Introduction: We used CBCT application as one-stop-shop nodule orientated approach in regards to increase DY, reduce complication rate, reduce time on-table and economical costs with classical peripheral instruments including mini-cryoprobe (ERBE 1,1mm), rEBUS (Olympus) and standard RUFBs (Olympus Company) with at least 2mm working channel and 4,2mm outer diameter for the diagnosis of peripheral targets (iSPNs) in a prospective all-comers registry after detailed analysis of pre-interventional CT for vessel- and bronchus sign classes. Materials and Methods: From Jun 2017 until Nov 2019 in 90 all-comers patients between 16 and 95 years fit for bronchoscopy with 101 peripheral lesions in a daily routine scheme after informed consent about this prospective registry were included. For histological proven benign disease in any lesion patients had to adhere FU according radiological guidelines and further on by re-visits for at least 2 years after biopsy resulting into last visit in Feb 2022 without any drop-out. Present HRCT was mandatory to achieve one day before intervention. It had to be decided by the examiner mainly after analysis of the preset HRCT which of the 3 CBCT driven modalities were used for diagnostical approach: A) Pure endobronchial approach (CBCT, rEBUS, TBB), B) Pure transthoracical approach with a 21G core-biopsy needle (BIOPINCE needle) with CBCT only, or C) Combined approach as described below (CBCT, rEBUS, TTNA). As instruments were available common forceps and needles, EWC, curette and various RUFB (Olympus Company) mentioned in the materials section. A second CBCT was only allowed in the combined approach group to plan the 3D transthoracic approach in expiration whereas even a CBCT for tool-in-lesion control (TIL CBCT) was never allowed in all 3 groups. Results: In 100 lesions predefined modalities pure endobiopsy, pure TTNA and combined approaches were performed in 77, 9 and 14 lesions respectively without any pneumothorax or bleeding. In these 3 modalities we found confirmed (mostly specific) benign and malignant cases 47 and 30, 4 and 5, 2 and 12 respectively. Lesion sizes in the 3 different groups were (median, mean) 14 and 17,7mm (of those 41 invisible of 77 under XR (53%) in the pure endobiopsy group), 27 and 31mm (11% invisible under XR in the pure TTNA group), 18,5 and 23mm (35% invisible under XR in the combined group) respectively. In the 3 groups for the malignant cases 25 of 30, 5 of 5 and 12 of 12 were diagnosed correctly rendering a diagnostical yield of 42 in 47 malignant cases for the whole algorithm (89,4%) with sizes (mean, median) for the whole algorithm of 16 and 19,7mm respectively which is comparable to published data for robotic-assisted bronchoscopy yield. In regards to vessel sign analysis it has to be clearly stated that the significance level for outcome prediction is inferior to bronchus sign analysis. In multivariate analysis there was a clear tendency towards higher outcome prediction especially if a pulmonary artery branch leads into such target even when a bronchus sign is missing. For NY when comparing univariate analysis and partition model analysis at a set diameter of >11mm with significance (p=0,0052) the additional advantage of analysing a given vessel sign (especially pulmonary artery branches) seems to add on 19% of valuable outcome prediction. Conclusion: A nodule orientated approach in a manual CBCT-AF environment including typical instruments renders in experienced hands comparable results to robotic assisted bronchoscopy even without UTN bronchoscopes or other specialized, therefore expensive tools. In multivariate analysis only bronchus sign analysis revealed significant (p = 0,05) prediction of navigational yield outcome prediction whereas vessel sign analysis increases highly the odds ratio in favor of positive outcome prediction but without significance at the given level. In a partition model to erase outliers at a set iSPN diameter >11mm vessel sign analysis (especially pulmonary artery branches) renders a significant and ameliorated prediction of NY.

