Factor In Lung Adenocarcinoma Research Articles

Upregulation of M6A Reader HNRNPA2B1 Associated with Poor Prognosis and Tumor Progression in Lung Adenocarcinoma.

Lung cancer is the most prevalent malignancy worldwide, and lung adenocarcinoma (LUAD) accounts for a substantial proportion of all cases. N6-methyladenosine (m6A) is the most frequent post-transcriptional modification in mRNAs that also plays a role in cancer development. Heterogeneous nuclear ribonucleoprotein A2/B1 (HNRNPA2B1) is a reader of m6A modification, which can affect tumor invasion, migration, and proliferation. The purpose of this study was to explore the prognostic factors of LUAD based on m6A through bioinformatics analysis. The expression levels and prognostic significance of HNRNPA2B1 in LUAD were analyzed on the basis of data extracted from the UALCAN, GEPIA, NCBI-GEO, Human Protein Atlas, STRING, miRDB, TargetScan, PROMO, Starbase, UCSC Xena browser, TIMER, and TISIDB databases. HNRNPA2B1 protein and mRNA levels in several LUAD cell lines were detected by western blotting and qRT-PCR. CCK8, wound-healing and transwell assays were performed to evaluate the proliferation, invasion, and migration abilities of LUAD cells. HNRNPA2B1 mRNA was found to be significantly overexpressed in LUAD tissues, and its high levels correlated with poor OS and DFS. The genes co-expressed with HNRNPA2B1 were related to mRNA production, cell cycle, and histone binding. To determine the mechanistic basis of HNRNPA2B1 in LUAD, we next predicted the microRNAs and transcription factors that were directly associated with HNRNPA2B1, as well as copy number changes. In addition, it was found that HNRNPA2B1 expression was significantly related to CD4+ T cells, neutrophils, lymphocytes, immunomodulators, and chemokines. Besides, knocking down HNRNPA2B1 in the LUAD cells led to a significant reduction in their proliferation, invasion, and migration rates in vitro. Elevated HNRNPA2B1 is a risk factor in LUAD and portends a poor prognosis.

Clinicopathological significance and prognostic values of claudin18.2 expression in solid tumors: a systematic review and meta-analysis.

Claudin18.2 has been established as a putative therapeutic target in human solid malignancies. The aim of this study is to determine claudin18.2 expression as a clinicopathological and prognostic factor in human solid tumors through a systematic review and meta-analysis. Articles were systematically reviewed for studies that included the correlation between claudin18.2 expression and clinicopathological features and prognosis in solid tumors. Meta-analysis was conducted to estimate either odds ratio and 95% confidence intervals (CIs) of clinicopathological factors or hazard ratio and 95% CIs of survival outcomes for claudin18.2 expression in all available solid tumors. 21 studies including 5,331 patients were identified. Overall proportion of claudin18.2 positivity was 29.7%. Analyses of clinicopathological features demonstrated that claudin18.2 positivity correlated with male predominance, lower T stage, more frequent MUC5AC positivity when all primary tumors included. In subgroup analysis, gastric cancer showed significant correlation between high claudin18.2 expression and frequent EBV infection, male predominance and lower T stage. In lung cancer, claudin18.2 expression was associated with favorable overall survival. However, analyses of survival outcomes in all solid tumors showed that claudin18.2 expression was not associated with overall survival and pooled disease-free survival, tumor-specific survival, progression-free survival and relapse-free survival. Our study emphasizes evaluation of claudin18.2 expression as a potential prognostic factor in lung adenocarcinoma and further exploration in other solid tumors as well. https://www.crd.york.ac.uk/prospero/, identifier CRD42023468651.

