The prognostic value of bioinformatics analysis of ECM receptor signaling pathways and LAMB1 identification as a promising prognostic biomarker of lung adenocarcinoma.

The extracellular matrix (ECM) is a complex and dynamic network of cross-linked proteins and a fundamental building block in multicellular organisms. Our study investigates the impact of genes related to the ECM receptor interaction pathway on immune-targeted therapy and lung adenocarcinoma (LUAD) prognosis. This study obtained LUAD chip data (GSE68465, GSE31210, and GSE116959) from NCBI GEO. Moreover, the gene data associated with the ECM receptor interaction pathway was downloaded from the Molecular Signature Database. Differentially expressed genes were identified using GEO2R, followed by analyzing their correlation with immune cell infiltration. Univariate Cox regression analysis screened out ECM-related genes significantly related to the survival prognosis of LUAD patients. Additionally, Lasso regression and multivariate Cox regression analysis helped construct a prognostic model. Patients were stratified by risk score and survival analyses. The prognostic models were evaluated using receiver operating characteristic curves, and risk scores and prognosis associations were analyzed using univariate and multivariate Cox regression analyses. A core gene was selected for gene set enrichment analysis and CIBERSORT analysis to determine its function and tumor-infiltrating immune cell proportion, respectively. The results revealed that the most abundant pathways among differentially expressed genes in LUAD primarily involved the cell cycle, ECM receptor interaction, protein digestion and absorption, p53 signaling pathway, complement and coagulation cascade, and tyrosine metabolism. Two ECM-associated subtypes were identified by consensus clustering. Besides, an ECM-related prognostic model was validated to predict LUAD survival, and it was associated with the tumor immune microenvironment. Additional cross-analysis screened laminin subunit beta 1 (LAMB1) for further research. The survival time of LUAD patients with elevated LAMB1 expression was longer than those with low LAMB1 expression. Gene set enrichment analysis and CIBERSORT analyses revealed that LAMB1 expression correlated with tumor immune microenvironment. In conclusion, a prognostic model of LUAD patients depending on the ECM receptor interaction pathway was constructed. Screening out LAMB1 can become a prognostic risk factor for LUAD patients or a potential target during LUAD treatment.

Predicting invasion in early-stage ground-glass opacity pulmonary adenocarcinoma: a radiomics-based machine learning approach.

BACKGROUND: To design a pulmonary ground-glass nodules (GGN) classification method based on computed tomography (CT) radiomics and machine learning for prediction of invasion in early-stage ground-glass opacity (GGO) pulmonary adenocarcinoma. METHODS: This retrospective study included pulmonary GGN patients who were histologically confirmed to have adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma cancer (IAC) from 2020 to 2023. CT images of all patients were automatically segmented and 107 radiomic features were obtained for each patient. Classification models were developed using random forest (RF) and cross-validation, including three one-versus-others models and one three-class model. For each model, features were ranked by normalized Gini importance, and a minimal subset was selected with a cumulative importance exceeding 0.9. These selected features were then used to train the final models. The models' performance metrics, including area under the curve (AUC), accuracy, sensitivity, and specificity, were computed. AUC and accuracy were compared to determine the final optimal method. RESULTS: The study comprised 193 patients (mean age 54 ± 11 years, 65 men), including 65 AIS, 54 MIA, and 74 IAC, divided into one training cohort (N = 154) and one test cohort (N = 39). The final three-class RF model outperformed three individual one-versus-others models in distinguishing each class from the other two. For the multiclass classification model, the AUC, accuracy, sensitivity, and specificity were 0.87, 0.79, 0.62, and 0.88 for AIS; 0.90, 0.79, 0.54, and 0.89 for MIA; and 0.87, 0.69, 0.73, and 0.67 for IAC, respectively. CONCLUSIONS: A radiomics-based multiclass RF model could effectively differentiate three types of pulmonary GGN, which enabled early diagnosis of GGO pulmonary adenocarcinoma.

