Validation of UBE2C protein as a prognostic marker in node-positive breast cancer

Ubiquitination-Binding Enzyme 2C is Associated with Cancer Development and Prognosis and is a Potential Therapeutic Target

UBE2C (Ubiquitination-binding enzyme 2C), one of the E2 enzymes encoded in the human genome, is a component of the ubiquitin proteasome system and plays a pivotal role in regulating cell cycle progression. Moreover, UBE2C is highly expressed and may play a pivotal role in both high-incidence and high-mortality malignancies, including lung cancers, breast cancers, and esophageal cancers. UBE2C influences a number of key processes, including cell cycle progression, tumor invasion and metastasis, proliferation, and drug resistance. However, few articles have systematically summarized the role of UBE2C in cancer. The aim of this review is to describe the structure and function of UBE2C, focusing on the current status of UBE2C research in malignant tumors. Furthermore, this review presents the potential of UBE2C as a new therapeutic target and a diagnostic and prognostic biomarker. Finally, future research directions for UBE2C are proposed. It is of great value to explore the mechanism of action of UBE2C in the tumor microenvironment (TME). A comprehensive and coherent comprehension of UBE2C will undoubtedly facilitate its transition from fundamental research to clinical applications.

The Chromosome Passenger Complex (CPC) Components and Its Associated Pathways Are Promising Candidates to Differentiate Between Normosensitive and Radiosensitive ATM-Mutated Cells

Background

Sensitivity to ionizing radiation differs between individuals, but there is a limited understanding of the biological mechanisms that account for these variations. One example of such mechanisms are the mutations in the ATM (mutated ataxia telangiectasia) gene, that cause the rare recessively inherited disease Ataxia telangiectasia (AT). Hallmark features include chromosomal instability and increased sensitivity to ionizing radiation (IR).

Objectives

To deepen the molecular understanding of radiosensitivity and to identify potential new markers to predict it, human ATM-mutated and proficient cells were compared on a proteomic level.

Design

In this study, we analyzed 3 cell lines from AT patients, with varying radiosensitivity, and 2 cell lines from healthy volunteers, 24 hours and 72 hours post-10 Gy irradiation.

Methods

We used label-free mass spectrometry to identify differences in signaling pathways after irradiation in normal and radiosensitive individuals. Cell viability was initially determined by water soluble tetrazolium (WST) assay and DNA damage response was analyzed with 53BP1 repair foci formation along with KRAB-associated protein 1 (KAP1) phosphorylation.

Results

Proteomic analysis identified 4028 proteins, which were used in subsequent in silico pathway enrichment analysis to predict affected biological pathways post-IR. In AT cells, networks were heterogeneous at both time points with no common pathway identified. Mitotic cell cycle progress was the most prominent pathway altered after IR in cells from healthy donors. In particular, components of the chromosome passenger complex (INCENP and CDCA8) were significantly downregulated after 72 hours. This could also be verified at the mRNA level.

Conclusion

Altogether, the most striking result was that proteins forming the chromosome passenger complex were downregulated after radiation exposure in healthy normosensitive control cells, but not in radiosensitive ATM-deficient cells. Thus, mitosis-associated proteins form an interesting compound to gain insights into the development and prediction of radiosensitivity.

UBE2C promotes LUAD progression by ubiquitin-dependent degradation of p53 to inactivate the p53/p21 signaling pathway

Lung adenocarcinoma (LUAD) is one of the greatest causes of cancer death worldwide. As a novel potential tumor biomarker, ubiquitin-conjugating enzyme E2C (UBE2C) is a critical factor during the onset and development of human cancers. However, the mechanisms of UBE2C in LUAD are not well understood. In this study, increased expression level of UBE2C was observed in LUAD tumor tissues. High LUAD level portended a worse prognosis of LUAD patients. Down-regulation of UBE2C attenuated the cell proliferation and cycle, migration, and invasion. Consistently, the tumorigenic capacity of LUAD cells in nude mice was significantly suppressed by the knockdown of UBE2C. Knockdown of UBE2C inhibited the degradation of p53 protein via an ubiquitin-proteasome pathway, thereby increasing p53 and p21 protein expression. Moreover, the inhibition of LUAD cell malignant phenotypes caused by UBE2C knockdown was attenuated on account of the inactivation of p53/p21 signaling pathway. In conclusion, UBE2C facilitates cell malignant behaviour in LUAD by ubiquitin-dependent degradation of p53 to suppress the p53/p21 signaling pathway. UBE2C is potentially developed as a therapeutic target for patients with LUAD.

UBE2C, targeted by miR-140-3p, promotes the progression of osteosarcoma via PI3K/AKT signaling pathway

BACKGROUND

UBE2C was reported to play carcinogenic effects in diverse cancers. However, the role of UBE2C in osteosarcoma was poorly understood, and its functional mechanisms were not fully clarified.

METHODS

RT-qPCR was used to assess the expression of UBE2C mRNA and miR-140-3p, and western blot technique was used to examine the UBE2C protein and PI3K/AKT pathway-associated proteins. CCK-8 test was applied to measure cell proliferation, and wound healing assay were used to measure migration. Using animal studies, the function of UBE2C in vivo was evaluated. Dual-luciferase reporter assay was used to confirm the potential interaction among UBE2C and miR-140-3p.

RESULTS

In osteosarcoma cells as well as tumor samples, UBE2C was strongly expressed. Osteosarcoma cell proliferation as well as cell migration were inhibited by UBE2C knockdown, and PI3K/AKT signaling activity was diminished. In addition, UBE2C knockdown impeded tumor growth in animal models. UBE2C expression was lessened by miR-140-3p as miR-140-3p targets it. UBE2C is overexpressed which promote osteosarcoma proliferation as well as migration, and strengthened the PI3K/AKT signaling activity, while forced miR-140-3p expression partially abolished these effects.

CONCLUSION

UBE2C, targeted by miR-140-3p, drove carcinogenic effects in osteosarcoma through activating the PI3K/AKT pathway.

UBE2C expression is elevated in hepatoblastoma and correlates with inferior patient survival

Hepatoblastoma (HB) is the most common malignant liver tumor among children. To gain insight into the pathobiology of HB, we performed RNA sequence analysis on 5 patient-derived xenograft lines (HB-243, HB-279, HB-282, HB-284, HB-295) and 1 immortalized cell line (HUH6). Using cultured hepatocytes as a control, we found 2,868 genes that were differentially expressed in all of the HB lines on mRNA level. The most upregulated genes were ODAM, TRIM71, and IGDCC3, and the most downregulated were SAA1, SAA2, and NNMT. Protein-protein interaction analysis identified ubiquitination as a key pathway dysregulated in HB. UBE2C, encoding an E2 ubiquitin ligase often overexpressed in cancer cells, was markedly upregulated in 5 of the 6 HB cell lines. Validation studies confirmed UBE2C immunostaining in 20 of 25 HB tumor specimens versus 1 of 6 normal liver samples. The silencing of UBE2C in two HB cell models resulted in decreased cell viability. RNA sequencing analysis showed alterations in cell cycle regulation after UBE2C knockdown. UBE2C expression in HB correlated with inferior patient survival. We conclude that UBE2C may hold prognostic utility in HB and that the ubiquitin pathway is a potential therapeutic target in this tumor.

Validation of a Disease-Free Survival Prediction Model Using UBE2C and Clinical Indicators in Breast Cancer Patients

Objective

To explore the validation of a disease-free survival (DFS) model for predicting disease progression based on the combination of ubiquitin-conjugating enzyme E2 C (UBE2C) levels and clinical indicators in breast cancer patients.

Methods

We enrolled 121 patients with breast cancer, collected their baseline characteristics and follow-up data, and analyzed the UBE2C levels in tumor tissues. We studied the relationship between UBE2C expression in tumor tissues and disease progression events of patients. We used the Kaplan-Meier method for identifying the disease-free survival rate of patients, and the multivariate Cox regression analysis to study the risk factors affecting the prognosis of patients. We sought to develop and validate a model for predicting disease progression.

Results

We found that the level of expression of UBE2C could effectively distinguish the prognosis of patients. In the Receiver Operating Characteristic (ROC) curve analysis, the Area under the ROC Curve (AUC) = 0.826 (0.714-0.938) indicating that high levels of UBE2C was a high-risk factor for poor prognosis. After evaluating different models using the ROC curve, Concordance index (C-index), calibration curve, Net Reclassification Index (NRI), Integrated Discrimination Improvement Index (IDI), and other methods, we finally developed a model for the expression of Tumor-Node (TN) staging using Ki-67 and UBE2C, which had an AUC=0.870, 95% CI of 0.786-0.953. The traditional TN model had an AUC=0.717, and 95% CI of 0.581-0.853. Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) analysis indicated that the model had good clinical benefits and it was relatively simple to use.

