Hypomethylation of CNTFRα is associated with proliferation and poor prognosis in lower grade gliomas

Enhanced therapeutic efficacy for glioblastoma immunotherapy with an oncolytic herpes simplex virus armed with anti-PD-1 antibody and IL-12

Glioblastoma is the most common and aggressive malignant brain tumor and has limited treatment options. Hence, innovative approaches are urgently needed. Oncolytic virus therapy is emerging as a promising modality for cancer treatment due to its tumor-specific targeting and immune-stimulatory properties. In this study, we developed a new generation of oncolytic herpes simplex virus C5252 by deletion of a 15-kb internal repeat region and both copies of γ34.5 genes. Additionally, C5252 was armed with anti-programmed cell death protein 1 antibody and interleukin-12 to enhance its therapeutic efficacy for glioblastoma immune-virotherapy. In vitro and in vivo experiments demonstrate that C5252 has a remarkable safety profile and potent anti-tumor activity against glioblastoma. Mechanistic studies demonstrated that C5252 specifically induces cell apoptosis by caspase-3/7 activation via downregulating ciliary neurotrophic factor receptor α. Furthermore, the enhanced anti-tumor therapeutic efficacy of C5252 in a subcutaneous glioblastoma model and an orthotopic glioblastoma model was confirmed. Moreover, syngeneic mouse models showed that the murine surrogate of C5252 has superior anti-tumor activity compared to the unarmed backbone virus, with enhanced immune activation. Taken together, our findings support C5252 as a promising therapeutic option for glioblastoma treatment, positioning it as a highly promising candidate for clinical translation.

Interleukin-6 Family of Cytokines in Cancers

Nine soluble ligands [interleukin-6 (IL-6), interleukin-11 (IL-11), leukemia inhibitory factor (LIF), oncostatin M (OSM), ciliary neurotrophic factor (CNTF), cardiotrophin-1 (CT-1), cardiotrophin-like cytokine, interleukin-27 (IL-27), and interleukin-31] share the ubiquitously expressed transmembrane protein-glycoprotein-130 beta-subunit (gp130) and thus form IL-6 family cytokines. Proteins that may be important for cancerogenesis, CT-1, IL-11, IL-27, LIF, OSM, and CNTF, belong to the superfamily of IL-6. Cytokines such as IL-6, IL-11, and IL-27 are better investigated in comparison with other members of the same family of cytokines, eg, CT-1. Gp130 is one of the main receptors through which these cytokines exert their effects. The clinical implication of understanding the pathways of these cytokines in oncology is that targeted therapy to inhibit or potentiate cytokine activity may lead to remission in some cases.

Identification of COL1A1 associated with immune infiltration in brain lower grade glioma

Brain low grade gliomas (LGG) often give serious clinical symptoms due to the invasion towards nervous system, affecting the life quality of patients. Collagen type I alpha 1(COL1A1) is the main component of type I collagen. Although there are many reports about abnormal expression of COL1A1 in various tumors, specific role and clinical significance of COL1A1 in LGG have not yet been elucidated. In this work, Tumor Immune Estimation Resource database was used for detecting the expression level of COL1A1 in cancer and normal tissues, and aimed to explore the relationship between COL1A1 and tumor immune infiltration. We applied Kaplan-Meier to analyze the role of COL1A1 in clinical prognosis. Univariate survival rate and multivariate Cox analysis were used to compare clinical characteristics and survival rate. The relativity between the expression of COL1A1 and the tumor microenvironment was evaluated using ESTIMATE algorithm. Finally, the relationship between expression level of COL1A1 and gene marker sets of immune cell infiltration was investigated via TIMER. According to TCGA, COL1A1 overexpression was correlated with overall survival (OS), progression free interval (PFI) and disease specific survival (DSS) of multiple tumors, especially in LGG. Multivariate analysis showed that COL1A1 expression was an independent prognostic factor for LGG. The expression of COL1A1 was positively correlated with the infiltration of CD4 + T and CD8 + T cells, neutrophils, macrophages and dendritic cells in LGG. In addition, there was a strong correlation between expression of COL1A1 and different immune marker sets in LGG. The results suggest that COL1A1 is related with tumor immune infiltration of LGG.

