Inhibition of CYFIP2 promotes gastric cancer cell proliferation and chemoresistance to 5-fluorouracil through activation of the Akt signaling pathway

Advances in prognostic models for osteosarcoma risk

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

CA9, CYFIP2 and LGALS3BP-A Novel Biomarker Panel to Aid Prognostication in Glioma

Brain cancer is a devastating and life-changing disease. Biomarkers are becoming increasingly important in addressing clinical issues, including in monitoring tumour progression and assessing survival and treatment response. The goal of this study was to identify prognostic biomarkers associated with glioma progression. Discovery proteomic analysis was performed on a small cohort of astrocytomas that were diagnosed as low-grade and recurred at a higher grade. Six proteins were chosen to be validated further in a larger cohort. Three proteins, CA9, CYFIP2, and LGALS3BP, were found to be associated with glioma progression and, in univariate analysis, could be used as prognostic markers. However, according to the results of multivariate analysis, these did not remain significant. These three proteins were then combined into a three-protein panel. This panel had a specificity and sensitivity of 0.7459 for distinguishing between long and short survival. In silico data confirmed the prognostic significance of this panel.

Cyfip2 controls the acoustic startle threshold through FMRP, actin polymerization, and GABAB receptor function

Animals process a constant stream of sensory input, and to survive they must detect and respond to dangerous stimuli while ignoring innocuous or irrelevant ones. Behavioral responses are elicited when certain properties of a stimulus such as its intensity or size reach a critical value, and such behavioral thresholds can be a simple and effective mechanism to filter sensory information. For example, the acoustic startle response is a conserved and stereotyped defensive behavior induced by sudden loud sounds, but dysregulation of the threshold to initiate this behavior can result in startle hypersensitivity that is associated with sensory processing disorders including schizophrenia and autism. Through a previous forward genetic screen for regulators of the startle threshold a nonsense mutation in Cytoplasmic Fragile X Messenger Ribonucleoprotein (FMRP)-interacting protein 2 (cyfip2) was found that causes startle hypersensitivity in zebrafish larvae, but the molecular mechanisms by which Cyfip2 establishes the acoustic startle threshold are unknown. Here we used conditional transgenic rescue and CRISPR/Cas9 to determine that Cyfip2 acts though both Rac1 and FMRP pathways, but not the closely related FXR1 or FXR2, to establish the acoustic startle threshold during early neurodevelopment. To identify proteins and pathways that may be downstream effectors of Rac1 and FMRP, we performed a candidate-based drug screen that indicated that Cyfip2 can also act acutely to maintain the startle threshold branched actin polymerization and N-methyl D-aspartate receptors (NMDARs). To complement this approach, we used unbiased discovery proteomics to determine that loss of Cyfip2 alters cytoskeletal and extracellular matrix components while also disrupting oxidative phosphorylation and GABA receptor signaling. Finally, we functionally validated our proteomics findings by showing that activating GABAB receptors, which like NMDARs are also FMRP targets, restores normal startle sensitivity in cyfip2 mutants. Together, these data reveal multiple mechanisms by which Cyfip2 regulates excitatory/inhibitory balance in the startle circuit to control the processing of acoustic information.

CYFIP2 serves as a prognostic biomarker and correlates with tumor immune microenvironment in human cancers

BACKGROUND

The mechanisms whereby CYFIP2 acts in tumor development and drives immune infiltration have been poorly explored. Thus, this study aimed to identifying the role of CYFIP2 in tumors and immune response.

METHODS

In this study, we first explored expression patterns, diagnostic role and prognostic value of CYFIP2 in cancers, particularly in lung adenocarcinoma (LUAD). Then, we performed functional enrichment, genetic alterations, DNA methylation analysis, and immune cell infiltration analysis of CYFIP2 to uncover its potential mechanisms involved in immune microenvironment.

RESULTS

We found that CYFIP2 significantly differentially expressed in different tumors including LUAD compared with normal tissues. Furthermore, CYFIP2 was found to be significantly correlated with clinical parameters in LUAD. According to the diagnostic and survival analysis, CYFIP2 may be employed as a potential diagnostic and prognostic biomarker. Moreover, genetic alterations revealed that mutation of CYFIP2 was the main types of alterations in different cancers. DNA methylation analysis indicated that CYFIP2 mRNA expression correlated with hypomethylation. Afterwards, functional enrichment analysis uncovered that CYFIP2 was involved in tumor-associated and immune-related pathways. Immune infiltration analysis indicated that CYFIP2 was significantly correlated with immune cells infiltration. In particular, CYFIP2 was strongly linked with immune microenvironment scores. Additionally, CYFIP2 exhibited a significant relationship with immune regulators and immune-related genes including chemokines, chemokines receptors, and MHC genes.

