The Diverse Roles of RNA-Binding Proteins in Glioma Development

Tumour microenvironment programming by an RNA-RNA-binding protein complex creates a druggable vulnerability in IDH-wild-type glioblastoma

Patients with IDH-wild-type glioblastomas have a poor five-year survival rate along with limited treatment efficacy due to immune cell (glioma-associated microglia and macrophages) infiltration promoting tumour growth and resistance. To enhance therapeutic options, our study investigated the unique RNA-RNA-binding protein complex LOC-DHX15. This complex plays a crucial role in driving immune cell infiltration and tumour growth by establishing a feedback loop between cancer and immune cells, intensifying cancer aggressiveness. Targeting this complex with blood-brain barrier-permeable small molecules improved treatment efficacy, disrupting cell communication and impeding cancer cell survival and stem-like properties. Focusing on RNA-RNA-binding protein interactions emerges as a promising approach not only for glioblastomas without the IDH mutation but also for potential applications beyond cancer, offering new avenues for developing therapies that address intricate cellular relationships in the body.

SERBP1 interacts with PARP1 and is present in PARylation-dependent protein complexes regulating splicing, cell division, and ribosome biogenesis

RNA binding proteins (RBPs) containing intrinsically disordered regions (IDRs) are present in diverse molecular complexes where they function as dynamic regulators. Their characteristics promote liquid-liquid phase separation (LLPS) and the formation of membraneless organelles such as stress granules and nucleoli. IDR-RBPs are particularly relevant in the nervous system and their dysfunction is associated with neurodegenerative diseases and brain tumor development. SERBP1 is a unique member of this group, being mostly disordered and lacking canonical RNA-binding domains. Using a proteomics approach followed by functional analysis, we defined SERBP1's interactome. We uncovered novel SERBP1 roles in splicing, cell division, and ribosomal biogenesis and showed its participation in pathological stress granules and Tau aggregates in Alzheimer's disease brains. SERBP1 preferentially interacts with other G-quadruplex (G4) binders, implicated in different stages of gene expression, suggesting that G4 binding is a critical component of SERBP1 function in different settings. Similarly, we identified important associations between SERBP1 and PARP1/polyADP-ribosylation (PARylation). SERBP1 interacts with PARP1 and its associated factors and influences PARylation. Moreover, protein complexes in which SERBP1 participates contain mostly PARylated proteins and PAR binders. Based on these results, we propose a feedback regulatory model in which SERBP1 influences PARP1 function and PARylation, while PARylation modulates SERBP1 functions and participation in regulatory complexes.

MYEF2: an immune infiltration-related prognostic factor in IDH-wild-type glioblastoma

Glioblastoma (GBM) is the most malignant and prevalent primary brain tumor. In this study, weighted gene coexpression network analysis (WGCNA) was performed to analyze RNA binding protein (RBP) expression data from The Cancer Genome Atlas (TCGA) for the IDH-wild type GBM cohort. The CIBERSORT algorithm quantified the cellular composition of immune cells and was used to identify key modules associated with CD8+ T cell infiltration. Coexpression networks analysis and protein-protein interaction (PPI) network analysis was used to filter out central RBP genes. Eleven RBP genes, including MYEF2, MAPT, NOVA1, MAP2, TUBB2B, CDH10, TTYH1, PTPRZ1, SOX2, NOVA2 and SCG3, were identified as candidate CD8+ T cell infiltration-associated central genes. A Cox proportional hazards regression model and Kaplan-Meier analysis were applied to identify candidate biomarkers. MYEF2 was selected as a prognostic biomarker based on the results of prognostic analysis. Flow Cytometric Analysis indicated that MYEF2 expression was negatively correlated with dysfunctional CD8+ T cell markers. Kaplan-Meier survival analysis (based on IHC staining) revealed that GBM patients with elevated MYEF2 expression have a better prognosis. Knockdown of MYEF2 in GBM cells via in vitro assays was observed to promote cell proliferation and migration. Our study suggests that MYEF2 expression negatively correlates with T cell exhaustion and tumor progression, rendering it a potentially valuable prognostic biomarker for GBM.

