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.

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.

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.

Gefitinib metabolism-related lncRNAs for the prediction of prognosis, tumor microenvironment and drug sensitivity in lung adenocarcinoma.

The complete compound of gefitinib is effective in the treatment of lung adenocarcinoma. However, the effect on lung adenocarcinoma (LUAD) during its catabolism has not yet been elucidated. We carried out this study to examine the predictive value of gefitinib metabolism-related long noncoding RNAs (GMLncs) in LUAD patients. To filter GMLncs and create a prognostic model, we employed Pearson correlation, Lasso, univariate Cox, and multivariate Cox analysis. We combined risk scores and clinical features to create nomograms for better application in clinical settings. According to the constructed prognostic model, we performed GO/KEGG and GSEA enrichment analysis, tumor immune microenvironment analysis, immune evasion and immunotherapy analysis, somatic cell mutation analysis, drug sensitivity analysis, IMvigor210 immunotherapy validation, stem cell index analysis and real-time quantitative PCR (RT-qPCR) analysis. We built a predictive model with 9 GMLncs, which showed good predictive performance in validation and training sets. The calibration curve demonstrated excellent agreement between the expected and observed survival rates, for which the predictive performance was better than that of the nomogram without a risk score. The metabolism of gefitinib is related to the cytochrome P450 pathway and lipid metabolism pathway, and may be one of the causes of gefitinib resistance, according to analyses from the Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Immunological evasion and immunotherapy analysis revealed that the likelihood of immune evasion increased with risk score. Tumor microenvironment analysis found most immune cells at higher concentrations in the low-risk group. Drug sensitivity analysis found 23 sensitive drugs. Twenty-one of these drugs exhibited heightened sensitivity in the high-risk group. RT-qPCR analysis validated the characteristics of 9 GMlncs. The predictive model and nomogram that we constructed have good application value in evaluating the prognosis of patients and guiding clinical treatment.

Ferredoxin 1: a gatekeeper in halting lung adenocarcinoma progression through activation of the GPRIN2 signaling pathway.

BACKGROUND: Lung adenocarcinoma (LUAD) is a highly lethal form of lung cancer. Despite advancements in treatments, managing LUAD is still challenging due to its aggressive behavior. Recent studies indicate that various molecular pathways, including the dysregulation of ferredoxin 1 (FDX1), play roles in LUAD progression. FDX1, a crucial protein in cellular redox reactions and energy metabolism, has been linked to several cancers. However, its exact role in the development of LUAD is not yet fully understood. METHODS: We investigated the role of ferredoxin 1 (FDX1) in LUAD progression through analysis of its expression in LUAD tissues and its impact on patient survival. Functional assays were performed to assess the effects of FDX1 overexpression on LUAD cell proliferation, migration, and invasion. A xenograft model was employed to evaluate the tumorigenesis potential of LUAD cells with FDX1 overexpression. Mechanistic insights into FDX1 regulation were gained through depletion experiments targeting the G protein-regulated inducer of neurite outgrowth 2 (GPRIN2)/PI3K signaling pathway. RESULTS: FDX1 expression was down-regulated in LUAD tissues, correlating with shorter patient survival. Overexpression of FDX1 suppressed LUAD cell proliferation, migration, and invasion in vitro, and inhibited tumorigenesis in vivo. Mechanistically, the GPRIN2/PI3K signaling pathway was implicated in FDX1 regulation, as depletion of GPRIN2 reversed the effects of FDX1 overexpression on cellular functions. CONCLUSIONS: Our findings highlight FDX1 as a potential tumor suppressor in LUAD, acting through modulation of the GPRIN2/PI3K signaling pathway. These results suggest FDX1 as a promising therapeutic target for LUAD treatment, warranting further investigation into its clinical relevance.

Upregulation of mRNA Expression of ADGRD1/GPR133 and ADGRG7/GPR128 in SARS-CoV-2-Infected Lung Adenocarcinoma Calu-3 Cells.

