ESPL1 is a candidate oncogene of luminal B breast cancers

lncRNA MIAT promotes luminal B breast cancer cell proliferation, migration, and invasion in vitro

Long noncoding RNAs (lncRNAs) play a role in the emergence and progression of several human tumors, including luminal B breast cancer (BC). The biological functions and potential mechanisms of lncRNA myocardial infarction-associated transcripts (MIAT) in luminal B BC, on the contrary, are unknown. In this work, we used UALCAN database analysis to find high expression of lncRNA MIAT in luminal BC tissues and also confirmed high levels of lncRNA MIAT expression in luminal B BC tissues and cells. In vitro knockdown of MIAT inhibited the proliferation, migration, and invasion of BT474 cells. In addition, we found that miR-150-5p levels were significantly reduced in luminal B BC specimens and cells, and miR-150-5p levels were significantly increased when MIAT was knocked down. And TIMER database analysis showed that MIAT was positively associated with PDL1. Through bioinformatic tools and in vitro experiments, lncRNA MIAT could function as a competitive endogenous RNA (CeRNA) to further regulate programmed cell death ligand 1 (PDL1) expression by directly sponging miR-150-5p. In conclusion, our data suggest that MIAT, an oncogene, may sponge miR-150-5p to regulate PDL1 expression and affect proliferation, migration, and invasion in luminal B BC in vitro.

Centrosomes and associated proteins in pathogenesis and treatment of breast cancer

Breast cancer is the most prevalent malignancy among women worldwide. Despite significant advances in treatment, it remains one of the leading causes of female mortality. The inability to effectively treat advanced and/or treatment-resistant breast cancer demonstrates the need to develop novel treatment strategies and targeted therapies. Centrosomes and their associated proteins have been shown to play key roles in the pathogenesis of breast cancer and thus represent promising targets for drug and biomarker development. Centrosomes are fundamental cellular structures in the mammalian cell that are responsible for error-free execution of cell division. Centrosome amplification and aberrant expression of its associated proteins such as Polo-like kinases (PLKs), Aurora kinases (AURKs) and Cyclin-dependent kinases (CDKs) have been observed in various cancers, including breast cancer. These aberrations in breast cancer are thought to cause improper chromosomal segregation during mitosis, leading to chromosomal instability and uncontrolled cell division, allowing cancer cells to acquire new genetic changes that result in evasion of cell death and the promotion of tumor formation. Various chemical compounds developed against PLKs and AURKs have shown meaningful antitumorigenic effects in breast cancer cells in vitro and in vivo. The mechanism of action of these inhibitors is likely related to exacerbation of numerical genomic instability, such as aneuploidy or polyploidy. Furthermore, growing evidence demonstrates enhanced antitumorigenic effects when inhibitors specific to centrosome-associated proteins are used in combination with either radiation or chemotherapy drugs in breast cancer. This review focuses on the current knowledge regarding the roles of centrosome and centrosome-associated proteins in breast cancer pathogenesis and their utility as novel targets for breast cancer treatment.

Comparative transcriptomic analyses of brain-liver-muscle in channel catfish (Ictalurus punctatus) with differential growth rate

Growth is an important economically trait for aquatic animals. The popularity of farmed channel catfish (Ictalurus punctatus) in China has recently surged, prompting a need for research into the genetic mechanisms that drive growth and development to expedite the selection of fast-growing variants. In this study, the brain, liver and muscle transcriptomes of channel catfish between fast-growing and slow-growing groups were analyzed using RNA-Seq. Totally, 63, 110 and 86 differentially expressed genes (DEGs) were from brain, liver and muscle tissues. DEGs are primarily involved in growth, development, metabolism and immunity, which are related to the growth regulation of channel catfish, such as growth hormone receptor b (ghrb), fibroblast growth factor receptor 4 (fgfr4), bone morphogenetic protein 1a (bmp1a), insulin-like growth factor 2a (igf2a), collagen, type I, alpha 1a (col1a1a), acyl-CoA synthetase long chain family member 2 (acsl2) and caveolin 1 (cav1). This study advances our knowledge of the genetic mechanisms accounting for differences in growth rate and offers crucial gene resources for future growth-related molecular breeding programs in channel catfish.

Role of chromosomal cohesion and separation in aneuploidy and tumorigenesis

Cell division is a crucial process, and one of its essential steps involves copying the genetic material, which is organized into structures called chromosomes. Before a cell can divide into two, it needs to ensure that each newly copied chromosome is paired tightly with its identical twin. This pairing is maintained by a protein complex known as cohesin, which is conserved in various organisms, from single-celled ones to humans. Cohesin essentially encircles the DNA, creating a ring-like structure to handcuff, to keep the newly synthesized sister chromosomes together in pairs. Therefore, chromosomal cohesion and separation are fundamental processes governing the attachment and segregation of sister chromatids during cell division. Metaphase-to-anaphase transition requires dissolution of cohesins by the enzyme Separase. The tight regulation of these processes is vital for safeguarding genomic stability. Dysregulation in chromosomal cohesion and separation resulting in aneuploidy, a condition characterized by an abnormal chromosome count in a cell, is strongly associated with cancer. Aneuploidy is a recurring hallmark in many cancer types, and abnormalities in chromosomal cohesion and separation have been identified as significant contributors to various cancers, such as acute myeloid leukemia, myelodysplastic syndrome, colorectal, bladder, and other solid cancers. Mutations within the cohesin complex have been associated with these cancers, as they interfere with chromosomal segregation, genome organization, and gene expression, promoting aneuploidy and contributing to the initiation of malignancy. In summary, chromosomal cohesion and separation processes play a pivotal role in preserving genomic stability, and aberrations in these mechanisms can lead to aneuploidy and cancer. Gaining a deeper understanding of the molecular intricacies of chromosomal cohesion and separation offers promising prospects for the development of innovative therapeutic approaches in the battle against cancer.

Identifying the driver miRNAs with somatic copy number alterations driving dysregulated ceRNA networks in cancers

BACKGROUND

MicroRNAs (miRNAs) play critical roles in cancer initiation and progression, which were critical components to maintain the dynamic balance of competing endogenous RNA (ceRNA) networks. Somatic copy number alterations (SCNAs) in the cancer genome could disturb the transcriptome level of miRNA to deregulate this balance. However, the driving effects of SCNAs of miRNAs were insufficiently understood.

METHODS

In this study, we proposed a method to dissect the functional roles of miRNAs under different copy number states and identify driver miRNAs by integrating miRNA SCNAs profile, miRNA-target relationships and expression profiles of miRNA, mRNA and lncRNA.

RESULTS

Applying our method to 813 TCGA breast cancer (BRCA) samples, we identified 29 driver miRNAs whose SCNAs significantly and concordantly regulated their own expression levels and further inversely dysregulated expression levels of their targets or disturbed the miRNA-target networks they directly involved. Based on miRNA-target networks, we further constructed dynamic ceRNA networks driven by driver SCNAs of miRNAs and identified three different patterns of SCNA interference in the miRNA-mediated dynamic ceRNA networks. Survival analysis of driver miRNAs showed that high-level amplifications of four driver miRNAs (including has-miR-30d-3p, has-mir-30b-5p, has-miR-30d-5p and has-miR-151a-3p) in 8q24 characterized a new BRCA subtype with poor prognosis and contributed to the dysfunction of cancer-associated hallmarks in a complementary way. The SCNAs of driver miRNAs across different cancer types contributed to the cancer development by dysregulating different components of the same cancer hallmarks, suggesting the cancer specificity of driver miRNA.