DNA Methylation-Driven Genes for Developing Survival Nomogram for Low-Grade Glioma

Low-grade gliomas (LGG) are heterogeneous, and the current predictive models for LGG are either unsatisfactory or not user-friendly. The objective of this study was to establish a nomogram based on methylation-driven genes, combined with clinicopathological parameters for predicting prognosis in LGG. Differential expression, methylation correlation, and survival analysis were performed in 516 LGG patients using RNA and methylation sequencing data, with accompanying clinicopathological parameters from The Cancer Genome Atlas. LASSO regression was further applied to select optimal prognosis-related genes. The final prognostic nomogram was implemented together with prognostic clinicopathological parameters. The predictive efficiency of the nomogram was internally validated in training and testing groups, and externally validated in the Chinese Glioma Genome Atlas database. Three DNA methylation-driven genes, ARL9, CMYA5, and STEAP3, were identified as independent prognostic factors. Together with IDH1 mutation status, age, and sex, the final prognostic nomogram achieved the highest AUC value of 0.930, and demonstrated stable consistency in both internal and external validations. The prognostic nomogram could predict personal survival probabilities for patients with LGG, and serve as a user-friendly tool for prognostic evaluation, optimizing therapeutic regimes, and managing LGG patients.

Analysis of Genetic Variants and the ceRNA Network of miR-9 in Non-Small Cell Lung Cancer

Objective: To explore the role of single-nucleotide polymorphisms (SNPs) in hsa-miR-9 in non-small cell lung cancer (NSCLC). Methods: Log-rank and Cox regression analyses were conducted to assess the association of four functional SNPs of miR-9 with overall survival (OS) of Chinese patients with NSCLC. A reporter luciferase assay was performed to examine the relationship between the SNPs and transcriptional activity of miR-9. The expression of miR-9 in cells was detected by quantitative real-time PCR assay. Xenograft model was established in nude mice, which were treated with Lv-MiR-9-mimics or Lv-miR-9-inhibitor. A long noncoding RNA (lncRNA)-miR-9-messenger RNA (mRNA) competing endogenous RNA (ceRNA) network was established based on bioinformatics analyses. Results: We found that rs1501672 was associated with the prognosis of 1001 Chinese NSCLC patients (A>G, additive model: adjusted hazard ratio = 0.89, 95% confidence interval = 0.79-1.00, p = 0.056). Luciferase reporter assay showed higher luciferase activity with wild A allele than that with mutant G allele in 293T, SPC-A1, and A549 cell lines. The miR-9 level was significantly higher in lung cancer cells than normal lung cells. miR-9 was also over expressed in lung cancer tissue according to The Cancer Genome Atlas and gene expression omnibus databases. Xenograft models based on H1299 cells showed that lv-miR-9-inhibitor significantly decreased tumor growth compared with the lv-miR-9-NC group (p < 0.001). Bioinformatics analysis showed that one target gene leukemia inhibitory factor receptor and two lncRNAs (KIAA0087 and GVINP1) were associated with OS of NSCLC patients. Conclusion: The rs1501672 of miR-9 was associated with the prognosis of NSCLC patients in the Chinese population. The lncRNA-miR-9-mRNA ceRNA network revealed potential molecular biological regulation pathways and prognostic biomarkers for NSCLC.

The diagnostic value of lower glucose consumption for IDH1 mutated gliomas on FDG-PET

Background

Non-invasive diagnosis of IDH1 mutation for gliomas has great clinical significance, and PET has natural advantage to detect metabolism, as IDH mutated gliomas share lower glucose consumption.

