ALK detection was performed on 2813 EGFR-unmutated NSCLC cases by simultaneous use of immunohistochemistry (VENTANA® anti-ALK D5F3, Roche Molecular Systems, Inc., Rotkreuz, Switzerland) and fluorescence in situ hybridization with the ALK break apart and the ALK/EML4 fusion probe (ZytoVision, Bremerhaven, Germany). A total of 33 cases were positive discordant (FISH-positive, IHC-negative) and 17 cases were negative discordant (FISH-negative, IHC-positive). This study\'s aim was to reevaluate the methods used and compare discordant samples to positive concordant samples in order to ellucidate the differences. FISH signal variants were examined and compared. Positive discordant cases featured one pattern of ALK rearrangement in 41.4%, two patterns in 48.3%, and three patterns in 10.3% of analysed samples, with a higher variability of detected patterns and a higher number of ALK copy gains. Positive concordant cases displayed one pattern of rearrangement in 82%, two patterns in 17.8%, and three patterns in 0.6% of analysed samples. The association between number of patterns and concordance/discordance was statistically significant (p < 0.05). Eleven positive discordant and two negative concordant cases underwent NGS analysis, which resulted in identification of ALK fusion in one positive discordant and two negative discordant cases. Positive protein expression regardless of FISH result correlated more with a positive NGS result compared to samples with a positive FISH result with negative protein expression. FISH analysis was able to detect atypical or heterogenous patterns of rearrangement in a proportion of cases with negative protein expression, which may be associated with more extensive genetic alterations rather than true ALK rearrangement.

UNASSIGNED: Using a previously unreported Peruvian registry of patients treated for early-stage non-small cell lung cancer (NSCLC), this study explored whether wedge resection and lobectomy were equivalent regarding survival and impact on radiologic-pathologic variables.
UNASSIGNED: This observational, analytical, longitudinal study used propensity score-matched (PSM) analysis of a single-center retrospective registry of 2,570 patients with pathologic stage I-II NSCLC who were treated with wedge resection (n=1,845) or lobectomy (n=725) during 2000-2020. After PSM, 650 cases were analyzed (resection, n=325; lobectomy, n=325) through preoperative and clinical variables, including patients with ≥1 lymph node removed. Kaplan-Meier curves and multivariable Cox proportional hazard models were created for 5-year overall survival (OS), disease-free survival (DFS), and locoregional-recurrence-free survival (LRFS).
UNASSIGNED: The principal complication was operative pain persisting >7 days for lobectomy versus wedge resection (58% vs. 23%, p=0.034) and shorter hospital stays for resection than for lobectomy (5.3 days vs. 12.8 days, p=0.009). The 5-year OS (84.3% vs. 81.2%, p=0.09) and DFS (79.1% vs. 74.1%, p=0.07) were similar and statistically insignificant between resections and lobectomies, respectively. LRFS was worse overall following wedge resection than lobectomy (79.8% vs. 91.1%, p<0.02). Nevertheless, in the PSM analysis, both groups experienced similar LRFS when the resection margin was >10 mm (90.9% vs. 87.3%, p<0.048) and ≥4 lymph nodes were removed (82.8% vs. 79.1%, p<0.011).
UNASSIGNED: Both techniques led to similar OS and DFS at 5 years; however, successful LRFS required a wedge resection with a surgical margin and adequate lymph node removal to obtain outcomes similar to lobectomy.