Conclusion

We found that high levels of UBE2C was a high-risk factor for poor prognosis. The use of UBE2C in addition to other breast cancer-related indicators effectively predicted the possible disease progression, thus providing a reliable basis for clinical decision-making.

UBE2C promotes leptomeningeal dissemination and is a therapeutic target in brain metastatic disease

Background

Despite current improvements in systemic cancer treatment, brain metastases (BM) remain incurable, and there is an unmet clinical need for effective targeted therapies.

Methods

Here, we sought common molecular events in brain metastatic disease. RNA sequencing of thirty human BM identified the upregulation of UBE2C, a gene that ensures the correct transition from metaphase to anaphase, across different primary tumor origins.

Results

Tissue microarray analysis of an independent BM patient cohort revealed that high expression of UBE2C was associated with decreased survival. UBE2C-driven orthotopic mouse models developed extensive leptomeningeal dissemination, likely due to increased migration and invasion. Early cancer treatment with dactolisib (dual PI3K/mTOR inhibitor) prevented the development of UBE2C-induced leptomeningeal metastases.

Conclusions

Our findings reveal UBE2C as a key player in the development of metastatic brain disease and highlight PI3K/mTOR inhibition as a promising anticancer therapy to prevent late-stage metastatic brain cancer.

Bone Marrow Mesenchymal Stem Cell-Derived Exosomes Inhibit Triple-Negative Breast Cancer Cell Stemness and Metastasis via an ALKBH5-Dependent Mechanism

BACKGROUND

Abnormal N6-methyladenosine (m6A) modification caused by m6A regulators is a common characteristic in various tumors. However, little is known about the role of m6A regulator AlkB homolog 5 (ALKBH5) in triple-negative breast cancer (TNBC). In this study, we analyzed the influence of ALKBH5 on the stemness of TNBC and the molecular mechanism using bioinformatics analysis and in vivo animal experiments.

METHODS

RNA expression data and single-cell RNA sequencing (scRNA-seq) data were downloaded from the TCGA and GEO databases. Following intersection analysis, key genes involved in the TNBC cell stemness were determined, which was followed by functional enrichment analysis, PPI and survival analysis. Exosomes were extracted from bone marrow mesenchymal stem cells (BMSC-Exos) where ALKBH5 inhibition assay was conducted to verify their function in the biological characteristics of TNBC cells.

RESULTS

Bioinformatics analysis revealed 45 key genes of ALKBH5 regulating TNBC cell stemness. In addition, UBE2C was predicted as a key downstream gene and p53 was predicted as a downstream signaling of ALKBH5. In vivo data confirmed that ALKBH5 upregulated UBE2C expression by regulating the m6A modification of UBE2C and reduced p53 expression, thus promoting the stemness, growth and metastasis of TNBC cells. BMSC-Exos suppressed the tumor stemness, growth and metastasis of TNBC cells and ALKBH5 shRNA-loaded BMSC-Exos showed a more significant suppressive role.

CONCLUSION

Taken together, our findings indicated that ALKBH5 shRNA-loaded BMSC-Exos reduced TNBC cell stemness, growth and metastasis and define a promising strategy to treat TNBC.

The clinical significance of <em>UBE2C</em> gene in progression of renal cell carcinoma

Renal cell carcinoma (RCC), with high morbidity and mortality, is one of the top ten serious cancers. Due to limited therapies and little knowledge about the mechanism underlying RCC, overall survival of RCC patients is poor. UBE2C is a member of ubiquitin modification system and promotes carcinogenesis in cancer, but its role in RCC is unknown. Based on the TCGA (The Cancer Genome Atlas) data, UBE2C was over-expressed in a total of 525 RCC tissues and displayed higher expression in advanced tissues (stage IV vs stage I, p<0.05). RT-qPCR and IHC analysis confirmed over-expression of UBE2C in 90 of clinical RCC tissues. Further, UBE2C was associated with clinical factors including TNM stage, gender, and pathological stage. And higher UBE2C expression predicted shorter overall survival and progression-free survival. Both univariate and multivariate COX analysis suggested UBE2C as a critical gene in RCC. Then GO and KEGG analysis showed that cell cycle and DNA replication pathways were two top signaling pathways affected by UBE2C. In vitro assay showed that knockdown of UBE2C in 786-O cells inhibited proliferation and migration significantly. Therefore, this study proves that UBE2C is an important gene in RCC and is essential to proliferation and migration of RCC.

Mapping of Genomic Vulnerabilities in the Post-Translational Ubiquitination, SUMOylation and Neddylation Machinery in Breast Cancer

Simple Summary

Breast cancer is a major cause of death worldwide and remains incurable in advanced stages. The dysregulation of the post-translational machinery has been found to underlie tumorigenesis and drug resistance in preclinical models but has only recently led to early trials in cancer patients. We performed an in silico analysis of the most common genomic alterations occurring in ubiquitination and ubiquitin-like SUMOylation and neddylation using data from publicly available repositories and with the aim of identifying those with prognostic and predictive value and those exploitable for therapeutic intervention. Clinical and statistical criteria were used to sort out the best candidates and the results were validated in independent datasets. UBE2T, UBE2C, and BIRC5 amplifications predicted a worse survival and poor response to therapy across different intrinsic subtypes of breast cancer. Mutated USP9X and USP7 also conferred detrimental outcome. Leveraging these molecular vulnerabilities as biomarkers or drug targets could benefit breast cancer patients.

Abstract

The dysregulation of post-translational modifications (PTM) transversally impacts cancer hallmarks and constitutes an appealing vulnerability for drug development. In breast cancer there is growing preclinical evidence of the role of ubiquitin and ubiquitin-like SUMO and Nedd8 peptide conjugation to the proteome in tumorigenesis and drug resistance, particularly through their interplay with estrogen receptor signaling and DNA repair. Herein we explored genomic alterations in these processes using RNA-seq and mutation data from TCGA and METABRIC datasets, and analyzed them using a bioinformatic pipeline in search of those with prognostic and predictive capability which could qualify as subjects of drug research. Amplification of UBE2T, UBE2C, and BIRC5 conferred a worse prognosis in luminal A/B and basal-like tumors, luminal A/B tumors, and luminal A tumors, respectively. Higher UBE2T expression levels were predictive of a lower rate of pathological complete response in triple negative breast cancer patients following neoadjuvant chemotherapy, whereas UBE2C and BIRC5 expression was higher in luminal A patients with tumor relapse within 5 years of endocrine therapy or chemotherapy. The transcriptomic signatures of USP9X and USP7 gene mutations also conferred worse prognosis in luminal A, HER2-enriched, and basal-like tumors, and in luminal A tumors, respectively. In conclusion, we identified and characterized the clinical value of a group of genomic alterations in ubiquitination, SUMOylation, and neddylation enzymes, with potential for drug development in breast cancer.

Identification of breast cancer prognostic modules via differential module selection based on weighted gene Co-expression network analysis

Breast cancer is a complex cancer which includes many different subtypes. Identifying prognostic modules, i.e., functionally related gene networks that play crucial roles in cancer development is essential in breast cancer study. Different subtypes of breast cancer correspond to different treatment methods. The purpose of this study is to use a new method to divide breast cancer into different prognostic modules, so as to provide scientific basis for improving clinical management. The method is based on comparing similarities between modules detected from different weighted gene co-expression networks. The method was applied on genomic data of breast cancer from The Cancer Genome Atlas database and was applied to select differential modules between two groups of patients with significant differences in survival times. It was compared with a previously proposed module selection method. The result shows that our method outperforms the previously proposed one. Moreover, within the identified two differential modules, the first one is highly enriched with genes involved in hormone responds, the second one is highly related with biological process engaged in M-phase. The two modules were further validated by log-rank test in the validation dataset GSE3494. Both of the two modules show significantly different with p-values less than 0.02. The identified two modules confirmed previous findings including importance of biological networks in breast cancer involved in hormone response and M-phase. Out of the top twenty hub genes in the two modules, fifteen genes were previously shown to be prognostic markers for breast cancer.

