Signatures of malignant cells and novel therapeutic targets revealed by single-cell sequencing in lung adenocarcinoma

Dissecting tumor transcriptional heterogeneity from single-cell RNA-seq data by generalized binary covariance decomposition

Profiling tumors with single-cell RNA sequencing (scRNA-seq) has the potential to identify recurrent patterns of transcription variation related to cancer progression, and produce new therapeutically relevant insights. However, the presence of strong inter-tumor heterogeneity often obscures more subtle patterns that are shared across tumors, some of which may characterize clinically relevant disease subtypes. Here we introduce a new statistical method, generalized binary covariance decomposition (GBCD), to address this problem. We show that GBCD can help decompose transcriptional heterogeneity into interpretable components - including patient-specific, dataset-specific and shared components relevant to disease subtypes - and that, in the presence of strong inter-tumor heterogeneity, it can produce more interpretable results than existing methods. Applied to data from three studies on pancreatic cancer adenocarcinoma (PDAC), GBCD produces a refined characterization of existing tumor subtypes (e.g., classical vs. basal), and identifies a new gene expression program (GEP) that is prognostic of poor survival independent of established prognostic factors such as tumor stage and subtype. The new GEP is enriched for genes involved in a variety of stress responses, and suggests a potentially important role for the integrated stress response in PDAC development and prognosis.

MAFF confers vulnerability to cisplatin-based and ionizing radiation treatments by modulating ferroptosis and cell cycle progression in lung adenocarcinoma

AIMS

Lung cancer is the leading cause of cancer mortality and lung adenocarcinoma (LUAD) accounts for more than half of all lung cancer cases. Tumor elimination is mostly hindered by drug resistance and the mechanisms remain to be explored in LUAD.

METHODS

CRISPR screens in cell and murine models and single-cell RNA sequencing were conducted, which identified MAF bZIP transcription factor F (MAFF) as a critical factor regulating tumor growth and treatment resistance in LUAD. RNA and ChIP sequencing analyses were performed for transcriptional target expression and specific binding sites of MAFF. Functions of MAFF in inhibiting tumor growth and promoting cisplatin or irradiation efficacy were investigated using cellular and xenograft models.

RESULTS

Patients with lung adenocarcinoma and reduced MAFF expression had worse clinical outcomes. MAFF inhibited tumor cell proliferation by regulating the expression of SLC7A11, CDK6, and CDKN2C, promoting ferroptosis and preventing cell cycle progression from G1 to S. MAFF also conferred tumor cells vulnerable to cisplatin-based or ionizing radiation treatments. MAFF reduction was a final event in the acquisition of cisplatin resistance of LUAD cells. The intracellular cAMP/PKA/CREB1 pathway upregulated MAFF in response to cisplatin-based or ionizing radiation treatments.

CONCLUSIONS

MAFF suppresses tumor growth, and pharmacological agonists targeting MAFF may improve cisplatin or irradiation therapies for lung adenocarcinoma patients.

In vitro vascularized immunocompetent patient-derived model to test cancer therapies

This work describes a patient-derived tumoroid model (PDTs) to support precision medicine in lung oncology. The use of human adipose tissue-derived microvasculature and patient-derived peripheral blood mononuclear cells (PBMCs) permits to achieve a physiologically relevant tumor microenvironment. This study involved ten patients at various stages of tumor progression. The vascularized, immune-infiltrated PDT model could be obtained within two weeks, matching the requirements of the therapeutic decision. Histological and transcriptomic analyses confirmed that the main features from the original tumor were reproduced. The 3D tumor model could be used to determine the dynamics of response to antiangiogenic therapy and platinum-based chemotherapy. Antiangiogenic therapy showed a significant decrease in vascular endothelial growth factor (VEGF)-A expression, reflecting its therapeutic effect in the model. In an immune-infiltrated PDT model, chemotherapy showed the ability to decrease the levels of lymphocyte activation gene-3 protein (LAG-3), B and T lymphocyte attenuator (BTLA), and inhibitory receptors of T cells functions.