Pan-cancer landscape analysis of NOP58 and its oncogenic driving role in lung adenocarcinoma

Despite improvements in treatment in recent years, patients with lung adenocarcinoma (LUAD) still face poor prognoses. In this study, we elucidated the potential role of NOP58 ribonucleoprotein in pan-cancer and validated its oncogenic significance in LUAD using bioinformatics and in vitro and in vivo functional assays. NOP58 was found to be overexpressed in various types of tumors. It had great precision for predicting 20 distinct cancer types using receiver operating characteristic curve (ROC) as well as significant connections with the prognoses in particular cancers. In LUAD, NOP58 expression was correlated substantially with the TNM stage, pathologic stage, smoking status, and effectiveness endpoints, when we analyzed its association with clinical characteristics in LUAD. Elevated NOP58 expression was shown as connected with Th2 cell infiltration while also negatively linked with infiltrating other immune cells, such as CD8 T, cytotoxic, and Th1. By inhibiting NOP58 within the LUAD cells, we found a decrease in cells’ capability to proliferate, migrate, and invade. Knockdown of NOP58 inhibited tumor growth in mouse xenograft models. Furthermore, the tissue microarray study indicated that there was a greater expression of NOP58 in the tumor tissues compared to adjacent normal tissues in LUAD. Our findings revealed that NOP58 could be an outstanding bio-index for pan-cancer diagnosis and prognosis and an independent prognostic risk factor in LUAD.

Deep learning-based analysis of EGFR mutation prevalence in lung adenocarcinoma H&E whole slide images.

EGFR mutations are a major prognostic factor in lung adenocarcinoma. However, current detection methods require sufficient samples and are costly. Deep learning is promising for mutation prediction in histopathological image analysis but has limitations in that it does not sufficiently reflect tumor heterogeneity and lacks interpretability. In this study, we developed a deep learning model to predict the presence of EGFR mutations by analyzing histopathological patterns in whole slide images (WSIs). We also introduced the EGFR mutation prevalence (EMP) score, which quantifies EGFR prevalence in WSIs based on patch-level predictions, and evaluated its interpretability and utility. Our model estimates the probability of EGFR prevalence in each patch by partitioning the WSI based on multiple-instance learning and predicts the presence of EGFR mutations at the slide level. We utilized a patch-masking scheduler training strategy to enable the model to learn various histopathological patterns of EGFR. This study included 868 WSI samples from lung adenocarcinoma patients collected from three medical institutions: Hallym University Medical Center, Inha University Hospital, and Chungnam National University Hospital. For the test dataset, 197 WSIs were collected from Ajou University Medical Center to evaluate the presence of EGFR mutations. Our model demonstrated prediction performance with an area under the receiver operating characteristic curve of 0.7680 (0.7607-0.7720) and an area under the precision-recall curve of 0.8391 (0.8326-0.8430). The EMP score showed Spearman correlation coefficients of 0.4705 (p = 0.0087) for p.L858R and 0.5918 (p = 0.0037) for exon 19 deletions in 64 samples subjected to next-generation sequencing analysis. Additionally, high EMP scores were associated with papillary and acinar patterns (p = 0.0038 and p = 0.0255, respectively), whereas low EMP scores were associated with solid patterns (p = 0.0001). These results validate the reliability of our model and suggest that it can provide crucial information for rapid screening and treatment plans.

Bioinformatics analysis reveals SOD1 is a prognostic factor in lung adenocarcinoma.

Lung cancer is a major cause of cancer-related deaths worldwide. Unfortunately, non-small cell lung cancer (NSCLC) often lacks clear clinical symptoms and molecular markers for early diagnosis, which can hinder the initiation of timely treatments. In this study, we conducted an extensive bioinformatics analysis of copper-zinc superoxide dismutase (SOD1), a molecule linked to lung adenocarcinoma (LUAD) to enhance early detection and treatment approaches for this condition. A bioinformatics analysis was conducted using a dataset from The Cancer Genome Atlas (TCGA) database. Several analytical methods, such as a differential expression analysis, a Kaplan-Meier survival analysis, a clinicopathological analysis, an enrichment analysis, protein-protein interaction (PPI) network construction using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and an immunoreactivity analysis of SOD1 expression in LUAD using TIMER were employed. We further validated the expression of SOD1 in LUAD through in vitro experiments using quantitative polymerase chain reaction (qPCR) and Western blot. Our findings indicate that LUAD tissues exhibited significantly higher expression levels of SOD1 than healthy tissues. The univariate Cox analysis showed that the elevated level was linked to unfavorable overall survival (OS) rates. Further, the Cox regression analysis of multiple variables suggested that elevated SOD1 expression levels acted as an autonomous prognosticator for unfavorable OS. We also conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and a gene set enrichment analysis (GSEA) and observed differential pathway enrichment among patients with high SOD1 expression. In addition, a correlation between SOD1 and immune cell infiltration was found. The in vitro experiments confirmed that SOD1 expression was upregulated in LUAD. SOD1 could serve as a reliable prognostic indicator in individuals diagnosed with LUAD. Our findings may prove valuable in the development of therapeutic and prognostic markers for LUAD. The potential clinical utility of SOD1 in LUAD requires further investigation.

