Comprehensive Transcriptomic Analysis and Experimental Validation Identify lncRNA HOXA-AS2/miR-184/COL6A2 as the Critical ceRNA Regulation Involved in Low-Grade Glioma Recurrence

Functional characterization of key protein biomarkers in spontaneous intracerebral hemorrhage pathogenesis: Structure and function of NUAK1 protein and ERO1L protein macromolecules

The pathogenesis of spontaneous intracerebral hemorrhage (SICH) is still unclear. NUAK1 and ERO1L, as key proteins, may be involved in the pathogenesis of SICH, and their structure and function are worthy of further study. The objective of this research was to examine the involvement of NUAK1 and ERO1L in the etiology of SICH and their potential as biomarkers. Utilizing data collection and analytical methods, the study compared gene expression disparities between the encephalopathy cohort and the normal control group, employing a differential expression genes (DEGs) identification technique for initial filtering. Subsequently, gene set enrichment analysis (GSEA) was implemented to assess the functionality of the genes that exhibited differential expression. The LASSO model and support vector machine recursive feature elimination (SVM-RFE) were then employed to construct a feature selection process for the purpose of identifying key genes. Multiple datasets (GSE24265 and GSE137902) were analyzed using gene co-expression networks (WGCNA) to validate the screening results. The results showed significant differences in gene expression between the encephalopathy group and the normal group. By LASSO and SVM regression analysis, NUAK1 and ERO1L were screened as key genes. WGCNA further validated the importance of these two genes in SICH, and their co-expression networks revealed their potential functional associations. Therefore, NUAK1 protein plays an important role in cell growth, apoptosis and stress response, while ERO1L is closely related to protein folding and REDOX reaction.

LncRNA HOXA‑AS2 is a prognostic and clinicopathological predictor in patients with cancer: A meta‑analysis

Elevated expression of long non-coding RNA homeobox A cluster antisense RNA 2 (lncRNA HOXA-AS2) is known to have prognostic value in various solid tumors. The present meta-analysis aimed to comprehensively quantify its prognostic significance across a wider spectrum of malignancies and to provide an updated synthesis of evidence that could refine prognostic models. To achieve this aim, multiple databases were carefully searched for lncRNA HOXA-AS2-related articles published in the past 10 years. Hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to demonstrate the prognostic value of lncRNA HOXA-AS2 using Stata 15.0 software. The function of lncRNA HOXA-AS2 was inferred from its associations with key clinical outcomes such as lymph node metastasis, distant metastasis, tumor stage and tumor size, which may reflect its role in tumor biology. In the present systematic review and meta-analysis of 454 patients across 7 studies, it was found that high lncRNA HOXA-AS2 expression was significantly associated with a shorter overall survival (OS) time in patients with cancer (HR=2.14; 95% CI, 1.40-3.27; P<0.001). High lncRNA HOXA-AS2 expression was also associated with lymph node metastasis [odds ratio (OR)=2.06; 95% CI, 1.07-3.99; P=0.032], distant metastasis (OR=2.11; 95% CI, 1.15-3.88; P=0.016), advanced tumor stage (OR=2.71; 95% CI, 1.50-4.89; P=0.001) and larger tumor size (OR=2.02; 95% CI, 0.86-4.78; P=0.006). However, no significant association was observed with age (OR=1.00; 95% CI, 0.63-1.59; P=0.991) or sex (OR=1.55; 95% CI, 0.72-3.34; P=0.258). In conclusion, elevated expression of lncRNA HOXA-AS2 was significantly related to poor clinical outcomes in various cancer types, such as osteosarcoma, non-small cell lung cancer and papillary thyroid carcinoma, a finding that was further confirmed by the present study. Specifically, the potential of lncRNAHOXA-AS2 as a biomarker in assessing tumor stage, metastasis risk and OS in patients was demonstrated. However, the results of the present study also indicated that the expression of lncRNA HOXA-AS2 was not significantly associated with age or sex, suggesting its role in cancer progression might be independent of these factors. This insight may direct future research to place more focus on the relationship between lncRNA HOXA-AS2 and specific cancer types and clinical characteristics.

