Malignant Tumor Purity Reveals the Driven and Prognostic Role of CD3E in Low-Grade Glioma Microenvironment

ZNF480 influences the prognosis, pathogenesis, and immune microenvironment in patients with lower-grade glioma

ZNF480 has not yet attracted attention in the study of malignant tumors. Therefore, this study attempts to explain the significance of ZNF480 in the pathological process of lower-grade gliomas (LGG) based on large-scale samples from public database sources and in vitro experiments. Reverse transcription quantitative real-time polymerase chain reaction and immunohistochemistry confirmed that ZNF480 was highly expressed at both the mRNA and protein levels in LGG. Prognostic correlation analysis confirmed that the high expression of ZNF480, as an independent pathogenic gene, significantly correlates with poor survival in patients. Furthermore, the expression level of ZNF480 was significantly inhibited in SHG-44 cells treated with ademetionine disulfate tosylate. Gene set enrichment analysis showed that ZNF480 exists in multiple tumor-related signaling pathways, including the Notch signaling pathway. Immunological correlation analysis showed that ZNF480 can promote the LGG microenvironment to a high immune state and significantly enhance the infiltration of various immune cells, such as M2 macrophages. Finally, Spearman analysis showed a positive correlation of ZNF480 with many immune checkpoints, such as PD-L1. Overall, this study reveals for the first time the adverse effects of ZNF480 on the prognosis of tumor patients, which expands our understanding of the molecular mechanisms behind the regulation of ZNF480. We believe that the high expression of ZNF480 in LGG may be valuable for molecular targeted therapy or combined immunotherapy.

Integrating machine learning and bioinformatics analysis to m6A regulator-mediated methylation modification models for predicting glioblastoma patients' prognosis and immunotherapy response

BACKGROUND

Epigenetic regulations of immune responses are essential for cancer development and growth. As a critical step, comprehensive and rigorous explorations of m6A methylation are important to determine its prognostic significance, tumor microenvironment (TME) infiltration characteristics and underlying relationship with glioblastoma (GBM).

METHODS

To evaluate m6A modification patterns in GBM, we conducted unsupervised clustering to determine the expression levels of GBM-related m6A regulatory factors and performed differential analysis to obtain m6A-related genes. Consistent clustering was used to generate m6A regulators cluster A and B. Machine learning algorithms were implemented for identifying TME features and predicting the response of GBM patients receiving immunotherapy.

RESULTS

It is found that the m6A regulatory factor significantly regulates the mutation of GBM and TME. Based on Europe, America, and China data, we established m6Ascore through the m6A model. The model accurately predicted the results of 1206 GBM patients from the discovery cohort. Additionally, a high m6A score was associated with poor prognoses. Significant TME features were found among the different m6A score groups, which demonstrated positive correlations with biological functions (i.e., EMT2) and immune checkpoints.

CONCLUSIONS

m6A modification was important to characterize the tumorigenesis and TME infiltration in GBM. The m6Ascore provided GBM patients with valuable and accurate prognosis and prediction of clinical response to various treatment modalities, which could be useful to guide patient treatments.

Integrative analyses of ferroptosis and immune related biomarkers and the osteosarcoma associated mechanisms

Osteosarcoma (OS) is the most common primary malignant bone tumor with high metastatic potential and relapse risk. To study the regulatory mechanism of the OS microenvironment, a complex regulatory network involving the ferroptosis- and immune response-related genes remains to be established. In the present study, we determined the effect of a comprehensive evaluation system established on the basis of ferroptosis- and immune-related genes on the immune status, related biomarkers, prognosis, and the potential regulatory networks underlying OS based on the TARGET and Gene Expression Omnibus databases that contain information on OS patients by bioinformatics analyses. We first characterized individual ferroptosis scores and immune scores through gene set variation analysis (GSVA) against TARGET-OS datasets. We then identified differentially expressed genes by score groups. Weighted gene co-expression network analysis was performed to identify the most relevant ferroptosis-related and immune-related gene modules, which facilitated the identification of 327 ferroptosis gene and 306 immune gene candidates. A 4-gene (WAS, CORT, WNT16, and GLB1L2) signature was constructed and valuation using the least absolute shrinkage and selection operator-Cox regression models to effectively predict OS prognosis. The prediction efficiency was further validated by GSE39055. We stratified patients based on the prognostic scoring systems. Eight hub genes (namely CD3D, CD8A, CD3E, IL2, CD2, MYH6, MYH7, and MYL2) were identified, and TF-miRNA target regulatory networks were constructed. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and GSVA were used to determine the signature's potential pathways and biological functions, which showed that the hub genes were enriched in ferroptosis-associated biological functions and immune-associated molecular mechanisms. Thereafter, we investigated the proportion and infiltration extent of 22 infiltrating immune cells by using CIBERSORT, which revealed significant subgroup differences in CD8 + T cells, M0 macrophages, and M2 macrophages. In conclusion, we determined a new ferroptosis-related and immune-related gene signature for predicting OS patients' prognosis and further explored the ferroptosis and immunity interactions during OS development, which provides insights into the exploration of molecular mechanisms and targeted therapies in patients with OS.