Prognostic model of lung adenocarcinoma based on immunoprognosis-related genes and related drug prediction.

Lung cancer (LC) is the most common malignant tumor in the world, and lung adenocarcinoma (LUAD) is the most common type of LC. Immune microenvironment plays a critical role in cancer from onset to relapse. We aimed to identify an effective immune-related prediction model for assessing prognosis and predicting the relevant tumor therapeutic drugs. According to the RNA sequencing data of LUAD transcriptome in The Cancer Genome Atlas (TCGA) database and the immune-related genes obtained from IMMPORT (The Immunology Database and Analysis Portal) database, immune prognosis-related genes were screened. Weighted gene co-expression network analysis (WGCNA) identified hub genes in differentially expressed immune-related genes (DEIRGs). Least absolute shrinkage and selection operator (LASSO) Cox and ten rounds of cross-validation were used to screen core genes to establish a prognostic model, and in situ hybridization was used to verify the expression of core genes in LUAD. Then the patients from the TCGA database were divided into high-risk group and low-risk group. The survival, tumor microenvironment (TME) and immune cell infiltration of different groups were further analyzed, and the differential genes between the two groups were analyzed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) enrichment analyses. Finally, the small molecular drugs that can inhibit the prognosis of LUAD were screened by Connectivity Map (CMAP), and the therapeutic mechanism of small molecular drug oxibendazole was verified by Cell Counting Kit-8 (CCK-8) experiment. A four-immunoprognosis-related gene model was established to forecast the overall survival (OS) of LUAD through LASSO Cox regression and ten rounds of cross-validation analysis. This prognostic model stratified LUAD patients into low-risk and high-risk groups. According to the findings of the survival analysis, the low-risk group had a greater OS than the high-risk group and the content of immune cells in LUAD was corrected with the survival prognosis of patients. Univariate and multivariate Cox regression also revealed that the prognostic model was an independent prognosis factor in LUAD. Five kinds of small molecular drugs which can inhibit the prognosis of LUAD were screened by CMAP. As shown by CCK-8 test, the small molecular drug "oxibendazole" can effectively inhibit the proliferation of LUAD cells. Based on immune-related prognostic genes, a new prognostic model for LUAD was constructed. Oxibendazole can inhibit the proliferation of LUAD cells, which provides a new idea for the treatment of LUAD.

MOSBY enables multi-omic inference and spatial biomarker discovery from whole slide images

The utility of deep neural nets has been demonstrated for mapping hematoxylin-and-eosin (H&E) stained image features to expression of individual genes. However, these models have not been employed to discover clinically relevant spatial biomarkers. Here we develop MOSBY (Multi-Omic translation of whole slide images for Spatial Biomarker discoverY) that leverages contrastive self-supervised pretraining to extract improved H&E whole slide images features, learns a mapping between image and bulk omic profiles (RNA, DNA, and protein), and utilizes tile-level information to discover spatial biomarkers. We validate MOSBY gene and gene set predictions with spatial transcriptomic and serially-sectioned CD8 IHC image data. We demonstrate that MOSBY-inferred colocalization features have survival-predictive power orthogonal to gene expression, and enable concordance indices highly competitive with survival-trained multimodal networks. We identify and validate (1) an ER stress-associated colocalization feature as a chemotherapy-specific risk factor in lung adenocarcinoma, and (2) the colocalization of T effector cell vs cysteine signatures as a negative prognostic factor in multiple cancer indications. The discovery of clinically relevant biologically interpretable spatial biomarkers showcases the utility of the model in unraveling novel insights in cancer biology as well as informing clinical decision-making.