CONCLUSION

Our results suggested that CYFIP2 may serve as a prognostic cancer biomarker for determining prognosis and might be a promising therapeutic strategy for tumor immunotherapy.

Migration speed of captured breast cancer subpopulations correlates with metastatic fitness

The genetic alterations contributing to migration proficiency, a phenotypic hallmark of metastatic cells required for colonizing distant organs, remain poorly defined. Here, we used single-cell magneto-optical capture (scMOCa) to isolate fast cells from heterogeneous human breast cancer cell populations, based on their migratory ability alone. We show that captured fast cell subpopulations retain higher migration speed and focal adhesion dynamics over many generations as a result of a motility-related transcriptomic profile. Upregulated genes in isolated fast cells encoded integrin subunits, proto-cadherins and numerous other genes associated with cell migration. Dysregulation of several of these genes correlates with poor survival outcomes in people with breast cancer, and primary tumors established from fast cells generated a higher number of circulating tumor cells and soft tissue metastases in pre-clinical mouse models. Subpopulations of cells selected for a highly migratory phenotype demonstrated an increased fitness for metastasis.

Comprehensive analysis of hypoxia-related genes for prognosis value, immune status, and therapy in osteosarcoma patients

Osteosarcoma is a common malignant bone tumor in children and adolescents. The overall survival of osteosarcoma patients is remarkably poor. Herein, we sought to establish a reliable risk prognostic model to predict the prognosis of osteosarcoma patients. Patients ' RNA expression and corresponding clinical data were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus databases. A consensus clustering was conducted to uncover novel molecular subgroups based on 200 hypoxia-linked genes. A hypoxia-risk models were established by Cox regression analysis coupled with LASSO regression. Functional enrichment analysis, including Gene Ontology annotation and KEGG pathway analysis, were conducted to determine the associated mechanisms. Moreover, we explored relationships between the risk scores and age, gender, tumor microenvironment, and drug sensitivity by correlation analysis. We identified two molecular subgroups with significantly different survival rates and developed a risk model based on 12 genes. Survival analysis indicated that the high-risk osteosarcoma patients likely have a poor prognosis. The area under the curve (AUC) value showed the validity of our risk scoring model, and the nomogram indicates the model's reliability. High-risk patients had lower Tfh cell infiltration and a lower stromal score. We determined the abnormal expression of three prognostic genes in osteosarcoma cells. Sunitinib can promote osteosarcoma cell apoptosis with down-regulation of KCNJ3 expression. In summary, the constructed hypoxia-related risk score model can assist clinicians during clinical practice for osteosarcoma prognosis management. Immune and drug sensitivity analysis can provide essential insights into subsequent mechanisms. KCNJ3 may be a valuable prognostic marker for osteosarcoma development.

A Novel 7-Methylguanosine (m7G)-Related Gene Signature for Overall Survival Prediction in Patient with Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common pathology type of renal cancer that has an abysmal prognosis. Although a crucial role for 7-methylguanosine modification in cancer cell development has been reported, its role in ccRCC remains uncertain. This study was conducted to determine the efficacy of predictive biomarkers based on m7G-related genes in ccRCC. Firstly, we extracted clinical data and gene expression profiles of ccRCC patients from publicly accessible databases. It identified that 22 of the m7G-related 34 genes were related to overall survival, and 5 of the 22 genes were significantly expressed differently in tumor tissues. Based on Lasso regression analysis, five optimal genes (CYFIP2, EIF4A1, NUDT1, NUDT10, and NUDT4) were chosen to build a new predictive risk model in the TCGA cohort. Validation was carried out with the E-MTAB-1980 cohort. Then, a prognostic nomogram was erected, including the m7G-related gene risk score, age, histological grade, and stage status. Further studies and analysis showed that immune cell infiltration might be associated with the m7G-related risk genes. In addition, the relationship between gene expression and drug response was evaluated by the Pearson correlation test. Therefore, the risk signature with five selected m7G-related genes may be a promising prognostic biomarker and contribute to standardized prognostic assessment for ccRCC.

Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas

Gliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expression patterns and function of the m7G RNA methylation regulator in gliomas are yet unknown. The goal of this study was to examine the expression patterns of 31 critical regulators linked with m7G RNA methylation and their prognostic significance in gliomas. To begin, we systematically analyzed patient clinical and prognostic data and mRNA gene expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We found that 17 key regulators of m7G RNA methylation showed significantly higher expression levels in gliomas. We then divided the sample into two subgroups by consensus clustering. Cluster 2 had a poorer prognosis than cluster 1 and was associated with a higher histological grade. In addition, cluster 2 was significantly enriched for cancer-related pathways. Based on this discovery, we developed a risk model involving three m7G methylation regulators. Patients were divided into high-risk and low-risk groups based on risk scores. Overall survival (OS) was significantly lower in the high-risk group than in the low-risk group. Further analysis showed that the risk score was an independent prognostic factor for gliomas.

