A novel entity of HIPK2::YAP1 pulmonary fibromatosis.

BACKGROUND: Pulmonary fibromatosis (PF) is a specific variant of fibromatosis, which is rarely reported occurring in the lung. PF with HIPK2-YAP1 fusion was a novel entity. CASE PRESENTATION: In this report, a 66-year-old male with PF had been smoking over 40 years. Multiple cords and small nodules in both lungs had been detected in a health examination two years earlier at our hospital. But approximately twofold enlarged in the lingual segment of the upper lobe in the left lung were disclosed in this year. Immunohistochemical analysis demonstrated that the vimentin and ß-Catenin were positive in the largest nodule. After underwent a DNA/RNA panel next-generation sequencing (NGS), missense mutations and HIPK2-YAP1 fusion were found in this sample. Ultimately, the case diagnosis as PF with HIPK2-YAP1 fusion after multidisciplinary treatment. Currently, the patient is doing well and recurrence-free at 14 months post-surgery. CONCLUSIONS: It's difficult for patients with complex morphology to make accurate diagnosis solely based on morphology and immunohistochemistry. But molecular detection is an effective method for further determining pathological subtypes.

Immune checkpoint inhibitor (ICI)-based treatment beyond progression with prior immunotherapy in patients with driver-gene negative advanced non-small cell lung cancer.

BACKGROUND: No definite conclusion has yet to be reached for immunotherapy beyond progression(IBP) of first-line immunotherapy as the second-line treatment for advanced NSCLC patients with negative driver genes. Therefore a retrospective study was conducted to evaluate the efficacy of IBP in this population and investigated whether the cycles best response and progressive mode of first-line immunotherapy could affect the results. PATIENTS AND METHODS: The clinical data of patients with advanced NSCLC whose response was evaluated as progressive disease (PD) after receiving a PD-1/PD-L1 inhibitors as first-line therapy were retrospectively collected and the patients were assigned to the IBP and non-IBP groups. The overall survival (OS), progression-free survival (PFS) were evaluated between the two groups. The survival effects of cycles best response and progressive mode of first-line immunotherapy were also evaluated. RESULTS: Between January 2019 and January 2022, a total of 121 patients was evaluated as PD after first-line immunotherapy in our institution; 53 (43.8%) patients were included in the IBP group and 68 (56.2%) patients were included in the non-IBP group. The OS and PFS were no significantly different between the two groups in whole population. Further analysis revealed the OS was prolonged with the prolongation of first-line medication cycle. The median OS was 15.4m (15.4 vs 10.8 p=0.047) 16.1m (16.1 vs 10.8 p=0.039), 16.3m (16.3 vs 10.9 p=0.029) for patients with ≥4, ≥6, ≥8 cycles in first-line immunotherapy, respectively. The advantages of OS and PFS were also seen in the subgroup of PR (best response) and oligo progression of first-line immunotherapy. CONCLUSIONS: The clinical outcomes of IBP were similar to those of non-IBP in patients with PD after first-line immnuotherapy in advanced NSCLC. But more cycles, PR as best response and oligo progression in first-line was benefit.

circ_PPAPDC1A promotes Osimertinib resistance by sponging the miR-30a-3p/ IGF1R pathway in non-small cell lung cancer (NSCLC).