Background: Gastric cancer (GC) is the third leading cause of cancer-related death and is associated with high mortality and morbidity. Helicobacter pylori (HP) infection is the most important cause of GC. We aimed to identify the core genes of HP caused GC and further elucidate the underlying mechanisms. Methods: GC and HP associated gastritis (HPAG) gene expression data were sourced from Gene Expression Omnibus. Key genes affecting GC prognosis were identified using Cytoscape software. Patient groups were formed based on key gene expression, and the immune analyses were performed with R. MNU, derived from nitrite by HP, was given to GC mice (240ppm) for histology and fluorescence assays. For in vitro experiments, cells received MNU (20 μM) stimulation for 24 hours. Results: CD14 was the only key gene identified. A total of 412 GC patients were divided into CD14-high and CD14-low groups. The two groups showed significant differences in immune cell populations and immune checkpoints. In particular, there was a notable increase in M2 macrophages in GC patients with high CD14 expression (P <0.001). GC Patients with high CD14 expression exhibited a more pronounced immune response than those with low CD14 expression, and elevated CD14 expression positively correlated with the efficacy of CTLA4 therapy (P <0.05). These results indicated that CD14 expression was strongly correlated with the GC immune response. A noticeable increase in CD14 levels was observed in MNU-induced GC animals, cell models, and GC patients. In addition, the number of M2 macrophages was increased in MNU-induced GC mice. Conclusion: Reducing CD14 expression may increase the survival rate of GC patients through the modulation of immune responses. The complex mechanism of CD14's influence on prognosis deserves further investigation.

A disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) plays critical roles in various cancer-associated biological events, such as cell multiplication, migration, and metastasis. This study employs both the TCGA database and patient samples to demonstrate that ADAM10 is highly expressed in non-small cell lung cancer (NSCLC) compared with normal tissue at different stages. Increased ADAM10 expression is positively correlated with decreased overall and recurrence-free survival. On the functional front, overexpression of ADAM10 promotes lung cancer cell progression, migration, and invasion, whereas downregulation of ADAM10 inhibits these processes. Mechanically, ADAM10 modulates the expression of Notch1, MMP9 and EMT markers such as Vimentin, N-cadherin, and E-cadherin. Overall, our findings suggest that ADAM10 may be a promising therapeutic and prognostic marker for NSCLC, emphasizing the importance of regulating its expression.

Head and neck squamous cell carcinoma (HNSCC) is one of the most frequent cancers with a high mortality rate. Lactate accumulation, a hallmark of cancer, has received extensive attention, but its role in HNSCC remains underexplored. Therefore, we identified 33 prognostic genes related to lactate accumulation. By consensus clustering, we separated all HNSCC samples into cluster_A or cluster_B and explored the difference of clinicopathological characteristics and genomics landscape. Next, we performed LASSO analysis and RSF to calculate the lactate-related gene score (LRGS) and constructed a risk model with high accuracy for predicting survival, as estimated by ROC, nomogram, and calibration curve. Then, through OncoPredict algorithm and TCIA, we filter the suitable drugs, especially immunology with diverse LRGS. GSEA analysis showed that the DEGs of LRGS were enriched in activation of immune response and positive regulation of immune response. Moreover, we developed a tumor-infiltrating immune-related lncRNA signature (TILSig) through a combination of 115 immune cell lines from 16 GEO datasets and DealGPL570. Subsequently, we identified the 9 tumor-infiltrating immune-related lncRNAs and calculated the TIL_score. The correlations among these tumor-infiltrating immune-related lncRNAs, hub lactate-related genes and LRGS levels were visualized. According to validation using multiple datasets including TCGA, GSE65858, GSE41613, GSE27020, and the IMvigor 210 database, CARS2, NFU1, and SYNJ1 were identified as hub genes. In light of a comprehensive pan-cancer study, we analyzed these genes to detect the potential clinical value. In conclusion, the constructed LRGS provides important insights for subsequent mechanistic research and can guide clinicians in proposing therapeutic strategies for HNSCC patients.

Background: Hepatocellular carcinoma (HCC) is a common malignant tumor and has a poor prognosis. Minichromosome maintenance 3 (MCM3) protein is upregulated in several cancers, but the biological function, molecular mechanisms and the relationship with tumor immunity of MCM3 in HCC remain poorly understood.Methods: The expression levels and prognosis role of MCM3 in HCC were analyzed based on TCGA, GEO and LIHC databases, and 40 paired tissue samples. We conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses on these DEGs to explore the potential impact of MCM3 on the biological behavior of HCC. In addition, flow cytometry, CCK-8, EdU, colony formation and nude mice xenograft models were employed to investigate the biological functions of MCM3. Furthermore, immune cell infiltration, markers and checkpoint-associated genes were analyzed by TIMER 2.0, ACLBI and TCGA database.Results: In this study, we investigated the expression and function of MCM3 in HCC. MCM3 was highly expressed in a variety of tumors including HCC, and high MCM3 expression was positively associated with various clinicopathological parameters and acted as an independent factor of the poor prognosis for overall survival in HCC. Meanwhile, immune characteristics analysis indicated that high MCM3 expression was related to the level of immune cell infiltration and immune checkpoints in HCC. Our functional enrichment analysis indicated that MCM3 is mainly involved in the cell cycle and cell metabolic related pathways. Moreover, in vitro and in vivo experiments further confirmed that MCM3 could promote the proliferation of HCC by regulating cell cycle progression.Conclusions: Our results indicated that MCM3 was up-regulated in HCC and might become a biomarker in the diagnosis and treatment of patients with HCC.