FLOT1, stabilized by WTAP/IGF2BP2 mediated N6-methyladenosine modification, predicts poor prognosis and promotes growth and invasion in gliomas

The expression, function, and mechanism of FLOT1 (flotillin-1) remains unknown in gliomas. Here, the expression and clinical value of FLOT1 in gliomas was bioinformatically and experimentally analyzed via online omics data and local tissues. Moreover, the effects of FLOT1 depletion on cell proliferation and invasion were also detected. Besides, the underlying roles of N6-methyladenosine modification (m6A) in FLOT1 upregulation was further explored. The results demonstrated that FLOT1 was significantly upregulated in gliomas and positively correlated with advanced progression and poor prognosis of patients. FLOT1 silencing notably suppressed the cell proliferation and invasion in gliomas. The expression of WTAP and IGF2BP2was positively correlated with FLOT1 expression and served as the writer and reader of FLOT1 m6A, respectively, which stabilized FLOT1 mRNA and maintained its upregulation in gliomas. Lastly, ectopic expression of FLOT1 could notably restore the inhibitory effects caused by WTAP and IGF2BP2 depletion in glioma cells. Collectively, our results originally confirmed the upregulation and oncogenic roles of FLOT1, and revealed that WTAP/IGF2BP2 mediated m6A contributed to the upregulation of FLOT1 in gliomas, highlighting the promising application of WTAP/IGF2BP2/FLOT1 axis in target treatment of gliomas.

FXR1 promotes glioma progression by downregulating microRNA-124-3p through long noncoding RNA FGD5-AS1 upregulation

OBJECTIVE

As reported, glioma progression is affected by altered FXR1, long non-coding RNA FGD5-AS1, and microRNA (miR)-124-3p. However, relationships among these genes remain unclear. Accordingly, this paper ascertains whether FXR1 manipulates glioma progression via the FGD5-AS1/miR-124-3p axis.

METHODS

Glioma tissues were harvested, in which FGD5-AS1 and miR-124-3p levels were examined with qRT-PCR and FXR1 level was assessed with qRT-PCR and western blot. The interaction of miR-124-3p with FGD5-AS1 was analyzed by dual-luciferase reporter, RIP, and Pearson correlation coefficient assays, and that of FXR1 with FGD5-AS1 was assessed by RIP and Pearson correlation coefficient assays. Glioma cells were obtained, followed by qRT-PCR detection of miR-124-3p expression. After gain- or loss-of-function assays, EdU, Transwell, and tubule formation assays were performed to determine cell proliferation, invasion and migration, and angiogenesis. Next, the intracranial in situ graft tumor model was established for in vivo verification.

RESULTS

FGD5-AS1 and FXR1 levels were high, but miR-124-3p level was low in glioma tissues. Likewise, glioma cells had downregulated miR-124-3p expression. Mechanistically, FGD5-AS1 negatively bound to miR-124-3p, and FXR1 was positively correlated and interacted with FGD5-AS1. miR-124-3p overexpression or FGD5-AS1 or FXR1 knockdown restricted cell invasion, proliferation, migration, and angiogenesis in gliomas. miR-124-3p inhibition abrogated the repressive impacts of FXR1 knockdown on the malignant progression of gliomas. Also, FXR1 constrained tumor growth and angiogenesis in mice, which was counterweighed by inhibiting miR-124-3p.

CONCLUSION

FXR1 might act as an oncogene in gliomas by declining miR-124-3p through FGD5-AS1.

The dark side of mRNA translation and the translation machinery in glioblastoma

Among the different types of cancer affecting the central nervous system (CNS), glioblastoma (GB) is classified by the World Health Organization (WHO) as the most common and aggressive CNS cancer in adults. GB incidence is more frequent among persons aged 45–55 years old. GB treatments are based on tumor resection, radiation, and chemotherapies. The current development of novel molecular biomarkers (MB) has led to a more accurate prediction of GB progression. Moreover, clinical, epidemiological, and experimental studies have established genetic variants consistently associated with the risk of suffering GB. However, despite the advances in these fields, the survival expectancy of GB patients is still shorter than 2 years. Thus, fundamental processes inducing tumor onset and progression remain to be elucidated. In recent years, mRNA translation has been in the spotlight, as its dysregulation is emerging as a key cause of GB. In particular, the initiation phase of translation is most involved in this process. Among the crucial events, the machinery performing this phase undergoes a reconfiguration under the hypoxic conditions in the tumor microenvironment. In addition, ribosomal proteins (RPs) have been reported to play translation-independent roles in GB development. This review focuses on the research elucidating the tight relationship between translation initiation, the translation machinery, and GB. We also summarize the state-of-the-art drugs targeting the translation machinery to improve patients’ survival. Overall, the recent advances in this field are shedding new light on the dark side of translation in GB.

