Classification related to immunogenic cell death predicts prognosis, immune microenvironment characteristics, and response to immunotherapy in lower-grade gliomas.

Background: Immunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG). Materials and methods: We identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation. Results: 32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells. Conclusion: We established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy.

Identification of cuproptosis-related subtypes and the development of a prognostic model in glioma.

Introduction: A copper-dependent cell death, cuproptosis, involves copper binding with lipoylated tricarboxylic acid (TCA) cycle components. In cuproptosis, ferredoxin 1 (FDX1) and lipoylation act as key regulators. The mechanism of cuproptosis differs from the current knowledge of cell death, which may invigorate investigations into copper's potential as a cancer treatment. An extremely dismal prognosis is associated with gliomas, the most prevalent primary intracranial tumor. In patients with glioma, conventional therapies, such as surgery and chemotherapy, have shown limited improvement. A variety of cell death modes have been confirmed to be operative in glioma oncogenesis and participate in the tumor microenvironment (TME), implicated in glioma development and progression. In this study, we aimed to explore whether cuproptosis influences glioma oncogenesis. Methods: Gene expression profiles related to cuproptosis were comprehensively evaluated by comparing adjacent tissues from glioma tissues in The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) database. Gene expression, prognostic, clinical, and pathological data of lower-grade gliomas (LGG) and glioblastoma were retrieved from TCGA and Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. The datasets were managed by "Combat" algorithm to eliminate batch effects and then combined. A consensus clustering algorithm based on the Partitioning Around Medoid (PAM) algorithm was used to classified 725 patients with LGG and glioblastoma multiforme (GBM) into two cuproptosis subtypes. According to the differentially expressed genes in the two cuproptosis subtypes, 725 patients were divided into 2 gene subtypes. Additionally, a scoring system that associated with TME was constructed to predict patient survival and patient immunotherapy outcomes. Furthermore, we constructed a prognostic CRG-score and nomogram system to predict the prognosis of glioma patients. 95 tissue specimens from 83 glioma patients undergoing surgical treatment were collected, including adjacent tissues. Using immunohistochemistry and RT-qPCR, we verified cuproptosis-related genes expression and CRG-score predictive ability in these clinical samples. Results: Our results revealed extensive regulatory mechanisms of cuproptosis-related genes in the cell cycle, TME, clinicopathological characteristics, and prognosis of glioma. We also developed a prognostic model based on cuproptosis. Through the verifications of database and clinical samples, we believe that cuproptosis affects the prognosis of glioma and potentially provides novel glioma research approaches. Conclusion: We suggest that cuproptosis has potential importance in treating gliomas and could be utilized in new glioma research efforts.

miR-33b in human cancer: Mechanistic and clinical perspectives.

The microRNAs (miRNAs), an extensive class of small noncoding RNAs (∼22 nucleotides), have been shown to have critical functions in various biological processes during development. miR-33b (or hsa-miR-33b) is down-regulated in cancer of multiple systems. Notably, at least 27 protein-coding genes can be targeted by miR-33b. miR-33b regulates the cell cycle, cell proliferation, various metabolism pathways, epithelial-mesenchymal transition (EMT), cancer cell invasion and migration, etc. In prostate cancer, Cullin 4B (CUL4B) can be recruited to the promoter to inhibit the expression of miR-33b. In gastric cancer, the hypermethylation of the CpG island regulated the expression of miR-33b. Besides, miR-33b could be negatively regulated by 7 competing-endogenous RNAs (ceRNAs), which are all long non-coding RNAs (lncRNAs). There are at least 4 signaling pathways, including NF-κB, MAP8, Notch1, and Wnt/ß-catenin signaling pathways, which could be regulated partially by miR-33b. Additionally, low expression of miR-33b was associated with clinicopathology and prognosis in cancer patients. In addition, the aberrant expression of miR-33b was connected with the resistance of cancer cells to 5 anticancer drugs (cisplatin, docetaxel, bortezomib, paclitaxel, and daunorubicin). Importantly, our work systematically summarizes the aberrant expression of miR-33b in various neoplastic diseases and the effect of its downregulation on the biological behavior of cancer cells. Furthermore, this review focuses on recent advances in understanding the molecular regulation mechanisms of miR-33b. Moreso, the relationship between the miR-33b expression levels and the clinicopathological data and prognosis of tumor patients was summarized for the first time. Overall, we suggest that the current studies of miR-33b are insufficient but provide potential hints and direction for future miR-33b-related research.

