CDK1 and CDK2 activity is a strong predictor of renal cell carcinoma recurrence

Long Noncoding RNA PSMB8-AS1 Mediates the Tobacco-Carcinogen-Induced Transformation of a Human Bronchial Epithelial Cell Line by Regulating Cell Cycle

Lung cancer is the main cause of cancer deaths around the world. Nitrosamine 4-(methyl nitrosamine)-1-(3-pyridyl)-1-butanone (NNK) is a tobacco-specific carcinogen of lung cancer. Abundant evidence implicates long noncoding RNAs (lncRNAs) in tumorigenesis. Yet, the effects and mechanisms of lncRNAs in NNK-induced carcinogenesis are still unclear. In this study, we discovered that NNK-induced transformed Beas-2B cells (Beas-2B-NNK) showed increased cell migration and proliferation while decreasing rates of apoptosis. RNA sequencing and differentially expressed lncRNAs analyses showed that lncRNA PSMB8-AS1 was obviously upregulated. Interestingly, silencing the lncRNA PSMB8-AS1 in Beas-2B-NNK cells reduced cell proliferation and migration and produced cell cycle arrest in the G2/M phase along with a decrease in CDK1 expression. Conclusively, our results demonstrate that lncRNA PSMB8-AS1 could promote the malignant characteristics of Beas-2B-NNK cells by regulating CDK1 and affecting the cell cycle, suggesting that it may supply a new prospective epigenetic mechanism for lung cancer.

Targeting apoptosis in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal cancer, accounting for approximately 80% of all renal cell cancers. Due to its exceptional inter- and intratumor heterogeneity, it is highly resistant to conventional systemic therapies. Targeting the evasion of cell death, one of cancer's hallmarks, is currently emerging as an alternative strategy for ccRCC. In this article, we review the current state of apoptosis-inducing therapies against ccRCC, including antisense oligonucleotides, BH3 mimetics, histone deacetylase inhibitors, cyclin-kinase inhibitors, inhibitors of apoptosis protein antagonists, and monoclonal antibodies. Although preclinical studies have shown encouraging results, these compounds fail to improve patients' outcomes significantly. Current evidence suggests that inducing apoptosis in ccRCC may promote tumor progression through apoptosis-induced proliferation, anastasis, and apoptosis-induced nuclear expulsion. Therefore, re-evaluating this approach is expected to enable successful preclinical-to-clinical translation.

The role of RNA-modifying proteins in renal cell carcinoma

Gene expression is one of the most critical cellular processes. It is controlled by complex mechanisms at the genomic, epigenomic, transcriptomic, and proteomic levels. Any aberration in these mechanisms can lead to dysregulated gene expression. One recently discovered process that controls gene expression includes chemical modifications of RNA molecules by RNA-modifying proteins, a field known as epitranscriptomics. Epitranscriptomics can regulate mRNA splicing, nuclear export, stabilization, translation, or induce degradation of target RNA molecules. Dysregulation in RNA-modifying proteins has been found to contribute to many pathological conditions, such as cancer, diabetes, obesity, cardiovascular diseases, and neurological diseases, among others. This article reviews the role of epitranscriptomics in the pathogenesis and progression of renal cell carcinoma. It summarizes the molecular function of RNA-modifying proteins in the pathogenesis of renal cell carcinoma.

Network Pharmacology and Experimental Validation to Explore the Effect and Mechanism of Kanglaite Injection Against Triple-Negative Breast Cancer

Purpose

Kanglaite injection (KLTi), made of Coix seed oil, has been shown to be effective in the treatment of numerous cancers. However, the anticancer mechanism requires further exploration. This study aimed to investigate the underlying anticancer mechanisms of KLTi in triple-negative breast cancer (TNBC) cells.

Methods

Public databases were searched for active compounds in KLTi, their potential targets and TNBC-related targets. KLTi's core targets and signaling pathways were determined through compound-target network, protein-protein interaction (PPI) network, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was carried out to predict the binding activity between active ingredients and key targets. In vitro experiments were conducted to further validate the predictions of network pharmacology.

Results

Fourteen active components of KLTi were screened from the database. Fifty-three candidate therapeutic targets were selected, and bioinformatics analysis was performed to identify the top two active compounds and three core targets. GO and KEGG enrichment analyses indicated that KLTi exerts therapeutic effects on TNBC through the cell cycle pathway. Molecular docking results showed that the main compounds of KLTi exhibited good binding activity to key target proteins. Results from in vitro experiments showed that KLTi inhibited proliferation and migration of TNBC cell lines 231 and 468, induced apoptosis, blocked cells in the G2/M phase, downregulated the mRNA expression of seven G2/M phase-related genes cyclin-dependent kinase 1 (CDK1), cyclin-dependent kinase 2 (CDK2), and checkpoint kinase 1 (CHEK1), cell division cycle 25A (CDC25A), cell division cycle 25B (CDC25B), maternal embryonic leucine zipper kinase (MELK), and aurora kinase A (AURKA), as well as downregulated CDK1 protein expression and up-regulated protein expression of Phospho-CDK1.

Conclusion

By utilizing network pharmacology, molecular docking, and in vitro experiments, KLTi was confirmed to have anti-TNBC effects by arresting cell cycle and inhibiting CDK1 dephosphorylation.

Adjuvant Therapy for High-Risk Localized Renal Cell Carcinoma: Current Landscape and Future Direction

Locally and regionally advanced renal cell carcinoma (RCC) can recur at high rates even after visually complete resection of primary disease. Both targeted therapies and immunotherapies represent potential agents that might help reduce recurrence of RCC in these patients. This paper reviews the current body of evidence defining their potential impact and examines the large Phase III randomized clinical trials that have been performed to assess the safety and efficacy of these systemic therapies in the adjuvant setting. Given that the findings from these trials have been predominantly negative, this paper also explores the role of other potential adjuvant agents, including single and combination agent targeted therapies and immunotherapies, whose use is currently limited to metastatic RCC. Finally, the use of radiation therapy and the use of advanced imaging modalities in RCC are also considered.

Discovery of pathway-independent protein signatures associated with clinical outcome in human cancer cohorts

Proteomic data provide a direct readout of protein function, thus constituting an information-rich resource for prognostic and predictive modeling. However, protein array data may not fully capture pathway activity due to the limited number of molecules and incomplete pathway coverage compared to other high-throughput technologies. For the present study, our aim was to improve clinical outcome prediction compared to published pathway-dependent prognostic signatures for The Cancer Genome Atlas (TCGA) cohorts using the least absolute shrinkage and selection operator (LASSO). RPPA data is particularly well-suited to the LASSO due to the relatively low number of predictors compared to larger genomic data matrices. Our approach selected predictors regardless of their pathway membership and optimally combined their RPPA measurements into a weighted risk score. Performance was assessed and compared to that of the published signatures using two unbiased approaches: 1) 10 iterations of threefold cross-validation for unbiased estimation of hazard ratio and difference in 5-year survival (by Kaplan-Meier method) between predictor-defined high and low risk groups; and 2) a permutation test to evaluate the statistical significance of the cross-validated log-rank statistic. Here, we demonstrate strong stratification of 445 renal clear cell carcinoma tumors from The Cancer Genome Atlas (TCGA) into high and low risk groups using LASSO regression on RPPA data. Median cross-validated difference in 5-year overall survival was 32.8%, compared to 25.2% using a published receptor tyrosine kinase (RTK) prognostic signature (median hazard ratios of 3.3 and 2.4, respectively). Applicability and performance of our approach was demonstrated in three additional TCGA cohorts: ovarian serous cystadenocarcinoma (OVCA), sarcoma (SARC), and cutaneous melanoma (SKCM). The data-driven LASSO-based approach is versatile and well-suited for discovery of new protein/disease associations.