Identification of key genes in spontaneous cerebral hemorrhage and prevention of disease damage: LASSO and SVM regression

Prevention is more important than treatment, and the incidence of intracerebral hemorrhage can be effectively reduced by intervening on the risk factors of intracerebral hemorrhage. By studying the risk factors of spontaneous intracerebral hemorrhage, we can identify the risk factors to achieve the target of treatment and prevention. Through the use of the Least Absolute Shrinkage and Selection Operator (LASSO) and the Support Vector Machine (SVM), the two essential SICH-related genes, NUAK1 and ERO1L, were eliminated from consideration. A Venn analysis was performed, and based on the two important modules, it found that SICH was related with four critical genes: VCM1, CRNDE, COL6A2, and HSPB6. One gene (NUAK1) was dramatically downregulated in the illness group compared to the control group, whereas three essential genes (ERO1L, VCAM1, and COL6A2) were significantly upregulated in the disease group. In the end, the genes ERO1L, VCAM1, COL6A2, and NUAK1 were shown to be the most important ones for SICH. It is anticipated that these genes will become novel biomarkers as well as targets for the development of new pharmacotherapies for SICH.

Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family

BACKGROUND

Homeobox A (HOXA) family is involved in the development of malignancies as either tumor suppressors or oncogenes. However, their roles in glioblastoma (GBM) and clinical significance have not been fully elucidated.

METHODS

HOXA mutation and expressions in pan-cancers were investigated using GSCA and Oncomine, which in GBM were validated by cBioPortal, Chinese Glioma Genome Atlas (CGGA), and The Cancer Genome Atlas (TCGA) datasets. Kaplan-Meier analyses were conducted to determine prognostic values of HOXAs at genetic and mRNA levels. Diagnostic roles of HOXAs in tumor classification were explored by GlioVis and R software. Independent prognostic HOXAs were identified using Cox survival analyses, the least absolute shrinkage and selection operator (LASSO) regression, quantitative real-time PCR, and immunohistochemical staining. A HOXAs-based nomogram survival prediction model was developed and evaluated using Kaplan-Meier analysis, time-dependent Area Under Curve, calibration plots, and Decision Curve Analysis in training and validation cohorts.

RESULTS

HOXAs were highly mutated and overexpressed in pan-cancers, especially in CGGA and TCGA GBM datasets. Genetic alteration and mRNA expression of HOXAs were both found to be prognostic. Specific HOXAs could distinguish IDH mutation (HOXA1-7, HOXA9, HOXA13) and molecular GBM subtypes (HOXA1-2, HOXA9-11, HOXA13). HOXA1/2/3/10 were confirmed to be independent prognostic members, with high expressions validated in clinical GBM tissues. The HOXAs-based nomogram model exhibited good prediction performance and net benefits for patients in training and validation cohorts.

CONCLUSION

HOXA family has diagnostic values, and the HOXAs-based nomogram model is effective in survival prediction, providing a novel approach to support the treatment of GBM patients.

Role of COL6A2 in malignant progression and temozolomide resistance of glioma

BACKGROUND

Gliomas are one of the most common primary malignant tumors of the central nervous system, and have an unfavorable prognosis. Even combining precise surgery, chemotherapy and radiotherapy, the survival rate is still unsatisfactory. Chemotherapy resistance is one of main reasons for its adverse prognosis. As shown by several studies, glioma stem cells (GSCs) were correlated with radiotherapy/chemotherapy resistance and high relapse rate. This study aimed to find a new biomarker related to GSCs and chemotherapy resistance.