Integrated single-cell and bulk RNA sequencing revealed the molecular characteristics and prognostic roles of neutrophils in pancreatic cancer

Pancreatic cancer, one of the most prevalent tumors of the digestive system, has a dismal prognosis. Cancer of the pancreas is distinguished by an inflammatory tumor microenvironment rich in fibroblasts and different immune cells. Neutrophils are important immune cells that infiltrate the microenvironment of pancreatic cancer tumors. The purpose of this work was to examine the complex mechanism by which neutrophils influence the carcinogenesis and development of pancreatic cancer and to construct a survival prediction model based on neutrophil marker genes. We incorporated the GSE111672 dataset, comprising RNA expression data from 27,000 cells obtained from 3 patients with PC, and conducted single-cell data analysis. Thorough investigation of pancreatic cancer single-cell RNA sequencing data found 350 neutrophil marker genes. Using The Cancer Genome Atlas (TCGA), GSE28735, GSE62452, GSE57495, and GSE85916 datasets to gather pancreatic cancer tissue transcriptome data, and consistent clustering was used to identify two categories for analyzing the influence of neutrophils on pancreatic cancer. Using the Random Forest algorithm and Cox regression analysis, a survival prediction model for pancreatic cancer was developed, the model showed independent performance for survival prognosis, clinic pathological features, immune infiltration, and drug sensitivity. Multivariate Cox analysis findings revealed that the risk scores derived from predictive models is independent prognostic markers for pancreatic patients. In conclusion, based on neutrophil marker genes, this research created a molecular typing and prognostic grading system for pancreatic cancer, this system was very accurate in predicting the prognosis, tumor immune microenvironment status, and pharmacological treatment responsiveness of pancreatic cancer patients.

AGRN promotes lung adenocarcinoma progression by activating Notch signaling pathway and acts as a therapeutic target

Lung cancer is the main reason for cancer-associated death globally, and lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer. Recently, AGRN is considered playing an vital role in the development of some cancers. However, the regulatory effects and mechanisms of AGRN in LUAD remain elusive. In this study, we clarified the significant upregulation of AGRN expression in LUAD by single-cell RNA sequencing combined with immunohistochemistry. Besides, we confirmed that LUAD patients with high AGRN expression are more susceptible to lymph node metastases and have a worse prognosis by a retrospective study of 120 LUAD patients. Next, we demonstrated that AGRN directly interact with NOTCH1, which results in the release of the intracellular structural domain of NOTCH1 and the subsequent activation of the NOTCH pathway. Moreover, we also found that AGRN promotes proliferation, migration, invasion, EMT and tumorigenesis of LUAD cells in vitro and in vivo, and that these effects are reversed by blocking the NOTCH pathway. Furthermore, we prepared several antibodies targeting AGRN, and clarify that Anti-AGRN antibody treatment could significantly inhibit proliferation and promote apoptosis of tumor cells. Our study highlights the important role and regulatory mechanism of AGRN in LUAD development and progression, and suggests that antibodies targeting AGRN have therapeutic potential for LUAD. We also provide theoretical and experimental evidence for further development of monoclonal antibodies targeting AGRN.

Characterization of Infiltrating Immune Cells and Secretory or Membrane-Associated Proteins in KRAS Lung Adenocarcinoma

Background

This study identified the expression and prognosis significance of secretory or membrane-associated proteins in KRAS lung adenocarcinoma (LUAD) and depicted the characteristics between the immune cell infiltration and the expression of these genes.

Methods

Gene expression data of LUAD samples (n = 563) were accessed from The Cancer Genome Atlas (TCGA). The expression of secretory or membrane-associated proteins was compared among the KRAS-mutant, wild-type, and normal groups, as well as the subgroup of the KRAS-mutant group. We identified the survival-related differentially expressed secretory or membrane-associated proteins and conducted the functional enrichment analysis. Then, the characterization and association between their expression and the 24 immune cell subsets were investigated. We also constructed a scoring model to predict KRAS mutation by LASSO and logistic regression analysis.

Results

Secretory or membrane-associated genes with differential expression (n = 74) across three groups (137 KRAS LUAD, 368 wild-type LUAD, and 58 normal groups) were identified, and the results of GO and KEGG indicated that they were strongly associated with immune cell infiltrations. Among them, ten genes were significantly related to the survival of patients with KRAS LUAD. The expression of IL37, KIF2, INSR, and AQP3 had the most significant correlations with immune cell infiltration. In addition, eight DEGs from the KRAS subgroups were highly correlated with immune infiltrations, especially TNFSF13B. Using LASSO-logistic regression, a KRAS mutation prediction model based on the 74 differentially expressed secretory or membrane-associated genes was built, and the accuracy was 0.79.

Conclusion

The research investigated the relationship between the expression of KRAS-related secretory or membrane-associated proteins in LUAD patients with prognostic prediction and immune infiltration characterization. Our study demonstrated that secretory or membrane-associated genes were closely associated with the survival of KRAS LUAD patients and were strongly correlated to immune cell infiltration.

Hepatic nuclear factor 4 alpha promotes the ferroptosis of lung adenocarcinoma via transcriptional activation of cytochrome P450 oxidoreductase

Background

Lung adenocarcinoma is one of the most prevalent cancers while ferroptosis is crucial for cancer therapies. This study aims to investigate the function and mechanism of hepatic nuclear factor 4 alpha (HNF4A) in lung adenocarcinomas' ferroptosis.

