Immune Resistance in Lung Adenocarcinoma

Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis is a newly discovered mechanism of programmed cell death. However, the effects of disulfidptosis-related lncRNAs (DR-lncRNAs) in LUAD have yet to be fully elucidated. The aim of the present study was to identify and validate a novel lncRNA-based prognostic marker that was associated with disulfidptosis. RNA-sequencing and associated clinical data were obtained from The Cancer Genome Atlas database. Univariate Cox regression and lasso algorithm analyses were used to identify DR-lncRNAs and to establish a prognostic model. Kaplan-Meier curves, receiver operating characteristic curves, principal component analysis, Cox regression, nomograms and calibration curves were used to assess the reliability of the prognostic model. Functional enrichment analysis, immune infiltration analysis, somatic mutation analysis, tumor microenvironment and drug predictions were applied to the risk model. Reverse transcription-quantitative PCR was subsequently performed to validate the mRNA expression levels of the lncRNAs in normal cells and tumor cells. These analyses enabled a DR-lncRNA prognosis signature to be constructed, consisting of nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO-AS1, TDRKH-AS1, AL157895.1, AL512363.1, AC010615.2 and GCC2-AS1. This risk model could serve as an independent prognostic tool for patients with LUAD. Numerous immune evaluation algorithms indicated that the low-risk group may exhibit a more robust and active immune response against the tumor. Moreover, the tumor immune dysfunction exclusion algorithm suggested that immunotherapy would be more effective in patients in the low-risk group. The drug-sensitivity results showed that patients in the high-risk group were more sensitive to treatment with crizotinib, erlotinib or savolitinib. Finally, the expression levels of AL157895.1 were found to be lower in A549. In summary, a novel DR-lncRNA signature was constructed, which provided a new index to predict the efficacy of therapeutic interventions and the prognosis of patients with LUAD.

Enzymatic response of heparin-protamine complex: Spectroscopic investigation and application for lung adenocarcinoma cells detection

Though the heparin-protamine complex (HP complex) is a crucial system utilized in clinical settings, the metabolic pathways of this complex remain inadequately understood. Herein, the enzymatic degradation of the heparin-protamine complex by trypsin and its broader implications were investigated. By utilizing fluorescent gold nanoclusters liganded with the HP complex (AuNCs-HP complex), we observed significant morphological and spectral changes during enzymatic degradation. Experiments showed that AuNCs-HP complex could be degraded and cleaved into small fragments by trypsin. Moreover, the AuNCs-HP complex demonstrated its potential as a highly sensitive spectral sensing platform, enabling precise measurement of trypsin activity with an outstanding detection limit (0.34 ng mL-1). Additionally, we explored its utility for specific tumor cell detection, focusing on lung adenocarcinoma cells, and successfully identified their presence through distinctive fluorescence changes. These remarkable findings not only contribute valuable insights into targeted degradation systems but also offer promising opportunities for cancer biomarker detection. The AuNCs-HP complex serves as an innovative tool for real-time trypsin activity monitoring, paving the way for advanced biomedical applications.

Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma

Lung cancer is a major cause accounting for cancer-related mortalities, with lung adenocarcinoma (LUAD) being the most prevalent subtype. Given the high clinical and cellular heterogeneities of LUAD, accurate diagnosis and prognosis are crucial to avoid overdiagnosis and overtreatment. Taking full advantage of scRNA-Seq data to resolve the tumor heterogeneities, we explored the overall landscape of LUAD microenvironment. Utilizing the stage-specific tumor cell markers, we have developed highly accurate diagnostic and prognostic models with elevated sensitivity and specificity. The diagnostic model, developed through random forest algorithms with a thirteen-gene signature, achieved an accuracy of 96.4% and an AUC of 0.993. These metrics were further demonstrated by benchmarking with available models and scoring systems in independent cohorts. Concurrently, the prognostic model, formulated via Cox regression with a six-gene signature, effectively predicted overall survival, with elevated risk scores associated with increased fractions of cancer-associated fibroblasts, and higher likelihood of immune escape and T-cell exclusion. Subsequently, two nomograms were developed to predict survival and drug responses, facilitating their integration into clinical practice. Overall, this study underscores the potential of our models for efficient, rapid, and cost-effective diagnosis and prognosis of LUAD, adaptable to multiple expression profiling platforms and quantification methods.

KIS, a target of SOX4, regulates the ID1-mediated enhancement of β-catenin to facilitate lung adenocarcinoma cell proliferation and metastasis

PURPOSE

Kinase interacting with stathmin (KIS) is a serine/threonine kinase involved in RNA processing and protein phosphorylation. Increasing evidence has suggested its involvement in cancer progression. The aim of this study was to investigate the role of KIS in the development of lung adenocarcinoma (LUAD). Dual luciferase assay was used to explore the relationship between KIS and SOX4, and its effect on ID1/β-catenin pathway.

METHODS

Real-time qPCR and western blot were used to assess the levels of KIS and other factors. Cell proliferation, migration, and invasion were monitored, and xenograft animal model were established to investigate the biological functions of KIS in vitro and in vivo.

RESULTS

In the present study, KIS was found to be highly expressed in LUAD tissues and cell lines. KIS accelerated the proliferative, migratory and invasive abilities of LUAD cells in vitro, and promoted the growth of LUAD in a mouse tumor xenograft model in vivo. Mechanistically, KIS activated the β-catenin signaling pathway by modulating the inhibitor of DNA binding 1 (ID1) and was transcriptionally regulated by SOX4 in LUAD cells.

CONCLUSION

KIS, a target of SOX4, regulates the ID1-mediated enhancement of β-catenin to facilitate LUAD cell invasion and metastasis.

A novel cancer-associated fibroblasts risk score model predict survival and immunotherapy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. Cancer-associated fibroblasts (CAFs) are a special type of fibroblasts, which play an important role in the development and immune escape of tumors. Weighted gene co-expression network analysis (WGCNA) was used to construct the co-expression module. In combination with univariate Cox regression and analysis of least absolute shrinkage operator (LASSO), characteristics associated with CAFs were developed for a prognostic model. The migration and proliferation of lung cancer cells were evaluated in vitro. Finally, the expression levels of proteins were analyzed by Western blot. LASSO Cox regression algorithm was then performed to select hub genes. Finally, a total of 2 Genes (COL5A2, COL6A2) were obtained. We then divided LUAD patients into high- and low-risk groups based on CAFs risk scores. Survival analysis, CAFs score correlation analysis and tumor mutation load analysis showed that COL5A2 and COL6A2 were high-risk genes for LUAD. Human Protein Atlas (HPA), western blot and PCR results showed that COL5A2 and COL6A2 were up-regulated in LUAD tissues. When COL5A2 and COL6A2 were knocked down, the proliferation, invasion and migration of lung cancer cells were significantly decreased. Finally, COL5A2 can affect LUAD progression through the Wnt/β-Catenin and TGF-β signaling pathways. Our CAFs risk score model offers a new approach for predicting the prognosis of LUAD patients. Furthermore, the identification of high-risk genes COL5A2 and COL6A2 and drug sensitivity analysis can provide valuable candidate clues for clinical treatment of LUAD.

New link between RNH1 and E2F1: regulates the development of lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a non-small cell carcinoma. Ribonuclease/angiogenin inhibitor 1 (RNH1) exerts multiple roles in virous cancers. E2F1 is a critical transcription factor involved in the LUAD development. Here, we analyze the expression of RNH1 in LUAD patients, investigate the biological function of RNH1 in LUAD, and demonstrate its potential mechanisms through E2F1 in LUAD.

METHODS

In the present study, we presented the expression of RNH1 in LUAD based on the database and confirmed it by western blot detection of RNH1 in human LUAD tissues. Lentiviral infection was constructed to silence or overexpress RNH1 in NCI-H1395 and NCI-H1437 cells. We assess the role of RNH1 on proliferation in LUAD cells by MTT assay, colony formation assays, and cell cycle detection. Hoechst staining and flow cytometry were used to evaluate the effects of RNH1 on apoptosis of LUAD cells. The function of RNH1 in invasion and migration was investigated by Transwell assay. Dual luciferase assay, ChIP detection, and pull-down assay were conducted to explore the association of E2F1 in the maintenance of RNH1 expression and function. The regulation of E2F1 on the functions of RNH1 in LUAD cells was explored. Mouse experiments were performed to confirm the in-vivo role of RNH1 in LUAD. mRNA sequencing indicated that RNH1 overexpression altered the expression profile of LUAD cells.

RESULTS

RNH1 expression in LUAD tissues of patients was presented in this work. Importantly, RNH1 knockdown improved the proliferation, migration and invasion abilities of cells and RNH1 overexpression produced the opposite effects. Dual luciferase assay proved that E2F1 bound to the RNH1 promoter (-1064 ∼ -1054, -1514 ∼ -1504) to reduce the transcriptional activity of RNH1. ChIP assay indicated that E2F1 DNA was enriched at the RNH1 promoter (-1148 ∼ -943, -1628 ∼ -1423). Pull-down assays also showed the association between E2F1 and RNH1 promoter (-1148 ∼ -943). E2F1 overexpression contributed to the malignant behavior of LUAD cells, while RNH1 overexpression reversed it. High-throughput sequencing showed that RNH1 overexpression induced multiple genes expression changes, thereby modulating LUAD-related processes.

CONCLUSION

Our study demonstrates that binding of E2F1 to the RNH1 promoter may lead to inhibition of RNH1 expression and thus promoting the development of LUAD.

