NSUN5/TET2-directed chromatin-associated RNA modification of 5-methylcytosine to 5-hydroxymethylcytosine governs glioma immune evasion.

Malignant glioma exhibits immune evasion characterized by highly expressing the immune checkpoint CD47. RNA 5-methylcytosine(m5C) modification plays a pivotal role in tumor pathogenesis. However, the mechanism underlying m5C-modified RNA metabolism remains unclear, as does the contribution of m5C-modified RNA to the glioma immune microenvironment. In this study, we demonstrate that the canonical 28SrRNA methyltransferase NSUN5 down-regulates ß-catenin by promoting the degradation of its mRNA, leading to enhanced phagocytosis of tumor-associated macrophages (TAMs). Specifically, the NSUN5-induced suppression of ß-catenin relies on its methyltransferase activity mediated by cysteine 359 (C359) and is not influenced by its localization in the nucleolus. Intriguingly, NSUN5 directly interacts with and deposits m5C on CTNNB1 caRNA (chromatin-associated RNA). NSUN5-induced recruitment of TET2 to chromatin is independent of its methyltransferase activity. The m5C modification on caRNA is subsequently oxidized into 5-hydroxymethylcytosine (5hmC) by TET2, which is dependent on its binding affinity for Fe2+ and α-KG. Furthermore, NSUN5 enhances the chromatin recruitment of RBFOX2 which acts as a 5hmC-specific reader to recognize and facilitate the degradation of 5hmC caRNA. Notably, hmeRIP-seq analysis reveals numerous mRNA substrates of NSUN5 that potentially undergo this mode of metabolism. In addition, NSUN5 is epigenetically suppressed by DNA methylation and is negatively correlated with IDH1-R132H mutation in glioma patients. Importantly, pharmacological blockage of DNA methylation or IDH1-R132H mutant and CD47/SIRPα signaling synergistically enhances TAM-based phagocytosis and glioma elimination in vivo. Our findings unveil a general mechanism by which NSUN5/TET2/RBFOX2 signaling regulates RNA metabolism and highlight NSUN5 targeting as a potential strategy for glioma immune therapy.

Overcoming therapeutic resistance in oncolytic herpes virotherapy by targeting IGF2BP3-induced NETosis in malignant glioma.

Oncolytic virotherapy holds promise for cancer treatment, but the factors determining its oncolytic activity remain unclear. Neutrophil extracellular traps (NETs) are associated with cancer progression, yet their formation mechanism and role in oncolytic virotherapy remain elusive. In this study, we demonstrate that, in glioma, upregulation of IGF2BP3 enhances the expression of E3 ubiquitin protein ligase MIB1, promoting FTO degradation via the ubiquitin-proteasome pathway. This results in increased m6A-mediated CSF3 release and NET formation. Oncolytic herpes simplex virus (oHSV) stimulates IGF2BP3-induced NET formation in malignant glioma. In glioma models in female mice, a BET inhibitor enhances the oncolytic activity of oHSV by impeding IGF2BP3-induced NETosis, reinforcing virus replication through BRD4 recruitment with the CDK9/RPB-1 complex to HSV gene promoters. Our findings unveil the regulation of m6A-mediated NET formation, highlight oncolytic virus-induced NETosis as a critical checkpoint hindering oncolytic potential, and propose targeting NETosis as a strategy to overcome resistance in oncolytic virotherapy.

Machine learning-based integration develops an immune-related risk model for predicting prognosis of high-grade serous ovarian cancer and providing therapeutic strategies.

