KLRC3, a Natural Killer receptor gene, is a key factor involved in glioblastoma tumourigenesis and aggressiveness

Distinct mechanisms by which Nrf1 and Nrf2 as drug targets contribute to the anticancer efficacy of cisplatin on hepatoma cells

Cisplatin (cis-Dichlorodiamineplatinum[II], CDDP) is generally accepted as a platinum-based alkylating agent type of the DNA-damaging anticancer drug, which is widely administrated in clinical treatment of many solid tumors. The pharmacological effect of CDDP is mainly achieved by replacing the chloride ion (Cl-) in its structure with H2O to form active substances with the strong electrophilic properties and then react with any nucleophilic molecules, primarily leading to genomic DNA damage and subsequent cell death. In this process, those target genes driven by the consensus electrophilic and/or antioxidant response elements (EpREs/AREs) in their promoter regions are also activated or repressed by CDDP. Thereby, we here examined the expression profiling of such genes regulated by two principal antioxidant transcription factors Nrf1 and Nrf2 (both encoded by Nfe2l1 and Nfe2l2, respectively) in diverse cellular signaling responses to this intervention. The results demonstrated distinct cellular metabolisms, molecular pathways and signaling response mechanisms by which Nrf1 and Nrf2 as the drug targets differentially contribute to the anticancer efficacy of CDDP on hepatoma cells and xenograft tumor mice. Interestingly, the role of Nrf1, rather than Nrf2, is required for the anticancer effect of CDDP, to suppress malignant behavior of HepG2 cells by differentially monitoring multi-hierarchical signaling to gene regulatory networks. To our surprise, it was found there exists a closer relationship of Nrf1α than Nrf2 with DNA repair, but the hyperactive Nrf2 in Nrf1α-∕- cells manifests a strong correlation with its resistance to CDDP, albeit their mechanistic details remain elusive.

Novel molecular insights into pyroptosis in triple-negative breast cancer prognosis and immunotherapy

BACKGROUND

Patients with triple-negative breast cancer (TNBC) often have a poor prognostic outcome. Current treatment strategies cannot benefit all TNBC patients. Previous findings suggested pyroptosis as a novel target for suppressing cancer development, although the relationship between TNBC and pyroptosis-related genes (PRGs) was still unclear.

METHODS

Gene expression data and clinical follow-up of TNBC patients were collected from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). PRGs were screened using weighted gene co-expression network analysis. Cox regression analysis and the least absolute shrinkage and selection operator (i.e. LASSO) technique were applied to construct a pyroptosis-related prognostic risk score (PPRS) model, which was further combined with the clinicopathological characteristics of TNBC patients to develop a survival decision tree and a nomogram. The model was used to calculate the PPRS, and then the overall survival, immune infiltration, immunotherapy response and drug sensitivity of TNBC patients were analyzed based on the PPRS.

RESULTS

The PPRS model was closely related to clinicopathological features and can independently and accurately predict the prognosis of TNBC. According to normalized PPRS, patients in different cohorts were divided into two groups. Compared with the high-PPRS group, the low-PPRS group had significantly higher ESTIMATE (i.e. Estimation of STromal and Immune cells in MAlignantTumours using Expression data) score, immune score and stromal score, and it also had overexpressed immune checkpoints and significantly reduced Tumor Immune Dysfunction and Exclusion (TIDE) score, as well as higher sensitivity to paclitaxel, veliparib, olaparib and talazoparib. A decision tree and nomogram based on PPRS and clinical characteristics can improve the prognosis stratification and survival prediction for TNBC patients.

CONCLUSIONS

A PPRS model was developed to predict TNBC patients' immune characteristics and response to immunotherapy, chemotherapy and targeted therapy, as well as their survival outcomes.

Identification of MARK2, CCDC71, GATA2, and KLRC3 as candidate diagnostic genes and potential therapeutic targets for repeated implantation failure with antiphospholipid syndrome by integrated bioinformatics analysis and machine learning

Background

Antiphospholipid syndrome (APS) is a group of clinical syndromes of thrombosis or adverse pregnancy outcomes caused by antiphospholipid antibodies, which increase the incidence of in vitro fertilization failure in patients with infertility. However, the common mechanism of repeated implantation failure (RIF) with APS is unclear. This study aimed to search for potential diagnostic genes and potential therapeutic targets for RIF with APS.

