samples matching the ground-truth distribution of a number of annotators; (2) Uncertainty Degree defined for quantitatively measuring the uncertainty of each sample and the imbalance of the whole multi-annotated dataset from a brand new perspective; (3) Uncertainty-aware Data Augmentation Strategy to help probabilistic models adaptively fit samples with different ranges of uncertainty. We have evaluated each of them on both the publicly available lung nodule dataset and our in-house Liver Tumor dataset. Results show that our proposed methods achieves the overall best performance on both accuracy and efficiency, demonstrating its great potential in lesion segmentations and more downstream tasks in real clinical scenarios., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)