Background: High-grade serous ovarian cancer (HGSOC) is a highly lethal gynecological cancer that requires accurate prognostic models and personalized treatment strategies. The tumor microenvironment (TME) is crucial for disease progression and treatment. Machine learning-based integration is a powerful tool for identifying predictive biomarkers and developing prognostic models. Hence, an immune-related risk model developed using machine learning-based integration could improve prognostic prediction and guide personalized treatment for HGSOC. Methods: During the bioinformatic study in HGSOC, we performed (i) consensus clustering to identify immune subtypes based on signatures of immune and stromal cells, (ii) differentially expressed genes and univariate Cox regression analysis to derive TME- and prognosis-related genes, (iii) machine learning-based procedures constructed by ten independent machine learning algorithms to screen and construct a TME-related risk score (TMErisk), and (iv) evaluation of the effect of TMErisk on the deconstruction of TME, indication of genomic instability, and guidance of immunotherapy and chemotherapy. Results: We identified two different immune microenvironment phenotypes and a robust and clinically practicable prognostic scoring system. TMErisk demonstrated superior performance over most clinical features and other published signatures in predicting HGSOC prognosis across cohorts. The low TMErisk group with a notably favorable prognosis was characterized by BRCA1 mutation, activation of immunity, and a better immune response. Conversely, the high TMErisk group was significantly associated with C-X-C motif chemokine ligands deletion and carcinogenic activation pathways. Additionally, low TMErisk group patients were more responsive to eleven candidate agents. Conclusion: Our study developed a novel immune-related risk model that predicts the prognosis of ovarian cancer patients using machine learning-based integration. Additionally, the study not only depicts the diversity of cell components in the TME of HGSOC but also guides the development of potential therapeutic techniques for addressing tumor immunosuppression and enhancing the response to cancer therapy.

Deciphering comprehensive features of tumor microenvironment controlled by chromatin regulators to predict prognosis and guide therapies in uterine corpus endometrial carcinoma.

Background: Dysregulation of chromatin regulators (CRs) can perturb the tumor immune microenvironment, but the underlying mechanism remains unclear. We focused on uterine corpus endometrial carcinoma (UCEC) and used gene expression data from TCGA-UCEC to investigate this mechanism. Methods: We used weighted gene co-expression network analysis (WGCNA) and consensus clustering algorithm to classify UCEC patients into Cluster_L and Cluster_H. TME-associated CRs were identified using WGCNA and differential gene expression analysis. A CR risk score (CRRS) was constructed using univariate Cox and LASSO-Cox regression analyses. A nomogram was developed based on CRRS and clinicopathologic factors to predict patients' prognosis. Results: Lower CRRS was associated with lower grade, more benign molecular subtypes, and improved survival. Patients with low CRRS showed abundant immune infiltration, a higher mutation burden, fewer CNVs, and better response to immunotherapy. Moreover, low CRRS patients were more sensitive to 24 chemotherapeutic agents. Conclusion: A comprehensive assessment of CRRS could identify immune activation and improve the efficacy of UCEC treatments.

A comprehensive analysis focusing on cuproptosis to investigate its clinical and biological relevance in uterine corpus endometrial carcinoma and its potential in indicating prognosis.

Cuproptosis, a novel copper-dependent cell death involving mitochondrial respiration, is distinct from other known death mechanisms, which inspires us to study further in uterine corpus endometrial carcinoma (UCEC). Herein, leveraging comprehensive data from TCGA-UCEC, we conducted transcriptional and genetic analyses of 13 recently identified cuproptosis genes. We discovered severe genetic instability of cuproptosis genes, extensive positive correlations among those genes with each other at the mRNA level, and their involvement in oncogenic pathways in UCEC samples. Next, WGCNA was performed to identify a potential module regulating cuproptosis, in which the hub genes, in addition to 13 cuproptosis genes, were drawn to construct a scoring system termed Cu. Score. Furthermore, its clinical and biological relevance and tumor immune landscape, genetic alterations, as well as predicted sensitivity of chemotherapy drugs in different Cu. Score subgroups had been discussed extensively and in detail. Additionally, univariate Cox and LASSO regression were performed to identify 13 cuproptosis-related prognostic genes to establish a prognostic signature, the Risk. Score. Integrating the Risk. Score and clinical parameters, we established a nomogram with excellent performance to predict the 1-/3-/5-year survival probabilities of UCEC patients. To conclude, we conducted a comprehensive analysis encompassing cuproptosis and developed a cuproptosis scoring system and a prognostic prediction model for UCEC, which may offer help with individualized assessment and treatment for UCEC patients from the perspective of a novel death mechanism.

Deciphering the immune landscape dominated by cancer-associated fibroblasts to investigate their potential in indicating prognosis and guiding therapeutic regimens in high grade serous ovarian carcinoma.

