Non-small Cell Lung Cancer Patients Research Articles

Changes in Staging and Management of Non-Small Cell Lung Cancer (NSCLC) Patients Following the Implementation of Low-Dose Chest Computed Tomography (LDCT) Screening at Kaohsiung Medical University Hospital.

Low-dose computed tomography (LDCT) has been widely adopted for lung cancer screening due to its proven ability to reduce lung cancer mortality, especially among high-risk populations. This retrospective study aims to evaluate the impact of LDCT screening on non-small cell lung cancer (NSCLC) staging at Kaohsiung Medical University Hospital (KMUH) from 2011 to 2020, following the introduction of LDCT in 2013. The study examines the correlation between LDCT screening volume and changes in the distribution of NSCLC stages, particularly early-stage (stages 0 and I) and late-stage (stage IV) diagnoses. Additionally, it explores the differences in histopathological subtypes, focusing on adenocarcinoma and squamous cell carcinoma, and assesses the impact of early detection on five-year survival rates. The results show a significant increase in early-stage NSCLC diagnoses, particularly in adenocarcinoma cases, where early-stage diagnoses rose from 10.4% in 2010 to 38.7% in 2019. However, the number of stage IV cases remained stable, indicating that LDCT may not substantially reduce late-stage diagnoses. Pearson's correlation analysis demonstrated a strong positive correlation between LDCT screening and early-stage NSCLC detection, particularly for adenocarcinoma (p < 0.001), though the early detection of squamous cell carcinoma and small cell carcinoma remained limited. The study concludes that LDCT screening plays a crucial role in improving early NSCLC detection and five-year survival rates. Future research should focus on optimizing screening strategies to capture more at-risk populations and enhance the detection of harder-to-diagnose subtypes like squamous cell carcinoma.

Radiomics As Biomarkers for the Treatment of Non-small Cell Lung Cancer With Stereotactic Body Radiation Therapy: A Review of Concepts.

Stereotactic body radiation therapy (SBRT) is currently the alternative for inoperable early-stage and oligometastatic non-small cell lung cancer (NSCLC) patients. While most patients are good responders among this specific group, some patients do not experience the benefits of this treatment. Even though physicians use clinical variables and semantic radiological features to make treatment decisions, medical images contain a wealth of personalized pathophysiological information that can be extracted and used for clinical decision support systems. In the form of radiomics features, details unique to each patient's medical scans can be utilized to create predictive models and to identify biomarking signatures. Then, these tools and indices can predict treatment outcomes and categorize patients to the most optimal treatment regimen. A conceptual review of relevant topics centered around the identification and development of radiomic-based biomarkers for SBRT-treated NSCLC was conducted. To begin with, an overview of the nature and management of non-small cell lung cancer was provided. To continue, biomarkers were defined in the context of cancer care. Then, the uses of stereotactic body radiation therapy in the treatment of NSCLC were further explained. Finally, the study of radiomics was discussed, and the uses and limitations of radiomic features and ML for SBRT-treated NSCLC were expanded upon. Radiomics-based biomarkers and predictive algorithmic models can potentially improve the SBRT treatment of early-stage and oligometastatic NSCLC by providing personalized support systems to healthcare professionals. While many institutions are attempting to optimize their biomarkers and AI-based tools for clinical use, additionalprospective studies are needed to properly ensure their efficacy. As such, the improvements made in the field of personalized medicine are promising.

Enhanced NSCLC subtyping and staging through attention-augmented multi-task deep learning: A novel diagnostic tool

ObjectivesThe objective of this study is to develop a novel multi-task learning approach with attention encoders for classifying histologic subtypes and clinical stages of non-small cell lung cancer (NSCLC), with superior performance compared to currently popular deep-learning models. Material and methodsData were collected from six publicly available datasets in The Cancer Imaging Archive (TCIA). Following the inclusion and exclusion criteria, a total of 4548 CT slices from 758 cases were allocated. We evaluated multiple multi-task learning models that integrate attention mechanisms to resolve challenges in NSCLC subtype classification and clinical staging. These models utilized convolution-based modules in their shared layers for feature extraction, while the task layers were dedicated to histological subtype classification and staging. Each branch sequentially processed features through convolution-based and attention-based modules prior to classification. ResultsOur study evaluated 758 NSCLC patients (mean age, 66.2 years ± 10.3; 473 men), spanning ADC and SCC cases. In the classification of histological subtypes and clinical staging of NSCLC, the MobileNet-based multi-task learning model enhanced with attention mechanisms (MN-MTL-A) demonstrated superior performance, achieving Area Under the Curve (AUC) scores of 0.963 (95 % CI: 0.943, 0.981) and 0.966 (95 % CI: 0.945, 0.982) for each task, respectively. The model significantly surpassed its counterparts lacking attention mechanisms and those configured for single-task learning, as evidenced by P-values of 0.01 or less for both tasks, according to DeLong’s test. ConclusionsThe integration of attention encoder blocks into our multi-task learning network significantly enhanced the accuracy of NSCLC histological subtyping and clinical staging. Given the reduced reliance on precise radiologist annotation, our proposed model shows promising potential for clinical application.

