IRF1 Negatively Regulates Oncogenic KPNA2 Expression Under Growth Stimulation and Hypoxia in Lung Cancer Cells

A novel immunogenomic classification for prognosis in non-small cell lung cancer

OBJECTIVE

To facilitate immunotherapy and prognostic assessment of non-small cell lung cancer (NSCLC), we established a novel immunogenomic classification to provide valid identification criteria.

METHODS

The immune enrichment scores were calculated by single sample gene set enrichment analysis (ssGSEA) and clustered into Immunity_L and Immunity_H, and the reliability of this classification was demonstrated. Immune microenvironment score and immune cell infiltration analysis of NSCLC were also performed. Randomly divided into training group and test group, a prognosis-related immune profile was developed using least absolute shrinkage and selection operator (LASSO) and stepwise COX proportional hazards model to construct a prognostic mode.

RESULTS

The risk score for this immune profile was identified as an independent prognostic factor and can be used as a powerful prognostic tool to refine tumor immunotherapy. Our study identified two NSCLC classifications based on immunomic profiling, Immunity_H and Immunity_L.

CONCLUSION

In conclusion, Immunogenomic classification can distinguish the immune status of different types of NSCLC patients and contribute to the immunotherapy of NSCLC patients.

Risk factors and actionable molecular signatures in COVID-19-associated lung adenocarcinoma and lung squamous cell carcinoma patients

The molecular mechanism of COVID-19's pathogenic effect on lung cancer patients is yet unknown. In this study, we used differential gene expression pattern analysis to try to figure out the possible disease mechanism of COVID-19 and its associated risk factors in patients with the two most common types of non-small-cell lung cancer, lung adenocarcinoma and lung squamous cell carcinoma. We also used network-based approaches to identify potential diagnostic and molecular targets for COVID-19-infected lung cancer patients. Our study showed that lung cancer and COVID-19 patients share 36 genes that are expressed differently and in common. Most of these genes are expressed in lung tissues and are mostly involved in the pathogenesis of different respiratory tract diseases. Additionally, we also found that COVID-19 may affect the expression of several cancer-associated genes in lung cancer patients, such as the oncogenes JUN, TNC, and POU2AF1. Moreover, we also reported that COVID-19 may predispose lung cancer patients to other diseases like acute liver failure and respiratory distress syndrome. Also, our findings in concert with published literature suggest that molecular signatures like hsa-mir-93-5p, CCNB2, IRF1, CD163, and different immune cell-based approaches could help both diagnose and treat this group of patients. Overall, the scientific results of this research will aid in the formulation of suitable management strategies as well as the development of diagnostic and therapeutic methods for COVID-19-infected lung cancer patients.

Development and validation of a genomic nomogram based on a ceRNA network for comprehensive analysis of obstructive sleep apnea

Objectives: Some ceRNA associated with lncRNA have been considered as possible diagnostic and therapeutic biomarkers for obstructive sleep apnea (OSA). We intend to identify the potential hub genes for the development of OSA, which will provide a foundation for the study of the molecular mechanism underlying OSA and for the diagnosis and treatment of OSA.

Methods: We collected plasma samples from OSA patients and healthy controls for the detection of ceRNA using a chip. Based on the differential expression of lncRNA, we identified the target genes of miRNA that bind to lncRNAs. We then constructed lncRNA-related ceRNA networks, performed functional enrichment analysis and protein-protein interaction analysis, and performed internal and external validation of the expression levels of stable hub genes. Then, we conducted LASSO regression analysis on the stable hub genes, selected relatively significant genes to construct a simple and easy-to-use nomogram, validated the nomogram, and constructed the core ceRNA sub-network of key genes.

Results: We successfully identified 282 DElncRNAs and 380 DEmRNAs through differential analysis, and we constructed an OSA-related ceRNA network consisting of 292 miRNA-lncRNAs and 41 miRNA-mRNAs. Through PPI and hub gene selection, we obtained 7 additional robust hub genes, CCND2, WT1, E2F2, IRF1, BAZ2A, LAMC1, and DAB2. Using LASSO regression analysis, we created a nomogram with four predictors (CCND2, WT1, E2F2, and IRF1), and its area under the curve (AUC) is 1. Finally, we constructed a core ceRNA sub-network composed of 74 miRNA-lncRNA and 7 miRNA-mRNA nodes.