Multi-omic characterization of genome-wide abnormal DNA methylation reveals diagnostic and prognostic markers for esophageal squamous-cell carcinoma

This study investigates aberrant DNA methylations as potential diagnosis and prognosis markers for esophageal squamous-cell carcinoma (ESCC), which if diagnosed at advanced stages has <30% five-year survival rate. Comparing genome-wide methylation sites of 91 ESCC and matched adjacent normal tissues, we identified 35,577 differentially methylated CpG sites (DMCs) and characterized their distribution patterns. Integrating whole-genome DNA and RNA-sequencing data of the same samples, we found multiple dysregulated transcription factors and ESCC-specific genomic correlates of identified DMCs. Using featured DMCs, we developed a 12-marker diagnostic panel with high accuracy in our dataset and the TCGA ESCC dataset, and a 4-marker prognostic panel distinguishing high-risk patients. In-vitro experiments validated the functions of 4 marker host genes. Together these results provide additional evidence for the important roles of aberrant DNA methylations in ESCC development and progression. Our DMC-based diagnostic and prognostic panels have potential values for clinical care of ESCC, laying foundations for developing targeted methylation assays for future non-invasive cancer detection methods.

The Downregulation of Prognosis- and Immune Infiltration-Related Gene CYFIP2 Serves as a Novel Target in ccRCC

Background

Increasing evidence indicated that the aberrant expression of the cytoplasmic FMR1-interacting protein (CYFIP) family might possess critical role and potential functions in cancer. But the role of CYFIP2 in clear cell renal cell carcinoma (ccRCC) is still uncharacteristic.

Methods

We investigated the Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC) database for the expression profile, clinicopathological variables, clinical prognosis information, and promoter methylation levels of CYFIPs in ccRCC. The aberrant CYFIP2 protein expression was validated by the Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to uncover CYFIP2 mRNA levels in 28 pairs of ccRCC cancer tissues. Kaplan–Meier analysis, univariate and multivariate Cox proportional hazard regression were performed to assess CYFIPs’ prognosis value. Gene set enrichment analysis (GSEA) was used to determined hallmark functions, gene ontology of CYFIP2. TIMER database was utilized to assess the correlation with immune infiltration in ccRCC.

Results

Results showed CYFIP2 was downregulated in ccRCC, relative to paired normal tissues in TCGA-KIRC database and 28 pairs of clinical samples (P < 0.0001). Similarly, a decreased CYFIP2 protein expression was confirmed by ccRCC tissues. The results showed CYFIP2 was negatively regulated by promoter DNA methylation. Survival analysis results showed CYFIP2 could be an independent biomarker for ccRCC and its reduction predicted a poor overall survival (OS) and disease-free survival (DFS). GSEA showed CYFIP2 was involved in metabolic pathways and epithelial–mesenchymal transition (EMT). Immune infiltration analysis revealed that a list of immune markers was significantly correlated with CYFIP2 expression especially with CD4+ cells and CD8+ cells in ccRCC.

Conclusion

These results show that CYFIP2 was downregulated in ccRCC patients and predicted an unfavorable prognosis. CYFIP2 might be a potential novel prognostic molecule, and related to immune infiltration, the metabolism, as well as EMT process in ccRCC. CYFIP2 could act as tumor suppressor gene in ccRCC and positive modulation of CYFIP2 might lead to development of a novel strategy for ccRCC treatment.

NUAK2 silencing inhibits the proliferation, migration and epithelial‑to‑mesenchymal transition of cervical cancer cells via upregulating CYFIP2

NUAK family kinase 2 (NUAK2) has been reported to be involved in various cancer cell processes, including proliferation, apoptosis and invasion, by targeting multiple genes. However, to the best of our knowledge, its biological function in cervical cancer (CC) has not yet been elucidated. Therefore, the present study aimed to measure the expression of NUAK2 and to evaluate its functions in CC. The expression levels of NUAK2 and cytoplasmic FMRP-interacting protein 2 (CYFIP2) were detected in CC tissues and cell lines. In addition, the effects of NUAK2 and CYFIP2 knockdown on CC cell proliferation, migration, invasion and epithelial-to-mesenchymal transition (EMT) were evaluated in vitro using Cell Counting Kit-8, immunofluorescence, wound healing assay, Transwell assay and western blotting, respectively. Furthermore, co-immunoprecipitation was performed to determine the interaction between NUAK2 and CYFIP2. The results revealed that the expression levels of NUAK2 were upregulated in CC tissues and cells, whereas CYFIP2 expression was reduced. In addition, knockdown of NUAK2 reduced cell proliferation, migration, invasion and EMT. Notably, NUAK2 was found to bind directly to CYFIP2. Furthermore, CYFIP2 inhibition reversed the effects of NUAK2 on CC cells. In summary, NUAK2 may regulate CYFIP2 expression to promote CC cell proliferation, migration, invasion and EMT.