The role of lncRNA just proximal to XIST (JPX) in human disease phenotypes and RNA methylation: The novel biomarker and therapeutic target potential.

Increasing evidence suggests that long non-coding RNAs (lncRNAs) are closely related to the initialization and development of human diseases. lncRNA just proximal to XIST (JPX), as a newly identified lncRNA, has been reported to be aberrantly expressed and associated with pathophysiological traits in numerous diseases, particularly cancers. More importantly, JPX has been proven to play important roles in various biological functions, including cell proliferation, migration, invasion, apoptosis, chemoresistance, and differentiation. In addition, we discuss the diverse molecular mechanisms and correlation with RNA methylation of JPX in several cancers. In this Review, we summarize current studies on JPX's roles in diseases and its potential application as a biomarker for both diagnoses and prognoses and a therapeutic target in human diseases.

Integrated analysis of inflammatory response subtype-related signature to predict clinical outcomes, immune status and drug targets in lower-grade glioma.

Background: The inflammatory response in the tumor immune microenvironment has implications for the progression and prognosis in glioma. However, few inflammatory response-related biomarkers for lower-grade glioma (LGG) prognosis and immune infiltration have been identified. We aimed to construct and identify the prognostic value of an inflammatory response-related signature, immune infiltration, and drug targets for LGG. Methods: The transcriptomic and clinical data of LGG samples and 200 inflammatory response genes were obtained from public databases. The LGG samples were separated into two inflammatory response-related subtypes based on differentially expressed inflammatory response genes between LGG and normal brain tissue. Next, inflammatory response-related genes (IRRGs) were determined through a difference analysis between the aforementioned two subtypes. An inflammatory response-related prognostic model was constructed using IRRGs by using univariate Cox regression and Lasso regression analyses and validated in an external database (CGGA database). ssGSEA and ESTIMATE algorithms were conducted to evaluate immune infiltration. Additionally, we performed integrated analyses to investigate the correlation between the prognostic signature and N 6-methyladenosine mRNA status, stemness index, and drug sensitivity. We finally selected MSR1 from the prognostic signature for further experimental validation. Results: A total of nine IRRGs were identified to construct the prognostic signature for LGG. LGG patients in the high-risk group presented significantly reduced overall survival than those in the low-risk group. An ROC analysis confirmed the predictive power of the prognostic model. Multivariate analyses identified the risk score as an independent predictor for the overall survival. ssGSEA revealed that the immune status was definitely disparate between two risk subgroups, and immune checkpoints such as PD-1, PD-L1, and CTLA4 were significantly expressed higher in the high-risk group. The risk score was strongly correlated with tumor stemness and m6A. The expression levels of the genes in the signature were significantly associated with the sensitivity of tumor cells to anti-tumor drugs. Finally, the knockdown of MSR1 suppressed LGG cell migration, invasion, epithelial-mesenchymal transition, and proliferation. Conclusion: The study constructed a novel signature composed of nine IRRGs to predict the prognosis, potential drug targets, and impact immune infiltration status in LGG, which hold promise for screening prognostic biomarkers and guiding immunotherapy for LGG.

Potential mechanisms underlying the promoting effects of 3D collagen scaffold culture on stemness and drug resistance of glioma cells.

BACKGROUND: 3D collagen scaffold culture is a good tool to study glioma metastasis and recurrence in vitro. METHODS: The effect of 3D collagen culture on the colony formation, the sphere formation, and drug sensitivity of glioma cells was observed by soft-agar colony formation assays, sphere formation assays, and CCK-8 assays, respectively. 3D-glioma-drug genes were identified by previous results and online databases. Gene enrichment and PPI analyses were performed by R software and Metacsape. Hub 3D-glioma-drug genes were screened by STRING and Cytoscape. TCGA and CGGA databases and R software were used to analyze the distribution of hub genes in glioma and their effects on the prognosis. Western Blot was used to verify the effect of 3D collagen culture on the expression of hub genes. miRNAs targeting hub genes were predicted by ENCORI. RESULTS: 3D collagen scaffold culture promoted colony formation, sphere formation, and drug resistance of glioma cells. There were 77 3D-glioma-drug genes screened, and the pathways enriched in the protein interaction network mainly included responses to stressors, DNA damage and repair, and drug metabolism. Hub 3D-glioma-drug genes were AKT1, ATM, CASP3, CCND1, EGFR, PARP1, and TP53. These genes and predicted miRNAs were expressed differentially in glioma samples and partially affected the prognosis of patients with glioma. These findings suggested these hub genes and miRNAs may play a key role in the effects generated by the 3D culture model and become new markers for glioma diagnosis and treatment.