Inflammation-based lung adenocarcinoma molecular subtype identification and construction of an inflammation-related signature with bulk and single-cell RNA-seq data

The role of inflammation is increasingly understood to have a central influence on therapeutic outcomes and prognosis in lung adenocarcinoma (LUAD). However, the detailed molecular divisions involved in inflammatory responses are yet to be fully elucidated. Our study identified two main inflammation-oriented LUAD grades: the inflammation-low (INF-low) and the inflammation-high (INF-high) subtypes. Both presented with unique clinicopathological features, implications for prognosis, and distinctive tumor microenvironment profiles. Broadly, the INF-low grade, marked by its dominant immunosuppressive tumor microenvironment, was accompanied by less favorable prognostic outcomes and a heightened prevalence of oncogenic mutations. In contrast, the INF-high grade exhibited more optimistic clinical trajectories, underscored by its immune-active environment. In addition, our efforts led to the conceptualization and empirical validation of an inflammation-centric predictive model with considerable predictive potency. Our study paves the way for a refined inflammation-centric LUAD classification and fosters a deeper understanding of tumor microenvironment intricacies.

Up-regulated ORC1 promotes lung adenocarcinoma by inhibiting ferroptosis via SLC7A11 dependent pathway

Background

Lung adenocarcinoma (LUAD) is a pulmonary malignant disease that poses a high risk of mortality and morbidity. Previous study indicated that ORC1 plays an oncogenic function. However, the precise regulatory function that ORC1 serves in the progression of LUAD is still not clearly known.

Methods

Bioinformatics analyses were performed using TCGA and GEO datasets. The human LUAD cell line NCIH1355, NCIH1568 as well as BEAS-2B cell line (human normal lung epithelial cell) were utilized for in vitro study. LUAD cell proliferation were determined via CCK-8 assays and RT-qPCR for ki-67. The relation of ORC1 and SLC7A11 was detected by Western blot and qPCR with or without sh-RNA. The expression level ACSL4, the biomarker of ferroptosis, were detected using RT-qPCR.

Results

ORC1 and SLC7A11 exhibit high expression levels in both LUAD patients and cell lines, and are strongly associated with poor prognosis. In vitro experiments demonstrate that ORC1 and SLC7A11 promote proliferation of LUAD cell lines while inhibiting gefitinib-induced ferroptosis. Additionally, the function of ORC1 in LUAD cells is dependent on SLC7A11.

Conclusion

ORC1 promotes LUAD cell proliferation and inhibits ferroptosis in a SLC7A11-dependent manner. This implies that ORC1 could potentially serve as a useful diagnosis biomarker and treatment target.

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.

Comprehensive molecular analyses of cuproptosis-related genes with regard to prognosis, immune landscape, and response to immune checkpoint blockers in lung adenocarcinoma

BACKGROUND

Recent studies have emphasized the importance of the biological processes of different forms of cell death in tumor heterogeneity and anti-tumor immunity. Nonetheless, the relationship between cuproptosis and lung adenocarcinoma (LUAD) remains largely unexplored.

METHODS

Data for 793 LUAD samples and 59 normal lung tissues obtained from TCGA-LUAD cohort GEO datasets were used in this study. A total of 165 LUAD tissue samples and paired normal lung tissue samples obtained from our hospital were used to verify the prognostic value of dihydrolipoamide S-acetyltransferase (DLAT) and dihydrolipoamide branched chain transacylase E2 (DBT) for LUAD. The cuproptosis-related molecular patterns of LUAD were identified using consensus molecular clustering. Recursive feature elimination with random forest and a tenfold cross-validation method was applied to construct the cuproptosis score (CPS) for LUAD.

RESULTS

Bioinformatic and immunohistochemistry (IHC) analyses revealed that 13 core genes of cuproptosis were all significantly elevated in LUAD tissues, among which DBT and DLAT were associated with poor prognosis (DLAT, HR = 6.103; DBT, HR = 4.985). Based on the expression pattern of the 13 genes, two distinct cuproptosis-related patterns have been observed in LUAD: cluster 2 which has a relatively higher level of cuproptosis was characterized by immunological ignorance; conversely, cluster 1 which has a relatively lower level of cuproptosis is characterized by TILs infiltration and anti-tumor response. Finally, a scoring scheme termed the CPS was established to quantify the cuproptosis-related pattern and predict the prognosis and the response to immune checkpoint blockers of each individual patient with LUAD.

CONCLUSION

Cuproptosis was found to influence tumor microenvironment (TME) characteristics and heterogeneity in LUAD. Patients with a lower CPS had a relatively better prognosis, more abundant immune infiltration in the TME, and an enhanced response to immune checkpoint inhibitors.

TFAP2A Upregulates SKA3 to Promote Glycolysis and Reduce the Sensitivity of Lung Adenocarcinoma Cells to Cisplatin

INTRODUCTION

Studies have shown that glycolysis metabolism affects the resistance or sensitivity of tumors to chemotherapy drugs. Emerging from recent research, a paradigm-shifting revelation has unfolded, elucidating the oncogenic nature of SKA3 within the context of lung adenocarcinoma (LUAD). Consequently, this work was designed to delve into the effects of SKA3 on glycolysis and cisplatin (CDDP) resistance in LUAD cells and to find new possibilities for individualized treatment of LUAD.

METHODS

LUAD mRNA expression data from the TCGA database were procured to scrutinize the differential expression patterns of SKA3 in both tumor and normal tissues. GSEA and Pearson correlation analyses were employed to elucidate the impact of SKA3 on signaling pathways within the context of LUAD. In order to discern the upstream regulatory mechanisms, the ChEA and JASPAR databases were utilized to predict the transcription factors and binding sites associated with SKA3. qRT-PCR and Western blot were implemented to assay the mRNA and protein expression levels of SKA3 and TFAP2A. Chromatin immunoprecipitation and dual-luciferase assays were performed to solidify the binding relationship between the two. Extracellular acidification rate, glucose consumption, lactate production, and glycolysis-related proteins (HK2, GLUT1, and LDHA) were used to evaluate the level of glycolysis. Cell viability under CDDP treatment was determined utilizing the CCK-8, allowing for the calculation of IC50. The expression levels of SKA3 and TFAP2A proteins were detected by immunohistochemistry (IHC).

RESULTS

SKA3 exhibited upregulation in LUAD tissues and cell lines, establishing a direct linkage with glycolysis pathway. Overexpression of SKA3 fostered glycolysis in LUAD, resulting in reduced sensitivity toward CDDP treatment. The upstream transcription factor of SKA3, TFAP2A, was also upregulated in LUAD and could promote SKA3 transcription. Overexpression of TFAP2A also fostered the glycolysis of LUAD. Rescue assays showed that TFAP2A promoted glycolysis in LUAD cells by activating SKA3, reducing the sensitivity of LUAD cells to CDDP. The IHC analysis revealed a positive correlation between high expression of SKA3 and TFAP2A and CDDP resistance.

CONCLUSION

In summary, TFAP2A can transcriptionally activate SKA3, promote glycolysis in LUAD, and protect LUAD cells from CDDP treatment, indicating that targeting the TFAP2A/SKA3 axis may become a plausible and pragmatic therapeutic strategy for the clinical governance of LUAD.

Comprehensive analysis of lung adenocarcinoma: Unveiling differential gene expression, survival-linked genes, subtype stratification, and immune landscape implications

This study offers a detailed exploration of lung adenocarcinoma (LUAD), addressing its heterogeneity and treatment challenges through a multi-faceted analysis that includes gene expression, genetic subtyping, pathway analysis, immune assessment, and drug sensitivity. It identifies 165 genes with significant expression differences and 46 genes associated with survival, revealing insights into oxidative stress and autophagy. LUAD samples were divided into three subtypes using consensus clustering on these 46 genes, with distinct survival outcomes. Gene Set Enrichment Analysis (GSEA) on HALLMARK gene sets indicated pathway variations with survival implications. The immune landscape, analyzed using the CIBERSORT algorithm, showed different immune cell distributions across subtypes, with the first subtype exhibiting a better immune environment and survival prospects. Advanced machine learning techniques developed a risk model from a set of four genes, effectively categorizing patients into high and low-risk groups, validated through external datasets and analyses. This model linked lower risk scores to better clinical stages, with a higher mutation rate and potential immunotherapy benefits observed in the high-risk group. Drug sensitivity assessments highlighted varied treatment responses between risk groups, suggesting avenues for personalized therapy. This comprehensive analysis enhances the understanding of LUAD's molecular and clinical nuances, offering valuable insights for tailored treatment approaches.

Prognostic and onco-immunological value of immune-related eRNAs-driven genes in lung adenocarcinoma

BACKGROUND

We aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease.

MATERIALS AND METHODS

Pearson's correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.

RESULTS

Five immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.

CONCLUSION

Above all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.

Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing

Tumor immune microenvironment (TIME) and its indications for lung cancer patient prognosis and therapeutic response have become new hotspots in cancer research in recent years. Tumor cells, immune cells, various regulatory factors, and their interactions in the TIME have been suggested to commonly influence lung cancer development and therapeutic outcome. The heterogeneity of TIME is composed of dynamic immune-related components, including various cancer cells, immune cells, cytokine/chemokine environments, cytotoxic activity, or immunosuppressive factors. The specific composition of cell subtypes may facilitate or hamper the response to immunotherapy and influence patient prognosis. Various markers have been found to stratify the patient prognosis or predict the therapeutic outcome. In this article, we systematically reviewed the recent advancement of TIME studies in lung adenocarcinoma (LUAD) using single-cell RNA sequencing (scRNA-seq) techniques, with specific focuses on the roles of TIME in LUAD development, TIME heterogeneity, indications of TIME in patient prognosis and therapeutic response during immunotherapy and drug resistance. The main findings in TIME heterogeneity and relevant markers or models for prognosis stratification and response prediction have been summarized. We hope that this review provides an overview of TIME status in LUAD and an inspiration for future development of strategies and biomarkers in LUAD treatment.