Englerin A Rewires Phosphosignaling via Hsp27 Hyperphosphorylation to Induce Cytotoxicity in Renal Cancer Cells

Englerin A (EA) is a small-molecule natural product with selective cytotoxicity against renal cancer cells. EA has been shown to induce apoptosis and cell death through cell-cycle arrest and/or insulin signaling pathways. However, its biological mode of action or targets in renal cancer remains enigmatic. In this study, we employed advanced mass spectrometry-based phosphoproteomics approaches to identify EA's functional roles in renal cancer. We identified 10,940 phosphorylation sites, of which 706 sites exhibited EA-dependent phosphorylation changes. Integrated analysis of motifs and interaction networks suggested activation of stress-activated kinases including p38 upon EA treatment. Of note, a downstream target of p38, Hsp27, was found to be hyperphosphorylated on multiple sites upon EA treatment. Among these, a novel site Ser65 on Hsp27, which was further validated by targeted proteomics, was shown to be crucial for EA-induced cytotoxicity in renal cancer cells. Taken together, these data reveal the complex signaling cascade that is induced upon EA treatment and importantly provide insights into its effects on downstream molecular signaling.

Synthetic lethality of cyclin-dependent kinase inhibitor Dinaciclib with VHL-deficiency allows for selective targeting of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (CC-RCC) remains one of the most deadly forms of kidney cancer despite recent advancements in targeted therapeutics, including tyrosine kinase and immune checkpoint inhibitors. Unfortunately, these therapies have not been able to show better than a 16% complete response rate. In this study we evaluated a cyclin-dependent kinase inhibitor, Dinaciclib, as a potential new targeted therapeutic for CC-RCC. In vitro, Dinaciclib showed anti-proliferative and pro-apoptotic effects on CC-RCC cell lines in Cell Titer Glo, Crystal Violet, FACS-based cell cycle analysis, and TUNEL assays. Additionally, these responses were accompanied by a reduction in phospho-Rb and pro-survival MCL-1 cell signaling responses, as well as the induction of caspase 3 and PARP cleavage. In vivo, Dinaciclib efficiently inhibited primary tumor growth in an orthotopic, patient-derived xenograft-based CC-RCC mouse model. Importantly, Dinaciclib targeted both CD105⁺ cancer stem cells (CSCs) and CD105⁻ non-CSCs in vivo. Moreover, normal cell lines, as well as a CC-RCC cell line with re-expressed von-Hippel Lindau (VHL) tumor suppressor gene, were protected from Dinaciclib-induced cytotoxicity when not actively dividing, indicating an effective therapeutic window due to synthetic lethality of Dinaciclib treatment with VHL loss. Thus, Dinaciclib represents a novel potential therapeutic for CC-RCC.

Clear Cell Renal Carcinoma: MicroRNAs With Efficacy in Preclinical In Vivo Models

In order to identify new targets and treatment modalities for clear cell renal carcinoma, we surveyed the literature with respect to microRNAs involved in this disease. In this review, we have focused on up- and down-regulated miRs which mediate efficacy in preclinical clear-cell renal carcinoma-related in vivo models. We have identified 10 up-regulated and 33 down-regulated micro-RNAs according to this criterion. As proof-of-concept, micro-RNAs interfering with VEGF (miR-205p) and mTOR (mir-99a) pathways, which are modulated by approved drugs for this disease, have been identified. miRs targeting hypoxia induced factor-2α (HIF-2α) (miR-145), E3 ubiquitinylases speckle-type POZ protein (SPOP) (miR 520/372/373) and casitas B-lineage lymphoma (CBL) (miR-200a-3p), interfere with druggable targets. Further identified miRs interfere with cell-cycle dependent kinases, such as CDK2 (miR-200c), CDK4, 6 (miR-1) and CDK4, 9 (206c). Transmembrane receptor Ral interacting protein of 76 kD (RLIP76), targeted by mir-137, has emerged as another important target for ccRCC. Additional miRs and their targets merrying further preclinical validation are discussed.

Computational study to evaluate the potency of phytochemicals in Boerhavia diffusa and the impact of point mutation on cyclin-dependent kinase 2-associated protein 1

A protein's function is closely related to its structural properties. Mutations can affect the functionality of a protein. Different cancer tissues have found disordered expression of the cyclin-dependent kinase 2-associated Protein 1 (CDK2AP1) gene. A protein molecule's conformational flexibility affects its interaction with phytochemicals and their biological partners at various levels. Boerhavia diffusa has been investigated most extensively for its medicinal activities like anticancer properties. It contains many bioactive compounds like Boeravinone A, Boeravinone B, Boeravinone C, Boeravinone D, Boeravinone E, Boeravinone F, Boeravinone G, Boeravinone H, Boeravinone I and Boeravinone J. We have studied to analyse the binding efficacy properties as well as essential dynamic behaviour, free energy landscape of both the native and mutant protein CDK2AP1 with bioactive compounds from Boerhavia diffusa plant extracts through computational approaches by homology modelling, docking and molecular dynamics simulation. From the molecular docking study, we found that. Boeravinone J have best binding affinity (-7.9 kcal/mol) towards the native protein of CDKAP1 compared to others phytochemicals. However, we found the binding energy for H23R and C105R (mutation point) -7.8 and -7.6 kcal/mol, respectively. A single minima energy point (from 100 ns molecular dynamics simulation study) was found in the H23R mutant with Boeravinone J complex suggested that minimum structural changes with less conformational mobility compared C105A mutant model.Communicated by Ramaswamy H. Sarma.

Development of cancer prognostic signature based on pan-cancer proteomics

Utilizing genomic data to predict cancer prognosis was insufficient. Proteomics can improve our understanding of the etiology and progression of cancer and improve the assessment of cancer prognosis. And the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has generated extensive proteomics data of the vast majority of tumors. Based on CPTAC, we can perform a proteomic pan-carcinoma analysis. We collected the proteomics data and clinical features of cancer patients from CPTAC. Then, we screened 69 differentially expressed proteins (DEPs) with R software in five cancers: hepatocellular carcinoma (HCC), children’s brain tumor tissue consortium (CBTTC), clear cell renal cell carcinoma (CCRC), lung adenocarcinoma (LUAD) and uterine corpus endometrial carcinoma (UCEC). GO and KEGG analysis were performed to clarify the function of these proteins. We also identified their interactions. The DEPs-based prognostic model for predicting over survival was identified by least absolute shrinkage and selection operator (LASSO)-Cox regression model in training cohort. Then, we used the time-dependent receiver operating characteristics analysis to evaluate the ability of the prognostic model to predict overall survival and validated it in validation cohort. The results showed that the DEPs-based prognostic model could accurately and effectively predict the survival rate of most cancers.