Multi-omics analysis of N6-methyladenosine reader IGF2BP3 as a promising biomarker in pan-cancer

Background

Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) has been reported to exhibit an oncogenic effect as an RNA-binding protein (RBP) by promoting tumor cell proliferation, migration and invasion in several tumor types. However, a pan-cancer analysis of IGF2BP3 is not currently available, and the exact roles of IGF2BP3 in prognosis and immunology in cancer patients remain enigmatic. The main aim of this study was to provide visualization of the systemic prognostic landscape of IGF2BP3 in pan-cancer and to uncover the potential relationship between IGF2BP3 expression in the tumor microenvironment and immune infiltration profile.

Methods

Raw data on IGF2BP3 expression were obtained from GTEx, CCLE, TCGA, and HPA data portals. We have investigated the expression patterns, diagnostic and prognostic significance, mutation landscapes, functional analysis, and functional states of IGF2BP3 utilizing multiple databases, including HPA, TISIDB, cBioPortal, GeneMANIA, GESA, and CancerSEA. Moreover, the relationship of IGF2BP3 expression with immune infiltrates, TMB, MSI and immune-related genes was evaluated in pan-cancer. IGF2BP3 with drug sensitivity analysis was performed from the CellMiner database. Furthermore, the expression of IGF2BP3 in different grades of glioma was detected by immunohistochemical staining and western blot.

Results

We found that IGF2BP3 was ubiquitously highly expressed in pan-cancer and significantly correlated with diagnosis, prognosis, TMB, MSI, and drug sensitivity in various types of cancer. Besides, IGF2BP3 was involved in many cancer pathways and varied in different immune and molecular subtypes of cancers. Additionally, IGF2BP3 is critically associated with genetic markers of immunomodulators in various cancers. Finally, we validated that IGF2BP3 protein expression was significantly higher in glioma than in normal tissue, especially in GBM.

Conclusions

IGF2BP3 may be a potential molecular biomarker for diagnosis and prognosis in pan-cancer, especially for glioma. It could become a novel therapeutic target for various cancers.

Mass spectroscopy-based proteomics and metabolomics analysis of triple-positive breast cancer cells treated with tamoxifen and/or trastuzumab

PURPOSE

HER2-enriched breast cancer with high levels of hormone receptor expression, known as "triple positive" breast cancer, may represent a new entity with a relatively favourable prognosis against which the combination of chemotherapy, HER-2 inhibition, and endocrine treatment may be considered overtreatment. We explored the effect of the anticancer drugs tamoxifen and trastuzumab, both separately and in combination, on the integrated proteomic and metabolic profile of "triple positive" breast cancer cells (BT-474).

METHOD

We employed ultra-high-performance liquid chromatography-quadrupole time of flight mass spectrometry using a Bruker timsTOF to investigate changes in BT-474 cell line treated with either tamoxifen, trastuzumab or a combination. Differentially abundant metabolites were identified using the Bruker Human Metabolome Database metabolite library and proteins using the Uniprot proteome for Homo sapiens using MetaboScape and MaxQuant, respectively, for identification and quantitation.

RESULTS

A total of 77 proteins and 85 metabolites were found to significantly differ in abundance in BT-474 treated cells with tamoxifen 5 μM/and or trastuzumab 2.5 μM. Findings suggest that by targeting important cellular signalling pathways which regulate cell growth, apoptosis, proliferation, and chemoresistance, these medicines have a considerable anti-growth effect in BT-474 cells. Pathways enriched for dysregulation include RNA splicing, neutrophil degranulation and activation, cellular redox homeostasis, mitochondrial transmembrane transport, ferroptosis and necroptosis, ABC transporters and central carbon metabolism.

CONCLUSION

Our findings in protein and metabolite level research revealed that anti-cancer drug therapy had a significant impact on the key signalling pathways and molecular processes in triple positive BT-474 cell lines.