METHODS

TCGA, CGGA, GSE16011, GSE23806 and GDSC datasets were used to screen the genes related to GSCs, Temozolomide (TMZ) resistance, and survival. In the TCGA, GTEx, GSE16011 and CGGA datasets, mRNA level, prognostic value, and correlation with immune infiltration in the selected genes were analyzed through methods including Kaplan-Meier analysis, Cox analysis, the ESTIMATE algorithm, and the CIBERSORT algorithm. The expression of COL6A2 mRNA and protein in different groups was detected by RT-qPCR and western blot. A MTT assay and flow cytometry were used to measure the effect of COL6A2 on proliferation and apoptosis of glioma cells.

RESULTS

COL6A2 was positively correlated with glioma stemness and TMZ resistance. Its expression was up-regulated in GBM, and high expression was correlated with adverse prognosis. As shown by Cox analysis, COL6A2 was an independent prognostic factor for glioma. COL6A2 mRNA was increased with the glioma grade. It was over-expressed in MGMT non-methylation and IDH wild-type specimens. The results of in vitro experiments showed that COL6A2 promots proliferation of glioma cells and inhibits their apoptosis. Meanwhile, the expression of COL6A2 in TMZ-resistant glioma cells was significantly higher than that in ordinary glioma cells. As shown by GO and KEGG pathway analysis, COL6A2 was correlated with glioma proliferation, migration, invasion, and immunity. In particular, it was significantly positively correlated with PD-1, PD-L2, PD-L1, B7-H3, CTLA-4, IDO1 and TIM-3 expression, further verifying that it may play an important role in immune response. In addition, COL6A2 might influence immune cell infiltration in the glioma microenvironment.

CONCLUSION

COL6A2 high-expression is an indicator for adverse glioma prognosis, and is correlated with TMZ-resistant and immune response. Meanwhile, it may be a prospective biomarker for treatment.

Immune-related matrisomes are potential biomarkers to predict the prognosis and immune microenvironment of glioma patients

The extracellular matrix (ECM) plays a vital role in the progression and metastasis of glioma and is an important part of the tumor microenvironment. The matrisome is composed of ECM components and related proteins. There have been several studies on the effects of matrisomes on the glioma immune microenvironment, but most of these studies were performed on individual glioma immune-related matrisomes rather than integral analysis. Hence, an overall analysis of all potential immune-related matrisomes in gliomas is needed. Here, we divided 667 glioma patients in The Cancer Genome Atlas (TCGA) database into low, moderate, and high immune infiltration groups. Immune-related matrisomes differentially expressed among the three groups were analyzed, and a risk signature was established. Eight immune-related matrisomes were screened, namely, LIF, LOX, MMP9, S100A4, SRPX2, SLIT1, SMOC1, and TIMP1. Kaplan-Meier analysis, operating characteristic curve analysis, and nomogram were constructed to analyze the relationships between risk signatures and the prognosis of glioma patients. The risk signature was significantly correlated with the overall survival of glioma patients. Both high- and low-risk signatures were also associated with some immune checkpoints. In addition, analysis of somatic mutations and anti-PD1/L1 immunotherapy responses in the high- and low-risk groups showed that the high-risk group had worse prognosis and a higher response to anti-PD1/L1 immunotherapy. Our analysis of immune-related matrisomes may improve understanding of the characteristics of the glioma immune microenvironment and provide direction for glioma immunotherapy development in the future.

The pro-invasive factor COL6A2 serves as a novel prognostic marker of glioma

Background

Glioma is an incurable malignant lesion with poor outcome characterized by easy recurrence after surgery with or without radiotherapy and chemotherapy. Studies have shown that COL6A2 is closely related to the tumorigenesis and development of a variety of tumors. However, the role of COL6A2 in glioma and the relationship between COL6A2 and tumor infiltrating immune cells remain unclear.