Materials and Methods

HNF4A expression in ferroptotic A549 cells was detected. Then HNF4A was knocked down in A549 cells while overexpressed in H23 cells. Cells with changed HNF4A expression were tested for cytotoxicity and the level of cellular lipid peroxidation. The expression of cytochrome P450 oxidoreductase (POR) expression was examined after HNF4A was knocked down or overexpressed. Chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) and dual-luciferase assays were performed to validate the regulation of HNF4A on POR. Finally, POR was restored in HNF4A-altered cells to check whether it restores the effect of HNF4A on ferroptosis.

Results

We found that HNF4A expression significantly decreased in the ferroptosis of A549 cells, and this change can be blocked by deferoxamine, an inhibitor of ferroptosis. Knockdown of HNF4A inhibited ferroptosis in A549 cells while overexpression of HNF4A promoted ferroptosis in H23 cells. We identified a key ferroptosis-related gene, POR serves as a potential target gene of HNF4A, whose expression was significantly changed in lung adenocarcinoma cells knocking down or overexpressing HNF4A. We demonstrated that HNF4A was bound to the POR's promoter to enhance POR expression, and identified the binding sites via ChIP-qPCR and luciferase assays. Restoration of POR expression blocked the promoting effect of HNF4A on ferroptosis in lung adenocarcinoma.

Conclusion

HNF4A promotes POR expression through binding to the POR's promoter, and subsequently promotes the ferroptosis of lung adenocarcinoma.

HNF4G increases cisplatin resistance in lung adenocarcinoma via the MAPK6/Akt pathway

Background

Lung adenocarcinoma is one of the most common tumors, and cisplatin is frequently used in treating lung adenocarcinoma patients. This study aimed to look into the roles and mechanisms of HNF4G in cisplatin resistance of lung adenocarcinoma.

Materials & Methods

Cisplatin resistance and gene expression data of 542 cell lines from the CTRP and CCLE databases were analyzed. HNF4G expression was detected in the lung adenocarcinoma cell lines after treatment with various concentrations of cisplatin. Cisplatin sensitivity curves were detected in cells that overexpressed or knocked down HNF4G. The ChIP-Seq data were then analyzed to identify the targets of HNF4G involved in cisplatin resistance. Expression and phosphorylation of the MAPK6/Akt pathway were detected after HNF4G was overexpressed or knocked down. Finally, ChIP-qPCR and dual-luciferase assays were used to investigate the regulation of HNF4G on MAPK6.

Results

In cell lines, high expression of HNF4G was significantly positively correlated with cisplatin resistance, and lung adenocarcinoma patients who had high HNF4G expression had a poor prognosis. Cisplatin treatment increased HNF4G expression, and overexpression of HNF4G significantly increased the resistance to cisplatin in A549 and HCC827 cells, whereas knockdown of HNF4G had the opposite effect. HNF4G overexpression increased MAPK6 expression and activated the MAPK6/Akt pathway, while an Akt inhibitor reduced the effects of HNF4G on cisplatin resistance. HNF4G bound to the MAPK6 promoter region, promoting MAPK6 expression, according to ChIP-qPCR and luciferase assays.

Conclusion

By binding to the MAPK6 promoter region, HNF4G promotes MAPK6 expression and subsequent Akt phosphorylation, resulting in resistance to cisplatin in lung adenocarcinoma.

Development of a ferroptosis-based model to predict prognosis, tumor microenvironment, and drug response for lung adenocarcinoma with weighted genes co-expression network analysis

Objective: The goal of this study was to create a risk model based on the ferroptosis gene set that affects lung adenocarcinoma (LUAD) patients' prognosis and to investigate the potential underlying mechanisms. Material and Methods: A cohort of 482 LUAD patients from the TCGA database was used to develop the prognostic model. We picked the module genes from the ferroptosis gene set using weighted genes co-expression network analysis (WGCNA). The least absolute shrinkage and selection operator (LASSO) and univariate cox regression were used to screen the hub genes. Finally, the multivariate Cox analysis constructed a risk prediction score model. Three other cohorts of LUAD patients from the GEO database were included to validate the prediction ability of our model. Furthermore, the differentially expressed genes (DEG), immune infiltration, and drug sensitivity were analyzed. Results: An eight-gene-based prognostic model, including PIR, PEBP1, PPP1R13L, CA9, GLS2, DECR1, OTUB1, and YWHAE, was built. The patients from the TCGA database were classified into the high-RS and low-RS groups. The high-RS group was characterized by poor overall survival (OS) and less immune infiltration. Based on clinical traits, we separated the patients into various subgroups, and RS had remarkable prediction performance in each subgroup. The RS distribution analysis demonstrated that the RS was significantly associated with the stage of the LUAD patients. According to the study of immune cell infiltration in both groups, patients in the high-RS group had a lower abundance of immune cells, and less infiltration was associated with worse survival. Besides, we discovered that the high-RS group might not respond well to immune checkpoint inhibitors when we analyzed the gene expression of immune checkpoints. However, drug sensitivity analysis suggested that high-RS groups were more sensitive to common LUAD agents such as Afatinib, Erlotinib, Gefitinib, and Osimertinib. Conclusion: We constructed a novel and reliable ferroptosis-related model for LUAD patients, which was associated with prognosis, immune cell infiltration, and drug sensitivity, aiming to shed new light on the cancer biology and precision medicine.