Methods

Clinical data of patients with gliomas and ¹⁸F-FDG PET were retrospectively reviewed. Receiver operating characteristic curve (ROC) analysis was conducted, and standard uptake value (SUV) was estimated in combination with grades or IDH1 mutation. The glucose consumption was investigated with U251 cells expressing wild-type or mutated IDH1 by glucose assay. Quantification of glucose was determined by HPLC in clinical tissues. Meanwhile, bioinformatics and western blot were applied to analyze the expression level of metabolic enzymes (e.g. HK1, PKM2, PC) in gliomas.

Results

Seventy-one glioma cases were enrolled, including 30 carrying IDH1 mutation. The sensitivity and specificity dependent on SUV_max (3.85) predicting IDH1 mutation reached 73.2 and 86.7%, respectively. The sensitivity and specificity of differentiating grades by SUVmax (3.1) were 92.3 and 64.4%, respectively. Glucose consumption of U251 IDH1 mutant cells (0.209 ± 0.0472 mg/ml) was obviously lower than IDH1wild-type cells (0.978 ± 0.0773 mg/ml, P = 0.0001) and astrocyte controls (0.335 ± 0.0592 mg/ml, P = 0.0451). Meanwhile, the glucose quantity in IDH1mutant glioma samples were significantly lower than those in IDH1 wild-type tissues (1.033 ± 1.19608 vs 6.361 ± 4.3909 mg/g, P = 0.0051). Silico analysis and western blot confirmed that HK1 and PKM2 in IDH1 wild-type gliomas were significantly higher than in IDH1 mutant group, while PC was significantly higher in IDH1 mutant gliomas.

Conclusion

SUV_max on PET can predict IDH1 mutation with adequate sensitivity and specificity, as is supported by reduced glucose consumption in IDH1 mutant gliomas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07797-6.

Modeling Basins of Attraction for Breast Cancer Using Hopfield Networks

Cancer is a genetic disease for which traditional treatments cause harmful side effects. After two decades of genomics technological breakthroughs, personalized medicine is being used to improve treatment outcomes and mitigate side effects. In mathematical modeling, it has been proposed that cancer matches an attractor in Waddington's epigenetic landscape. The use of Hopfield networks is an attractive modeling approach because it requires neither previous biological knowledge about protein-protein interactions nor kinetic parameters. In this report, Hopfield network modeling was used to analyze bulk RNA-Seq data of paired breast tumor and control samples from 70 patients. We characterized the control and tumor attractors with respect to their size and potential energy and correlated the Euclidean distances between the tumor samples and the control attractor with their corresponding clinical data. In addition, we developed a protocol that outlines the key genes involved in tumor state stability. We found that the tumor basin of attraction is larger than that of the control and that tumor samples are associated with a more substantial negative energy than control samples, which is in agreement with previous reports. Moreover, we found a negative correlation between the Euclidean distances from tumor samples to the control attractor and patient overall survival. The ascending order of each node's density in the weight matrix and the descending order of the number of patients that have the target active only in the tumor sample were the parameters that withdrew more tumor samples from the tumor basin of attraction with fewer gene inhibitions. The combinations of therapeutic targets were specific to each patient. We performed an initial validation through simulation of trastuzumab treatment effects in HER2+ breast cancer samples. For that, we built an energy landscape composed of single-cell and bulk RNA-Seq data from trastuzumab-treated and non-treated HER2+ samples. The trajectory from the non-treated bulk sample toward the treated bulk sample was inferred through the perturbation of differentially expressed genes between these samples. Among them, we characterized key genes involved in the trastuzumab response according to the literature.

Identification of core biomarkers associated with pathogenesis and prognostic outcomes of laryngeal squamous-cell cancer using bioinformatics analysis

PURPOSE

Despite advances in the treatment of laryngeal squamous-cell carcinoma (LSCC), the survival rate of LSCC remains poor. Thereby, it is urgent to identify novel diagnostic and prognostic biomarkers for LSCC. The study aimed to identify potential core genes associated with the pathogenesis and prognosis of LSCC.