CONCLUSIONS

These results demonstrate the efficacy of our method in identifying driver miRNAs and elucidating their functional roles driven by endogenous SCNAs, which is useful for interpreting cancer genomes and pathogenic mechanisms.

ZNF703 mRNA-Targeting Antisense Oligonucleotide Blocks Cell Proliferation and Induces Apoptosis in Breast Cancer Cell Lines

The luminal B molecular subtype of breast cancers (BC) accounts for more than a third of BCs and is associated with aggressive clinical behavior and poor prognosis. The use of endocrine therapy in BC treatment has significantly contributed to the decrease in the number of deaths in recent years. However, most BC patients with prolonged exposure to estrogen receptor (ER) selective modulators such as tamoxifen develop resistance and become non-responsive over time. Recent studies have implicated overexpression of the ZNF703 gene in BC resistance to endocrine drugs, thereby highlighting ZNF703 inhibition as an attractive modality in BC treatment, especially luminal B BCs. However, there is no known inhibitor of ZNF703 due to its nuclear association and non-enzymatic activity. Here, we have developed an antisense oligonucleotide (ASO) against ZNF703 mRNA and shown that it downregulates ZNF703 protein expression. ZNF703 inhibition decreased cell proliferation and induced apoptosis. Combined with cisplatin, the anti-cancer effects of ZNF703-ASO9 were improved. Moreover, our work shows that ASO technology may be used to increase the number of targetable cancer genes.

Identifying M1-like macrophage related genes for prognosis prediction in lung adenocarcinoma based on a gene co-expression network

Macrophages are one of the most important players in the tumor microenvironment. But the contribution of macrophages to lung adenocarcinoma (LUAD) is still controversial. The current study aimed to display an immune landscape to clarify the function of macrophages and detect prognostic hub genes in LUAD. The transcriptome data were adopted to screen differently expressed genes (DEGs) in The Cancer Genome Atlas database (TCGA). The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to reveal the immune landscape. Weighted gene co-expression network analysis (WGCNA) analysis was performed to identify the hub module associated with macrophages. Function Enrichment analysis was conducted on hub module genes. Moreover, univariate and multivariate Cox regression analyses were performed to identify prognostic hub genes. Kaplan-Meier (KM) and Time-dependent receiver operating characteristic (ROC) curves were plotted to assess the prognostic capacity of the four prognostic hub genes. The GES1196959 dataset from the Gene Expression Omnibus (GEO) database was downloaded to verify the differential expression of the 4 prognostic hub genes.

Association of the Timeless Gene with Prognosis and Clinical Characteristics of Human Lung Cancer

(1) Background: As the most common malignant tumor type worldwide, it is necessary to identify novel potential prognostic biomarkers to improve the poor prognosis of lung cancer. The Timeless gene, a circadian rhythm-related gene, is associated with several types of cancer. However, studies analyzing the clinical significance of the Timeless gene in patients with lung cancer are currently limited. (2) Methods: In the present study, the expression levels and prognostic potential of the Timeless gene and its co-expressed genes in different subtypes of lung cancer were explored using multiple bioinformatics approaches. The correlations between the Timeless gene and its co-expressed genes were validated using A549 and NCI-H226 cells by transfecting them with expression vectors and analyses using Western blot and reverse transcription-quantitative PCR. (3) Results: The Oncomine and GEPIA database analyses indicated that the expression of the Timeless gene was significantly higher in lung cancer as compared to that in the normal tissue. Using the UALCAN database, significant differences in Timeless gene expression were determined among different stages of lung cancer and between genders. A Kaplan-Meier plotter analysis indicated that high expression of the Timeless gene was associated with poor overall survival (OS) and progression-free survival (PFS) of patients with lung cancer. In the cBioPortal and GEPIA database analyses, extra spindle pole bodies like 1 (ESPL1) was the top correlated gene of Timeless in patients with lung cancer. Similar to the Timeless gene, high expression of the ESPL1 gene was also associated with poor OS and PFS. Of note, overexpression of the Timeless gene increased the expression level of ESPL1 at both the mRNA and protein levels. (4) Conclusion: The present study explored the clinical significance of the Timeless gene and its correlated gene ESPL1 in patients with lung cancer, thereby providing a potential therapeutic target for lung cancer.

Chromatin Separation Regulators Predict the Prognosis and Immune Microenvironment Estimation in Lung Adenocarcinoma

Background: Abnormal chromosome segregation is identified to be a common hallmark of cancer. However, the specific predictive value of it in lung adenocarcinoma (LUAD) is unclear.

Method: The RNA sequencing and the clinical data of LUAD were acquired from The Cancer Genome Atlas (TACG) database, and the prognosis-related genes were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were carried out for functional enrichment analysis of the prognosis genes. The independent prognosis signature was determined to construct the nomogram Cox model. Unsupervised clustering analysis was performed to identify the distinguishing clusters in LUAD-samples based on the expression of chromosome segregation regulators (CSRs). The differentially expressed genes (DEGs) and the enriched biological processes and pathways between different clusters were identified. The immune environment estimation, including immune cell infiltration, HLA family genes, immune checkpoint genes, and tumor immune dysfunction and exclusion (TIDE), was assessed between the clusters. The potential small-molecular chemotherapeutics for the individual treatments were predicted via the connectivity map (CMap) database.

Results: A total of 2,416 genes were determined as the prognosis-related genes in LUAD. Chromosome segregation is found to be the main bioprocess enriched by the prognostic genes. A total of 48 CSRs were found to be differentially expressed in LUAD samples and were correlated with the poor outcome in LUAD. Nine CSRs were identified as the independent prognostic signatures to construct the nomogram Cox model. The LUAD-samples were divided into two distinct clusters according to the expression of the 48 CSRs. Cell cycle and chromosome segregation regulated genes were enriched in cluster 1, while metabolism regulated genes were enriched in cluster 2. Patients in cluster 2 had a higher score of immune, stroma, and HLA family components, while those in cluster 1 had higher scores of TIDES and immune checkpoint genes. According to the hub genes highly expressed in cluster 1, 74 small-molecular chemotherapeutics were predicted to be effective for the patients at high risk.

Conclusion: Our results indicate that the CSRs were correlated with the poor prognosis and the possible immunotherapy resistance in LUAD.

Extra Spindle Pole Bodies-Like 1 Serves as a Prognostic Biomarker and Promotes Lung Adenocarcinoma Metastasis

Extra spindle pole bodies-like 1 (ESPL1), a cysteine endopeptidase, plays a vital role in chromosome inheritance. However, the association of ESPL1 with prognosis and immune infiltration in lung adenocarcinoma (LUAD) has not yet been explored. Here, we analyzed the expression level, prognostic values, diagnostic value, and immune infiltration level in LUAD using various databases. Immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR) assays were used to detect the expression of ESPL1 in LUAD tissues and cell lines. In this study, we found that ESPL1 was upregulated in LUAD and a higher expression of ESPL1 was correlated with unfavorable prognosis in LUAD. Meanwhile, Cox hazard regression analysis results suggested that ESPL1 may be an independent prognostic factor for LUAD. Moreover, we demonstrated that ESPL1 expression was significantly correlated with immune infiltration of Th2 and dendritic cells in LUAD. We also confirmed that DNA copy number amplification and DNA hypo-methylation were positively correlated with ESPL1 expression in LUAD. Additionally, DNA copy number amplification was significantly associated with adverse clinical outcomes in LUAD. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) confirmed that ESPL1 was mainly involved in the DNA replication and glycolysis signaling pathway. Finally, we revealed that ESPL1 was highly expressed in LUAD tissues and cell lines. Knockdown of ESPL1 significantly inhibited cell migration and the invasion abilities of LUAD. Our study comprehensively confirmed that ESPL1 expression may serve as a novel prognostic biomarker for both the clinical outcome and immune cell infiltration in LUAD.