BACKGROUND: Recent evidence has demonstrated that abnormal expression and regulation of circular RNA (circRNAs) are involved in the occurrence and development of a variety of tumors. The aim of this study was to investigate the effects of circ_PPAPDC1A in Osimertinib resistance in NSCLC. METHODS: Human circRNAs microarray analysis was conducted to identify differentially expressed (DE) circRNAs in Osimertinib-acquired resistance tissues of NSCLC. The effect of circ_PPAPDC1A on cell proliferation, invasion, migration, and apoptosis was assessed in both in vitro and in vivo. Dual-luciferase reporter assay, RT-qPCR, Western-blot, and rescue assay were employed to confirm the interaction between circ_PPAPDC1A/miR-30a-3p/IGF1R axis. RESULTS: The results revealed that circ_PPAPDC1A was significantly upregulated in Osimertinib acquired resistance tissues of NSCLC. circ_PPAPDC1A reduced the sensitivity of PC9 and HCC827 cells to Osimertinib and promoted cell proliferation, invasion, migration, while inhibiting apoptosis in Osimertinib-resistant PC9/OR and HCC829/OR cells, both in vitro and in vivo. Silencing circ_PPAPDC1A partially reversed Osimertinib resistance. Additionally, circ_PPAPDC1A acted as a competing endogenous RNA (ceRNA) by targeting miR-30a-3p, and Insulin-like Growth Factor 1 Receptor (IGF1R) was identified as a functional gene for miR-30a-3p in NSCLC. Furthermore, the results confirmed that circ_PPAPDC1A/miR-30a-3p/IGF1R axis plays a role in activating the PI3K/AKT/mTOR signaling pathway in NSCLC with Osimertinib resistance. CONCLUSIONS: Therefore, for the first time we identified that circ_PPAPDC1A was significantly upregulated and exerts an oncogenic role in NSCLC with Osimertinib resistance by sponging miR-30a-3p to active IGF1R/PI3K/AKT/mTOR pathway. circ_PPAPDC1A may serve as a novel diagnostic biomarker and therapeutic target for NSCLC patients with Osimertinib resistance.

GTSE1: A potential prognostic and diagnostic biomarker in various tumors including lung adenocarcinoma.

OBJECTIVE: This research was aimed to comprehensively investigate the expression levels, diagnostic and prognostic implications, and the relationship with immune infiltration of G2 and S phase-expressed-1 (GTSE1) across 33 tumor types, including lung adenocarcinoma (LUAD), through gene expression profiling. METHODS: GTSE1 mRNA expression data together with clinical information were acquired from Xena database of The Cancer Genome Atlas (TCGA), ArrayExpress, and Gene Expression Omnibus (GEO) database for this study. The Wilcoxon rank-sum test was used to detect differences in GTSE1 expression between groups. The ability of GTSE1 to accurately predict cancer status was evaluated by calculating the area under the curve (AUC) value for the receiver operating characteristic curve. Additionally, we investigated the predictive value of GTSE1 in individuals diagnosed with neoplasms using univariate Cox regression analysis as well as Kaplan-Meier curves. Furthermore, the correlation between GTSE1 expression and levels of immune infiltration was assessed by utilizing the Tumor Immune Estimate Resource (TIMER) database to calculate the Spearman rank correlation coefficient. Finally, the pan-cancer analysis findings were validated by examining the association between GTSE1 expression and prognosis among patients with LUAD. RESULTS: GTSE1 exhibited significantly increased expression levels in a wide range of tumor tissues in contrast with normal tissues (p < 0.05). The expression of GTSE1 in various tumors was associated with clinical features, overall survival, and disease-specific survival (p < 0.05). In immune infiltration analyses, a strong correlation of the level of immune infiltration with the expression of GTSE1 was observed. Furthermore, GTSE1 demonstrated good discriminative and diagnostic value for most tumors. Additional experiments confirmed the relationship between elevated GTSE1 expression and unfavorable prognosis in individuals diagnosed with LUAD. These findings indicated the crucial role of GTSE1 expression level in influencing the development and immune infiltration of different types of tumors. CONCLUSIONS: GTSE1 might be a potential biomarker for the prognosis of pan-cancer. Meanwhile, it represented a promising target for immunotherapy.

Spon1+ inflammatory monocytes promote collagen remodeling and lung cancer metastasis through lipoprotein receptor 8 signaling.

Lung cancer is the leading cause of cancer-related deaths in the world, and non-small cell lung cancer (NSCLC) is the most common subset. We previously found that infiltration of tumor inflammatory monocytes (TIMs) into lung squamous carcinoma (LUSC) tumors is associated with increased metastases and poor survival. To further understand how TIMs promote metastases, we compared RNA-Seq profiles of TIMs from several LUSC metastatic models with inflammatory monocytes (IMs) of non-tumor-bearing controls. We identified Spon1 as upregulated in TIMs and found that Spon1 expression in LUSC tumors corresponded with poor survival and enrichment of collagen extracellular matrix signatures. We observed SPON1+ TIMs mediate their effects directly through LRP8 on NSCLC cells, which resulted in TGF-ß1 activation and robust production of fibrillar collagens. Using several orthogonal approaches, we demonstrated that SPON1+ TIMs were sufficient to promote NSCLC metastases. Additionally, we found that Spon1 loss in the host, or Lrp8 loss in cancer cells, resulted in a significant decrease of both high-density collagen matrices and metastases. Finally, we confirmed the relevance of the SPON1/LRP8/TGF-ß1 axis with collagen production and survival in patients with NSCLC. Taken together, our study describes how SPON1+ TIMs promote collagen remodeling and NSCLC metastases through an LRP8/TGF-ß1 signaling axis.