Does Extraesophageal Reflux Support the Development of Lung Adenocarcinoma? Analysis of Pepsin in Bronchoalveolar Lavage in Non-Smoker Patients.

The significance of extraesophageal reflux as a risk factor in lung adenocarcinoma has been understudied. In this study, we investigated whether extraesophageal reflux leads to higher pepsin concentrations in bronchoalveolar lavage (BAL) in patients with lung adenocarcinoma compared to controls. Subjects were recruited from non-smoker patients (lifelong non-smokers and ex-smokers with more than 5 years of non-smoking history) who had undergone bronchoscopy due to pulmonary abnormalities on a CT scan and met the inclusion criteria. Based on histological verification of the lung process, the patients were divided into three groups: (1) lung adenocarcinoma, (2) pulmonary metastases, and (3) lung sarcoidosis. Lung adenocarcinoma cases were further categorized as central or peripheral. BAL samples collected during bronchoscopy were quantitatively analyzed by enzyme-linked immunosorbent assay (ELISA) to measure pepsin levels. No statistically significant difference in pepsin concentration was observed between the lung adenocarcinoma group and control groups (p = 0.135). After excluding hemorrhagic BAL samples, the pepsin concentration was significantly the lowest in patients with lung adenocarcinoma (p = 0.023) compared to the control groups. The results of the study do not support the hypothesis of a higher occurrence of extraesophageal reflux (evaluated as the amount of pepsin in BAL) in non-smoker patients with lung adenocarcinoma.

Identification and immunological characteristics of anoikis-associated molecular clusters in lung adenocarcinoma

Anoikis plays a crucial role in the progression, prognosis, and immune response of lung adenocarcinoma (LUAD). However, its specific impact on LUAD remains unclear. In this study, we investigated the intricate interplay of nesting apoptotic factors in LUAD. By analyzing nine key nesting apoptotic factors, we categorized LUAD patients into two distinct clusters. Further examination of immune cell profiles revealed that Cluster A exhibited greater infiltration of innate immune cells than did Cluster B. Additionally, we identified two genes closely associated with prognosis and developed a predictive model to differentiate patients based on molecular clusters. Our findings suggest that the loss of specific anoikis-related genes could significantly influence the prognosis, tumor microenvironment, and clinical features of LUAD patients. Furthermore, we validated the expression and functional roles of two pivotal prognostic genes, solute carrier family 2 member 1 (SLC2A1) and sphingosine kinase 1 (SPHK1), in regulating tumor cell viability, migration, apoptosis, and anoikis. These results offer valuable insights for future mechanistic investigations. In conclusion, this study provides new avenues for advancing our understanding of LUAD, improving prognostic assessments, and developing more effective immunotherapy strategies.

Prognostic effect of TCF1+ CD8+ T cell and TOX+ CD8+ T cell infiltration in lung adenocarcinoma.

Recent studies have highlighted the pivotal roles of T cell transcription factors TCF-1 and TOX in modulating the immune response in cancer, with TCF-1 maintaining CD8+ T cell stemness and TOX promoting T cell exhaustion. The prognostic significance of these factors in lung adenocarcinoma (LUAD) remains a critical area of investigation. The retrospective study included 191 patients with LUAD who underwent surgery, of whom 83% were in stages II and III. These patients were divided into exploratory (n = 135) and validation (n = 56) groups based on the time of diagnosis. Multiplex fluorescence immunohistochemistry was used to examine the infiltration levels of CD8+ T cells, TCF1+ CD8+ T cells, and TOX+ CD8+ T cells. The percentage of CD8+ T cells in tumor was markedly lower than that in stroma (p < 0.05). In tumor-draining lymph nodes (TDLNs) invaded by tumor, the proportion of stem-like TCF1+ CD8+ T cells was significantly decreased (p < 0.01). Importantly, higher infiltration levels of CD8+ T cells and TCF1+ CD8+ T cells were associated with improved disease-free survival (DFS) (p = 0.009 and p = 0.006, respectively) and overall survival (OS) (p = 0.018 and p = 0.010, respectively). This study underscores the potential of TCF1+ CD8+ T cells as prognostic biomarkers in LUAD, providing insights into the tumor immune microenvironment and guiding future therapeutic strategies.

