Elucidation of the genetic and epigenetic landscape alterations in RNA binding proteins in glioblastoma

The differential expression of AFF3 in cervical cancer and its correlation with clinicopathological features and prognosis

BACKGROUND

Cervical cancer (CC) is the second most common malignancy in women, and identifying biomarkers of CC is crucial for prognosis prediction. Here, we investigated the expression of AF4/FMR2 Family Member 3 (AFF3) in CC and its association with clinicopathological features and prognosis.

METHODS

Tumour and adjacent tissues, along with clinicopathological features and follow-up information, were collected from 78 patients. AFF3 expression was assessed using quantitative real-time polymerase chain reaction and Western blotting. The correlation between AFF3 expression and CC symptoms was using chi-square test. The 5-year overall survival (OS) was analysed using the Kaplan-Meier method. The Univariate analysis of prognostic risk factors was conducted using the COX proportional hazards model, followed by multivariate COX regression analysis including variables with p < 0.01.

RESULTS

AFF3 expression was downregulated in CC, and its levels were correlated with lymph node metastasis (LNM) and International Federation of Gynaecology and Obstetrics (FIGO) stage. Patients with low AFF3 expression had a lower 5-year OS rate (52.78%, 19/36). Postoperative survival was reduced in patients with histological grade 3 (G3), myometrial invasion (depth ≥ 1/2), lymphovascular space invasion, LNM, and advanced FIGO stage. Low expression of AFF3 (HR: 2.848, 95% CI: 1.144-7.090) and histological grade G3 (HR: 4.393, 95% CI: 1.663-11.607) were identified as independent prognostic risk factors in CC patients.

CONCLUSION

Low expression of AFF3 and histological G3 are independent predictors of poor prognosis in CC patients, suggesting that AFF3 could serve as a potential biomarker for prognostic assessment in CC.

Single-cell RNA sequencing analysis of vestibular schwannoma reveals functionally distinct macrophage subsets

BACKGROUND

Vestibular schwannomas (VSs) remain a challenge due to their anatomical location and propensity to growth. Macrophages are present in VS but their roles in VS pathogenesis remains unknown.

OBJECTIVES

The objective was to assess phenotypic and functional profile of macrophages in VS with single-cell RNA sequencing (scRNAseq).

METHODS

scRNAseq was carried out in three VS samples to examine characteristics of macrophages in the tumour. RT-qPCR was carried out on 10 VS samples for CD14, CD68 and CD163 and a panel of macrophage-associated molecules.

RESULTS

scRNAseq revealed macrophages to be a major constituent of VS microenvironment with three distinct subclusters based on gene expression. The subclusters were also defined by expression of CD163, CD68 and IL-1β. AREG and PLAUR were expressed in the CD68+CD163+IL-1β+ subcluster, PLCG2 and NCKAP5 were expressed in CD68+CD163+IL-1β- subcluster and AUTS2 and SPP1 were expressed in the CD68+CD163-IL-1β+ subcluster. RT-qPCR showed expression of several macrophage markers in VS of which CD14, ALOX15, Interleukin-1β, INHBA and Colony Stimulating Factor-1R were found to have a high correlation with tumour volume.

CONCLUSIONS

Macrophages form an important component of VS stroma. scRNAseq reveals three distinct subsets of macrophages in the VS tissue which may have differing roles in the pathogenesis of VS.

HERC5 downregulation in non-small cell lung cancer is associated with altered energy metabolism and metastasis

BACKGROUND

Metastasis is the leading cause of cancer-related death in non-small cell lung cancer (NSCLC) patients. We previously showed that low HERC5 expression predicts early tumor dissemination and a dismal prognosis in NSCLC patients. Here, we performed functional studies to unravel the mechanism underlying the "metastasis-suppressor" effect of HERC5, with a focus on mitochondrial metabolism pathways.