Mining therapeutic and prognostic significance of STATs in renal cell carcinoma with bioinformatics analysis

Renal cell carcinoma is one of the most common malignancies with high morbidity and mortality. STAT proteins play a significant role in cell biological behavior and immune response associated with cancer progression. In our study, the datasets analyzed for the expression and potential functions can be found in several bioinformatics analysis tools. We found that STAT1/2/4/6 were upregulated in RCC while STAT3/5B were downregulated. The expression of STAT2/4/5B were significantly associated with the pathological stage of RCC patients. RCC patients with high expression of STAT2/4 and low/medium expression of STAT5B had a poor overall survival. The function of STATs and the neighboring genes mainly enriched in JAK-STAT signaling pathway and NOD-like receptor signaling pathway. Several transcription factor, kinase, and miRNA targets were identified. Close correlations were obtained between immune cell infiltration and STATs in RCC. Our results have provided novel insights for the selection of immunotherapeutic targets and prognostic biomarkers.

Screening and verifying key genes with poor prognosis in colon cancer through bioinformatics analysis

Background

Colon cancer (CC) is one of the tumors with high morbidity and mortality in the world, and has a trend of younger generation. The molecular level of CC has not been fully elaborated. The purpose of this study is to screen and identify important genes with poor prognosis and their mechanisms at different levels.

Methods

GSE74602 and GSE10972 gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. There were 58 normal tissues and 58 CC tissues. Differentially expressed genes (DEGs) were screened out by using the GEO2R tool and Venn diagram. Then, the DAVID online database was used to perform the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Six hub genes with the highest correlation were screened out after the modular analysis of the protein-protein interaction (PPI) network by using Cytoscape’s MCODE plug-in. Finally, the overall survival of key hub genes and potential pathways were verified in GEPIA and UALCAN database.

Results

A total of 78 up-regulated DEGs were enriched in the mitotic nuclear division, cell division, cell proliferation, anaphase-promoting complex-dependent catabolic process and G2/M transition of the mitotic cell cycle. In total, 130 down-regulated DEGs were enriched in muscle contraction, bicarbonate transport, cellular response to zinc ion, negative regulation of growth, negative regulation of leukocyte apoptotic process and one-carbon metabolic process. CDK1, CCNB1, CDC20, AURKA, CCNA2 and TOP2A were the top six hub genes, mainly enriched in cell cycle pathways. Among them, CCNB1, CDK1, CDC20, CCNA2 were enriched in the G2/M phase. GEPIA and UALCAN database confirmed that CCNA2 and CCNB1 had a significant relationship with the poor prognosis of CC patients. Meanwhile, there was a positive correlation between the two.

Conclusions

Screening out genes with abnormal expression in CC help understand the initiation and progression of CC at the molecular level and explore candidate biomarkers for diagnosis, treatment and prognosis.

Proteomic analysis reveals distinctive protein expression patterns of thrombus in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a type of malignant tumor of the urinary system. The renal vein or vena cava thrombus can be found in a subset of ccRCC patients in whom it leads to worse prognosis. However, the protein expression profile and molecular features of ccRCC thrombus remain largely unclear. Here, a comparative proteomic analysis was performed using the 2D-LC-MS strategy for the thrombus-tumor-normal tissue triples of 15 ccRCC patients. Statistical analysis, GO enrichment analysis, protein-protein interaction network construction, and mRNA-based survival analysis were used to interpret the proteomic data. Three dysregulated proteins, GGT5 (gamma-glutamyl transferase 5), KRT7 (keratin 7) and CFHR1 (complement factor H related 1), were analyzed using western blot (WB) and immunohistochemistry (IHC) to validate the reliability of the proteomic analysis. The result of this analysis revealed 251 dysregulated proteins, which could be divided into 11 clusters depending on the changing trends, among the thrombus, tumor, and normal tissues. Several pathways and regulation networks were found to be associated with the thrombus, and some dysregulated proteins showed potential values for prognosis prediction. WB and IHC results were in accordance with the proteomic results, further validating the reliability of this study. In conclusion, our findings provide an overview of the thrombus at the molecular level as well as valuable information for further pathological studies or research on biomarkers and therapeutic targets.

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Proteomic analysis was performed using thrombus-tumor-normal tissue triples of 15 ccRCC patients.

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Statistical and bioinformatic analyses were performed to better interpret the proteomic data.

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Our findings provided an overview of the molecular landscape of thrombus.

Inhibition of the CDK4/6-Cyclin D-Rb Pathway by Ribociclib Augments Chemotherapy and Immunotherapy in Renal Cell Carcinoma

Renal cell carcinoma (RCC) is the most aggressive type of genitourinary cancer and is resistant to current therapies. Identifying drugs that enhance the efficacy of RCC standard-of-care drugs at sublethal concentrations is an alternative therapeutic strategy. Ribociclib is an orally available cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor that is approved for the treatment of breast cancer. In this work, we demonstrate that ribociclib at clinically achievable concentrations inhibits proliferation of 7 out of 9 tested RCC cell lines, with IC₅₀ range from 76 to 280 nM. In addition, ribociclib induces apoptosis of RCC cells, but with less potency compared to its antiproliferative activity. The combination of ribociclib with chemotherapeutic or immunotherapeutic agents is synergistic in RCC cell lines. Of note, ribociclib demonstrates selective anti-RCC activity by sparing normal kidney cells and fibroblast cells. Consistent with the in vitro findings, ribociclib inhibits RCC growth at the dosage that does not lead to toxicity in mice and enhances the in vivo efficacy of RCC standard-of-care drugs. Mechanistically, we show that ribociclib remarkably inhibits phosphorylation of retinoblastoma protein (Rb) at various sites, leading to the suppression of transcription of E2F target genes in RCC cells. Our findings clearly demonstrate the potency and selectivity of ribociclib in RCC preclinical models, via inhibition of the CDK4/6-cyclin D/Rb pathway. Our findings support a clinical trial for the combination of ribociclib with chemo/immunotherapy in RCC.

CDK1 dependent phosphorylation of hTERT contributes to cancer progression

The telomerase reverse transcriptase is upregulated in the majority of human cancers and contributes directly to cell transformation. Here we report that hTERT is phosphorylated at threonine 249 during mitosis by the serine/threonine kinase CDK1. Clinicopathological analyses reveal that phosphorylation of hTERT at threonine 249 occurs more frequently in aggressive cancers. Using CRISPR/Cas9 genome editing, we introduce substitution mutations at threonine 249 in the endogenous hTERT locus and find that phosphorylation of threonine 249 is necessary for hTERT-mediated RNA dependent RNA polymerase (RdRP) activity but dispensable for reverse transcriptase and terminal transferase activities. Cap Analysis of Gene Expression (CAGE) demonstrates that hTERT phosphorylation at 249 regulates the expression of specific genes that are necessary for cancer cell proliferation and tumor formation. These observations indicate that phosphorylation at threonine 249 regulates hTERT RdRP and contributes to cancer progression in a telomere independent manner.