Adhesion G protein-coupled receptors (aGPCRs) play an important role in neurodevelopment, immune defence and cancer; however, their role throughout viral infections is mostly unexplored. We have been searching for specific aGPCRs involved in SARS-CoV-2 infection of mammalian cells. In the present study, we infected human epithelial cell lines derived from lung adenocarcinoma (Calu-3) and colorectal carcinoma (Caco-2) with SARS-CoV-2 in order to analyse changes in the level of mRNA encoding individual aGPCRs at 6 and 12 h post infection. Based on significantly altered mRNA levels, we identified four aGPCR candidates-ADGRB3/BAI3, ADGRD1/GPR133, ADGRG7/GPR128 and ADGRV1/GPR98. Of these receptors, ADGRD1/GPR133 and ADGRG7/GPR128 showed the largest increase in mRNA levels in SARS-CoV-2-infected Calu-3 cells, whereas no increase was observed with heat-inactivated SARS-CoV-2 and virus-cleared conditioned media. Next, using specific siRNA, we downregulated the aGPCR candidates and analysed SARS-CoV-2 entry, replication and infectivity in both cell lines. We observed a significant decrease in the amount of SARS-CoV-2 newly released into the culture media by cells with downregulated ADGRD1/GPR133 and ADGRG7/GPR128. In addition, using a plaque assay, we observed a reduction in SARS-CoV-2 infectivity in Calu-3 cells. In summary, our data suggest that selected aGPCRs might play a role during SARS-CoV-2 infection of mammalian cells.

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.

Clinical relevance of somatic mutations in Chinese lung adenocarcinoma and their prognostic implications for survival.

BACKGROUND: To comprehensively elucidate the genomic and mutational features of lung cancer cases, and lung adenocarcinoma (LUAD), it is imperative to conduct ongoing investigations into the genomic landscape. In this study, we aim to analyze the somatic mutation profile and assessed the significance of these informative genes utilizing a retrospective LUAD cohort. METHODS: A total of 247 Chinese samples were analyzed to exhibit the tumor somatic genomic alterations in patients with LUAD. The Cox regression analysis was employed to identify prognosis-related genes and establish a predictive model for stratifying patients with LUAD. RESULTS: In the Dianjiang People's Hospital (DPH) cohort, the top five frequent mutated genes were (Epidermal growth factor receptor) EGFR (68%), TP53 (30%), RBM10 (13%), LRP1B (9%), and KRAS (9%). Of which, EGFR is a mostly altered driver gene, and most mutation sites are located in tyrosine kinase regions. Oncogene pathway alteration and mutation signature analysis demonstrated the RTK-RAS pathway alteration, and smoking was the main carcinogenic factor of the DPH cohort. Furthermore, we identified 34 driver genes in the DPH cohort, including EGFR (68%), TP53 (30.4%), RBM10 (12.6%), KRAS (8.5%), LRP1B (8.5%), and so on, and 45 Clinical Characteristic-Related Genes (CCRGs) were found to closely related to the clinical high-risk factors. We developed a Multiple Parameter Gene Mutation (MPGM) risk model by integrating critical genes and oncogenic pathway alterations in LUAD patients from the DPH cohort. Based on publicly available LUAD datasets, we identified five genes, including BRCA2, Anaplastic lymphoma kinase (ALK), BRAF, EGFR, and Platelet-Derived Growth Factor Receptor Alpha (PDGFRA), according to the multivariable Cox regression analysis. The MPGM-low group showed significantly better overall survival (OS) compared to the MPGM-high group (p < 0.0001, area under the curve (AUC) = 0.754). The robust performance was validated in 55 LUAD patients from the DPH cohort and another LUAD dataset. Immune characteristics analysis revealed a higher proportion of primarily DCs and mononuclear cells in the MPGM-low risk group, while the MPGM-high risk group showed lower immune cells and higher tumor cell infiltration. CONCLUSION: This study provides a comprehensive genomic landscape of Chinese LUAD patients and develops an MPGM risk model for LUAD prognosis stratification. Further follow-up will be performed for the patients in the DPH cohort consistently to explore the resistance and prognosis genetic features.

Death associated protein kinase 1 predicts the prognosis and the immunotherapy response of various cancers.