METHODS

We assessed cell proliferation, colony formation potential, anchorage-independent growth, migration, and wound healing in NSCLC cell line models with HERC5 overexpression (OE) or knockout (KO). To study early tumor cell dissemination, we used these cell line models in zebrafish experiments and performed intracardial injections in nude mice. Mass spectrometry (MS) was used to analyze protein changes in whole-cell extracts. Furthermore, electron microscopy (EM) imaging, cellular respiration, glycolytic activity, and lactate production were used to investigate the relationships with mitochondrial energy metabolism pathways.

RESULTS

Using different in vitro NSCLC cell line models, we showed that NSCLC cells with low HERC5 expression had increased malignant and invasive properties. Furthermore, two different in vivo models in zebrafish and a xenograft mouse model showed increased dissemination and metastasis formation (in particular in the brain). Functional enrichment clustering of MS data revealed an increase in mitochondrial proteins in vitro when HERC5 levels were high. Loss of HERC5 leads to an increased Warburg effect, leading to improved adaptation and survival under prolonged inhibition of oxidative phosphorylation.

CONCLUSIONS

Taken together, these results indicate that low HERC5 expression increases the metastatic potential of NSCLC in vitro and in vivo. Furthermore, HERC5-induced proteomic changes influence mitochondrial pathways, ultimately leading to alterations in energy metabolism and demonstrating its role as a new potential metastasis suppressor gene.

A Transcription Factor ZNF384, Regulated by LINC00265, Activates the Expression of IFI30 to Stimulate Malignant Progression in Glioma

Glioma remains one of the most challenging primary brain malignancies to treat. Long noncoding RNAs (lncRNAs) and mRNAs (mRNAs) are implicated in regulating the malignant phenotypes of cancers including glioma. This study aimed to elucidate the functions and mechanisms of lncRNA LINC00265 and mRNA IFI30 in the pathogenesis of glioma. Quantitative real-time polymerase chain reaction (RT-qPCR) analysis revealed the upregulated expression of LINC00265 and IFI30 in glioma cells compared to normal human astrocytes. Western blot (WB) quantified the associated proteins. Glioma stemness and epithelial-to-mesenchymal transition (EMT) were assessed by aldehyde dehydrogenase 1 (ALDH1) activity, sphere formation, and WB. Mechanistic and rescue assays evaluated the LINC00265/miR-let-7d-5p/IFI30/ZNF384/IGF2BP2 axis. The results demonstrated that LINC00265 and IFI30 were highly expressed in glioma cells, promoting stemness and EMT. ZNF384 was identified as a transcription factor that upregulates IFI30. Moreover, LINC00265 elevated ZNF384 by sponging miR-let-7d-5p and recruiting IGF2BP2. In conclusion, LINC00265 and IFI30 act as oncogenes in glioma by driving stemness and EMT, underscoring their potential as therapeutic targets.

AHNAKs roles in physiology and malignant tumors

The AHNAK family currently consists of two members, namely AHNAK and AHNAK2, both of which have a molecular weight exceeding 600 kDa. Homologous sequences account for approximately 90% of their composition, indicating a certain degree of similarity in terms of molecular structure and biological functions. AHNAK family members are involved in the regulation of various biological functions, such as calcium channel modulation and membrane repair. Furthermore, with advancements in biological and bioinformatics technologies, research on the relationship between the AHNAK family and tumors has rapidly increased in recent years, and its regulatory role in tumor progression has gradually been discovered. This article briefly describes the physiological functions of the AHNAK family, and reviews and analyzes the expression and molecular regulatory mechanisms of the AHNAK family in malignant tumors using Pubmed and TCGA databases. In summary, AHNAK participates in various physiological and pathological processes in the human body. In multiple types of cancers, abnormal expression of AHNAK and AHNAK2 is associated with prognosis, and they play a key regulatory role in tumor progression by activating signaling pathways such as ERK, MAPK, Wnt, and MEK, as well as promoting epithelial-mesenchymal transition.

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.