Regulated telomerase reverse transcriptase (hTERT) activity is common in human tumors. Here, the authors show that hTERT is phosphorylated by CDK1 and that this event is necessary for hTERT-mediated RNA dependent RNA polymerase activity but not for reverse transcriptase and terminal transferase activities.

Screening for genes and subnetworks associated with atypical teratoid/rhabdoid tumors using bioinformatics analysis

Objectives: Atypical teratoid/rhabdoid tumors (AT/RTs) are rare, fast-growing lesions of central nervous system and their prognosis is poor. Nowadays, multimodal managements, including surgery, chemotherapy and radiation therapy are advocated; however, low survival rate and severe neurocognitive toxicity of chemotherapy as well as the irreversible long-term sequelae of irradiation in infants and young children with AT/RTs are alarming. The aim of our study is to provide valid biological information for more tailored advance therapy for these lesions.Methods: Gene expression profile of GSE94349 was downloaded from GEO database and was analyzed using limma R package. Function and enrichment analyses of DEGs were performed based on DAVID database. PPI network construction, hub gene selection and module analysis were conducted in Cytoscape software.Results: In this study, 224 up-regulated genes and 572 down-regulated genes were selected as DEGs. The up-regulated genes were mainly enriched in molecular function and cell component, which mainly included protein binding and nucleus, respectively. The down-regulated DEGs were significantly involved in cell component such as plasma membrane and integral component of membrane. Cell cycle and retrograde endocannabinoid signaling were the main KEGG pathway of up and down DEGs, respectively. CDK1, CCNA2, CDC20, TOP2A were identified as hub genes and two significant network modules were also obtained.Conclusions: Our study may help to further understand the molecular characteristics and provide more tailored targets for future treatment of AT/RTs. Hub genes CDK1, CCNA2, CDC20, TOP2A as well as cell cycle signaling pathway may be new more tailored targets for future treatment of AT/RTs.

A novel prognostic nomogram based on 5 long non-coding RNAs in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common and invasive histological subtype of all kidney malignancies, with high levels of incidence and mortality. In the present study, long non-coding (lnc)RNA expression profiles of patients with ccRCC from The Cancer Genome Atlas database were comprehensively analyzed to identify differentially expressed lncRNAs (DElncRNAs). The patients with ccRCC were then divided into training and validation cohorts. Univariate and LASSO regression analyses were performed to select the most significant survival-associated candidate DElncRNAs in the training cohort. Multivariate Cox regression analysis was then performed to develop a risk score formula and a prognostic nomogram for predicting 3- and 5-year overall survival (OS). The accuracies of the nomogram predictions were evaluated by determining the area under the receiver operating characteristic curve (AUC) and a calibration plot. Finally, functional enrichment analysis and protein-protein interaction network prediction were implemented to predict the functions and molecular mechanisms of the candidate DElncRNAs in ccRCC. A total of 1,553 DElncRNAs were identified, and 5 candidate DElncRNAs (AC026992.2, AC245041.2, LINC00524, LINC01956 and LINC02080) were included in the nomogram. The AUC values for 3- and 5-year overall survival in the training cohort were 0.768 and 0.814, respectively, which were increased compared with that based on the clinical index (0.760 and 0.694, respectively). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that the 521 mRNAs highly associated with 5 DElncRNAs were primarily involved in 17 terms and 25 pathways, respectively. Based on the 5 DElncRNAs, a novel and convenient prognostic nomogram for predicting 3- and 5-year OS for patients with ccRCC was developed. The results of the present study may be conducive to the development of a precise predictive tool for the prognosis of ccRCC and may provide information regarding the molecular mechanisms of ccRCC. However, additional experimental in vitro and in vivo studies investigating lncRNAs may be required.

CDKN2A, CDK1, and CCNE1 overexpression in sebaceous gland carcinoma of eyelid

PURPOSE

To investigate the overexpression of genes in sebaceous gland carcinoma (SGC) of the eyelid compared to sebaceous adenoma of the eyelid in order to elucidate the molecular mechanism underlying pathogenesis.

METHODS

We performed histopathological examination of eyelid tissues surgically removed from four patients diagnosed with SGC (cases 1-3) and sebaceous adenoma (case 4) of the eyelid. Next, we performed global gene expression analysis of surgical tissue samples using a GeneChip^® system and the Ingenuity Pathways Knowledge Base. The results of the GeneChip^® analysis were explored with quantitative real-time polymerase chain reaction (qRT-PCR) analysis.

RESULTS

In the SGC samples, we found that 211, 199, and 199 genes, respectively, showed ≥ 2.0-fold higher expression than those in the sebaceous adenoma sample (case 4); 194 genes were common to all three SGC samples. For the 194 genes with upregulated expression, functional category analysis showed that SGC of the eyelid employed a unique gene network, including cyclin-dependent kinase inhibitor 2A (CDKN2A), cyclin-dependent kinase 1 (CDK1), and cyclin E1 (CCNE1), which are related to cell cycle progression, incidence of tumor, and cell viability. Furthermore, qRT-PCR analysis showed that the expression levels of CDKN2A, CDK1, and CCNE1 were significantly upregulated in all SGC cases compared to those in the sebaceous adenoma case. These data were similar to the results of microarray analysis.

CONCLUSION

Overexpression of cell cycle-related genes CDKN2A, CDK1, CCNE1, and their gene network may help elucidate the pathogenic pathway of SGC of the eyelid at the molecular level.

ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins

Interpretation of genetic variation is needed for deciphering genotype-phenotype associations, mechanisms of inherited disease, and cancer driver mutations. Millions of single nucleotide variants (SNVs) in human genomes are known and thousands are associated with disease. An estimated 21% of disease-associated amino acid substitutions corresponding to missense SNVs are located in protein sites of post-translational modifications (PTMs), chemical modifications of amino acids that extend protein function. ActiveDriverDB is a comprehensive human proteo-genomics database that annotates disease mutations and population variants through the lens of PTMs. We integrated >385,000 published PTM sites with ∼3.6 million substitutions from The Cancer Genome Atlas (TCGA), the ClinVar database of disease genes, and human genome sequencing projects. The database includes site-specific interaction networks of proteins, upstream enzymes such as kinases, and drugs targeting these enzymes. We also predicted network-rewiring impact of mutations by analyzing gains and losses of kinase-bound sequence motifs. ActiveDriverDB provides detailed visualization, filtering, browsing and searching options for studying PTM-associated mutations. Users can upload mutation datasets interactively and use our application programming interface in pipelines. Integrative analysis of mutations and PTMs may help decipher molecular mechanisms of phenotypes and disease, as exemplified by case studies of TP53, BRCA2 and VHL. The open-source database is available at https://www.ActiveDriverDB.org.

Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis

Background: The molecular mechanism of tumorigenesis remains to be fully understood in breast cancer. It is urgently required to identify genes that are associated with breast cancer development and prognosis and to elucidate the underlying molecular mechanisms. In the present study, we aimed to identify potential pathogenic and prognostic differentially expressed genes (DEGs) in breast adenocarcinoma through bioinformatic analysis of public datasets.

Methods: Four datasets (GSE21422, GSE29431, GSE42568, and GSE61304) from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) dataset were used for the bioinformatic analysis. DEGs were identified using LIMMA Package of R. The GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were conducted through FunRich. The protein-protein interaction (PPI) network of the DEGs was established through STRING (Search Tool for the Retrieval of Interacting Genes database) website, visualized by Cytoscape and further analyzed by Molecular Complex Detection (MCODE). UALCAN and Kaplan–Meier (KM) plotter were employed to analyze the expression levels and prognostic values of hub genes. The expression levels of the hub genes were also validated in clinical samples from breast cancer patients. In addition, the gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD).

Results: In total, 203 up-regulated and 118 down-regulated DEGs were identified. Mitotic cell cycle and epithelial-to-mesenchymal transition pathway were the major enriched pathways for the up-regulated and down-regulated genes, respectively. The PPI network was constructed with 314 nodes and 1,810 interactions, and two significant modules are selected. The most significant enriched pathway in module 1 was the mitotic cell cycle. Moreover, six hub genes were selected and validated in clinical sample for further analysis owing to the high degree of connectivity, including CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK, and they were all correlated to worse overall survival (OS) in breast cancer.

Conclusion: These results revealed that mitotic cell cycle and epithelial-to-mesenchymal transition pathway could be potential pathways accounting for the progression in breast cancer, and CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK may be potential crucial genes. Further, it could be utilized as new biomarkers for prognosis and potential new targets for drug synthesis of breast cancer.

Comparative STAT3-Regulated Gene Expression Profile in Renal Cell Carcinoma Subtypes

Renal cell carcinomas (RCC) are heterogeneous and can be further classified into three major subtypes including clear cell, papillary and chromophobe. Signal transducer and activator of transcription 3 (STAT3) is commonly hyperactive in many cancers and is associated with cancer cell proliferation, invasion, migration, and angiogenesis. In renal cell carcinoma, increased STAT3 activation is associated with increased metastasis and worse survival outcomes, but clinical trials targeting the STAT3 signaling pathway have shown varying levels of success in different RCC subtypes. Using RNA-seq data from The Cancer Genome Atlas (TCGA), we compared expression of 32 STAT3 regulated genes in 3 RCC subtypes. Our results indicate that STAT3 activation plays the most significant role in clear cell RCC relative to the other subtypes, as half of the evaluated genes were upregulated in this subtype. MMP9, BIRC5, and BCL2 were upregulated and FOS was downregulated in all three subtypes. Several genes including VEGFA, VIM, MYC, ITGB4, ICAM1, MMP1, CCND1, STMN1, TWIST1, and PIM2 had variable expression in RCC subtypes and are potential therapeutic targets for personalized medicine.

MiR-31-5p acts as a tumor suppressor in renal cell carcinoma by targeting cyclin-dependent kinase 1 (CDK1)

BACKGROUND

Renal cell carcinoma (RCC) accounts for more than 90% of cancers in the kidney. RCC is often asymptomatic, as a result people with RCC generally have advanced disease by the time it is discovered and has a poor prognosis compared to other cancers. Therefore, it is necessary to explore its pathogenesis and identify some reliable prognostic biomarker of RCC. miRNAs are emerging as important players in the development and progression of RCC. miR-31-5p has been reported to act as a tumor suppressor in hepatocellular carcinoma (HCC). The aim of this study is to determine the detailed molecular mechanism of miR-31-5p in the progression of RCC and to investigate its potential clinical value.

METHODS

In this study, RT-qPCR, EdU assay, CCK-8 assay, wound scratch assay, transwell assay, flow cytometry assay and cell cycle assay were performed to detect miR-31-5p expression and its functions in RCC. Moreover, 42 formalin-fixed paraffin-embedded (FFPE) RCC samples were used to analyze the relationship between miR-31-5p expression and patients' overall survival. Finally, luciferase reporter assay, RT-qPCR assay and western blot were used to explore the association between miR-31-5p and its potential targets.

RESULTS

miR-31-5p was significantly down-regulated in RCC tissues and RCC cell lines compared with paired adjacent normal tissues and normal cell lines. miR-31-5p downregulation was associated with poor prognosis in RCC patients. Overexpression of miR-31-5p inhibited RCC cell proliferation, migration and invasion and cell cycle. Conversely, down-regulation of miR-31-5p promoted cell proliferation, migration and invasion. Furthermore, cyclin-dependent kinasec1 (CDK1), a key player in cell cycle regulation, was identified as a functional target of miR-31-5p.

CONCLUSIONS

Our results suggest that miR-31-5p serves as a tumor suppressor in RCC and is expected to be a molecular biomarker for poor prognosis of RCC.

Overexpression of CBX3 in Pancreatic Adenocarcinoma Promotes Cell Cycle Transition-Associated Tumor Progression

BACKGROUND

Previous studies showed that Chromobox protein homolog 3 (CBX3) was overexpressed in several types of human cancers, however its pattern and role in pancreatic adenocarcinoma (PAAD) has not yet been understood. The aim of this study was to identify the expression and function of CBX3 in PAAD.

METHODS

Data of transcriptomic and protein expression of CBX3 in PAAD were collected from different databases and analyzed. The in vitro and in vivo role of CBX3 in PAAD was examined.

RESULTS

CBX3 was overexpressed in human PAAD tissues, which was associated with poor prognosis of overall and disease-free survival of the patients. Overexpression of CBX3 induced the in vitro proliferation, anchorage-free growth, migration and invasion of the PAAD cells, and led to in vivo growth of orthotoptic PAAD tumors in mice. GO and KEGG pathway analysis, as well as experimental observation showed that CBX3 may be associated with cell cycle transition of PAAD cells, and cyclin-dependent kinase 1 (CDK1) and proliferating cell nuclear antigen (PCNA) may mediate the tumor-promoting action of CBX3. CDK1 knockdown attenuated the cell cycle transition, proliferation and invasion of CBX3-overexpressing PAAD cells.

CONCLUSION

Our findings suggest the tumor-promoting role of CBX3 in PAAD to be targeted by novel therapeutic strategies.