Background: Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal technology for investigating novel therapeutic targets in cancer. Despite its significance, there remains a scarcity of studies utilizing this technology to address treatment strategies specifically tailored for early-stage lung adenocarcinoma (LUAD). Consequently, this study aimed to investigate the tumor microenvironment (TME) characteristics and develop a prognostic model for early-stage LUAD. Methods: The markers identifying cell types were obtained from the CellMarker database and published research. The SCEVAN package was employed for identifying malignant lung epithelial cells. Single-cell downstream analyses were conducted using the SCP package, encompassing gene set enrichment analysis, enrichment analysis, pseudotime trajectory analysis, and differential expression analysis. Calibration curves, receiver operating characteristic curves, and decision curve analysis were employed to assess the performance of the prognostic model for LUAD. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), western blot, cell transfection, cell proliferation, and cell invasion assays were performed to validate the expression and biological function. Results: Seven cell types were distinguished in the scRNA-seq dataset through the utilization of cell markers documented in published literature. Four subpopulations of early-stage LUAD tumor cells exhibited a high degree of heterogeneity. The prognostic model constructed by PERP and KRT8 showed a great prediction for distinguishing the early-stage LUAD and normal tissues. The validation of PERP and KRT8 expression levels was carried out through both RT-qPCR and western blot analyses. Eventually, in vitro experiments, including CCK8, colony formation, EdU, and transwell assays, confirmed that KRT8 and PERP could promote LUAD cell proliferation and migration. Conclusions: Our study provided a comprehensive characterization of the TME in LUAD through integrative single-cell and bulk transcriptomic analyses. We identified dynamic transitions from normal epithelial cells to tumor cells, revealing the heterogeneity and evolution of malignant LUAD cells. The novel prognostic model based on KRT8 and PERP demonstrated robust predictive performance, offering a promising tool for early-stage LUAD risk stratification. Functional experiments further confirmed that KRT8 and PERP promote tumor proliferation and migration, providing new insights into their roles as therapeutic targets.

Background: Ubiquitination is involved in several tumor immunomodulatory processes, and targeting E3 ubiquitin ligases has substantial potential in cancer therapy. Methods: In this study, the key E3 ubiquitin ligases involved in regulating the malignant progression of LUAD were studied. We first systematically investigated the expression landscape, prognosis, immune infiltration, drug sensitivity, and potential molecular mechanisms of these hub genes in LUAD. CDC20 was localized by immunofluorescence analysis in tumor cell lines, and its expression level was determined by immunohistochemistry on tissue chips. Single-cell analysis and spatial transcriptomics were used to determine CDC20 expression in multiple cell types. Molecular docking was performed via computer simulation to verify the ability of drugs to bind to target genes. Results: We found that these hub genes are specifically overexpressed in LUAD and are associated with poor patient prognosis. All five E3 ubiquitin ligase genes were negatively correlated with B cells and dendritic cells but positively related to neutrophil immune infiltration. In addition, analysis of the CTRP and GDSC databases revealed that the sensitivity to multiple antitumor drugs increased when CCNF was highly expressed. GSEA enrichment analysis demonstrated that the G2M_CHECKPOINT, MTORC1_SIGNALING, OXIDATIVE_PHOSPHORYLATION, and GLYCOLYSIS signaling pathways were enriched when CDC20 was highly expressed. Further correlation analysis indicated that CDC20 was positively correlated with the expression of the key genes mTOR, S6K1, and 4E-BP1 and the autophagy-related gene ULK1 in the mTORC1 signaling pathway. Conclusions: These key E3 ubiquitin ligases serve as potential molecular biomarkers for predicting the prognosis, immune response, and drug sensitivity of LUAD patients.