BACKGROUND: Death Associated Protein Kinase 1 (DAPK1) is a calcium/calmodulin-dependent serine/threonine kinase, which has been reported to be a tumor suppressor with unbalanced expression in various tissues. However, its function in tumor immunotherapy is still unclear. METHODS: The online GEPIA2 database was used to support TCGA results. We explored the DAPK1 pan-cancer genomic alteration analysis using the cBioPortal web tool. The Human Protein Atlas (HPA) was employed to mine DAPK1 protein information. We verified the expression of DAPK1 in lung adenocarcinoma samples using RT-qPCR. Subsequently, the relationship between the expression of DAPK1 and the clinical stage was analyzed. We used TIMER2.0 as the primary platform for studying DAPK1-related immune cell infiltration. Associations between DAPK1 and immunotherapy biomarkers were analyzed using Spearman correlation analysis. TMB and MSI expression was also examined. Finally, we used Kaplan-Meier Plots to evaluate the relationship between DAPK1 expression and the efficacy of immunotherapy. RESULTS: DAPK1 is aberrantly expressed in most cancer types and has prognostic power in various cancers. Gene mutation was the most common DAPK1 alteration across pan-cancers. The DAPK1 protein was mainly localized to tumor cell centrosomes. DAPK1 was also significantly associated with immune-activated hallmarks, immune cell infiltration, and the expression of immunomodulators. Notably, DAPK1 can also significantly predict responses to anti-PD1 and anti-CTLA-4 therapy in cancer patients. CONCLUSIONS: Our findings suggest that DAPK1 may not only be an effective prognostic factor in cancer patients but may also function as a promising predictive immunotherapy biomarker for cancer patients treated with immune checkpoint inhibitors.

[Establishment of Dual Fluorescent Labeled Human High Bone Metastasis 
Lung Adenocarcinoma Cell Line and Transcriptomic Characterization Analysis].

BACKGROUND: Bone is a common site for metastasis in lung adenocarcinoma, but the mechanism behind lung adenocarcinoma bone metastasis is still unclear. And currently, there is a lack of easily traceable and stable lung adenocarcinoma bone metastasis cell models, which limits the research on the mechanism of lung adenocarcinoma bone metastasis. The establishment of human lung adenocarcinoma cell line that are highly metastatic to bone, labeled with green fluorescent proteins (GFP) and fireflies luciferase (LUC), along with transcriptomic characterization, would be beneficial for research on lung adenocarcinoma bone metastasis and provide new experimental methods. METHODS: The human lung adenocarcinoma cell line A549-GFP-LUC was injected into nude mice via the left ventricle to construct a bone metastasis model, and was domesticated in vivo for three consecutive times to obtain the human high bone metastasis lung adenocarcinoma cell line A549-GFP-LUC-BM3; cell counting kit-8 (CCK-8), colony formation assay, scratch wound assays, Transwell assay and Western blot were used to compare the proliferation and invasion abilities of A549-GFP-LUC-BM3 with the parental cells. A549-GFP-LUC-BM3 cells and parental cells were further analyzed by transcriptomic sequencing. RESULTS: Human high-bone metastatic lung adenocarcinoma cells A549-GFP-LUC-BM3 was successfully established. Compared to parental cells, this cells exhibited a significantly higher incidence of bone metastasis and enhanced in vitro proliferation, migration, and invasion abilities. Transcriptomic sequencing results revealed that the A549-GFP-LUC-BM3 cell line had 2954 differentially expressed genes compared to the parental cells, with 1021 genes up-regulated and 1933 genes down-regulated. Gene Ontology (GO) functional enrichment analysis indicated that the differentially expressed genes were primarily localized in cellular components such as the cell periphery. The molecular functions identified as significantly enriched included signaling receptor activity, calcium ion binding, and extracellular matrix structural constituent. Additionally, the biological processes found to be enriched were cell adhesion and biological adhesion. The enrichment analysis conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that the differentially expressed genes were primarily involved in the metabolism of xenobiotics by cytochrome P450, retinol metabolism, drug metabolism-cytochrome P450, cell adhesion molecules, steroid hormone biosynthesis, and the nuclear factor kappa B (NF-κB) signaling pathway. CONCLUSIONS: The highly bone-metastatic human lung adenocarcinoma cell line with GFP and luciferase double labeling was successfully established. The biological behavior and transcriptome sequencing of the cell line suggest that it has a high bone-metastatic potential.