Let-7c-5p Restrains Cell Growth and Induces Apoptosis of Lung Adenocarcinoma Cells via Targeting ESPL1

Lung adenocarcinoma (LUAD) is a predominant malignancy, and its high mortality prompts us to incessantly probe the relevant targeted treatment. This work intended to study the molecular mechanism of ESPL1 in LUAD. Bioinformatics analysis was performed for pan-cancer and prognosis analysis as well as target gene prediction. Expression of ESPL1 mRNA and let-7c-5p was determined via qRT-PCR, and western blot was employed to detect protein level of ESPL1. Dual-luciferase reporter gene method verified the interaction between ESPL1 and let-7c-5p. Thereafter, CCK-8, wound healing, Transwell, and flow cytometry assays were utilized to investigate proliferation, migration, and apoptosis of LUAD cells. The results revealed that ESPL1 was upregulated in LUAD, which was associated with poor prognosis. Overexpressed ESPL1 promoted LUAD cells to invade, proliferate, and migrate. Furthermore, ESPL1 was a target gene of let-7c-5p. Let-7c-5p was downregulated in LUAD cells, and played a suppressive role in LUAD malignant development, while reversed by ESPL1. Taken together, it was posited that let-7c-5p/ESPL1 may be underlying therapeutic targets of LUAD.

MONTI: A Multi-Omics Non-negative Tensor Decomposition Framework for Gene-Level Integrative Analysis

Multi-omics data is frequently measured to enrich the comprehension of biological mechanisms underlying certain phenotypes. However, due to the complex relations and high dimension of multi-omics data, it is difficult to associate omics features to certain biological traits of interest. For example, the clinically valuable breast cancer subtypes are well-defined at the molecular level, but are poorly classified using gene expression data. Here, we propose a multi-omics analysis method called MONTI (Multi-Omics Non-negative Tensor decomposition for Integrative analysis), which goal is to select multi-omics features that are able to represent trait specific characteristics. Here, we demonstrate the strength of multi-omics integrated analysis in terms of cancer subtyping. The multi-omics data are first integrated in a biologically meaningful manner to form a three dimensional tensor, which is then decomposed using a non-negative tensor decomposition method. From the result, MONTI selects highly informative subtype specific multi-omics features. MONTI was applied to three case studies of 597 breast cancer, 314 colon cancer, and 305 stomach cancer cohorts. For all the case studies, we found that the subtype classification accuracy significantly improved when utilizing all available multi-omics data. MONTI was able to detect subtype specific gene sets that showed to be strongly regulated by certain omics, from which correlation between omics types could be inferred. Furthermore, various clinical attributes of nine cancer types were analyzed using MONTI, which showed that some clinical attributes could be well explained using multi-omics data. We demonstrated that integrating multi-omics data in a gene centric manner improves detecting cancer subtype specific features and other clinical features, which may be used to further understand the molecular characteristics of interest. The software and data used in this study are available at: https://github.com/inukj/MONTI.

ESPL1 Is a Novel Prognostic Biomarker Associated With the Malignant Features of Glioma

Research has confirmed that extra spindle pole bodies-like 1 (ESPL1), an etiological factor, promotes the malignant progression of cancers. However, the relationship between ESPL1 and glioma has not yet been demonstrated. The purpose of this study was to reveal the potential mechanisms of ESPL1-mediated malignant glioma progression. Gene expression data and detailed clinical information of glioma cases were obtained from multiple public databases. Subsequently, a series of bioinformatics analyses were used to elucidate the effects of ESPL1 on glioma. The results demonstrated that the mRNA and protein levels of ESPL1 in glioma were higher than those in normal brain tissues. In addition, ESPL1 expression was considerably associated with the clinical and pathological features of gliomas, such as World Health Organization grade, histology, and 1p19q co-deletion status. Importantly, ESPL1 reduced the overall survival (OS) of glioma patients and had prognostic value for gliomas. Gene set enrichment analysis (GSEA) indirectly revealed that ESPL1 regulates the activation of cancer-related pathways, such as the cell cycle and base excision repair pathways. In addition, we used the Connectivity Map (CMap) database to screen three molecular drugs that inhibit ESPL1: thioguanosine, antimycin A, and zidovudine. Finally, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression levels of ESPL1 in glioma cell lines. This study plays an important role in revealing the etiology of glioma by revealing the function of ESPL1, providing a potential molecular marker for the diagnosis and treatment of glioma, especially low-grade glioma.

Claspin Overexpression Promotes Tumor Progression and Predicts Poor Clinical Outcome in Prostate Cancer

Background: Claspin (CLSPN) expression is acknowledged as a poor clinical prognostic factor in various tumors. However, the clinical characteristics and biological functions of CLSPN in prostate cancer (PCa) are still to be clarified. The aim of our study was to evaluate the association of CLSPN expression during PCa progression and its potential role in prognosis. Methods: We analyzed mRNA expression of the CLSPN gene with various clinicopathological features using the Cancer Genome Atlas and GSE21032 dataset. Immunohistochemical assays were used to detect the protein expression levels of CLSPN in human PCa tissue microarrays. Furthermore, we characterized the role of CLSPN in PCa progression through in vitro experiments using a CLSPN knockout. Results: Immunohistochemistry and public datasets revealed that CLSPN expression was increased in PCa with: a high Gleason score; advanced pathological stage; and positive surgical margins. In addition, upregulation of CLSPN was correlated with shorter biochemical recurrence (BCR)-free survival and overall survival. After we knocked-out CLSPN in DU145 and LNCaP cells, the in vitro phenotypic results showed that the ability of the knockouts to proliferate, migrate, and invade was attenuated; but that apoptosis was promoted. Conclusions: Our data support an oncogenic role for CLSPN in PCa progression. Moreover, increased CLSPN expression was identified as an independent factor in predicting bCR-free survival and disease-free survival in PCa patients.

Identification and analysis of genes associated with epithelial ovarian cancer by integrated bioinformatics methods

Background

Though considerable efforts have been made to improve the treatment of epithelial ovarian cancer (EOC), the prognosis of patients has remained poor. Identifying differentially expressed genes (DEGs) involved in EOC progression and exploiting them as novel biomarkers or therapeutic targets is of great value.

Methods

Overlapping DEGs were screened out from three independent gene expression omnibus (GEO) datasets and were subjected to Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses. The protein-protein interactions (PPI) network of DEGs was constructed based on the STRING database. The expression of hub genes was validated in GEPIA and GEO. The relationship of hub genes expression with tumor stage and overall survival and progression-free survival of EOC patients was investigated using the cancer genome atlas data.

Results

A total of 306 DEGs were identified, including 265 up-regulated and 41 down-regulated. Through PPI network analysis, the top 20 genes were screened out, among which 4 hub genes, which were not researched in depth so far, were selected after literature retrieval, including CDC45, CDCA5, KIF4A, ESPL1. The four genes were up-regulated in EOC tissues compared with normal tissues, but their expression decreased gradually with the continuous progression of EOC. Survival curves illustrated that patients with a lower level of CDCA5 and ESPL1 had better overall survival and progression-free survival statistically.

Conclusion

Two hub genes, CDCA5 and ESPL1, identified as probably playing tumor-promotive roles, have great potential to be utilized as novel therapeutic targets for EOC treatment.

Serum ESPL1 Can Be Used as a Biomarker for Patients With Hepatitis B Virus-Related Liver Cancer: A Chinese Case-Control Study

AIMS

To investigate the feasibility of serum extra spindle pole bodies-like 1 (ESPL1) used as a biomarker for patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).