UNASSIGNED: Numerous studies have investigated methods of predicting postoperative pulmonary complications (PPCs) in lung cancer surgery, with chronic obstructive pulmonary disease (COPD) and low forced expiratory volume in 1 second (FEV1) being recognized as risk factors. However, predicting complications in COPD patients with preserved FEV1 poses challenges. This study considered various diffusing capacity of the lung for carbon monoxide (DLCO) parameters as predictors of pulmonary complication risks in mild COPD patients undergoing lung resection.
UNASSIGNED: From January 2011 to December 2019, 2,798 patients undergoing segmentectomy or lobectomy for non-small cell lung cancer (NSCLC) were evaluated. Focusing on 709 mild COPD patients, excluding no COPD and moderate/severe cases, 3 models incorporating DLCO, predicted postoperative DLCO (ppoDLCO), and DLCO divided by the alveolar volume (DLCO/VA) were created for logistic regression. The Akaike information criterion and Bayes information criterion were analyzed to assess model fit, with lower values considered more consistent with actual data.
UNASSIGNED: Significantly higher proportions of men, current smokers, and patients who underwent an open approach were observed in the PPC group. In multivariable regression, male sex, an open approach, DLCO <80%, ppoDLCO <60%, and DLCO/VA <80% significantly influenced PPC occurrence. The model using DLCO/VA had the best fit.
UNASSIGNED: Different DLCO parameters can predict PPCs in mild COPD patients after lung resection for NSCLC. The assessment of these factors using a multivariable logistic regression model suggested DLCO/VA as the most valuable predictor.

BACKGROUND: Current treatment guidelines for patients with epidermal growth factor receptor (EGFR)-mutated metastatic non-small cell lung cancer (mNSCLC) recommend EGFR tyrosine kinase inhibitors (TKIs) as the standard of care for first-line treatment, with third-generation osimertinib the preferred choice. However, most patients develop resistance to targeted therapy, and subsequent systemic chemotherapy is recommended. The aim of this study was to characterize the subsequent line of therapy (LOT) following osimertinib in patients with EGFR-mNSCLC.
METHODS: Medical and pharmacy claims of adults who initiated a subsequent LOT (index) after initial osimertinib discontinuation between November 2015 and September 2019 were analyzed retrospectively.
RESULTS: A total of 135 patients met the inclusion criteria. After metastatic diagnosis, 22.2% and 49.6% of patients were treated with osimertinib in the first and second line, respectively. After osimertinib discontinuation, most patients were treated with a platinum-based chemotherapy regimen (57%), of which 40.3% included immuno-oncology therapy. Reuse or continuation of EGFR TKIs was also common (24%). Overall, the median time to treatment discontinuation for the index LOT was 2.4 months. Proportions of patients with ≥ 1 inpatient or emergency department visit were 31.9% and 35.6%, respectively.
CONCLUSIONS: The duration of the LOT following osimertinib was short and associated with tolerability issues underscoring a high unmet need for new therapies to address EGFR TKI resistance.

Brain metastasis (BM) is one of the main causes of death in patients with non-small cell lung carcinoma. The specific pathological processes of BM, which are inextricably linked to the brain tumor microenvironment, such as the abundance of astrocytes, lead to limited treatment options and poor prognosis. Reactive astrocytes are acquired in the BM; however, the underlying mechanisms remain unclear. This study aimed to explore the mechanisms by which astrocytes promote BM development. We determined the crucial role of reactive astrocytes in promoting the proliferation and migration of brain metastatic lung tumor cells by upregulating protocadherin 1 (PCDH1) expression in an in vitro co-culture model. The overexpression of PCDH1 was confirmed in clinical BM samples using immunohistochemical staining. Survival analysis indicated that high-PCDH1 expression was associated with poor survival in patients with lung adenocarcinoma. In vivo assays further showed that silence of PCDH1 effectively inhibited the tumor progression of brain metastases and prolonged the survival of animals. RNA sequencing has revealed that PCDH1 plays an important role in cell proliferation and adhesion. In conclusion, the present study revealed the promoting role of astrocytes in enhancing the aggressive phenotype of brain metastatic tumor cells by regulating the expression of PCDH1, which might be a biomarker for BM diagnosis and prognosis, suggesting the potential efficacy of targeting important astrocyte-tumor interactions in the treatment of patients with non-small cell lung carcinoma with BM.