FBXW7 and the Hallmarks of Cancer: Underlying Mechanisms and Prospective Strategies.

FBXW7, a member of the F-box protein family within the ubiquitin-proteasome system, performs an indispensable role in orchestrating cellular processes through ubiquitination and degradation of its substrates, such as c-MYC, mTOR, MCL-1, Notch, and cyclin E. Mainly functioning as a tumor suppressor, inactivation of FBXW7 induces the aberrations of its downstream pathway, resulting in the occurrence of diseases especially tumorigenesis. Here, we decipher the relationship between FBXW7 and the hallmarks of cancer and discuss the underlying mechanisms. Considering the interplay of cancer hallmarks, we propose several prospective strategies for circumventing the deficits of therapeutic resistance and complete cure of cancer patients.

LncRNAs and their RBPs: How to influence the fate of stem cells?

Stem cells are distinctive cells that have self-renewal potential and unique ability to differentiate into multiple functional cells. Stem cell is a frontier field of life science research and has always been a hot spot in biomedical research. Recent studies have shown that long non-coding RNAs (lncRNAs) have irreplaceable roles in stem cell self-renewal and differentiation. LncRNAs play crucial roles in stem cells through a variety of regulatory mechanisms, including the recruitment of RNA-binding proteins (RBPs) to affect the stability of their mRNAs or the expression of downstream genes. RBPs interact with different RNAs to regulate gene expression at transcriptional and post-transcriptional levels and play important roles in determining the fate of stem cells. In this review, the functions of lncRNAs and their RBPs in self-renewal and differentiation of stem cell are summarized. We focus on the four regulatory mechanisms by which lncRNAs and their RBPs are involved in epigenetic regulation, signaling pathway regulation, splicing, mRNA stability and subcellular localization and further discuss other noncoding RNAs (ncRNAs) and their RBPs in the fate of stem cells. This work provides a more comprehensive understanding of the roles of lncRNAs in determining the fate of stem cells, and a further understanding of their regulatory mechanisms will provide a theoretical basis for the development of clinical regenerative medicine.

TBL1X and Flot2 form a positive feedback loop to promote metastasis in nasopharyngeal carcinoma.

Metastasis is the main cause of death in patients with nasopharyngeal carcinoma (NPC). The molecular mechanisms underlying the metastasis of NPC remain to be elucidated. TBL1X has been shown abnormally expressed in diverse cancers. However, the role and mechanism of TBL1X in NPC remain unknown. Here, we showed TBL1X expression was significantly higher in metastatic NPC tissues compared to non-metastatic tissues and significantly correlated with TNM stage and metastasis of NPC patients. In addition, NPC patients with high TBL1X expression had a poor prognosis. TBL1X interacted with TCF4 to trans-activate Flot2 expression. TBL1X promoted NPC cell migration and invasion in vitro and in vivo through Flot2. Moreover, Flot2 increased the expression of TBL1X by upregulating c-myc, which was identified to be a positively regulatory transcription factor of TBL1X. TBL1X could restore the functional changes of NPC cells resulting from Flot2 alteration. TBL1X and Flot2 were positively correlated in NPC. Patients with high expression of both TBL1X and Flot2 possessed poorer overall survival (OS) and disease-free survival (DFS) compared to patients with high expression of any single one of the two proteins. Our findings demonstrate that TBL1X and Flot2 positively regulate each other to promote NPC metastasis, which provides novel potential molecular targets for NPC treatment.

Research progress on drugs targeting the TGF-ß signaling pathway in fibrotic diseases.

Tissue fibrosis is a key factor leading to disability and death worldwide; however, thus far, there are no approved treatments for fibrosis. Transforming growth factor (TGF)-ß is a major pro-fibrotic cytokine, which is expected to become a target in the treatment of fibrosis; however, since TGF-ß has a wide range of biological functions involving a variety of biological processes in the body, a slight change in TGF-ß may have a systematic effect. Indiscriminate inhibition of TGF-ß can lead to adverse reactions, which can affect the efficacy of treatment. Therefore, it has become very important to explore how both the TGF-ß signaling pathway is inhibited and the safe and efficient TGF-ß small molecule inhibitors or neutralizing antibodies are designed in the treatment of fibrotic diseases. In this review, we mainly discuss the key role of the TGF-ß signaling pathway in fibrotic diseases, as well as the development of fibrotic drugs in recent years, and explore potential targets in the treatment of fibrotic diseases in order to guide subsequent drug development.

