Development and Validation of an Mesenchymal-Related Long Non-Coding RNA Prognostic Model in Glioma

Unravelling the mosaic: Epigenetic diversity in glioblastoma

Glioblastoma is the most common primary malignant brain tumour. Despite decades of intensive research in the disease, its prognosis remains poor, with an average survival of only 14 months after diagnosis. The remarkable level of intra- and interpatient heterogeneity is certainly contributing to the lack of progress in tackling this tumour. Epigenetic dysregulation plays an important role in glioblastoma biology and significantly contributes to intratumour heterogeneity. However, it is becoming increasingly clear that it also contributes to intertumour heterogeneity, which historically had mainly been linked to diverse genetic events occurring in different patients. In this review, we explore how DNA methylation, chromatin remodelling, microRNA (miRNA) dysregulation, and long noncoding RNA (lncRNA) alterations contribute to intertumour heterogeneity in glioblastoma, including its implications for advanced tumour stratification, which is the essential first step for developing more effective patient-specific therapeutic approaches.

Role of glioma stem cells in promoting tumor chemo- and radioresistance: A systematic review of potential targeted treatments

BACKGROUND

Gliomas pose a significant challenge to effective treatment despite advancements in chemotherapy and radiotherapy. Glioma stem cells (GSCs), a subset within tumors, contribute to resistance, tumor heterogeneity, and plasticity. Recent studies reveal GSCs' role in therapeutic resistance, driven by DNA repair mechanisms and dynamic transitions between cellular states. Resistance mechanisms can involve different cellular pathways, most of which have been recently reported in the literature. Despite progress, targeted therapeutic approaches lack consensus due to GSCs' high plasticity.

AIM

To analyze targeted therapies against GSC-mediated resistance to radio- and chemotherapy in gliomas, focusing on underlying mechanisms.

METHODS

A systematic search was conducted across major medical databases (PubMed, Embase, and Cochrane Library) up to September 30, 2023. The search strategy utilized relevant Medical Subject Heading terms and keywords related to including "glioma stem cells", "radiotherapy", "chemotherapy", "resistance", and "targeted therapies". Studies included in this review were publications focusing on targeted therapies against the molecular mechanism of GSC-mediated resistance to radiotherapy resistance (RTR).

RESULTS

In a comprehensive review of 66 studies on stem cell therapies for SCI, 452 papers were initially identified, with 203 chosen for full-text analysis. Among them, 201 were deemed eligible after excluding 168 for various reasons. The temporal breakdown of studies illustrates this trend: 2005-2010 (33.3%), 2011-2015 (36.4%), and 2016-2022 (30.3%). Key GSC models, particularly U87 (33.3%), U251 (15.2%), and T98G (15.2%), emerge as significant in research, reflecting their representativeness of glioma characteristics. Pathway analysis indicates a focus on phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin (mTOR) (27.3%) and Notch (12.1%) pathways, suggesting their crucial roles in resistance development. Targeted molecules with mTOR (18.2%), CHK1/2 (15.2%), and ATP binding cassette G2 (12.1%) as frequent targets underscore their importance in overcoming GSC-mediated resistance. Various therapeutic agents, notably RNA inhibitor/short hairpin RNA (27.3%), inhibitors (e.g., LY294002, NVP-BEZ235) (24.2%), and monoclonal antibodies (e.g., cetuximab) (9.1%), demonstrate versatility in targeted therapies. among 20 studies (60.6%), the most common effect on the chemotherapy resistance response is a reduction in temozolomide resistance (51.5%), followed by reductions in carmustine resistance (9.1%) and doxorubicin resistance (3.0%), while resistance to RTR is reduced in 42.4% of studies.

CONCLUSION

GSCs play a complex role in mediating radioresistance and chemoresistance, emphasizing the necessity for precision therapies that consider the heterogeneity within the GSC population and the dynamic tumor microenvironment to enhance outcomes for glioblastoma patients.

Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma

BACKGROUND

Being among the most common malignancies worldwide, hepatocellular carcinoma (HCC) accounting for the third cause of cancer mortality. The regulation of cell death is the most crucial step in tumor progression and has become a crucial target for nearly all therapeutic options. Cuproptosis, a copper-induced cell death, was recently reported in Science. However, its primary function in carcinogenesis is still unclear.