Whole exome sequencing reveals novel risk genes of pituitary neuroendocrine tumors

Somatic genetic alterations in pituitary neuroendocrine tumors (PitNET) tissues have been identified in several studies, but detection of overlapping somatic PitNET candidate genes is rare. We sequenced and by employing multiple data analysis methods studied the exomes of 15 PitNET patients to improve discovery of novel factors involved in PitNET development. PitNET patients were recruited to the study before PitNET removal surgery. For each patient, two samples for DNA extraction were acquired: venous blood and PitNET tissue. Exome sequencing was performed using Illumina NexSeq 500 sequencer and data analyzed using two separate workflows and variant calling algorithms: GATK and Strelka2. A combination of two data analysis pipelines discovered 144 PitNET specific somatic variants (mean = 9.6, range 0–19 per PitNET) of which all were SNVs. Also, we detected previously known GNAS PitNET mutation and identified somatic variants in 11 genes, which have contained somatic variants in previous WES and WGS studies of PitNETs. Noteworthy, this is the third study detecting somatic variants in gene RYR1 in the exomes of PitNETs. In conclusion, we have identified two novel PitNET candidate genes (AC002519.6 and AHNAK) with recurrent somatic variants in our PitNET cohort and found 13 genes overlapping from previous PitNET studies that contain somatic variants. Our study demonstrated that the use of multiple sequencing data analysis pipelines can provide more accurate identification of somatic variants in PitNETs.

AFF3 is a novel prognostic biomarker and a potential target for immunotherapy in gastric cancer

Background

Gastric cancer (GC) is one of the most common cancers worldwide with a poor prognosis. The tumor microenvironment (TME) serves a pivotal role in affecting the prognosis and efficacy of immunotherapy. Given the poor prognosis of GC patients and the limitation of immunotherapy, we urged to identify new prognostic and immunotherapeutic biomarkers.

Methods

The transcriptome data were downloaded from the TCGA, GEO, and GEPIA databases, and performed differential analysis of AFF3 in tumor samples and normal samples. The UALCAN, Kaplan–Meier plotter and GEPIA databases were employed to assess the correlation of AFF3 with clinicopathological characteristics and prognosis. The potential mechanism of AFF3 was explored by the GO and KEGG enrichment. The potential role of AFF3 on tumor‐infiltrating immune cells (TIICs) was explored by TIMER2.0 and TISIDB. TIMER2.0 and SangerBox3.0 databases were, respectively, used to determine the correlation of AFF3 with immune checkpoint (ICs), tumor mutational burden (TMB), and microsatellite instability (MSI) in GC.

Results

We found significant downregulation of AFF3 in GC tissues as compared with normal tissues. However, GC patients having a higher expression of AFF3 were found to have worse clinicopathological characteristics and prognosis. Moreover, the GO enrichment analysis illustrated that AFF3 might regulate the immune cells in the TME. In addition, the AFF3 was positively correlated with TIICs, ICs, TMB, and MSI.

Conclusion

Here, we conclude that AFF3 may be a promising potential marker for the diagnosis and prognosis of GC patients, and may influence response to ICIs by affecting TIICs and ICs expression in the TME.

Interaction between TMEFF1 and AHNAK proteins in ovarian cancer cells: Implications for clinical prognosis