When stem cells meet COVID-19: recent advances, challenges and future perspectives.

Coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory coronavirus 2 is currently spreading throughout the world with a high rate of infection and mortality and poses a huge threat to global public health. COVID-19 primarily manifests as hypoxic respiratory failure and acute respiratory distress syndrome, which can lead to multiple organ failure. Despite advances in the supportive care approaches, there is still a lack of clinically effective therapies, and there is an urgent need to develop novel strategies to fight this disease. Currently, stem cell therapy and stem cell-derived organoid models have received extensive attention as a new treatment and research method for COVID-19. Here, we discuss how stem cells play a role in the battle against COVID-19 and present a systematic review and prospective of the study on stem cell treatment and organoid models of COVID-19, which provides a reference for the effective control of the COVID-19 pandemic worldwide.

Identification of three tumor antigens and immune subtypes for mRNA vaccine development in diffuse glioma.

Rationale: Diffuse glioma patients have high mortality and recurrence despite multimodal therapies. This study aims to identify the potential tumor antigens for mRNA vaccines and subtypes suitable for the immunotherapy of patients with diffuse glioma. Methods: Gene expression profiles and corresponding clinical information were obtained from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) databases. Genetic alterations were extracted from cBioPortal. Differential gene analysis, survival analysis, correlation analysis, consensus clustering analysis, and immune cell infiltration analysis were conducted based on the various databases. Finally, the hub genes, the modules related to tumor antigens, and the immune subtypes were identified using WGCNA method. Results: Three over-expressed, amplified, and mutated tumor antigens, including KDR, COL1A2, and SAMD9, were associated with clinical outcomes. The expression of the three genes had a positive correlation with the abundance of antigen-presenting cells (APCs) and APC marker expression. Subsequently, three immune subtypes (Ims1, Ims2, and Ims3) were distinguished in the TCGA cohort, which exhibited distinct molecular, cellular, and clinical characteristics consistent with the CGGA cohort. Diffuse gliomas with subtype Ims1 were more malignant with immunosuppressive phenotypes and more associated with poor prognosis than the other two subtypes. The three antigens and the immune checkpoints were differentially expressed among the three immune subtypes. Finally, functional enrichment analysis of the genes related to tumor antigens and immune subtypes suggested that they are enriched in many immune-associated processes. Conclusions: KDR, COL1A2, and SAMD9 are potential antigens for developing mRNA vaccines against diffuse glioma. The results suggest that immunotherapy targeting these three antigens is more suitable for patients with subtype Ims1. This study provides insights into immunotherapy for diffuse glioma.

The clinical features, prognostic significance, and immune heterogeneity of CD37 in diffuse gliomas.

Diffuse glioma is the most prevalent and malignant brain tumor. The function and significance of CD37 in diffuse gliomas remain largely unknown. Here, we showed CD37 was abnormally expressed in diverse cancers, especially glioma by pan-cancer differential expression analysis. In addition, we found CD37 was upregulated in higher grade and IDH or IDH1-wildtype gliomas, which was further validated by qPCR and IHC. Survival analysis revealed CD37 served as an independent indicator for unfavorable prognosis of patients with diffuse gliomas. Functional enrichment analysis revealed CD37 was associated with immunological processes. Moreover, immune infiltration analyses suggested gliomas with high-expression CD37 had greater infiltration of M2 macrophages and neutrophils, and lower NK cell abundance. CD37 was closely correlated to immune checkpoint molecules, including CD276, CD80, CD86, and PD-L2. Our results indicated CD37 is an independent prognostic factor and plays an immunosuppressive role in diffuse gliomas. Targeting CD37 could be a promising immunotherapeutic strategy for diffuse gliomas.

METTL7B is a novel prognostic biomarker of lower-grade glioma based on pan-cancer analysis.