METHODS

131 chronic HBV-infection patients were recruited and divided into HBV S gene integration, non-HBV S gene integration, chronic hepatitis B (CHB), HBV-related liver cirrhosis (LC) and HBV-related HCC group, 24 non-HBV-related HCC patients were selected as HCC control group, 30 people without HBV-infection as healthy control group. Serum ESPL1 were detected and compared.

RESULTS

ESPL1 level of integration group was significantly higher than that of non-integration group (346.7 vs 199.6 ng/ml, P = 0.000) and healthy control group (346.7 vs 41.3 ng/ml, P = 0.000). ESPL1 level of non-integration group was significantly higher than that of healthy control group (199.6 vs 41.3 ng/ml, P = 0.000); ESPL1 levels in chronic HBV-infection related groups were increased in turn according to CHB group (95.8 ng/ml), HBV-related LC group (268.2 ng/ml), HBV-related HCC group (279.9 ng/ml) and integration group (346.7 ng/ml). Except that there was no significant difference in ESPL1 levels between HBV-related LC and HCC group (P = 0.662), pairwise comparisons between other groups showed significant differences (P < 0.05). ESPL1 level of HBV-related HCC group was significantly higher than that of non-HBV-related HCC group (279.9 vs 46.6 ng/ml, P = 0.000), there was no noticeable difference between non-HBV-related HCC and healthy control group (46.6 vs 41.3 ng/ml, P = 0.848). ESPL1 level of HBV-related HCC group after resection was significantly lower than that of before resection (178.4 vs 260.8 ng/ml, P = 0.000).

CONCLUSIONS

Chronic HBV-infection patients with high ESPL1 level may indicate HBV S gene integration and is a high-risk population for HBV-related HCC. Serum ESPL1 can be used as a biomarker for screening HBV-related HCC high-risk population and monitoring recurrence.

TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer

Objective

Endometrial cancer (EC) is one of the most common malignant gynaecological tumours worldwide. This study was aimed at identifying EC prognostic genes and investigating the molecular mechanisms of these genes in EC.

Methods

Two mRNA datasets of EC were downloaded from the Gene Expression Omnibus (GEO). The GEO2R tool and Draw Venn Diagram were used to identify differentially expressed genes (DEGs) between normal endometrial tissues and EC tissues. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Next, the protein-protein interactions (PPIs) of these DEGs were determined by the Search Tool for the Retrieval of Interacting Genes (STRING) tool and Cytoscape with Molecular Complex Detection (MCODE). Furthermore, Kaplan-Meier survival analysis was performed by UALCAN to verify genes associated with significantly poor prognosis. Next, Gene Expression Profiling Interactive Analysis (GEPIA) was used to verify the expression levels of these selected genes. Additionally, a reanalysis of the KEGG pathways was performed to understand the potential biological functions of selected genes. Finally, the associations between these genes and clinical features were analysed based on TCGA cancer genomic datasets for EC.

Results

In EC tissues, compared with normal endometrial tissues, 147 of 249 DEGs were upregulated and 102 were downregulated. A total of 64 upregulated genes were assembled into a PPI network. Next, 14 genes were found to be both associated with significantly poor prognosis and highly expressed in EC tissues. Reanalysis of the KEGG pathways found that three of these genes were enriched in the cell cycle pathway. TTK, CDC25A, and ESPL1 showed higher expression in cancers with late stage and higher tumour grade.

Conclusion

In summary, through integrated bioinformatics approaches, we found three significant prognostic genes of EC, which might be potential therapeutic targets for EC patients.

Tumour profiling tests to guide adjuvant chemotherapy decisions in early breast cancer: a systematic review and economic analysis

BACKGROUND

Breast cancer and its treatment can have an impact on health-related quality of life and survival. Tumour profiling tests aim to identify whether or not women need chemotherapy owing to their risk of relapse.

OBJECTIVES

To conduct a systematic review of the effectiveness and cost-effectiveness of the tumour profiling tests oncotype DX^® (Genomic Health, Inc., Redwood City, CA, USA), MammaPrint^® (Agendia, Inc., Amsterdam, the Netherlands), Prosigna^® (NanoString Technologies, Inc., Seattle, WA, USA), EndoPredict^® (Myriad Genetics Ltd, London, UK) and immunohistochemistry 4 (IHC4). To develop a health economic model to assess the cost-effectiveness of these tests compared with clinical tools to guide the use of adjuvant chemotherapy in early-stage breast cancer from the perspective of the NHS and Personal Social Services.

DESIGN

A systematic review and health economic analysis were conducted.

REVIEW METHODS

The systematic review was partially an update of a 2013 review. Nine databases were searched in February 2017. The review included studies assessing clinical effectiveness in people with oestrogen receptor-positive, human epidermal growth factor receptor 2-negative, stage I or II cancer with zero to three positive lymph nodes. The economic analysis included a review of existing analyses and the development of a de novo model.

RESULTS

A total of 153 studies were identified. Only one completed randomised controlled trial (RCT) using a tumour profiling test in clinical practice was identified: Microarray In Node-negative Disease may Avoid ChemoTherapy (MINDACT) for MammaPrint. Other studies suggest that all the tests can provide information on the risk of relapse; however, results were more varied in lymph node-positive (LN+) patients than in lymph node-negative (LN0) patients. There is limited and varying evidence that oncotype DX and MammaPrint can predict benefit from chemotherapy. The net change in the percentage of patients with a chemotherapy recommendation or decision pre/post test ranged from an increase of 1% to a decrease of 23% among UK studies and a decrease of 0% to 64% across European studies. The health economic analysis suggests that the incremental cost-effectiveness ratios for the tests versus current practice are broadly favourable for the following scenarios: (1) oncotype DX, for the LN0 subgroup with a Nottingham Prognostic Index (NPI) of > 3.4 and the one to three positive lymph nodes (LN1-3) subgroup (if a predictive benefit is assumed); (2) IHC4 plus clinical factors (IHC4+C), for all patient subgroups; (3) Prosigna, for the LN0 subgroup with a NPI of > 3.4 and the LN1-3 subgroup; (4) EndoPredict Clinical, for the LN1-3 subgroup only; and (5) MammaPrint, for no subgroups.

LIMITATIONS

There was only one completed RCT using a tumour profiling test in clinical practice. Except for oncotype DX in the LN0 group with a NPI score of > 3.4 (clinical intermediate risk), evidence surrounding pre- and post-test chemotherapy probabilities is subject to considerable uncertainty. There is uncertainty regarding whether or not oncotype DX and MammaPrint are predictive of chemotherapy benefit. The MammaPrint analysis uses a different data source to the other four tests. The Translational substudy of the Arimidex, Tamoxifen, Alone or in Combination (TransATAC) study (used in the economic modelling) has a number of limitations.