TMEFF1 is a newly discovered protein involved in the physiological functions of the central nervous system, embryonic development, and other biological processes. Our previous study revealed that TMEFF1 acts as a tumor-promoting gene in ovarian cancer. AHNAK, as a giant scaffolding protein, plays a role in the formation of the blood-brain barrier, cell architecture and the regulation of cardiac calcium channels. However, its role in ovarian cancer remains poorly researched. In this study, we detected the expression of AHNAK and TMEFF1 in 148 different ovarian cancer tissues, determined their relationship with pathological parameters and prognosis, clarified the interaction between the two proteins, and explored the related cancer-promoting mechanisms through immunohistochemistry, immunoprecipitation, immunofluorescence double staining, western blotting, and bioinformatics. The high expression of ANHAK and TMEFF1 in ovarian cancer indicated a higher degree of tumor malignancy and a worse prognosis. Furthermore, the expression of TMEFF1 and AHNAK was significantly positively correlated. The results also showed that AHNAK and TMEFF1 co-localized and interacted with each other in ovarian cancer tissues and cells. And knockdown of AHNAK promoted proliferation, migration and invasion of ovarian cancer cells in vitro. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that AHNAK and related genes were enriched during mitosis regulation, cytoskeleton formation, gene epigenetics, etc., whereas TMEFF1 and related genes are enriched during immune regulation and other processes. We also clarified the network of kinases, microRNA, and transcription factor targets, and the impact of genetic mutations on prognosis. Notably, AHNAK was regulated by the expression of TMEFF1 and can activate the MAPK pathways. Overall, high expression of AHNAK and TMEFF1 in ovarian cancer cells indicated a higher degree of tumor malignancy and a worse prognosis. Therefore, the interaction between AHNAK and TMEFF1 may become a potential anti-tumor target for ovarian cancer treatment.

Translational Regulation by hnRNP H/F Is Essential for the Proliferation and Survival of Glioblastoma

Deregulation of mRNA translation is a widespread characteristic of glioblastoma (GBM), aggressive malignant brain tumors that are resistant to conventional therapies. RNA-binding proteins (RBPs) play a critical role in translational regulation, yet the mechanisms and impact of these regulations on cancer development, progression and response to therapy remain to be fully understood. Here, we showed that hnRNP H/F RBPs are potent regulators of translation through several mechanisms that converge to modulate the expression and/or the activity of translation initiation factors. Among these, hnRNP H/F regulate the phosphorylation of eIF4E and its translational targets by controlling RNA splicing of the A-Raf kinase mRNA, which in turn modulates the MEK-ERK/MAPK signaling pathway. The underlying mechanism involves RNA G-quadruplex (RG4s), RNA structures whose modulation phenocopies hnRNP H/F translation regulation in GBM cells. Our results highlighted that hnRNP H/F are essential for key functional pathways regulating proliferation and survival of GBM, highlighting its targeting as a promising strategy for improving therapeutic outcomes.

The alerting expression of microRNA-411 predicts clinical prognosis and regulates tumor progression of glioblastoma

Glioblastoma is a malignant intracranial tumor with indispensable growth. Identification of biomarkers associated with the progression of tumors could benefit the clinical therapy of and improve patient’s survival. miR-411 has been reported to play a role in other cancers, while its function in glioblastoma has been explored in the present study. The expression of miR-411 was evaluated in glioblastoma tissues (collected from 108 glioblastoma patients) and cells by polymerase chain reaction. The clinical significance of miR-411 was estimated with a series of statistical analyses. The biological function of miR-411 in the cellular processes of glioblastoma was assessed by cell counting kit 8 and Transwell assay. The expression of miR-411 was significantly reduced in glioblastoma, which was associated with the Karnofsky Performance Score (KPS) and Isocitrate dehydrogenase 1 (IDH1) status of patients. miR-411 was identified as an independent prognostic indicator that correlated with the poor prognosis of patients. miR-411 suppressed the growth, migration, and invasion of glioblastoma cells via modulating signal transducer and activator of transcription 3 (STAT3). miR-411 participated in the development of glioblastoma and function as a prognostic biomarker. miR-411 functions as a tumor suppressor, which provides a novel potential therapeutic target for glioblastoma.

The Impact of Epigenetic Modifications on Adaptive Resistance Evolution in Glioblastoma

Glioblastoma (GBM) is a highly lethal cancer that is universally refractory to the standard multimodal therapies of surgical resection, radiation, and chemotherapy treatment. Temozolomide (TMZ) is currently the best chemotherapy agent for GBM, but the durability of response is epigenetically dependent and often short-lived secondary to tumor resistance. Therapies that can provide synergy to chemoradiation are desperately needed in GBM. There is accumulating evidence that adaptive resistance evolution in GBM is facilitated through treatment-induced epigenetic modifications. Epigenetic alterations of DNA methylation, histone modifications, and chromatin remodeling have all been implicated as mechanisms that enhance accessibility for transcriptional activation of genes that play critical roles in GBM resistance and lethality. Hence, understanding and targeting epigenetic modifications associated with GBM resistance is of utmost priority. In this review, we summarize the latest updates on the impact of epigenetic modifications on adaptive resistance evolution in GBM to therapy.