A novel subtype based on driver methylation-transcription in lung adenocarcinoma.

AIMS: To identify driver methylation genes and a novel subtype of lung adenocarcinoma (LUAD) by multi-omics and elucidate its molecular features and clinical significance. METHODS: We collected LUAD patients from public databases, and identified driver methylation genes (DMGs) by MethSig and MethylMix algrothms. And novel driver methylation multi-omics subtypes were identified by similarity network fusion (SNF). Furthermore, the prognosis, tumor microenvironment (TME), molecular features and therapy efficiency among subtypes were comprehensively evaluated. RESULTS: 147 overlapped driver methylation were identified and validated. By integrating the mRNA expression and methylation of DMGs using SNF, four distinct patterns, termed as S1-S4, were characterized by differences in prognosis, biological features, and TME. The S2 subtype showed unfavorable prognosis. By comparing the characteristics of the DMGs subtypes with the traditional subtypes, S3 was concentrated in proximal-inflammatory (PI) subtype, and S4 was consisted of terminal respiratory unit (TRU) subtype and PI subtype. By analyzing TME and epithelial mesenchymal transition (EMT) features, increased immune infiltration and higher expression of immune checkpoint genes were found in S3 and S4. While S4 showed higher EMT score and expression of EMT associated genes, indicating S4 may not be as immunosensitive as the S3. Additionally, S3 had lower TIDE and higher IPS score, indicating its increased sensitivity to immunotherapy. CONCLUSION: The driver methylation-related subtypes of LUAD demonstrate prognostic predictive ability that could help inform treatment response and provide complementary information to the existing subtypes.

Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.

Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-specific antigen, exposing "danger signals" to stimulate the body's immune response. Given the recent development of immunotherapy in lung adenocarcinoma, we explored the role of tumor immunogenic cell death-related lncRNAs in lung adenocarcinoma for prognosis and immunotherapy benefit, which has never been uncovered yet. Based on the lung adenocarcinoma cohorts from the TCGA database and GEO database, the study developed the immunogenic cell death index signature by several machine learning algorithms and then validated the signature for prognosis and immunotherapy benefit of lung adenocarcinoma patients, which had a more stable performance compared with published signatures in predicting the prognosis, and demonstrated predictive value for benefiting from immunotherapy in multiple cohorts of multiple cancers, and also guided the utilization of chemotherapy drugs.

HMGN1 loss sensitizes lung cancer cells to chemotherapy.

The high mobility group nucleosome binding (HMGN) family, constitutes a large family of non-histone protein family known to bind the acidic patch of the nucleosomes with various key cellular functions. Several studies have highlighted the pivotal roles of HMGNs in the pathogenic process of various cancer types. However, the roles of HMGN family in lung adenocarcinoma (LUAD) have not been fully elucidated. Herein, integrative analyses of multiple-omics data revealed that HMGNs frequently exhibit dysregulation in LUAD. Subsequent analysis of the clinical relevance of HMGN1 demonstrated its association with poor prognosis in LUAD and its potential as a diagnostic marker to differentiate LUAD from healthy controls. Additionally, functional enrichment analysis suggested that HMGN1 was mainly involved in DNA repair. To corroborate these findings, cellular experiments were conducted, confirming HMGN1's crucial involvement in homologous recombination repair and its potential to enhance the sensitivity of LUAD cells to standard chemotherapeutic drugs. This study proposes HMGN1 as a novel prognostic biomarker and a promising target for chemotherapy in lung adenocarcinoma.

Integrated single-cell and bulk RNA-Seq analysis enhances prognostic accuracy of PD-1/PD-L1 immunotherapy response in lung adenocarcinoma through necroptotic anoikis gene signatures.