Lin-28 Homolog B-Activated Protein Disulfide Isomerase A4 Regulates Cell Proliferation, Migration and Invasion of Glioma

The goal of this study is to elucidate the role of protein disulfide isomerase A4 (PDIA4) in glioma, as well as its regulatory mechanism. Cell transfection was performed to adjust the expression level of PDIA4 and RNA-binding protein lin-28 homolog B (LIN28B). The expression of PDIA4 in human astrocytes and glioma cell lines was determined by quantitative real-time PCR and western blot. CCK-8, colony formation, Transwell and wound-healing assays were applied to determine the capabilities of cells to proliferate, invade and migrate. The connection between PDIA4 and LIN28B was demonstrated by RNA immunoprecipitation (RIP) and RNA pull down assays. As a result, PDIA4 was elevated in glioma. PDIA4 depletion hugely suppressed cell proliferative ability, which was characterized by the reduced cell viability and colony formation, and declined contents of PCNA and Ki67. Meanwhile, PDIA4 knockdown repressed the cell capabilities to migrate and invade, accompanied with downregulated MMP2 and MMP9. LIN28N was also found to be upregulated in glioma cells, and was verified to bind with PDIA4 and positively regulate PDIA4 expression. Additionally, LIN28B overexpression partly hindered the suppressive impacts of PDIA4 knockdown on cell abilities to proliferate, migrate and invade. In conclusion, this study delineates that LIN28B-mediated PDIA4 plays a critical role in the progression of glioma.

Identification of a 6-RBP gene signature for a comprehensive analysis of glioma and ischemic stroke: Cognitive impairment and aging-related hypoxic stress

There is mounting evidence that ischemic cerebral infarction contributes to vascular cognitive impairment and dementia in elderly. Ischemic stroke and glioma are two majorly fatal diseases worldwide, which promote each other's development based on some common underlying mechanisms. As a post-transcriptional regulatory protein, RNA-binding protein is important in the development of a tumor and ischemic stroke (IS). The purpose of this study was to search for a group of RNA-binding protein (RBP) gene markers related to the prognosis of glioma and the occurrence of IS, and elucidate their underlying mechanisms in glioma and IS. First, a 6-RBP (POLR2F, DYNC1H1, SMAD9, TRIM21, BRCA1, and ERI1) gene signature (RBPS) showing an independent overall survival prognostic prediction was identified using the transcriptome data from TCGA-glioma cohort (n = 677); following which, it was independently verified in the CGGA-glioma cohort (n = 970). A nomogram, including RBPS, 1p19q codeletion, radiotherapy, chemotherapy, grade, and age, was established to predict the overall survival of patients with glioma, convenient for further clinical transformation. In addition, an automatic machine learning classification model based on radiomics features from MRI was developed to stratify according to the RBPS risk. The RBPS was associated with immunosuppression, energy metabolism, and tumor growth of gliomas. Subsequently, the six RBP genes from blood samples showed good classification performance for IS diagnosis (AUC = 0.95, 95% CI: 0.902–0.997). The RBPS was associated with hypoxic responses, angiogenesis, and increased coagulation in IS. Upregulation of SMAD9 was associated with dementia, while downregulation of POLR2F was associated with aging-related hypoxic stress. Irf5/Trim21 in microglia and Taf7/Trim21 in pericytes from the mouse cerebral cortex were identified as RBPS-related molecules in each cell type under hypoxic conditions. The RBPS is expected to serve as a novel biomarker for studying the common mechanisms underlying glioma and IS.