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.

Gene expression-based biomarkers designating glioblastomas resistant to multiple treatment strategies

Despite advances in molecular characterization of glioblastoma multiforme (GBM), only a handful of predictive biomarkers exist with limited clinical relevance. We aimed to identify differentially expressed genes in tumor samples collected at surgery associated with response to subsequent treatment, including temozolomide (TMZ) and nitrosoureas. Gene expression was collected from multiple independent datasets. Patients were categorized as responders/nonresponders based on their survival status at 16 months postsurgery. For each gene, the expression was compared between responders and nonresponders with a Mann-Whitney U-test and receiver operating characteristic. The package 'roc' was used to calculate the area under the curve (AUC). The integrated database comprises 454 GBM patients from 3 independent datasets and 10 103 genes. The highest proportion of responders (68%) were among patients treated with TMZ combined with nitrosoureas, where FCGR2B upregulation provided the strongest predictive value (AUC = 0.72, P < 0.001). Elevated expression of CSTA and MRPS17 was associated with a lack of response to multiple treatment strategies. DLL3 upregulation was present in subsequent responders to any treatment combination containing TMZ. Three genes (PLSCR1, MX1 and MDM2) upregulated both in the younger cohort and in patients expressing low MGMT delineate a subset of patients with worse prognosis within a population generally associated with a favorable outcome. The identified transcriptomic changes provide biomarkers of responsiveness, offer avenues for preclinical studies and may enhance future GBM patient stratifications. The described methodology provides a reliable pipeline for the initial testing of potential biomarker candidates for future validation studies.

Biology of Glioblastoma Multiforme-Exploration of Mitotic Catastrophe as a Potential Treatment Modality

Glioblastoma multiforme (GBM) represents approximately 60% of all brain tumors in adults. This malignancy shows a high biological and genetic heterogeneity associated with exceptional aggressiveness, leading to a poor survival of patients. This review provides a summary of the basic biology of GBM cells with emphasis on cell cycle and cytoskeletal apparatus of these cells, in particular microtubules. Their involvement in the important oncosuppressive process called mitotic catastrophe will next be discussed along with select examples of microtubule-targeting agents, which are currently explored in this respect such as benzimidazole carbamate compounds. Select microtubule-targeting agents, in particular benzimidazole carbamates, induce G₂/M cell cycle arrest and mitotic catastrophe in tumor cells including GBM, resulting in phenotypically variable cell fates such as mitotic death or mitotic slippage with subsequent cell demise or permanent arrest leading to senescence. Their effect is coupled with low toxicity in normal cells and not developed chemoresistance. Given the lack of efficient cytostatics or modern molecular target-specific compounds in the treatment of GBM, drugs inducing mitotic catastrophe might offer a new, efficient alternative to the existing clinical management of this at present incurable malignancy.

HERC Ubiquitin Ligases in Cancer

HERC proteins are ubiquitin E3 ligases of the HECT family. The HERC subfamily is composed of six members classified by size into large (HERC1 and HERC2) and small (HERC3-HERC6). HERC family ubiquitin ligases regulate important cellular processes, such as neurodevelopment, DNA damage response, cell proliferation, cell migration, and immune responses. Accumulating evidence also shows that this family plays critical roles in cancer. In this review, we provide an integrated view of the role of these ligases in cancer, highlighting their bivalent functions as either oncogenes or tumor suppressors, depending on the tumor type. We include a discussion of both the molecular mechanisms involved and the potential therapeutic strategies.