Identification of potential target genes and crucial pathways in small cell lung cancer based on bioinformatic strategy and human samples

Small cell lung cancer (SCLC) is a carcinoma of the lungs with strong invasion, poor prognosis and resistant to multiple chemotherapeutic drugs. It has posed severe challenges for the effective treatment of lung cancer. Therefore, searching for genes related to the development and prognosis of SCLC and uncovering their underlying molecular mechanisms are urgent problems to be resolved. This study is aimed at exploring the potential pathogenic and prognostic crucial genes and key pathways of SCLC via bioinformatic analysis of public datasets. Firstly, 117 SCLC samples and 51 normal lung samples were collected and analyzed from three gene expression datasets. Then, 102 up-regulated and 106 down-regulated differentially expressed genes (DEGs) were observed. And then, functional annotation and pathway enrichment analyzes of DEGs was performed utilizing the FunRich. The protein-protein interaction (PPI) network of the DEGs was constructed through the STRING website, visualized by Cytoscape. Finally, the expression levels of eight hub genes were confirmed in Oncomine database and human samples from SCLC patients. It showed that CDC20, BUB1, TOP2A, RRM2, CCNA2, UBE2C, MAD2L1, and BUB1B were upregulated in SCLC tissues compared to paired adjacent non-cancerous tissues. These suggested that eight hub genes might be viewed as new biomarkers for prognosis of SCLC or to guide individualized medication for the therapy of SCLC.

Identification of hub genes associated with esophageal cancer progression using bioinformatics analysis

The underlying causes of esophageal cancer (EC) are unknown. To explore the molecular mechanisms that lead to EC, gene expression profiles of large cohorts of patients with EC were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases (GSE5364, GSE20347 and GSE23400). The present study identified 83 upregulated and 22 downregulated genes between EC and normal tissue using R statistical software and the GEO2R web tool. The Database for Annotation, Visualization and Integrated Discovery was used to identify the associated pathways, and for functional annotation of the differentially expressed genes (DEGs). Protein-protein interactions of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database, and hub genes were visualized using Cytoscape software. An online Kaplan-Meier plotter survival analysis tool was utilized to evaluate the prognostic value of hub gene expression in patients with EC. Further analysis of an additional dataset from GEO (GSE21293) revealed that these genes were associated with infiltration and metastasis in EC. In addition, the Gene Expression Profiling Interactive Analysis tool was used to evaluate expression levels of hub genes in patients with EC for different pathological stages. The Ualcan analysis tool was used to evaluate the expression levels of hub genes for different histological types. Overall, ubiquitin conjugating enzyme E2 C, cyclin dependent kinase inhibitor 3, CDC28 protein kinase regulatory subunit 2, kinesin family member 20A (KIF20A) and RAD51 associated protein 1 (RAD51AP1) were upregulated in EC tissues compared with normal tissues, and upregulation of these genes was a poor prognostic factor for patients with EC, indicating that these genes may mediate EC cell infiltration and metastasis. Among the hub genes, KIF-20A had potential value for predicting the pathological stage of EC. KIF20A and RAD51AP1 were more informative biomarkers of esophageal squamous cell carcinoma. Further studies are required to explore the value of these genes in the treatment of EC.

UBE2C Overexpression Aggravates Patient Outcome by Promoting Estrogen-Dependent/Independent Cell Proliferation in Early Hormone Receptor-Positive and HER2-Negative Breast Cancer

We previously showed that UBE2C mRNA expression is significantly associated with poor prognosis only in patients with hormone receptor (HR)+/human epidermal growth factor receptor 2 (HER2)– breast cancer. In this study, we further reanalyzed the correlation between UBE2C mRNA expression and clinical outcomes in patients with HR+/HER2– breast cancer, and we investigated the molecular mechanism underlying the role of UBE2C modulation in disease progression in this subgroup of patients. Univariate and multivariate analyses showed that high UBE2C expression was associated with significantly shorter survival of breast cancer patients with pN0 and pN1 tumors but not pN2/N3 tumors (P < 0.05). In vitro functional experiments in HR+/HER2– breast cancer cells showed that UBE2C expression is a tumorigenic factor, and that estrogen upregulated UBE2C mRNA and protein by directly binding to the UBE2C promoter region. UBE2C knockdown inhibited cell proliferation by affecting cell cycle progression, and UBE2C overexpression was associated with estrogen-independent growth. UBE2C depletion markedly increased the cytotoxicity of tamoxifen by inducing apoptosis. The present findings suggest that UBE2C overexpression is correlated with relapse and promotes estrogen-dependent/independent proliferation in early HR+/HER2– breast cancer.

ClearF: a supervised feature scoring method to find biomarkers using class-wise embedding and reconstruction

BACKGROUND

Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information-theoretic approaches. However, most of these methods generally require a long processing time. In addition, information-theoretic methods discretize continuous features, which is a drawback that can lead to the loss of information.

RESULTS

In this paper, a novel supervised feature scoring method named ClearF is proposed. The proposed method is suitable for continuous-valued data, which is similar to the principle of feature selection using mutual information, with the added advantage of a reduced computation time. The proposed score calculation is motivated by the association between the reconstruction error and the information-theoretic measurement. Our method is based on class-wise low-dimensional embedding and the resulting reconstruction error. Given multi-class datasets such as a case-control study dataset, low-dimensional embedding is first applied to each class to obtain a compressed representation of the class, and also for the entire dataset. Reconstruction is then performed to calculate the error of each feature and the final score for each feature is defined in terms of the reconstruction errors. The correlation between the information theoretic measurement and the proposed method is demonstrated using a simulation. For performance validation, we compared the classification performance of the proposed method with those of various algorithms on benchmark datasets.

CONCLUSIONS

The proposed method showed higher accuracy and lower execution time than the other established methods. Moreover, an experiment was conducted on the TCGA breast cancer dataset, and it was confirmed that the genes with the highest scores were highly associated with subtypes of breast cancer.

Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer

Background

Exploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same patient were performed to identify the key genes and signaling pathways related to breast cancer development.

Methods

Samples of breast tumor tissue and paracancerous breast tissue were obtained from 6 patients. Sequencing used the Illumina HiSeq platform. All. Only perfectly matched clean reads were mapped to the reference genome database, further analyzed and annotated based on the reference genome information. Differentially expressed genes (DEGs) were identified using the DESeq R package (1.10.1) and DEGSeq R package (1.12.0). Using KOBAS software to execute the KEGG bioinformatics analyses, enriched signaling pathways of DEGs involved in the occurrence of breast cancer were determined. Subsequently, quantitative real time PCR was used to verify the accuracy of the expression profile of key DEGs from the RNA-seq result and to explore the expression patterns of novel cancer-related genes on 8 different clinical individuals.

Results

The transcriptomic sequencing results showed 937 DEGs, including 487 upregulated and 450 downregulated genes in the breast cancer specimens. Further quantitative gene expression analysis was performed and captured 252 DEGs (201 downregulated and 51 upregulated) that showed the same differential expression pattern in all libraries. Finally, 6 upregulated DEGs (CST2, DRP2, CLEC5A, SCD, KIAA1211, DTL) and 6 downregulated DEGs (STAC2, BTNL9, CA4, CD300LG, GPIHBP1 and PIGR), were confirmed in a quantitative real time PCR comparison of breast cancer and paracancerous breast tissues from 8 clinical specimens. KEGG analysis revealed various pathway changes, including 20 upregulated and 21 downregulated gene enrichment pathways. The extracellular matrix–receptor (ECM-receptor) interaction pathway was the most enriched pathway: all genes in this pathway were DEGs, including the THBS family, collagen and fibronectin. These DEGs and the ECM-receptor interaction pathway may perform important roles in breast cancer.

Conclusion

Several potential breast cancer-related genes and pathways were captured, including 7 novel upregulated genes and 76 novel downregulated genes that were not found in other studies. These genes are related to cell proliferation, movement and adhesion. They may be important for research into breast cancer mechanisms, particularly CST2 and CA4. A key signaling pathway, the ECM-receptor interaction signal pathway, was also identified as possibly involved in the development of breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s11658-019-0162-0) contains supplementary material, which is available to authorized users.

Fabrication of an immunosensor for quantitative detection of breast cancer biomarker UBE2C

Antibodies crosslinking on PANI modified electrode to design a highly selective immunosensor to detect UBE2C.

Identification of Five Genes as a Potential Biomarker for Predicting Progress and Prognosis in Adrenocortical Carcinoma

Background: Adrenocortical carcinoma (ACC) is a limited endocrine fatality with a minor diagnosis and rare remedial options. The progressive and predictive meaning of message RNA (mRNA) expression oddity in ACC has been studied extensively in recent years. However, differences in measurement platforms and lab protocols as well as small sample sizes can render gene expression levels incomparable.