Advancing predictive markers in lung adenocarcinoma: A machine learning-based immunotherapy prognostic prediction signature

The prognosis of lung adenocarcinoma (LUAD) is generally poor. Immunotherapy has emerged as a promising therapeutic modality, demonstrating remarkable potential for substantially prolonging the overall survival of individuals afflicted with LUAD. However, there is currently a lack of reliable signatures for identifying patients who would benefit from immunotherapy. We conducted a comparative analysis of two immunotherapy cohorts (OAK and POPLAR) and utilized single-factor COX regression to identify genes that significantly impact the prognosis of LUAD. Based on the TCGA-LUAD dataset, we employed a combination of 101 machine learning algorithms to construct a model and selected the optimal model. The model was validated on five GEO datasets and compared with 144 previously published signatures to assess its performance. Subsequently, we explored the underlying biological mechanisms through tumor mutation burden analysis, enrichment analysis, and immune infiltration analysis. An immunotherapy prognostic prediction signature (IPPS) was constructed based on 13 genes, showing robust performance in the TCGA-LUAD dataset. IPPS exhibited consistent predictive accuracy in the validation cohorts. Compared to 144 previously published signatures, IPPS consistently ranked among the top in terms of C-index values. Further exploration revealed differences between high and low-IPPS groups in terms of tumor mutation burden, pathway enrichment, and immune infiltration. IPPS demonstrates strong predictive capabilities for the prognosis of LUAD patients, offering the potential to identify suitable candidates for immunotherapy and contribute to precision treatment strategies for LUAD.

NKX2-1-AS1 promotes the lymphangiogenesis of lung adenocarcinoma through regulation of ERG-mediated FABP4

Lymphatic metastasis is a common metastasis of lung adenocarcinoma (LUAD). The current study illustrated the action of lncRNA NKX2-1-AS1 in lymphangiogenesis in LUAD and the underlying mechanisms. Clinical tissue samples were collected for determining NKX2-1-AS1 expression. Then, H441 and H661 cells were selected to perform gain- and loss-of-function assays for dissecting the roles of NKX2-1-AS1 in LUAD cell proliferation and migration. Besides, H441 and H661 cell supernatant was harvested to stimulate HLECs for assessing tube formation ability. Interaction among NKX2-1-AS1, ERG, and fatty acid binding protein 4 (FABP4) was validated through luciferase and RIP assays. NKX2-1-AS1 was highly-expressed in LUAD tissues. Silencing NKX2-1-AS1 suppressed H441 and H661 cell proliferation and migration, reduced expression levels of lymphangiogenesis-related factors (LYVE-1, VEGF-C, VEGFR3, VEGF-A, VEGFR2, and CCR7), and inhibited HLEC tube formation. Interaction validation demonstrated that NKX2-1-AS1 regulated FABP4 transcription by binding to ERG. Overexpression of FABP4 could effectively block the inhibition role of NKX2-1-AS1 silencing in lymphangiogenesis in H441 and H661 cells. This study provided evidence that NKX2-1-AS1 regulated FABP4 transcription by binding to ERG to facilitate the proliferation and migration of LUAD cells and tube formation of HLECs, thus participating in lymphangiogenesis.

Prognostic and immunological implications of paraptosis-related genes in lung adenocarcinoma: Comprehensive analysis and functional verification of hub gene

BACKGROUND

Lung adenocarcinoma (LUAD) poses significant clinical challenges due to its inherent heterogeneity and variable response to treatment. Recent research has specifically focused on elucidating the role of Paraptosis-related genes (PRGs) in the progression of cancer and the prognosis of patients.

METHODS

We conducted a comprehensive analysis of the differential expression of PRGs in LUAD. Additionally, univariate Cox regression analysis was utilized to determine the prognostic significance of these genes. Furthermore, consensus clustering was employed to differentiate molecular subtypes within LUAD, while immune heterogeneity was assessed. To evaluate treatment outcomes, the expression of immune checkpoint inhibitors was examined, and the sensitivity of LUAD patients to chemotherapy drugs was assessed. Moreover, machine learning algorithms were employed to construct a Paraptosis-related risk score with prognostic and immunological indicators. Finally, to validate the findings, in vitro experiments were performed to verify the regulatory effect of key PRGs on Paraptosis.

RESULTS

Our analysis identified 24 PRGs that exhibited differential expression, with CDKN3, TP53, and PHB emerging as the most prominently upregulated genes in tumor tissues. Among these genes, seven were identified as prognostic markers, with HSPB8 being the sole protective factor. Notably, our analysis also revealed the existence of two distinct molecular subtypes within LUAD, each characterized by unique prognoses and immune responses. Specifically, Subtype B displayed a poorer prognosis but demonstrated increased sensitivity to both chemotherapy and immunotherapy. In addition, our development of a Paraptosis-Associated Risk Score yielded a significant prognostic value in predicting patient outcomes. Furthermore, we found regulatory effect of CDKN3 on Paraptosis in two cell lines.

CONCLUSIONS

Our study highlights the importance of PRGs in LUAD, particularly in prognosis and treatment response. The identified molecular subtypes and Paraptosis-Associated Risk Score offer valuable insights for personalized treatment strategies.

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.

Proteomics-based Model for Predicting the Risk of Brain Metastasis in Patients with Resected Lung Adenocarcinoma carrying the EGFR Mutation

Introduction: Epidermal growth factor receptor (EGFR) mutation is common in Chinese patients with lung adenocarcinoma (LUAD). Brain metastases (BMs) is high and associated with poor prognosis. Identification of EGFR-mutant patients at high risk of developing BMs is important to reduce or delay the incidence of BMs. Currently, there is no literature on the prediction and modeling of EGFR brain metastasis at the proteinomics level. Methods: We conducted a retrospective study of BMs in postoperative recurrent LUAD with EGFR mutation in the First Affiliated Hospital of Guangzhou Medical University. Tissue proteomic analysis was applied in the primary tumors of resected LUAD in this study using liquid chromatography-mass spectrometry (LC-MS/MS). To identify potential markers for predicting LUAD BM, comparative analyses were performed on different groups to evaluate proteins associated with high risk of BMs. Results: A combination of three potential marker proteins was found to discriminate well between distal metastasis (DM) and local recurrence (LR) of postoperative LUAD with EGFR mutation. Gene Ontology (GO) analysis of significantly altered proteins between BM and non-BM (NBM) indicated that lipid metabolism and cell cycle-related pathways were involved in BMs of LUAD. And the enriched pathways correlated with BMs were found to be quite different in the comparison groups of postoperative adjuvant therapy, tyrosine kinase inhibitor (TKI), and chemotherapy groups. Finally, we developed a random forest algorithm model with eight proteins (RRS1, CPT1A, DNM1, SRCAP, MLYCD, PCID2, IMPAD1 and FILIP1), which showed excellent predictive value (AUC: 0.9401) of BM in patients with LUAD harboring EGFR mutation. Conclusions: A predictive model based on protein markers was developed to accurately predict postoperative BM in operable LUAD harboring EGFR mutation.

METTL3-mediated m6 A methylation of TRAF5 inhibits lung adenocarcinoma cell metastasis via activation of the PI3K/AKT/NF-κB signaling pathway

Tumor necrosis factor receptor-associated factor 5 (TRAF5) has been implicated in the pathogenesis of human malignancies. This work aimed to clarify the role of TRAF5 in lung adenocarcinoma (LUAD) progression. Herein, we uncovered that TRAF5 level was reduced in LUAD tissues. Low TRAF5 expression correlated with dismal prognosis in LUAD patients. Moreover, upregulated TRAF5 impeded cell viability, migration, and invasion, induced apoptosis in vitro, as well as impaired tumorigenicity in vivo. However, depletion of TRAF5 revealed opposing results. Moreover, TRAF5 was identified as the downstream target of methyltransferase-like 3 (METTL3)-elicited N6 -methyladenosine (m6 A) modification. METTL3 stabilized TRAF5 mRNA and positively modulated TRAF5 level. Further, TRAF5 depletion relieved the repressive phenotype caused by METTL3 addition. In addition, it was manifested that the METTL3/TRAF5 axis served as an inhibitor in LUAD through the PI3K/AKT/Nuclear Factor-Kappa B (NF-κB) signaling. Collectively, we propose that METTL3-mediated TRAF5 m6 A modification exerted as a vital tumor inhibitory function in LUAD development. The METTL3/TRAF5 axis may be a critical effector of LUAD progression.

Multidimensional progressive single-cell sequencing reveals cell microenvironment composition and cancer heterogeneity in lung cancer

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single-cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re-dimensional grouping of cancer-associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell-to-cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer-associated endothelial and fibroblast cells showed a co-expression relationship with myeloid cells and B cells. Through cell-to-cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB-CD8 T cells, and GZMK-CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment.

FSTL3 is associated with prognosis and immune cell infiltration in lung adenocarcinoma

PURPOSE

FSTL3 expression is altered in various types of cancer. However, the role and mechanism of action of FSTL3 in lung adenocarcinoma development and tumor immunity are unknown. We investigated the association between FSTL3 expression and clinical characteristics and immune cell infiltration in lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) and a separate validation set from our hospital.

METHODS

Data on immune system infiltration, gene expression, and relevant clinical information were obtained by analyzing lung adenocarcinoma sample data from TCGA database. Using online tools like GEPIA, the correlations between FSTL3 expression and prognosis, clinical stage, survival status, and tumor-infiltrating immune cells were examined. In a validation dataset, immunohistochemistry was performed to analyze FSTL3 expression and its related clinical characteristics.