Methods

To obtain differentially expressed genes (DEGs), we downloaded the APS and RIF datasets separately from the public Gene Expression Omnibus database and performed differential expression analysis. We then identified the common DEGs of APS and RIF. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed, and we then generated protein-protein interaction. Furthermore, immune infiltration was investigated by using the CIBERSORT algorithm on the APS and RIF datasets. LASSO regression analysis was used to screen for candidate diagnostic genes. To evaluate the diagnostic value, we developed a nomogram and validated it with receiver operating characteristic curves, then analyzed these genes in the Comparative Toxicogenomics Database. Finally, the Drug Gene Interaction Database was searched for potential therapeutic drugs, and the interactions between drugs, genes, and immune cells were depicted with a Sankey diagram.

Results

There were 11 common DEGs identified: four downregulated and seven upregulated. The common DEG analysis suggested that an imbalance of immune system-related cells and molecules may be a common feature in the pathophysiology of APS and RIF. Following validation, MARK2, CCDC71, GATA2, and KLRC3 were identified as candidate diagnostic genes. Finally, Acetaminophen and Fasudil were predicted as two candidate drugs.

Conclusion

Four immune-associated candidate diagnostic genes (MARK2, CCDC71, GATA2, and KLRC3) were identified, and a nomogram for RIF with APS diagnosis was developed. Our findings may aid in the investigation of potential biological mechanisms linking APS and RIF, as well as potential targets for diagnosis and treatment.

Glioblastoma Microenvironment and Invasiveness: New Insights and Therapeutic Targets

Glioblastoma (GBM) is the most common and malignant primary brain cancer in adults. Without treatment the mean patient survival is approximately 6 months, which can be extended to 15 months with the use of multimodal therapies. The low effectiveness of GBM therapies is mainly due to the tumor infiltration into the healthy brain tissue, which depends on GBM cells' interaction with the tumor microenvironment (TME). The interaction of GBM cells with the TME involves cellular components such as stem-like cells, glia, endothelial cells, and non-cellular components such as the extracellular matrix, enhanced hypoxia, and soluble factors such as adenosine, which promote GBM's invasiveness. However, here we highlight the role of 3D patient-derived glioblastoma organoids cultures as a new platform for study of the modeling of TME and invasiveness. In this review, the mechanisms involved in GBM-microenvironment interaction are described and discussed, proposing potential prognosis biomarkers and new therapeutic targets.

Advances in NK cell therapy for brain tumors

Despite advances in treatment regimens that comprise surgery, chemotherapy, and radiation, outcome of many brain tumors remains dismal, more so when they recur. The proximity of brain tumors to delicate neural structures often precludes complete surgical resection. Toxicity and long-term side effects of systemic therapy remain a concern. Novel therapies are warranted. The field of NK cell-based cancer therapy has grown exponentially and currently constitutes a major area of immunotherapy innovation. This provides a new avenue for the treatment of cancerous lesions in the brain. In this review, we explore the mechanisms by which the brain tumor microenvironment suppresses NK cell mediated tumor control, and the methods being used to create NK cell products that subvert immune suppression. We discuss the pre-clinical studies evaluating NK cell-based immunotherapies that target several neuro-malignancies and highlight advances in molecular imaging of NK cells that allow monitoring of NK cell-based therapeutics. We review current and ongoing NK cell based clinical trials in neuro-oncology.

Systematic Analysis of Molecular Subtypes and Immune Prediction Based on CD8 T Cell Pattern Genes Based on Head and Neck Cancer

CD8+ T lymphocytes, also known as cytotoxic T lymphocytes, are the most powerful antitumour cells in the human body. Patients with head and neck squamous cell carcinoma (HNSCC) in whom CD8+ T lymphocyte infiltration is high have a better prognosis. However, the clinical significance and prognostic significance of CD8+ T cell-related regulatory genes in HNSCC remain unclear, and further research is required. In total, 446 CD8+ T cell-related genes were obtained using WGCNA. It was discovered that 111 genes included within the TCGA and GSE65858 datasets were intimately linked to the patient’s prognosis. These genes were included in the subsequent analysis. According to consensus clustering analysis, HNSCC samples were classified into 3 subtypes (IC1, IC2, and IC3). There were substantial differences between the three subtypes in terms of immunological molecules, immune function, and the response to drug treatment. In addition, the 8-gene signature, which was generated premised on CD8+ T cell-related genes, exhibited stable prognostic prediction in the TCGA and GEO datasets and different HNSCC patient subgroups and independently served as a prognostic indicator for HNSCC. More importantly, the 8-gene signature effectively predicted immunotherapy response. We first constructed a molecular subtype of HNSCC based on CD8+ T cell-related genes. Between the three subtypes, there were significant differences in the prognosis, clinical features, immunological molecules, and drug treatment response. The 8-gene signature that was further constructed effectively predicted prognosis and immunotherapy response.