Background: This study aimed to investigate glycogen metabolism in gastric cancer (GC) and develop a glycogen-based riskScore model for predicting GC prognosis. Methods: Patients' expression profiles for 33 tumor types were retrieved from TCGA. Four GC bulk and one single-cell sequencing datasets were obtained from GEO database. This study also enrolled a bladder urothelial carcinoma immunotherapeutic IMvigor210 cohort. The ssGSEA method was conducted to assess glycogen biosynthesis and degradation level. Consensus clustering analysis was conducted to identify different clusters. A glycogen riskScore signature was developed to evaluate prognostic value across different cohorts. Besides, in vitro experiments were conducted to further evaluate the role of glycogen metabolism related genes in GC. Results: Both glycogen biosynthesis and degradation were significantly associated with worse overall survival and were also related with malignant phenotype in GC at both bulk and single-cell levels. Differential outcomes and immune functions were verified in the three identified clusters. The constructed glycogen riskScore model accurately classified GC patients with different outcomes, genomic and immune landscape, and performed well in predicting prognosis through external validation, immunotherapy and pan-cancer cohorts. Furthermore, the riskScore could predict response to chemotherapy and immunotherapy. Functional analyses revealed the signature's connection to pro-tumor and immunosuppression related pathways across pan-cancer. Additionally, glycogen metabolism related genes were found to regulate the malignant phenotypes of GC cells. Conclusion: This study revealed important roles of glycogen metabolism in promoting progression of GC and presented a glycogen riskScore model as a novel tool for predicting prognosis and treatment response.

Metastasis is the leading cause of cancer-related deaths and poses a treatment challenge. Although studies have shown the importance of epithelial-mesenchymal transition (EMT) and metabolic reprogramming during cancer metastasis, the link between EMT and metabolic reprogramming, as well as the underlying molecular mechanisms by which both mediate cancer cell invasion and metastasis have not been elucidated. Here, we observed that interactions between platelets and cancer cells promote the secretion of TGF-β, thereby initiating EMT, promoting the invasion, and altering the metastatic and metabolic potential of colon cancer cells. TGF-β activates the AKT signaling pathway to enhance HK1 and HK2 expression in cancer cells, leading to increased glucose consumption, ATP production, and precise modulation of cell cycle distribution. In an energy-deficient model induced by oxidative phosphorylation (OXPHOS) inhibition with oligomycin A, TGF-β-induced highly metastatic HCT116 (H-HCT116) cells adapt by upregulating HK expression and glycolytic metabolism, while concurrently decreasing cell proliferation to conserve energy for survival. Mechanistically, H-HCT116 cells regulate cell division rates by downregulating CDK2, CDK4, and Cyclin D1 protein expression and upregulating p21 expression. Furthermore, H-HCT116 cells display enhanced motility, which is linked to increased mitochondrial metabolic activity. These findings indicated that cancer cells-platelets interaction secreted TGF-β activates cancer metastasis potential by inducing metabolic reprogramming and bioenergetic adaptation. The present study provides new insights into the adaptive strategies of highly metastatic cancer cells under adverse conditions and indicates that targeting glycolysis and metabolic reprogramming could serve as a viable approach to prevent cancer metastasis.

Gamma-delta (γδ) T cells are a crucial component of the tumor immune microenvironment which are considered a promising potential therapeutic strategy and target. Increasing evidence suggests that these unique immune cells play significant roles across various cancers. However, γδ T cells are often regarded as having dual roles in tumors, and their influence on lung adenocarcinoma (LUAD) remains controversial. In this research, we employed a wild-ranging approach using multi-omics data to investigate the function of γδ T cells in LUAD. The abundance of γδ T cell infiltration is linked to a positive prognosis in lung adenocarcinoma. The tumor-inhibiting role of γδ T cells was played through intrinsic lineage evolution, acquiring cytotoxic functions and engaging in signal transduction with antigen-presenting cells. Furthermore, patients with higher γδ T cells infiltration abundance might be more favorable for immunotherapy. Lastly, we established a predictive model using CT images based on radiomics, providing a non-invasive strategy to assess γδ T cells infiltration in LUAD patients. These findings offer new insights and perspectives the personalized therapies of γδ T cells.