Conclusion: Our study provides a new foundation for elucidating the molecular mechanism of lncRNA in OSA and for diagnosing and treating OSA.

KPNA2 promotes angiogenesis by regulating STAT3 phosphorylation

PURPOSE

Angiogenesis is involved in many pathological and physiological processes and is mainly driven by hypoxia. Karyopherin subunit alpha 2 (KPNA2), a member of the nuclear transport protein family, was recently shown to be induced by hypoxia in various types of tumours, so we aimed to investigate the role and mechanism of KPNA2 in angiogenesis under hypoxia.

MATERIALS AND METHODS

After overexpression or knockdown of KPNA2 in human umbilical vein endothelial cells (HUVEC) by adenovirus vector infection, the tube formation, proliferation and migration of HUVEC under hypoxia were detected by tubule formation assay, 5-ethynyl-2'-deoxyuridine (EdU) staining and Transwell assay, respectively. After overexpression or knockdown of KPNA2 in a murine hindlimb ischemia model by local injection of purified adenovirus vector into the gastrocnemius muscle, blood flow changes were examined with a laser Doppler system. Changes in KPNA2-binding proteins under hypoxia were detected by immunoprecipitation-mass spectrometry (IP-MS) and co-immunoprecipitation (Co-IP). The effect of KPNA2 on signal transducer and activator of transcription 3 (STAT3) was detected by Western blotting and quantitative RT‒PCR.

RESULTS

KPNA2 was upregulated in the HUVEC hypoxia model and murine hindlimb ischemia model. Overexpression of KPNA2 increased the proliferation, migration and tube formation of HUVEC under hypoxia, while knockdown of KPNA2 reduced the proliferation, migration and tube formation of HUVEC. Overexpression of KPNA2 promoted the restoration of blood flow in the murine hindlimb ischemia model, while knockout of KPNA2 inhibited the restoration of blood flow in the murine hindlimb ischemia model. Mechanistically, hypoxia promoted the binding of STAT3 to KPNA2. Overexpression of KPNA2 promoted STAT3 phosphorylation and then upregulated vascular endothelial growth factor (VEGF) and angiopoietin 2(ANGPT2), whereas knockdown of KPNA2 inhibited STAT3 phosphorylation and then downregulated VEGF and ANGPT2.

CONCLUSION

Our study demonstrates that hypoxia promotes the binding of STAT3 to KPNA2 and KPNA2 promotes angiogenesis under hypoxia by promoting the binding of STAT3 and JAK1 and regulating STAT3 phosphorylation.

Identification of ZDHHC1 as a Pyroptosis Inducer and Potential Target in the Establishment of Pyroptosis-Related Signature in Localized Prostate Cancer

Pyroptosis or cellular inflammatory necrosis is a programmed cell death kind. Accumulating evidence shows that pyroptosis plays a crucial role in the invasion, metastasis, and proliferation of tumor cells, thus affecting the prognosis of tumors and therapeutic effects. Prostate cancer (PCa), a common malignancy among men, is associated with inflammation. Pathophysiological effects of pyroptosis on tumor development and progression, as well as the mediation of PCa, are known, but its effects on the potential prognosis for PCa warrant in-depth investigation. Herein, we built a risk model of six pyroptosis-related genes and verified their predictive abilities for prognostic and therapeutic effects. Higher risk scores indicated a higher probability of biochemical recurrence (BCR), higher immune infiltration, and worsened clinicopathological features. To derive scientific and reliable predictions for BCR in patients having PCa, the findings of the current study were verified in the Gene Expression Omnibus (GEO) cohort following evaluation in The Cancer Genome Atlas (TCGA) dataset. Additionally, after evaluating the six genes in the model, ZDHHC1 was found to be an important component. Its antitumor role was further assessed through in vivo and in vitro experiments, and its promoting effect on pyroptosis was further evaluated and verified. The above results provided a new perspective for further studies on pyroptosis and its clinical utility for PCa.