FMRP modulates the Wnt signalling pathway in glioblastoma

Converging evidence indicates that the Fragile X Messenger Ribonucleoprotein (FMRP), which absent or mutated in Fragile X Syndrome (FXS), plays a role in many types of cancers. However, while FMRP roles in brain development and function have been extensively studied, its involvement in the biology of brain tumors remains largely unexplored. Here we show, in human glioblastoma (GBM) biopsies, that increased expression of FMRP directly correlates with a worse patient outcome. In contrast, reductions in FMRP correlate with a diminished tumor growth and proliferation of human GBM stem-like cells (GSCs) in vitro in a cell culture model and in vivo in mouse brain GSC xenografts. Consistently, increased FMRP levels promote GSC proliferation. To characterize the mechanism(s) by which FMRP regulates GSC proliferation, we performed GSC transcriptome analyses in GSCs expressing high levels of FMRP, and in these GSCs after knockdown of FMRP. We show that the WNT signalling is the most significantly enriched among the published FMRP target genes and genes involved in ASD. Consistently, we find that reductions in FMRP downregulate both the canonical WNT/β-Catenin and the non-canonical WNT-ERK1/2 signalling pathways, reducing the stability of several key transcription factors (i.e. β-Catenin, CREB and ETS1) previously implicated in the modulation of malignant features of glioma cells. Our findings support a key role for FMRP in GBM cancer progression, acting via regulation of WNT signalling.

The RNA-Binding Protein Musashi1 Regulates a Network of Cell Cycle Genes in Group 4 Medulloblastoma

Medulloblastoma is the most common malignant brain tumor in children. Treatment with surgery, irradiation, and chemotherapy has improved survival in recent years, but patients are frequently left with devastating neurocognitive and other sequelae. Patients in molecular subgroups 3 and 4 still experience a high mortality rate. To identify new pathways contributing to medulloblastoma development and create new routes for therapy, we have been studying oncogenic RNA-binding proteins. We defined Musashi1 (Msi1) as one of the main drivers of medulloblastoma development. The high expression of Msi1 is prevalent in Group 4 and correlates with poor prognosis while its knockdown disrupted cancer-relevant phenotypes. Genomic analyses (RNA-seq and RIP-seq) indicated that cell cycle and division are the main biological categories regulated by Msi1 in Group 4 medulloblastoma. The most prominent Msi1 targets include CDK2, CDK6, CCND1, CDKN2A, and CCNA1. The inhibition of Msi1 with luteolin affected the growth of CHLA-01 and CHLA-01R Group 4 medulloblastoma cells and a synergistic effect was observed when luteolin and the mitosis inhibitor, vincristine, were combined. These findings indicate that a combined therapeutic strategy (Msi1 + cell cycle/division inhibitors) could work as an alternative to treat Group 4 medulloblastoma.

A novel risk signature with 6 RNA binding proteins for prognosis prediction in patients with glioblastoma

Recent studies suggested that RNA binding proteins (RBPs) were related to the tumorigenesis and progression of glioma. This study was conducted to identify prognostic RBPs of glioblastoma (GBM) and construct an RBP signature to predict the prognosis of GBM.Univariate Cox regression analysis was carried out to identify the RBPs associated with overall survival of GBM in the The Cancer Genome Atlas (TCGA), GSE16011, and Repository for Molecular Brain Neoplasia data (Rembrandt) datasets, respectively. Overlapping RBPs from the TCGA, GSE16011, and Rembrandt datasets were selected. The biological role of prognostic RBPs was assessed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses. Least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis were used to construct an RBP-related risk signature. The prognostic value of RBP signature was measured by Kaplan-Meier method and time-dependent receiver operating characteristic curve. A nomogram based on independent prognostic factors was established to predict survival for GBM. The CGGA cohort was used as the validation cohort for external validation.This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature. Kaplan-Meier curves suggested that high-risk score was associated with a poor prognosis. Area under the curve of 1-, 3-, and 5-year overall survival was 0.618, 0.728, and 0.833 for TCGA cohort, 0.655, 0.909, and 0.911 for GSE16011 cohort, and 0.665, 0.792, and 0.781 for Rembrandt cohort, respectively. A nomogram with 4 parameters (age, chemotherapy, O6-methylguanine-DNA methyltransferase promoter status, and risk score) was constructed. The calibration curve showed that the nomogram prediction was in good agreement with the actual observation.The 6-RBPs signature could effectively predict the prognosis of GBM, and our findings supplemented the prognostic index of GBM to a certain extent.

A novel 13 RNA binding proteins (RBPs) signature could predict prostate cancer biochemical recurrence

BACKGROUND

Cancer precision medicine requires biomarkers or signatures to predict prognosis and therapeutic benefits. Driven by this, we established a biochemical recurrence (BCR) predictive model for prostate cancer (PCA) patients based on RNA-binding proteins (RBPs).