In addition to presenting significant diagnostic and treatment challenges, lung adenocarcinoma (LUAD) is the most common form of lung cancer. Using scRNA-Seq and bulk RNA-Seq data, we identify three genes referred to as HMR, FAM83A, and KRT6A these genes are related to necroptotic anoikis-related gene expression. Initial validation, conducted on the GSE50081 dataset, demonstrated the model's ability to categorize LUAD patients into high-risk and low-risk groups with significant survival differences. This model was further applied to predict responses to PD-1/PD-L1 blockade therapies, utilizing the IMvigor210 and GSE78220 cohorts, and showed strong correlation with patient outcomes, highlighting its potential in personalized immunotherapy. Further, LUAD cell lines were analyzed using quantitative PCR (qPCR) and Western blot analysis to confirm their expression levels, further corroborating the model's relevance in LUAD pathophysiology. The mutation landscape of these genes was also explored, revealing their broad implication in various cancer types through a pan-cancer analysis. The study also delved into molecular subclustering, revealing distinct expression profiles and associations with different survival outcomes, emphasizing the model's utility in precision oncology. Moreover, the diversity of immune cell infiltration, analyzed in relation to the necroptotic anoikis signature, suggested significant implications for immune evasion mechanisms in LUAD. While the findings present a promising stride towards personalized LUAD treatment, especially in immunotherapy, limitations such as the retrospective nature of the datasets and the need for larger sample sizes are acknowledged. Prospective clinical trials and further experimental research are essential to validate these findings and enhance the clinical applicability of our prognostic model.

CRTAC1 identified as a promising diagnosis and prognostic biomarker in lung adenocarcinoma.

CRTAC1, one of the pyroptosis-related genes, has been identified as a protective factor in certain kinds of cancer, such as gastric adenocarcinoma and bladder cancer. The study aimed to investigate the role of CRTAC1 in lung adenocarcinoma (LUAD). LUAD datasets were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), pyroptosis-related genes from GeneCard. Limma package used to find differentially expressed genes (DEGs), least absolute shrinkage and selection operator (LASSO) regression and weighted genes co-expression network analysis (WGCNA) to identify CRTAC1 as hub gene. CRTAC1 expression was confirmed in a real-world cohort using quantitative polymerase chain reaction (qPCR) and Western Blot (WB) analyses. Cellular experiments were conducted to investigate CRTAC1's potential oncogenic mechanisms. CRTAC1 mRNA expression was significantly lower in LUAD tissues (p < 0.05) and showed high accuracy in diagnosing LUAD. Reduced CRTAC1 expression was associated with a poor prognosis. Higher CRTAC1 expression correlated with increased immune cell infiltration. Individuals with high CRTAC1 expression showed increased drug sensitivity. Additionally, qPCR and WB analyses showed that CRTAC1 expression was lower in tumor tissue compared to adjacent normal tissue at both the RNA and protein levels. Upregulation of CRTAC1 significantly inhibited LUAD cell proliferation, invasion, and migration in cellular experiments. CRTAC1 has the potential to serve as a diagnostic and prognostic biomarker in LUAD.

Detection of fucosylated extracellular vesicles miR-4732-5p related to diagnosis of early lung adenocarcinoma by the electrochemical biosensor.

Our preliminary investigation has identified the potential of serum fucosylated extracellular vesicles (EVs) miR-4732-5p in the early diagnosis of lung adenocarcinoma (LUAD) by a fucose-captured strategy utilizing lentil lectin (LCA)-magnetic beads and subsequent screening of high throughput sequencing and validation of real-time quantitative polymerase chain reaction (RT-qPCR). Considering the relatively complicated procedure, expensive equipment, and stringent laboratory condition, we have constructed an electrochemical biosensor assay for the detection of miR-4732-5p. miR-4732-5p is extremely low in serum, down to the fM level, so it needs to be detected by highly sensitive electrochemical methods based on the Mg2+-dependent DNAzyme splitting nucleic acid lock (NAL) cycle and hybridization chain reaction (HCR) signal amplification. In this study, signal amplification is achieved through the dual amplification reactions using NAL cycle in combination with HCR. In addition, hybridized DNA strands bind to a large number of methylene blue (MB) molecules to enhance signaling. Based on the above strategy, we further enhance our signal amplification strategies to improve detection sensitivity and accuracy. The implementation of this assay proceeded as follows: initially, miR-4732-5p was combined with NAL, and then Mg2+-dependent DNAzyme splitted NAL to release auxiliary DNA (S1) strands, which were subsequently captured by the immobilized capture probe DNA (C1) strands on the electrode surface. Following this, abundant quantities of DNA1 (H1) and DNA2 (H2) tandems were generated by HCR, and S1 strands then hybridized with the H1 and H2 tandems through base complementary pairing. Finally, MB was bonded to the H1 and H2 tandems through π-π stacking interaction, leading to the generation of a signal current upon the detection of a potential capable of inducing a redox change of MB by the electrode. Furthermore, we evaluated the performance of our developed electrochemical biosensor assay. The results demonstrated that our assay is a reliable approach, characterized by its high sensitivity (with a detection limit of 2.6 × 10-17 M), excellent specificity, good accuracy, reproducibility, and stability. Additionally, it is cost-effective, requires simple operation, and is portable, making it suitable for the detection of serum fucosylated extracellular vesicles miR-4732-5p. Ultimately, this development has the potential to enhance the diagnostic efficiency for patients with early-stage LUAD.