CONCLUSIONS

The review suggests that all the tests can provide prognostic information on the risk of relapse; results were more varied in LN+ patients than in LN0 patients. There is limited and varying evidence that oncotype DX and MammaPrint are predictive of chemotherapy benefit. Health economic analyses indicate that some tests may have a favourable cost-effectiveness profile for certain patient subgroups; all estimates are subject to uncertainty. More evidence is needed on the prediction of chemotherapy benefit, long-term impacts and changes in UK pre-/post-chemotherapy decisions.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42017059561.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

The New Paradigm of Network Medicine to Analyze Breast Cancer Phenotypes

Breast cancer (BC) is a heterogeneous and complex disease as witnessed by the existence of different subtypes and clinical characteristics that poses significant challenges in disease management. The complexity of this tumor may rely on the highly interconnected nature of the various biological processes as stated by the new paradigm of Network Medicine. We explored The Cancer Genome Atlas (TCGA)-BRCA data set, by applying the network-based algorithm named SWItch Miner, and mapping the findings on the human interactome to capture the molecular interconnections associated with the disease modules. To characterize BC phenotypes, we constructed protein-protein interaction modules based on "hub genes", called switch genes, both common and specific to the four tumor subtypes. Transcriptomic profiles of patients were stratified according to both clinical (immunohistochemistry) and genetic (PAM50) classifications. 266 and 372 switch genes were identified from immunohistochemistry and PAM50 classifications, respectively. Moreover, the identified switch genes were functionally characterized to select an interconnected pathway of disease genes. By intersecting the common switch genes of the two classifications, we selected a unique signature of 28 disease genes that were BC subtype-independent and classification subtype-independent. Data were validated both in vitro (10 BC cell lines) and ex vivo (66 BC tissues) experiments. Results showed that four of these hub proteins (AURKA, CDC45, ESPL1, and RAD54L) were over-expressed in all tumor subtypes. Moreover, the inhibition of one of the identified switch genes (AURKA) similarly affected all BC subtypes. In conclusion, using a network-based approach, we identified a common BC disease module which might reflect its pathological signature, suggesting a new vision to face with the disease heterogeneity.

Identification and genomic analysis of pedigrees with exceptional longevity identifies candidate rare variants

BACKGROUND

Longevity as a phenotype entails living longer than average and typically includes living without chronic age-related diseases. Recently, several common genetic components to longevity have been identified. This study aims to identify additional genetic variants associated with longevity using unique and powerful analyses of pedigrees with a statistical excess of healthy elderly individuals identified in the Utah Population Database (UPDB).

METHODS

From an existing biorepository of Utah pedigrees, six independent cousin pairs were selected from four extended pedigrees that exhibited an excess of healthy elderly individuals; whole exome sequencing (WES) was performed on two elderly individuals from each pedigree who were either first cousins or first cousins once removed. Rare (<.01 population frequency) variants shared by at least one elderly cousin pair in a region likely to be identical by descent were identified as candidates. Ingenuity Variant Analysis was used to prioritize putative causal variants based on quality control, frequency, and gain or loss of function. The variant frequency was compared in healthy cohorts and in an Alzheimer's disease cohort. Remaining variants were filtered based on their presence in genes reported to have an effect on the aging process, aging of cells, or the longevity process. Validation of these candidate variants included tests of segregation on other elderly relatives.

RESULTS

Fifteen rare candidate genetic variants spanning 17 genes shared within cousins were identified as having passed prioritization criteria. Of those variants, six were present in genes that are known or predicted to affect the aging process: rs78408340 (PAM), rs112892337 (ZFAT), rs61737629 (ESPL1), rs141903485 (CEBPE), rs144369314 (UTP4), and rs61753103 (NUP88 and RABEP1). ESPL1 rs61737629 and CEBPE rs141903485 show additional evidence of segregation with longevity in expanded pedigree analyses (p-values = .001 and .0001, respectively).

DISCUSSION

This unique pedigree analysis efficiently identified several novel rare candidate variants that may affect the aging process and added support to seven genes that likely contribute to longevity. Further analyses showed evidence for segregation for two rare variants, ESPL1 rs61737629 and CEBPE rs141903485, in the original longevity pedigrees in which they were initially observed. These candidate genes and variants warrant further investigation.

Identification of aberrantly methylated differentially expressed genes and associated pathways in endometrial cancer using integrated bioinformatic analysis

Endometrial cancer (EC) is a fatal female reproductive tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. In this study, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17025 and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40032 were obtained from Gene Expression Omnibus (GEO). “limma” package and Venn diagram tool were used to identify hub genes. FunRich was used for functional analysis. Retrieval of Interacting Genes Database (STRING) was used to analyze protein‐protein interaction (PPI) complex. Cancer Genome Atlas (TCGA), GEPIA, immunohistochemistry staining, and ROC curve analysis were carried out for validation. Univariate and multivariate regression analyses were performed to predict the risk score. Compound muscle action potential (CMap) was used to find potential drugs. GSEA was also done. We retrieved seven oncogenes which were upregulated and hypomethylated and 12 tumor suppressor genes (TSGs) which were downregulated and hypermethylated. The upregulated and hypomethylated genes were strikingly enriched in term “immune response” while the downregulated and hypermethylated genes were mainly focused on term “aromatic compound catabolic process.” TCGA and GEPIA were used to screen out EDNRB, CDO1, NDN, PLCD1, ROR2, ESPL1, PRAME, and PTTG1. Among them, ESPL1 and ROR2 were identified by Cox regression analysis and were used to construct prognostic risk model. The result showed that ESPL1 was a negative independent prognostic factor. Cmap identified aminoglutethimide, luteolin, sulfadimethoxine, and maprotiline had correlation with EC. GSEA results showed that “hedgehog signaling pathway” was enriched. This research inferred potential aberrantly methylated DEGs and dysregulated pathways may participate in EC development and firstly reported eight hub genes, including EDNRB, CDO1, NDN, PLCD1, ROR2, ESPL1, PRAME, and PTTG1 that could be used to predict EC prognosis. Aminoglutethimide and luteolin may be used to fight against EC.

Comprehensive analysis of prognosis-related methylated sites in breast carcinoma

Background

Breast carcinoma has become a nonnegligible public health problem in China with its increasing incidence and mortality in woman. As a early event regulating tumorigenesis and development, DNA methylation became one of the focuses of current carcinoma researches on potential diagnostic and therapeutic targets.

Methods

In this study, we comprehensively analyzed the gene expression data and DNA methylation data of breast carcinoma and adjacent normal tissues samples in the Gene Expression Omnibus database. Influences of tumor stage, adjuvant therapy, hormone therapy, and chemotherapy on CpG methylation level were explored by linear regression analysis. Correlations between methylation and gene expression levels were determined by spearman rank correlation analysis. Log‐rank test was applied for determining significance of associations between CpG sites methylation level and breast cancer patients' Kaplan–Meier survival.

Results

A total of 229 CpG sites were found to be significantly associated with tumor stage or treatment, and eight of which were potential markers that affect the survival of breast carcinoma and negatively correlated with their genes' expression levels.

Conclusions

We reported eight CpG sites as potential breast cancer prognosis signatures through comprehensively analyzed gene expression and DNA methylation datasets, and excluding influences of tumor stage and treatment. This should be helpful for breast cancer early diagnosis and treatment.

Bioinformatics Analysis Identified Key Molecular Changes in Bladder Cancer Development and Recurrence

Background and Objectives: Bladder cancer (BC) is a complex tumor associated with high recurrence and mortality. To discover key molecular changes in BC, we analyzed next-generation sequencing data of BC and surrounding tissue samples from clinical specimens. Methods. Gene expression profiling datasets of bladder cancer were analyzed online. The Database for Annotation, Visualization, and Integrated Discovery (DAVID, https://david.ncifcrf.gov/) was used to perform Gene Ontology (GO) functional and KEGG pathway enrichment analyses. Molecular Complex Detection (MCODE) in Cytoscape software (Cytoscape_v3.6.1) was applied to identify hub genes. Protein expression and survival data were downloaded from OncoLnc (http://www.oncolnc.org/). Gene expression data were obtained from the ONCOMINE website (https://www.oncomine.org/). Results. We identified 4211 differentially expressed genes (DEGs) by analysis of surrounding tissue vs. cancer tissue (SC analysis) and 410 DEGs by analysis of cancer tissue vs. recurrent tissue cluster (CR analysis). GO function analysis revealed enrichment of DEGs in genes related to the cytoplasm and nucleoplasm for both clusters, and KEGG pathway analysis showed enrichment of DEGs in the PI3K-Akt signaling pathway. We defined the 20 genes with the highest degree of connectivity as the hub genes. Cox regression revealed CCNB1, ESPL1, CENPM, BLM, and ASPM were related to overall survival. The expression levels of CCNB1, ESPL1, CENPM, BLM, and ASPM were 4.795-, 5.028-, 8.691-, 2.083-, and 3.725-fold higher in BC than the levels in normal tissues, respectively. Conclusions. The results suggested that the functions of CCNB1, ESPL1, CENPM, BLM, and ASPM may contribute to BC development and the functions of CCNB1, ESPL1, CENPM, and BLM may also contribute to BC recurrence.