Limited immunotherapeutic effect in high-grade serous ovarian carcinoma (HGSOC) propels exploration of the mechanics behind this resistance, which may be partly elucidated by investigating characters of cancer-associated fibroblasts (CAFs), a significant population in HGSOC involved in shaping tumor immune microenvironment. Herein, leveraging gene expression data of HGSOC samples from The Cancer Genome Atlas and Gene Expression Omnibus datasets, we suggested that CAFs detrimentally affected the outcomes of HGSOC patients. Subsequently, we performed weighted gene co-expression network analysis (WGCNA) to identify a CAFs-related module and screened out seven hub genes from this module, all of which were positively correlated with the infiltration of immunosuppressive macrophages. As one of the hub genes, the expression of fibrillin 1 (FBN1) and its relevance to CD206 were further verified by immunohistochemistry staining in HGSOC samples. Meanwhile, we extracted genes that correlated well with CAF signatures to construct a CAFscore. The capacity of the CAFscore as an independent prognostic factor was validated by Cox regression analyses, and its relevance to components as well as signals in the tumor immune microenvironment was also investigated. Under the evaluation by the CAFscore, HGSOC patients with relatively high CAFscore had worse outcomes, activated mesenchymal signaling pathways, and immune checkpoint blockade (ICB) resistance signatures, which was consistent with the fact that non-responders in anti-PD-1 treatment cohorts tended to have higher CAFscore. Besides, the possibility of CAFscore to guide the selection of sensitive chemotherapeutic agents was explored. In conclusion, individualized assessment of the CAFscore could uncover the extent of stroma activation and immunosuppression and inform therapeutic strategies to improve the benefit of therapies.

A 13-Gene Signature Based on Estrogen Response Pathway for Predicting Survival and Immune Responses of Patients With UCEC.

Background: Accumulating evidence suggests that anti-estrogens have been effective against multiple gynecological diseases, especially advanced uterine corpus endometrial carcinoma (UCEC), highlighting the contribution of the estrogen response pathway in UCEC progression. This study aims to identify a reliable prognostic signature for potentially aiding in the comprehensive management of UCEC. Methods: Firstly, univariate Cox and LASSO regression were performed to identify a satisfying UCEC prognostic model quantifying patients' risk, constructed from estrogen-response-related genes and verified to be effective by Kaplan-Meier curves, ROC curves, univariate and multivariate Cox regression. Additionally, a nomogram was constructed integrating the prognostic model and other clinicopathological parameters. Next, UCEC patients from the TCGA dataset were divided into low- and high-risk groups according to the median risk score. To elucidate differences in biological characteristics between the two risk groups, pathway enrichment, immune landscape, genomic alterations, and therapeutic responses were evaluated to satisfy this objective. As for treatment, effective responses to anti-PD-1 therapy in the low-risk patients and sensitivity to six chemotherapy drugs in the high-risk patients were demonstrated. Results: The low-risk group with a relatively favorable prognosis was marked by increased immune cell infiltration, higher expression levels of HLA members and immune checkpoint biomarkers, higher tumor mutation burden, and lower copy number alterations. This UCEC prognostic signature, composed of 13 estrogen-response-related genes, has been identified and verified as effective. Conclusion: Our study provides molecular signatures for further functional and therapeutic investigations of estrogen-response-related genes in UCEC and represents a potential systemic approach to characterize key factors in UCEC pathogenesis and therapeutic responses.

Downregulation of MEIS1 mediated by ELFN1-AS1/EZH2/DNMT3a axis promotes tumorigenesis and oxaliplatin resistance in colorectal cancer.

Oxaliplatin is widely used in the frontline treatment of colorectal cancer (CRC), but an estimated 50% of patients will eventually stop responding to treatment due to acquired resistance. This study revealed that diminished MEIS1 expression was detected in CRC and harmed the survival of CRC patients. MEIS1 impaired CRC cell viabilities and tumor growth in mice and enhanced CRC cell sensitivity to oxaliplatin by preventing DNA damage repair. Mechanistically, oxaliplatin resistance following MEIS1 suppression was critically dependent on enhanced FEN1 expression. Subsequently, we confirmed that EZH2-DNMT3a was assisted by lncRNA ELFN1-AS1 in locating the promoter of MEIS1 to suppress MEIS1 transcription epigenetically. Based on the above, therapeutics targeting the role of MEIS1 in oxaliplatin resistance were developed and our results suggested that the combination of oxaliplatin with either ELFN1-AS1 ASO or EZH2 inhibitor GSK126 could largely suppress tumor growth and reverse oxaliplatin resistance. This study highlights the potential of therapeutics targeting ELFN1-AS1 and EZH2 in cell survival and oxaliplatin resistance, based on their controlling of MEIS1 expression, which deserve further verification as a prospective therapeutic strategy.

miR-221/222 suppression induced by activation of the cAMP/PKA/CREB1 pathway is required for cAMP-induced bidirectional differentiation of glioma cells.