Identification of immune hub genes participating in the pathogenesis and progression of Vogt-Koyanagi-Harada disease

Background

Vogt-Koyanagi-Harada (VKH) disease is an autoimmune inflammatory disorder characterized by bilateral granulomatous uveitis. The objective of this study was to identify immune hub genes involved in the pathogenesis and progression of VKH disease.

Methods

High throughput sequencing data were downloaded from the Gene Expression Omnibus (GEO) and an immune dataset was downloaded from ImmPort. Immune differentially expressed genes (DEGs) were obtained from their intersection in the GEO and ImmPort datasets. Immune hub genes for VKH disease were selected through differential expression analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO), protein-protein interaction (PPI) network, and clustering analyses. Confidence in the immune hub genes was subsequently validated using box plots and receiver operating characteristic (ROC) curves.

Results

A total of 254 DEGs were screened and after the intersection with ImmPort, 20 genes were obtained as immune DEGs. Functional enrichment analysis indicated that the key genes were mainly involved in several types of immune pathways (such as the lymphocyte mediated and leukocyte mediated immune responses, natural killer cell mediated cytotoxicity, and antigen binding) and immunodeficiency diseases. Following PPI network analysis, the top seven genes in cluster 1 were selected as potential immune hub genes in VKH. After evaluating the accuracy of the hub genes, one gene (GNLY) was excluded because its expression level was statistically similar in VKH patients and healthy controls. Finally, six immune hub genes, namely KLRC2, KLRC3 SH2D1B, GZMB, KIR2DL3, and KIR3DL2 were identified as playing important roles in the occurrence and development of VKH disease.

Conclusion

Six immune hub genes (KLRC2, KLRC3 SH2D1B, GZMB, KIR2DL3, and KIR3DL2) identified by our bioinformatics analyses may provide new diagnostic and therapeutic targets for VKH disease.

Integrative Analysis of Multi-Omics Data-Identified Key Genes With KLRC3 as the Core in a Gene Regulatory Network Related to Immune Phenotypes in Lung Adenocarcinoma

In a recent study, the PD-1 inhibitor has been widely used in clinical trials and shown to improve various cancers. However, PD-1/PD-L1 inhibitors showed a low response rate and were effective for only a small number of cancer patients. Thus, it is important to figure out the issue about the low response rate of immunotherapy. Here, we performed ssGSEA and unsupervised clustering analysis to identify three clusters (clusters A, B, and C) according to different immune cell infiltration status, prognosis, and biological action. Of them, cluster C showed a better survival rate, higher immune cell infiltration, and immunotherapy effect, with enrichment of a variety of immune active pathways including T and B cell signal receptors. In addition, it showed more significant features associated with immune subtypes C2 and C3. Furthermore, we used WGCNA analysis to confirm the cluster C-associated genes. The immune-activated module highly correlated with 111 genes in cluster C. To pick candidate genes in SD/PD and CR/PR patients, we used the least absolute shrinkage (LASSO) and SVM-RFE algorithms to identify the targets with better prognosis, activated immune-related pathways, and better immunotherapy. Finally, our analysis suggested that there were six genes with KLRC3 as the core which can efficiently improve immunotherapy responses with greater efficacy and better prognosis, and our study provided clues for further investigation about target genes associated with the higher response rate of immunotherapy.

Identifying Potential New Gene Expression-Based Biomarkers in the Peripheral Blood Mononuclear Cells of Hepatitis B-Related Hepatocellular Carcinoma

OBJECTIVE

The analysis of the gene expression of peripheral blood mononuclear cells (PBMCs) is important to clarify the pathogenesis of hepatocellular carcinoma (HCC) and the detection of suitable biomarkers. The purpose of this investigation was to use RNA-sequencing to screen the appropriate differentially expressed genes (DEGs) in the PBMCs for the HCC.

METHODS

The comprehensive transcriptome of extracted RNA of PBMC (n = 20) from patients with chronic hepatitis B (CHB), liver cirrhosis, and early stage of HCC (5 samples per group) was carried out using RNA-sequencing. All raw RNA-sequencing data analyses were performed using conventional RNA-sequencing analysis tools. Next, gene ontology (GO) analyses were carried out to elucidate the biological processes of DEGs. Finally, relative transcript abundance of selected DEGs was verified using qRT-PCR on additional validation groups.