RESULTS

FSTL3 expression was markedly reduced in patients with lung adenocarcinoma. N stage, pathological stage, and overall survival were significantly correlated with FSTL3 expression. According to GSEA, FSTL3 is strongly linked to signaling pathways such as DNA replication and those involved in cell cycle regulation. Examination of TCGA database and TIMER online revealed a correlation between FSTL3 and B cell, T cell, NK cell, and neutrophil levels. The prognosis of patients with lung adenocarcinoma was significantly affected by six genes (KRT6A, VEGFC, KRT14, KRT17, SNORA12, and KRT81) related to FSTL3.

CONCLUSION

FSTL3 is significantly associated with the prognosis and progression of lung adenocarcinoma and the infiltration of immune cells. Thus, targeting FSTL3 and its associated genes in immunotherapy could be potentially beneficial for the treatment of lung adenocarcinoma.

Integrated multi-omic analysis and experiment reveals the role of endoplasmic reticulum stress in lung adenocarcinoma

BACKGROUND

Lung cancer is a highly prevalent malignancy worldwide and is associated with high mortality rates. While the involvement of endoplasmic reticulum (ER) stress in the development of lung adenocarcinoma (LUAD) has been established, the underlying mechanism remains unclear.

METHODS

In this study, we utilized data from The Cancer Genome Atlas (TCGA) to identify differentially expressed endoplasmic reticulum stress-related genes (ERSRGs) between LUAD and normal tissues. We performed various bioinformatics analyses to investigate the biological functions of these ERSRGs. Using LASSO analysis and multivariate stepwise regression, we constructed a novel prognostic model based on the ERSRGs. We further validated the performance of the model using two independent datasets from the Gene Expression Omnibus (GEO). Additionally, we conducted functional enrichment analysis, immune checkpoint analysis, and immune infiltration analysis and drug sensitivity analysis of LUAD patients to explore the potential biological function of the model. Furthermore, we conducted a battery of experiments to verify the expression of ERSRGs in a real-world cohort.

RESULTS

We identified 106 ERSRGs associated with LUAD, which allowed us to classify LUAD patients into two subtypes based on gene expression differences. Using six prognostic genes (NUPR1, RHBDD2, VCP, BAK1, EIF2AK3, MBTPS2), we constructed a prognostic model that exhibited excellent predictive performance in the training dataset and was successfully validated in two independent external datasets. The risk score derived from this model emerged as an independent prognostic factor for LUAD. Confirmation of the linkage between this risk model and immune infiltration was affirmed through the utilization of Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The q-PCR results verified significant differences in the expression of prognostic genes between cancer and paracancer tissues. Notably, the protein expression of NUPR1, as determined by immunohistochemistry (IHC), exhibited an opposite pattern compared to the mRNA expression patterns.

CONCLUSION

This study establishes a novel prognostic model for LUAD based on six ER stress-related genes, facilitating the prediction of LUAD prognosis. Additionally, NUPR1 was identified as a potential regulator of stress in LUAD.

Low UPB1 Level Correlates With Poor Prognosis in Lung Adenocarcinoma

OBJECTIVES

Lung adenocarcinoma (LUAD) is a critical cancer with high mortality, worse prognosis, and crucial lymphatic metastasis. Consequently, prognostic biomarkers for LUAD are truly required. β-Ureidopropionase (UPB1) is abnormally expressed in various cancers. However, the function of UPB1 in LUAD is still ambiguous. This study aimed to explore the expression profile and prognostic significance of UPB1 in LUAD.

MATERIALS AND METHODS

The differential UPB1 levels in pan cancers and their prognostic significance were comprehensively investigated through Gene Expression Profiling Interactive Analysis, UALCAN, Tumor Immune Estimation Resource, and Kaplan-Meier plotter platform. The correlation between UPB1 and tumor infiltration immune cells was explored using Tumor Immune Estimation Resource, Gene Expression Profiling Interactive Analysis, and Tumor-Immune System Interactions and Drug Bank database databases.

RESULTS

The UPB1 level was abnormally expressed in pan-tumor tissue than in adjacent tissue from The Cancer Genome Atlas tool. Low UPB1 level was correlated with poor overall survival in patients with LUAD. Furthermore, a comparison of the various pathologic characteristics of LUAD between high and low UPB1 level subgroups revealed that low UPB1 expression was correlated with lymph node metastasis. Kaplan-Meier survival analysis indicated that a low UPB1 level was associated with worse progression‑free survival and overall survival in patients with LUAD. Univariate and multivariate analyses suggested that UPB1 could be a useful prognostic indicator for LUAD. Abnormal UPB1 may be correlated with aberrant LUAD immune infiltration, prompting a worse survival outcome.

CONCLUSIONS

Results showed that low UPB1 is correlated with a worse prognosis of LUAD and may be a valuable prognostic indicator for LUAD.

New molecular insights into ferroptosis in lung adenocarcinoma progression and pharmacological compounds for targeted therapy

BACKGROUND

The involvement of ferroptosis has been found in many pathological conditions of the lung. The genetic engineering of ferroptosis-related genes may provide a potential target for the treatment of lung adenocarcinoma (LUAD).

METHODS

Nine ferroptosis regulators and markers were collected from FerrDb and their somatic mutations and expressions were analyzed based on The Cancer Genome Atlas (TCGA)-LUAD cohort data. Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were performed to screen genes significantly associated with ferroptosis. The ferroptosis-related gene signature was constructed using TCGA-LUAD cohort data and was verified using the GSE cohort with pooled data for GSE30219, GSE31210, GSE37745 and GSE50081. Immune microenvironment component and mutation analysis were performed for genes in the ferroptosis-related gene signature.

RESULTS

All nine ferroptosis regulators and markers were differentially expressed between normal LUAD tumor tissues and adjacent normal tissues and were related to copy number variation. The expression of 1329 genes were significantly associated with nine ferroptosis regulators and markers in the TCGA-LUAD dataset, five (ALDOA, PLK1, CD47, CENPC and TMOD3) of which were integrated into a ferroptosis-related gene signature to calculate the risk score of LUAD samples, showing a significant correlation with the abundance of immune cell infiltration and the immune score. Molecular docking showed the binding activity of natural active compound quercetin to target proteins ALDOA and CD47, as well as the binding activity of aristolochic acid to PLK1 protein and TMOD3 protein.

CONCLUSIONS

In the present study, a ferroptosis-related gene signature with predictive value for LUAD prognosis was constructed, in which the gene was a potential therapeutic target for LUAD. Quercetin and aristolochic acid were potential candidates for inhibiting these targets by directly binding to them and showing high affinity and strong stability.

A novel iTreg-related signature for prognostic prediction in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Most patients are diagnosed at an advanced stage, therefore it is crucial to identify novel prognostic biomarkers for LUAD. As important regulatory cells, inducible regulatory T cells (iTregs) play a vital role in immune suppression and are important for the maintenance of immune homeostasis. This study explored the prognostic value and therapeutic effects of iTreg-related genes in LUAD. Data for LUAD patients, including immune infiltration data, RNA sequencing data, and clinical features, were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and Tumor Immune Single-cell Hub 2 databases. Immune-related subgroups with different infiltration patterns and iTreg-related genes were identified through univariate and multivariate Cox regression analyses and weighted correlation network analysis. Functional enrichment analyses were performed to explore the underlying mechanisms of iTreg-related genes. A prognostic risk signature was constructed using Cox regression analysis with the least absolute shrinkage and selection operator penalty. The ESTIMATE algorithm was applied to determine the immune status of LUAD patients. We applied the constructed signature to predict chemosensitivity and performed single-cell RNA sequencing analysis. The infiltration of iTregs was identified as an independent factor for predicting patient outcomes. We constructed a prognostic signature based on seven iTreg-related genes (GIMAP5, SLA, MS4A7, ZNF366, POU2AF1, MRPL12, and COL5A1), which was applied to subdivide patients into high- and low-risk subgroups. Our results revealed that patients in the iTreg-related low-risk subgroup had a better prognosis and possibly greater sensitivity to traditional chemotherapy. Our study provides a novel iTreg-related signature to elucidate the mechanisms underlying LUAD prognosis and promote individualized chemotherapy treatment.

Elucidating the molecular role of MUC5B in progressive lung adenocarcinoma: Prospects for early diagnosis

Gel-forming mucin MUC5B is significantly deregulated in lung adenocarcinoma (LUAD), however, its role in tumor progression is not yet clearly understood. Here, we used an integrated computational-pipeline-initiated with gene expression analysis followed by network, functional-enrichment, O-linked glycosylation analyses, mutational profiling, and immune cell infiltration estimation to functionally characterize MUC5B gene in LUAD. Thereafter, clinical biomarker validation was supported by the overall survival (OA) and comparative expression profiling across clinical stages using computational algorithms. The gene expression profile of LUAD identified MUC5B to be significantly up-regulated (logFC: 2.36; p-value: 0.01). Network analysis on LUAD interactome screened MUC5B-related genes, having key enrichment in immune suppression and O-linked glycosylation with serine-threonine-rich tandem repeats being highly glycosylated. Furthermore, positive correlation of mutant MUC5B with immune cells in tumor microenvironment (TME) such as cancer-associated fibroblasts and myeloid-derived suppressor cells indicates TME-mediated tumor progression. The positive correlation with immune inhibitors suggested the enhanced tumor proliferation mediated by MUC5B. Structural stability due to genetic alterations identified overall rigid N-H-backbone dynamics (S2 : 0.756), indicating an overall stable mutant protein. Moreover, the low median OA (<50 months) with a hazard ratio of 1.4 and clinical profile of MUC5B gene showed high median expression corresponding to lymph node (N2) and tumor (T3) stages. Our study concludes by highlighting the functional role of O-glycosylated and mutant MUC5B in promoting LUAD by immune suppression. Further, clinical gene expression validation of MUC5B suggests its potential role as a diagnostic biomarker for LUAD metastasis.