A Novel Prognostic Signature Revealed the Interaction of Immune Cells in Tumor Microenvironment Based on Single-Cell RNA Sequencing for Lung Adenocarcinoma

Background

The tumor immune microenvironment (TIME) played an important role in immunotherapy prognosis and treatment response. Immune cells constitute a large part of the tumor microenvironment and regulate tumor progression. Our research is dedicated to studying the infiltrating immune cell in lung adenocarcinoma (LUAD) and seeking potential targets.

Methods

The scRNA-seq data were collected from our FDZSH and two public datasets. The code for cell-type mapping algorithms was downloaded from the CIBERSORTx portal. The bioinformatics data of LUAD patients could be approached from The Cancer Genome Atlas (TCGA) portal. Weighted gene coexpression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analyses were performed to construct a risk model. TIMER2 and TIDE helped with the immune infiltration estimation, while PROGENy helped the cancer-related pathways' enrichment analysis. GSE31210 dataset and IMVigor ICB therapy cohort validated our findings as the external validation datasets.

Results

We clustered the scRNA-seq dataset (integrating our FDZSH datasets and other public datasets) into 23 subpopulations. After curated cell annotation, we implemented Cibersort and WGCNA analysis to anchor the brown module and natural killer cell cluster1 due to the most relationship with tumor trait. The overlap of the brown module gene, natural killer cell signature, and DEGs of tumor and adjacent normal samples was screened by LASSO Cox regression. The obtained 5-gene risk model showed an excellent prognostic performance in the validation dataset. Furthermore, there was a correlation between risk score and tumor-infiltrating immune cells and tumor genomics abnormity. Patients with higher risk scores had a significantly lower immunotherapy response rate.

Conclusion

Our observations implied that immune cells played a pivotal role in TIME and established a 5-gene signature (including IDH2, ADRB2, SFTPC, CCDC69, and CCND2) on the basement of nature killer markers targeted by WGCNA analysis. The significance of clinical outcome and immunotherapy response prediction was validated robustly.

Identification of Significant Secreted or Membrane-Located Proteins in Laryngeal Squamous Cell Carcinoma

Background. This study is aimed at investigating the expressions and prognostic values of secreted or membrane-located proteins (SMPs) in laryngeal squamous cell carcinoma (LSCC). The correlations between the expressions of SMPs and immune cells’ infiltrations were also investigated. Methods. The expression data of normal laryngeal and LSCC samples were obtained from the TCGA and GEO datasets. The differentially expressed SMPs were identified, and their prognostic values were analyzed. The biological functions of differentially expressed and worse-survival-related SMPs were explored. LASSO regression, Cox multivariate analysis, and nomogram were used to construct a model to predict the survival. Then, the infiltrations of the 24 immune cell populations were calculated using the GSVA method, and the correlations between the expression of SMPs and the immune infiltration were investigated. Results. 122 samples (12 normal and 120 LSCC) of the TCGA database and 114 samples (57 normal and 57 LSCC) of GSE127165 were included. We identified that 138 SMPs were significantly upregulated in LSCC samples of both the TCGA and GEO datasets, among which 52 SMPs were significantly correlated with worse survival. GO and KEGG analyses revealed those 52 SMPs significantly participate in tumor microenvironment and immune cells’ communication. Nine of 52 SMPs (ABCC5, ATP1B3, CLEC11A, FLNA, FSTL3, MMP1, NME1, OAS3, and PHLDB2) were included in the nomogram to effectively and accurately predict the LSCC patients’ survival. The expressions of most SMPs, such as MMP1 and FSTL3, were significantly positively correlated with the immune infiltration of LSCC. Conclusions. In this study, the expression, prognostic values, and correlations with immune infiltration of SMPs were analyzed in LSCC samples. Our analyses identified several significant SMPs differentially expressed between normal laryngeal and LSCC samples, correlated with worse survival, and related to the immune infiltration.