Methods: An extensive study of GEO datasets was conducted to define potential mRNA biomarkers for ACC. The study compared the mRNA expression profiles of ACC tissues and neighboring noncancerous adrenal tissues in the pair. The study covered a sum of 165 tumors and 36 benign control samples. Hub genes were identified through a protein-protein interaction (PPI) network and Robust Rank Aggregation method. Then the Cancer Genome Atlas (TCGA) and Oncomine database were used to perform the validation of hub genes. 4 ACC tissues and 4 normal tissues were collected and then Polymerase Chain Reaction (PCR), Western-blot and immunofluorescence were conducted to validate the expression of five hub genes.

Results: We identified five statistically significant genes (TOP2A, NDC80, CEP55, CDKN3, CDK1) corrected with clinical features. The expression of five hub genes in TCGA and Oncomine database were significantly overexpressed in ACC compared with normal ones. Among all the TCGA ACC cases, the strong expression of TOP2A (logrank p=1.4e-04, HR=4.7), NDC80 (logrank p=8.8e-05, HR=4.9), CEP55 (logrank p=5.2e-07, HR=8.6), CDKN3 (log rank p=2.3e-06, HR=7.6) and CDK1 (logrank p=7e-08, HR=11) were correlated with low comprehensive survival, disease free survival (logrank p < 0.001), pathology stage and pathology T stage (FDR < 0.001). PCR results showed that the transcriptional levels of these five genes were significantly higher in ACC tissues than in normal tissues. The western blotting results also showed that the translational level of TOP2A was significantly higher in tumor tissues than in normal tissues. The results of immunofluorescence showed that TOP2A was abundantly observed in the adrenal cortical cell membrane and nucleus and its expression in ACC tissues was significantly higher than that in normal tissues.

Conclusions: The distinguished five genes may be utilized to form a board of progressive and predictive biomarkers for ACC for clinical purpose.

Identification of Candidate Biomarkers Correlated With the Pathogenesis and Prognosis of Non-small Cell Lung Cancer via Integrated Bioinformatics Analysis

Background and Objective: Non-small cell lung cancer (NSCLC) accounts for 80-85% of all patients with lung cancer and 5-year relative overall survival (OS) rate is less than 20%, so that identifying novel diagnostic and prognostic biomarkers is urgently demanded. The present study attempted to identify potential key genes associated with the pathogenesis and prognosis of NSCLC. Methods: Four GEO datasets (GSE18842, GSE19804, GSE43458, and GSE62113) were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between NSCLC samples and normal ones were analyzed using limma package, and RobustRankAggreg (RRA) package was used to conduct gene integration. Moreover, Search Tool for the Retrieval of Interacting Genes database (STRING), Cytoscape, and Molecular Complex Detection (MCODE) were utilized to establish protein-protein interaction (PPI) network of these DEGs. Furthermore, functional enrichment and pathway enrichment analyses for DEGs were performed by Funrich and OmicShare. While the expressions and prognostic values of top genes were carried out through Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan Meier-plotter (KM) online dataset. Results: A total of 249 DEGs (113 upregulated and 136 downregulated) were identified after gene integration. Moreover, the PPI network was established with 166 nodes and 1784 protein pairs. Topoisomerase II alpha (TOP2A), a top gene and hub node with higher node degrees in module 1, was significantly enriched in mitotic cell cycle pathway. In addition, Interleukin-6 (IL-6) was enriched in amb2 integrin signaling pathway. The mitotic cell cycle was the most significant pathway in module 1 with the highest P-value. Besides, five hub genes with high degree of connectivity were selected, including TOP2A, CCNB1, CCNA2, UBE2C, and KIF20A, and they were all correlated with worse OS in NSCLC. Conclusion: The results showed that TOP2A, CCNB1, CCNA2, UBE2C, KIF20A, and IL-6 may be potential key genes, while the mitotic cell cycle pathway may be a potential pathway contribute to progression in NSCLC. Further, it could be used as a new biomarker for diagnosis and to direct the synthesis medicine of NSCLC.

The miR 495-UBE2C-ABCG2/ERCC1 axis reverses cisplatin resistance by downregulating drug resistance genes in cisplatin-resistant non-small cell lung cancer cells

Cisplatin (DDP) resistance has become the leading cause of mortality in non-small cell lung cancer (NSCLC). miRNA dysregulation significantly contributes to tumor progression. In this study, we found that miR-495 was significantly downregulated in lung cancer tissue specimens. This study aimed to elucidate the functions, direct target genes, and molecular mechanisms of miR-495 in lung cancer. miR-495 downregulated its substrate UBE2C through direct interaction with UBE2C 3′- untranslated region. UBE2C is a proto-oncogene activated in lung cancer; however, its role in chemotherapeutic resistance is unclear. Herein, UBE2C expression levels were higher in DDP-resistant NSCLC cells; this was associated with the proliferation, invasion, and DDP resistance in induced cisplatin-resistant NSCLC cells. Furthermore, epithelial–mesenchymal transitions (EMT) contributed to DDP resistance. Moreover, UBE2C knockdown downregulated vimentin. In contrast, E-cadherin was upregulated. Importantly, miR-495 and UBE2C were associated with cisplatin resistance. We attempted to evaluate their effects on cell proliferation and cisplatin resistance. We also performed EMT, cell migration, and invasion assays in DDP-resistant NSCLC cells overexpressing miR-495 and under-expressing UBE2C. Furthermore, in silico assays coupled with western blotting and luciferase assays revealed that UBE2C directly binds to the 5′-UTR of the drug-resistance genes ABCG2 and ERCC1. Furthermore, miR-495 downregulated ABCG2 and ERCC1 via regulation of UBE2C. Together, the present results indicate that the miR495-UBE2C-ABCG2/ERCC1 axis reverses DDP resistance via downregulation of anti-drug genes and reducing EMT in DDP-resistant NSCLC cells.

Co-expression network analysis identified six hub genes in association with progression and prognosis in human clear cell renal cell carcinoma (ccRCC)

Human clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney tumors. We constructed a weighted gene co-expression network to identify gene modules associated with clinical features of ccRCC (n = 97). Six hub genes (CCNB2, CDC20, CEP55, KIF20A, TOP2A and UBE2C) were identified in both co-expression and protein-protein interaction (PPI) networks, which were highly correlated with pathologic stage. The significance of expression of the hub genes in ccRCC was ranked top 4 among all cancers and correlated with poor prognosis. Functional analysis revealed that the hub genes were significantly enriched in cell cycle regulation and cell division. Gene set enrichment analysis suggested that the samples with highly expressed hub gene were correlated with cell cycle and p53 signaling pathway. Taken together, six hub genes were identified to be associated with progression and prognosis of ccRCC, and they might lead to poor prognosis by regulating p53 signaling pathway.

The clinicopathological significance of UBE2C in breast cancer: a study based on immunohistochemistry, microarray and RNA-sequencing data

BACKGROUND

Ubiquitin-conjugating enzyme E2C (UBE2C) has been previously reported to correlate with the malignant progression of various human cancers, however, the exact molecular function of UBE2C in breast carcinoma (BRCA) remained elusive. We aimed to investigate UBE2C expression in BRCA and its clinical significance.

METHODS

The expression of UBE2C in 209 BRCA tissue samples and 53 adjacent normal tissue samples was detected using immunohistochemistry. The clinical role of UBE2C was analyzed. Public databases including the human protein atlas and Oncomine were used to assess UBE2C expression in BRCA. Moreover, the cancer genome atlas (TCGA) database was employed to investigate the prognostic value of UBE2C in BRCA.

RESULTS

The positive expression rate of UBE2C in BRCA was 70.8% (148/209), and UBE2C expression in the adjacent breast tissue was negative. The expression of UBE2C was positively correlated with tumor size (r = 0.32, P < 0.001), histological grade (r = 0.237, P = 0.001), clinical stage (r = 0.198, P = 0.004), lymph node metastasis (r = 0.155, P = 0.026), HER2 expression level (r = 0.356, P < 0.001), Ki-67 expression level (r = 0.504, P < 0.001), and P53 expression level (r = 0.32, P = 0.001). Negative correlations were found between UBE2C expression and the ER (r = - 0.403, P < 0.001) and PR (r = - 0.468, P < 0.001) status. UBE2C gene expression data from the public databases all proved that UBE2C was overexpressed in BRCA. According to the TCGA data analysis, a higher positive expression of UBE2C was associated with worse survival of BRCA patients (P = 0.0428), and data from cBioPortal indicated that 11% of all sequenced BRCA patients possessed a gene alteration of UBE2C, predominately gene amplification and mRNA regulation.

CONCLUSION

Ubiquitin-conjugating enzyme E2C might pose an oncogenic effect on the progression of BRCA.