Drug repurposing based on differentially expressed genes suggests drug combinations with possible synergistic effects in treatment of lung adenocarcinoma

Lung adenocarcinoma is one of the leading causes of cancer-related mortality globally. Various treatment approaches and drugs had little influence on overall survival; thus, new drugs and treatment strategies are needed. Drug repositioning (repurposing) seems a favorable approach considering that developing new drugs needs much more time and costs. We performed a meta-analysis on 6 microarray datasets to obtain the main genes with significantly altered expression in lung adenocarcinoma. Following that, we found major gene clusters and hub genes. We assessed their enrichment in biological pathways to get insight into the underlying biological process involved in lung adenocarcinoma pathogenesis. The L1000 database was explored for drug perturbations that might reverse the expression of differentially expressed genes in lung adenocarcinoma. We evaluated the potential drug combinations that interact the most with hub genes and hence have the most potential to reverse the disease process. A total of 2148 differentially expressed genes were identified. Six main gene clusters and 27 significant hub genes mainly involved in cell cycle regulation have been identified. By assessing the interaction between 3 drugs and hub genes and information gained from previous clinical investigations, we suggested the three possible repurposed drug combinations, Vorinostat - Dorsomorphin, PP-110 - Dorsomorphin, and Puromycin - Vorinostat with a high chance of success in clinical trials.

Stemness genes and miR-1247-3p expression associate with clinicopathological parameters and prognosis in lung adenocarcinoma

Lung cancer makes up one-fourth of all cancer-related mortality with the highest mortality rate among all cancers. Despite recent scientific advancements in cancer therapeutics, the 5-year survival rate of lung adenocarcinoma (LUAD) cancer patients remains below 15 percent. It has been suggested that the high mortality rate of LUAD is linked to the acquisition of progenitor-like cells with stem-like characteristics that assist the whole tumor in regulating immune cell infiltration. To examine this hypothesis further, this study mined several databases to explore the presence of stemness-related genes and miRNAs in LUAD cancers. We examine their association with immune and accessory cell infiltration rates and patient survival. We found 3 stem cell-related genes, ORC1L, KIF20A, and DLGAP5, present in LUAD that also correlate with changes in immune infiltration rates and reduced patient survival rates. Additionally, the modulation in myeloid-derived suppressor cell (MDSC) infiltration and miRNA hsa-mir-1247-3p mediated targeting of tumor suppressor SLC24A4 and oncogenes RAB3B and HJURP appears to primarily regulate LUAD patient survival. Given these findings, hsa-mir-1247-3p and/or its associated gene targets may offer a promising avenue to enhance patient survivability.

Elaboration and validation of a prognostic signature associated with disulfidoptosis in lung adenocarcinoma, consolidated with integration of single-cell RNA sequencing and bulk RNA sequencing techniques

Background

Lung adenocarcinoma (LUAD), the predominant subtype of non-small cell lung cancer (NSCLC), remains a pervasive global public health concern. Disulfidoptosis, a nascent form of regulated cell death (RCD), presents an emerging field of inquiry. Currently, investigations into disulfidoptosis are in their initial stages. Our undertaking sought to integrate single-cell RNA sequencing (scRNA-seq) in conjunction with traditional bulk RNA sequencing (bulk RNA-seq) methodologies, with the objective of delineating genes associated with disulfidoptosis and subsequently prognosticating the clinical outcomes of LUAD patients.

Methods

Initially, we conducted an in-depth examination of the cellular composition disparities existing between LUAD and normal samples using scRNA-seq data sourced from GSE149655. Simultaneously, we scrutinized the expression patterns of disulfidoptosis-associated gene sets across diverse cell types. Subsequently, leveraging the bulk RNA-seq data, we formulated disulfidoptosis-related prognostic risk signatures (DRPS) employing LASSO-Cox regression. This was accomplished by focusing on genes implicated in disulfidoptosis that exhibited differential expression within endothelial cells (ECs). Sequentially, the robustness and precision of the DRPS model were rigorously verified through both internal and external validation datasets. In parallel, we executed single-cell trajectory analysis to delve into the differentiation dynamics of ECs. Concluding our study, we undertook a comprehensive investigation encompassing various facets. These included comparative assessments of enrichment pathways, clinicopathological parameters, immune cell abundance, immune response-associated genes, impacts of immunotherapy, and drug predictions among distinct risk cohorts.

Results

The scrutiny of scRNA-seq data underscored discernible disparities in cellular composition between LUAD and normal samples. Furthermore, disulfidoptosis-associated genes exhibited marked discrepancies within endothelial cells (ECs). Consequently, we formulated the Disulfidoptosis-Related Prognostic Signature (DRPS) to facilitate prognostic prediction. The prognostic nomogram based on the risk score effectively demonstrated DRPS's robust capacity to prognosticate survival outcomes. This assertion was corroborated by rigorous assessments utilizing both internal and external validation sets, thus affirming the commendable predictive accuracy and enduring stability of DRPS. Functional enrichment analysis shed light on the significant correlation of DRPS with pathways intrinsic to the cell cycle. Subsequent analysis unveiled correlations between DRPS and gene mutations characteristic of LUAD, as well as indications of an immunosuppressive status. Through drug prediction, we explored potential therapeutic agents for low-risk patients. Concluding our investigation, qRT-PCR experiments confirmed the heightened expression levels of EPHX1, LDHA, SHC1, MYO6, and TLE1 in lung cancer cell lines.

Association of LncRNA PCBP1-AS1 with cancer occurrence and development: A review

Long-stranded noncoding RNAs (LncRNAs) are noncoding RNAs >200 nucleotides in length. Polycytidine binding protein 1 antisense LncRNA is abbreviated as LncRNA polycytosine binding protein 1 antisense1 (PCBP1-AS1). Since studies in recent years have revealed the importance of PCBP1-AS1 in human genetic analysis, it is an important member of the LncRNA family. Genetically engineered group analysis of PCBP1-AS1 regulates the progression of cancer in biology. Therefore, it may be an important RNA in the regulation of human cancer. This article summarizes the molecular mechanism and clinical role of PCBP1-AS1 in various tumor types. Taking "PCBP1-AS1" and "cancer" as keywords, this paper analyzed the relationship between PCBP1-AS1 and various tumors by searching PubMed and Geen Medical, and summarized the related regulatory mechanism of PCBP1-AS1. PCBP1-AS1 is a valuable tumor-associated LncRNA that plays different biological roles in different cancers. Overall, it can both promote and inhibit the development of cancer. For example, abnormally high expression in castration-resitant prostate cancer, hepatocellular carcinoma, cervical cancer, glioma, and colorectal cancer promotes the proliferation and progression of these cancers; in contrast, PCBP1-AS1 inhibits cancer proliferation, metastasis, invasion, and recurrence when highly expressed in vulvar squamous cell carcinoma, Hodgkin lymphoma, and lung adenocarcinoma. PCBP1-AS1 regulates the development of multiple tumors, and the specific mechanism needs to be further investigated, which may become a new tumor marker and potential therapeutic target.

Eriocitrin inhibits epithelial-mesenchymal transformation (EMT) in lung adenocarcinoma cells via triggering ferroptosis

INTRODUCTION

Lung adenocarcinoma (LUAD) is the most prevalent pathological subtype of non-small cell lung cancer (NSCLC), characterized by a high propensity for relapse and metastasis due to epithelial-mesenchymal transition (EMT) of cancer cells. Ferroptosis, a newly discovered regulated cell death modality, is interconnected with the EMT process in certain cancers. Eriocitrin, a natural flavonoid compound, exerts anti-inflammatory and anticancer effects.

OBJECTIVES

The aim of this study is to investigate the potential inhibitory effect of eriocitrin on lung adenocarcinoma metastasis and explore whether its underlying mechanism involves ferroptosis induction in cancer cells.

METHODS

The CCK8 assay and wound healing assay and transwell were conducted to determine the cell viability and migration ability of A549 and H1299 cells, respectively. EMT process was assessed by western blot and RT-PCR to detect protein and mRNA levels of EMT markers. ROS and cell iron were measured to determine ferroptosis level.

RESULTS

Eriocitrin treatment significantly inhibited cell viability and migration ability in a concentration-dependent manner. Furthermore, eriocitrin administration for 24 hours resulted in enhanced expression of E-cadherin, while downregulating vimentin, N-cadherin and snail expression, indicating marked repression of the EMT process. Additionally, eriocitrin significantly induced ferroptosis in A549 and H1299 cells, as evidenced by increased ROS levels, downregulation of Nrf-2, SLC7A11 and GPX4 expression, and enhanced cellular iron accumulation. Moreover, pretreatment with the ferroptosis inhibitor ferrostatin-1 effectively abrogated the inhibitory effects of eriocitrin on EMT.

CONCLUSIONS

Our findings further support the anti-cancer properties of eriocitrin, as evidenced by its ability to inhibit the EMT process in LUAD cells, which is partially mediated through induction of ferroptosis in cancer cells.

