IRF8 induces senescence of lung cancer cells to exert its tumor suppressive function

Machine-learning and combined analysis of single-cell and bulk-RNA sequencing identified a DC gene signature to predict prognosis and immunotherapy response for patients with lung adenocarcinoma

BACKGROUND

Innate immune effectors, dendritic cells (DCs), influence cancer prognosis and immunotherapy significantly. As such, dendritic cells are important in killing tumors and influencing tumor microenvironment, whereas their roles in lung adenocarcinoma (LUAD) are largely unknown.

METHODS

In this study, 1658 LUAD patients from different cohorts were included. In addition, 724 cancer patients who received immunotherapy were also included. To identify DC marker genes in LUAD, we used single-cell RNAsequencing data for analysis and determined 83 genes as DC marker genes. Following that, integrative machine learning procedure was developed to construct a signature for DC marker genes.

RESULTS

Using TCGA bulk-RNA sequencing data as the training set, we developed a signature consisting of seven genes and classified patients by their risk status. Another six independent cohorts demonstrated the signature' s prognostic power, and multivariate analysis demonstrated it was an independent prognostic factor. LUAD patients in the high-risk group displayed more advanced features, discriminatory immune-cell infiltrations and immunosuppressive states. Cell-cell communication analysis indicates that tumor cells with lower risk scores communicate more actively with the tumor microenvironment. Eight independent immunotherapy cohorts revealed that patients with low-risk had better immunotherapy responses. Drug sensitivity analysis indicated that targeted therapy agents exhibited greater sensitivity to low-risk patients, while chemotherapy agents displayed greater sensitivity to high-risk patients. In vitro experiments confirmed that CTSH is a novel protective factor for LUAD.

CONCLUSIONS

An unique signature based on DC marker genes that is highly predictive of LUAD patients' prognosis and response to immunotherapy. CTSH is a new biomarker for LUAD.

Targeting cGAS/STING signaling-mediated myeloid immune cell dysfunction in TIME

Myeloid immune cells (MICs) are potent innate immune cells serving as first responders to invading pathogens and internal changes to cellular homeostasis. Cancer is a stage of altered cellular homeostasis that can originate in response to different pathogens, chemical carcinogens, and internal genetic/epigenetic changes. MICs express several pattern recognition receptors (PRRs) on their membranes, cytosol, and organelles, recognizing systemic, tissue, and organ-specific altered homeostasis. cGAS/STING signaling is a cytosolic PRR system for identifying cytosolic double-stranded DNA (dsDNA) in a sequence-independent but size-dependent manner. The longer the cytosolic dsDNA size, the stronger the cGAS/STING signaling activation with increased type 1 interferon (IFN) and NF-κB-dependent cytokines and chemokines' generation. The present article discusses tumor-supportive changes occurring in the tumor microenvironment (TME) or tumor immune microenvironment (TIME) MICs, specifically emphasizing cGAS/STING signaling-dependent alteration. The article further discusses utilizing MIC-specific cGAS/STING signaling modulation as critical tumor immunotherapy to alter TIME.

Genome-wide DNA methylation profiling of HPV-negative leukoplakia and gingivobuccal complex cancers

BACKGROUND

Gingivobuccal complex oral squamous cell carcinoma (GBC-OSCC) is an aggressive malignancy with high mortality often preceded by premalignant lesions, including leukoplakia. Previous studies have reported genomic drivers in OSCC, but much remains to be elucidated about DNA methylation patterns across different stages of oral carcinogenesis.

RESULTS

There is a serious lack of biomarkers and clinical application of biomarkers for early detection and prognosis of gingivobuccal complex cancers. Hence, in search of novel biomarkers, we measured genome-wide DNA methylation in 22 normal oral tissues, 22 leukoplakia, and 74 GBC-OSCC tissue samples. Both leukoplakia and GBC-OSCC had distinct methylation profiles as compared to normal oral tissue samples. Aberrant DNA methylation increases during the different stages of oral carcinogenesis, from premalignant lesions to carcinoma. We identified 846 and 5111 differentially methylated promoters in leukoplakia and GBC-OSCC, respectively, with a sizable fraction shared between the two sets. Further, we identified potential biomarkers from integrative analysis in gingivobuccal complex cancers and validated them in an independent cohort. Integration of genome, epigenome, and transcriptome data revealed candidate genes with gene expression synergistically regulated by copy number and DNA methylation changes. Regularised Cox regression identified 32 genes associated with patient survival. In an independent set of samples, we validated eight genes (FAT1, GLDC, HOXB13, CST7, CYB5A, MLLT11, GHR, LY75) from the integrative analysis and 30 genes from previously published reports. Bisulfite pyrosequencing validated GLDC (P = 0.036), HOXB13 (P < 0.0001) promoter hypermethylation, and FAT1 (P < 0.0001) hypomethylation in GBC-OSCC compared to normal controls.