Factors that increase cAMP levels can induce lineage-specific differentiation of glioma cells into astrocyte-like cells. However, the differentiation pattern and underlying mechanisms remain unclear. Here, we find that cAMP/protein kinase A (PKA)/cAMP responsive element binding protein 1 (CREB1)-induced miR-221/222 suppression contributes to the neuron-like differentiation of gliomas. cAMP agonists selectively induced neuron- and astrocyte-like but not oligodendrocyte-like differentiation of C6 glioma cells. PKA inhibitors and CREB1 knockout blocked neuron-like differentiation of glioma cells. cAMP inhibited miR-221/222 in a PKA/CREB1-dependent manner. Importantly, both in vitro and in vivo assays demonstrated that transcriptional suppression of miR-221/222 is required for neuronal differentiation of glioma cells. Our findings suggest that increasing cAMP levels can induce bidirectional differentiation of glioma cells. Furthermore, the miR-221/222 cluster acts as an epigenetic brake during glioma differentiation.

Identification of ZNF26 as a Prognostic Biomarker in Colorectal Cancer by an Integrated Bioinformatic Analysis.

The dysregulation of transcriptional factors (TFs) leads to malignant growth and the development of colorectal cancer (CRC). Herein, we sought to identify the transcription factors relevant to the prognosis of colorectal cancer patients. We found 526 differentially expressed TFs using the TCGA database of colorectal cancer patients (n = 544) for the differential analysis of TFs (n = 1,665) with 210 upregulated genes as well as 316 downregulated genes. Subsequently, GO analysis and KEGG pathway analysis were performed for these differential genes for investigating their pathways and function. At the same time, we established a genetic risk scoring model for predicting the overall survival (OS) by using the mRNA expression levels of these differentially regulated TFs, and defined the CRC into low and high-risk categories which showed significant survival differences. The genetic risk scoring model included four high-risk genes (HSF4, HEYL, SIX2, and ZNF26) and two low-risk genes (ETS2 and SALL1), and validated the OS in two GEO databases (p = 0.0023 for the GSE17536, p = 0.0193 for the GSE29623). To analyze the genetic and epigenetic changes of these six risk-related TFs, a unified bioinformatics analysis was conducted. Among them, ZNF26 is progressive in CRC and its high expression is linked with a poor diagnosis as well. Knockdown of ZNF26 inhibits the proliferative capacity of CRC cells. Moreover, the positive association between ZNF26 and cyclins (CDK2, CCNE2, CDK6, CHEK1) was also identified. Therefore, as a novel biomarker, ZNF26 may be a promising candidate in the diagnosis and prognostic evaluation of colorectal cancer.

Identification and Validation of an Immune-Associated RNA-Binding Proteins Signature to Predict Clinical Outcomes and Therapeutic Responses in Glioma Patients.

The prognosis of patients with glioma is largely related to both the tumor-infiltrating immune cells and the expression of RNA-binding proteins (RBPs) that are able to regulate various pro-inflammatory and oncogenic mediators. However, immune-associated RBPs in glioma remain unexplored. In this study, we captured patient data from The Cancer Genome Atlas (TCGA) and divided them into two immune subtype groups according to the difference in infiltration of immune cells. After differential expression and co-expression analysis, we identified 216 RBPs defined as immune-associated RBPs. After narrowing down processes, eight RBPs were selected out to construct a risk signature that proven to be a novel and independent prognostic factor. The patients were divided into high- and low-risk groups on the basis of risk score. Higher risk scores meant worse overall survival and higher expression of human leukocyte antigen and immune checkpoints such as PD1 and CTLA4. In addition, analyses of pathway enrichment, somatic mutation, copy number variations and immuno-/chemotherapeutic response prediction were performed in high- and low-risk groups and compared with each other. For the first time, we demonstrated a novel signature composed of eight immune-associated RBPs that was valuable in predicting the survival of glioma patients and directing immunotherapy and chemotherapy.