Clinical Significance And Integrative Analysis Of Kinesin Family Member 18B In Lung Adenocarcinoma

Background

Kinesin family member 18B (KIF18B) is a member of the kinesin-8 superfamily, and functions as an oncogene in human cancers. However, its expression profile and role in lung adenocarcinoma (LUAD) remain unclear.

Materials and methods

We examined the expression profile of KIF18B using quantitative real-time reverse transcription polymerase chain reaction and immunohistochemistry in fresh clinical samples. Using data downloaded from the Cancer Genome Atlas database and Gene Expression Omnibus, we explored the clinical significance of KIF18B, potential mechanisms of its dysregulation and its underlying biological function in LUAD.

Results

KIF18B was significantly over-expressed in LUAD tissues relative to normal tissues. High KIF18B expression was associated with smoking history, positive nodal invasion, advanced clinical stage, death status and poorer prognosis. Cox regression analyses revealed that KIF18B overexpression was an independent prognostic biomarker for poor overall survival (OS) and recurrence-free survival in LUAD. In addition, KIF18B mutation was observed in 2.2% of LUAD cases. DNA copy number variation was correlated with upregulated expression of KIF18B in LUAD tissues and cell lines. The methylation level of some KIF18B DNA CpG sites was negatively associated with its mRNA expression. KIF18B was predictively targeted by miR-125a-5p, which was downregulated in LUAD tissues, inversely correlated with KIF18B mRNA expression and significantly associated with poor OS. Furthermore, gene set enrichment analysis revealed that genes positively co-expressed with KIF18B were mainly enriched in cell cycle signaling pathways.

Conclusion

Our results indicate that KIF18B is a promising prognostic biomarker for LUAD. DNA amplification, hypomethylation as well as miR-125a-5p downregulation may be involved in the mechanism of KIF18B dysregulation in LUAD. KIF18B might function as a novel oncogene through cell cycle regulation pathways in LUAD.

Exploring the Molecular Mechanism of the Drug-Treated Breast Cancer Based on Gene Expression Microarray

: Breast cancer (BRCA) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers expressed during estradiol and tamoxifen treatment of BRCA. The microarray dataset of E-MTAB-4975 from Array Express database was downloaded, and the differential expressed genes (DEGs) between estradiol-treated BRCA sample and tamoxifen-treated BRCA sample were identified by limma package. The pathway and gene ontology (GO) enrichment analysis, construction of protein-protein interaction (PPI) network, module analysis, construction of target genes-miRNA interaction network and target genes-transcription factor (TF) interaction network were performed using bioinformatics tools. The expression, prognostic values, and mutation of hub genes were validated by SurvExpress database, cBioPortal, and human protein atlas (HPA) database. A total of 856 genes (421 up-regulated genes and 435 down-regulated genes) were identified in T47D (overexpressing Split Ends (SPEN) + estradiol) samples compared to T47D (overexpressing Split Ends (SPEN) + tamoxifen) samples. Pathway and GO enrichment analysis revealed that the DEGs were mainly enriched in response to lysine degradation II (pipecolate pathway), cholesterol biosynthesis pathway, cell cycle pathway, and response to cytokine pathway. DEGs (MCM2, TCF4, OLR1, HSPA5, MAP1LC3B, SQSTM1, NEU1, HIST1H1B, RAD51, RFC3, MCM10, ISG15, TNFRSF10B, GBP2, IGFBP5, SOD2, DHF and MT1H) , which were significantly up- and down-regulated in estradiol and tamoxifen-treated BRCA samples, were selected as hub genes according to the results of protein-protein interaction (PPI) network, module analysis, target genes-miRNA interaction network and target genes-TF interaction network analysis. The SurvExpress database, cBioPortal, and Human Protein Atlas (HPA) database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. A comprehensive bioinformatics analysis was performed, and potential therapeutic applications of estradiol and tamoxifen were predicted in BRCA samples. The data may unravel the future molecular mechanisms of BRCA.

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

Background and Objective

Endometrial cancer (EC) is a common gynecological malignancy worldwide. Despite advances in the development of strategies for treating EC, prognosis of the disease remains unsatisfactory, especially for advanced EC. The aim of this study was to identify novel genes that can be used as potential biomarkers for identifying the prognosis of EC and to construct a novel risk stratification using these genes.

Methods and Results

An mRNA sequencing dataset, corresponding survival data and expression profiling of an array of EC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus, respectively. Common differentially expressed genes (DEGs) were identified based on sequencing and expression as given in the profiling dataset. Pathway enrichment analysis of the DEGs was performed using the Database for Annotation, Visualization, and Integrated Discovery. The protein-protein interaction network was established using the string online database in order to identify hub genes. Univariate and multivariable Cox regression analyses were used to screen prognostic DEGs and to construct a prognostic signature. Survival analysis based on the prognostic signature was performed on TCGA EC dataset. A total of 255 common DEGs were found and 11 hub genes (TOP2A, CDK1, CCNB1, CCNB2, AURKA, PCNA, CCNA2, BIRC5, NDC80, CDC20, and BUB1BA) that may be closely related to the pathogenesis of EC were identified. A panel of 7 DEG signatures consisting of PHLDA2, GGH, ESPL1, FAM184A, KIAA1644, ESPL1, and TRPM4 were constructed. The signature performed well for prognosis prediction (p < 0.001) and time-dependent receiver-operating characteristic (ROC) analysis displayed an area under the curve (AUC) of 0.797, 0.734, 0.729, and 0.647 for 1, 3, 5, and 10-year overall survival (OS) prediction, respectively.

Conclusion

This study identified potential genes that may be involved in the pathophysiology of EC and constructed a novel gene expression signature for EC risk stratification and prognosis prediction.

SHON expression predicts response and relapse risk of breast cancer patients after anthracycline-based combination chemotherapy or tamoxifen treatment

Background

SHON nuclear expression (SHON-Nuc⁺) was previously reported to predict clinical outcomes to tamoxifen therapy in ERα⁺ breast cancer (BC). Herein we determined if SHON expression detected by specific monoclonal antibodies could provide a more accurate prediction and serve as a biomarker for anthracycline-based combination chemotherapy (ACT).

Methods

SHON expression was determined by immunohistochemistry in the Nottingham early-stage-BC cohort (n = 1,650) who, if eligible, received adjuvant tamoxifen; the Nottingham ERα⁻ early-stage-BC (n = 697) patients who received adjuvant ACT; and the Nottingham locally advanced-BC cohort who received pre-operative ACT with/without taxanes (Neo-ACT, n = 120) and if eligible, 5-year adjuvant tamoxifen treatment. Prognostic significance of SHON and its relationship with the clinical outcome of treatments were analysed.