GPX8+ cancer-associated fibroblast, as a cancer-promoting factor in lung adenocarcinoma, is related to the immunosuppressive microenvironment

BackgroundCancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment of lung adenocarcinoma (LUAD) and are often associated with poorer clinical outcomes. This study aimed to screen for CAF-specific genes that could serve as promising therapeutic targets for LUAD.MethodsWe established a single-cell transcriptional profile of LUAD, focusing on genetic changes in fibroblasts. Next, we identified key genes associated with fibroblasts through weighted gene co-expression network analysis (WGCNA) and univariate Cox analysis. Then, we evaluated the relationship between glutathione peroxidase 8 (GPX8) and clinical features in multiple independent LUAD cohorts. Furthermore, we analyzed immune infiltration to shed light on the relationship between GPX8 immune microenvironment remodeling. For clinical treatment, we used the tumor immune dysfunction and exclusion (TIDE) algorithm to assess the immunotherapy prediction efficiency of GPX8. After that, we screened potential therapeutic drugs for LUAD by the connectivity map (cMAP). Finally, we conducted a cell trajectory analysis of GPX8+ CAFs to show their unique function.ResultsFibroblasts were found to be enriched in tumor tissues. Then we identified GPX8 as a key gene associated with CAFs through comprehensive bioinformatics analysis. Further analysis across multiple LUAD cohorts demonstrated the relationship between GPX8 and poor prognosis. Additionally, we found that GPX8 played a role in inducing the formation of an immunosuppressive microenvironment. The TIDE method indicated that patients with low GPX8 expression were more likely to be responsive to immunotherapy. Using the cMAP, we identified beta-CCP as a potential drug-related to GPX8. Finally, cell trajectory analysis provided insights into the dynamic process of GPX8+ CAFs formation.ConclusionsThis study elucidates the association between GPX8+ CAFs and poor prognosis, as well as the induction of immunosuppressive formation in LUAD. These findings suggest that targeting GPX8+ CAFs could potentially serve as a therapeutic strategy for the treatment of LUAD.

UPP1 promotes lung adenocarcinoma progression through the induction of an immunosuppressive microenvironment

The complexity of the tumor microenvironment (TME) is a crucial factor in lung adenocarcinoma (LUAD) progression. To gain deeper insights into molecular mechanisms of LUAD, we perform an integrative single-cell RNA sequencing (scRNA-seq) data analysis of 377,574 cells from 117 LUAD patient samples. By linking scRNA-seq data with bulk gene expression data, we identify a cluster of prognostic-related UPP1high tumor cells. These cells, primarily situated at the invasive front of tumors, display a stronger association with the immunosuppressive components in the TME. Our cytokine array analysis reveals that the upregulation of UPP1 in tumor cells leads to the increased release of various immunosuppressive cytokines, with TGF-β1 being particularly prominent. Furthermore, this UPP1 upregulation also elevates the expression of PD-L1 through the PI3K/AKT/mTOR pathway, which contributes to the suppression of CD8 + T cells. Cytometry by time-of-flight (CyTOF) analysis provides additional evidence of the role of UPP1 in shaping the immunosuppressive nature of the TME. Using patient-derived organoids (PDOs), we discover that UPP1high tumors exhibit relatively increased sensitivity to Bosutinib and Dasatinib. Collectively, our study highlights the immunosuppressive role of UPP1 in LUAD, and these findings may provide insights into the molecular features of LUAD and facilitate the development of personalized treatment strategies.

Retraction: Long noncoding RNA TUG1 is a diagnostic factor in lung adenocarcinoma and suppresses apoptosis via epigenetic silencing of BAX.