Integrated analysis of transcription factor-mRNA-miRNA regulatory network related to immune characteristics in medullary thyroid carcinoma

Background

Medullary thyroid carcinoma (MTC), a thyroid C cell-derived malignancy, is poorly differentiated and more aggressive than papillary, follicular and oncocytic types of thyroid cancer. The current therapeutic options are limited, with a third of population suffering resistance. The differential gene expression pattern among thyroid cancer subtypes remains unclear. This study intended to explore the exclusive gene profile of MTC and construct a comprehensive regulatory network via integrated analysis, to uncover the potential key biomarkers.

Methods

Multiple datasets of thyroid and other neuroendocrine tumors were obtained from GEO and TCGA databases. Differentially expressed genes (DEGs) specific in MTC were identified to construct a transcription factor (TF)-mRNA-miRNA network. The impact of the TF-mRNA-miRNA network on tumor immune characteristics and patient survival was further explored by single-sample GSEA (ssGSEA) and ESTIMATE algorithms, as well as univariate combined with multivariate analyses. RT-qPCR, cell viability and apoptosis assays were performed for in vitro validation.

Results

We identified 81 genes upregulated and 22 downregulated in MTC but not in other types of thyroid tumor compared to the normal thyroid tissue. According to the L1000CDS2 database, potential targeting drugs were found to reverse the expressions of DEGs, with panobinostat (S1030) validated effective for tumor repression in MTC by in vitro experiments. The 103 DEGs exclusively seen in MTC were involved in signal release, muscle contraction, pathways of neurodegeneration diseases, neurotransmitter activity and related amino acid metabolism, and cAMP pathway. Based on the identified 15 hub genes, a TF-mRNA-miRNA linear network, as well as REST-cored coherent feed-forward loop networks, namely REST-KIF5C-miR-223 and REST-CDK5R2-miR-130a were constructed via online prediction and validation by public datasets and our cohort. Hub-gene, TF and miRNA scores in the TF-mRNA-miRNA network were related to immune score, immune cell infiltration and immunotherapeutic molecules in MTC as well as in neuroendocrine tumor of lung and neuroblastoma. Additionally, a high hub-gene score or a low miRNA score indicated good prognoses of neuroendocrine tumors.

Conclusion

The present study uncovers underlying molecular mechanisms and potential immunotherapy-related targets for the pathogenesis and drug discovery of MTC.

Radiotherapy-Related Gene Signature in Prostate Cancer

Simple Summary

Radiation therapy (RT) is an established therapeutic regimen for prostate cancer patients which aims for the direct elimination of tumor cells in the prostate gland and occasionally at distant anatomic sites. In this study, we performed next-generation sequencing-based gene expression analysis in peripheral blood from prostate cancer patients obtained pre- and post-radiotherapy and found six independently down-regulated genes including CCR7, FCGR2B, BTLA, CD6, CD3D, and CD3E. The analysis of the expression of the 6-genes as a signature also revealed significantly lower levels post- vs. pre-radiotherapy. Data extracted from the PRAD (PRostate ADenocarcinomas) dataset linked low levels of the 6-gene signature to better survival. More importantly, this 6-gene signature strongly correlated with a favorable prognosis regardless of poor standard clinicopathological parameters (i.e., Gleason score ≥ 8 and T3), thus highlighting its potential predictive value.