Hsa-miR-503-5p regulates CTDSPL to accelerate cisplatin resistance and angiogenesis of lung adenocarcinoma cells

The study aimed to assess the role of hsa-miR-503-5p in cisplatin resistance and angiogenesis in LUAD and its underlying mechanisms. Hsa-miR-503-5p expression in LUAD and the target gene downstream of hsa-miR-503-5p was predicted by bioinformatics analysis. Binding relationship between the two genes was verified by dual-luciferase reporter assay. qRT-PCR was conducted for detecting gene expression in cells, CCK-8 for IC50 value, angiogenesis assay for human umbilical vein endothelial cell (HUVEC) angiogenic ability, flow cytometry for apoptosis ability, transwell assay for migration ability, and western blot for detecting the protein expression of vascular endothelial growth factor receptor 1 (VEGFR1), VEGFR2, and CTD small phosphatase like (CTDSPL). The results showed that hsa-miR-503-5p showed high expression, while its target gene CTDSPL presented decreased expression in LUAD. Hsa-miR-503-5p also had high expression in cisplatin-resistant LUAD cells. Knockdown of hsa-miR-503-5p resensitized LUAD cells to cisplatin, inhibited angiogenesis of drug-resistant cells, and reduced the protein expression of VEGFR1, VEGFR2, and EMT-related targets in cisplatin-resistant LUAD cells, but promoted the apoptosis ability. Hsa-miR-503-5p bound to CTDSPL gene and promoted cisplatin resistance and malignant progression of LUAD cells by negatively regulating CTDSPL. Our results revealed that hsa-miR-503-5p and CTDSPL may be novel targets for overcoming cisplatin resistance in LUAD.

Lipid metabolism-related gene signatures for predicting the prognosis of lung adenocarcinoma

Background

Lung cancer is one of the most common epithelial malignancies worldwide, accounting for the highest number of new cases and deaths. Metabolism is the sum of chemical reactions that produce energy to keep an organism alive. Several studies have shown that glucose and lipid metabolic disorders are common phenomena related to cancer cell genesis and progression.

Methods

We screened the differentially expressed genes (DEGs) of lung adenocarcinoma (LUAD) samples of The Cancer Genome Atlas (TCGA) database, the Gene Set Enrichment Analysis (GSEA), and Gene Card database metabolism-related data, the metabolism-related DEGs of LUAD, as well as the univariate Cox regression analysis genes, for identifying significant outcome-related genes. The least absolute shrinkage and gene selection operator (LASSO) analysis was performed to establish the best risk model.

Results

Our study aimed to establish a lipid metabolism-related model for predicting LUAD prognosis. Furthermore, our model's prognosis prediction power was evaluated by survival analysis. This study finally identified 11 DEGs related to lipid metabolism that were significantly associated with the prognosis of lung adenocarcinoma. It provided a new idea for the treatment of high-risk lung adenocarcinoma patients.

Conclusions

The constructed clinical prognosis model of lung adenocarcinoma related to lipid metabolism provides a new idea for clinical treatment of lung adenocarcinoma.

A novel defined risk signature of cuproptosis-related long non-coding RNA for predicting prognosis, immune infiltration, and immunotherapy response in lung adenocarcinoma

Background: Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor immunity formation and patient-tailored treatment optimization of lung adenocarcinoma (LUAD) is still unclear. Methods: RNA sequencing and survival data of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database for model training. The patients with LUAD in GSE29013, GSE30219, GSE31210, GSE37745, and GSE50081 were used for validation. The proofed cuproptosis-related genes were extracted from the previous studies. The Pearson correlation was applied to select cuproptosis-related lncRNAs. We chose differentially expressed cuproptosis-related lncRNAs in the tumor and normal tissues and allowed them to go to a Cox regression and a LASSO regression for a lncRNA signature that predicts the LUAD prognosis. Kaplan-Meier estimator, Cox model, ROC, tAUC, PCA, nomogram predictor, decision curve analysis, and real-time PCR were further deployed to confirm the model's accuracy. We examined this model's link to other regulated cell death forms. Applying TMB, immune-related signatures, and TIDE demonstrated the immunotherapeutic capabilities of signatures. We evaluated the relationship of our signature to anticancer drug sensitivity. GSEA, immune infiltration analysis, and function experiments further investigated the functional mechanisms of the signature and the role of immune cells in the prognostic power of the signature. Results: An eight-lncRNA signature (TSPOAP1-AS1, AC107464.3, AC006449.7, LINC00324, COLCA1, HAGLR, MIR4435-2HG, and NKILA) was built and demonstrated owning prognostic power by applied to the validation cohort. Each signature gene was confirmed differentially expressed in the real world by real-time PCR. The eight-lncRNA signature correlated with 2321/3681 (63.05%) apoptosis-related genes, 11/20 (55.00%) necroptosis-related genes, 34/50 (68.00%) pyroptosis-related genes, and 222/380 (58.42%) ferroptosis-related genes. Immunotherapy analysis suggested that our signature may have utility in predicting immunotherapy efficacy in patients with LUAD. Mast cells were identified as key players that support the predicting capacity of the eight-lncRNA signature through the immune infiltrating analysis. Conclusion: In this study, an eight-lncRNA signature linked to cuproptosis was identified, which may improve LUAD management strategies. This signature may possess the ability to predict the effect of LUAD immunotherapy. In addition, infiltrating mast cells may affect the signature's prognostic power.

Circ_0001715 accelerated lung adenocarcinoma process by the miR-1322/CANT1 axis

Lung adenocarcinoma (LUAD) is a type of lung cancer, which belongs to non-small cell lung cancer and has seriously endangered the physical and mental health of people. The study of circRNAs (circRNAs) has been increasingly hot in recent years, in which circRNAs also play an important regulatory role in cancer. The aim of this study was to investigate the biological molecular mechanisms of circ_0001715 in the progression of LUAD. The expression of circ_0001715, miR-1322 and calcium-activated nucleotidase 1 (CANT1) in LUAD tissues and cell lines was assessed by quantitative reverse transcription PCR (RT-qPCR) and western bot assay. Clone formation assay, 5-Ethynyl-2'-Deoxyuridine (EDU) assay and wound healing assay were used to verify the proliferation ability of cells. Dual-luciferase reporter assay and RNA pull-down assay were performed to characterize the interactions between the three factors. Finally, a mouse tumor model was constructed to assess the tumorigenicity of circ_0001715. RT-qPCR assay results showed that circ_0001715 expression was significantly increased in LUAD tissues and cell lines. Finally, knockdown of circ_0001715 could inhibit tumor growth in vivo. Circ_0001715 regulated the progression of LUAD through the miR-1322/CANT1 axis. The results of this study provided ideas for understanding the molecular mechanisms of circ_0001715 in LUAD.

The activity of cuproptosis pathway calculated by AUCell algorithm was employed to construct cuproptosis landscape in lung adenocarcinoma

Cuproptosis is a recently described copper-dependent cell death pathway. Consequently, there are still few studies on lung adenocarcinoma (LUAD)-related cuproptosis, and we aimed to deepen in this matter. In this study, data from 503 patients with lung cancer from the TCGA-LUAD cohort data collection and 11 LUAD single-cells from GSE131907 as well as from 10 genes associated with cuproptosis were analyzed. The AUCell R package was used to determine the copper-dependent cell death pathway activity for each cell subpopulation, calculate the CellChat score, and display cell communication for each cell subpopulation. The PROGENy score was calculated to show the scores of tumor-related pathways in different cell populations. GO and KEGG analyses were used to calculate pathway activity. Univariate COX and random forest analyses were used to screen prognosis-associated genes and construct models. The ssGSEA and xCell algorithms were used to calculate the immunocyte infiltration score. Based on data from the GDSC database, the drug sensitivity score was calculated using oncoPredict. Finally, in vitro experiments were performed to determine the role of TLE1, the most important gene in the prognostic model. The 11 LUAD single-cell samples were classified into 8 different cell populations, from which epithelial cells showed the highest copper-dependent cell death pathway activity. Epithelial cell subsets were significantly positively correlated with MAKP, hypoxia, and other pathways. In addition, cell subgroup communication showed highly active collagen and APP pathways. Using the Findmark algorithm, differentially expressed genes (DEGs) between epithelial and other cell types were identified. Combined with the bulk data in the TCGA-LUAD database, DEGs were enriched in pathways such as EGFR tyrosine kinase inhibitor resistance, Hippo signaling pathway, and tight junction. Subsequently, we selected 4 genes (out of 112) with prognostic significance, ANKRD29, RHOV, TLE1, and NPAS2, and used them to construct a prognostic model. The high- and low-risk groups, distinguished by the median risk score, showed significantly different prognoses. Finally, we chose TLE1 as a biomarker based on the relative importance score in the prognostic model. In vitro experiments showed that TLE1 promotes tumor proliferation and migration and inhibits apoptosis.

A five-collagen-based risk model in lung adenocarcinoma: prognostic significance and immune landscape

As part of the tumor microenvironment (TME), collagen plays a significant role in cancer fibrosis formation. However, the collagen family expression profile and clinical features in lung adenocarcinoma (LUAD) are poorly understood. The objective of the present work was to investigate the expression pattern of genes from the collagen family in LUAD and to develop a predictive signature based on collagen family. The Cancer Genome Atlas (TCGA) samples were used as the training set, and five additional cohort samples obtained from the Gene Expression Omnibus (GEO) database were used as the validation set. A predictive model based on five collagen genes, including COL1A1, COL4A3, COL5A1, COL11A1, and COL22A1, was created by analyzing samples from the TCGA cohort using LASSO Cox analysis and univariate/multivariable Cox regression. Using Collagen-Risk scores, LUAD patients were then divided into high- and low-risk groups. KM survival analysis showed that collagen signature presented a robust prognostic power. GO and KEGG analyses confirmed that collagen signature was associated with extracellular matrix organization, ECM-receptor interaction, PI3K-Akts and AGE-RAGE signaling activation. High-risk patients exhibited a considerable activation of the p53 pathway and cell cycle, according to GSEA analysis. The Collage-Risk model showed unique features in immune cell infiltration and tumor-associated macrophage (TAM) polarization of the TME. Additionally, we deeply revealed the association of collagen signature with immune checkpoints (ICPs), tumor mutation burden (TMB), and tumor purity. We first constructed a reliable prognostic model based on TME principal component-collagen, which would enable clinicians to treat patients with LUAD more individually.