Prognostic genes of breast cancer revealed by gene co-expression network analysis

The aim of the present study was to identify genes that may serve as markers for breast cancer prognosis by constructing a gene co-expression network and mining modules associated with survival. Two gene expression datasets of breast cancer were downloaded from ArrayExpress and genes from these datasets with a coefficient of variation >0.5 were selected and underwent functional enrichment analysis with the Database for Annotation, Visualization and Integration Discovery. Gene co-expression networks were constructed with the WGCNA package in R. Modules were identified from the network via cluster analysis. Cox regression was conducted to analyze survival rates. A total of 2,669 genes were selected, and functional enrichment analysis of them revealed that they were mainly associated with the immune response, cell proliferation, cell differentiation and cell adhesion. Seven modules were identified from the gene co-expression network, one of which was found to be significantly associated with patient survival time. Expression status of 144 genes from this module was used to cluster patient samples into two groups, with a significant difference in survival time revealed between these groups. These genes were involved in the cell cycle and tumor protein p53 signaling pathway. The top 10 hub genes were identified in the module. The findings of the present study could advance the understanding of the molecular pathogenesis of breast cancer.

Prognostic significance of PLIN1 expression in human breast cancer

Breast cancer is a heterogeneous disease associated with diverse clinical, biological and molecular features, presenting huge challenges for prognosis and treatment. Here we found that perilipin-1 (PLIN1) mRNA expression is significantly downregulated in human breast cancer. Kaplan-Meier analysis indicated that patients presenting with reduced PLIN1 expression exhibited poorer overall metastatic relapse-free survival (p = 0.03). Further Cox proportional hazard models analysis revealed that the reduced expression of PLIN1 is an independent predictor of overall survival in estrogen receptor positive (p < 0.0001, HR = 0.87, 95% CI = 0.81-0.92, N = 3,600) and luminal A-subtype (p = 0.02, HR = 0.88, 95% CI = 0.78-0.98, N = 1,469) breast cancer patients. We also demonstrated that the exogenous expression of PLIN1 in human breast cancer MCF-7 and MDA-MB-231 cells significantly inhibits cell proliferation, migration, invasion and in vivo tumorigenesis in mice. Together, these data provide novel insights into a prognostic significance of PLIN1 in human breast cancer and reveal a potentially new gene therapy target for breast cancer.

Prognostic value of different cut-off levels of Ki-67 in breast cancer: a systematic review and meta-analysis of 64,196 patients

A proliferative marker, expressed as the percentage of cells in a cell cycle, has been developed and used as a discriminant of more aggressive malignant phenotypes in early breast cancer (BC). The marker is usually expressed by the immunohistochemical staining of the cell cycle antigen Ki-67. It has not, however, yet been definitely evaluated, due to methodological concerns, which specific Ki-67 cut-off provide the strongest prognostic information in resected BC. We conducted a meta-analysis to explore the prognostic value of different cut-off levels of Ki-67 in terms of overall survival (OS) and disease-free survival (DFS) in early BC. The databases of PubMed, the ISI Web of Science, EMBASE, SCOPUS, the Cochrane Central Register of Controlled Trials, and CINHAL were used to identify the relevant literature. Data from studies reporting a hazard ratio (HR) and a 95 % confidence interval (CI) calculated as a multivariate analysis were pooled in a meta-analysis, with metaregression used to test for trends in predefined subgroups. All the statistical tests were 2-sided. Forty-one studies encompassing 64,196 BC patients were included in the analysis. Overall, n = 25 studies were available for the OS analysis. The pooled HR for high versus low Ki-67 was 1.57 (95 % CI 1.33-1.87, P < 0.00001). Twenty-nine studies were available for the DFS analysis. The pooled HR for high versus low Ki-67 was 1.50 (95 % CI 1.34-1.69, P < 0.00001). When a cut-off of Ki-67 staining ≥ 25 % was used, the pooled HR for OS was 2.05 (95 % CI 1.66-2.53, P < 0.00001), which was significantly different to studies where the cut-offs chosen were <25 %. In ER+ tumors, the HR for high versus low Ki-67 was similar and significant (HR = 1.51, 95 % CI 1.25-1.81, P < 0.0001). We conclude that Ki-67 has an independent prognostic value in terms of OS in BC patients. The Ki-67 threshold with the greatest prognostic significance is as yet unknown, but a cut-off >25 % is associated with a greater risk of death compared with lower expression rates.

The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set

BACKGROUND

The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction.

METHODS AND FINDINGS

The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method.

CONCLUSIONS

The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes.

Evolving transcriptomic fingerprint based on genome-wide data as prognostic tools in prostate cancer

Background Information

Prostate cancer (PCa) is a common disease but only a small subset of patients are at risk of developing metastasis and lethal disease, and identifying which patients will progress is challenging because of the heterogeneity underlying tumour progression. Understanding this heterogeneity at the molecular level and the resulting clinical impact is a critical step necessary for risk stratification. Defining genomic fingerprint elucidates molecular variation and may improve PCa risk stratification, providing more accurate prognostic information of tumour aggressiveness (or lethality) for prognostic biomarker development. Therefore, we explored transcriptomic differences between patients with indolent disease outcome and patients who developed metastasis post‐radical prostatectomy using genome‐wide expression data in the post radical prostatectomy clinical space before metastatic spread.

Results

Based on differential expression analysis, patients with adverse pathological findings who are at higher risk of developing metastasis have a distinct transcriptomic fingerprint that can be detected on surgically removed prostate specimens several years before metastasis detection. Nearly half of the transcriptomic fingerprint features were non‐coding RNA highlighting their pivotal role in PCa progression. Protein‐coding RNA features in the fingerprint are involved in multiple pathways including cell cycle, chromosome structure maintenance and cytoskeleton organisation. The metastatic transcriptomic fingerprint was determined in independent cohorts verifying the association between the fingerprint and metastatic patients. Further, the fingerprint was confirmed in metastasis lesions demonstrating that the fingerprint represents early metastatic transcriptomic changes, suggesting its utility as a prognostic tool to predict metastasis and provide clinical value in the early radical prostatectomy setting.

Conclusions

Here, we show that transcriptomic patterns of metastatic PCa exist that can be detected early after radical prostatectomy. This metastatic fingerprint has potential prognostic ability that can impact PCa treatment management potentially circumventing the requirements for unnecessary therapies.

Ubiquitin-conjugating enzyme E2C regulates apoptosis-dependent tumor progression of non-small cell lung cancer via ERK pathway

The oncogenic role of ubiquitin-conjugating enzyme E2C (UBE2C) had been identified in some types of human tumors, while the clinical and biological role of UBE2C in non-small cell lung cancer (NSCLC) is still elusive. Here, we have determined the specific role of UBE2C in NSCLC. Western blot and qRT-PCR were used for detecting the mRNA level and protein level of UBE2C in NSCLC samples and cell lines, respectively. Lentivirus product was used to conduct loss of function assay. qRT-PCR array was employed to detect potential downstream genes regulated by UBE2C. As the result, UBE2C mRNA level was approximately threefold overexpression in NSCLC tissues compared with normal tissues, while a sharp change was detected at protein level. Overexpression of UBE2C in lung cancer samples was correlated with advanced pathological stage. UBE2C regulated cell growth in an apoptosis-dependent way. PCR Array analysis revealed that UBE2C regulated the expression of genes associated with tumor growth, apoptosis, and angiogenesis. Furthermore, UBE2C could regulate phospho-ERK1/2 level but not STAT3, YAP, or AKT pathway, which was accompanied with the classic function of ERK pathway in cell growth and apoptosis. In conclusion, our results indicated UBE2C might be a novel therapeutic target in NSCLC.

Expression of regulators of mitotic fidelity are associated with intercellular heterogeneity and chromosomal instability in primary breast cancer

Regulators of transition through mitosis such as SURVIVIN and Aurora kinase A (AURKA) have been previously implicated in the initiation of chromosomal instability (CIN), a driver of intratumour heterogeneity. We investigate the relationship between protein expression of these genes and directly quantified CIN, and their prognostic utility in breast cancer. The expression of SURVIVIN and AURKA was determined by immunohistochemistry in a cohort of 426 patients with primary breast cancer. The association between protein expression and histopathological characteristics, clinical outcome and CIN status, as determined by centromeric FISH and defined by modal centromere deviation, was analysed. Significantly poorer clinical outcome was observed in patients with high AURKA expression levels. Expression of SURVIVIN was elevated in ER-negative relative to ER-positive breast cancer. Both AURKA and SURVIVIN increased expression were significantly associated with breast cancer grade. There was a significant association between increased CIN and both increased AURKA and SURVIVIN expression. AURKA gene amplification was also associated with increased CIN. To our knowledge this is the largest study assessing CIN status in parallel with the expression of the mitotic regulators AURKA and SURVIVIN. These data suggest that elevated expression of AURKA and SURVIVIN, together with AURKA gene amplification, are associated with increased CIN in breast cancer, and may be used as a proxy for CIN in breast cancer samples in the absence of more advanced molecular measurements.