METHODS

RNA-sequencing and corresponding clinicopathological data were downloaded from the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Univariate COX, LASSO and multivariate COX regression analyses were carried out to develop the BCR predictive riskScore model. Survival analysis, ROC curve, independent prognostic analysis, nomogram were also performed to evaluate this signature internally and externally.

RESULTS

A total of 13 RBPs including TRMT1L, WBP4, MBNL3, SMAD9, NSUN7, ENG9, PIWIL4, PEG10, CSDC2, HELZ2, CELF2, YBX2 and ESRP2 were eventually identified as BCR-related hub biomarkers and utilized to establish a riskScore. Further analysis including external and internal verification indicated that the patients with high riskScores had shorter time to BCR compared to those with low riskScores in both TCGA and GSE116918. The area under the curve (AUC) of the time-dependent receiver operator characteristic curve (ROC) of the predictive model exhibited a good predictive performance. The signature was also proven to be a valuable independent prognostic factor (all P < 0.05). We also established a nomogram based on the 13 RBPs to visualize the relationships between individual predictors and 1-, 3- and 5-year BCR for PCA.

CONCLUSIONS

Our results successfully screened out 13 RBPs as a robust BCR-predictive signature in PCA by external and internal verification, helping clinician predict patients' cancer progression status and promoting the specific individualized treatment than original clinical parameters.

Systematic analysis of the function and prognostic value of RNA binding protein in head and neck squamous cell carcinoma

OBJECTIVE

Dysregulation of RNA binding proteins (RBPs) plays an important role in controlling processes in cancer development. However, the function of RBPs has not been thoroughly and systematically documented in head and neck cancer. We aim to explore the role of RPB in the pathogenesis of HNSC.

METHODS

We obtained HNSC gene expression data and corresponding clinical information from The Cancer Genome Atlas (TCGA) and the GEO databases, and identified aberrantly expressed RBPs between tumors and normal tissues. Meanwhile, we performed a series of bioinformatics to explore the function and prognostic value of these RBPs.

RESULTS

A total of 249 abnormally expressed RBPs were identified, including 101 downregulated RBPs and 148 upregulated RBPs. Using least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analysis, the 15 RPBs were identified as hub genes. With the 15 RPBS, the prognostic prediction model was constructed. Further analysis showed that the high-risk score of the patients expressed a better survival outcome. The prediction model was validated in another HNSC dataset, and similar findings were observed.

CONCLUSIONS

Our results provide novel insights into the pathogenesis of HNSC. The fifteen RBP gene signature exhibited the predictive value of moderate HNSC prognosis, and have potential application value in clinical decision-making and individualized treatment.

Development and Validation of a RNA Binding Protein-Associated Prognostic Model for Hepatocellular Carcinoma

BACKGROUND

Dysregulation of RNA binding proteins (RBPs) has been identified in multiple malignant tumors correlated with tumor progression and occurrence. However, the function of RBPs is not well understood in hepatocellular carcinoma (HCC).

METHODS

The RNA sequence data of HCC was extracted out of the Cancer Genome Atlas (TCGA) database and different RBPs were calculated between regular and cancerous tissue. The study explored the expression and predictive value of the RBPs systemically with a series of bioinformatic analyzes.

RESULTS

A total of 330 RBPs, including 208 up-regulated and 122 down-regulated RBPs, were classified differently. Four RBPs (MRPL54, EZH2, PPARGC1A, EIF2AK4) were defined as the forecast related hub gene and used to construct a model for prediction. Further study showed that the high-risk subgroup is poor survived (OS) compared to the model-based low-risk subgroup. The area of the prognostic model under the time-dependent receiver operator characteristic (ROC) curve is 0.814 in TCGA training group and 0.729 in validation group, indicating a strong prognostic model. We also created a predictive nomogram and a web-based calculator (https://dxyjiang.shinyapps.io/RBPpredict/) based on the 4 RBPs and internal validation in the TCGA cohort, which displayed a beneficial predictive ability for HCC.

CONCLUSIONS

Our results provide new insights into HCC pathogenesis. The 4-RBP gene signature showed a reliable HCC prediction ability with possible applications in therapeutic decision making and personalized therapy.