Prognostic Value of RNASEH2A-, CDK1-, and CD151-Related Pathway Gene Profiling for Kidney Cancers

The nucleotide degrading enzyme gene RNASEH2A (ribonuclease H2 subunit A) has been found to be overexpressed in cancers. Our aim was to understand the role of RNASEH2A in cancer prognostication and to establish a scoring system based on the expressions of genes interacting with RNASEH2A. We screened the nucleotide degrading enzyme gene expression in RNAseq data of 14 cancer types derived from The Cancer Genome Atlas (TCGA) and found that RNASEH2A overexpression was associated with poor patient survival only in renal cell carcinomas (RCCs). Further cluster analyses of samples with poor outcomes revealed that cluster of differentiation 151 (CD151) upregulation correlated with low cyclin dependent kinase 1 (CDK1) and high RNASEH2A expression. The combination of low CD151 expression and high RNASEH2A expression resulted in impaired proliferation in four kidney cancer cell lines, suggesting potential synthetic dosage lethality (SDL) interactions between the two genes. A prognostication scoring system was established based on the expression levels of RNASEH2A-, CDK1-, and CD151-related genes, which could effectively predict the overall survival in a TCGA clear cell RCC cohort (n = 533, 995.3 versus 2242.2 days, p < 0.0001), in another clear cell renal cell carcinoma (ccRCC) cohort E-GEOD-22541 (n = 44, 390.0 versus 1889.2 days, p = 0.0007), and in a TCGA papillary RCC (pRCC) cohort (n = 287, 741.6 versus 1623.7 days, p < 0.0001). Our results provide a clinically applicable prognostication scoring system for renal cancers.

Mevalonate pathway blockage enhances the efficacy of mTOR inhibitors with the activation of retinoblastoma protein in renal cell carcinoma

Renal cell carcinoma (RCC) is the most common malignancy of kidney and remains largely intractable once it recurs after resection. mTOR inhibitors have been one of the mainstays used against recurrent RCC; however, there has been a major problem of the resistance to mTOR inhibitors, and thus new combination treatments with mTOR inhibitors are required. We here retrospectively showed that regular use of antilipidemic drug statins could provide a longer progression free survival (PFS) in RCC patients prescribed with an mTOR inhibitor everolimus than without statins (median PFS, 7.5 months vs. 3.2 months, respectively; hazard ratio, 0.52; 95% CI, 0.22-1.11). In order to give a rationale for this finding, we used RCC cell lines and showed the combinatorial effects of an mTOR inhibitor with statins induced a robust activation of retinoblastoma protein, whose mechanisms were involved in statins-mediated hindrance of KRAS or Rac1 protein prenylation. Finally, statins treatment also enhanced the efficacy of an mTOR inhibitor in RCC xenograft models. Thus, we provide molecular and (pre)clinical data showing that statins use could be a drug repositioning for RCC patients to enhance the efficacy of mTOR inhibitors.

PolyC-binding proteins enhance expression of the CDK2 cell cycle regulatory protein via alternative splicing

The PolyC binding proteins (PCBPs) impact alternative splicing of a subset of mammalian genes that are enriched in basic cellular functions. Here, we focus our analysis on PCBP-controlled cassette exon-splicing within the cell cycle control regulator cyclin-dependent kinase-2 (CDK2) transcript. We demonstrate that PCBP binding to a C-rich polypyrimidine tract (PPT) preceding exon 5 of the CDK2 transcript enhances cassette exon inclusion. This splice enhancement is U2AF65-independent and predominantly reflects actions of the PCBP1 isoform. Remarkably, PCBPs' control of CDK2 ex5 splicing has evolved subsequent to mammalian divergence via conversion of constitutive exon 5 inclusion in the mouse CDK2 transcript to PCBP-responsive exon 5 alternative splicing in humans. Importantly, exclusion of exon 5 from the hCDK2 transcript dramatically represses the expression of CDK2 protein with a corresponding perturbation in cell cycle kinetics. These data highlight a recently evolved post-transcriptional pathway in primate species with the potential to modulate cell cycle control.

Accumulation of cytoplasmic Cdk1 is associated with cancer growth and survival rate in epithelial ovarian cancer

Cyclin dependent kinase 1 (Cdk1) have previously reported correlation with cancer growth and a key regulator for cell cycle. Mostly, Cdk1′s function of nucleus for cell cycle is well known to be associated with cancer, but cytoplasmic Cdk1′s traits are not clearly identified, yet. We revealed that tissue microarray blocks of epithelial ovarian cancer (n = 249) showed increased level of cytoplasmic Cdk1 (p < 0.001), but not in nucleus (p = 0.192) of histologic cell type independently. On survival analysis, Cdk1 overexpression conferred a significantly worse prognosis in 5-year overall survival (Log-rank p = 0.028, Hazard ratio = 2.016, 95% CI = 1.097 to 4.635). Also, the expression of Cdk1 was increased in ovarian cancer cell lines and Gene Expression Omnibus datasets. When the expression and activity of Cdk1 were inhibited by si-Cdk1 or RO-3306 which is a potent Cdk1 inhibitor, the growth of ovarian cancer was diminished. Moreover, combined treatment with RO-3306 and cisplatin in ovarian cancer significantly elevated anti-cancer effects than single-agent treatment. In conclusion, cytoplasmic Cdk1 expression which was elevated in ovarian cancer predicts a poor overall survival. The inhibition of Cdk1 expression and activity reduced ovarian cancer growth.

Identification of key genes and pathways in human clear cell renal cell carcinoma (ccRCC) by co-expression analysis

Human clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In our study, we screened differential expressed genes, and constructed protein-protein interaction (PPI) network and a weighted gene co-expression network to identify key genes and pathways associated with the progression of ccRCC (n = 56). Functional and pathway enrichment analysis demonstrated that upregulated differentially expressed genes (DEGs) were significantly enriched in response to wounding, positive regulation of immune system process, leukocyte activation, immune response and cell activation. Downregulated DEGs were significantly enriched in oxidation reduction, monovalent inorganic cation transport, ion transport, excretion and anion transport. In the PPI network, top 10 hub genes were identified (TOP2A, MYC, ALB, CDK1, VEGFA, MMP9, PTPRC, CASR, EGFR and PTGS2). In co-expression network, 6 ccRCC-related modules were identified. They were associated with immune response, metabolic process, cell cycle regulation, angiogenesis and ion transport. In conclusion, our study illustrated the hub genes and pathways involved in the progress of ccRCC, and further molecular biological experiments are needed to confirm the function of the candidate biomarkers in human ccRCC.

Diagnostic significance and potential function of miR-338-5p in hepatocellular carcinoma: A bioinformatics study with microarray and RNA sequencing data

MicroRNA (miR)-338-5p has been studied in hepatocellular carcinoma (HCC); however, the diagnostic value and molecular mechanism underlying its actions remains to be elucidated. The present study aimed to validate the diagnostic ability of miR-338-5p and further explore the underlying molecular mechanism. Data from eligible studies, Gene Expression Omnibus (GEO) chips and The Cancer Genome Atlas (TCGA) datasets were gathered in the data mining and the integrated meta-analysis, to evaluate the significance of miR-338-5p in diagnosing HCC comprehensively. The potential target genes of miR-338-5p were achieved from the intersection of the deregulated targets of miR-338-5p from GEO and TCGA in addition to the predicted target genes from 12 online software. A protein-protein-interaction (PPI) network was drawn to illustrate the interaction between target genes and to define the hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the function of the target genes. From the results, miR-338-5p exhibited favorable value in diagnosing HCC. Types of sample and experiment were defined as the possible sources of heterogeneity in meta-analysis. A total of 423 genes were selected as the potential target genes of miR-338-5p, and five genes were defined as the hub genes from the PPI network. The GO and KEGG analyses indicated that the target genes were significantly assembled in the pathways of metabolic process and cell cycle. miR-338-5p may function as a novel diagnostic target for HCC through regulating certain target genes and signaling pathways.