Results

As previously reported, SHON-Nuc⁺ in high risk/ERα⁺ patients was significantly associated with a 48% death risk reduction after exclusive adjuvant tamoxifen treatment compared with SHON-Nuc⁻ [HR (95% CI) = 0.52 (0.34–0.78), p = 0.002]. Meanwhile, in ERα⁻ patients treated with adjuvant ACT, SHON cytoplasmic expression (SHON-Cyto⁺) was significantly associated with a 50% death risk reduction compared with SHON-Cyto⁻ [HR (95% CI) = 0.50 (0.34–0.73), p = 0.0003]. Moreover, in patients received Neo-ACT, SHON-Nuc⁻ or SHON-Cyto⁺ was associated with an increased pathological complete response (pCR) compared with SHON-Nuc⁺ [21 vs 4%; OR (95% CI) = 5.88 (1.28–27.03), p = 0.012], or SHON-Cyto⁻ [20.5 vs. 4.5%; OR (95% CI) = 5.43 (1.18–25.03), p = 0.017], respectively. After receiving Neo-ACT, patients with SHON-Nuc⁺ had a significantly lower distant relapse risk compared to those with SHON-Nuc⁻ [HR (95% CI) = 0.41 (0.19–0.87), p = 0.038], whereas SHON-Cyto⁺ patients had a significantly higher distant relapse risk compared to SHON-Cyto⁻ patients [HR (95% CI) = 4.63 (1.05–20.39), p = 0.043]. Furthermore, multivariate Cox regression analyses revealed that SHON-Cyto⁺ was independently associated with a higher risk of distant relapse after Neo-ACT and 5-year tamoxifen treatment [HR (95% CI) = 5.08 (1.13–44.52), p = 0.037]. The interaction term between ERα status and SHON-Nuc⁺ (p = 0.005), and between SHON-Nuc⁺ and tamoxifen therapy (p = 0.007), were both statistically significant.

Conclusion

SHON-Nuce⁺ in tumours predicts response to tamoxifen in ERα⁺ BC while SHON-Cyto⁺ predicts response to ACT.

Local activation of mammalian separase in interphase promotes double-strand break repair and prevents oncogenic transformation

Separase halves eukaryotic chromosomes in M-phase by cleaving cohesin complexes holding sister chromatids together. Whether this essential protease functions also in interphase and/or impacts carcinogenesis remains largely unknown. Here, we show that mammalian separase is recruited to DNA double-strand breaks (DSBs) where it is activated to locally cleave cohesin and facilitate homology-directed repair (HDR). Inactivating phosphorylation of its NES, arginine methylation of its RG-repeats, and sumoylation redirect separase from the cytosol to DSBs. In vitro assays suggest that DNA damage response-relevant ATM, PRMT1, and Mms21 represent the corresponding kinase, methyltransferase, and SUMO ligase, respectively. SEPARASE heterozygosity not only debilitates HDR but also predisposes primary embryonic fibroblasts to neoplasia and mice to chemically induced skin cancer. Thus, tethering of separase to DSBs and confined cohesin cleavage promote DSB repair in G2 cells. Importantly, this conserved interphase function of separase protects mammalian cells from oncogenic transformation.

EarlyR: A Robust Gene Expression Signature for Predicting Outcomes of Estrogen Receptor-Positive Breast Cancer

INTRODUCTION

Early stage estrogen receptor (ER)-positive breast cancer may be treated with chemotherapy in addition to hormone therapy. Currently available molecular signatures assess the risk of recurrence and the benefit of chemotherapy; however, these tests may have large intermediate risk groups, limiting their usefulness.

METHODS

The EarlyR prognostic score was developed using integrative analysis of microarray data sets and formalin-fixed, paraffin-embedded-based quantitative real-time PCR assay and validated in Affymetrix data sets and METABRIC cohort using Cox proportional hazards models and Kaplan-Meier survival analysis. Concordance index was used to measure the probability of prognostic score agreement with outcome.

RESULTS

The EarlyR score and categorical risk strata (EarlyR-Low, EarlyR-Int, EarlyR-High) derived from expression of ESPL1, MKI67, SPAG5, PLK1 and PGR was prognostic of 8-year distant recurrence-free interval in Affymetrix (categorical P = 3.5 × 10^-14; continuous P = 8.8 × 10^-15) and METABRIC (categorical P < 2.2 × 10^-16; continuous P < 10^-16) data sets of ER⁺ breast cancer. Similar results were observed for the breast cancer-free interval end point. At most 13% of patients were intermediate risk and at least 66% patients were low risk in both ER⁺ cohorts. The EarlyR score was significantly prognostic (distant recurrence-free interval; P < .001) in both lymph node-negative and lymph node-positive patients and was independent from clinical factors. EarlyR and surrogates of current molecular signatures were comparable in prognostic significance by concordance index.

CONCLUSION

The 5-gene EarlyR score is a robust prognostic assay that identified significantly fewer patients as intermediate risk and more as low risk than currently available assays. Further validation of the assay in clinical trial-derived cohorts is ongoing.

Expression of the Long Intergenic Non-Protein Coding RNA 665 (LINC00665) Gene and the Cell Cycle in Hepatocellular Carcinoma Using The Cancer Genome Atlas, the Gene Expression Omnibus, and Quantitative Real-Time Polymerase Chain Reaction

Background

Long non-coding RNAs (lncRNAs) have a role in physiological and pathological processes, including cancer. The aim of this study was to investigate the expression of the long intergenic non-protein coding RNA 665 (LINC00665) gene and the cell cycle in hepatocellular carcinoma (HCC) using database analysis including The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and quantitative real-time polymerase chain reaction (qPCR).

Material/Methods

Expression levels of LINC00665 were compared between human tissue samples of HCC and adjacent normal liver, clinicopathological correlations were made using TCGA and the GEO, and qPCR was performed to validate the findings. Other public databases were searched for other genes associated with LINC00665 expression, including The Atlas of Noncoding RNAs in Cancer (TANRIC), the Multi Experiment Matrix (MEM), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) networks.

Results

Overexpression of LINC00665 in patients with HCC was significantly associated with gender, tumor grade, stage, and tumor cell type. Overexpression of LINC00665 in patients with HCC was significantly associated with overall survival (OS) (HR=1.47795%; CI: 1.046–2.086). Bioinformatics analysis identified 469 related genes and further analysis supported a hypothesis that LINC00665 regulates pathways in the cell cycle to facilitate the development and progression of HCC through ten identified core genes: CDK1, BUB1B, BUB1, PLK1, CCNB2, CCNB1, CDC20, ESPL1, MAD2L1, and CCNA2.

Conclusions

Overexpression of the lncRNA, LINC00665 may be involved in the regulation of cell cycle pathways in HCC through ten identified hub genes.

Separase Inhibitor Sepin-1 Inhibits Foxm1 Expression and Breast Cancer Cell Growth

Sepin-1, a potent non-competitive inhibitor of separase, inhibits cancer cell growth, but the mechanisms of Sepin-1-mediated growth inhibition are not fully understood. Here we report that Sepin-1 hinders growth of breast cancer cells, cell migration, and wound healing. Inhibition of cell growth induced by Sepin-1 in vitro doesn't appear to be through apoptosis but rather due to growth inhibition. Following Sepin-1 treatment caspases 3 and 7 are not activated and Poly (ADP-ribose) polymerase (Parp) is not cleaved. The expression of Forkhead box protein M1 (FoxM1), a transcription factor, and its target genes in the cell cycle, including Plk1, Cdk1, Aurora A, and Lamin B1, are reduced in a Sepin-1-dependent manner. Expressions of Raf kinase family members A-Raf, B-Raf, and C-Raf also are inhibited following treatment with Sepin-1. Raf is an intermediator in the Raf-Mek-Erk signaling pathway that phosphorylates FoxM1. Activated FoxM1 can promote its own transcription via a positive feedback loop. Sepin-1-induced downregulation of Raf and FoxM1 may inhibit expression of cell cycle-driving genes, resulting in inhibition of cell growth.