Methods

Western blot, real-time PCR, a tissue microarray and immunohistochemistry were applied to detect COL6A2 mRNA and protein amounts in glioma, and all experiments were repeated three times. A tissue microarray of glioma samples was used for prognostic analysis. Detection of COL6A2 co-expression with immune genes using immunohistochemical methods, and tumor modeling using nude mice for prevention and treatment studies. Based on the mRNA expression of COL6A2, patients with glioma in TCGA were divided into the low and high COL6A2 expression groups, and GO and KEGG pathway analyses were performed. A PPI network was constructed using STRING, and the associations of COL6A2 with tumor-infiltrating immune cells and immune genes were analyzed in the CIBERSORT and TISIDB databases. COL6A2 mRNA and protein amounts were increased in glioma.

Results

Multiple-database and tissue microarray analyses showed that COL6A2 expression in glioma was associated with poor prognosis, Tissue microarray showed that COL6A2 was the highest expressed in WHO IV and significantly higher in TCGA-GBM than in TCGA-LGG. Immunohistochemistry can well demonstrate the co-expression of COL6A2 with immune genes in a tumor model established in nude mice, showing that interference with COL6A2 expression may have an inhibitory effect on tumors. The mRNA expression of COL6A2 was involved in 22 KEGG pathways, and GSEA analysis showed that 28 and 57 gene sets were significantly enriched at nominal p values <0.01 and <0.05, respectively, protein network revealed a tight interaction between COL6A2 and SPARC. The CIBERSORT database indicated that COL6A2 was correlated with 15 types of tumor-infiltrating immune cells, including M2 macrophages, CD8 T cells, neutrophils, gamma delta T cells, activated CD4 memory T cells, follicular helper T cells, M0 macrophages, M1 macrophages, regulatory T cells (Tregs), activated NK cells, eosinophils, activated mast cells, monocytes, activated dendritic cells, and resting CD4 memory T cells. The TISIDB database indicated that COL6A2 was significantly correlated with lymphocytes such as regulatory T cell, Type 17 T helper cell, Type 1 T helper cell, and immunomodulatory genes. In addition, COL6A2-related immune regulatory genes show that most immune regulatorygenes have prognostic value for glioma, and high-risk immune genes are notconducive to the survival of glioma patients.

Conclusions

COL6A2-related immune regulatory genes show that most immune regulatory genes have prognostic value for glioma, and high-risk immune genes are not conducive to the survival of glioma patients. COL6A2 may be a novel potential prognostic biomarker of glioma and associated with tumor-infiltrating immune cells in the tumor microenvironment, and interference with COL6A2 expression can inhibit tumor growth, which suggests COL6A2 as a potential target for future treatment.

HOXA-AS2 may predict the prognosis of solid tumors among Chinese patients: A meta-analysis and bioinformatic analysis

Background

HOXA cluster antisense RNA 2 (lncRNA HOXA-AS2) is a long noncoding RNA (lncRNA) that aberrantly expressed in various cancers and is closely associated with cancer progression. To overcome the limitation of small sample sizes that are inherent to single studies, a meta-analysis was conducted to explore the relationship between the expression level of HOXA-AS2 and cancer prognosis.

Methods

Correlational studies were retrieved by searching the databases of PubMed, Embase and Web of Science (up to August 10, 2022). The survival and prognosis data included overall survival (OS), and clinical parameters were gathered and analyzed.

Results

Eighteen publications with 1181 patients who were diagnosed with solid tumors were ultimately included. The results showed that, compared with patients with low HOXA-AS2 expression, patients with high HOXA-AS2 expression tended to have poorer overall survival (OS) (HR= 2.52, 95% CI 1.87-3.38, P < 0.01) and shorter disease-free survival (DFS) (HR=7.19, 95% CI 3.20-16.17, P < 0.01). In addition, elevated HOXA-AS2 expression indicated a larger tumor size (OR =2.43, 95% CI 1.53–3.88,P < 0.01), more advanced TNM stage (OR=3.85, 95% CI 2.79-5.31, P < 0.01), earlier lymph node metastasis (LNM) (OR = 4.41, 95% CI 3.05-6.39, P < 0.01) and distant metastasis (DM) (OR= 2.96, 95% CI 1.87-4.7, P < 0.01). Furthermore, HOXA-AS2 expression was notassociated with age (OR=1.15, 95% CI 0.90-1.47), gender (OR=1.16, 95% CI 0.89-1.53), or tumor differentiation (OR=1.21, 95% CI 0.56-2.63). Moreover, aberrant HOXA-AS2 expression was related to drug sensitivity in various types of cancers.