Robust selection of cancer survival signatures from high-throughput genomic data using two-fold subsampling

Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal) subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external) subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable consensus signature. The software is available as an R package rsig at CRAN (http://cran.r-project.org).

Ubiquitin-conjugating enzyme UBE2C is highly expressed in breast microcalcification lesions

Ubiquitin-conjugating enzyme 2C (UBE2C) contributes to ubiquitin-mediated proteasome degradation of cell cycle progression in breast cancer. Microcalcification (MC) is the most common mammographic feature of early breast cancer. In this study, we evaluated whether UBE2C could be a tumor marker of early breast cancer with MC found on screening mammography. UBE2C protein and mRNA expression were measured in breast core biopsy pairs of MC and adjacent non-MC breast tissue from each subject. Immunohistochemistry revealed UBE2C positivity in 69.4% of MC samples and 77.6% negativity in non-MC samples (p<0.0001). On RT-qPCR, 56.1% of malignant MC lesion samples showed high mRNA level of UBE2C and 80% of benign MC lesion samples showed a low level of UBE2C (p = 0.1766). We investigated the carcinogenic role of UBE2C in MCF-7 breast cancer cells with UBE2C knockdown; UBE2C knockdown downregulated cell proliferation and activated the cellular apoptosis pathway to inhibit cell colony formation. Furthermore, UBE2C expression was associated with that of carcinogenic genes human epidermal growth factor receptor type 2 (HER2), cellular c-Ki-ras2 proto-oncogene (KRAS), vascular endothelial growth factor (VEGF), CXC chemokine receptor 4 (CXCR4), C-C motif chemokine 5 (CCL5), neural precursor cell expressed, developmentally downregulated 9 (NEDD9) and Ras homolog family member C (RhoC). UBE2C may be a marker for diagnosis of nonpalpable breast lesions but not benign or malignant tumors in mammography core biopsies. Suppression of UBE2C may be a potential therapy target in breast cancer.

Small activating RNA restores the activity of the tumor suppressor HIC-1 on breast cancer

HIC-1 is a gene that is hypermethylated in cancer, and commonly downregulated in human breast cancer. However, the precise mechanisms and molecular pathways regulated by HIC-1 remain unclear. We assessed HIC-1 expression on a tissue microarray containing 80 cases of breast cancer. We also analyzed its biological function by restoring HIC-1 expression using 5-aza-2′ deoxycytidine (5-CdR) and small-activating RNAs for the reversal of HIC-1 tumor suppressive effects on MCF-7 and MDA-MB-231 cell lines. An Agilent Q44h global expressing microarray was probed after restoring the expression of HIC-1. Data demonstrated that HIC-1 expression was reduced significantly in breast cancer tissues. HIC-1 immunohistochemistry resulted in mean staining scores in cancer tissue and normal ductal epithelia of 3.54 and 8.2, respectively (p<0.01). 5-CdR partially reversed HIC-1 expression, and modulated cell growth and apoptosis. dsHIC1-2998, an saRNA, showed activating efficacy in breast cancer cells. A group of differentially expressed genes were characterized by cDNA microarray. Upon saRNA treatment, genes upregulated included those involved in immune activation, cell cycle interference, the induction of apoptosis, anti-metastasis, and cell differentiation. Downregulated genes included oncogenes and those that play roles in cell invasion, cell growth, and cell division. Our findings may provide valuable resources not only for gene functional studies, but also for potential clinical applications to develop novel drug targets.

Inhibition of ubiquitin conjugating enzyme UBE2C reduces proliferation and sensitizes breast cancer cells to radiation, doxorubicin, tamoxifen and letrozole

PURPOSE

The objective of this study was to determine radiation, doxorubicin, tamoxifen and letrozole sensitivity of breast cancer cells in response to functional inhibition of the ubiquitin conjugating enzyme UBE2C.

METHODS

Taqman Real time PCR was performed to measure UBE2C levels in breast cancer cell lines and control HBL100 and HEK293T cells. A dominant negative form of UBE2C (DN-UBE2C) was used to functionally inhibit wild type UBE2C. Cell proliferation and anchorage independent growth were measured by colorimetric and soft agar assays, respectively. Radiation, doxorubicin, tamoxifen and letrozole responses of the cell lines were assessed by colorimetric and clonogenic assays.

RESULTS

Overexpression of UBE2C was observed in all breast cancer cell lines tested using quantitative real time PCR. UBE2C expression was found to be highest in MDAMB231 and relatively lowest in MCF7 cells, compared to control cells. Both the growth rate and the anchorage independent growth of MCF7 and MDAMB231 cells transfected with DN-UBE2C were significantly reduced compared to cells transfected with vector alone. MCF7 and MDAMB231 cells expressing DN-UBE2C were significantly more sensitive to different doses of radiation and doxorubicin compared to both wild type and vector alone transfected cells. In addition, DN-UBE2C transfected MCF7 cells were more sensitive to inhibition by tamoxifen and letrozole compared to wild type and vector alone transfected cells.

CONCLUSIONS

Our results show that inhibition of UBE2C sensitizes breast cancer cells to radiation, doxorubicin and hormone blocking agents. UBE2C may, therefore, serve as a potential therapeutic target aimed at inducing radiation and chemo sensitization.

UBE2C is a marker of unfavorable prognosis in bladder cancer after radical cystectomy

It has been suggested that ubiquitin-conjugating enzyme E2C (UBE2C, also known as UBCH10) represents a promising cancer biomarker. However, the clinicopathological or prognostic significance as well as the functions of UBE2C in bladder cancer are largely unknown. To investigate the significance of UBE2C expression in bladder cancer, immunohistochemical analysis was performed using a tissue microarray. UBE2C positivity was observed in 51 of 82 (62%) bladder urothelial carcinoma cases treated with radical cystectomy. In contrast, UBE2C was negative in all of the non-neoplastic urothelium examined. UBE2C positivity was significantly associated with higher tumor stage (p=0.0061) and presence of lymphovascular invasion (p=0.0045). In addition, UBE2C positivity was significantly associated with shorter cancer-specific survival after cystectomy (log rank p=0.0017; multivariate hazard ratio, 2.49; 95% confidence interval, 1.09-5.71). Small interfering RNA-mediated suppression of UBE2C in UM-UC-3 bladder cancer cells inhibited cell proliferation in vitro. Taken together, our results suggest that UBE2C is a novel prognostic biomarker as well as a potential therapeutic target in bladder cancer.

bc-GenExMiner 3.0: new mining module computes breast cancer gene expression correlation analyses

We recently developed a user-friendly web-based application called bc-GenExMiner (http://bcgenex.centregauducheau.fr), which offered the possibility to evaluate prognostic informativity of genes in breast cancer by means of a ‘prognostic module’. In this study, we develop a new module called ‘correlation module’, which includes three kinds of gene expression correlation analyses. The first one computes correlation coefficient between 2 or more (up to 10) chosen genes. The second one produces two lists of genes that are most correlated (positively and negatively) to a ‘tested’ gene. A gene ontology (GO) mining function is also proposed to explore GO ‘biological process’, ‘molecular function’ and ‘cellular component’ terms enrichment for the output lists of most correlated genes. The third one explores gene expression correlation between the 15 telomeric and 15 centromeric genes surrounding a ‘tested’ gene. These correlation analyses can be performed in different groups of patients: all patients (without any subtyping), in molecular subtypes (basal-like, HER2+, luminal A and luminal B) and according to oestrogen receptor status. Validation tests based on published data showed that these automatized analyses lead to results consistent with studies’ conclusions. In brief, this new module has been developed to help basic researchers explore molecular mechanisms of breast cancer.