Modernizing the assessment and reporting of adverse events in oncology clinical trials using complementary statistical approaches: a case study of the MOTIVATE trial.

The reporting of adverse events (AEs) is fundamental to characterize safety profiles of novel therapeutic drug classes, however, conventional analysis strategies are suboptimal tools for this task. We therefore attempted to contribute to the modernization of AE analysis by encompassing the dimension of time, the duration and the recurrent nature of AEs induced by these extended treatment durations. This paper presents and highlights the benefits of alternative approaches to modernize AE analysis based on the MOTIVATE prospective study modeling immune-related AEs (irAEs) in patients with solid tumors (regardless of the primary site) treated with immune checkpoint inhibitor irrespective of disease stage. The probability of presenting an irAE over time was estimated using the prevalence function. The time-to-onset (TTO) and the mean number of recurrent irAEs were also assessed. Among the 147 patients analyzed, 39.7% had a melanoma, 37.7% a non-small cell lung cancer (NSCLC) and 74.8% were treated for metastatic disease. Despite a higher proportion of melanoma patients presenting at least one irAE, the prevalence of irAEs was lower in melanoma than in NSCLC patients over time. TTO analysis showed that irAEs occurred earlier in NSCLC patients whereas melanoma patients experienced more recurrent irAEs over the long-term. The prevalence function of non-metastatic and metastatic patients revealed different long-term toxicity profiles. These alternative methodologies capture different toxicity patterns (time-to-onset, recurrent, acute episodic or long-term moderate AEs) and provide a more consistent safety assessment for new therapeutics, thereby assisting clinicians and health authorities in their therapeutic decision-making processes.

Association Between Body Mass Index and Survival in Patients with De Novo Metastatic Non-Small Cell Lung Cancer.

BACKGROUND This retrospective study from a single center included 289 patients diagnosed with advanced non-small cell lung cancer (NSCLC) between 2010 to 2017 and aimed to evaluate the effects of body mass index (BMI) on overall survival. MATERIAL AND METHODS This retrospective study involved 289 patients diagnosed with metastatic-stage NSCLC at a single institution between January 2010 and December 2017. Patients were categorized into 2 groups based on their BMI at diagnosis: those with a BMI <25 kg/m² and those with a BMI ≥25 kg/m². Univariate and multivariate Cox regression analyses were conducted to identify factors associated with overall survival. RESULTS A total of 289 patients (241 men, 48 women) were included in the study, with a mean age of 60.1±11.1 years. Among them, 175 patients (60.6%) had a BMI less than 25 kg/m². Multivariate analysis revealed that BMI, pathological diagnosis, and complete response after first-line treatment were independently associated with survival in patients with lung cancer. Predicted survival time was significantly shorter in the BMI <25 group than in the BMI ≥25 group (9.3 months vs 13.0 months, P<0.05). CONCLUSIONS The study demonstrated that a higher BMI at the time of diagnosis is associated with improved overall survival in patients with de novo metastatic NSCLC. BMI may serve as an important prognostic factor in this patient population. Future prospective, multi-center studies are necessary to further validate the role of BMI in predicting survival outcomes in NSCLC patients across different treatment modalities.

Evaluating machine learning model bias and racial disparities in non-small cell lung cancer using SEER registry data.