PM2.5 regulates the progression of lung adenocarcinoma through the axis of HCG18, miR-195 and ATG14.

Relevant studies have indicated the association of HCG18 with tumour occurrence and progression. In this study, we observed that PM2.5 can enhance the growth of lung adenocarcinoma cells by modulating the expression of HCG18. Further investigations, including overexpression and knockout experiments, elucidated that HCG18 suppresses miR-195, which in turn upregulates the expression of ATG14, resulting in the upregulation of autophagy. Consequently, exposure to PM2.5 leads to elevated HCG18 expression in lung tissues, which in turn increases Atg14 expression and activates autophagy pathways through inhibition of miR-195, thereby contributing to oncogenesis.

Genome-wide CRISPR screens in spheroid culture reveal that the tumor suppressor LKB1 inhibits growth via the PIKFYVE lipid kinase.

The tumor suppressor LKB1 is a serine/threonine protein kinase that is frequently mutated in human lung adenocarcinoma (LUAD). LKB1 regulates a complex signaling network that is known to control cell polarity and metabolism; however, the pathways that mediate the tumor-suppressive activity of LKB1 are incompletely defined. To identify mechanisms of LKB1-mediated growth suppression, we developed a spheroid-based cell culture assay to study LKB1-dependent growth. We then performed genome-wide CRISPR screens in spheroidal culture and found that LKB1 suppresses growth, in part, by activating the PIKFYVE lipid kinase. Finally, we used chemical inhibitors and a pH-sensitive reporter to determine that LKB1 impairs growth by promoting the internalization of wild-type EGFR in a PIKFYVE-dependent manner.

Overcoming Nutrient Stress: Integrin αvß3-Driven Metabolic Adaptation Supports Tumor Initiation.

Nutrient stress accompanies several stages of tumor progression, including metastasis formation. Metabolic reprogramming is a hallmark of cancer, and it has been associated with stress tolerance and anchorage-independent cell survival. Adaptive responses are required to support cancer cell survival under these conditions. In this issue of Cancer Research, Nam and colleagues showed that the extracellular matrix (ECM) receptor integrin ß3 was upregulated in lung cancer cells in response to nutrient starvation, resulting in increased cell survival that was independent from ECM binding. Delving into the molecular mechanisms responsible for this, the authors found that integrin ß3 promoted glutamine metabolism and oxidative phosphorylation (OXPHOS) by activating a Src/AMPK/PGC1α signaling pathway. Importantly, in vivo experiments confirmed that OXPHOS inhibition suppressed tumor initiation in an orthotopic model of lung cancer, while ß3 knockout completely abrogated tumor initiation. These observations indicate that targeting signaling pathways downstream of αvß3 could represent a promising therapeutic avenue to prevent lung cancer progression and metastasis. See related article by Nam et al., p. 1630.

Prognostic implications of STK11 with different mutation status and its relationship with tumor-infiltrating immune cells in non-small cell lung cancer.