Retraction: Long noncoding RNA TUG1 is a diagnostic factor in lung adenocarcinoma and suppresses apoptosis via epigenetic silencing of BAX.

DLX1 acts as a novel prognostic biomarker involved in immune cell infiltration and tumor progression in lung adenocarcinoma.

The biological function of distal-less homeobox 1 (DLX1) in lung adenocarcinoma (LUAD) remains unclear, despite a growing body of evidence that DLX1 is involved in the initiation and progression of various tumors. This study explored and confirmed the prognostic and immunologic roles of DLX1 in LUAD via bioinformatic analysis and cellular functional validation. MethSurv was used to analyze the DNA methylation levels of DLX1 and the prognostic value of CpG islands. DLX1 mutation rates and prognoses between patients with and without the mutated DLX1 gene were analyzed by cBioPortal. Finally, cellular functional assays were used to investigate the effect of DLX1 on LUAD cells. Our results showed that DLX1 mRNA expression was significantly upregulated in LUAD. High DLX1 expression or promoter methylation was associated with worse prognosis, which confirmed DLX1 as an independent prognostic factor in LUAD. The level of multiple immune cell infiltration was significantly associated with DLX1 expression. Genes in the high DLX1 expression group were mainly enriched in cell cycle checkpoint, DNA replication, DNA repair, Fceri-mediated MAPK activation, TP53 activity regulation, and MET activation of PTK2-regulated signaling pathways. Cellular functional assays showed that the knockdown of DLX1 inhibited the proliferation, migration, and invasion of LUAD cells. Our study identified DLX1 as a potential diagnostic and prognostic biomarker, and a promising therapeutic target in LUAD.

High expression of VTA1 is an adverse prognostic factor in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a common pathological type of non-small cell lung cancer; identifying preferable biomarkers has become one of the current challenges. Given that VTA1 has been reported associated with tumor progression in various human solid cancers but rarely reported in LUAD, herein, RNA sequencing data from TCGA and GTEx were obtained for analysis of VTA1 expression and differentially expressed gene (DEG). Furthermore, functional enrichment analysis of VTA1-related DEGs was performed by GO/KEGG, GSEA, immune cell infiltration analysis, and protein-protein interaction (PPI) network. In addition, the clinical significance of VTA1 in LUAD was figured out by Kaplan-Meier Cox regression and prognostic nomogram model. R package was used to analyze incorporated studies. As a result, VTA1 was highly expressed in various malignancies, including LUAD, compared with normal samples. Moreover, high expression of VTA1 was associated with poor prognosis in 533 LUAD samples, as well as T stage T2&T3&T4, N stage N1&N2&N3, M stage M1, pathologic stage II&III&IV, and residual tumor R1&R2, et al. (P < 0.05). High VTA1 was an independent prognostic factor in Cox regression analysis; Age and cytogenetics risk were included in the nomogram prognostic model. Furthermore, a total of 4232 DEGs were identified between the high- and the low-expression group, of which 736 genes were up-regulated and 3496 genes were down-regulated. Collectively, high expression of VTA1 is a potential biomarker for adverse outcomes in LUAD. The DEGs and pathways recognized in the study provide a preliminary grasp of the underlying molecular mechanisms of LUAD carcinogenesis and progression.

DCAF13 inhibits the p53 signaling pathway by promoting p53 ubiquitination modification in lung adenocarcinoma