RESULTS

Specifically, 13, 1262, and 1450 DEGs were identified for CHB, liver cirrhosis, and HCC, when compared with the healthy controls. GO enrichment analysis indicated that HCC is closely related to the immune response. Seven DEGs (TYMP, TYROBP, CD14, TGFBI, LILRA2, GNLY, and GZMB) were common to HCC, cirrhosis, and CHB when compared to healthy controls. The data revealed that the expressions of these 7 DEGs were consistent with those from the RNA-sequencing results. Also, the expressions of 7 representative genes that had higher sensitivity were obtained by receiver operating characteristic analysis, which indicated their important diagnostic accuracy for HBV-HCC.

CONCLUSION

This study provides us with new horizons into the biological process and potential prospective clinical diagnosis and prognosis of HCC in the near future.

Targeting Mitochondrial Oncometabolites: A New Approach to Overcome Drug Resistance in Cancer

Drug resistance is the main obstacle for a successful cancer therapy. There are many mechanisms by which cancers avoid drug-mediated death, including alterations in cellular metabolism and apoptotic programs. Mitochondria represent the cell's powerhouse and the connection between carbohydrate, lipid and proteins metabolism, as well as crucial controllers of apoptosis, playing an important role not only in tumor growth and progression, but also in drug response. Alterations in tricarboxylic acid cycle (TCA) caused by mutations in three TCA enzymes-isocitrate dehydrogenase, succinate dehydrogenase and fumarate hydratase-lead to the accumulation of 2-hydroxyglutarate, succinate and fumarate respectively, collectively known as oncometabolites. Oncometabolites have pleiotropic effects on cancer biology. For instance, they generate a pseudohypoxic phenotype and induce epigenetic changes, two factors that may promote cancer drug resistance leading to disease progression and poor therapy outcome. This review sums up the most recent findings about the role of TCA-derived oncometabolites in cancer aggressiveness and drug resistance, highlighting possible pharmacological strategies targeting oncometabolites production in order to improve the efficacy of cancer treatment.

The Role of Autophagy and lncRNAs in the Maintenance of Cancer Stem Cells

Simple Summary

Cancer stem cells (CSCs) represent a distinct cancer subpopulation that can influence the tumour microenvironment, in addition to cancer progression and relapse. A multitude of factors including CSC properties, long noncoding RNAs (lncRNAs), and autophagy play pivotal roles in maintaining CSCs. We discuss the methods of detection of CSCs and how our knowledge of regulatory and cellular processes, and their interaction with the microenvironment, may lead to more effective targeting of these cells. Autophagy and lncRNAs can regulate several cellular functions, thereby promoting stemness factors and CSC properties, hence understanding this triangle and its associated signalling networks can lead to enhanced therapy response, while paving the way for the development of novel therapeutic approaches.

Abstract

Cancer stem cells (CSCs) possess properties such as self-renewal, resistance to apoptotic cues, quiescence, and DNA-damage repair capacity. Moreover, CSCs strongly influence the tumour microenvironment (TME) and may account for cancer progression, recurrence, and relapse. CSCs represent a distinct subpopulation in tumours and the detection, characterisation, and understanding of the regulatory landscape and cellular processes that govern their maintenance may pave the way to improving prognosis, selective targeted therapy, and therapy outcomes. In this review, we have discussed the characteristics of CSCs identified in various cancer types and the role of autophagy and long noncoding RNAs (lncRNAs) in maintaining the homeostasis of CSCs. Further, we have discussed methods to detect CSCs and strategies for treatment and relapse, taking into account the requirement to inhibit CSC growth and survival within the complex backdrop of cellular processes, microenvironmental interactions, and regulatory networks associated with cancer. Finally, we critique the computationally reinforced triangle of factors inclusive of CSC properties, the process of autophagy, and lncRNA and their associated networks with respect to hypoxia, epithelial-to-mesenchymal transition (EMT), and signalling pathways.

Identification of TYROBP and C1QB as Two Novel Key Genes With Prognostic Value in Gastric Cancer by Network Analysis