Despite decades of pursuing health equity, racial and ethnic disparities persist in healthcare in America. For cancer specifically, one of the leading observed disparities is worse mortality among non-Hispanic Black patients compared to non-Hispanic White patients across the cancer care continuum. These real-world disparities are reflected in the data used to inform the decisions made to alleviate such inequities. Failing to account for inherently biased data underlying these observations could intensify racial cancer disparities and lead to misguided efforts that fail to appropriately address the real causes of health inequity. Estimate the racial/ethnic bias of machine learning models in predicting two-year survival and surgery treatment recommendation for non-small cell lung cancer (NSCLC) patients. A Cox survival model, and a LOGIT model as well as three other machine learning models for predicting surgery recommendation were trained using SEER data from NSCLC patients diagnosed from 2000-2018. Models were trained with a 70/30 train/test split (both including and excluding race/ethnicity) and evaluated using performance and fairness metrics. The effects of oversampling the training data were also evaluated. The survival models show disparate impact towards non-Hispanic Black patients regardless of whether race/ethnicity is used as a predictor. The models including race/ethnicity amplified the disparities observed in the data. The exclusion of race/ethnicity as a predictor in the survival and surgery recommendation models improved fairness metrics without degrading model performance. Stratified oversampling strategies reduced disparate impact while reducing the accuracy of the model. NSCLC disparities are complex and multifaceted. Yet, even when accounting for age and stage at diagnosis, non-Hispanic Black patients with NSCLC are less often recommended to have surgery than non-Hispanic White patients. Machine learning models amplified the racial/ethnic disparities across the cancer care continuum (which are reflected in the data used to make model decisions). Excluding race/ethnicity lowered the bias of the models but did not affect disparate impact. Developing analytical strategies to improve fairness would in turn improve the utility of machine learning approaches analyzing population-based cancer data.

Evolution of treatment strategies for solid tumors with RET rearrangement in China and real-world treatment status of Non-small Cell Lung Cancer (NSCLC)

ObjectiveThe present study endeavors to furnish an exhaustive review of the research advancements on solid tumors harboring RET rearrangement within the Chinese context, particularly emphasizing the examination of real-world therapeutic strategies and clinical outcomes observed in individuals diagnosed with advanced non-small cell lung cancer (NSCLC). The review delves into a critical assessment of the therapeutic efficacy of targeted RET inhibitors, while also scrutinizing the diverse array of treatment modalities employed in the Chinese patient population.MethodsThe study conducted a comprehensive review of the advancements made by Chinese scholars in the realm of RET driver genes. It delved into the analysis of the incidence of RET rearrangements in solid tumors, alongside an examination of the varied treatment paradigms and their current status within China. Utilizing the RECIST 1.1 criteria, the study evaluated the therapeutic efficacy achieved in RET-positive NSCLC patients undergoing diverse treatment modalities. Furthermore, treatment-related adverse events (TRAEs) were meticulously graded following the Common Terminology Criteria for Adverse Events (CTCAE).ResultsA retrospective, multi-center, real-world analysis was conducted, encompassing 64 patients diagnosed with pathologically confirmed RET rearrangement advanced non-small cell lung cancer (NSCLC) between December 2015 and November 2023. Notably, KIF5B-RET emerged as the most prevalent RET fusion partner, accounting for 59.4% of cases. Therapeutic interventions among these patients included specific targeted inhibitors such as Pralsetinib (48.4%), chemotherapy (34.3%), multi-target inhibitors (15.6%), and one case (1.6%) involving immunotherapy combined with anti-angiogenic therapy. In terms of progression-free survival (PFS), Pralsetinib monotherapy demonstrated a median PFS of 16.03 months, outperforming chemotherapy (2.87 months; p < 0.0001), chemotherapy combined with anti-angiogenic therapy (6.90 months; p = 0.048), and multi-target inhibitors (2.50 months; p < 0.0001). Furthermore, the one-year and two-year overall survival (OS) rates for Pralsetinib monotherapy were 64.3% and 46.4%, respectively. Regarding safety, 71.0% of patients receiving Pralsetinib experienced at least one adverse event, with 45.2% classified as grade 3–4 in severity. Notably, no fatalities were attributed to adverse events. Common adverse events included hemoglobin reduction (35.5%) and neutropenia (32.3%), indicative of an overall favorable safety profile for Pralsetinib in this patient population.ConclusionThis study encapsulates the research endeavors and treatment advancements of RET rearrangement solid tumors within the Chinese healthcare landscape, specifically highlighting the diverse real-world therapeutic approaches and their effectiveness in managing advanced RET rearrangement NSCLC among Chinese patients. Notably, targeted RET inhibitors like Pralsetinib have emerged as potent therapeutic agents, exhibiting remarkable efficacy and a manageable safety profile in this patient cohort. These findings underscore the potential of Pralsetinib and similar targeted therapies as novel treatment options for individuals with RET fusion-positive NSCLC.