Lung cancer is the leading cause of cancer-associated mortality and non-small cell lung carcinoma (NSCLC) constitutes 85 % of all lung cancer cases. This malignancy is characterized by multifactorial risk factors, poor prognosis, and deplorable clinical outcome. Considerable evidence indicates that there is inter-individual variability in the lung cancer predisposition and survival due to genetic variations introduced by genetic polymorphisms between individuals, indirectly affecting the lung cancer susceptibility and the patient survival. In the past decades, immune landscape in the tumour environment and host immune response are constantly implicated as determining factor in NSCLC development and patients\' survival. With the change of paradigm in NSCLC treatment to immunotherapy and increasing recognition of the role of the immune system in cancer development and survival, the inspection of single nucleotide polymorphisms (SNPs) in immunomodulated markers associated with the risk and prognosis for NSCLC is crucial. Despite extensive studies reported the implication of SNPs in predicting the risk and survival of NSCLC. SNPs in the genes that modulate immune response in NSCLC have not been reviewed before. Hence, this review uncovers the evidence on the genetic polymorphisms of immunomodulatory markers which include immune checkpoints, immune checkpoint inhibitors, chemokines, interleukins, human leukocyte antigen and its receptors, and antigen presenting machinery genes, and their significance in the susceptibility, prognosis and survival in NSCLC. The identification of genetic factors associated with NSCLC risk and survival provides invaluable information for a greater comprehension of the pathogenesis and progression of the disease, also to refine prognosis and personalize clinical care in early and advanced-stages disease.

UNASSIGNED: The main objective of this study was to investigate the antitumor effect of a mouse anti-human glypican-1 (GPC1) monoclonal antibody (mAb) on non-small cell lung carcinoma (NSCLC) and associated molecular mechanisms.
UNASSIGNED: The anti-proliferative and anti-migratory activities of anti-GPC1 mAb were examined in A549 and H460 NSCLC cells and LL97A lung fibroblasts. The inhibitory effect of anti-GPC1 mAb on tumor growth was evaluated in an orthotopic lung tumor model.
UNASSIGNED: The in vitro study showed that anti-GPC1 mAb profoundly inhibited the anchorage-independent growth of A549 and H460 NSCLC cells and exhibited relatively high cytotoxic activities towards LL97A lung fibroblasts, A549/LL97A and H460/LL97A coculture spheroids. Moreover, anti-GPC1 mAb significantly decreased the expression of phospho-Src (p-Src; Tyr416), p-Akt (Ser473) and β-catenin in the co-cultured LL97A lung fibroblasts, and the expression of phospho-mitogen-activated protein kinase kinase (p-MEK; Ser217/221) and phospho-90 kDa ribosomal s6 kinase (p-p90RSK; Ser380) in co-cultured A549 cells. When anti-GPC1 mAb was administered to tumor-bearing mice, the inhibitory effect of anti-GPC1 mAb on the orthotopic lung tumor growth was not statistically significant. Nonetheless, results of Western blot analysis showed significant decrease in the phosphorylation of fibroblast growth factor receptor 1 (FGFR1) at Tyr766, Src at Tyr416, extracellular signal-regulated kinase (ERK) at Thr202/Tyr204, 90 kDa ribosomal S6 kinase (RSK) at Ser380, glycogen synthase kinases 3α (GSK3α) at Ser21 and GSK3β at Ser9 in tumor tissues. These data implicate that anti-GPC1 mAb treatment impairs the interaction between tumor cells and tumor associated fibroblasts by attenuating the paracrine FGFR signal transduction.
UNASSIGNED: The relatively potent cytotoxicity of anti-GPC1 mAb in lung fibroblasts and its potential inhibitory effect on the paracrine FGFR signal transduction warrant further studies on the combined use of this mAb with targeted therapeutics to improve therapeutic outcomes in lung cancer.