Identification of Dysregulated Competitive Endogenous RNA Networks Driven by Copy Number Variations in Malignant Gliomas

Gliomas represent 80% of malignant brain tumors. Because of the high heterogeneity, the oncogenic mechanisms in gliomas are still unclear. In this study, we developed a new approach to identify dysregulated competitive endogenous RNA (ceRNA) interactions driven by copy number variation (CNV) in both lower-grade glioma (LGG) and glioblastoma multiforme (GBM). By analyzing genome and transcriptome data from The Cancer Genome Atlas (TCGA), we first found out the protein coding genes and long non-coding RNAs (lncRNAs) significantly affected by CNVs and further determined CNV-driven dysregulated ceRNA interactions by a customized pipeline. We obtained 13,776 CNV-driven dysregulated ceRNA pairs (including 3,954 mRNAs and 306 lncRNAs) in LGG and 262 pairs (including 221 mRNAs and 11 lncRNAs) in GBM, respectively. Our results showed that most of the ceRNA interactions were weakened by CNVs in both LGG and GBM, and many CNV-driven genes shared the same ceRNAs in the dysregulated ceRNA networks. Functional analysis indicated that the CNV-driven ceRNA network involved in some important mechanisms of tumorigenesis, such as cell cycle, p53 signaling pathway and TGF-beta signaling pathway. Further investigation of the ceRNA pairs in the communities from the dysregulated ceRNA network revealed more detailed biological functions related to the oncogenesis of malignant gliomas. Moreover, by exploring the association of CNV-driven ceRNAs with prognosis and histological subtype, we found that the copy number status of MTAP, KLHL9, and ELAVL2 related to the overall survival in LGG and showed high correlation with histological subtype. In conclusion, this study provided new insight into the molecular mechanisms and clinical biomarkers in gliomas.

Transcriptomic Analysis Identifies RNA Binding Proteins as Putative Regulators of Myelopoiesis and Leukemia

Acute myeloid leukemia (AML) is a common and aggressive hematological malignancy. Acquisition of heterogeneous genetic aberrations and epigenetic dysregulation lead to the transformation of hematopoietic stem cells (HSC) into leukemic stem cells (LSC), which subsequently gives rise to immature blast cells and a leukemic phenotype. LSCs are responsible for disease relapse as current chemotherapeutic regimens are not able to completely eradicate these cellular sub-populations. Therefore, it is critical to improve upon the existing knowledge of LSC specific markers, which would allow for specific targeting of these cells more effectively allowing for their sustained eradication from the cellular milieu. Although significant milestones in decoding the aberrant transcriptional network of various cancers, including leukemia, have been achieved, studies on the involvement of post-transcriptional gene regulation (PTGR) in disease progression are beginning to unfold. RNA binding proteins (RBPs) are key players in mediating PTGR and they regulate the intracellular fate of individual transcripts, from their biogenesis to RNA metabolism, via interactions with RNA binding domains (RBDs). In this study, we have used an integrative approach to systematically profile RBP expression and identify key regulatory RBPs involved in normal myeloid development and AML. We have analyzed RNA-seq datasets (GSE74246) of HSCs, common myeloid progenitors (CMPs), granulocyte-macrophage progenitors (GMPs), monocytes, LSCs, and blasts. We observed that normal and leukemic cells can be distinguished on the basis of RBP expression, which is indicative of their ability to define cellular identity, similar to transcription factors. We identified that distinctly co-expressing modules of RBPs and their subclasses were enriched in hematopoietic stem/progenitor (HSPCs) and differentiated monocytes. We detected expression of DZIP3, an E3 ubiquitin ligase, in HSPCs, knockdown of which promotes monocytic differentiation in cell line model. We identified co-expression modules of RBP genes in LSCs and among these, distinct modules of RBP genes with high and low expression. The expression of several AML-specific RBPs were also validated by quantitative polymerase chain reaction. Network analysis identified densely connected hubs of ribosomal RBP genes (rRBPs) with low expression in LSCs, suggesting the dependency of LSCs on altered ribosome dynamics. In conclusion, our systematic analysis elucidates the RBP transcriptomic landscape in normal and malignant myelopoiesis, and highlights the functional consequences that may result from perturbation of RBP gene expression in these cellular landscapes.