CONCLUSIONS

Our findings identified methylation signatures associated with leukoplakia and gingivobuccal complex cancers. The integrative analysis in GBC-OSCC identified putative biomarkers that enhance existing knowledge of oral carcinogenesis and may potentially help in risk stratification and prognosis of GBC-OSCC.

Oligosaccharides from Sargassum thunbergii inhibit osteoclast differentiation via regulation of IRF-8 signaling

Osteoporosis (OP) is a systemic bone degenerative disease characterized by low bone mass and deteriorated microarchitecture of bone tissue, causing high morbidity and mortality rates. Bone resorption by overactivated osteoclasts (OCs) is the main cause of osteoporosis. Glucuronomannan and its oligomers (Gs) and their sulfated derivatives (SGs) were previously prepared. The anti-osteoporosis activities of these glycans were evaluated. Firstly, we determined the viability of RAW264.7 by CCK-8 test. Nextly, we investigated the inhibitory effects of Gs and SGs on the differentiation of RAW264.7 cells into OCs using tartrate-resistant acid phosphatase (TRAP) staining, F-actin ring staining, qualitative reverse-transcription polymerase chain reaction(qRT-PCR) and western blotting. TRAP staining revealed that Gs significantly blocked RANKL-induced OC generation while SGs did not exhibit this ability. F-actin staining assays demonstrated that Gs inhibits RANKL-induced actin ring formation. qRT-PCR analyses indicated that Gs dose-dependently inhibited the expression of OCs marker genes including Trap, NFATc1, c-Fos, DC-Stamp and ATP60 during the differentiation process, while SGs did not suppress. Regarding the mechanism of Gs, it was found that Gs suppressed osteoclastogenesis via inhibiting the degradation of IRF-8 and interfering with NF-κB pathway activation. Together, these results suggest that Gs have the ability to inhibit osteoclastogenesis by modulating IRF-8 signaling.

IRF8 Regulates Intrinsic Ferroptosis through Repressing p53 Expression to Maintain Tumor Cell Sensitivity to Cytotoxic T Lymphocytes

Ferroptosis has emerged as a cytotoxic T lymphocyte (CTL)-induced tumor cell death pathway. The regulation of tumor cell sensitivity to ferroptosis is incompletely understood. Here, we report that interferon regulatory factor 8 (IRF8) functions as a regulator of tumor cell intrinsic ferroptosis. Genome-wide gene expression profiling identified the ferroptosis pathway as an IRF8-regulated pathway in tumor cells. IRF8.KO tumor cells acquire resistance to intrinsic ferroptosis induction and IRF8-deficient tumor cells also exhibit decreased ferroptosis in response to tumor-specific CTLs. Irf8 deletion increased p53 expression in tumor cells and knocking out p53 in IRF8.KO tumor cells restored tumor cell sensitivity to intrinsic ferroptosis induction. Furthermore, IRF8.KO tumor cells grew significantly faster than WT tumor cells in immune-competent mice. To restore IRF8 expression in tumor cells, we designed and synthesized codon usage-optimized IRF8-encoding DNA to generate IRF8-encoding plasmid NTC9385R-mIRF8. Restoring IRF8 expression via a lipid nanoparticle-encapsulated NTC9385R-mIRF8 plasmid therapy suppressed established tumor growth in vivo. In human cancer patients, nivolumab responders have a significantly higher IRF8 expression level in their tumor cells as compared to the non-responders. Our data determine that IRF8 represses p53 expression to maintain tumor cell sensitivity to intrinsic ferroptosis.