Construction of Prognostic Risk Model for Small Cell Lung Cancer Based on Immune-Related Genes

Small cell lung cancer (SCLC) is a highly invasive and fatal malignancy. Research at the present stage implied that the expression of immune-related genes is associated with the prognosis in SCLC. Accordingly, it is essential to explore effective immune-related molecular markers to judge prognosis and treat SCLC. Our research obtained SCLC dataset from Gene Expression Omnibus (GEO) and subjected mRNAs in it to differential expression analysis. Differentially expressed mRNAs (DEmRNAs) were intersected with immune-related genes to yield immune-related differentially expressed genes (DEGs). The functions of these DEGs were revealed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Thereafter, we categorized 3 subtypes of immune-related DEGs via K-means clustering. Kaplan-Meier curves analyzed the effects of 3 subtypes on SCLC patients' survival. Single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE validated that the activation of different immune gene subtypes differed significantly. Finally, an immune-related-7-gene assessment model was constructed by univariate-Lasso-multiple Cox regression analyses. Riskscores, Kaplan-Meier curves, receiver operating characteristic (ROC) curves, and independent prognostic analyses validated the prognostic value of the immune-related-7-gene assessment model. As suggested by GSEA, there was a prominent difference in cytokine-related pathways between high- and low-risk groups. As the analysis went further, we discovered a statistically significant difference in the expression of human leukocyte antigen (HLA) proteins and costimulatory molecules expressed on the surface of CD274, CD152, and T lymphocytes in different groups. In a word, we started with immune-related genes to construct the prognostic model for SCLC, which could effectively evaluate the clinical outcomes and offer guidance for the treatment and prognosis of SCLC patients.

IRF2 Destabilizes Oncogenic KPNA2 to Modulate the Development of Osteosarcoma

Osteosarcomas (OS) are the most common primary malignant bone tumor. Emerging evidence revealed that karyopherin alpha 2 (KPNA2) was strongly associated with the tumorigenesis and development of numerous human cancers. The aim of the present study was to investigate the expression pattern, biological functions, and underlying mechanism of KPNA2 in OS. Bioinformatics TFBIND online was applied to forecast transcription factor (TF) binding sites in the promoter region of KPNA2. The expression profile of KPNA2 in OS tissues were firstly assessed. CCK8, colony formation, wound healing, and Transwell assays were used to assess cell viability, proliferation, and migration in vitro, and in vivo experiments were performed to explore the effects of KPNA2 and interferon regulatory factor-2 (IRF2) on tumor growth. Furthermore, the correlation between IRF2 and KPNA2 was investigated using chromatin immunoprecipitation (ChIP), RT-qPCR, western blot, and dual-luciferase assays. KPNA2 was obviously upregulated, while IRF2 decreased significantly in OS tissues and cell lines, as well as negatively correlated with each other. KPNA2 removal remarkably suppressed OS cell growth, migration, invasion in vitro, and tumor growth in vivo, while IRF2 knockdown exerts an opposing effect. IRF2 binds to the KPNA2 promoter to modulate the malignant phenotypes of OS cells by regulating epithelial-to-mesenchymal transition (EMT). The present study demonstrated that KPNA2 performed the oncogenic function, possibly regulating tumor development through EMT. Importantly, it was confirmed that IRF2 serves as a potential upstream TF of KPNA2 involved in the regulation of EMT progress in OS.