KRAS G12C mutation in NSCLC in a small genetic center: insights into sotorasib therapy response potential

Lung cancer remains a significant health challenge, characterized by aberrant tissue growth within the pulmonary system. Early carcinogenic events often involve genomic instability and the emergence of a mutator phenotype. In this study, we aimed to explore the mutator phenotype in 89 patients diagnosed with non-small-cell lung cancer (NSCLC). RNA isolation from formalin-fixed paraffin-embedded (FFPE) tissue samples was performed using the Promega ReliaPrep RNA Miniprep System, facilitating gene amplification relevant to cancer through the Archer® FusionPlexComprehensiveThyroid and Lung (CTL) kit. Next-generation sequencing (NGS) on the Illumina NextSeq platform enabled comprehensive analysis of target areas. Utilizing Archer Analysis software, secondary analyses involving data cleansing, alignment, and variant/fusion identification were executed against the human reference genome hg19 (GRCh37). Expression patterns were visualized using HeatMap graphics. Our findings revealed a notable presence of KRAS gene mutations in approximately 20% of NSCLC patients. Among these mutations, the G12C variant was predominant at 50%, followed by G12V and G12D variants at 11.2% each. Notably, patients harboring the G12C variant responded favorably to sotorasib medication. These results underscore the importance of mutational profiling and targeted therapeutic approaches in managing NSCLC, particularly highlighting the promising efficacy of sotorasib in G12C-mutated cases.

Real-world evidence for pembrolizumab in non-small cell lung cancer: a nationwide cohort study.

Based on favourable results from clinical trials, immune checkpoint inhibitors (ICI) have become the standard first line (1 L) systemic anticancer treatment (SACT) for advanced stage non-small cell lung cancer (NSCLC) without targetable mutations. We evaluate whether these results are generalizable to everyday clinical practice and compare overall survival (OS) of patients treated with ICI to a historical cohort of patients treated with chemotherapy and results from clinical trials. Our study comprised all advanced NSCLC patients initiating SACT in 2012-21 in Norway. Clinical characteristics and treatment information was retrieved from Norwegian Health Registries. Survival for all 8416 advanced NSCLC patients treated with SACT increased concurrently with the gradual implementation of ICIs. Median OS of patients treated with 1 L pembrolizumab after 2017 was better (mono-/combination therapy: 13.8/12.8 months) than for patients treated with chemotherapy before 2017 (8.0 months). Although median OS for patients treated with pembrolizumab was lower in clinical practice than clinical trials (Keynote-024/189: 26.3/22.0 months), the survival benefit relative to chemotherapy was similar. Our nationwide study demonstrated a survival benefit over conventional chemotherapy of a similar magnitude as observed in clinical trials and confirms the effectiveness of pembrolizumab in routine clinical practice.

G9a/DNMT1 co-targeting inhibits non-small cell lung cancer growth and reprograms tumor cells to respond to cancer-drugs through SCARA5 and AOX1

The treatment of non-small cell lung cancer (NSCLC) patients has significantly improved with recent therapeutic strategies; however, many patients still do not benefit from them. As a result, new treatment approaches are urgently needed. In this study, we evaluated the antitumor efficacy of co-targeting G9a and DNMT1 enzymes and its potential as a cancer drug sensitizer. We observed co-expression and overexpression of G9a and DNMT1 in NSCLC, which were associated with poor prognosis. Co-targeting G9a/DNMT1 with the drug CM-272 reduced proliferation and induced cell death in a panel of human and murine NSCLC cell lines. Additionally, the transcriptomes of these cells were reprogrammed to become highly responsive to chemotherapy (cisplatin), targeted therapy (trametinib), and epigenetic therapy (vorinostat). In vivo, CM-272 reduced tumor volume in human and murine cell-derived cancer models, and this effect was synergistically enhanced by cisplatin. The expression of SCARA5 and AOX1 was induced by CM-272, and both proteins were found to be essential for the antiproliferative response, as gene silencing decreased cytotoxicity. Furthermore, the expression of SCARA5 and AOX1 was positively correlated with each other and inversely correlated with G9a and DNMT1 expression in NSCLC patients. SCARA5 and AOX1 DNA promoters were hypermethylated in NSCLC, and SCARA5 methylation was identified as an epigenetic biomarker in tumors and liquid biopsies from NSCLC patients. Thus, we demonstrate that co-targeting G9a/DNMT1 is a promising strategy to enhance the efficacy of cancer drugs, and SCARA5 methylation could serve as a non-invasive biomarker to monitor tumor progression.