BackgroundLung cancer is a malignant tumor with the highest mortality worldwide. Abnormalities in the ubiquitin proteasome system are considered to be contributed to lung cancer progression with deleterious effects. DDB1 and CUL4 associated factor 13 (DCAF13) is a substrate receptor of the E3 ubiquitin ligase CRL4, but its role in lung cancer remains unknown. In this study, we aimed to investigate the regulatory mechanisms of DCAF13 in lung adenocarcinoma (LUAD).MethodsSo as to investigate the effect of DCAF13 on lung adenocarcinoma cell function using in vivo and in vitro. Mechanistically, we have identified the downstream targets of DCAF13 by using RNA-sequencing, as well as ubiquitination assays, co-immunoprecipitation, immunofluorescence, immunohistochemistry and chromatin immunoprecipitation - qPCR experiments.ResultsOur findings reveal that DCAF13 is a carcinogenic factor in LUAD, as it is highly expressed and negatively correlated with clinical outcomes in LUAD patients. Through RNA-sequencing, it has been shown that DCAF13 negatively regulates the p53 signaling pathway and inhibits p53 downstream targets including p21, BAX, FAS, and PIDD1. We also demonstrate that DCAF13 can bind to p53 protein, leading to K48-linked ubiquitination and degradation of p53. Functionally, we have shown that DCAF13 knockdown inhibits cell proliferation and migration. Our results highlight the significant role of DCAF13 in promoting LUAD progression by inhibiting p53 protein stabilization and the p53 signaling pathway. Furthermore, our findings suggest that high DCAF13 expression is a poor prognostic indicator in LUAD, and DCAF13 may be a potential therapeutic target for treating with this aggressive cancer.ConclusionsThe DCAF13 as a novel negative regulator of p53 to promote LUAD progression via facilitating p53 ubiquitination and degradation, suggesting that DCAF13 might be a novel biomarker and therapeutical target for LUAD.

Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort.

The programmed cell death (PCD) plays a key role in the development and progression of lung adenocarcinoma. In addition, immune-related genes also play a crucial role in cancer progression and patient prognosis. However, further studies are needed to investigate the prognostic significance of the interaction between immune-related genes and cell death in LUAD. In this study, 10 clustering algorithms were applied to perform molecular typing based on cell death-related genes, immune-related genes, methylation data and somatic mutation data. And a powerful computational framework was used to investigate the relationship between immune genes and cell death patterns in LUAD patients. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations, and we constructed an immune-associated programmed cell death model (PIGRS) using the machine learning model that exhibited the best performance. Finally, based on a series of in vitro experiments used to explore the role of PSME3 in LUAD. We used 10 clustering algorithms and multi-omics data to categorize TCGA-LUAD patients into three subtypes. patients with the CS3 subtype had the best prognosis, whereas patients with the CS1 and CS2 subtypes had a poorer prognosis. PIGRS, a combination of 15 high-impact genes, showed strong prognostic performance for LUAD patients. PIGRS has a very strong prognostic efficacy compared to our collection. In conclusion, we found that PSME3 has been little studied in lung adenocarcinoma and may be a novel prognostic factor in lung adenocarcinoma. Three LUAD subtypes with different molecular features and clinical significance were successfully identified by bioinformatic analysis, and PIGRS was constructed using a powerful machine learning framework. and investigated PSME3, which may affect apoptosis in lung adenocarcinoma cells through the PI3K/AKT/Bcl-2 signaling pathway.

MiR-940 modulates CD47 to suppress biological functions of lung adenocarcinoma cells.

mir-940 and CD47 play regulatory and immunoregulatory roles in lung cancer. While previous study found that the expression of mir-940 decreased, associated with the increasing of CD47 in lung adenocarcinoma. However, their inherent correlations remain elusive. Herein, this experiment intends to search for the relevant molecular mechanisms regulating the biological function of non-small cell lung cancer. The cancer and adjacent tissue samples were collected from 20 pairs of newly diagnosed non-small cell lung cancer patients without applying radiotherapy and chemotherapy. We performed immunohistochemistry containing 45 lung adenocarcinoma tissues to investigate the relationship between the clinicopathological features and CD47 expression. The expressions of mir-940 and CD47 were detected by real-time quantitative polymerase chain reaction (qRT-PCR). Lung epithelial and lung adenocarcinoma (A549, H1299, GLC-82, PC-9) cell lines were cultured to detect the expression of mir-940 and CD47 molecules in each cell line. According to the expression situation, 2 cell lines were selected for mimic and siRNA transfection, and the transfection efficiency was also verified by qRT-PCR and western blot. CCK-8, transwell migration, transwell invasion, and colony formation assays were used to detect the changes in biological functions of lung adenocarcinoma cells after transfection, such as enhanced proliferation, migration, invasion, and cloning. The changes of related protein molecules after transfection were detected by western blot. The dual-luciferase experiment verified the targeting regulation relationship between mir-940 and CD47. Finally, flow cytometry analysis of apoptosis and cell cycle were carried out to detect apoptosis cells and change phase of cell cycle distribution. CD47 expression was not associated with clinicopathologic factors in lung adenocarcinoma. The proliferation, migration, invasion, and cloning abilities of lung adenocarcinoma cells were weakened after transfection with mir-940 mimic and siRNA-CD47. Overexpression of CD47 could promote proliferation, migration, invasion, cloning abilities, reduce apoptosis rate and attenuate the antitumor effect of mir-940 on lung adenocarcinoma. Dual luciferase experiments confirmed that mir-940 can target CD47 molecules. mir-940 can inhibit the biological function of lung adenocarcinoma cells by targeting CD47.