IRF8: Mechanism of Action and Health Implications

Interferon regulatory factor 8 (IRF8) is a transcription factor of the IRF protein family. IRF8 was originally identified as an essentialfactor for myeloid cell lineage commitment and differentiation. Deletion of Irf8 leads to massive accumulation of CD11b⁺Gr1⁺ immature myeloid cells (IMCs), particularly the CD11b⁺Ly6C^hi/+Ly6G⁻ polymorphonuclear myeloid-derived suppressor cell-like cells (PMN-MDSCs). Under pathological conditions such as cancer, Irf8 is silenced by its promoter DNA hypermethylation, resulting in accumulation of PMN-MDSCs and CD11b⁺ Ly6G⁺Ly6C^lo monocytic MDSCs (M-MDSCs) in mice. IRF8 is often silenced in MDSCs in human cancer patients. MDSCs are heterogeneous populations of immune suppressive cells that suppress T and NK cell activity to promote tumor immune evasion and produce growth factors to exert direct tumor-promoting activity. Emerging experimental data reveals that IRF8 is also expressed in non-hematopoietic cells. Epithelial cell-expressed IRF8 regulates apoptosis and represses Osteopontin (OPN). Human tumor cells may use the IRF8 promoter DNA methylation as a mechanism to repress IRF8 expression to advance cancer through acquiring apoptosis resistance and OPN up-regulation. Elevated OPN engages CD44 to suppress T cell activation and promote tumor cell stemness to advance cancer. IRF8 thus is a transcription factor that regulates both the immune and non-immune components in human health and diseases.

Uncovering of potential molecular markers for cervical squamous cell carcinoma (CESC) based on analysis of methylated-differentially expressed genes

OBJECTIVE

Cervical squamous cell carcinoma (CESC) is a cancer with high mortality caused by human papillomavirus. The aim of this study was to uncover potential CESC biomarkers to help early diagnosis and treatment.

MATERIALS AND METHODS

The mRNA transcriptome data and DNA methylation data were downloaded from database for the identification of differentially expressed mRNAs (DEmRNAs) and DNA methylation analysis. Functional analysis was used to reveal the molecular functions. Then, the association between differential methylation and DEmRNA was analyzed. Protein-protein interaction (PPI) network analysis was performed on the selected differentially methylated genes (DEGs). Subsequently, we analyzed the prognosis and constructed a prognostic risk model. We also performed diagnostic analyses of risk model genes. In addition, we verified the protein expression level of identified DEGs.

RESULTS

1438 DEmRNAs, 1669 differentially methylated sites (DMSs), 46 differentially methylated CpG islands and 53 differential methylation genes (DMGs) were obtained. In PPI, the highest interaction scores were MX2 and IRF8, and their interaction score was 0.928. Interestingly, 5 DMGs were found to be associated with CESC prognosis. In addition, our results demonstrated that high risk score was associated with poor prognosis of CESC. Furthermore, it was found that ZIK1, ZNRF2, HHEX, VCAM1 could be diagnostic molecular markers for CESC.

CONCLUSION

Analysis of methylated-differentially expressed genes may contribute to the identification of early diagnosis and therapeutic targets of CESC. In addition, a prognostic model based on 5 DMGs can be used to predict the prognosis of CESC.

Identification of prognostic candidate signatures by systematically revealing transcriptome characteristics in lung adenocarcinoma with differing tumor microenvironment immune phenotypes

Accumulated evidence shows that tumor microenvironment plays crucial roles in predicting clinical outcomes of lung adenocarcinoma (LUAD). The current study aimed to identify some potentially prognostic signatures by systematically revealing the transcriptome characteristics in LUADs with differing immune phenotypes. LUAD gene expression data were retrieved from the public TCGA and GEO databases, and the transcriptome characteristics were systematically revealed using a comprehensive bioinformatics method including single-sample gene set enrichment analysis, differentially expressed gene (DEG) analysis, protein and protein interaction (PPI) network construction, competitive endogenous RNA (ceRNA) network construction, weighted gene coexpression network analysis and prognostic model establishment. Finally, 1169 key DEGs associated with LUAD immune phenotype, including 88 immune DEGs, were excavated. Five essential and eight immune essential DEGs were separately identified by constructing two PPI networks based on the above DEGs. Totals of 1085 key DElncRNAs and 45 key DEmiRNAs were excavated and one ceRNA network consisting of 26 DEmRNAs, 3 DEmiRNAs and 57 DElncRNAs were established. The most significant gene coexpression module (cor=0.63 and p=3e-55) associated with LUAD immune phenotypes and three genes (FGR, BTK, SPI1) related to the immune cell infiltration were identified. Three robust prognostic signatures including a 9-lncRNA, an 8-lncRNA and an 8-mRNA were established. The areas under the curves of 5-year correlated with overall survival rate were separately 0.7319, 0.7228 and 0.713 in the receiver operating characteristic curve. The findings provide novel insights into the immunological mechanism in LUAD biology and in predicting the prognosis of LUAD patients.