Methyltransferase-like 7B (METTL7B) is a member of the methyltransferase-like protein family that plays an important role in the development and progression of tumors. However, its prognostic value and the correlation of METTL7B expression and tumor immunity in some cancers remain unclear. By analyzing online data, we found that METTL7B is abnormally overexpressed in multiple human tumors and plays an important role in the overall survival (OS) of patients with 8 cancer types and disease-free survival (DFS) of patients with 5 cancer types. Remarkably, METTL7B expression was positively correlated with the OS and DFS of patients with lower-grade glioma (LGG). In addition, a positive correlation between METTL7B expression and immune cell infiltration in LGG was observed. Moreover, we identified a strong correlation between METTL7B expression and immune checkpoint gene expression in kidney chromophobe (KICH), LGG and pheochromocytoma and paraganglioma (PCPG). Furthermore, METTL7B was involved in the extracellular matrix (ECM) and immune-related pathways in LGGs. Finally, in vitro experiments showed that knockdown of METTL7B inhibited the growth, migration, invasion and the epithelial-mesenchymal transition (EMT) of LGG cells. METTL7B expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in LGG.

Development of an Immune-Related LncRNA Prognostic Signature for Glioma.

INTRODUCTION: Glioma is the most common primary cancer of the central nervous system with dismal prognosis. Long noncoding RNAs (lncRNAs) have been discovered to play key roles in tumorigenesis in various cancers, including glioma. Because of the relevance between immune infiltrating and clinical outcome of glioma, identifying immune-related lncRNAs is urgent for better personalized management. MATERIALS AND METHODS: Single-sample gene set enrichment analysis (ssGSEA) was applied to estimate immune infiltration, and glioma samples were divided into high immune cell infiltration group and low immune cell infiltration group. After screening differentially expressed lncRNAs in two immune groups, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune-related prognostic signature. Additionally, we explored the correlation between immune infiltration and the prognostic signature. RESULTS: A total of 653 samples were appropriate for further analyses, and 10 lncRNAs were identified as immune-related lncRNAs in glioma. After univariate Cox regression and LASSO Cox regression analysis, six lncRNAs were identified to construct a prognostic signature for glioma, which could be taken as independent prognostic factors in both univariate and multivariate Cox regression analyses. Moreover, risk score was significantly correlated with all the 29 immune-related checkpoint expression (p < 0.05) in ssGSEA except neutrophils (p = 0.43). CONCLUSION: The study constructed an immune-related prognostic signature for glioma, which contributed to improve clinical outcome prediction and guide immunotherapy.

Identification of collagen genes related to immune infiltration and epithelial-mesenchymal transition in glioma.

BACKGROUND: Gliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression. METHODS: We downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assays were used to measure the cell migration and invasion capacity. Western blotting was used to test the expression of epithelial-mesenchymal transition (EMT) related markers. RESULTS: We identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the EMT process of glioma. Finally, taking COL3A1 as a further research object, the results showed that knockdown of COL3A1 significantly inhibited the migration, invasion, and EMT process of SHG44 and A172 cells. CONCLUSIONS: In summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management.

Scar tissue removal-activated endogenous neural stem cells aid Taxol-modified collagen scaffolds in repairing chronic long-distance transected spinal cord injury.

Scar tissue removal combined with biomaterial implantation is considered an effective measure to repair chronic transected spinal cord injury (SCI). However, whether more scar tissue removal surgeries could affect the treatment effects of biomaterial implantation still needs to be explored. In this study, we performed the first scar tissue removal surgery in the 3rd month and the second in the 6th month after completely removing 1 cm of spinal tissue in canines. We found that Taxol-modified linear ordered collagen scaffold (LOCS + Taxol) implantation could promote axonal regeneration, neurogenesis, and electrophysiological and functional recovery only in canines at the first scar tissue removal surgery, but not in canines at the second scar tissue removal surgery. Interestingly, we found that more endogenous neural stem cells (NSCs) around the injured site could be activated in canines with the first rather than the second scar tissue removal. Furthermore, we demonstrated that Taxol could promote the neuronal differentiation of NSCs in the myelin inhibition microenvironment through the p38 MAPK signaling pathway in vitro. Therefore, we speculated that endogenous NSC activation by the first scar tissue removal surgery and its further differentiation into neurons induced by Taxol may contribute to functional recovery in canines. Together, LOCS + Taxol implantation in combination with the first scar tissue removal provides a promising therapy for chronic long-distance transected SCI repair with the help of scar tissue removal activated endogenous NSCs.

Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma Patients.