Multi­omics identification of a signature based on malignant cell-associated ligand-receptor genes for lung adenocarcinoma.

PURPOSE: Lung adenocarcinoma (LUAD) significantly contributes to cancer-related mortality worldwide. The heterogeneity of the tumor immune microenvironment in LUAD results in varied prognoses and responses to immunotherapy among patients. Consequently, a clinical stratification algorithm is necessary and inevitable to effectively differentiate molecular features and tumor microenvironments, facilitating personalized treatment approaches. METHODS: We constructed a comprehensive single-cell transcriptional atlas using single-cell RNA sequencing data to reveal the cellular diversity of malignant epithelial cells of LUAD and identified a novel signature through a computational framework coupled with 10 machine learning algorithms. Our study further investigates the immunological characteristics and therapeutic responses associated with this prognostic signature and validates the predictive efficacy of the model across multiple independent cohorts. RESULTS: We developed a six-gene prognostic model (MYO1E, FEN1, NMI, ZNF506, ALDOA, and MLLT6) using the TCGA-LUAD dataset, categorizing patients into high- and low-risk groups. This model demonstrates robust performance in predicting survival across various LUAD cohorts. We observed distinct molecular patterns and biological processes in different risk groups. Additionally, analysis of two immunotherapy cohorts (N = 317) showed that patients with a high-risk signature responded more favorably to immunotherapy compared to those in the low-risk group. Experimental validation further confirmed that MYO1E enhances the proliferation and migration of LUAD cells. CONCLUSION: We have identified malignant cell-associated ligand-receptor subtypes in LUAD cells and developed a robust prognostic signature by thoroughly analyzing genomic, transcriptomic, and immunologic data. This study presents a novel method to assess the prognosis of patients with LUAD and provides insights into developing more effective immunotherapies.

Association of mean platelet volume (MPV), MPV/PLATELET (PLT) ratio, and lymphocyte/monocyte ratio (LMR) as poor prognostic factor in EGFR-mutant lung adenocarcinoma treated with EGFR tyrosine kinase inhibitor.

Introduction: Platelets (PLT) and host systemic inflammatory response (SIR) are known to be effective in the aggregation of cancer cells and the formation of metastasis. There are studies pointing out to the prognostic efficacy of lymphocyte-monocyte ratio (LMR) showing SIR activation and mean platelet volume (MPV) values indicating platelet activation in various cancer types. We predict that easy-to-access hemogram parameters such as MPV, MPV/PLT, and LMR can be guiding in the clinical follow-up period of patients with epidermal growth factor receptor (EGFR) positive mutation and who received EGFR, tyrosine kinase inhibitor (TKI) in the first-line treatment in predicting the progression of the disease, predicting the survival time of the patients, and evaluating the response to treatment. Materials and Methods: The study is retrospective and included patients with stage III and stage IV pulmonary adenocarcinoma with positive EGFR mutations and for whom TKI was used in the first-line treatment between January 2011 and January 2021. MPV, MPV/PLT, and LMR values of the patients were calculated before treatment. Age, sex, comorbidity, smoking history, TNM stage, metastasis localizations, EGFR mutation types, TKI treatments used in first-line treatment, and MPV, MPV/PLT, and LMR values at the 1st month of treatment were recorded. With Kaplan-Meier, six-month, one-year, three-year, and five-year survival rates, average life expectancy, and 95% confidence intervals for these periods were calculated. Variables that may affect progression and overall survival (OS) were determined by performing univariate and multivariate Cox regression analysis. Result: One hundred and two patients were included in the study. The mean age of the patients was 64.30 ± 12.6 years. Eighty-four patients were in stage IV at the time of diagnosis. The expected mean progression-free survival (PFS) period of the cases was found to be 13.3 months. The mean life expectancy of the cases was found to be 35.1 months. Web-based Cutoff Finder algorithm written in the R program (http://molpath.charite.de/cutoff) was used to determine the ideal cut points for MPV, MPV/PLT, and LMR. The cut-off values were found to be 7.55 fL for MPV, 0.251 for MPV/PLT, and 2.615 for LMR, respectively. In univariate Cox regression analysis, LMR level lower than 2.615 increased the rate of progression 1.747 times (95% confidence interval: 1.129-2.705) and the death rate 2.056 times (95% confidence interval: 1.217-3.475) (p= 0.012, p= 0.007). The mean PFS LMR cut-off value was 10.3 months, and 15.3 months, and mean OS durations were 25.1 months and 40.8 months for the groups with low and high cut-off values respectively (p= 0.011, p= 0.006 log-rank test). According to the results of multivariate Cox regression analysis, MPV/PLT < 0.251, smoking, presence of pleural and adrenal metastases, and gefitinib treatment were independent factors in determining PFS. The independent factors determining OS in multivariate Cox regression analysis were being male, platelet increase, MPV > 7.55, gefitinib treatment, and smoking. Conclusions: MPV, MPV/PLT, and LMR are potential biomarkers that can be used for the clinical follow-up of lung ADC patients receiving EGFR-TKI treatment.