Methylation modification is a poor prognostic factor in non-small cell lung Cancer and regulates the tumor microenvironment: mRNA molecular structure and function

Non-small cell lung cancer (NSCLC) is the most common and deadly type of lung cancer, and its poor prognosis is closely related to the complex interactions of the tumor microenvironment. Through methylation analysis of tumor tissue samples from NSCLC patients, combined with high-throughput sequencing technology, the methylation status and structural characteristics of mRNA molecules were studied. Bioinformatics tools were used to analyze the regulatory effects of methylation modification on mRNA expression and genes associated with the tumor microenvironment. The results showed that the methylation level of specific mRNA was significantly correlated with the expression changes of tumor microenvironment-related factors. In addition, methylation modification affected mRNA stability and translation efficiency, further altering the metabolic activity and immune escape capacity of tumor cells. The results showed that mRNA with high methylation level was significantly associated with poor prognosis. Methylation modification profoundly affects the tumor microenvironment and prognosis of non-small cell lung cancer by altering the structure and function of mRNA molecules.

Impact of perioperative high-protein nutritional support on the quality of life of patients with primary lung cancer: a Russian prospective multicenter comparative study (NUTRILUNC study)

BACKGROUND: Individuals over the age of 70 comprise over half of operable patients with stage 0–IIIA lung cancer. In the early postoperative period of this cohort, pain, fatigue, insomnia, and/or mood disturbances are the four most common symptoms, which can significantly diminish quality of life and functional status. Perioperative nutritional support in such patients, which enhances exercise tolerance, can have a positive impact on their quality of life and socialization. AIM: To assess the effect of perioperative nutritional support using high-protein oral nutrition supplements on the general health and quality of life of non-small cell lung cancer patients during the postoperative period. MATERIALS AND METHODS: Patients with primary non-small cell lung cancer (n=112, 69 males), aged 57.2±8.2, who were awaiting lung surgery and at risk of malnutrition (Nutritional Risk Screening Assessment 2002 score ≥3) were randomly assigned into two groups. Oral nutritional support (Nutridrink Compact Protein, Nutricia LLC) was administered to the study group (n=55) at a rate of 250 ml/d (36 g of protein, 612 kcal) for 14 days prior to and 14 days following the surgery, in addition to the standard diet. Control group patients (n=57) were provided a standard diet. The quality of life was assessed using the Quality of Life Questionnaire Core-30. Results are presented as mean ± standard deviation. Differences were considered significant at p ≤0.05. RESULTS: Throughout the entire observation period, the study group exhibited superior growth indicators in terms of general health status, physical, and role functioning than the control group (p 0.05). The study group patients exhibited a propensity toward improved emotional functioning, and by the end of the study, weakness and insomnia were less pronounced (p 0.05). Other indicators did not exhibit any significant variations. CONCLUSION: Нigh-protein perioperative oral nutrition supplements exert a positive impact on the quality of life of non-small cell lung cancer patients.

Dosimetric predictors of acute radiation pneumonitis and esophagitis in hypofractionated thoracic irradiation of non-small cell lung cancer patients with poor prognostic factors: Dosimetric predictors of acute radiation pneumonitis and esophagitis following hypofractionation in NSCLC

PurposeThe proliferation rates of non-small cell lung cancer (NSCLC) and associated radiation resistance highlight the potential of hypofractionated radiotherapy (hypoRT). However, radiation pneumonitis and esophagitis remain dose-limiting adverse events. This study aims to investigate dosimetric factors influencing the risk of pneumonitis and esophagitis in highly multimorbid patients undergoing moderately hypofractionated radiotherapy. Methods Forty-seven NSCLC patients with poor performance status treated between January 2014 and July 2021 were included. Dosimetric parameters including mean lung dose (MLD), percentage of normal (ipsi-/contralateral) lung volume (Vx) receiving ≥x Gy [x=20 Gy, 18 Gy, 10 Gy, 5 Gy]; Mean heart dose (MHD), percentage of the heart volume (HVx) receiving ≥x Gy [x=20 Gy, 10 Gy, 5 Gy]; Mean esophageal dose (MED), percentage of esophagus volume (EVx) receiving ≥x Gy [x=40 Gy, 30 Gy, 20 Gy, 18 Gy, 10 Gy, 5 Gy] were analyzed retrospectively. Acute radiation pneumonitis/esophagitis events were assessed within 6/3 months posttreatment. Statistical analyses included Random forests, binary logistic regression, and linear regression. ResultsAmong the 47 patients with compromised lung function and poor prognostic factors, 8 (17%) and 26 (55%) patients developed all-grade pneumonitis or esophagitis, while 4 (9%) and 10 (21%) patients developed CTCAE grade ≥2 pneumonitis and esophagitis, respectively. Exploratory analyses suggest that V10, V18, and mean lung dose (MLD) values are associated with an increased risk of pneumonitis. Linear regressions confirmed this for MLD values greater than 9.2 Gy (p=0.050). Additionally, higher V5 and V10 values in the contralateral lung were associated with a greater risk of pneumonitis (p=0.013/ p=0.032). Dmax proved to be a significant predictor of esophagitis (p=0.020). Moreover, evidence suggests that EV5 and EV40 may portend esophagitis onset. ConclusionThis study provides insights into dosimetric factors influencing pneumonitis/esophagitis development in NSCLC patients undergoing hypoRT. While MLD and Dmax emerged as significant predictors of pneumonitis and esophagitis, the small sample size limited the depth of conclusions. Further research with larger cohorts is warranted to validate these observations, potentially optimizing treatment planning and outcomes in this challenging patient population