Integrated single-cell RNA sequencing analysis reveals distinct cellular and transcriptional modules associated with survival in lung cancer

Lung adenocarcinoma (LUAD) and squamous carcinoma (LUSC) are two major subtypes of non-small cell lung cancer with distinct pathologic features and treatment paradigms. The heterogeneity can be attributed to genetic, transcriptional, and epigenetic parameters. Here, we established a multi-omics atlas, integrating 52 single-cell RNA sequencing and 2342 public bulk RNA sequencing. We investigated their differences in genetic amplification, cellular compositions, and expression modules. We revealed that LUAD and LUSC contained amplifications occurring selectively in subclusters of AT2 and basal cells, and had distinct cellular composition modules associated with poor survival of lung cancer. Malignant and stage-specific gene analyses further uncovered critical transcription factors and genes in tumor progression. Moreover, we identified subclusters with proliferating and differentiating properties in AT2 and basal cells. Overexpression assays of ten genes, including sub-cluster markers AQP5 and KPNA2, further indicated their functional roles, providing potential targets for early diagnosis and treatment in lung cancer.

Nuclear accumulation of KPNA2 impacts radioresistance through positive regulation of the PLSCR1-STAT1 loop in lung adenocarcinoma

Lung adenocarcinoma (ADC) is the predominant histological type of lung cancer, and radiotherapy is one of the current therapeutic strategies for lung cancer treatment. Unfortunately, biological complexity and cancer heterogeneity contribute to radioresistance development. Karyopherin α2 (KPNA2) is a member of the importin α family that mediates the nucleocytoplasmic transport of cargo proteins. KPNA2 overexpression is observed across cancer tissues of diverse origins. However, the role of KPNA2 in lung cancer radioresistance is unclear. Herein, we demonstrated that high expression of KPNA2 is positively correlated with radioresistance and cancer stem cell (CSC) properties in lung ADC cells. Radioresistant cells exhibited nuclear accumulation of KPNA2 and its cargos (OCT4 and c‐MYC). Additionally, KPNA2 knockdown regulated CSC‐related gene expression in radioresistant cells. Next‐generation sequencing and bioinformatic analysis revealed that STAT1 activation and nuclear phospholipid scramblase 1 (PLSCR1) are involved in KPNA2‐mediated radioresistance. Endogenous PLSCR1 interacting with KPNA2 and PLSCR1 knockdown suppressed the radioresistance induced by KPNA2 expression. Both STAT1 and PLSCR1 were found to be positively correlated with dysregulated KPNA2 in radioresistant cells and ADC tissues. We further demonstrated a potential positive feedback loop between PLSCR1 and STAT1 in radioresistant cells, and this PLSCR1‐STAT1 loop modulates CSC characteristics. In addition, AKT1 knockdown attenuated the nuclear accumulation of KPNA2 in radioresistant lung cancer cells. Our results collectively support a mechanistic understanding of a novel role for KPNA2 in promoting radioresistance in lung ADC cells.

Analyses of DNA Methylation Involved in the Activation of Nuclear Karyopherin Alpha 2 Leading to Identify the Progression and Prognostic Significance Across Human Breast Cancer

Background

Karyopherin alpha 2 (KPNA2) is a nuclear import factor that plays a crucial role in nucleocytoplasmic transport, as well as cell proliferation, migration, and invasion in several cancers. However, the roles of KPNA2 in breast cancer as well as the underlying molecular mechanisms have not been elucidated.

Materials and Methods

To evaluate gene expression alterations during breast carcinogenesis, KPNA2 expression was analyzed using the Gene Expression Profiling Interactive Analysis and Oncomine analyses. The correlation between methylation and expression was analyzed using the MEXPRESS tool, UALCAN cancer database, and cBioPortal browser. Then, the expression and prognostic value of KPNA2 were investigated by our own breast cancer samples using RT-PCR. KPNA2 methylation level was detected by methylation-specific PCR.

Results

We obtained the following important results. (1) KPNA2 expression was significantly higher in breast cancer than normal samples and regulated by aberrant DNA hypomethylation of promoter region. (2) Among patients with breast cancer, those with higher KPNA2 expression had a lower survival rate. (3) The major mutation type of KPNA2 in breast cancer samples was missense mutation. (4) Homer1 was able to promote breast cancer progression may be through upregulating TPX2 expression.

Conclusion

Our findings suggest that aberrant DNA hypomethylation of promoter regions contributes to the aberrant expression of KPNA2 in breast cancer, which might be a potential indicator of poor prognosis.