Deciphering Dormant Cells of Lung Adenocarcinoma: Prognostic Insights from O-glycosylation-Related Tumor Dormancy Genes Using Machine Learning.

Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristics and high recurrence rate. The high recurrence rate of LUAD is closely associated with cellular dormancy, which enhances resistance to chemotherapy and evasion of immune cell destruction. Using single-cell RNA sequencing (scRNA-seq) data from LUAD patients, we categorized the cells into two subclusters: dormant and active cells. Utilizing high-density Weighted Gene Co-expression Network Analysis (hdWGCNA) and pseudo-time cell trajectory, aberrant expression of genes involved in protein O-glycosylation was detected in dormant cells, suggesting a crucial role for O-glycosylation in maintaining the dormant state. Intercellular communication analysis highlighted the interaction between fibroblasts and dormant cells, where the Insulin-like Growth Factor (IGF) signaling pathway regulated by O-glycosylation was crucial. By employing Gene Set Variation Analysis (GSVA) and machine learning, a risk score model was developed using hub genes, which showed high accuracy in determining LUAD prognosis. The model also demonstrated robust performance on the training dataset and excellent predictive capability, providing a reliable basis for predicting patient clinical outcomes. The group with a higher risk score exhibited a propensity for adverse outcomes in the tumor microenvironment (TME) and tumor mutational burden (TMB). Additionally, the 50% inhibitory concentration (IC50) values for chemotherapy exhibited significant variations among the different risk groups. In vitro experiments demonstrated that EFNB2, PTTG1IP, and TNFRSF11A were upregulated in dormant tumor cells, which also contributed greatly to the diagnosis of LUAD. In conclusion, this study highlighted the crucial role of O-glycosylation in the dormancy state of LUAD tumors and developed a predictive model for the prognosis of LUAD patients.

Repeated rebiopsy for detection of EGFR T790M mutation in patients with advanced-stage lung adenocarcinoma: Associated factors and treatment outcomes of Osimertinib.