Integrated Analysis of RNA-Binding Proteins Associated With the Prognosis and Immunosuppression in Squamous Cell Carcinoma of Head and Neck

RNA-binding proteins (RBPs) interacting with target RNAs play essential roles in RNA metabolism at the post-transcription level. Perturbations of RBPs can accelerate cancer development and cause dysregulation of the immune cell function and activity leading to evade immune destruction of cancer cells. However, few studies have systematically analyzed the potential prognostic value and functions of RBPs in squamous cell carcinoma of head and neck (SCCHN). Here, for the first time, we comprehensively identified 92 differentially expressed RBPs from The Cancer Genome Atlas (TCGA) database. In the training set, a prognosis risk model was constructed with six RBPs, including NCBP2, MKRN3, MRPL47, AZGP1, IGF2BP2, and EZH2, and validated by the TCGA test set, the TCGA all set, and the GEO data set. In addition, the risk score was related to the clinical stage, T classification, and N classification. Furthermore, the high-risk score was significantly correlated with immunosuppression, and low expression of EZH2 and AZGP1 and high expression of IGF2BP2 were the main factors. Thus, the risk model may serve as a prognostic signature and offer highlights for individualized immunotherapy in SCCHN patients.

Integrated analysis of the functions of RNA binding proteins in clear cell renal cell carcinoma

RNA binding proteins (RBPs) dysregulation is involved in the processes of various tumors. However, the roles of RBPs in clear cell renal cell carcinoma (ccRCC) remain poorly understand. In present study, we first performed consensus clustering and identified two clusters, of which cluster 2 was closely correlated with the malignancy of ccRCC. Differentially expressed RBPs between normal and tumor tissues were obtained, comprising 71 up-regulated and 44 down-regulated ones. Then, ten hub genes were selected and validated using The Human Protein Atlas database and receiver operating characteristic curves, showing good diagnostic value for cancers. Besides, we identified ten RBPs with the most useful prognostic values, and were used to construct a risk score model. The model could be used to stratify patients with different prognosis and phenotype distributions. The model showed good performance and can be used as a complementation for clinical factors to guide clinical practice in the future.

The RNA-binding protein SERBP1 functions as a novel oncogenic factor in glioblastoma by bridging cancer metabolism and epigenetic regulation

BACKGROUND

RNA-binding proteins (RBPs) function as master regulators of gene expression. Alterations in RBP expression and function are often observed in cancer and influence critical pathways implicated in tumor initiation and growth. Identification and characterization of oncogenic RBPs and their regulatory networks provide new opportunities for targeted therapy.

RESULTS

We identify the RNA-binding protein SERBP1 as a novel regulator of glioblastoma (GBM) development. High SERBP1 expression is prevalent in GBMs and correlates with poor patient survival and poor response to chemo- and radiotherapy. SERBP1 knockdown causes delay in tumor growth and impacts cancer-relevant phenotypes in GBM and glioma stem cell lines. RNAcompete identifies a GC-rich region as SERBP1-binding motif; subsequent genomic and functional analyses establish SERBP1 regulation role in metabolic routes preferentially used by cancer cells. An important consequence of these functions is SERBP1 impact on methionine production. SERBP1 knockdown decreases methionine levels causing a subsequent reduction in histone methylation as shown for H3K27me3 and upregulation of genes associated with neurogenesis, neuronal differentiation, and function. Further analysis demonstrates that several of these genes are downregulated in GBM, potentially through epigenetic silencing as indicated by the presence of H3K27me3 sites.

CONCLUSIONS

SERBP1 is the first example of an RNA-binding protein functioning as a central regulator of cancer metabolism and indirect modulator of epigenetic regulation in GBM. By bridging these two processes, SERBP1 enhances glioma stem cell phenotypes and contributes to GBM poorly differentiated state.