METHODS

Cuproptosis-related lncRNAs significantly associated with overall survival (OS) were screened by stepwise univariate Cox regression. The signature of cuproptosis-related lncRNAs for HCC prognosis was constructed by the LASSO algorithm and multivariate Cox regression. Further Kaplan-Meier analysis, proportional hazards model, and ROC analysis were performed. Functional annotation was performed using gene set enrichment analysis (GSEA). The relationship between prognostic cuproptosis-related lncRNAs and HCC prognosis was further explored by GEPIA( http://gepia.cancer-pku.cn/ ) online analysis tool. Finally, we used the ESTIMATE and XCELL algorithms to estimate stromal and immune cells in tumor tissue and cast each sample to infer the underlying mechanism of cuproptosis-related lncRNAs in the tumor immune microenvironment (TIME) of HCC patients.

RESULTS

Four cuproptosis-related lncRNAs were used to construct a prognostic lncRNA signature, which was an independent factor in predicting OS in HCC patients. Kaplan-Meier curves showed significant differences in survival rates between risk subgroups (p = 0.002). At the same time, we found that the expression levels of most immune checkpoint genes increased with increasing risk scores. Tumorigenesis and immunological-related pathways were primarily enhanced in the high-risk group, as determined by GSEA. The results of drug sensitivity analysis showed that compared with patients in the high-risk group, the IC50 values of erlotinib and lapatinib were lower in patients in the low-risk group, while the opposite was true for sunitinib, paclitaxel, gemcitabine, and imatinib. We also found that elevated AL133243.2 expression was significantly associated with worse OS and disease-free survival (DFS), more advanced T stage and higher tumor grade, and reduced immune cell infiltration, suggesting that HCC patients with low AL133243.2 expression in tumor tissues may have a better response to immunotherapy.

CONCLUSION

Collectively, the cuproptosis-associated lncRNA signature can serve as an independent predictor to guide individual treatment strategies. Furthermore, AL133243.2 is a promising marker for predicting immunotherapy response in HCC patients. This data may facilitate further exploration of more effective immunotherapy strategies for HCC.

LncRNA as potential biomarker and therapeutic target in glioma

Glioma is the most frequent type of malignant tumor in the central nervous system, accounting for about 80% of primary malignant brain tumors, usually with a poor prognosis. A number of studies have been conducted on the molecular abnormalities in glioma to further understand its pathogenesis, and it has been found that lncRNAs (long non-coding RNA) play a key role in angiogenesis, tumor growth, infiltration and metastasis of glioma. Since specific lncRNAs have an aberrant expression in brain tissue, cerebrospinal fluid as well as peripheral circulation of glioma patients, they are considered to be potential biomarkers. This review focuses on the biological characteristics of lncRNA and its value as a biomarker for glioma diagnosis and prognosis. Moreover, in view of the role of lncRNAs in glioma proliferation and chemoradiotherapy resistance, we discussed the feasibility for lncRNAs as therapeutic targets. Finally, the persisting deficiencies and future prospects of using lncRNAs as clinical biomarkers and therapeutic targets were concluded.

Systematic characterization and biological functions of non-coding RNAs in glioblastoma

Glioblastoma multiforme (GBM) is the most malignant and aggressive type of glioma. Non-coding RNAs (ncRNAs) are RNAs that do not encode proteins but widely exist in eukaryotic cells. The common characteristics of these RNAs are that they can all be transcribed from the genome without being translated into proteins, thus performing biological functions, particularly microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs. Studies have found that ncRNAs are associated with the occurrence and development of GBM, and there is a complex regulatory network among ncRNAs, which can regulate cell proliferation, migration, apoptosis and differentiation, thus provide a basis for the development of highly specific diagnostic tools and therapeutic strategies in the future. The present review aimed to comprehensively describe the biogenesis, general features and functions of regulatory ncRNAs in GBM, and to interpret the potential biological functions of these ncRNAs in GBM as well as their impact on clinical diagnosis, treatment and prognosis and discusses the potential mechanisms of these RNA subtypes leading to cancer in order to contribute to the better design of personalized GBM therapies in the future.

KDELR1 Is an Independent Prognostic Predictor and Correlates With Immunity in Glioma

Background

Gliomas are the most malignant central nervous system tumors. With the development of sequencing technology, more potential biomarkers related to the treatment, prognosis, and molecular classification of glioma have been identified. Here, we intend to investigate the potential biological function and clinical value of a new biomarker in glioma.