A novel pyroptosis-related gene signature to predict outcomes in laryngeal squamous cell carcinoma

Pyroptosis, a pro-inflammatory form of programmed cell death, is associated with carcinogenesis and progression. However, there is little information concerning pyroptosis-related genes (PRGs) in laryngeal squamous cell carcinoma (LSCC). Herein, we aim to explore the prognostic value of PRGs in LSCC. The expression and clinical data of 47 PRGs in LSCC patients were obtained from The Cancer Genome Atlas. A novel prognostic PRG signature was constructed using least absolute shrinkage and selection operator analysis. Receiver operating characteristic (ROC) curves were drawn, and Kaplan-Meier survival Cox proportional hazard regression analyses were performed to measure the predictive capacity of the PRG signature. Furthermore, we constructed a six-PRG signature to divide LSCC patients into high- and low-risk groups. Patients in the high-risk group had worse overall survival than the low-risk group. The area under the time-dependent ROC curve was 0.696 for 1 year, 0.784 for 3 years, and 0.738 for 5 years. We proved that the PRGs signature was an independent predictor for LSCC. Functional enrichment analysis indicated that several immune-related pathways were significantly enriched in the low-risk group. Consistent with this, patients with low-risk scores had higher immune scores and better immunotherapeutic responses than the high-risk group. In conclusion, we established a novel PRGs signature that can predict outcome and response to immunotherapy of LSCC, pyroptosis may be a potential target for LSCC.

p28-functionalized PLGA nanoparticles loaded with gefitinib reduce tumor burden and metastases formation on lung cancer

Lung cancer is still the main cause of cancer-related deaths worldwide. Its treatment generally includes surgical resection, immunotherapy, radiotherapy, and chemo-targeted therapies such as the application of tyrosine kinase inhibitors. Gefitinib (GEF) is one of them, but its poor solubility in gastric fluids weakens its bioavailability and therapeutic activity. In addition, like all other chemotherapy treatments, GEF administration can cause damage to healthy tissues. Therefore, the development of novel GEF delivery systems to increase its bioavailability and distribution in tumor site is highly demanded. Herein, an innovative strategy for GEF delivery, by functionalizing PLGA nanoparticles with p28 (p28-NPs), a cell-penetrating peptide derived from the bacterial protein azurin, was developed. Our data indicated that p28 potentiates the selective interaction of these nanosystems with A549 lung cancer cells (active targeting). Further p28-NPs delivering GEF (p28-NPs-GEF) were able to selectively reduce the metabolic activity of A549 cells, while no impact was observed in non-tumor cells (16HBE14o-). In vivo studies using A549 subcutaneous xenograft showed that p28-NPs-GEF reduced A549 primary tumor burden and lung metastases formation. Overall, the design of a p28-functionalized delivery nanosystem to effectively penetrate the membranes of cancer cells while deliver GEF could provide a new strategy to improve lung cancer therapy.

Identification of key genes in the tumor microenvironment of lung adenocarcinoma

The tumor microenvironment plays an important role in tumor development and progression, but the role of immune and stromal cells in this environment has not been sufficiently studied. In this study, we aimed to identify key genes associated with the microenvironment of lung adenocarcinoma (LUAD). Raw data for stromal and immune cells in malignant tumors were downloaded from The Cancer Genome Atlas (TCGA). These expression data were used to identify the differentially expressed genes (DEGs) in tissue samples of LUAD with high and low immune scores. A protein-protein interaction (PPI) network based on genes with significant differential expression was constructed. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to functionally annotate putative hub genes. These genes were assessed via Kaplan Meier analysis to determine their correlation with overall survival. In total, we identified 216 DEGs which were correlated with immune and stromal scores, including 30 hub genes which were identified based on the PPI network. Further analysis suggested that the expression levels of 10 of these genes were significantly correlated with overall survival of LUAD patients. These key hub genes included CCR2, CCR5, CD53, CYBB, HCK, IRF8, LCP2, PLEK, PTPRC, and TLR7. Moreover, the expression level of CCR2 was found to have strong prognostic value for LUAD patients. Additionally, high expression of CYBB was also correlated with better survival of patients with LUAD. The results of this study open several new avenues to explore in the treatment of LUAD.

High IRF8 expression correlates with CD8 T cell infiltration and is a predictive biomarker of therapy response in ER-negative breast cancer

Background

Characterization of breast cancer (BC) through the determination of conventional markers such as ER, PR, HER2, and Ki67 has been useful as a predictive and therapeutic tool. Also, assessment of tumor-infiltrating lymphocytes has been proposed as an important prognostic aspect to be considered in certain BC subtypes. However, there is still a need to identify additional biomarkers that could add precision in distinguishing therapeutic response of individual patients. To this end, we focused in the expression of interferon regulatory factor 8 (IRF8) in BC cells. IRF8 is a transcription factor which plays a well-determined role in myeloid cells and that seems to have multiple antitumoral roles: it has tumor suppressor functions; it acts downstream IFN/STAT1, required for the success of some therapeutic regimes, and its expression in neoplastic cells seems to depend on a cross talk between the immune contexture and the tumor cells.