Abstract

Radiotherapy for localized prostate cancer has increased the cure and survival rates of patients. Besides its local tumoricidal effects, ionizing radiation has been linked to mechanisms leading to systemic immune activation, a phenomenon called the abscopal effect. In this study, we performed gene expression analysis on peripheral blood from prostate cancer patients obtained post- radiotherapy and showed that 6 genes, including CCR7, FCGR2B, BTLA, CD6, CD3D, and CD3E, were down-regulated by a range of 1.5–2.5-fold as compared to pre-radiotherapy samples. The expression of the signature consisting of these six genes was also significantly lower post- vs. pre-radiotherapy. These genes are involved in various tumor-promoting immune pathways and their down-regulation post-radiotherapy could be considered beneficial for patients. This is supported by the fact that low mRNA expression levels for the 6-gene signature in the prostate tumor tissue was linked to better survival. Importantly, we report that this 6-gene signature strongly correlated with a favorable prognosis regardless of poor standard clinicopathological parameters (i.e., Gleason score ≥ 8 and T3 (including T3a and T3b). Our pioneering data open the possibility that the 6-gene signature identified herein may have a predictive value, but this requires further long-term studies.

Identification of adenylate cyclase 2 methylation in bladder cancer with implications for prognosis and immunosuppressive microenvironment

Background

The incidence and mortality of bladder cancer (BCa) are increasing, while the existing diagnostic methods have limitations. Therefore, for early detection and response prediction, it is crucial to improve the prognosis and treatment strategies. However, with existing diagnostic methods, detecting BCa in the early stage is challenging. Hence, novel biomarkers are urgently needed to improve early diagnosis and treatment efficiency.

Methods

The gene expression profile and gene methylation profile dataset were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs), differentially methylated genes (DMGs), and methylation-regulated differentially expressed genes (MeDEGs) were gradually identified. A cancer genome map was obtained using online gene expression profile interaction analysis, and survival implications were produced using Kaplan-Meier survival analysis. GSEA was employed to predict the marker pathways where DEGs were significantly involved. The study used bisulfite PCR amplification combined with bisulfite amplicon sequencing (BSAS) to screen for methylation analysis of multiple candidate regions of the adenylate cyclase 2 (ADCY2) based on the sequence design of specific gene regions and CpG islands.

Results

In this study, DEGs and DMGs with significantly up- or down-regulated expression were selected. The intersection method was used to screen the MeDEGs. The interaction network group in STRING was then visualized using Cytoscape, and the PPI network was constructed to identify the key genes. The key genes were then analyzed using functional enrichment. To compare the relationship between key genes and the prognosis of BCa patients, we further investigated ADCY2 and found that ADCY2 can be a potential clinical biomarker in BCa prognosis and immunotherapy response prediction. In human BCa 5637 and MGH1 cells, we developed and verified the effectiveness of ADCY2 primers using BSAS technology. The findings revealed that the expression of ADCY2 is highly regulated by the methylation of the promoter regions.

Conclusion

This study revealed that increased expression of ADCY2 was significantly correlated with increased tumor heterogeneity, predicting worse survival and immunotherapy response in BCa patients.

Correlation analysis of tumor purity with clinicopathological, molecular, and imaging features in high-grade gliomas

High-grade gliomas (HGG) have high malignancy, high heterogeneity, and a poor prognosis. Tumor purity is an intrinsic feature of the HGG microenvironment and an independent prognostic factor. The purpose of this study was to analyze the correlation of tumor purity with clinicopathological, molecular, and imaging features. We performed a retrospective analysis of 112 patients diagnosed with HGG (grades III and IV) in our center. Eleven regions of interest (ROI) were randomly selected on whole-slide images (WSI, 40 × magnification) based on HGG tissue paraffin sections and hematoxylin-eosin (H&E) staining. Of these 11 ROIs, five ROIs were visually estimated by pathologists and six ROIs were automatically analyzed using ImageJ software. Last, the average tumor purity (%) of the 11 ROIs was calculated. Correlation analysis of tumor purity with clinicopathological, molecular, and imaging features was conducted. Of the 112 patients included in the study, the mean tumor purity of HGG was 70.96%. There were differences in tumor purity between WHO grades III and IV; the tumor purity of grade IV patients (67.59%) was lower than that of grade III patients (76.00%) (p < 0.001). There were also differences in tumor purity between IDH1 mutant and wild type, and the tumor purity of IDH1 mutant patients was higher than that of IDH1 wild-type patients (p = 0.006). The average range of peritumoral edema was about 19.18 mm, and the diameter of edema, ADC_mean, and ADC_min were negatively correlated with tumor purity(r =  - 0.236, r =  - 0.306, and r =  - 0.242; p < 0.05). The grade of HGG, IDH1 mutant/wild type, peritumoral edema, and ADC value were correlated with tumor purity. HGG grade, IDH1 mutant/wild type, peritumoral edema, and ADC value can predict tumor purity and indirectly reflect patient prognosis.