Circadian Regulation Patterns With Distinct Immune Landscapes in Gliomas Aid in the Development of a Risk Model to Predict Prognosis and Therapeutic Response.

Circadian disruption in tumorigenesis has been extensively studied, but how circadian rhythm (CR) affects the formation of tumor microenvironment (TME) and the crosstalk between TME and cancer cells is largely unknown, especially in gliomas. Herein, we retrospectively analyzed transcriptome data and clinical parameters of glioma patients from public databases to explore circadian rhythm-controlled tumor heterogeneity and characteristics of TME in gliomas. Firstly, we pioneered the construction of a CR gene set collated from five datasets and review literatures. Unsupervised clustering was used to identify two CR clusters with different CR patterns on the basis of the expression of CR genes. Remarkably, the CR cluster-B was characterized by enriched myeloid cells and activated immune-related pathways. Next, we applied principal component analysis to construct a CRscore to quantify CR patterns of individual tumors, and the function of the CRscore in prognostic prediction was further verified by univariate and multivariate regression analyses in combination with a nomogram. The CRscore could not only be an independent factor to predict prognosis of glioma patients but also guide patients to choose suitable treatment strategies: immunotherapy or chemotherapy. A glioma patient with a high CRscore might respond to immune checkpoint blockade, whereas one with a low CRscore could benefit from chemotherapy. In this study, we revealed that circadian rhythms modulated tumor heterogeneity, TME diversity, and complexity in gliomas. Evaluating the CRscore of an individual tumor would contribute to gaining a greater understanding of the tumor immune status of each patient, enhancing the accuracy of prognostic prediction, and suggesting more effective treatment options.

EN2 as an oncogene promotes tumor progression via regulating CCL20 in colorectal cancer.

Engrailed-2 (EN2), a member of the engrailed homeobox family, has been shown to be abnormally expressed in a variety of cancers. However, the expression and the clinical significance of EN2 in colorectal cancer (CRC) are largely unknown. Firstly, we found that EN2 acted as an oncogene in CRC. EN2 was upregulated in colorectal cancer tissues compared with adjacent normal tissues. Higher EN2 expression was significantly associated with poorer survival rate. Knockdown of EN2 markedly inhibited proliferation and migration capacities of SW480 cells in vitro, and suppressed tumorigenicity in vivo. Mechanistically, Chemokine ligand 20 (CCL20), a member of the C-C motif chemokine subfamily, was identified as a direct target gene of EN2 in CRC. CCL20 expression was positively correlated with EN2 expression in CRC tissues. Moreover, EN2 promoted the proliferation and migration of CRC cells by regulating the expression of CCL20 in vitro. These results suggest that EN2 plays a critical role in the CRC tumor progression and may serve as a potential target for CRC prevention and therapy.

Methylation-mediated repression of MiR-424/503 cluster promotes proliferation and migration of ovarian cancer cells through targeting the hub gene KIF23.

Ovarian cancer is one type of gynecological malignancies with extremely high lethal rate. Abnormal proliferation and metastasis are regarded to play important roles in patients' death, whereas we know little about the underlying molecular mechanisms. Under this circumstance, our current study aims to investigate the role of hub genes in ovarian cancer. Bioinformatics analysis of the data from GEO and analyses of ovarian cancer samples were performed. Then, the results showed that KIF23, a hub gene, was mainly related to cell cycle and positively associated with poor prognosis. Meanwhile, both miR-424-5p and miR-503-5p directly targeted to 3'UTR of KIF23 to suppress the expression of KIF23 and inhibit ovarian cancer cell proliferation and migration. Furthermore, we discovered that miR-424/503 was epigenetically repressed by hypermethylation in the promoter regions, which directly modulated the expression of KIF23 to improve the oncogenic performance of cancer cells in vitro. Together, our research certifies that miR-424/503 cluster is silenced by DNA hypermethylation, which promotes the expression of KIF23, thereby regulating the proliferation and migration of ovarian cancer cells. Interposing this process might be a novel approach in cancer therapy.