Conclusion

The overexpression of HOXA-AS2 predicted poor cancer prognosis in the Chinese population, including poor OS, DFS, TNM, LNM, and DM. HOXA-AS2 could serve as a promising prognostic biomarker and therapeutic target.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42022352604.

A Novel-Defined Necroptosis-Related miRNA Signature for Forecasting the Prognosis of Low-Grade Glioma

Background

Increasing evidence has shown that necroptosis has enormous significance in the generation and deterioration of cancer, and miRNA molecular markers involved in necroptosis in low-grade gliomas (LGGs) have not been thoroughly reported.

Methods

Using the miRNA data of 512 samples from The Cancer Genome Atlas (TCGA), 689 miRNAs from LGG samples were split into high immunity score and low immunity score groups for analysis. The differential miRNAs related to necroptosis were analyzed by univariate Cox regression analysis. On the basis of the outcome of univariate Cox regression analysis, miRNAs with significant differences were selected to construct a multivariate Cox regression model and calculate the risk score. Then, we evaluated whether the risk score could be used as an unaided prognostic factor.

Results

Overall, six differential miRNAs were identified (hsa-miR-148a-3p, hsa-miR-141-3p, hsa-miR-223-3p, hsa-miR-7-5p, hsa-miR-500a-3p, and hsa-miR-200a-5p). Univariate and multivariate Cox regression analyses were performed, and the c index was 0.71. Then, by mixing the risk score with clinicopathological factors, univariate Cox regression (HR: 2.7146, 95% CI: 1.8402−4.0044, P < 0.0001) and multivariate Cox regression analyses (HR: 2.3280, 95% CI: 1.5692−3.4536, P < 0.001) were performed. The data suggested that the risk score is an unaided prognostic indicator, which is markedly related with the overall survival time of LGG sufferers. Thus, a lower risk score is correlated with better prediction of LGG.

Conclusion

In order to achieve the ultimate goal of improving the living conditions of patients, we established prognostic risk model using 6 miRNAs related to necroptosis, which has the ability to predict the prognosis of LGG. It is possible to further enrich the therapeutic targets for LGG and provide clinical guidance for the treatment of LGG in the future.

Recognition of a Novel Gene Signature for Human Glioblastoma

Glioblastoma (GBM) is one of the most common malignant and incurable brain tumors. The identification of a gene signature for GBM may be helpful for its diagnosis, treatment, prediction of prognosis and even the development of treatments. In this study, we used the GSE108474 database to perform GSEA and machine learning analysis, and identified a 33-gene signature of GBM by examining astrocytoma or non-GBM glioma differential gene expression. The 33 identified signature genes included the overexpressed genes COL6A2, ABCC3, COL8A1, FAM20A, ADM, CTHRC1, PDPN, IBSP, MIR210HG, GPX8, MYL9 and PDLIM4, as well as the underexpressed genes CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C, SHANK2 and VIPR2. Protein functional analysis by CELLO2GO implied that these signature genes might be involved in regulating various aspects of biological function, including anatomical structure development, cell proliferation and adhesion, signaling transduction and many of the genes were annotated in response to stress. Of these 33 signature genes, 23 have previously been reported to be functionally correlated with GBM; the roles of the remaining 10 genes in glioma development remain unknown. Our results were the first to reveal that GBM exhibited the overexpressed GPX8 gene and underexpressed signature genes including CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C and SHANK2, which might play crucial roles in the tumorigenesis of different gliomas.