Meta-analysis of mRNA expression profiles to identify differentially expressed genes in lung adenocarcinoma tissue from smokers and non-smokers

Compared to other types of lung cancer, lung adenocarcinoma patients with a history of smoking have a poor prognosis during the treatment of lung cancer. How lung adenocarcinoma-related genes are differentially expressed between smoker and non-smoker patients has yet to be fully elucidated. We performed a meta-analysis of four publicly available microarray datasets related to lung adenocarcinoma tissue in patients with a history of smoking using R statistical software. The top 50 differentially expressed genes (DEGs) in smoking vs. non‑smoking patients are shown using heat maps. Additionally, we conducted KEGG and GO analyses. In addition, we performed a PPI network analysis for 8 genes that were selected during a previous analysis. We identified a total of 2,932 DEGs (1,806 upregulated, 1,126 downregulated) and five genes (CDC45, CDC20, ANAPC7, CDC6, ESPL1) that may link lung adenocarcinoma to smoking history. Our study may provide new insights into the complex mechanisms of lung adenocarcinoma in smoking patients, and our novel gene expression signatures will be useful for future clinical studies.

IGF2 mRNA binding protein 3 (IMP3) mediated regulation of transcriptome and translatome in glioma cells

RNA binding proteins mediate global regulation at the level of transcriptome and translatome of a cell. We studied the global level expression changes regulated by IMP3 in transcriptome and translatome by performing microarray using total cellular RNA and heavy polysome derived RNA of IMP3 silenced glioma cells respectively. Differentially regulated transcripts at the transcriptome level (n = 2388) and at the level of translatome (n = 479) were identified. Further, these transcripts were classified as direct and indirect targets on the basis of presence of IMP3 binding site. Additional investigation revealed that direct targets at transcriptome level were found to be associated with processes related to cell cycle, whereas direct targets at the translatome level participated in apoptosis related pathways. Probable mechanism of indirect regulation at both the levels is also investigated. Collectively, our study reveals multi-level gene expression regulation imposed by IMP3 in glioma cells.

Integrated mRNAseq and microRNAseq data analysis for grade III gliomas

The World Health Organization classification distinguishes four grades for gliomas. Grade III gliomas, which are brain malignant brain tumors with variable biological behavior and propensity, have been not widely investigated. The objective of the present study was to identify specific gene modules and valuable hubs associated with gliomagenesis and molecular signatures to assist in determining grade III glioma prognosis. mRNAseq and micro (mi)RNAseq data were used to construct a co-expression network of gliomas using weight gene co-expression network analysis, and revealed the prognostic molecular signature of grade III gliomas. The differently expressed miRNAs and mRNAs were identified. A total of 37 mRNAs and 10 miRNAs were identified, which were closely associated with the survival rates of patients with grade III glioma. To further understand the tumorigenesis, Cytoscape software was used to construct a network containing these differently expressed molecules. The result suggested that both the downregulated genes and upregulated genes are vital in the process of glioma deterioration, and certain genes are closely associated with clinical prognosis.

Separase is a marker for prognosis and mitotic activity in breast cancer

Background:

Cancer cell proliferation is a critical feature in classifying and predicting the outcome of breast carcinoma. Separase has a central role in cell cycle progression in unleashing sister-chromatids at anaphase onset. Abnormally functioning separase is known to lead to chromosomal instability.

Methods:

The study comprises 349 breast carcinoma patients treated in Central Hospital of Central Finland. The prognostic value, role as a proliferation marker and regulatory interactions of separase are evaluated by immunohistochemical and double- and triple-immunofluorescence (IF) detections based on complete clinical data and >22-year follow-up of the patient material.

Results:

In our material, abnormal separase expression predicted doubled risk of breast cancer death (P<0.001). Up to 11.3-year survival difference was observed when comparing patients with and without separase expressing cancer cell mitoses. Particularly, abnormal separase expression predicted impaired survival for luminal breast carcinoma (P<0.001, respectively). In multivariate analyses, abnormal separase expression showed independent prognostic value. The complex inhibitory interactions involving securin and cyclin B1 were investigated in double- and triple-IFs and revealed patient subgroups with aberrant regulation and expression patterns of separase.

Conclusions:

In our experience, separase is a promising and clinically applicable proliferation marker. Separase expression shows strong and independent prognostic value and could be developed into a biomarker for treatment decisions in breast carcinoma, particularly defining prognostic subgroups among luminal carcinomas.

Separase: Function Beyond Cohesion Cleavage and an Emerging Oncogene

Proper and timely segregation of genetic endowment is necessary for survival and perpetuation of every species. Mis-segregation of chromosomes and resulting aneuploidy leads to genetic instability, which can jeopardize the survival of an individual or population as a whole. Abnormality with segregation of genetic contents has been associated with several medical consequences including cancer, sterility, mental retardation, spontaneous abortion, miscarriages, and other birth related defects. Separase, by irreversible cleavage of cohesin complex subunit, paves the way for metaphase/anaphase transition during the cell cycle. Both over or reduced expression and altered level of separase have been associated with several medical consequences including cancer, as a result separase now emerges as an important oncogene and potential molecular target for medical intervenes. Recently, separase is also found to be essential in separation and duplication of centrioles. Here, I review the role of separase in mitosis, meiosis, non-canonical roles of separase, separase regulation, as a regulator of centriole disengagement, nonproteolytic roles, diverse substrates, structural insights, and association of separase with cancer. At the ends, I proposed a model which showed that separase is active throughout the cell cycle and there is a mere increase in separase activity during metaphase contrary to the common believes that separase is inactive throughout cell cycle except for metaphase. J. Cell. Biochem. 118: 1283-1299, 2017. © 2016 Wiley Periodicals, Inc.

Measurement of separase proteolytic activity in single living cells by a fluorogenic flow cytometry assay

ESPL1/Separase, an endopeptidase, is required for centrosome duplication and separation of sister-chromatides in anaphase of mitosis. Overexpression and deregulated proteolytic activity of Separase as frequently observed in human cancers is associated with the occurrence of supernumerary centrosomes, chromosomal missegregation and aneuploidy. Recently, we have hypothesized that increased Separase proteolytic activity in a small subpopulation of tumor cells may serve as driver of tumor heterogeneity and clonal evolution in chronic myeloid leukemia (CML). Currently, there is no quantitative assay to measure Separase activity levels in single cells. Therefore, we have designed a flow cytometry-based assay that utilizes a Cy5- and rhodamine 110 (Rh110)-biconjugated Rad21 cleavage site peptide ([Cy5-D-R-E-I-M-R]₂-Rh110) as smart probe and intracellular substrate for detection of Separase enzyme activity in living cells. As measured by Cy5 fluorescence the cellular uptake of the fluorogenic peptide was fast and reached saturation after 210 min of incubation in human histiocytic lymphoma U937 cells. Separase activity was recorded as the intensity of Rh110 fluorescence released after intracellular peptide cleavage providing a linear signal gain within a 90–180 min time slot. Compared to conventional cell extract-based methods the flow cytometric assay delivers equivalent results but is more reliable, bypasses the problem of vague loading controls and unspecific proteolysis associated with whole cell extracts. Especially suited for the investigaton of blood- and bone marrow-derived hematopoietic cells the flow cytometric Separase assay allows generation of Separase activity profiles that tell about the number of Separase positive cells within a sample i.e. cells that currently progress through mitosis and about the range of intercellular variation in Separase activity levels within a cell population. The assay was used to quantify Separase proteolytic activity in leukemic cell lines and peripheral blood samples from leukemia patients.