Background: Mutations in STK11 (STK11Mut) gene may present a negative impact on survival in Non-small Cell Lung Cancer (NSCLC) patients, however, its relationship with immune related genes remains unclear. This study is to unveil whether overexpressed- and mutated-STK11 impact survival in NSCLC and to explore whether immune related genes (IRGs) are involved in STK11 mutations. Methods: 188 NSCLC patients with intact formalin-fixed paraffin-embedded (FFPE) tissue available for detecting STK11 protein expression were included in the analysis. After immunohistochemical detection of STK11 protein, patients were divided into high STK11 expression group (STK11High) and low STK11 expression group (STK11Low), and then Kaplan-Meier survival analysis and COX proportional hazards model were used to compare the overall survival (OS) and progression-free survival (PFS) of the two groups of patients. In addition, the mutation data from the TCGA database was used to categorize the NSCLC population, namely STK11 Mutated (STK11Mut) and wild-type (STK11Wt) subgroups. The difference in OS between STK11Mut and STK11Wt was compared. Finally, bioinformatics analysis was used to compare the differences in IRGs expression between STK11Mut and STK11Wt populations. Results: The median follow-up time was 51.0 months (range 3.0 - 120.0 months) for real-life cohort. At the end of follow-up, 64.36% (121/188) of patients experienced recurrence or metastasis. 64.89% (122/188) of patients ended up in cancer-related death. High expression of STK11 was a significant protective factor for NSCLC patients, both in terms of PFS [HR=0.42, 95% CI= (0.29-0.61), P<0.001] and OS [HR=0.36, 95% CI= (0.25, 0.53), P<0.001], which was consistent with the finding in TCGA cohorts [HR=0.76, 95%CI= (0.65, 0.88), P<0.001 HR=0.76, 95%CI= (0.65, 0.88), P<0.001]. In TCGA cohort, STK11 mutation was a significant risk factor for NSCLC in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) histology in terms of OS [HR=6.81, 95%CI= (2.16, 21.53), P<0.001; HR=1.50, 95%CI= (1.00, 2.26), P=0.051, respectively]. Furthermore, 7 IRGs, namely CALCA, BMP6, S100P, THPO, CGA, PCSK1 and MUC5AC, were found significantly overexpressed in STK11-mutated NSCLC in both LUSC and LUAD histology. Conclusions: Low STK11 expression at protein level and presence of STK11 mutation were associated with poor prognosis in NSCLC, and mutated STK11 might probably alter the expression IRGs profiling.

Diagnostic leukapheresis reveals distinct phenotypes of NSCLC circulating tumor cells.

BACKGROUND: Circulating tumor cells (CTCs) hold immense promise for unraveling tumor heterogeneity and understanding treatment resistance. However, conventional methods, especially in cancers like non-small cell lung cancer (NSCLC), often yield low CTC numbers, hindering comprehensive analyses. This study addresses this limitation by employing diagnostic leukapheresis (DLA) to cancer patients, enabling the screening of larger blood volumes. To leverage DLA's full potential, this study introduces a novel approach for CTC enrichment from DLAs. METHODS: DLA was applied to six advanced stage NSCLC patients. For an unbiased CTC enrichment, a two-step approach based on negative depletion of hematopoietic cells was used. Single-cell (sc) whole-transcriptome sequencing was performed, and CTCs were identified based on gene signatures and inferred copy number variations. RESULTS: Remarkably, this innovative approach led to the identification of unprecedented 3,363 CTC transcriptomes. The extensive heterogeneity among CTCs was unveiled, highlighting distinct phenotypes related to the epithelial-mesenchymal transition (EMT) axis, stemness, immune responsiveness, and metabolism. Comparison with sc transcriptomes from primary NSCLC cells revealed that CTCs encapsulate the heterogeneity of their primary counterparts while maintaining unique CTC-specific phenotypes. CONCLUSIONS: In conclusion, this study pioneers a transformative method for enriching CTCs from DLA, resulting in a substantial increase in CTC numbers. This allowed the creation of the first-ever single-cell whole transcriptome in-depth characterization of the heterogeneity of over 3,300 NSCLC-CTCs. The findings not only confirm the diagnostic value of CTCs in monitoring tumor heterogeneity but also propose a CTC-specific signature that can be exploited for targeted CTC-directed therapies in the future. This comprehensive approach signifies a major leap forward, positioning CTCs as a key player in advancing our understanding of cancer dynamics and paving the way for tailored therapeutic interventions.

Abnormal methylation mediated upregulation of LINC00857 boosts malignant progression of lung adenocarcinoma by modulating the miR-486-5p/NEK2 axis.