OBJECTIVES: This study was performed to investigate the detection rate of EGFR T790M mutation by repeated rebiopsy, to identify the clinical factors related to repeated rebiopsy, and to assess survival outcomes according to the methods and numbers of repeated rebiopsies in patients with lung adenocarcinoma who received sequential osimertinib after failure of previous 1st or 2nd generation EGFR-tyrosine kinase inhibitors. METHODS: This retrospective study included patients with advanced-stage lung adenocarcinoma who were confirmed to have EGFR T790M mutation and to have received osimertinib from January 2020 to February 2021 at Samsung Medical Center. The presence of T790M mutation was assessed based on either plasma circulating tumor DNA (ctDNA) or tissue specimens. Results A total of 443 patients underwent rebiopsy, with 186 (42.0%) testing positive for the T790M mutation by the sixth rebiopsy. The final analysis included 143 eligible patients. Progression-free survival was not significantly different in terms of the methods (tissue: 13.3 months, 95% confidence interval [CI]: [9.4, 23.5] vs plasma: 11.1 months, 95% CI: [8.1, 19.4], p = 0.33) and numbers (one: 13.4 months, 95% CI: [9.4, 23.5] vs two or more: 11.0 months, 95% CI: [8.1, 14.8], p = 0.51) of repeated rebiopsies. Longer overall survival (OS) was found in patients in whom T790M was detected by tissue specimens rather than by plasma ctDNA (2-year OS rate: 81.7% for tissue vs 63.9% for plasma, p = 0.0038). Factors related to the lower numbers of rebiopsies included age and bone metastasis. Factor associated with T790M detection in tissue rather than in plasma was pleural metastasis, while advanced tumor stage was related to T790M confirmation in plasma rather than in tissue. CONCLUSIONS: Repeated rebiopsy for T790M detection in patients with NSCLC can increase the detection rate of the mutation. Detection of T790M by plasma ctDNA might be related to poor survival outcomes.

NCAPD2 serves as a potential prognostic biomarker for lung adenocarcinoma and promotes cell proliferation, migration, invasion and cell cycle in vitro.

Objectives: The pro-oncogenic effects of NCAPD2 have been extensively studied across various tumor types; however, its precise role within the context of lung adenocarcinoma (LUAD) remains elusive. This study aims to elucidate the biological functions of NCAPD2 in LUAD and unravel the underlying mechanistic pathways. Methods: Utilizing bioinformatics methodologies, we explored the differential expression of NCAPD2 between normal and tumor samples, along with its correlations with clinical-pathological characteristics, survival prognosis, and immune infiltration. Results: In the TCGA-LUAD dataset, tumor samples demonstrated significantly elevated levels of NCAPD2 expression compared to normal samples (p < 0.001). Clinically, higher NCAPD2 expression was notably associated with advanced T, N, and M stages, pathologic stage, gender, smoking status, and diminished overall survival (OS). Moreover, differentially expressed genes (DEGs) associated with NCAPD2 were predominantly enriched in pathways related to cell division. Immune infiltration analysis revealed that NCAPD2 expression levels were linked to the infiltration of memory B cells, naïve CD4+ T cells, activated memory CD4+ T cells, and M1 macrophages. In vitro experiments demonstrated that silencing NCAPD2 suppressed LUAD cell proliferation, migration, invasion, epithelial-mesenchymal transition (EMT), and cell cycle progression. Conclusions: In summary, NCAPD2 may represent a promising prognostic biomarker and novel therapeutic target for LUAD.

No genetic causal association between human papillomavirus and lung cancer risk: a bidirectional two-sample Mendelian randomization analysis.

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.

The role of local ablative therapy in patients with advanced invasive mucinous adenocarcinoma of the lung.

PURPOSE: Invasive mucinous adenocarcinoma (IMA) of the lungs is a rare subtype of lung adenocarcinoma with a limited understanding of its prognosis, particularly in advanced stages. This study aimed to assess the prognosis of patients with advanced IMA by focusing on treatment modalities. METHODS: This single-center retrospective study evaluated 33 patients with IMAs diagnosed with advanced-stage disease or disease progression after curative treatment between 2011 and 2021. The primary outcome was overall survival (OS), and the secondary outcome was progression-free survival (PFS). OS and PFS were calculated from the date of the diagnosis of advanced IMA. RESULTS: The study cohort included 13 patients at the initial advanced stage and 20 patients who progressed after curative treatment. Treatment modalities included conventional chemotherapy in 24 patients (72.7%), targeted therapy in seven (21.2%), immunotherapy in 13 (39.4%), and local ablative therapy (LAT) in 13 (39.4%). The median OS was 32 months (95% confidence interval [CI], 2.9-61.0), with LAT significantly associated with improved OS compared to non-LAT treatment (not reached vs. 11.3 months, p = 0.001). However, there was no significant difference in OS based on conventional chemotherapy (p = 0.396), targeted therapy (p = 0.655), or immunotherapy (p = 0.992). In multivariate analysis, LAT remained an independent prognostic factor for OS (hazard ratio, 0.125; 95% CI, 0.026-0.608; p = 0.01). PFS was 8.6 months (95% CI, 3.6-13.7), with no significant differences observed among the treatment modalities. CONCLUSION: Our findings suggest that LAT may provide favorable survival outcomes in patients with advanced IMA.