HOXA-AS2 enhances GBM cell malignancy by suppressing miR-2116-3p thereby upregulating SERPINA3

Background

Glioblastoma (GBM) is malignant, demanding more attention to the improvement of the diagnosis and therapy. LncRNAs have been implicated in the malignancy of GBM cells.

Methods

HOXA-AS2, miR-2116-3p and SERPINA3 expression levels in GBM tissues and cell lines were detected by qRT-PCR. Western blotting was performed to detect the protein levels of Bax and Bcl-2. Dual-luciferase reporter assay was for detection of relationship among these factors, together with RIP and RNA pull-down. CCK-8, EdU, wound healing and transwell assays were for detection of the role of HOXA-AS2, miR-2116-3p and SERPINA3 in cell viability, proliferation, migration and invasion in GBM, respectively.

Results

HOXA-AS2 and SERPINA3 showed higher level in GBM tissues and cell lines. Low level of HOXA-AS2 attenuated GBM cell growth in vitro. Moreover, the anti-tumor impact of silenced HOXA-AS2 was restored by miR-2116-3p inhibitor, but its tumor-promotional effect could be reversed by silenced SERPINA3.

Conclusion

HOXA-AS2 enhanced GBM cell malignancy through sponging miR-2116-3p and releasing SERPINA3, which might shed light on the diagnosis and therapy for GBM in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09462-y.

Establishment and Validation of a 5 m6A RNA Methylation Regulatory Gene Prognostic Model in Low-Grade Glioma

Background: The prognosis of low-grade glioma (LGG) is different from that of other intracranial tumors. Although many markers of LGG have been established, few are used in clinical practice. M6A methylation significantly affects the biological behavior of LGG tumors. Therefore, establishment of an LGG prognostic model based on m6A methylation regulatory genes is of great interest.

Methods: Data from 495 patients from The Cancer Genome Atlas (TCGA) and 172 patients from the Chinese Glioma Genome Atlas (CGGA) were analyzed. Univariate Cox analysis was used to identify methylation regulatory genes with prognostic significance. LASSO Cox regression was used to identify prognostic genes. Receiver operating characteristic (ROC) and Kaplan–Meier curves were used to verify the accuracy of the model. Gene Set Enrichment Analysis (GSEA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to identify cellular pathways that were significantly associated with the prognosis of LGG.

Results: A glioma prognostic model based on five methylation regulatory genes was established. Compared with low-risk patients, patients identified as high risk had a poorer prognosis. There was a high degree of consistency between the internal training and internal validation CGGA cohorts and the external validation TCGA cohort. Furthermore, KEGG and GSEA analyses showed that the focal adhesion and cell cycle pathways were significantly upregulated in high-risk patients. This signature could be used to distinguish among patients with different immune checkpoint gene expression levels, which may inform immune checkpoint inhibitor (ICI) immunotherapy.

Conclusion: We comprehensively evaluated m6A methylation regulatory genes in LGG and constructed a prognostic model based on m6A methylation, which may improve prognostic prediction for patients with LGG.

Emerging role of long noncoding RNAs in recurrent hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains one of the most frequent types of liver cancer and is characterized by a high recurrence rate. Recent studies have proposed that long non-coding RNAs (lncRNAs) are potential biomarkers in several recurrent tumor types. It is now well understood that invasion, migration, and metastasis are important factors for tumor recurrence. Moreover, some of the known risk factors for HCC may affect the expression levels of several types of lncRNAs and thus affect the recurrence of liver cancer through lncRNA regulation. In this paper, we review the biological functions, molecular mechanisms, and roles of lncRNAs in HCC and summarize current knowledge about lncRNAs as potential biomarkers in recurrent HCC.

