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.

LINC00467 Is Upregulated by DNA Copy Number Amplification and Hypomethylation and Shows ceRNA Potential in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common histological lung cancer, and it is the leading cause of cancer-related deaths worldwide. Long noncoding RNAs (lncRNAs) have been implicated in tumorigenesis. LINC00467 is a novel lncRNA that is abnormally expressed in several cancer types including LUAD. However, its function and regulatory mechanism in LUAD progression remain unclear. In this study, based on The Cancer Genome Atlas data mining, we demonstrated that DNA copy number amplification and hypomethylation was positively correlated with LINC00467 expression in LUAD. In addition, DNA copy number amplification was significantly associated with distant metastasis, immune infiltration and poor survival. Microarray analysis demonstrated that LINC00467 knockdown in the LUAD A549 cell line led to a distinct microRNA expression profile that impacted various target genes involved in multiple biological processes. This finding suggests that LINC00467 may regulate LUAD progression by functioning as a competing endogenous RNA (ceRNA). Finally, we constructed a ceRNA network that included two microRNAs (hsa-miR-1225-5p, hsa-miR-575) and five mRNAs (BARX2, BCL9, KCNK1, KIAA1324, TMEM182) specific to LINC00467 in LUAD. Subsequent Kaplan-Meier survival analysis in both The Cancer Genome Atlas and Gene Expression Omnibus databases revealed that two genes, BARX2 and BCL9, were potential prognostic biomarkers for LUAD patients. In conclusion, our data provide possible mechanisms underlying the abnormal upregulation of LINC00467 as well as a comprehensive view of the LINC00467-mediated ceRNA network in LUAD, thereby highlighting its potential role in diagnosis and therapy.

Integrin Alpha L as an Immune-Related Biomarker Correlated with the Prognosis and Effect of Immunotherapy in Gliomas

Backgroud: Discovering effective immune-related biomarkers is vital to ensure efficient immunotherapy for glioma patients. Integrin Alpha L(ITGAL), essential to inflammatory and immune responses, have not been studied in gliomas, systematically. Methods RNA‑seq data and corresponding clinical information of glioma patients were collected from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), and mRNA data of normal brain tissues were obtained in Genotype-Tissue Expression (GTEx) project. Wilcoxon test was performed to analyze the correlation of ITGAL expression and glioma subtypes. Univariate and multivariate cox proportional hazards regression, receiver operating characteristic (ROC) curves and Kaplan-Meier plots were used to evaluate the prognostic value of ITGAL in glioma. Functional enrichment analyses and immune infiltration analysis were performed to investigate the potential function in mediating the immune response in the tumor microenvironment. Finally, we evaluated the ability of ITGAL for predicting the efficacy of ICB treatment for patients. Results We found the up-regulation of ITGAL may predict a poor prognosis for glioma patients, the expression level increased with the increasing of WHO grade and 1p19q co-deletion status and IDH mutation status. The total methylation level and copy number variation of ITGAL were moderately correlated with its mRNA expression in LGG samples (P < 0.05). Furthermore, ITGAL was correlated with the immunosuppressive tumor microenvironment for the strong correlation with M2 macrophages and Tregs. Finally, GSEA showed the upregulation of ITGAL was mainly involved in the signal recognition and regulation between immune cells, and Toll-like receptor signaling pathway. Conclusion ITGAL is a novel tumor-related and immune-associated biomarker, which could predict the prognosis and effect of ICB therapy for glioma patients.