The prognostic effect of infiltrating immune cells is shaped by proximal M2 macrophages in lung adenocarcinoma.

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.

The impact of postoperative adjuvant therapy on EGFR-mutated stage IA lung adenocarcinoma with micropapillary pathological subtypes.

BACKGROUND: Micropapillary (MPP) adenocarcinoma is considered one of the most aggressive pathological types of lung adenocarcinoma (LADC). This retrospective study aimed to evaluate the prognostic significance and benefit of postoperative adjuvant therapy (PAT) in stage IA LADC patients with different proportions of MPP components. MATERIALS AND METHODS: We retrospectively examined clinical stage IA LADC patients who underwent surgical resection between August 2012 and December 2019. In terms of the proportion of MPP components (TPM), the tumors were reclassified into three categories: MPP patterns absent (TPMN); low proportions of MPP components (TPML); and high proportions of MPP components (TPMH). The dates of recurrence and metastasis were identified based on physical examinations and were confirmed by histopathological examination. RESULTS: Overall, 505 (TPMN, n = 375; TPML, n = 92; TPMH, n = 38) patients harboring EGFR mutations were enrolled in the study. Male sex (P = 0.044), high pathological stage (P < 0.001), and MPP pathological subtype (P < 0.001) were more frequent in the TPM-positive (TPMP) group than in the TPM-negative (TPMN) group. Five-year disease-free survival (DFS) rates were significantly lower in the TPMP group than in the TPMN group (84.5% vs. 93.4%, P = 0.006). In addition, patients with high proportions (greater than 10%) of MPP components had worse overall survival (OS) (91.0% vs. 98.9%, P = 0.025) than those with low proportions (5%≤ TPM ≤ 10%). However, postoperative EGFR tyrosine kinase inhibitors (TKIs) or adjuvant chemotherapy (ACT) cannot improve DFS and OS between EGFR-mutated patients with different proportions of MPP components. CONCLUSION: MPP was related to earlier recurrence and shortened survival time, even in stage IA. Further research needs a larger sample size to clarify that EGFR-mutated stage IA patients with MPP components obtain survival benefits from adjuvant therapy.

Evaluation of the invasiveness of pure ground-glass nodules based on dual-head ResNet technique.

OBJECTIVE: To intelligently evaluate the invasiveness of pure ground-glass nodules with multiple classifications using deep learning. METHODS: pGGNs in 1136 patients were pathologically confirmed as lung precursor lesions [atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS)], minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IAC). Four different models [EfficientNet-b0 2D, dual-head ResNet_3D, a 3D model combining three features (3D_3F), and a 3D model combining 19 features (3D_19F)] were constructed to evaluate the invasiveness of pGGNs using the EfficientNet and ResNet networks. The Obuchowski index was used to evaluate the differences in diagnostic efficiency among the four models. RESULTS: The patients with pGGNs (360 men, 776 women; mean age, 54.63 ± 12.36 years) included 235 cases of AAH + AIS, 332 cases of MIA, and 569 cases of IAC. In the validation group, the areas under the curve in detecting the invasiveness of pGGNs as a three-category classification (AAH + AIS, MIA, IAC) were 0.8008, 0.8090, 0.8165, and 0.8158 for EfficientNet-b0 2D, dual-head ResNet_3D, 3D_3F, and 3D_19F, respectively, whereas the accuracies were 0.6422, 0.6158, 0.651, and 0.6364, respectively. The Obuchowski index revealed no significant differences in the diagnostic performance of the four models. CONCLUSIONS: The dual-head ResNet_3D_3F model had the highest diagnostic efficiency for evaluating the invasiveness of pGGNs in the four models.