LINC00857 is frequently dysregulated in varying cancers, which in turn exerts carcinogenic effects; however, its DNA methylation status in promoter region and molecular mechanisms underlying the progression of lung adenocarcinoma (LUAD) remain rarely understood. Through bioinformatics analysis, we examined the expression state and methylation site of LINC00857 in LUAD and further investigated the properties of LINC00857 as a competitive endogenous RNA in the cancer progression. The current study revealed that the overexpression of LINC00857 in LUAD tissue and cells was mainly caused by the hypomethylation of the promoter region. LINC00857 knockdown prominently reduced cell proliferation, impeded cell migration and invasion, and restrained lymph node metastasis, with enhancing radiosensitivity. The effects of LINC00857 on tumor growth were also investigated in nude mice models. Subsequently, the downstream factors, miR-486-5p and NEK2, were screened, and the putative regulatory axis was examined. Overall, the regulatory effect of methylation-mediated LINC00857 overexpression on miR-486-5p/NEK2 axis may be a new mechanism for LUAD progression.

Lung cancer clustering by identification of similarities and discrepancies of DNA copy numbers using maximal information coefficient.

Lung cancer is the second most diagnosed cancer and the first cause of cancer related death for men and women in the United States. Early detection is essential as patient survival is not optimal and recurrence rate is high. Copy number (CN) changes in cancer populations have been broadly investigated to identify CN gains and deletions associated with the cancer. In this research, the similarities between cancer and paired peripheral blood samples are identified using maximal information coefficient (MIC) and the spatial locations with substantially high MIC scores in each chromosome are used for clustering analysis. The results showed that a sizable reduction of feature set can be obtained using only a subset of locations with high MIC values. The clustering performance was evaluated using both true rate and normalized mutual information (NMI). Clustering results using the reduced feature set outperformed the performance of clustering using entire feature set in several chromosomes that are highly associated with lung cancer with several identified oncogenes.

[Value of peripheral blood rare cell EGFR gene amplification detection in the evaluation of benign and malignant pulmonary nodules].

Objective: To explore the value of detection of epidermal growth factor receptor (EGFR) gene amplification in peripheral blood rare cells in the assessment of benign and malignant pulmonary nodules. Methods: A total of 262 patients with pulmonary nodules were selected as the retrospectively study subjects from the Second Affiliated Hospital of Army Military Medical University and Peking Union Medical College Hospital from July 2022 to August 2023. There were 98 males and 164 females, with the age range from 16 to 79 (52.1±12.1) years. The EGFR gene amplification testing was performed on the rare cells enriched from patients' peripheral blood, and the clinical manifestations, CT imaging features, histopathological and/or pathological cytological confirmed results of patients were collected. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value of the method of detection of EGFR gene amplification in peripheral blood rare cells, and its diagnostic efficacy was evaluated. Results: Among the 262 patients, 143 were malignant pulmonary nodules and 119 were benign pulmonary nodules. The differences between malignant pulmonary nodules and benign pulmonary nodules in nodule diameter and nodule density were statistically significant (both P<0.001), while the differences in age, gender and nodule number were not statistically significant (all P>0.05). The number [M (Q1, Q3)] of EGFR gene amplification positive rare cells in patients with malignant pulmonary nodule was 8 (6, 11), which was higher than that in patients with benign pulmonary nodule [2 (1, 4), P<0.001]. The ROC curve results showed that when the optimal cut-off value was 5 (that was, the number of EGFR gene amplification positive rare cells was>5), the area under the curve (AUC) of the detection of EGFR gene amplification in peripheral blood rare cells for discrimination of benign and malignant pulmonary lesions was 0.816 (95%CI: 0.761-0.870), with a sensitivity of 83.2%, a specificity of 80.7%, and an accuracy of 82.1%. Based on the analysis of the diameter of the nodules, the AUC for distinguishing between benign and malignant pulmonary nodules with diameter 5-9 mm and 10-30 mm was 0.797 (95%CI: 0.707-0.887) and 0.809 (95%CI: 0.669-0.949), respectively, with sensitivity, specificity and accuracy reached 75% or above. Based on the analysis of nodule density, the AUC for distinguishing between benign and malignant solid nodule and subsolid nodule was 0.845 (95%CI: 0.751-0.939) and 0.790 (95%CI: 0.701-0.880), respectively, with sensitivity, specificity and accuracy reached 75% or above. Based on the analysis of nodule number, the AUC for distinguishing between benign and malignant solitary pulmonary nodule and multiple pulmonary nodule was 0.830 (95%CI: 0.696-0.965) and 0.817 (95%CI: 0.758-0.877), respectively, with sensitivity, specificity and accuracy reached 80% or above. Conclusion: The detection of EGFR gene amplification in peripheral blood rare cells contributes to the evaluation of benign and malignant pulmonary nodules, and can be used in the auxiliary diagnosis of benign and malignant pulmonary nodules.