The ALDH Family Contributes to Immunocyte Infiltration, Proliferation and Epithelial-Mesenchymal Transformation in Glioma

Gliomas are malignant tumors that originate from the central nervous system. The aldehyde dehydrogenase family has been documented to affect cancer progression; however, its role in gliomas remains largely unexplored. Bulk RNA-seq analysis and single-cell RNA-Seq analysis were performed to explore the role of the aldehyde dehydrogenases family in gliomas. Training cohort contained The Cancer Genome Atlas data, while data from Chinese Glioma Genome Atlas and Gene Expression Omnibus were set as validation cohorts. Our scoring system based on the aldehyde dehydrogenases family suggested that high-scoring samples were associated with worse survival outcomes. The enrichment score of pathways were calculated by AUCell to substantiate the biofunction prediction results that the aldehyde dehydrogenases family affected glioma progression by modulating tumor cell proliferation, migration, and immune landscape. Tumor immune landscape was mapped from high-scoring samples. Moreover, ALDH3B1 and ALDH16A1, two main contributors of the scoring system, could affect glioblastoma cell proliferation and migration by inducing cell-cycle arrest and the epithelial-mesenchymal transition. Taken together, the aldehyde dehydrogenases family could play a significant role in the tumor immune landscape and could be used to predict patient prognosis. ALDH3B1 and ALDH16A1 could influence tumor cell proliferation and migration.

Comprehensive Analysis of Pyroptosis-Associated in Molecular Classification, Immunity and Prognostic of Glioma

Integrative analysis was performed in the Chinese Glioma Genome Atlas and The Cancer Genome Atlas to describe the pyroptosis-associated molecular classification and prognostic signature in glioma. Pyroptosis-related genes were used for consensus clustering and to develop a prognostic signature. The immune statuses, molecular alterations, and clinical features of differentially expressed genes were analyzed among different subclasses and risk groups. A lncRNA-miRNA-mRNA network was built, and drug sensitivity analysis was used to identify small molecular drugs for the identified genes. Glioma can be divided into two subclasses using 30 pyroptosis-related genes. Cluster 1 displayed high immune signatures and poor prognosis as well as high immune-related function scores. A prognostic signature based on 15 pyroptosis-related genes of the CGGA cohort can predict the overall survival of glioma and was well validated in the TCGA cohort. Cluster 1 had higher risk scores. The high-risk group had high immune cell and function scores and low DNA methylation of pyroptosis-related genes. The differences in pyroptosis-related gene mutations and somatic copy numbers were significant between the high-risk and low-risk groups. The ceRNA regulatory network uncovered the regulatory patterns of different risk groups in glioma. Nine pairs of target genes and drugs were identified. In vitro, CASP8 promotes the progression of glioma cells. Pyroptosis-related genes can reflect the molecular biological and clinical features of glioma subclasses. The established prognostic signature can predict prognosis and distinguish molecular alterations in glioma patients. Our comprehensive analyses provide valuable guidelines for improving glioma patient management and individualized therapy.

Prognostic characterization of the pyroptosis-related subtypes and tumor microenvironment infiltration in glioma

Background Pyroptosis could regulate tumor cell trafficking, invasion, and metastasis, as well as tumor microenvironment (TME). However, prognostic characteristics of pyroptosis-related genes (PRGs) and their impact on the progression of glioma remain insufficient. Methods The genetic, transcriptional, and survival data of glioma patients used for bioinformatics analysis were obtained from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. Results We first screened two different molecular subtypes and found that PRG variations were associated with the characteristics of TME cell infiltration, clinicopathological characteristics, and prognosis of patients with glioma. After Cox regression of differentially expressed genes, a risk-score for predicting overall survival (OS) and progression-free survival (PFS) was calculated and its predictive accuracy in glioma patients was then validated. The high-risk group of PRGs signature showed a significantly poor OS compared to the low-risk group (training cohort, p <0.001, validation cohort, p <0.001). A high risk-score implies more immune cell infiltration and a better immunotherapy response to immune checkpoint blockers. Furthermore, the risk-score was significantly associated with the chemotherapeutic drug sensitivity and cancer stem cell (CSC) index. Subsequently, we established a highly accurate nomogram to facilitate the applicability in the preliminary clinical application of the risk-score. Conclusion Our findings may lay the foundation for future research targeting pyroptosis in glioma and pave the way for evaluating prognosis and developing more effective immunotherapy strategies.