Differential effects of hypoxia on motility using various in vitro models of lung adenocarcinoma.

Lung cancer is the leading cause of cancer-related death globally. Metastasis is the most common reason of mortality in which hypoxia is suggested to have a pivotal role. However, the effect of hypoxia on the metastatic potential and migratory activity of cancer cells is largely unexplored and warrants detailed scientific investigations. Accordingly, we analyzed changes on cell proliferation and migratory activity both in single-cell migration and invasion under normoxic and hypoxic conditions in lung adenocarcinoma cell lines. Alterations in crucial genes and proteins associated with cellular response to hypoxia, epithelial-mesenchymal transition, proliferation and apoptosis were also analyzed. Generally, we observed no change in proliferation upon hypoxic conditions and no detectable induction of apoptosis. Interestingly, we observed that single-cell motility was generally reduced while invasion under confluent conditions using scratch assay was enhanced by hypoxia in most of the cell lines. Furthermore, we detected changes in the expression of EMT markers that are consistent with enhanced motility and metastasis-promoting effect of hypoxia. In summary, our study indicated cell line-, time of exposure- and migrational type-dependent effects of hypoxia in cellular proliferation, motility and gene expression. Our results contribute to better understanding and tackling cancer metastasis.

Exploring the molecular and immune landscape of cellular senescence in lung adenocarcinoma.

Introduction: The connection between aging and cancer is complex. Previous research has highlighted the association between the aging process of lung adenocarcinoma (LUAD) cells and the immune response, yet there remains a gap in confirming this through single-cell data validation. Here, we aim to develop a novel aging-related prognostic model for LUAD, and verify the alterations in the genome and immune microenvironment linked to cellular senescence. Methods: We integrated a comprehensive collection of senescence genes from the GenAge and CellAge databases and employed the least absolute shrinkage and selection operator (LASSO) Cox analysis to construct and validate a novel prognostic model for LUAD. This model was then utilized to examine the relationship between aging, tumor somatic mutations, and immune cell infiltration. Additionally, we explored the heterogeneity of senescence and intercellular communication within the LUAD tumor microenvironment (TME) through single-cell transcriptomic data analysis. Results: By exploring the expression profiles of 586 cellular senescence-related genes in 428 LUAD patients, we constructed an aging-related genes (ARGs) risk model included 10 ARGs and validated it as an independent prognostic predictor for LUAD patients. Notably, patients with low aging scores (LAS group) exhibited better survival, lower tumor mutation burden (TMB), lower somatic mutation frequency, lower tumor proliferation rate, and an immune activated phenotype compared to patients with high aging scores (HAS group). While the HAS group was enriched in tumor cells and showed a lower infiltration of CD8-CCR7, CD8- CXCL13, CD8-GNLY, FCGR3A NK cells, XCL1 NK cells, plasma cell (PC) and other immune subsets. Furthermore, the SPP1 and TENASCIN pathways, associated with tumor immune escape and tumor progression, were also enriched in the HAS group. Additionally, our study also indicated that senescence levels were heterogeneous in the LUAD tumor microenvironment (TME), especially with tumor cells in the LAS group showing higher age scores compared to those in the HAS group. Conclusions: Collectively, our findings underscore that ARRS through ARGs serves as a robust biomarker for the prognosis in LUAD.

FOXF1 inhibits invasion and metastasis of lung adenocarcinoma cells and enhances anti-tumor immunity via MFAP4/FAK signal axis.