MiR-1976/NCAPH/P65 axis inhibits the malignant phenotypes of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a malignancy with an abysmal survival rate. High metastasis is the leading cause of the low survival rate of LUAD. NCAPH, an oncogene, is involved in the carcinogenesis of LUAD. However, the regulation of NCAPH in LUAD remains controversial. In this work, we identified an up-regulation of NCAPH in LUAD tissues. Patients who expressed more NCAPH had shorter overall survival (OS). Furthermore, NCAPH overexpression promoted LUAD cell migration while inhibiting apoptosis. MiR-1976 and miR-133b were predicted to target NCAPH expression by searching TargetScan and linkedomics databases. Following that, we confirmed that miR-1976 suppressed NCAPH by directly targeting a 7-bp region of NCAPH 3' untranslated regions (UTR). In addition, increased expression of miR-1976 decreased the proliferation & migration and promoted apoptosis of LUAD cells, and the re-introduction of NCAPH reversed these influences. Furthermore, the xenograft and metastasis mouse models also confirmed that miR-1976 inhibited tumor growth and metastasis in vivo by targeting NCAPH. Finally, we found that MiR-1976 targeting NCAPH blocked the activation of NF-κB. In conclusion, miR-1976 inhibits NCAPH activity in LUAD and acts as a tumor suppressor. The miR-1976/NCAPH/NF-κB axis may, in the future, represent crucial diagnostic and prognostic biomarkers and promising therapeutic options.

Long non­coding RNA lung cancer­associated transcript 1 regulates ferroptosis via microRNA­34a­5p­mediated GTP cyclohydrolase 1 downregulation in lung cancer cells.

Ferroptosis, a recently discovered type of programmed cell death triggered by excessive accumulation of iron­dependent lipid peroxidation, is linked to several malignancies, including non­small cell lung cancer. Long non­coding RNAs (lncRNAs) are involved in ferroptosis; however, data on their role and mechanism in cancer therapy remains limited. Therefore, the aim of the present study was to identify ferroptosis­associated mRNAs and lncRNAs in A549 lung cancer cells treated with RAS­selective lethal 3 (RSL3) and ferrostatin­1 (Fer­1) using RNA sequencing. The results demonstrated that lncRNA lung cancer­associated transcript 1 (LUCAT1) was significantly upregulated in lung adenocarcinoma and lung squamous cell carcinoma tissues. Co­expression analysis of differentially expressed mRNAs and lncRNAs suggested that LUCAT1 has a crucial role in ferroptosis. LUCAT1 expression was markedly elevated in A549 cells treated with RSL3, which was prevented by co­incubation with Fer­1. Functionally, overexpression of LUCAT1 facilitated cell proliferation and reduced the occurrence of ferroptosis induced by RSL3 and Erastin, while inhibition of LUCAT1 expression reduced cell proliferation and increased ferroptosis. Mechanistically, downregulation of LUCAT1 resulted in the downregulation of both GTP cyclohydrolase 1 (GCH1) and ferroptosis suppressor protein 1 (FSP1). Furthermore, inhibition of LUCAT1 expression upregulated microRNA (miR)­34a­5p and then downregulated GCH1. These results indicated that inhibition of LUCAT1 expression promoted ferroptosis by modulating the downregulation of GCH1, mediated by miR­34a­5p. Therefore, the combination of knocking down LUCAT1 expression with ferroptosis inducers may be a promising strategy for lung cancer treatment.

Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most invasive malignant tumor of the respiratory system. It is also the common pathological type leading to the death of LUAD. Maintaining the homeostasis of immune cells is an important way for anti-tumor immunotherapy. However, the biological significance of maintaining immune homeostasis and immune therapeutic effect has not been well studied. METHODS: We constructed a diagnostic and prognostic model for LUAD based on B and T cells homeostasis-related genes. Minimum absolute contraction and selection operator (LASSO) analysis and multivariate Cox regression are used to identify the prognostic gene signatures. Based on the overall survival time and survival status of LUAD patients, a 10-gene prognostic model composed of ABL1, BAK1, IKBKB, PPP2R3C, CCNB2, CORO1A, FADD, P2RX7, TNFSF14, and ZC3H8 was subsequently identified as prognostic markers from The Cancer Genome Atlas (TCGA)-LUAD to develop a prognostic signature. This study constructed a gene prognosis model based on gene expression profiles and corresponding survival information through survival analysis, as well as 1-year, 3-year, and 5-year ROC curve analysis. Enrichment analysis attempted to reveal the potential mechanism of action and molecular pathway of prognostic genes. The CIBERSORT algorithm calculated the infiltration degree of 22 immune cells in each sample and compared the difference of immune cell infiltration between high-risk group and low-risk group. At the cellular level, PCR and CKK8 experiments were used to verify the differences in the expression of the constructed 10-gene model and its effects on cell viability, respectively. The experimental results supported the significant biological significance and potential application value of the molecular model in the prognosis of lung cancer. Enrichment analyses showed that these genes were mainly related to lymphocyte homeostasis. CONCLUSION: We identified a novel immune cell homeostasis prognostic signature. Targeting these immune cell homeostasis prognostic genes may be an alternative for LUAD treatment. The reliability of the prediction model was confirmed at bioinformatics level, cellular level, and gene level.

Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy response.

BACKGROUND: Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures. METHODS: This study encompasses 1564 LUAD patients, 1249 NSCLC patients, and over 10,000 patients with various cancer types from diverse cohorts. We employed the R package ConsensusClusterPlus to separate patients into different ICSM (Iron, Copper, and Sulfur-Metabolism) subtypes. Various machine-learning methods were utilized to develop the ICSMI. Enrichment analyses were conducted using ClusterProfiler and GSVA, while IOBR quantified immune cell infiltration. GISTIC2.0 and maftools were utilized for CNV and SNV data analysis. The Oncopredict package predicted drug information based on GDSC1. TIDE algorithm and cohorts GSE91061 and IMvigor210 evaluated patient response to immunotherapy. Single-cell data was processed using the Seurat package, AUCell package calculated cells geneset activity scores, and the Scissor algorithm identified ICSMI-associated cells. In vitro experiments was conducted to explore the role of ICSMRGs in LUAD. RESULTS: Unsupervised clustering identified two distinct ICSM subtypes of LUAD, each with unique clinical characteristics. The ICSMI, comprising 10 genes, was constructed using integrated machine-learning methods. Its prognostic power was validated in 10 independent datasets, revealing that LUAD patients with higher ICSMI levels had poorer prognoses. Furthermore, ICSMI demonstrated superior predictive abilities compared to 102 previously published signatures. A nomogram incorporating ICSMI and clinical features exhibited high predictive performance. ICSMI positively correlated with patients gene mutations, and integrated analysis of bulk and single-cell transcriptome data revealed its association with TME modulators. Cells representing the high-ICSMI phenotype exhibited more malignant features. LUAD patients with high ICSMI levels exhibited sensitivity to chemotherapy and targeted therapy but displayed resistance to immunotherapy. In a comprehensive analysis across various cancers, ICSMI retained significant prognostic value and emerged as a risk factor for the majority of cancer patients. CONCLUSIONS: ICSMI provides critical prognostic insights for LUAD patients, offering valuable insights into the tumor microenvironment and predicting treatment responsiveness.