Methods

KDELR1 expression data and the corresponding clinical information were downloaded from public databases and then preprocessed using R language. Correlation, Kaplan–Meier survival, and Cox regression analyses were performed to explore the clinical significance of KDELR1 in glioma patients. Furthermore, the immune infiltration and microenvironment parameters were evaluated via TIMER and CIBERSORT. Immunohistochemistry was conducted to confirm the KDELR1 expression and its correlation with immunity infiltration and prognosis.

Results

KDELR1 was upregulated in glioma samples compared with normal brain tissues, and its expression was significantly correlated with age, the World Health Organization (WHO) grade, recurrence, necrosis, microvascular proliferation, molecular classification, isocitrate dehydrogenase (IDH) mutation, and 1p/19q codeletion status. In addition, survival analysis showed that glioma patients with KDELR1 overexpression had shorter overall survival (OS) and disease-free survival times, and Cox regression analysis revealed that KDELR1 acted as an independent prognostic factor of OS in glioma patients. Gene set enrichment analysis indicated a significant enrichment of metabolism-associated pathways. KDELR1 expression was positively associated with immune infiltration (including infiltration by CD8+ T cells, CD4+ T cells, macrophages, and so on) and microenvironment parameters (including stromal, immune, and ESTIMATE scores) in gliomas. The expression of KDELR1 and its correlation with the tumor grade and prognosis were confirmed by immunohistochemistry in clinical samples (n = 119, P < 0.05).

Conclusions

Taken together, these findings suggest that KDELR1 is correlated with the tumor grade, molecular classifications, and immune infiltration; highlighting that KDELR1 is a novel and promising biomarker for molecular classification, treatment, and prognostic assessment may further indicate the treating effect of immune therapy.

Modification Patterns of DNA Methylation-Related lncRNAs Regulating Genomic Instability for Improving the Clinical Outcomes and Tumour Microenvironment Characterisation of Lower-Grade Gliomas

Background: DNA methylation is an important epigenetic modification that affects genomic instability and regulates gene expression. Long non-coding RNAs (lncRNAs) modulate gene expression by interacting with chromosomal modifications or remodelling factors. It is urgently needed to evaluate the effects of DNA methylation-related lncRNAs (DMlncRNAs) on genome instability and further investigate the mechanism of action of DMlncRNAs in mediating the progression of lower-grade gliomas (LGGs) and their impact on the immune microenvironment.

Methods: LGG transcriptome data, somatic mutation profiles and clinical features analysed in the present study were obtained from the CGGA, GEO and TCGA databases. Univariate, multivariate Cox and Lasso regression analyses were performed to establish a DMlncRNA signature. The KEGG and GO analyses were performed to screen for pathways and biological functions associated with key genes. The ESTIMATE and CIBERSORT algorithms were used to determine the level of immune cells in LGGs and the immune microenvironment fraction. In addition, DMlncRNAs were assessed using survival analysis, ROC curves, correlation analysis, external validation, independent prognostic analysis, clinical stratification analysis and qRT-PCR.

Results: We identified five DMlncRNAs with prognostic value for LGGs and established a prognostic signature using them. The Kaplan–Meier analysis revealed 10-years survival rate of 10.10% [95% confidence interval (CI): 3.27–31.40%] in high-risk patients and 57.28% (95% CI: 43.17–76.00%) in low-risk patients. The hazard ratio (HR) and 95% CI of risk scores were 1.013 and 1.009–1.017 (p &lt; 0.001), respectively, based on the univariate Cox regression analysis and 1.009 and 1.004–1.013 (p &lt; 0.001), respectively, based on the multivariate Cox regression analysis. Therefore, the five-lncRNAs were identified as independent prognostic markers for patients with LGGs. Furthermore, GO and KEGG analyses revealed that these lncRNAs are involved in the prognosis and tumorigenesis of LGGs by regulating cancer pathways and DNA methylation.

Conclusion: The findings of the study provide key information regarding the functions of lncRNAs in DNA methylation and reveal that DNA methylation can regulate tumour progression through modulation of the immune microenvironment and genomic instability. The identified prognostic lncRNAs have high potential for clinical grouping of patients with LGGs to ensure effective treatment and management.