METHODS

Differentially expressed genes between LSCC and normal laryngeal tissue samples were screened by an integrated analysis of data from GEO and TCGA databases. Core genes related to the pathogenesis and prognosis of LSCC were identified by employing protein-protein interaction network and Cox proportional hazards model analyses.

RESULTS

Ten hub genes (AURKA, AURKB, CDC45, KIF2C, NDC80, EXO1, TYMS, RAD51AP1, ITGA3, and UBE2T) that might be highly related to the pathogenesis of LSCC were identified. An eight-gene prognostic signature consisted of ZG16B, STATH, RTN4R, MSRA, CBX8, SLC5A1, EFNB1 and CNTFR was constructed with a good performance in predicting overall survivals.

CONCLUSION

Our findings might shed some new light on the pathogenesis of LSCC and help identify new therapeutic targets of LSCC.

Antitumor activity of an engineered decoy receptor targeting CLCF1-CNTFR signaling in lung adenocarcinoma

Proinflammatory cytokines in the tumor microenvironment can promote tumor growth, yet their value as therapeutic targets remains underexploited. We validated the functional significance of the cardiotrophin-like cytokine factor 1 (CLCF1)-ciliary neurotrophic factor receptor (CNTFR) signaling axis in lung adenocarcinoma (LUAD) and generated a high-affinity soluble receptor (eCNTFR-Fc) that sequesters CLCF1, thereby inhibiting its oncogenic effects. eCNTFR-Fc inhibits tumor growth in multiple xenograft models and in an autochthonous, highly aggressive genetically engineered mouse model of LUAD, driven by activation of oncogenic Kras and loss of Trp53. Abrogation of CLCF1 through eCNTFR-Fc appears most effective in tumors driven by oncogenic KRAS. We observed a correlation between the effectiveness of eCNTFR-Fc and the presence of KRAS mutations that retain the intrinsic capacity to hydrolyze guanosine triphosphate, suggesting that the mechanism of action may be related to altered guanosine triphosphate loading. Overall, we nominate blockade of CLCF1-CNTFR signaling as a novel therapeutic opportunity for LUAD and potentially for other tumor types in which CLCF1 is present in the tumor microenvironment.

Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma

BACKGROUND The aim of this study was to identify gene signals for lower-grade glioma (LGG) and to assess their potential as recurrence biomarkers. MATERIAL AND METHODS An LGG-related mRNA sequencing dataset was downloaded from The Cancer Genome Atlas (TCGA) Informix. Multiple bioinformatics analysis methods were used to identify key genes and potential molecular mechanisms in recurrence of LGG. RESULTS A total of 326 differentially-expressed genes (DEGs), were identified from 511 primary LGG tumor and 18 recurrent samples. Gene ontology (GO) analysis revealed that the DEGs were implicated in cell differentiation, neuron differentiation, negative regulation of neuron differentiation, and cell proliferation in the forebrain. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database suggests that DEGs are associated with proteoglycans in cancer, the Wnt signaling pathway, ECM-receptor interaction, the PI3K-Akt signaling pathway, transcriptional deregulation in cancer, and the Hippo signaling pathway. The hub DEGs in the protein-protein interaction network are apolipoprotein A2 (APOA2), collagen type III alpha 1 chain (COL3A1), collagen type I alpha 1 chain (COL1A1), tyrosinase (TYR), collagen type I alpha 2 chain (COL1A2), neurotensin (NTS), collagen type V alpha 1 chain (COL5A1), poly(A) polymerase beta (PAPOLB), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), and anomalous homeobox (ANHX). GSEA revealed that the following biological processes may associated with LGG recurrence: cell cycle, DNA replication and repair, regulation of apoptosis, neuronal differentiation, and Wnt signaling pathway. CONCLUSIONS Our study demonstrated that hub DEGs may assist in the molecular understanding of LGG recurrence. These findings still need further molecular studies to identify the assignment of DEGs in LGG.