Background: Gastric cancer (GC) is the fifth most frequently diagnosed malignancy, and the third leading cause of tumor-related mortalities worldwide. Due to a high heterogeneity in GC, its treatment and prognosis are challenging, necessitating urgent identification of novel prognostic predictors for GC patients. Methods: We downloaded RNA sequence data, from the Cancer Genome Atlas and microarray data from Gene Expression Omnibus database, then identified common differentially-expressed genes (DEGs) between GC and normal gastric tissues across four datasets. We then used a combination of protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA) to identify key genes with prognostic value in GC. Thereafter, we used quantitative real time polymerase chain reaction (qRT-PCR) to validate expression of the identified key genes in the Zhejiang University (ZJU) cohort. Finally, we evaluated the relationships between gene expression and immune factors, including immune cells and biomarkers of immunotherapy. Results: Among 426 common DEGs screened, 333 and 93 were upregulated and downregulated, respectively. PPI network and WGCNA successfully identified the top 30 hub genes, among which PTPRC, TYROBP, CCR1, CYBB, LCP2, and C1QB were common. Furthermore, TYROBP and C1QB were negatively associated with prognosis of GC patients, implying that they were key GC predictors. Interestingly, TYROBP and C1QB were positively correlated with predictive biomarkers for GC immunotherapy, including PD-L1 expression, CD8⁺ T cells infiltration, and EBV status. Conclusions: TYROBP and C1QB were identified as two novel key genes with prognostic value in GC by network analysis.

Immunologic Profiling of Mutational and Transcriptional Subgroups in Pediatric and Adult High-Grade Gliomas

Immunologic treatment strategies are under investigation for high-grade gliomas. Determining relevant immunologic pathways is required for invigorating a tumor-specific immune response. We therefore investigated the immunologic phenotypes within different subgroups of high-grade gliomas, with a focus on rare genetic subgroups of pediatric and adolescent patients to identify potentially targetable mechanisms. We gathered published gene-expression data from 1,135 high-grade glioma patients and applied a machine-learning technique to determine their transcriptional (mesenchymal, classic, neural, and proneural) and mutational [K27, G34, IDH, and wild type (WT)] subtypes. Gene signatures of infiltrating immune cells and functional immune pathways were evaluated in correlation to histologic diagnosis, age, and transcriptional and mutational subgroups. Our analysis identified four distinct microenvironmental signatures of immune cell infiltration (immune 1-4), which can be stratified into vascular, monocytic/stromal, monocytic/T-cell-, and antigen-presenting cell (APC)/natural killer (NK) cell/T-cell-dominated immune clusters. Immune cell expression profiles correlated with transcriptional and mutational subgroups but were independent of age and histologic diagnosis. By including functional pathways and correlating the expression of immunostimulatory and -inhibitory receptor-ligand interactions, we were able to define the immunologic microenvironment and identify possible immunologic subtypes associated with poor prognosis. In addition, comparison of overall survival with the immunologic landscape and with checkpoint molecules revealed correlations within the transcriptional and mutational subgroups, highlighting the potential application of PD-1/PD-L1 checkpoint inhibition in K27-mutated tumors. Our study shows that transcriptional and mutational subgroups are characterized by distinct immunologic tumor microenvironments, demonstrating the immunologic heterogeneity within high-grade gliomas and suggesting an immune-specific stratification for upcoming immunotherapy trials.

Adenylosuccinate lyase enhances aggressiveness of endometrial cancer by increasing killer cell lectin-like receptor C3 expression by fumarate

Adenylosuccinate lyase (ADSL) is an enzyme that plays important roles in de novo purine synthesis. Although ADSL was reported to be upregulated in various malignancies, such as colorectal, breast, and prostate cancer, as well as gliomas, the mechanism by which elevated ADSL expression contributes to cancer has not been elucidated. We previously performed a shotgun proteomics analysis to characterize specific proteins associated with the properties of the aldehyde dehydrogenase (ALDH)-high cell population, which was reported to be involved in tumorigenic potential, and showed that ADSL expression is upregulated in the ALDH-high population of endometrial cancer. Here, we showed that ADSL is involved in endometrial cancer aggressiveness by regulating expression of killer cell lectin-like receptor C3 (KLRC3), which is a receptor expressed on natural killer cells. Immunohistochemical analysis indicated that ADSL expression increased as endometrioid carcinoma specimens became more poorly differentiated and higher degree of primary tumor progression. Knockdown of ADSL in endometrial cancer cells decreased cell proliferation, migration, and invasive capability, and caused the cells to adopt a more rounded shape. DNA microarray analysis and quantitative real-time PCR showed that KLRC3 expression was decreased in ADSL knockdown cells. Knockdown of KLRC3 in endometrial cancer cells resulted in the same phenotype as knockdown of ADSL. Moreover, fumarate, which could be produced by ADSL and was recently shown to be an oncometabolite, recovered KLRC3 expression in ADSL knockdown cells, suggesting that fumarate produced by ADSL could regulate KLRC3 expression. Our findings indicate that ADSL enhances cell proliferation, migration, and invasive capability through regulation of KLRC3 expression by fumarate.