Immunotherapy in resectable NSCLC: Answering the question or questioning the answer?

As immunotherapy makes its way into the perioperative setting, a growing number of clinical trials are expanding the evidence base for resectable non-small cell lung cancer (NSCLC) management. Identifying the optimal treatment pattern-whether it's neoadjuvant, adjuvant, or a combination of both-is a crucial next step, particularly in pinpointing which patients benefit the most. This decision-making process requires a multi-disciplinary treatment team capable of utilizing tissue and plasma genomic testing to inform therapeutic choices. Leveraging the perioperative treatment platform, it remains pivotal to integrate circulating tumor DNA (ctDNA) monitoring into clinical trial design efficiently and provide clear guidance on treatment.

Integration of multi-omics data for survival prediction of lung adenocarcinoma.

BACKGROUND AND OBJECTIVE: The morbidity of lung adenocarcinoma (LUAD) has been increasing year by year and the prognosis is poor. This has prompted researchers to study the survival of LUAD patients to ensure that patients can be cured in time or survive after appropriate treatment. There is still no fully valid model that can be applied to clinical practice. METHODS: We introduced struc2vec-based multi-omics data integration (SBMOI), which could integrate gene expression, somatic mutations and clinical data to construct mutation gene vectors representing LUAD patient features. Based on the patient features, the random survival forest (RSF) model was used to predict the long- and short-term survival of LUAD patients. To further demonstrate the superiority of SBMOI, we simultaneously replaced scale-free gene co-expression network (FCN) with a protein-protein interaction (PPI) network and a significant co-expression network (SCN) to compare accuracy in predicting LUAD patient survival under the same conditions. RESULTS: Our results suggested that compared with SCN and PPI network, the FCN based SBMOI combined with RSF model had better performance in long- and short-term survival prediction tasks for LUAD patients. The AUC of 1-year, 5-year, and 10-year survival in the validation dataset were 0.791, 0.825, and 0.917, respectively. CONCLUSIONS: This study provided a powerful network-based method to multi-omics data integration. SBMOI combined with RSF successfully predicted long- and short-term survival of LUAD patients, especially with high accuracy on long-term survival. Besides, SBMOI algorithm has the potential to combine with other machine learning models to complete clustering or stratificational tasks, and being applied to other diseases.

PRMT5-mediated methylation of STAT3 is required for lung cancer stem cell maintenance and tumour growth.

STAT3 is constitutively activated in many cancer types, including lung cancer, and can induce cancer cell proliferation and cancer stem cell (CSC) maintenance. STAT3 is activated by tyrosine kinases, such as JAK and SRC, but the mechanism by which STAT3 maintains its activated state in cancer cells remains unclear. Here, we show that PRMT5 directly methylates STAT3 and enhances its activated tyrosine phosphorylation in non-small cell lung cancer (NSCLC) cells. PRMT5 expression is also induced by STAT3, suggesting the presence of a positive feedback loop in cancer cells. Furthermore, methylation of STAT3 at arginine 609 by PRMT5 is important for its transcriptional activity and support of tumour growth and CSC maintenance. Indeed, NSCLC cells expressing the STAT3 mutant which R609 was replaced to alanine (R609K) show significantly impaired tumour growth in nude mice. Overall, our study reveals a mechanism by which STAT3 remains activated in NSCLC and provides a new target for cancer therapeutic approaches.