An ICD-Associated DAMP Gene signature predicts survival and immunotherapy response of patients with lung adenocarcinoma

BACKGROUND

While some lung adenocarcinoma (LUAD) patients benefit long-term from treatment with immune checkpoint inhibitors, the sad reality is that a considerable proportion of patients do not. The classification of the LUAD tumor microenvironment (TME) can be used to conceptually comprehend primary resistance mechanisms. In addition, the most recent research demonstrates that the release of damage-associated molecular pattern (DAMP) in TME by immunogenic cell death (ICD) may contribute to the adaptive immune response. Currently, however, there is no such comprehensive research on this topic in LUAD patients. Therefore, we set out to investigate how to reverse the poor infiltration characteristics of immune cells and boost antitumor immunity by identifying DAMP model.

METHODS

In this study, ICD-related DAMP genes were selected to investigate their effects on the prognosis of LUAD. To create a risk signature using the TCGA-LUAD cohort, the univariate COX regression and the least absolute shrinkage and selection operator regression were carried out, and the results were verified in a GEO dataset. Subsequently, the multivariate COX regression was applied to establish a prognostic nomogram. And the ESTIMATE and ssGSEA algorithms were utilized to analyze immune activity and the TIDE algorithm was for responsiveness to immunotherapy. Moreover, clinical tissue samples were used to verify the differential expression of 9 DAMP genes in the signature.

RESULTS

We identified two distinct DAMP molecular subtypes, and there are remarkable differences in survival probability between the two subtypes, and patients with higher levels of DAMP-related genes are "hot tumors" with increased immune activity. In addition, 9 DAMP genes were selected as prognostic signature genes, and clinical outcomes and immunotherapy response were better for participants in the low-risk group. Importantly, according to the area under the curve (AUC) value in evaluating the efficacy of immunotherapy, this signature is superior to existing predictors, such as PD-L1 and TIDE.

CONCLUSIONS

Our study suggests ICD plays an important part in modeling the TME of LUAD patients. And this signature could be utilized as a reliable predictor to estimate clinical outcomes and predict immunotherapy efficacy among LUAD patients.

Identification of m7G-Related miRNA Signatures Associated with Prognosis, Oxidative Stress, and Immune Landscape in Lung Adenocarcinoma

The role of N7-methylguanosine(m7G)-related miRNAs in lung adenocarcinoma (LUAD) remains unclear. We used LUAD data from The Cancer Genome Atlas (TCGA) to establish a risk model based on the m7G-related miRNAs, and divided patients into high-risk or low-risk subgroups. A nomogram for predicting overall survival (OS) was then constructed based on the independent risk factors. In addition, we performed a functional enrichment analysis and defined the oxidative stress-related genes, immune landscape as well as a drug response profile in the high-risk and low-risk subgroups. This study incorporated 28 m7G-related miRNAs into the risk model. The data showed a significant difference in the OS between the high-risk and low-risk subgroups. The receiver operating characteristic curve (ROC) predicted that the area under the curve (AUC) of one-year, three-year and five-year OS was 0.781, 0.804 and 0.853, respectively. The C-index of the prognostic nomogram for predicting OS was 0.739. We then analyzed the oxidative stress-related genes and immune landscape in the high-risk and low-risk subgroups. The data demonstrated significant differences in the expression of albumin (ALB), estimated score, immune score, stromal score, immune cell infiltration and functions between the high-risk and low-risk subgroups. In addition, the drug response analysis showed that low-risk subgroups may be more sensitive to tyrosine kinase inhibitor (TKI) and histone deacetylase (HDAC) inhibitors. We successfully developed a novel risk model based on m7G-related miRNAs in this study. The model can predict clinical prognosis and guide therapeutic regimens in patients with LUAD. Our data also provided new insights into the molecular mechanisms of m7G in LUAD.

Ferroptosis patterns modulate immunocyte communication in tumor microenvironments: clinical value and therapeutic guidance of lung adenocarcinoma

Lung adenocarcinoma (LUAD) emerges as one of the most aggressive tumor types with a poor prognosis. As a novel form of regulated cell death, ferroptosis promotes the clearance of tumor cells. However, few studies demonstrated whether ferroptosis-related genes can modify the behavior of tumor microenvironment (TME) cells. Resorting to non-negative matrix factorization (NMF) clustering based on the expression of ferroptosis-related genes, we identified multiple LUAD TME cell-type subpopulations. These subtypes of TME cells displayed extensive communication with tumor epithelial cells. ATF3+cancer-associated fibroblasts (CAFs), SLC40A1+CD8+T cells, and ALOX5+CD8+T cells showed distinct biological features compared to non-ferroptosis-related TME cells. Patients with a higher abundance of these ferroptosis-related TME cell subtypes showed a favorable clinical outcome. Our study depicted a detailed landscape of LUAD cell composition with a focus on ferroptosis-related genes, which, hopefully, may provide novel insight into further study of the LAUD immune microenvironment.

Advances in lung adenocarcinoma: A novel perspective on prognoses and immune responses of CENPO as an oncogenic superenhancer

Lung adenocarcinoma (LUAD) is the most prevalent form of lung cancer globally, and its treatment remains a significant challenge. Therefore, it is crucial to comprehend the microenvironment to improve therapy and prognosis urgently. In this study, we utilized bioinformatic methods to analyze the transcription expression profile of patient samples with complete clinical information from the TCGA-LUAD datasets. To validate our findings, we also analyzed the Gene Expression Omnibus (GEO) datasets. The super-enhancer (SE) was visualized using the peaks of the H3K27ac and H3K4me1 ChIP-seq signal, which were identified by the Integrative Genomics Viewer (IGV). To further investigate the role of Centromere protein O (CENPO) in LUAD, we conducted various assays including Western blot, qRT-PCR, flow cytometry, wound healing and transwell assays to assess the cell functions of CENPO in vitro. The overexpression of CENPO is linked to a poor prognosis in patients with LUAD. Strong signal peaks of H3K27ac and H3K4me1 were also observed near the predicted SE regions of CENPO. CENPO was found to be positively associated with the expression levels of immune checkpoints and drug IC50 value (Roscovitine and TGX221), but negatively associated with the fraction levels of several immature cells and drug IC50 value (CCT018159, GSK1904529A, Lenaildomide, and PD-173074). Additionally, CENPO-associated prognostic signature (CPS) was identified as an independent risk factor. The high-risk group for LUAD is identified based on CPS enrichment, which involved not only endocytosis that transfers mitochondria to promote cell survival in response to chemotherapy but also cell cycle promotion that leads to drug resistance. The removal of CENPO significantly suppressed metastasis and induced arrest and apoptosis of LUAD cells. The involvement of CENPO in the immunosuppression of LUAD provides a prognostic signature for LUAD patients.

RBM14 as a novel epigenetic-activated tumor oncogene is implicated in the reprogramming of glycolysis in lung cancer

BACKGROUND

RNA-binding motif protein 14 (RBM14) is upregulated in a variety of tumors. However, the expression and biological role of RBM14 in lung cancer remain unclear.

METHODS

Chromatin immunoprecipitation and PCR were carried out to measure the levels of sedimentary YY1, EP300, H3K9ac, and H3K27ac in the RBM14 promoter. Co-immunoprecipitation was used to verify the interaction between YY1 and EP300. Glycolysis was investigated according to glucose consumption, lactate production, and the extracellular acidification rate (ECAR).

RESULTS

RBM14 level is increased in lung adenocarcinoma (LUAD) cells. The increased RBM14 expression was correlated with TP53 mutation and individual cancer stages. A high level of RBM14 predicted a poorer overall survival of LUAD patients. The upregulated RBM14 in LUAD is induced by DNA methylation and histone acetylation. The transcription factor YY1 directly binds to EP300 and recruits EP300 to the promoter regions of RBM14, which further enhances H3K27 acetylation and promotes RBM14 expression. YY1-induced upregulation of RBM14 promoted cell growth and inhibited apoptosis by affecting the reprogramming of glycolysis.

CONCLUSIONS

These results indicated that epigenetically activated RBM14 regulated growth and apoptosis by regulating the reprogramming of glycolysis and RBM14 may serve as a promising biomarker and therapeutic target for LUAD.

Comprehensively Analyze the Prognosis Significance and Immune Implication of PTPRO in Lung Adenocarcinoma

Immunotherapy for lung adenocarcinoma (LUAD) is considered to be a promising treatment option, but only a minority of patients benefit from it. Therefore, it is essential to clarify the regulation mechanism of the tumor immune microenvironment (TIM) of the LUAD. Receptor-type protein tyrosine phosphatase (PTPRO) has been shown to be a tumor suppressor in a variety of tumor; however, its role in LUAD has never been reported. In this study, we first found that PTPRO was lowly expressed in LUAD and positively correlated with patient prognosis. Next, we investigated the relationship between PTPRO and clinical characteristics, and the results showed that gender, age, T, and stage were closely related to the expression level of PTPRO. Moreover, we performed univariate and multivariate analyses, and the results revealed that PTPRO was a protective factor for LUAD. By constructing a nomogram based on the expression level of PTPRO and various clinical characteristics, it was proved that the nomogram has a good predictive capacity. Furthermore, we analyzed the coexpression network of PTPRO through multiple databases and performed GO and KEGG enrichment analyses. The results demonstrated that PTPRO was involved in the regulation of multiple immune pathways. In addition, we analyzed whether PTPRO expression of LUAD regulate immune cell infiltration and the results demonstrated that PTPRO was closely related to the infiltration of various immune cells. Finally, we predicted LUAD sensitivity to chemotherapeutics and response to immunotherapy by PTPRO expression levels. The results showed that PTPRO expression level affect the sensitivity of various chemotherapeutic drugs and may be involved in the efficacy of immunotherapy. These results we obtained suggested that PTPRO is closely related to the prognosis and TIM of LUAD, which may be a potential immunotherapeutic target for LUAD.