Database URL:http://bcgenex.centregauducheau.fr

Molecular features of triple negative breast cancer cells by genome-wide gene expression profiling analysis

Triple negative breast cancer (TNBC) has a poor outcome due to the lack of beneficial therapeutic targets. To clarify the molecular mechanisms involved in the carcinogenesis of TNBC and to identify target molecules for novel anticancer drugs, we analyzed the gene expression profiles of 30 TNBCs as well as 13 normal epithelial ductal cells that were purified by laser-microbeam microdissection. We identified 301 and 321 transcripts that were significantly upregulated and downregulated in TNBC, respectively. In particular, gene expression profile analyses of normal human vital organs allowed us to identify 104 cancer-specific genes, including those involved in breast carcinogenesis such as NEK2, PBK and MELK. Moreover, gene annotation enrichment analysis revealed prominent gene subsets involved in the cell cycle, especially mitosis. Therefore, we focused on cell cycle regulators, asp (abnormal spindle) homolog, microcephaly-associated (Drosophila) (ASPM) and centromere protein K (CENPK) as novel therapeutic targets for TNBC. Small-interfering RNA-mediated knockdown of their expression significantly attenuated TNBC cell viability due to G1 and G2/M cell cycle arrest. Our data will provide a better understanding of the carcinogenesis of TNBC and could contribute to the development of molecular targets as a treatment for TNBC patients.

Ubiquitin- and ubiquitin-like proteins-conjugating enzymes (E2s) in breast cancer

Breast cancer is the most common malignancy in women and a significant cause of morbidity and mortality. Sub-types of breast cancer defined by the expression of steroid hormones and Her2/Neu oncogene have distinct prognosis and undergo different therapies. Besides differing in their phenotype, sub-types of breast cancer display various molecular lesions that participate in their pathogenesis. BRCA1 is one of the common hereditary cancer predisposition genes and encodes for an ubiquitin ligase. Ubiquitin ligases or E3 enzymes participate together with ubiquitin activating enzyme and ubiquitin conjugating enzymes in the attachment of ubiquitin (ubiquitination) in target proteins. Ubiquitination is a post-translational modification regulating multiple cell functions. It also plays important roles in carcinogenesis in general and in breast carcinogenesis in particular. Ubiquitin conjugating enzymes are a central component of the ubiquitination machinery and are often perturbed in breast cancer. This paper will discuss ubiquitin and ubiquitin-like proteins conjugating enzymes participating in breast cancer pathogenesis, their relationships with other proteins of the ubiquitination machinery and their role in phenotype of breast cancer sub-types.

Dominant negative Ubiquitin-conjugating enzyme E2C sensitizes cervical cancer cells to radiation

PURPOSE

To find the radiation sensitivity of human cervical carcinoma cell lines and to investigate the effect of the dominant negative-Ubiquitin-conjugating enzyme E2C (DN-UBE2C) on cell proliferation and radiation response.

MATERIALS AND METHODS

Radiation sensitivities of human cervical cell lines (SiHa, HeLa, BU25TK, ME 180, and C33A) were analyzed by assessing their cell survival after irradiation by MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assay. Soft agar cloning assay, growth curve and radiation response of DN-UBE2C stably transfected SiHa and HeLa cell lines were assessed by MTS assay and Clonogenic assay.

RESULTS

Difference in sensitivity to radiation was observed among the cervical cancer cell lines studied. SiHa was found to be the most resistant cell line whereas C33A cells were the most sensitive. The growth rate of SiHa and HeLa transfected with DN-UBE2C was significantly reduced compared to vector control. Furthermore, DN-UBE2C-mediated radiosensitivity was correlated with a significant decrease in resistance to radiation by SiHa and HeLa cells after transfection with the DN-UBE2C when compared to control cultures.

CONCLUSION

These results suggested that the Ubiquitin-conjugating enzyme E2C (UBE2C) gene is a potential therapeutic target for cervical cancer treatment.

Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration

BACKGROUND

The Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) checklist consists of 20 items to report for published tumor marker prognostic studies. It was developed to address widespread deficiencies in the reporting of such studies. In this paper we expand on the REMARK checklist to enhance its use and effectiveness through better understanding of the intent of each item and why the information is important to report.

METHODS

REMARK recommends including a transparent and full description of research goals and hypotheses, subject selection, specimen and assay considerations, marker measurement methods, statistical design and analysis, and study results. Each checklist item is explained and accompanied by published examples of good reporting, and relevant empirical evidence of the quality of reporting. We give prominence to discussion of the 'REMARK profile', a suggested tabular format for summarizing key study details.

SUMMARY

The paper provides a comprehensive overview to educate on good reporting and provide a valuable reference for the many issues to consider when designing, conducting, and analyzing tumor marker studies and prognostic studies in medicine in general. To encourage dissemination of the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration, this article has also been published in PLoS Medicine.

The chemokine receptor CXCR4 as a novel independent prognostic marker for node-positive breast cancer patients

BACKGROUND

Node-positive breast cancer patients are a high-risk group. However, not all such patients will succumb to the disease. The molecular basis for this biologic heterogeneity is poorly understood. The chemokine receptor CXCR4 is a marker of metastatic disease. Its prognostic role in node-positive patients is unknown. We postulate that high CXCR4 overexpression in node-positive breast cancer specimens predicts a poor outcome.

METHODS

185 node-positive breast cancer patients were evaluated. All had standardized treatment and surveillance protocols. CXCR4 levels were detected with Western blots. Results were quantified against 1 µg of HeLa cells. CXCR4 expression was defined as high (≥ 7.5-fold) or low (<7.5-fold). Primary endpoints were cancer recurrence and death. Statistical analyses were Kaplan-Meier curves, log-rank test, and Cox proportional hazard model, with a P-value of ≤ 0.05 as significant.

RESULTS

The mean follow-up time was 54 months; 148 patients (80%) had low CXCR4 and 37 patients (20%) had high CXCR4 level. The 5-year overall survival (OS) for the low and high CXCR4 group was 69% and 57%, respectively (P=0.02). The 5-year disease-free survival (DFS) for the low and high CXCR4 group was 62% and 53%, respectively (P=0.08). On multivariate analysis, T stage (P=0.001) and grade (P=0.04) were independent predictors of DFS, while T stage (P=0.005), grade (P=0.024), and CXCR4 level (P=0.01) were independent predictors of OS.

CONCLUSION

High CXCR4 level in cancer specimens independently predicts a poor outcome for patients with node-positive breast cancer.

Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): explanation and elaboration

The REMARK (Reporting Recommendations for Tumor Marker Prognostic Studies) guideline includes a checklist which aims to improve the reporting of these types of studies. Here, we expand on the REMARK checklist to enhance its use and effectiveness through better understanding of the intent of each item and why the information is important to report. Each checklist item of the REMARK guideline is explained in detail and accompanied by published examples of good reporting. The paper provides a comprehensive overview to educate on good reporting and provide a valuable reference of issues to consider when designing, conducting, and analyzing tumor marker studies and prognostic studies in medicine in general.

Ubiquitin-conjugating enzyme UBE2C: molecular biology, role in tumorigenesis, and potential as a biomarker

Ubiquitin-conjugating enzyme 2C (UBE2C) participates in cell cycle progression and checkpoint control by targeted degradation of short-lived proteins. As a conjugating enzyme, it directs polyubiquitination to preferred lysine in the substrates. In addition to its well-known role in cyclin B destruction that is essential for exit from mitosis, UBE2C also plays an important role in mitotic spindle checkpoint control. Cells overexpressing UBE2C ignore the mitotic spindle checkpoint signals and lose genomic stability, which is a hallmark of cancer. UBE2C expression is upregulated upon malignant transformation, and amplification of UBE2C is often seen at the chromosome level in cancers in a manner similar to c-Myc, which is directly upstream of UBE2C. UBE2C levels are upregulated in a wide range of solid tumors and hematological malignancies. The level of expression correlates with the aggressiveness of the tumor. High UBE2C expression is predictive of poor survival and perhaps high risk for relapse. UBE2C immunochemistry may be integrated into the diagnosis of thyroid malignancy and gliomas. This minireview summarizes what is known about the function of UBE2C focusing on its role in the regulation of spindle assembly checkpoint, its part in tumorigenesis, and its potential as a tumor marker for various cancers.

Prognostic significance of UBE2C mRNA expression in high-risk early breast cancer. A Hellenic Cooperative Oncology Group (HeCOG) Study

BACKGROUND

The ubiquitin-proteasome system (UPS) plays a pivotal role in tumorigenesis. Components of the UPS have recently been implicated in breast cancer progression. In the present study, we sought to explore the prognostic and/or predictive significance of UBE2C messenger RNA (mRNA) expression on disease-free survival (DFS) and overall survival (OS) in high-risk operable breast cancer patients.

METHODS

Five hundred and ninety-five high-risk breast cancer patients were treated in a two-arm trial evaluating postoperative, dose-dense sequential chemotherapy with epirubicin followed by CMF (cyclophosphamide, methotrexate and 5-fluorouracil) with or without paclitaxel (Taxol). RNA was extracted from 313 formalin-fixed primary tumor tissue samples followed by one-step quantitative RT-PCR for assessment of mRNA expression of UBE2C.