Integrated Analysis of RNA-Binding Proteins in Glioma

RNA-binding proteins (RBPs) play important roles in many cancer types. However, RBPs have not been thoroughly and systematically studied in gliomas. Global analysis of the functional impact of RBPs will provide a better understanding of gliomagenesis and new insights into glioma therapy. In this study, we integrated a list of the human RBPs from six sources-Gerstberger, SONAR, Gene Ontology project, Poly(A) binding protein, CARIC, and XRNAX-which covered 4127 proteins with RNA-binding activity. The RNA sequencing data were downloaded from The Cancer Genome Atlas (TCGA) (n = 699) and Chinese Glioma Genome Atlas (CGGA) (n = 325 + 693). We examined the differentially expressed genes (DEGs) using the R package DESeq2, and constructed a weighted gene co-expression network analysis (WGCNA) of RBPs. Furthermore, survival analysis was also performed based on the univariate and multivariate Cox proportional hazards regression models. In the WGCNA analysis, we identified a key module involved in the overall survival (OS) of glioblastomas. Survival analysis revealed eight RBPs (PTRF, FNDC3B, SLC25A43, ZC3H12A, LRRFIP1, HSP90B1, HSPA5, and BNC2) are significantly associated with the survival of glioblastoma patients. Another 693 patients within the CGGA database were used to validate the findings. Additionally, 3564 RBPs were classified into canonical and non-canonical RBPs depending on the domains that they contain, and non-canonical RBPs account for the majority (72.95%). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that some non-canonical RBPs may have functions in glioma. Finally, we found that the knockdown of non-canonical RBPs, PTRF, or FNDC3B can alone significantly inhibit the proliferation of LN229 and U251 cells. Simultaneously, RNA Immunoprecipitation (RIP) analysis indicated that PTRF may regulate cell growth and death- related pathways to maintain tumor cell growth. In conclusion, our findings presented an integrated view to assess the potential death risks of glioblastoma at a molecular level, based on the expression of RBPs. More importantly, we identified non-canonical RNA-binding proteins PTRF and FNDC3B, showing them to be potential prognostic biomarkers for glioblastoma.

Autophagy Regulation by the Translation Machinery and Its Implications in Cancer

Various metabolic pathways and molecular processes in the cell act intertwined, and dysregulating the interplay between some of them may lead to cancer. It is only recently that defects in the translation process, i.e., the synthesis of proteins by the ribosome using a messenger (m)RNA as a template and translation factors, have begun to gain strong attention as a cause of autophagy dysregulation with effects in different maladies, including cancer. Autophagy is an evolutionarily conserved catabolic process that degrades cytoplasmic elements in lysosomes. It maintains cellular homeostasis and preserves cell viability under various stress conditions, which is crucial for all eukaryotic cells. In this review, we discuss recent advances shedding light on the crosstalk between the translation and the autophagy machineries and its impact on tumorigenesis. We also summarize how this interaction is being the target for novel therapies to treat cancer.

Integrated Analysis of the Functions and Prognostic Values of RNA Binding Proteins in Lung Squamous Cell Carcinoma

Lung cancer is the leading cause of cancer-related deaths worldwide. Dysregulation of RNA binding proteins (RBPs) has been found in a variety of cancers and is related to oncogenesis and progression. However, the functions of RBPs in lung squamous cell carcinoma (LUSC) remain unclear. In this study, we obtained gene expression data and corresponding clinical information for LUSC from The Cancer Genome Atlas (TCGA) database, identified aberrantly expressed RBPs between tumors and normal tissue, and conducted a series of bioinformatics analyses to explore the expression and prognostic value of these RBPs. A total of 300 aberrantly expressed RBPs were obtained, comprising 59 downregulated and 241 upregulated RBPs. Functional enrichment analysis indicated that the differentially expressed RBPs were mainly associated with mRNA metabolic processes, RNA processing, RNA modification, regulation of translation, the TGF-beta signaling pathway, and the Toll-like receptor signaling pathway. Nine RBP genes (A1CF, EIF2B5, LSM1, LSM7, MBNL2, RSRC1, TRMU, TTF2, and ZCCHC5) were identified as prognosis-associated hub genes by univariate, least absolute shrinkage and selection operator (LASSO), Kaplan–Meier survival, and multivariate Cox regression analyses, and were used to construct the prognostic model. Further analysis demonstrated that high risk scores for patients were significantly related to poor overall survival according to the model. The area under the time-dependent receiver operator characteristic curve of the prognostic model was 0.712 at 3 years and 0.696 at 5 years. We also developed a nomogram based on nine RBP genes, with internal validation in the TCGA cohort, which showed a favorable predictive efficacy for prognosis in LUSC. Our results provide novel insights into the pathogenesis of LUSC. The nine-RBP gene signature showed predictive value for LUSC prognosis, with potential applications in clinical decision-making and individualized treatment.