Establishing a metastasis-related diagnosis and prognosis model for lung adenocarcinoma through CRISPR library and TCGA database

PURPOSE

Existing biomarkers for diagnosing and predicting metastasis of lung adenocarcinoma (LUAD) may not meet the demands of clinical practice. Risk prediction models with multiple markers may provide better prognostic factors for accurate diagnosis and prediction of metastatic LUAD.

METHODS

An animal model of LUAD metastasis was constructed using CRISPR technology, and genes related to LUAD metastasis were screened by mRNA sequencing of normal and metastatic tissues. The immune characteristics of different subtypes were analyzed, and differentially expressed genes were subjected to survival and Cox regression analyses to identify the specific genes involved in metastasis for constructing a prediction model. The biological function of RFLNA was verified by analyzing CCK-8, migration, invasion, and apoptosis in LUAD cell lines.

RESULTS

We identified 108 differentially expressed genes related to metastasis and classified LUAD samples into two subtypes according to gene expression. Subsequently, a prediction model composed of eight metastasis-related genes (RHOBTB2, KIAA1524, CENPW, DEPDC1, RFLNA, COL7A1, MMP12, and HOXB9) was constructed. The areas under the curves of the logistic regression and neural network were 0.946 and 0.856, respectively. The model effectively classified patients into low- and high-risk groups. The low-risk group had a better prognosis in both the training and test cohorts, indicating that the prediction model had good diagnostic and predictive power. Upregulation of RFLNA successfully promoted cell proliferation, migration, invasion, and attenuated apoptosis, suggesting that RFLNA plays a role in promoting LUAD development and metastasis.

CONCLUSION

The model has important diagnostic and prognostic value for metastatic LUAD and may be useful in clinical applications.

DDX11-AS1 modulates DNA damage repair to enhance paclitaxel resistance of lung adenocarcinoma cells

Aim: To investigate the influence of DDX11-AS1 on paclitaxel (PTX) resistance in lung adenocarcinoma (LUAD). Methods: LncRNA expression and functional enrichment analyses were processed via bioinformatics methods. DDX11-AS1 expression was detected via quantitative real-time PCR. Cell counting kit-8, colony formation, flow cytometry and comet assays were manipulated to measure cell proliferation, apoptosis, cell cycle and DNA damage repair, respectively. Western blot was used to assess DNA damage-related protein expression. Results: DDX11-AS1 was in a high expression status in LUAD, and could promote LUAD cell proliferation and PTX resistance, while suppressing cell apoptosis. DNA damage repairing ability was also modulated by the change of DDX11-AS1 expression. Conclusion: LncRNA DDX11-AS1 promotes DNA damage repair to enhance PTX resistance in LUAD.

Systemic analysis of the DNA replication regulator origin recognition complex in lung adenocarcinomas identifies prognostic and expression significance

BACKGROUND

DNA replication alteration is a hallmark of patients with lung adenocarcinoma (LUAD) and is frequently observed in LUAD progression. Origin recognition complex (ORC) 1, ORC2, ORC3, ORC4, ORC5, and ORC6 form a replication-initiator complex to mediate DNA replication, which plays a key role in carcinogenesis, while their roles in LUAD remain poorly understood.

METHODS

The mRNA and protein expression of ORCs was confirmed by the GEPIA, HPA, CPTAC, and TCGA databases. The protein-protein interaction network was analyzed by the GeneMANIA database. Functional enrichment was confirmed by the Metascape database. The effects of ORCs on immune infiltration were validated by the TIMER database. The prognostic significance of ORCs in LUAD was confirmed by the KM-plot and GENT2 databases. DNA alteration and protein structure were determined in the cBioProtal and PDB databases. Moreover, the protein expression and prognostic value of ORCs were confirmed in our LUAD data sets by immunohistochemistry (IHC) staining.

RESULTS

ORC mRNA and protein were significantly increased in patients with LUAD compared with corresponding normal tissue samples. The results of IHC staining analysis were similar result to those of the above bioinformatics analysis. Furthermore, ORC1 and ORC6 had significant prognostic values for LUAD patients. Furthermore, the ORC cooperatively promoted LUAD development by driving DNA replication, cellular senescence, and metabolic processes.

CONCLUSION

The ORC, especially ORC1/6, has important prognostic and expression significance for LUAD patients.

Secreted proteins MDK, WFDC2, and CXCL14 as candidate biomarkers for early diagnosis of lung adenocarcinoma

BACKGROUND

Early diagnosis of lung adenocarcinoma (LUAD), one of the most common types of lung cancer, is very important to improve the prognosis of patients. The current methods can't meet the requirements of early diagnosis. There is a pressing need to identify novel diagnostic biomarkers. Secretory proteins are the richest source for biomarker research. This study aimed to identify candidate secretory protein biomarkers for early diagnosis of LUAD by integrated bioinformatics analysis and clinical validation.

METHODS

Differentially expressed genes (DEGs) of GSE31210, gene expression data of early stage of LUAD, were analyzed by GEO2R. Upregulated DEGs predicted to encode secreted proteins were obtained by taking the intersection of the DEGs list with the list of genes encoding secreted proteins predicted by the majority decision-based method (MDSEC). The expressions of the identified secreted proteins in the lung tissues of early-stage LUAD patients were further compared with the healthy control group in mRNA and protein levels by using the UALCAN database (TCGA and CPTAC). The selected proteins expressed in plasma were further validated by using Luminex technology. The diagnostic value of the screened proteins was evaluated by receiver operating characteristic (ROC) analysis. Cell counting kit-8 assay was carried out to investigate the proliferative effects of these screened proteins.

RESULTS

A total of 2183 DEGs, including 1240 downregulated genes and 943 upregulated genes, were identified in the GSE31210. Of the upregulated genes, 199 genes were predicted to encode secreted proteins. After analysis using the UALCAN database, 16 molecules were selected for further clinical validation. Plasma concentrations of three proteins, Midkine (MDK), WAP four-disulfide core domain 2 (WFDC2), and C-X-C motif chemokine ligand 14 (CXCL14), were significantly higher in LUAD patients than in healthy donors. The area under the curve values was 0.944, 0.881, and 0.809 for MDK, WFDC2, and CXCL14, 0.962 when combined them. Overexpression of the three proteins enhanced the proliferation activity of A549 cells.

CONCLUSIONS

MDK, WFDC2, and CXCL14 were identified as candidate diagnostic biomarkers for early-stage LUAD and might also play vital roles in tumorigenesis.

Successful treatment of a patient with advanced lung adenocarcinoma (EGFR-T790M and C797S cis) with lazertinib: A case report and literature review

Lazertinib has been shown to treat non-small cell lung cancer (NSCLC) patients with EGFR-T790M, Ex19del, and L858R mutations. However, there are still no studies to prove that lazertinib could be used in patients with EGFR-T790M and C797s cis mutations in NSCLC. We report a case of a patient with advanced lung adenocarcinoma with EGFR-T790M and C797s cis mutations who were treated with lazertinib and achieved satisfactory efficacy without serious side effects. And the scratch assay and colony-forming unit assay were performed using lung adenocarcinoma cells from patients, the results showed that both lazertinib and amivantamab could inhibit the proliferation and migration of lung adenocarcinoma cells to some extent, and the inhibitory effect of lazertinib was better than that of amivantamab (p < 0. 01), while the inhibitory effect of lazertinib combined with amivantamab was not statistically different from that of lazertinib alone(p>0.05). This finding suggests that lazertinib may be an effective treatment option for patients with lung adenocarcinoma presenting with EGFR-T790M and C797s cis mutations.

Identification of natural killer cell associated subtyping and gene signature to predict prognosis and drug sensitivity of lung adenocarcinoma

Introduction: This research explored the immune characteristics of natural killer (NK) cells in lung adenocarcinoma (LUAD) and their predictive role on patient survival and immunotherapy response. Material and methods: Molecular subtyping of LUAD samples was performed by evaluating NK cell-associated pathways and genes in The Cancer Genome Atlas (TCGA) dataset using consistent clustering. 12 programmed cell death (PCD) patterns were acquired from previous study. Riskscore prognostic models were constructed using Least absolute shrinkage and selection operator (Lasso) and Cox regression. The model stability was validated in Gene Expression Omnibus database (GEO). Results: We classified LUAD into three different molecular subgroups based on NK cell-related genes, with the worst prognosis in C1 patients and the optimal in C3. Homologous Recombination Defects, purity and ploidy, TMB, LOH, Aneuploidy Score, were the most high-expressed in C1 and the least expressed in C3. ImmuneScore was the highest in C3 type, suggesting greater immune infiltration in C3 subtype. C1 subtypes had higher TIDE scores, indicating that C1 subtypes may benefit less from immunotherapy. Generally, C3 subtype presented highest PCD patterns scores. With four genes, ANLN, FAM83A, RHOV and PARP15, we constructed a LUAD risk prediction model with significant differences in immune cell composition, cell cycle related pathways between the two risk groups. Samples in C1 and high group were more sensitive to chemotherapy drug. The score of PCD were differences in high- and low-groups. Finally, we combined Riskscore and clinical features to improve the performance of the prediction model, and the calibration curve and decision curve verified that the great robustness of the model. Conclusion: We identified three stable molecular subtypes of LUAD and constructed a prognostic model based on NK cell-related genes, maybe have a greater potential for application in predicting immunotherapy response and patient prognosis.