Based on the joint analysis of multi-omic data and the biological experiments, we demonstrate that FOXF1 inhibits invasion and metastasis of lung adenocarcinoma cells and enhances anti-tumor immunity via regulating MFAP4/FAK signal axis in this study. The levels of FOXF1 and MFAP4 are significantly down-regulated in LUAD, and the increased levels of two genes can improve the clinical prognosis of LUAD patients. Fluorescein reporter gene determination, chromatin immunoprecipitation and gene co-expression analysis indicate that MFAP4 level is positively regulated by transcription factor FOXF1. The function enrichment analysis shows that the levels of FOXF1 and MFAP4 are closely associated with an enrichment of tumor metastasis signatures. FOXF1 can inhibit the migration and invasion of LAUD cells by transcriptionally activating MFAP4 expression. And the overexpression of FOXF1/MFAP4 can reduce focal adhesion kinase (FAK) phosphorylation, while their knockdown result in the opposite effects. The increased levels of FOXF1/MFAP4 enhance the antitumor immunity by increasing the infiltration of dendritic cells and CD4+ T cells, and the interactions between LUAD cells and immune cells, and activating multiple anti-tumor immunity-related pathways. In conclusion, our study reveals the potential function of FOXF1/MFAP4/FAK signal axis in inhibiting metastasis of LUAD cells and modulating anti-tumor immunity of LUAD patients.

Ropivacaine Administration Suppressed A549 Lung Adenocarcinoma Cell Proliferation and Migration via ACE2 Upregulation and Inhibition of the Wnt1 Pathway.

BACKGROUND: Previous studies have suggested that perioperative anesthesia could have direct impacts on cancer cell biology. The present study investigated the effects of ropivacaine administration on lung adenocarcinoma cells. METHODS: Ropivacaine was administered to A549 cells at concentrations of 0.1, 1, and 6 mM for 2 h. Angiotensin-converting enzyme 2 (ACE2) small interfering RNA (siRNA) transfection was performed 6 h prior to ropivacaine administration. Cell proliferation and migration were assessed with cell counting kit 8 (CCK-8) and a wound healing assay at 0 and 24 h after anesthesia exposure. PCR arrays were performed, followed by PCR validation. RESULTS: Ropivacaine administration inhibited A549 cell proliferation and migration in a concentration-dependent manner, with ACE2 upregulation and HIF1α (hypoxia-inducible factor 1α) downregulation. The anticancer effect of ropivacaine was canceled out via ACE2 siRNA transfection. PCR arrays showed specific gene change patterns in the ropivacaine and respective ACE2-knockdown groups. EGFR (epidermal growth factor receptor), BAX (Bcl-2-associated X protein) and BCL2 (B-cell/CLL lymphoma 2) were suppressed with ropivacaine administration; these effects were reversed via ACE2 siRNA induction. CONCLUSION: Ropivacaine administration inhibited A549 cell biology in conjunction with ACE2 upregulation via the inhibition of the Wnt1 (wingless/Integrated 1) pathway.

Dissecting transcriptome signals of anti-PD-1 response in lung adenocarcinoma.

Immune checkpoint blockades are actively adopted in diverse cancer types including metastatic melanoma and lung cancer. Despite of durable response in 20-30% of patients, we still lack molecular markers that could predict the patient responses reliably before treatment. Here we present a composite model for predicting anti-PD-1 response based on tumor mutation burden (TMB) and transcriptome sequencing data of 85 lung adenocarcinoma (LUAD) patients who received anti-PD-(L)1 treatment. We found that TMB was a good predictor (AUC = 0.81) for PD-L1 negative patients (n = 20). For PD-L1 positive patients (n = 65), we built an ensemble model of 100 XGBoost learning machines where gene expression, gene set activities and cell type composition were used as input features. The transcriptome-based models showed excellent accuracy (AUC > 0.9) and highlighted the contribution of T cell activities. Importantly, nonresponder patients with high prediction score turned out to have high CTLA4 expression, which suggested that neoadjuvant CTLA4 combination therapy might be effective for these patients. Our data and analysis results provide valuable insights into developing biomarkers and strategies for treating LUAD patients using immune checkpoint inhibitors.