UNASSIGNED: Stereotactic radiosurgery (SRS) or fractionated stereotactic radiotherapy (FSRT) are increasingly used as initial therapies for brain metastases (BM). We aimed to assess the outcomes of SRS/FSRT in patients aged ≥65 years who had 1-10 BM from non-small cell lung cancer (NSCLC).
UNASSIGNED: We retrospectively reviewed 91 elderly NSCLC patients with 222 BM who were treated with SRS/FSRT at two institutions between 2010 and 2020. The primary endpoint was overall survival (OS) after SRS/FSRT. In addition, in-field local control (IFLC) within the treated field was evaluated. Statistical analysis was performed to identify the prognostic factors affecting OS and IFLC.
UNASSIGNED: During a median follow-up of 18 months, the median OS was 32 months. The 1- and 2-year survival rates were 69.8 and 56.1%, respectively. In multivariate analysis, the NSCLC-specific graded prognostic assessment (GPA) score (p=0.007) and administration of systemic therapy (p=0.039) were defined as prognosticators affecting OS. The median IFLC period was 31 months, and the 1- and 2-year IFLC rates were 75.9 and 57.6%, respectively. The total BM volume (p=0.042) significantly affected IFLC. No severe adverse events were reported after SRS/FSRT.
UNASSIGNED: SRS/FSRT is an effective upfront treatment option for BM arising from NSCLC in elderly patients, with a good OS without severe side effects. Higher GPA score and active systemic treatment were associated with improved OS, indicating that elderly patients are significant candidates for SRS/FSRT.

UNASSIGNED: Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are effective for treating non-small cell lung cancer (NSCLC) harboring EGFR mutations. However, higher tumor programmed death ligand-1 (PD-L1) expression is associated with a poor response to EGFR-TKIs, and information on the comparison between afatinib and osimertinib in PD-L1-positive EGFR-mutant NSCLC is scarce.
UNASSIGNED: We retrospectively analyzed data of patients with PD-L1-positive EGFR-mutant NSCLC to compare the effectiveness of afatinib and osimertinib.
UNASSIGNED: A total of 177 patients were included in the study. The Cox proportion hazard model was adjusted for age, sex, performance status, EGFR mutation status, PD-L1 expression level, and brain metastasis, revealing that there was no significant difference in risk for progression [hazard ratio (HR)=0.99, 95% confidence interval (CI)=0.64-1.53] or death (HR=0.96, 95% CI=0.54-1.73) between afatinib and osimertinib.
UNASSIGNED: In conclusion, the EGFR-TKI treatment duration and overall survival after the treatment with afatinib or osimertinib were similar in patients with PD-L1-positive EGFR-mutant NSCLC in the present study.

Non-small cell lung carcinoma (NSCLC) is a prevalent and aggressive form of lung cancer, with a poor prognosis for metastatic disease. Immunotherapy, particularly immune checkpoint inhibitors (ICIs), has revolutionized the management of NSCLC, but response rates are highly variable. Identifying reliable predictive biomarkers is crucial to optimize patient selection and treatment outcomes. This systematic review aimed to evaluate the current state of artificial intelligence (AI) and machine learning (ML) applications in predicting the response to immunotherapy in NSCLC. A comprehensive literature search identified 19 studies that met the inclusion criteria. The studies employed diverse AI/ML techniques, including deep learning, artificial neural networks, support vector machines, and gradient boosting methods, applied to various data modalities such as medical imaging, genomic data, clinical variables, and immunohistochemical markers. Several studies demonstrated the ability of AI/ML models to accurately predict immunotherapy response, progression-free survival, and overall survival in NSCLC patients. However, challenges remain in data availability, quality, and interpretability of these models. Efforts have been made to develop interpretable AI/ML techniques, but further research is needed to improve transparency and explainability. Additionally, translating AI/ML models from research settings to clinical practice poses challenges related to regulatory approval, data privacy, and integration into existing healthcare systems. Nonetheless, the successful implementation of AI/ML models could enable personalized treatment strategies, improve treatment outcomes, and reduce unnecessary toxicities and healthcare costs associated with ineffective treatments.