Correlation Between the Extent of N1 Lymph Node Station Examination and Prognosis in Stage I Nonsmall Cell Lung Cancer Patients: One Station is Insufficient

BackgroundExamination standards for hilar and intrapulmonary (N1) lymph nodes (LNs) have been debated. The objective of this study was to assess the prognostic significance of the extent of examination for N1 LN stations in patients with pathological stage I nonsmall cell lung cancer (NSCLC). MethodsA total of 1868 patients were identified and divided into 3 groups on the basis of the number of N1 stations examined: group A (≥3 stations), group B (2 stations) and group C (1 station). Moreover, we investigated the prognostic significance of each individual N1 station examined. The primary outcome was 5-year disease-free survival (DFS). ResultsOverall, 1062, 607, and 199 patients were in groups A, B, and C, respectively. The baseline demographic and clinical characteristics were similar among the groups, except for the tumor side. The 5-year DFS rates were comparable between groups A and B (85.1% vs. 82.7%, P = .3), both of which were significantly greater than that of group C (74.4%) (P < .01). Similar results were observed for the corresponding 5-year overall survival rates. The number of N1 stations examined was an independent predictor in multiple analyses. Additionally, the examination of stations 10 and 13 were independent favorable predictors for 5-year DFS. ConclusionFor patients with pathological stage I NSCLC, examination of only 1 N1 station is insufficient. Examinations of a minimum of two N1 stations, including stations 10 and 13, is recommended to obtain the optimal survival benefit.

A comparative dosimetric evaluation of dynamic conformal arc therapy and volumetric modulated arc therapy for lung stereotactic body radiotherapy

PurposeThis study assesses the viability of utilizing dynamic conformal arc therapy (DCAT) as an alternative to volumetric-modulated arc therapy (VMAT) in stereotactic body radiation therapy (SBRT) for lung cancer, with a focus on four-dimensional computed tomography (4DCT) in free-breathing conditions. Materials and methodsWe selected four non-small cell lung cancer (NSCLC) patients who had previously undergone VMAT SBRT and re-planned their treatment using DCAT. We compared the DCAT and VMAT plans based on dose distribution, conformity index (CI), homogeneity index (HI), gradient index (GI), and total monitor units (MUs). Quality assurance (QA) assessments for both plans were conducted using the Octavius 4D system (PTW, Freiburg, Germany). ResultsThe results showed that CIPaddick was 0.80 ± 0.06 and 0.79 ± 0.04 (p-value >0.05), HI was 1.16 ± 0.03 (p-value <0.05) and 1.07 ± 0.02, GI was 3.91 ± 0.05 and 3.40 ± 0.05 (p-value <0.05), and MU was 1880.42 ± 135.19 and 5020.82 ± 188.03 for DCAT and VMAT, respectively (p-value <0.05). The average gamma passing rate exceeded 95 % with a 2 %/2 mm criteria. The dose distribution displayed remarkable similarity between DCAT and VMAT. ConclusionThe DCAT technique exhibits the capacity to deliver PTV dose distributions comparable to those achieved with VMAT, while significantly reducing treatment duration.

Effect of Perioperative Factors on Short-Term Outcomes in Patients with Non-Small Cell Lung Cancer Over 60 Years of Age.

People in China have gradually entered old age society, and the number of lung cancer cases is expected to increase annually among the elderly. This study aimed to retrospectively explore the association between perioperative factors and short-term outcomes in elderly patients with non-small cell lung cancer (NSCLC). A total of 490 elderly patients with NSCLC between January 1, 2003, and December 31, 2009, were selected. Perioperative factors were grouped and analyzed according to postoperative complications (PPCs) and length of hospital stay. A logistic regression analysis model was used to screen for the independent predictors of patient prognosis. The primary endpoint was postoperative complications and the secondary endpoint was postoperative hospital stay. Of all patients, 344 (70.2%) developed postoperative complications, and the average length of stay after surgery was 14.0±5.6 days. Perioperative fentanyl equivalents>28.7μg/kg and duration of surgery>4.4h were associated were associated with an increased risk of postoperative complications (P < 0.05); intraoperative blood loss (IBL) > 200 mL was associated with extended hospital stay (P < 0.05). This study suggested that Perioperative factors may affect the short-term prognosis of elderly NSCLC patients after surgery. Perioperative fentanyl equivalents>28.7μg/kg, surgery duration, and IBL may be independent predictors of short-term outcomes in elderly patients.