The Future of Anticancer Drugs: A Cytotoxicity Assessment Study of CdSe/ZnS Quantum Dots

Quantum dots (QDs), including CdSe/ZnS, are nanoparticles emitting various wavelengths of fluorescent light depending on their size. Fluorescence allows them to be exploited for in vivo sensing/imaging of cancer cells. Nevertheless, thorough assessments of the effects of these commonly used QDs on cell stability are essentially required prior to their full applications. To investigate the effects of Cd QDs on the growth of human cervical cancer cells (HeLa), we utilized a growth assay, a reactive oxygen species (ROS) assay, an apoptosis assay, and RNA-seq. The growth assay results showed significant proliferation inhibition of HeLa cells by CdSe/ZnS. We revealed that smaller green CdSe/ZnS exerts more toxic effects than slightly larger yellow CdSe/ZnS. There were no significant increases of ROSs under the treatment of Cd QDs, which is consistent with the notion that low concentration of Cd QDs does not cause significant production of ROSs. In addition, we found that Cd QDs induced late apoptosis. RNA-Seq-based transcriptome analysis revealed that the exposure to green Cd QDs significantly upregulated antiapoptotic, antiproliferative, and antitumorigenic functions. The transcriptome profile also noted the downregulation of pro-proliferation, mitochondrial respiratory chain, detoxification, and receptor-mediated endocytosis. Taken together, our findings provide evidence that green CdSe/ZnS can be an alternative anticancer drug. In addition, our transcriptome analysis provides new insights into alteration of physiological state induced by CdSe/ZnS QDs in HeLa cancer cells.

Comprehensive molecular biomarker identification in breast cancer brain metastases

Background

Breast cancer brain metastases (BCBM) develop in about 20–30% of breast cancer (BC) patients. BCBM are associated with dismal prognosis not at least due to lack of valuable molecular therapeutic targets. The aim of the study was to identify new molecular biomarkers and targets in BCBM by using complementary state-of-the-art techniques.

Methods

We compared array expression profiles of three BCBM with 16 non-brain metastatic BC and 16 primary brain tumors (prBT) using a false discovery rate (FDR) p < 0.05 and fold change (FC) > 2. Biofunctional analysis was conducted on the differentially expressed probe sets. High-density arrays were employed to detect copy number variations (CNVs) and whole exome sequencing (WES) with paired-end reads of 150 bp was utilized to detect gene mutations in the three BCBM.

Results

The top 370 probe sets that were differentially expressed between BCBM and both BC and prBT were in the majority comparably overexpressed in BCBM and included, e.g. the coding genes BCL3, BNIP3, BNIP3P1, BRIP1, CASP14, CDC25A, DMBT1, IDH2, E2F1, MYCN, RAD51, RAD54L, and VDR. A number of small nucleolar RNAs (snoRNAs) were comparably overexpressed in BCBM and included SNORA1, SNORA2A, SNORA9, SNORA10, SNORA22, SNORA24, SNORA30, SNORA37, SNORA38, SNORA52, SNORA71A, SNORA71B, SNORA71C, SNORD13P2, SNORD15A, SNORD34, SNORD35A, SNORD41, SNORD53, and SCARNA22. The top canonical pathway was entitled, role of BRCA1 in DNA damage response. Network analysis revealed key nodes as Akt, ERK1/2, NFkB, and Ras in a predicted activation stage. Downregulated genes in a data set that was shared between BCBM and prBT comprised, e.g. BC cell line invasion markers JUN, MMP3, TFF1, and HAS2. Important cancer genes affected by CNVs included TP53, BRCA1, BRCA2, ERBB2, IDH1, and IDH2. WES detected numerous mutations, some of which affecting BC associated genes as CDH1, HEPACAM, and LOXHD1.

Conclusions

Using complementary molecular genetic techniques, this study identified shared and unshared molecular events in three highly aberrant BCBM emphasizing the challenge to detect new molecular biomarkers and targets with translational implications. Among new findings with the capacity to gain clinical relevance is the detection of overexpressed snoRNAs known to regulate some critical cellular functions as ribosome biogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12967-017-1370-x) contains supplementary material, which is available to authorized users.