Characterization and verification of CD81 as a potential target in lung squamous cell carcinoma

CD81 is a cell surface transmembrane protein of the tetraspanin family, which critically regulates signal transduction and immune response. Growing evidence has shown that CD81 plays important roles in tumorigenesis and influences immunotherapy response. Here, combining bio-informatics and functional analysis, we find that CD81 is a risk factor in lung squamous cell carcinoma (LUSC), whereas a protective factor in lung adenocarcinoma. In LUSC with high expression of CD81, the autophagy and JAK-STAT signaling pathway are activated. Meanwhile, the expression level of CD81 is negatively correlated with tumor mutational load (TMB), microsatellite instability (MSI), and neoantigen (NEO). Furthermore, patients with LUSC and high expression of CD81 do not respond to immunotherapy drugs, but can respond to chemotherapy drugs. Importantly, depletion of CD81 suppresses the proliferation of LUSC cell, and enhances the sensitivity to cisplatin. Our findings suggest that CD81 represents a potential target for cisplatin-based chemotherapy in patients with LUSC.

Identification of metabolism-related gene signature in lung adenocarcinoma.

Lung cancer is one of the most common cancers in China and has a high mortality rate. Most patients who are diagnosed have lost the opportunity to undergo surgery. Aberrant metabolism is closely associated with tumorigenesis. We aimed to identify an effective metabolism-related prediction model for assessing prognosis based on the cancer genome atlas (TCGA) and GSE116959 databases. TCGA and GSE116959 datasets from Gene Expression Omnibus were used to obtain lung adenocarcinoma (LUAD) data. Additionally, we captured metabolism-related genes (MRGs) from the GeneCards database. First, we extracted differentially expressed genes using R to analyze the LUAD data. We then selected the same differentially expressed genes, including 168 downregulated and 77 upregulated genes. Finally, 218 differentially expressed MRGs (DEMRGs) were included to perform functional enrichment analysis and construct a protein-protein interaction network with the help of Cytoscape and Search Tool for the Retrieval of Interacting Genes database. Cytoscape was used to visualize the intensive intervals in the network. Then univariate and Least Absolute Shrinkage and Selection Operator Cox regression analyses, which assisted in identifying the overall survival (OS)-related DEMRGs and building a 10-DEMRG prognosis model, were performed. The prognostic values, tumor immunity relevance, and molecular mechanism were further investigated. A nomogram incorporating signature, age, gender, and TNM stage was established. A 10-DEMRG model was established to forecast the OS of LUAD through Least Absolute Shrinkage and Selection Operator regression analysis. This prognostic signature stratified LUAD patients into low-risk and high-risk groups. The receiver operating characteristic curve and K-M analysis indicated good performance of the DEMRGs signature at predicting OS in the TCGA dataset. Univariate and multivariate Cox regression also revealed that the DEMRGs signature was an independent prognosis factor in LUAD. We noticed that the risk score was substantially related to the clinical parameters of LUAD patients, covering age and stage. Immune analysis results showed that risk score was associated with some immune cells and immune checkpoints. Nomogram also verified the clinical value of the DEMRGs signature. In this study, we constructed a DEMRGs signature and established a prognostic nomogram that is robust and reliable to predict OS in LUAD. Overall, the findings could help with therapeutic customization and personalized therapies.