Ranking genomic features using an information-theoretic measure of epigenetic discordance

Background

Establishment and maintenance of DNA methylation throughout the genome is an important epigenetic mechanism that regulates gene expression whose disruption has been implicated in human diseases like cancer. It is therefore crucial to know which genes, or other genomic features of interest, exhibit significant discordance in DNA methylation between two phenotypes. We have previously proposed an approach for ranking genes based on methylation discordance within their promoter regions, determined by centering a window of fixed size at their transcription start sites. However, we cannot use this method to identify statistically significant genomic features and handle features of variable length and with missing data.

Results

We present a new approach for computing the statistical significance of methylation discordance within genomic features of interest in single and multiple test/reference studies. We base the proposed method on a well-articulated hypothesis testing problem that produces p- and q-values for each genomic feature, which we then use to identify and rank features based on the statistical significance of their epigenetic dysregulation. We employ the information-theoretic concept of mutual information to derive a novel test statistic, which we can evaluate by computing Jensen-Shannon distances between the probability distributions of methylation in a test and a reference sample. We design the proposed methodology to simultaneously handle biological, statistical, and technical variability in the data, as well as variable feature lengths and missing data, thus enabling its wide-spread use on any list of genomic features. This is accomplished by estimating, from reference data, the null distribution of the test statistic as a function of feature length using generalized additive regression models. Differential assessment, using normal/cancer data from healthy fetal tissue and pediatric high-grade glioma patients, illustrates the potential of our approach to greatly facilitate the exploratory phases of clinically and biologically relevant methylation studies.

Conclusions

The proposed approach provides the first computational tool for statistically testing and ranking genomic features of interest based on observed DNA methylation discordance in comparative studies that accounts, in a rigorous manner, for biological, statistical, and technical variability in methylation data, as well as for variability in feature length and for missing data.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2777-6) contains supplementary material, which is available to authorized users.

A Potential Prognostic Gene Signature for Predicting Survival for Glioblastoma Patients

OBJECTIVE

This study aimed to screen prognostic gene signature of glioblastoma (GBM) to construct prognostic model.

METHODS

Based on the GBM information in the Cancer Genome Atlas (TCGA, training set), prognostic genes (Set X) were screened by Cox regression. Then, the optimized prognostic gene signature (Set Y) was further screened by the Cox-Proportional Hazards (Cox-PH). Next, two prognostic models were constructed: model A was based on the Set Y; model B was based on part of the Set X. The samples were divided into low- and high-risk groups according to the median prognosis index (PI). GBM datasets in Gene Expression Ominous (GEO, GSE13041) and Chinese Glioma Genome Atlas (CGGA) were used as the testing datasets to confirm the prognostic models constructed based on TCGA.

RESULTS

We identified that the prognostic 14-gene signature was significantly associated with the overall survival (OS) in the TCGA. In model A, patients in high- and low-risk groups showed the significantly different OS (P = 7.47 × 10-9, area under curve (AUC) 0.995) and the prognostic ability were also confirmed in testing sets (P=0.0098 and 0.037). The model B in training set was significant but failed in testing sets.

CONCLUSION

The prognostic model which was constructed based on the prognostic 14-gene signature presented a high predictive ability for GBM. The 14-gene signature may have clinical implications in the subclassification of GBM.