Associations between chronic obstructive pulmonary disease and ten common cancers: novel insights from Mendelian randomization analyses.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a significant global health issue, suspected to elevate the risk for various cancers. This study sought to discern whether COPD serves as a risk marker or a causative factor for prevalent cancers. METHODS: We employed univariable MR (UVMR) analyses to investigate the causal relationship between COPD and the top ten common cancers. Sensitivity analyses were performed to validate the main findings. Multivariable MR (MVMR) and two-step MR analyses were also conducted. False-discovery-rate (FDR) was used to correct multiple testing bias. RESULTS: The UVMR analysis demonstrated notable associations between COPD and lung cancer (odds ratio [OR] = 1.42, 95%CI 1.15-1.77, FDR = 6.37 × 10-3). This relationship extends to lung cancer subtypes such as squamous cell carcinoma (LUSC), adenocarcinoma (LUAD), and small cell lung cancer (SCLC). A tentative link was also identified between COPD and bladder cancer (OR = 1.53, 95%CI 1.03-2.28, FDR = 0.125). No significant associations were found between COPD and other types of cancer. The MVMR analysis that adjusted for smoking, alcohol drinking, and body mass index did not identify any significant causal relationships between COPD and either lung or bladder cancer. However, the two-step MR analysis indicates that COPD mediated 19.2% (95% CI 12.7-26.1%), 36.1% (24.9-33.2%), 35.9% (25.7-34.9%), and 35.5% (26.2-34.8%) of the association between smoking and overall lung cancer, as well as LUAD, LUSC, and SCLC, respectively. CONCLUSIONS: COPD appears to act more as a risk marker than a direct cause of prevalent cancers. Importantly, it partially mediates the connection between smoking and lung cancer, underscoring its role in lung cancer prevention strategies.

Molecular mechanism of radiation tolerance in lung adenocarcinoma cells using single-cell RNA sequencing.

The efficacy of radiotherapy, a cornerstone in the treatment of lung adenocarcinoma (LUAD), is profoundly undermined by radiotolerance. This resistance not only poses a significant clinical challenge but also compromises patient survival rates. Therefore, it is important to explore this mechanism for the treatment of LUAD. Multiple public databases were used for single-cell RNA sequencing (scRNA-seq) data. We filtered, normalized and downscaled scRNA-seq data based on the Seurat package to obtain different cell subpopulations. Subsequently, the ssGSEA algorithm was used to assess the enrichment scores of the different cell subpopulations, and thus screen the cell subpopulations that are most relevant to radiotherapy tolerance based on the Pearson method. Finally, pseudotime analysis was performed, and a preliminary exploration of gene mutations in different cell subpopulations was performed. We identified HIST1H1D+ A549 and PIF1+ A549 as the cell subpopulations related to radiotolerance. The expression levels of cell cycle-related genes and pathway enrichment scores of these two cell subpopulations increased gradually with the extension of radiation treatment time. Finally, we found that the proportion of TP53 mutations in patients who had received radiotherapy was significantly higher than that in patients who had not received radiotherapy. We identified two cellular subpopulations associated with radiotherapy tolerance, which may shed light on the molecular mechanisms of radiotherapy tolerance in LUAD and provide new clinical perspectives.

Methods to Enable Spatial Transcriptomics of Bone Tissues.

Understanding the relationship between the cells and their location within each tissue is critical to uncover the biological processes associated with normal development and disease pathology. Spatial transcriptomics is a powerful method that enables the analysis of the whole transcriptome within tissue samples, thus providing information about the cellular gene expression and the histological context in which the cells reside. While this method has been extensively utilized for many soft tissues, its application for the analyses of hard tissues such as bone has been challenging. The major challenge resides in the inability to preserve good quality RNA and tissue morphology while processing the hard tissue samples for sectioning. Therefore, a method is described here to process freshly obtained bone tissue samples to effectively generate spatial transcriptomics data. The method allows for the decalcification of the samples, granting successful tissue sections with preserved morphological details while avoiding RNA degradation. In addition, detailed guidelines are provided for samples that were previously paraffin-embedded, without demineralization, such as samples collected from tissue banks. Using these guidelines, high-quality spatial transcriptomics data generated from tissue bank samples of primary tumor and lung metastasis of bone osteosarcoma are shown.