A bioinformatic analysis study of m7G regulator-mediated methylation modification patterns and tumor microenvironment infiltration in glioblastoma

BACKGROUND

Glioblastoma is one of the most common brain cancers in adults, and is characterized by recurrence and little curative effect. An effective treatment for glioblastoma patients remains elusive worldwide. 7-methylguanosine (m7G) is a common RNA modification, and its role in tumors has become a research hotspot.

METHODS

By searching for differentially expressed genes related to m7G, we generated a prognostic signature via cluster analysis and established classification criteria of high and low risk scores. The effectiveness of classification was validated using the Non-negative matrix factorization (NMF) algorithm, and repeatedly verified using training and test groups. The dimension reduction method was used to clearly show the difference and clinical significance of the data. All analyses were performed via R (version 4.1.2).

RESULTS

According to the signature that included four genes (TMOD2, CACNG2, PLOD3, and TMSB10), glioblastoma patients were divided into high and low risk score groups. The survival rates between the two groups were significantly different, and the predictive abilities for 1-, 3-, and 5-year survivals were effective. We further established a Nomogram model to further examine the signature,as well as other clinical factors, with remaining significant results. Our signature can act as an independent prognostic factor related to immune-related processes in glioblastoma.

CONCLUSIONS

Our research addresses the gap in knowledge in the m7G and glioblastoma research fields. The establishment of a prognostic signature and the extended analysis of the tumor microenvironment, immune correlation, and tumor mutation burden further suggest the important role of m7G in the development and development of this disease. This work will provide support for future research.

Transcriptome Profiles Reveal a 12-Signature Metabolic Prediction Model and a Novel Role of Myo-Inositol Oxygenase in the Progression of Prostate Cancer

Prostate adenocarcinoma (PRAD) is an extremely common type of cancer in the urinary system. Here, we aimed to establish a metabolic signature to identify novel targets in a predictive model of PRAD patients. A total of 133 metabolic differentially expressed genes (MDEGs) were identified with significant prognostic value. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a 12-mRNA signature model, a metabolic prediction model (MPM), in 491 PRAD patients. The risk score of the MPM significantly predicted the progression of PRAD patients (p < 0.001, area under the curve (AUC) = 0.745). Furthermore, myo-inositol oxygenase (MIOX), the most prominently upregulated metabolic enzyme and hub gene in the protein-protein interaction network of the MPM, showed significant prognostic implications. Next, MIOX expression in normal prostate tissues was lower than in PRAD tissues, and high MIOX expression was significantly associated with disease progression (p = 0.005, HR = 2.274) in 81 PRAD patients undergoing first-line androgen receptor signaling inhibitor treatment from the Renji cohort. Additionally, MIOX was significantly involved in the abnormal immune infiltration of the tumor microenvironment and associated with the DNA damage repair process of PRAD. In conclusion, this study provides the first opportunity to comprehensively elucidate the landscape of prognostic MDEGs, establish novel prognostic modeling of MPM using large-scale PRAD transcriptomic data, and identify MIOX as a potential prognostic target in PRAD patients from multiple cohorts. These findings help manage risk assessment and provide valuable insights into treatment strategies for PRAD.

Effect of High-Quality Nursing Based on Comprehensive Nursing on the Postoperative Quality of Life and Satisfaction of Patients with Malignant Glioma

Objective

To explore the effect of high-quality nursing based on comprehensive nursing on postoperative quality of life and satisfaction of patients with malignant glioma.

Methods

From September 2017 to May 2020, 86 patients with malignant glioma treated in our hospital were recruited and assigned (1 : 1) to receive either comprehensive nursing (comprehensive group) or high-quality nursing plus comprehensive nursing (high-quality group). Outcome measures included preoperative and postoperative self-rating anxiety scale (SAS) scores, self-rating depression scale (SDS) scores, quality of life, and nursing satisfaction.

Results

High-quality nursing plus comprehensive nursing was associated with significantly lower SAS and SDS scores versus comprehensive nursing alone (P < 0.05). Patients receiving high-quality nursing plus comprehensive nursing showed higher quality of life scores versus those only given comprehensive nursing (P < 0.05). High-quality nursing plus comprehensive nursing resulted in higher nursing satisfaction of the patients versus comprehensive nursing alone (P < 0.05).

Conclusion

High-quality nursing can relieve the negative emotions of patients with malignant glioma and significantly enhance their quality of life, thereby improving the nursing satisfaction of patients with nursing, so it is worthy of clinical application.