Glioma is the common histological subtype of malignancy in the central nervous system, with high morbidity and mortality. Glioma cancer stem cells (CSCs) play essential roles in tumor recurrence and treatment resistance. Thus, exploring the stem cell-related genes and subtypes in glioma is important. In this study, we collected the RNA-sequencing (RNA-seq) data and clinical information of glioma patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. With the differentially expressed genes (DEGs) and weighted gene correlation network analysis (WGCNA), we identified 86 mRNA expression-based stemness index (mRNAsi)-related genes in 583 samples from TCGA RNA-seq dataset. Furthermore, these samples from TCGA database could be divided into two significantly different subtypes with different prognoses based on the mRNAsi corresponding gene, which could also be validated in the CGGA database. The clinical characteristics and immune cell infiltrate distribution of the two stemness subtypes are different. Then, functional enrichment analyses were performed to identify the different gene ontology (GO) terms and pathways in the two different subtypes. Moreover, we constructed a stemness subtype-related risk score model and nomogram to predict the prognosis of glioma patients. Finally, we selected one gene (ETV2) from the risk score model for experimental validation. The results showed that ETV2 can contribute to the invasion, migration, and epithelial-mesenchymal transition (EMT) process of glioma. In conclusion, we identified two distinct molecular subtypes and potential therapeutic targets of glioma, which could provide new insights for the development of precision diagnosis and prognostic prediction for glioma patients.

Crucial roles of different RNA-binding hnRNP proteins in Stem Cells.

The self-renewal, pluripotency and differentiation of stem cells are regulated by various genetic and epigenetic factors. As a kind of RNA binding protein (RBP), the heterogeneous nuclear ribonucleoproteins (hnRNPs) can act as "RNA scaffold" and recruit mRNA, lncRNA, microRNA and circRNA to affect mRNA splicing and processing, regulate gene transcription and post-transcriptional translation, change genome structure, and ultimately play crucial roles in the biological processes of cells. Recent researches have demonstrated that hnRNPs are irreplaceable for self-renewal and differentiation of stem cells. hnRNPs function in stem cells by multiple mechanisms, which include regulating mRNA stability, inducing alternative splicing of mRNA, epigenetically regulate gene expression, and maintaining telomerase activity and telomere length. The functions and the underlying mechanisms of hnRNPs in stem cells deserve further investigation.

Multi-Omics Analysis Based on Genomic Instability for Prognostic Prediction in Lower-Grade Glioma.

Background: Lower-grade gliomas (LGGs) are a heterogeneous set of gliomas. One of the primary sources of glioma heterogeneity is genomic instability, a novel characteristic of cancer. It has been reported that long noncoding RNAs (lncRNAs) play an essential role in regulating genomic stability. However, the potential relationship between genomic instability and lncRNA in LGGs and its prognostic value is unclear. Methods: In this study, the LGG samples from The Cancer Genome Atlas (TCGA) were divided into two clusters by integrating the lncRNA expression profile and somatic mutation data using hierarchical clustering. Then, with the differentially expressed lncRNAs between these two clusters, we identified genomic instability-related lncRNAs (GInLncRNAs) in the LGG samples and analyzed their potential function and pathway by co-expression network. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were conducted to establish a GInLncRNA prognostic signature (GInLncSig), which was assessed by internal and external verification, correlation analysis with somatic mutation, independent prognostic analysis, clinical stratification analysis, and model comparisons. We also established a nomogram to predict the prognosis more accurately. Finally, we performed multi-omics-based analyses to explore the relationship between risk scores and multi-omics data, including immune characteristics, N 6-methyladenosine (m6A), stemness index, drug sensitivity, and gene set enrichment analysis (GSEA). Results: We identified 52 GInLncRNAs and screened five from them to construct the GInLncSig model (CRNDE, AC025171.5, AL390755.1, AL049749.1, and TGFB2-AS1), which could independently and accurately predict the outcome of patients with LGG. The GInLncSig model was significantly associated with somatic mutation and outperformed other published signatures. GSEA revealed that metabolic pathways, immune pathways, and cancer pathways were enriched in the high-risk group. Multi-omics-based analyses revealed that T-cell functions, m6A statuses, and stemness characteristics were significantly disparate between two risk subgroups, and immune checkpoints such as PD-L1, PDCD1LG2, and HAVCR2 were significantly highly expressed in the high-risk group. The expression of GInLncSig prognostic genes dramatically correlated with the sensitivity of tumor cells to chemotherapy drugs. Conclusion: A novel signature composed of five GInLncRNAs can be utilized to predict prognosis and impact the immune status, m6A status, and stemness characteristics in LGG. Furthermore, these lncRNAs may be potential and alternative therapeutic targets.