MicroRNAs, Hypoxia and the Stem-Like State as Contributors to Cancer Aggressiveness

MicroRNAs (miRNAs) are small non-coding RNA molecules that play key regulatory roles in cancer acting as both oncogenes and tumor suppressors. Due to their potential roles in improving cancer prognostic, predictive, diagnostic and therapeutic approaches, they have become an area of intense research focus in recent years. Several studies have demonstrated an altered expression of several miRNAs under hypoxic condition and even shown that the hypoxic microenvironment drives the selection of a more aggressive cancer cell population through cellular adaptations referred as the cancer stem-like cell. These minor fractions of cells are characterized by their self-renewal abilities and their ability to maintain the tumor mass, suggesting their crucial roles in cancer development. This review aims to highlight the interconnected role between miRNAs, hypoxia and the stem-like state in contributing to the cancer aggressiveness as opposed to their independent contributions, and it is based in four aggressive tumors, namely glioblastoma, cervical, prostate, and breast cancers.

IGF2 mRNA binding protein 3 (IMP3) promotes glioma cell migration by enhancing the translation of RELA/p65

The diffusely infiltrative nature of glioblastoma (GBM) makes them highly recurrent. IGF2 mRNA-binding protein 3 (IMP3), a GBM upregulated RNA binding protein, promotes glioma cell migration. An integrative bioinformatics analysis identified p65 (RELA), a subunit of NF-κB heterodimer as a target and an important mediator of IMP3 promoted glioma cell migration. IMP3 increased p65 protein levels without any change in p65 transcript levels, but promoted its polysome association. RIP-PCR demonstrated the binding of IMP3 to p65 transcript. UV crosslinking experiments with in vitro transcribed RNA confirmed the specific and direct binding of IMP3 to sites on p65 3′UTR. Further, IMP3 induced luciferase activity from p65 3′UTR reporter carrying wild type sites but not mutated sites. Exogenous overexpression of p65 from a 3′UTR-less construct rescued the reduced migration of glioma cells in IMP3 silenced condition. In addition, IMP3 silencing inhibited glioma stem-like cell maintenance and migration. The exogenous overexpression of 3′UTR-less p65 significantly alleviated the inhibition of neurosphere formation observed in IMP3 silenced glioma stem-like cells. Further, we show that IMP3 is transcriptionally activated by NF-κB pathway indicating the presence of a positive feedback loop between IMP3 and p65. This study establishes p65 as a novel target of IMP3 in increasing glioma cell migration and underscores the significance of IMP3-p65 feedback loop for therapeutic targeting in GBM.

AHNAK as a Prognosis Factor Suppresses the Tumor Progression in Glioma

PURPOSE

AHNAK is originally identified as a giant protein based on the estimated size of approximately 700 kDa. The aim of this study is to identify the role of AHNAK in the pathogenesis of glioma.

METHODS

We tested AHNAK mRNA level in a panel of six human glioma cell lines, and in 30 cases of normal brain tissues and 73 cases of glioma tissue samples using a qRT-PCR method. Further, we analyzed the relationship of AHNAK expression with clinicopathological characteristics in glioma patients. Meanwhile, we analyzed the relationship of expression of AHNAK and survival of glioma patients in survival analyses. Then, in vitro, we analyzed the biological effects of AHNAK in glioma cell lines (U87 and U251) including proliferation assay, cell transwell assay, and apoptosis. And in vivo, we examined the effects of AHNAK on tumor growth using xenograft model of human glioma cells in nude mice. Then we examined the expression of Ki-67-positive cells in these tumors.

RESULTS

We found that the mRNA levels of AHNAK were down-regulated in 4 of 6 human glioma cell lines, especially in U87 and U251 cell lines. Meanwhile, in glioma patients, a negative correlation was found between the expression of AHNAK and the glioma histopathology. And a low expression of AHNAK was a significant and independent prognostic factor for poor survival of glioma patients. Through over expression of AHNAK in both of U87 and U251, we demonstrated that overexpression of AHNAK could inhibit glioma cell proliferation and invasion, induce apoptosis, and inhibit in vivo glioma tumor growth and ki-67 expression.

CONCLUSIONS

The AHNAK acts as a potential tumor suppressor. Our study provides a preclinical basis for developing AHNAK as a reliable clinical prognostic indicator for glioma patients, and a new biomarker for treatment response, and a potentially therapeutic target in glioma management options.