The goal of the present study was to examine the relationship between IRF8 with the therapeutic response and the immune contexture in BC, since its clinical significance in this type of cancer has not been thoroughly addressed.

Methods

We identified the relationship between IRF8 expression and the clinical outcome of BC patients and validated IRF8 as predictive biomarker by using public databases and then performed in silico analysis. To correlate the expression of IRF8 with the immune infiltrate in BC samples, we performed quantitative multiplex immunohistochemistry.

Results

IRF8 expression can precisely predict the complete pathological response to monoclonal antibody therapy or to select combinations of chemotherapy such as FAC (fluorouracil, adriamycin, and cytoxan) in ER-negative BC subtypes. Analysis of immune cell infiltration indicates there is a strong correlation between activated and effector CD8⁺ T cell infiltration and tumoral IRF8 expression.

Conclusions

We propose IRF8 expression as a potent biomarker not only for prognosis, but also for predicting therapy response in ER-negative BC phenotypes. Its expression in neoplastic cells also correlates with CD8⁺ T cell activation and infiltration. Therefore, our results justify new efforts towards understanding mechanisms regulating IRF8 expression and how they can be therapeutically manipulated.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01418-7.

Interferon regulatory factor 6 correlates with the progression of non-small cell lung cancer and can be regulated by miR-320

OBJECTIVES

The expression of interferon regulatory factor 6 (IRF6) has been reported in several cancer types, but its roles underlying the progression of lung cancer have not been detailedly investigated.

METHODS

The pairs of lung cancer tissues and para-carcinoma tissues and The Cancer Genome Atlas database were collected to detect IRF6 expression. Cell counting kit-8, transwell and terminal-deoxynucleoitidyl transferase-mediated nick end labelling assays were used to evaluate cell proliferation, migration and apoptosis.

KEY FINDINGS

A significant up-regulation of IRF6 in both lung adenocarcinoma and lung squamous cell carcinoma tissues compared with normal non-tumor tissues. Subsequently, Immunostaining also revealed that canceration of lung tissues predisposed to evoke IRF6 expression. In vitro experiments revealed the antitumour effects, including growth and migration inhibition, of IRF6 siRNA transfection. Considering miR-320 as an endogenous inhibitor to IRF6, miR-320 mimics transfection led to the inhibition of proliferation and migration of lung cancer cells. However, overexpressed IRF6 neutralized the antineoplastic activities of miR-320 in lung cancer cells.

CONCLUSIONS

The miR-320/IRF6 signalling axis was implicated in pulmonary canceration. miR-320 as an endogenous inhibitor of IRF6 provided a novel therapeutic strategy for the treatment of lung cancer.

Comprehensive Analysis of Novel lncRNA-TF Regulatory Cross Talks and Identification of Core lncRNA-TF Feedback Loops in Sarcoma

Sarcomas are a broad family of cancers that arise from cells of mesenchymal origin in virtually every tissue of the body. Some transcription factors (TFs) have been reported to be involved in the pathogenesis and metastasis of sarcomas. The expression of certain long noncoding RNAs (lncRNAs) has been correlated with the degree of cancer prognosis. There is an urgent need to effectively integrate TFs and lncRNA/microRNA/mRNA regulatory axis and further identify more key regulators that play crucial roles in sarcomas. We performed a network-based computational analysis to investigate the lncRNA-TF cross talks via integrating lncRNA-TF ceRNA interactions and TF-TF protein-protein interactions. Multiple topology analyses were performed to the sarcomas-related global lncRNA-TF network. Several lncRNAs or TFs with central topology structures were identified as key regulators and used to locate a hub-associated lncRNA-TF subnetwork. Three functional modules were identified from the sarcomas-related global lncRNA-TF network, which have shown significant pathway enrichment and prognosis capability. The lncRNAs and TFs of these modules were shown to participate in sarcoma-related biological phenomena through involving in mitogen-activated protein kinases (MAPK), Jak-STAT, and transforming growth factor (TGF-beta) signaling pathways. More importantly, a subset of core lncRNA-TF cross talks that might form positive feedback loops to control biological processes of sarcomas was identified. These core lncRNA-TF positive feedback loops showed more TF binding affinity than other lncRNAs. All the results can help us uncover the molecular mechanism of sarcomas and provide a novel way for diagnosis biomarker and therapeutic target identification.