Functional implications of aging-related lncRNAs for predicting prognosis and immune status in glioma patients

Glioma, is the most prevalent intracranial tumor with high recurrence and mortality rate. Long noncoding RNAs (lncRNAs) play a critical role in the occurrence and progression of tumors as well as in aging regulation. Our study aimed to establish a new glioma prognosis model by integrating aging-related lncRNAs expression profiles and clinical parameters in glioma patients from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) datasets. The Pearson correlation analysis ( |R|> 0.6, P＜0.001) was performed to explore the aging-related lncRNAs, and univariate cox tregresion and least absolute shrinkage and selection operator (LASSO) regression were used to screening prognostic signature in glioma patients. Based on the fifteen lncRNAs, we can divide glioma patients into three subtypes, and developed a prognostic model. Kaplan-Meier survival curve analysis showed that low-risk patients had longer survival time than high-risk group. Principal component analysis indicated that aging-related lncRNAs signature had a clear distinction between high- and low-risk groups. We also found that fifteen target lncRNAs were closely correlated with 119 genes by establishing a co-expression network. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis displayed different function and pathways enrichment in high-and low-risk groups. The different missense mutations were observed in two groups, and the most frequent variant types were single nucleotide polymorphism (SNP). This study demonstrated that the novel aging-related lncRNAs signature had an important prognosis prediction and may contribute to individual treatment for glioma.

Down-Regulation of miR-194-5p for Predicting Metastasis in Breast Cancer Cells

MicroRNAs (miRNAs), as key negative regulators of gene expression, are closely related to tumor occurrence and progression. miR-194-5p (miR-194-1) has been shown to play a regulatory role in various cancers however, its biological function and mechanism of action in breast cancer have not yet been well explored. In this study, we use the UALCAN and LinkedOmics databases to analyze transcription expression in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA). The epithelial-mesenchymal transition status of breast cancer cells was evaluated by wound-healing assay, trans-well assays, and gelatin zymography, while protein expression was assessed by Western blotting. miR-194-5p expression was found to be up-regulated in breast cancer clinical specimens but down-regulated in the triple-negative breast cancer (TNBC) cell line MDA-MB-231 and breast cancer clinical specimens in The Cancer Genome Atlas (TCGA). miR-194-5p significantly inhibited the expression of the epithelial marker ZO-1 and increased the expression of mesenchymal markers, including ZEB-1 and vimentin, in MDA-MB-231 cells. miR-194-5p significantly reduced the gelatin-degrading activity of matrix metalloproteinase-2 (MMP-2) and MMP-9 in zymography assays. In MDA-MB-231 cells and TCGA patient samples, ZEB-1 expression was significantly inversely correlated with miR-194-5p expression. High levels of miR-194-5p were associated with good overall survival. miR-194-5p regulates epithelial–mesenchymal transition (EMT) in TNBC. Our findings suggest that miR-194-5p functions as a tumor biomarker in breast cancer, providing new insights for the study of breast cancer development and metastasis.

Classification Systems of Endometrial Cancer: A Comparative Study about Old and New

Endometrial cancer is the most common gynecological malignancy of the female reproductive organs. Historically it was divided into type I and type II, until 2013 when the Cancer Genome Atlas molecular classification was proposed. Here, we applied the different classification types on our endometrial cancer patient cohort in order to identify the most predictive one. We enrolled 117 endometrial cancer patients available for the study and collected the following parameters: age, body mass index, stage, menopause, Lynch syndrome status, parity, hypertension, type of localization of the lesion at hysteroscopy, type of surgery and complications, and presence of metachronous or synchronous tumors. The tumors were classified according to the European Society for Medical Oncology, Proactive Molecular Risk Classifier for Endometrial Cancer, Post-Operative Radiation Therapy in Endometrial Carcinoma, and Cancer Genome Atlas classification schemes. Our data confirmed that European Society for Medical Oncology risk was the strongest predictor of prognosis in our cohort. The parameters correlated with poor prognosis were the histotype, FIGO stage, and grade. Our study cohort shows that risk stratification should be based on the integration of histologic, clinical, and molecular parameters.