AGAP2-AS1 May Promote the Occurrence and Development of Glioblastoma by Sponging miR-9-5p: Evidence From a ceRNA Network

Glioblastoma (GBM), the primary malignant brain tumor, is typically associated with a poor prognosis and poor quality of life, mainly due to the lack of early diagnostic biomarkers and therapeutic targets. However, gene sequencing technologies and bioinformatics analysis are currently being actively utilized to explore potential targets for the diagnosis and management of malignancy. Herein, based on a variety of bioinformatics tools for the reverse prediction of target genes associated with the prognosis of GBM, a ceRNA network of AGAP2-AS1-miR-9-5p-MMP2/MMP9 was constructed, and a potential therapeutic target for GBM was identified. Enrichment analysis predicted that the ceRNA regulatory network participates in the processes of cell proliferation, differentiation, and migration.

NPC2 as a Prognostic Biomarker for Glioblastoma Based on Integrated Bioinformatics Analysis and Cytological Experiments

Glioblastoma (GBM) is one of the most common and fatal malignancies worldwide, while its prognostic biomarkers are still being explored. This study aims to identify potential genes with clinical and prognostic significance by integrating bioinformatics analysis and investigating their function in HNSCC. Based on the Single-cell RNA sequencing (scRNA-seq) results of H3K27M-glioma cells, computational bioinformatics methods were employed for selecting prognostic biomarker for GBM. The protein NPC2 (NPC Intracellular Cholesterol Transporter 2), which has been shown to be related to lipoprotein metabolism and innate immune system, was identified to be upregulated in GBM. NPC2 showed a relatively higher expression in GBM samples, and a negative correlation with tumor purity and tumor infiltrating immune cells. Additionally, NPC2 was knocked down in U87-MG and U251 cells line, and cell proliferation and migration capability were evaluated with CCK-8, scratch and transwell assay, respectively. Cytological experiments has shown that NPC2 overexpression inhibited GBM cells proliferation and migration, indicating its important role in GBM progression. This is the first investigation into the prognostic value of NPC2 interact with GBM. The potential molecular factor NPC2 have been identified as a prognostic biomarker for GBM.

Long non-coding RNA signatures as predictors of prognosis in thyroid cancer: a narrative review

Thyroid cancer (TC) is the most common endocrine malignancy, with high incidence rates in recent decades. Most TC cases have good prognoses, but a high risk of recurrence and metastases poses challenges, especially for patients with high-risk factors. Currently used prognostic markers for TC involve a combination of genetic factors and overexpressed proteins. Long non-coding RNAs (lncRNAs) regulate several integral biologic processes by playing key roles in the transcription of several downstream targets maintaining cellular behavior. Prior studies have revealed that lncRNAs promote tumor cell proliferation, invasion, metastasis, and angiogenesis, making them important targets for therapeutic intervention in cancer. While the exact molecular mechanisms underlying the role of lncRNAs in modulating TC progression and recurrence is still unclear, it is important to note that some lncRNAs are upregulated in certain cancers, while others are downregulated. In the present study, we review several key lncRNAs, their association with cancer progression, and the important roles they may play as tumor suppressors or tumor promoters in tumorigenesis. We discuss the potential mechanisms of lncRNA-mediated pathogenesis that can be targeted for the treatment of TC, the existing and potential benefits of using lncRNAs as diagnostic and prognostic measures for cancer detection, and tumor burden in patients.

Long non-coding RNAs as epigenetic mediator and predictor of glioma progression, invasiveness, and prognosis

Gliomas are aggressive brain tumors with high mortality rate. Over the past several years, non-coding RNAs, specifically the long non-coding RNAs (lncRNAs), have emerged as biomarkers of considerable interest. Emerging data reveals distinct patterns of expressions of several lncRNAs in the glioma tissues, relative to their expression in normal brains. This has led to the speculation for putative exploitation of lncRNAs as diagnostic biomarkers as well as biomarkers for targeted therapy. With a focus on lncRNAs that have shown promise as epigenetic biomarkers in the proliferation, migration, invasion, angiogenesis and metastasis in various glioma models, we discuss several such lncRNAs. The data from cell line / animal model-based studies as well as analysis from human patient samples is presented for the most up-to-date information on the topic. Overall, the information provided herein makes a compelling case for further evaluation of lncRNAs in clinical settings.