A subset of neutrophils activates anti-tumor immunity and inhibits non-small-cell lung cancer progression.

Neutrophils in the tumor microenvironment (TME) are heterogeneous populations associated with cancer prognosis and immunotherapy. However, the plasticity and function of heterogeneous neutrophils in the TME of non-small-cell lung cancer (NSCLC) remain unclear. Here, we show that neutrophils produce high levels of interleukin (IL)-8, which induce the differentiation of CD74highSiglecFlow neutrophils and suppress the generation of CD74lowSiglecFhigh neutrophils in the TME of IL-8-humanized NSCLC mice. The CD74highSiglecFlow neutrophils boost anti-tumor Tcell responses via antigen cross-presentation. Deleting CD74 in IL-8-humanized neutrophils impairs Tcell activation and exacerbates NSCLC progression, whereas a CD74 agonist enhances Tcell activation and the efficacy of anti-programmed cell death 1 (PD-1) or osimertinib therapies. Additionally, the CD74highCD63low neutrophils in the TME and peripheral blood of advanced NSCLC patients phenocopy the CD74highSiglecFlow neutrophils in the TME of NSCLC mice and correlate well with the responsiveness to anti-PD-1 plus chemotherapies. These findings demonstrate an IL-8-CD74high neutrophil axis that promotes anti-tumor immunity in NSCLC.

Machine learning models reveal ARHGAP11A's impact on lymph node metastasis and stemness in NSCLC.

Most patients with non-small cell lung cancer (NSCLC) are diagnosed at an advanced stage of the disease, which complicates treatment due to a heightened risk of metastasis. Consequently, the timely identification of biomarkers associated with lymph node metastasis is essential for improving the clinical management of NSCLC patients. In this research, the WGCNA algorithm was utilized to pinpoint genes linked to lymph node metastasis in NSCLC. A cluster analysis was carried out to investigate how these genes correlate with the prognosis and the outcomes of immunotherapy for NSCLC patients. Following this, diagnostic and prognostic models were created and validated through various machine learning methodologies. The random forest technique highlighted the importance of ARHGAP11A, leading to an in-depth examination of its role in NSCLC. By analyzing 78 tissue chip samples from NSCLC patients, the study confirmed the association between ARHGAP11A expression, patient prognosis, and lymph node metastasis. Finally, the influence of ARHGAP11A on NSCLC cells was assessed through cell function experiments. This research utilized the WGCNA technique to identify 25 genes that are related to lymph node metastasis, clarifying their connections with tumor invasion, growth, and the activation of stemness pathways. Cluster analysis revealed significant associations between these genes and lymph node metastasis in NSCLC, especially concerning immunotherapy and targeted treatments. A diagnostic system that combines various machine learning approaches demonstrated strong efficacy in forecasting both the diagnosis and prognosis of NSCLC. Importantly, ARHGAP11A was identified as a key prognostic gene associated with lymph node metastasis in NSCLC. Molecular docking analyses suggested that ARHGAP11A has a strong affinity for targeted therapies within NSCLC. Additionally, immunohistochemical assessments confirmed that higher levels of ARHGAP11A expression correlate with unfavorable outcomes for NSCLC patients. Experiments on cells showed that reducing ARHGAP11A expression can hinder the proliferation, metastasis, and stemness traits of NSCLC cells. This investigation reveals the novel insight that ARHGAP11A may function as a potential biomarker connected to lymph node metastasis in NSCLC. Moreover, reducing the expression of ARHGAP11A has demonstrated the ability to diminish tumor stemness characteristics, presenting a promising opportunity for improving treatment strategies for this condition.