RESULTS

High UBE2C mRNA expression was associated with poor DFS (Wald's P = 0.003) and OS (Wald's P = 0.005). High tumor grade, as well as high Ki67 protein expression, was more frequent in the high-expression group of UBE2C. Results of the Cox multivariate regression analysis revealed that high UBE2C mRNA expression remained an independent adverse prognostic factor for relapse (P = 0.037) and death (P = 0.05).

CONCLUSIONS

High UBE2C mRNA expression was found to be of adverse prognostic significance in high-risk breast cancer patients. These findings need to be validated in larger cohorts.

Validation of tumor-associated macrophage ferritin light chain as a prognostic biomarker in node-negative breast cancer tumors: A multicentric 2004 national PHRC study

Novel prognostic biomarkers are imperatively needed to help direct treatment decisions by typing subgroups of node-negative breast cancer patients. Large screening of different biological compartments, such as the proteome, by means of high throughput techniques may greatly help scientists to find such markers. The present retrospective multicentric study included 268 node-negative breast cancer patients. We used a proteomic approach of SELDI-TOF-MS screening to identify differentially expressed cytosolic proteins with prognostic impact. The screening cohort was composed of 198 patients. Seventy supplementary patients were included for validation. Immunohistochemistry (IHC) and immunoassay (IA) were run to confirm the prognostic role of the marker identified by SELDI-TOF-MS screening. IHC was also used to explore links between selected marker and epithelial-mesenchymal transition (EMT)-like, proliferation and macrophage markers. Ferritin light chain (FTL) was identified as an independent prognostic marker (HR = 1.30-95% CI: 1.10-1.50, p = 0.001). Validation step by means of IHC and IA confirmed the prognostic value of FTL level. CD68 IHC showed that FTL was stored in tumor-associated macrophages (TAM), which exhibit an M2-like phenotype. We report here, first, the validation of FTL as a breast tumor prognostic biomarker in node-negative patients, and second, the fact that FTL is stored in TAM.

CCI-779 inhibits cell-cycle G2-M progression and invasion of castration-resistant prostate cancer via attenuation of UBE2C transcription and mRNA stability

The cell-cycle G(2)-M phase gene UBE2C is overexpressed in various solid tumors including castration-resistant prostate cancer (CRPC). Our recent studies found UBE2C to be a CRPC-specific androgen receptor (AR) target gene that is necessary for CRPC growth, providing a potential novel target for therapeutic intervention. In this study, we showed that the G(1)-S cell-cycle inhibitor-779 (CCI-779), an mTOR inhibitor, inhibited UBE2C mRNA and protein expression in AR-positive CRPC cell models abl and C4-2B. Treatment with CCI-779 significantly decreased abl cell proliferation in vitro and in vivo through inhibition of cell-cycle progression of both G(2)-M and G(1)-S phases. In addition, exposure of abl and C4-2B cells to CCI-779 also decreased UBE2C-dependent cell invasion. The molecular mechanisms for CCI-779 inhibition of UBE2C gene expression involved a decreased binding of AR coactivators SRC1, SRC3, p300, and MED1 to the UBE2C enhancers, leading to a reduction in RNA polymerase II loading to the UBE2C promoter, and attenuation of UBE2C mRNA stability. Our data suggest that, in addition to its ability to block cell-cycle G(1) to S-phase transition, CCI-779 causes a cell-cycle G(2)-M accumulation and an inhibition of cell invasion through a novel UBE2C-dependent mechanism, which contributes to antitumor activities of CCI-779 in UBE2C overexpressed AR-positive CRPC.

DNA methylation patterns in luminal breast cancers differ from non-luminal subtypes and can identify relapse risk independent of other clinical variables

The diversity of breast cancers reflects variations in underlying biology and affects the clinical implications for patients. Gene expression studies have identified five major subtypes- Luminal A, Luminal B, basal-like, ErbB2+ and Normal-Like. We set out to determine the role of DNA methylation in subtypes by performing genome-wide scans of CpG methylation in breast cancer samples with known expression-based subtypes. Unsupervised hierarchical clustering using a set of most varying loci clustered the tumors into a Luminal A majority (82%) cluster, Basal-like/ErbB2+ majority (86%) cluster and a non-specific cluster with samples that were also inconclusive in their expression-based subtype correlations. Contributing methylation loci were both gene associated loci (30%) and non-gene associated (70%), suggesting subtype dependant genome-wide alterations in the methylation landscape. The methylation patterns of significant differentially methylated genes in luminal A tumors are similar to those identified in CD24 + luminal epithelial cells and the patterns in basal-like tumors similar to CD44 + breast progenitor cells. CpG islands in the HOXA cluster and other homeobox (IRX2, DLX2, NKX2-2) genes were significantly more methylated in Luminal A tumors. A significant number of genes (2853, p < 0.05) exhibited expression-methylation correlation, implying possible functional effects of methylation on gene expression. Furthermore, analysis of these tumors by using follow-up survival data identified differential methylation of islands proximal to genes involved in Cell Cycle and Proliferation (Ki-67, UBE2C, KIF2C, HDAC4), angiogenesis (VEGF, BTG1, KLF5), cell fate commitment (SPRY1, OLIG2, LHX2 and LHX5) as having prognostic value independent of subtypes and other clinical factors.

Diagnostic value and prognostic significance of plasmatic proteasome level in patients with melanoma

Plasmatic proteasome (p-proteasome) also called circulating proteasome has recently been described as a tumor marker. We investigated the diagnostic and prognostic accuracies of p-proteasome levels in a melanoma population classified according to the American Joint Committee on Cancer staging system. Using an ELISA test, we measured p-proteasome levels in 90 patients and 40 controls between March 2003 and March 2008. The subunit composition of p-proteasomes was determined in metastatic melanoma by proteomic analysis. The mean p-proteasome levels were correlated with stages (P < 0.0001; r(S) = 0.664). They were significantly higher in patients with stage IV and stage III with lymph node metastasis (9187 ± 1294 and 5091 ± 454 ng/ml, respectively) compared to controls (2535 ± 187 ng/ml; P < 0.001), to stage I/II (2864 ± 166 ng/ml; P < 0.001) and to stage III after curative lymphadenectomy (2859 ± 271 ng/ml; P < 0.001). The diagnostic accuracy of p-proteasome was evaluated by receiver operating characteristic analysis. With a cut-off of 4300 ng/ml, diagnostic specificity and sensitivity of p-proteasome for regional or visceral metastases were respectively 96.3% and 72.2%. In univariate analysis, high p-proteasome levels (>4300 ng/ml) were significantly correlated with an increased risk of progression [hazard ratio (HR) = 7.34; 95% CI 3.54-15.21, P < 0.0001] and a risk of death (HR = 5.92; 95% CI 2.84-12.33, P < 0.0001). In multivariate analysis, high p-proteasome levels were correlated with a poorer clinical outcome in the subgroup analysis limited to patients with disease stages I, II and III. Proteomic analysis confirmed the presence of all proteasome and immunoproteasome subunits. Taken together, these results indicate that p-proteasomes are a new marker for metastatic dissemination in patients with melanoma.

Overexpression of the novel human gene, UBE2Q2, in breast cancer

The ubiquitin-proteasome pathway facilitates the degradation of damaged proteins and regulates growth and stress response. This pathway is activated in various cancers, including breast cancer. We have previously reported that the novel human gene, UBE2Q2, is a putative ubiquitin-conjugating enzyme that is located on chromosome 15 and is overexpressed in tumor mass and invasive epithelium in head and neck squamous-cell carcinoma. Here, real-time polymerase chain reaction was used to investigate the expression levels of UBE2Q2 gene in a collection of 21 breast cancer tissues matched with normal adjacent counterparts. Immunohistochemistry and Western blot testing were also performed on formalin-fixed, paraffin-embedded tissue sections by using a rabbit polyclonal antibody that we generated against an amino acid sequence predicted from the DNA sequence of UBE2Q2 gene. In the 21 cases investigated, a high increase in the expression of UBE2Q2 mRNA was found in 8 breast cancers (38.1%), a moderately increased UBE2Q2 expression was observed in 7 cases (33.3%), and no significant changes were detected in 6 cases (28.6%) of tumor samples when compared with corresponding normal tissues. Consistently, a higher level of immunoreactivity for UBE2Q2 protein was detected in invasive epithelium of cancerous tissues when compared with that in the normal epithelium. Our data suggest that the novel human gene UBE2Q2 may have implications for pathogenesis of breast cancer and could be used in molecular diagnosis purposes in the future.