ARMCX1 inhibits lung adenocarcinoma progression by recruiting FBXW7 for c-Myc degradation.

BACKGROUND: Armadillo Repeat Containing X-Linked 1 (ARMCX1), a member of the ARM Repeat X-linked protein family, exerts inhibitory function in various tumors. However, its biological role in lung adenocarcinoma (LUAD) and the underlying molecular mechanisms require further exploration. METHODS: LUAD tissue microarrays and bioinformatic databases were used to evaluate the relationship between ARMCX1 and clinicopathological features. The influence of ARMCX1 on LUAD cell proliferation, migration, and invasion in vitro was determined by colony formation, CCK-8, EdU incorporation, cell cycle, wound healing, and Transwell assays. The impact of ARMCX1 on LUAD cell growth and metastasis in vivo was determined by subcutaneously transplanted tumor and pulmonary metastasis assays. Western blot, immunoprecipitation, immunofluorescence, cycloheximide, and proteasome inhibitor assays were finally conducted to explore the potential underlying molecular mechanisms. RESULTS: ARMCX1 expression was downregulated in clinical LUAD samples due to which patient prognoses were poor. Functional experiments indicated that ARMCX1 overexpression inhibited the growth and metastasis of LUAD cells in vitro and in vivo. The molecular mechanism suggested that ARMCX1 recruits the E3 ubiquitin ligase FBXW7 for mediating ubiquitinated degradation of c-Myc, suppressing its nuclear accumulation, and ultimately inactivating cell cycle and epithelial-mesenchymal transition (EMT) signals. CONCLUSION: ARMCX1 inhibits LUAD cell proliferation and metastasis by interacting with c-Myc and enhancing its ubiquitination and degradation. Consequently, it can act as a tumor suppressor in this disease. These results suggest that ARMCX1 is a potential target in the treatment of LUAD.

Metastatic lung adenocarcinoma presenting with small bowel obstruction.

Lung cancer is one of the most lethal solid organ malignancies. Metastasis commonly spreads to the liver, adrenal glands and bone. We report a case of a male patient who presented with an 8 week history of cramping abdominal pain and vomiting. Subsequent investigation revealed evidence of an obstructing small bowel lesion. He underwent a small bowel resection. Histopathology revealed evidence of lung adenocarcinoma as the likely primary disease. Although metastasis of lung adenocarcinoma to the small bowel is rare, early recognition may prevent potentially life-threatening sequelae including bowel perforation and peritonitis.

Combination of MDM2 and Targeted Kinase Inhibitors Results in Prolonged Tumor Control in Lung Adenocarcinomas With Oncogenic Tyrosine Kinase Drivers and MDM2 Amplification.

PURPOSE: MDM2, a negative regulator of the TP53 tumor suppressor, is oncogenic when amplified. MDM2 amplification (MDM2amp) is mutually exclusive with TP53 mutation and is seen in 6% of patients with lung adenocarcinoma (LUAD), with significant enrichment in subsets with receptor tyrosine kinase (RTK) driver alterations. Recent studies have shown synergistic activity of MDM2 and MEK inhibition in patient-derived LUAD models with MDM2amp and RTK driver alterations. However, the combination of MDM2 and RTK inhibitors in LUAD has not been studied. METHODS: We evaluated the combination of MDM2 and RTK inhibition in patient-derived models of LUAD. RESULTS: In a RET-fusion LUAD patient-derived model with MDM2amp, MDM2 inhibition with either milademetan or AMG232 combined with selpercatinib resulted in long-term in vivo tumor control markedly superior to either agent alone. Similarly, in an EGFR-mutated model with MDM2amp, combining either milademetan or AMG232 with osimertinib resulted in long-term in vivo tumor control, which was strikingly superior to either agent alone. CONCLUSION: These preclinical in vivo data provide a rationale for further clinical development of this combinatorial targeted therapy approach.