The effects of immune checkpoint inhibitors vs. chemotherapy combined with brain radiotherapy in non-small cell lung cancer patients with brain metastases

BackgroundNon-small cell lung cancer (NSCLC) is a prevalent form of cancer, often leading to brain metastases (BM) and a significant decline in patient prognosis. Whether immune checkpoint inhibitors (ICIs) combined with brain radiotherapy is superior to conventional chemotherapy combined with brain radiotherapy in those patients remains to be explored.Materials and methodsOur study enrolled 161 NSCLC patients with BM who underwent either ICIs combined with brain radiotherapy or chemotherapy combined with brain radiotherapy. End points included overall survival (OS), progression-free survival (PFS), intracranial PFS (IPFS), and extracranial PFS (EPFS). Univariate and multivariate Cox regressions were employed to identify prognostic risk variables.ResultsPatients receiving ICIs combined with brain radiotherapy exhibited significantly longer OS compared to those receiving chemotherapy combined with brain radiotherapy (34.80 months vs. 17.17 months, P = 0.005). In the Cox regression analysis, chemotherapy combined with brain radiotherapy (HR, 1.82; 95% CI, 1.09–3.05; P = 0.023), smoking (HR, 1.75; 95% CI, 1.02–2.99; P = 0.043) and squamous cell carcinoma (HR, 2.59; 95% CI, 1.31–5.13; P = 0.006) were associated with a worse prognosis. After propensity score matching (PSM), this finding remained consistent with before PSM (43.73 months vs. 17.17 months, P = 0.018). Squamous cell carcinoma (HR, 2.46; 95% CI, 1.15–5.26; P = 0.021) and CT + RT (HR, 2.11; 95% CI, 1.15–3.88; P = 0.016) were associated with a less favorable prognosis.ConclusionThe study suggests that the combination of ICIs and brain radiotherapy provides superior OS for NSCLC patients with BM, compared to the chemotherapy combined with brain radiotherapy.

Clinical characteristics and prognostic factors of epidermal growth factor receptor-mutated non-small cell lung cancer transformed into small-cell lung cancer after treatment

Objective: To analyze the clinical characteristics and prognostic factors of non-small cell lung cancer (NSCLC) patients with sensitive epidermal growth factor receptor (EGFR) mutations who developed small cell lung cancer (SCLC) transformation after treatment with EGFR tyrosine kinase inhibitors (TKI). Methods: We conducted a retrospective collection of clinical data for 21 patients with advanced EGFR mutant NSCLC who developed SCLC transformation after EGFR-TKI treatment at Beijing Chest Hospital, Capital Medical University from January 2015 to December 2021. The clinical characteristics were summarized and the prognosis analysis was conducted. Patients were followed up until February 2024. The efficacy was evaluated using Solid Tumor Response Evaluation Criteria, and survival curves were plotted using the Kaplan-Meier method, and the log-rank test was used to compare the differences in survival time (OS) between limited stage and extensive stage in transformed SCLC patients. Cox proportional hazards model was used to analyze the influencing factors of survival after SCLC transformation. Results: Among the 21 patients, there were 5 males and 16 females, with an age range of 33-74 years old [(58.9±2.6) years old]. All 21 patients were adenocarcinoma with sensitive EGFR mutations. There were 18 cases (85.7%) with EGFR gene 19del mutation, including 1 case of 19del+anaplastic lymphoma kinase (ALK) mutation, and 3 cases of L858R mutation. Among the transformed SCLC, there were 11 cases of pure SCLC and 10 cases of mixed SCLC (coexisting of adenocarcinoma and small cell carcinoma components). The median time from diagnosis of NSCLC to SCLC transformation was 12.0 months (95%CI: 7.6-16.3 months). Among the 21 cases of SCLC transformation, there were 13 cases with the extensive stage and 8 cases with the limited stage. Among them, 16 patients received systemic chemotherapy based on etoposide, of which 13 cases could be evaluated for efficacy, 11 cases could be calculated for PFS. Five cases had partial remission, 5 cases were stable, 3 cases had disease progression, and 3 cases cloud not be evaluated. The median progression free survival time (PFS) was 4.8 months (95%CI: 2.8-6.8 months). The median survival time (OS) after SCLC transformation in 21 patients was 10.6 months (95%CI: 7.0-14.2 months), with a median OS of 8.8 months (95%CI: 6.3-11.4 months) for patients with the extensive stage and 27.5 months (95%CI: 9.6-34.4 months) for patients with the limited stage, with statistically significant differences (P=0.002). Cox proportional hazards model analysis showed that the limited stage after SCLC transformation was a protective factor for OS (HR=0.32, 95%CI: 0.12-0.73, P=0.010). The median OS of 21 patients from the diagnosis of lung cancer was 24.9 months (95%CI: 13.0-36.7 months). Conclusions: NSCLC patients with SCLC transformation are all adenocarcinomas, and the proportion of EGFR19del mutations is relatively high. After SCLC transformation, the standard chemotherapy regimen for SCLC is generally used for treatment. The OS after SCLC transformation is related to the stage, and the prognosis is better in the limited stage.