Giving Drugs a Second Chance: Overcoming Regulatory and Financial Hurdles in Repurposing Approved Drugs As Cancer Therapeutics

The repositioning or “repurposing” of existing therapies for alternative disease indications is an attractive approach that can save significant investments of time and money during drug development. For cancer indications, the primary goal of repurposed therapies is on efficacy, with less restriction on safety due to the immediate need to treat this patient population. This report provides a high-level overview of how drug developers pursuing repurposed assets have previously navigated funding efforts, regulatory affairs, and intellectual property laws to commercialize these “new” medicines in oncology. This article provides insight into funding programs (e.g., government grants and philanthropic organizations) that academic and corporate initiatives can leverage to repurpose drugs for cancer. In addition, we highlight previous examples where secondary uses of existing, Food and Drug Administration- or European Medicines Agency-approved therapies have been predicted in silico and successfully validated in vitro and/or in vivo (i.e., animal models and human clinical trials) for certain oncology indications. Finally, we describe the strategies that the pharmaceutical industry has previously employed to navigate regulatory considerations and successfully commercialize their drug products. These factors must be carefully considered when repurposing existing drugs for cancer to best benefit patients and drug developers alike.

Cytotoxicity and Proapoptotic Effects of Allium atroviolaceum Flower Extract by Modulating Cell Cycle Arrest and Caspase-Dependent and p53-Independent Pathway in Breast Cancer Cell Lines

Breast cancer is the second leading cause of cancer death among women and despite significant advances in therapy, it remains a critical health problem worldwide. Allium atroviolaceum is an herbaceous plant, with limited information about the therapeutic capability. We aimed to study the anticancer effect of flower extract and the mechanisms of action in MCF-7 and MDA-MB-231. The extract inhibits the proliferation of the cells in a time- and dose-dependent manner. The underlying mechanism involved the stimulation of S and G2/M phase arrest in MCF-7 and S phase arrest in MDA-MB-231 associated with decreased level of Cdk1, in a p53-independent pathway. Furthermore, the extract induces apoptosis in both cell lines, as indicated by the percentage of sub-G0 population, the morphological changes observed by phase contrast and fluorescent microscopy, and increase in Annexin-V-positive cells. The apoptosis induction was related to downregulation of Bcl-2 and also likely to be caspase-dependent. Moreover, the combination of the extract and tamoxifen exhibits synergistic effect, suggesting that it can complement current chemotherapy. LC-MS analysis displayed 17 major compounds in the extract which might be responsible for the observed effects. Overall, this study demonstrates the potential applications of Allium atroviolaceum extract as an anticancer drug for breast cancer treatment.

Data-Independent Acquisition-Based Quantitative Proteomic Analysis Reveals Potential Biomarkers of Kidney Cancer

PURPOSE

Renal cell carcinoma (RCC) is a malignant and metastatic cancer with 95% mortality, and clear cell RCC (ccRCC) is the most observed among the five major subtypes of RCC. Specific biomarkers that can distinguish cancer tissues from adjacent normal tissues should be developed to diagnose this disease in early stages and conduct a reliable prognostic evaluation.

EXPERIMENTAL DESIGN

Data-independent acquisition (DIA) strategy has been widely employed in proteomic analysis because of various advantages, including enhanced protein coverage and reliable data acquisition. In this study, a DIA workflow is constructed on a quadrupole-Orbitrap LC-MS platform to reveal dysregulated proteins between ccRCC and adjacent normal tissues.

RESULTS

More than 4000 proteins are identified, 436 of these proteins are dysregulated in ccRCC tissues. Bioinformatic analysis reveals that multiple pathways and Gene Ontology items are strongly associated with ccRCC. The expression levels of L-lactate dehydrogenase A chain, annexin A4, nicotinamide N-methyltransferase, and perilipin-2 examined through RT-qPCR, Western blot, and immunohistochemistry confirm the validity of the proteomic analysis results.

CONCLUSIONS AND CLINICAL RELEVANCE

The proposed DIA workflow yields optimum time efficiency and data reliability and provides a good choice for proteomic analysis in biological and clinical studies, and these dysregulated proteins might be potential biomarkers for ccRCC diagnosis.

The aberrant upstream pathway regulations of CDK1 protein were implicated in the proliferation and apoptosis of ovarian cancer cells

Background

Upregulation of Cyclin dependent kinase 1 (CDK1) protein is closely related with the prognosis of several malignant tumors. Chk1-CDC25C-CDK1 signaling and P53-P21WAF1-CDK1 signaling pathways are closely related with the cell cycle G2/M phase regulation. The present study aimed to analyze the relationship between CDK1 and the proliferation and apoptosis of ovarian cancer cells, investigate its molecular mechanism preliminarily.

Methods

The specific short-hair RNA (shRNA) plasmids and negative control plasmid of CDK1, checkpoint kinase 1 (CHK1) and p53 genes were transfected into ovarian cancer SK-OV-3 and OVCAR-3 cells respectively. The expressions of CDK1, CHK1 and p53 mRNA and CDK1, Chk1 and P53 protein were detected by sqRT-PCR and Western blot, levels of phospho-CDK1(Thr14/Tyr15), CyclinB1, phospho-Chk1(ser345), cell division cycle 25C (CDC25C), phospho-CDC25C(ser216), P21WAF1, phospho-P53(ser15), proliferating cell nuclear antigen (PCNA), Ki-67, Bcl-2, Bax, Caspase8, Cleaved-caspase3 and Cytochrome C were examined by Western blot. The cell proliferation was measured by MTT and Trypan blue exclusion assay respectively, the cell cycle phase distribution and cell apoptosis rate were detected by flow cytometry (FCM) assay.

Results

As results of CDK1 inhibition by shRNA, the cell proliferation was repressed, the cell numbers of G2/M phase and cell apoptosis rate were increased in both SK-OV-3 and OVCAR-3 cells. After knockdown of CDK1, expressions of PCNA, Ki-67 and Bcl-2 protein were downregulated, expressions of Bax, Caspase8, Cleaved-caspase3 and Cytochrome C were upregulated. While knockdown the CHK1 and p53 by shRNA respectively, the similar effects were observed on the cell proliferation, cell cycle phase distribution and apoptosis in both SK-OV-3 and OVCAR-3 cells, as well as the expressions of the proliferation and apoptosis related proteins mentioned above. Moreover, the levels of p-CDK1(Thr14/Tyr15) were increased after either CHK1 inhibition or p53 inhibition.

Conclusions

Abnormal activation of CDK1 was implicated in the proliferation and apoptosis regulation of ovarian cancer cells, which might be due to the aberrant regulations of the upstream Chk1-CDC25C and P53-P21WAF1 signaling pathway.

Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties

Many molecular classification and prognostic gene signatures for hepatocellular carcinoma (HCC) patients have been established based on genome-wide gene expression profiling; however, their generalizability is unclear. Herein, we systematically assessed the prognostic effects of these gene signatures and identified valuable prognostic biomarkers by integrating these gene signatures. With two independent HCC datasets (GSE14520, N = 242 and GSE54236, N = 78), 30 published gene signatures were evaluated, and 11 were significantly associated with the overall survival (OS) of postoperative HCC patients in both datasets. The random survival forest models suggested that the gene signatures were superior to clinical characteristics for predicting the prognosis of the patients. Based on the 11 gene signatures, a functional protein-protein interaction (PPI) network with 1406 nodes and 10,135 edges was established. With tissue microarrays of HCC patients (N = 60), we determined the prognostic values of the core genes in the network and found that RAD21, CDK1, and HDAC2 expression levels were negatively associated with OS for HCC patients. The multivariate Cox regression analyses suggested that CDK1 was an independent prognostic factor, which was validated in an independent case cohort (N = 78). In cellular models, inhibition of CDK1 by siRNA or a specific inhibitor, RO-3306, reduced cellular proliferation and viability for HCC cells. These results suggest that the prognostic predictive capacities of these gene signatures are reproducible and that CDK1 is a potential prognostic biomarker or therapeutic target for HCC patients.

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Eleven gene signatures have promising values for the OS prediction of HCC patients who undergo the surgical treatments.

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Prediction results for the 11 gene signatures were in moderate concordance, and genes included were functionally linked.

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CDK1 is an independent prognostic biomarker and a potential therapeutic target for HCC patients.

Various gene signatures for hepatocellular carcinoma (HCC) patients have been reported; however, their generalizability is unclear. Using two HCC patient datasets, we assessed the prognostic values of these gene signatures and identified 11 gene signatures that were associated with overall survival for postoperative HCC patients in both cohorts. Genes derived from these signatures formed a functional protein-protein interaction network with 1,406 nodes and 10,135 edges, and the expression levels of three core genes, RAD21, CDK1, and HDAC2, in the network were negatively associated with the overall survival of HCC patients. Further studies suggested that CDK1 is an independent prognostic factor and that it is a potential therapeutic target for HCC patients.

Eukaryotic translation initiation factor 3 subunit D overexpression is associated with the occurrence and development of ovarian cancer

Ovarian cancer is the most common cause of gynaecological cancer-associated death; thus, promising biomarkers and new therapeutic targets for ovarian cancer must be explored. Here, we report that eukaryotic translation initiation factor 3 subunit D (EIF3D), a member of the EIF3 family, was overexpressed in ovarian cancer clinical tissues. Furthermore, the expression of EIF3D was correlated with the International Federation of Gynecology and Obstetrics stage and pathological differentiation stage. 3-(4,5-dimethylthylthiazol-2-yl)-2 (MTT) and colony formation assays revealed that the lentivirus-mediated knockdown of EIF3D suppresses cell proliferation in the ovarian tumour cell lines CAOV-3 and SKOV-3. Flow cytometry revealed that cells were arrested at the G2/M phase of the cell cycle and that cyclin-dependent kinase 1 was also altered after EIF3D silencing. The results presented here demonstrate that EIF3D may play an important role in the occurrence and development of ovarian cancer.

Reduced cytosolic carboxypeptidase 6 (CCP6) level leads to accumulation of serum polyglutamylated DNAJC7 protein: A potential biomarker for renal cell carcinoma early detection

Renal cell carcinoma (RCC) is frequently diagnosed at advanced stages of disease, although early diagnosis has much favorable prognosis. This study assessed aberrant expression of cytosolic carboxypeptidase 6 (CCP6) leading to accumulation of serum polyglutamylated DNAJC7 as a biomarker for early RCC detection. A total of 835 RCCs, 143 chronic nephritis, 170 kidney stones and 415 health controls were collected for qRT-PCR, immunohistochemistry and Western blot analysis of CCP6 expression and mass spectrometry of DNAJC7 and polyglutamylated DNAJC7. The data showed that CCP6 expression was significantly decreased in 30 RCC tissues and that mass spectrometric and pull-down analysis identified DNAJC7 as a substrate of CCP6 and showed upregulated polyglutamylated-DNAJC7 (polyE-DNAJC7) in sera of RCC patients. The electrochemiluminescence immunoassay of large-scale serum samples from multi-institutes further confirmed the remarkable increase of polyE-DNAJC7 in 805 RCCs compared to that of 385 healthy controls (p < 0.001), 128 patients with chronic nephritis (p < 0.001), and 153 with kidney stone (p < 0.001). Serum level of DNAJC7-polyE protein was also associated with advanced RCC stage and grade in 805 patients. The data from the current study for the first time demonstrated increased serum polyglutamylated DNAJC7 as a potential biomarker for RCC early detection and association with advanced tumor stages and grade, which provides support of further polyglutamylation research in RCC.

Phosphorylated retinoblastoma protein is a potential predictive marker of irinotecan efficacy for colorectal cancer

Irinotecan has been used in the first-line treatment of metastatic colorectal cancer. However, no clear predictive marker of irinotecan efficacy has been identified. It is controversial whether the response to irinotecan could be predicted by the expression level of topoisomerase-I, a direct target of irinotecan. The present study aimed to identify a feasible predictive marker of irinotecan efficacy. We hypothesized that the efficacy of SN38 (an active metabolite of irinotecan) is related to the cell proliferation and the phosphorylation status of RB in colorectal cancer cells. Indeed, the IC50 of SN38 was positively correlated with the doubling time of each cell line (R2=0.9315). Moreover, the phosphorylation level of RB was related to SN38 sensitivity. Consistent with the in vitro data, colorectal cancer tissues of irinotecan responders showed a significantly higher rate of phosphorylated RB (serine 780) expression using immunohistochemistry (P=0.0006), although a generally used proliferative marker, Ki-67, showed no significance. Finally, we investigated whether the phosphorylation of RB plays a crucial role in the efficacy of irinotecan. To suppress the expression of phosphorylated RB, we performed the knockdown of CDKs, which are known to phosphorylate RB. Intriguingly, the knockdown of both CDK4 and CDK6, but not CDK2, allowed RB to become the most hypophosphorylated form and converted the SN38-sensitive cells to a resistant state. Taking together the above findings from in vitro and clinical research, the immunohistochemistry of phosphorylated RB protein might be feasible to predict the irinotecan efficacy of colorectal cancer in clinical practice.

ZFX is a Strong Predictor of Poor Prognosis in Renal Cell Carcinoma

Background

This study was designed to assay the expression of zinc finger protein X-linked (ZFX) in renal cell carcinoma (RCC) tissues and evaluate the correlation between ZFX expression and prognosis of RCC patients.

Material/Methods

The expressions of ZFX mRNA in 53 RCC tissues and 51 normal tissues were determined by quantitative real-time polymerase chain reaction (qRT-PCR). Immunohistochemistry (IHC) technology was used to measure the expression of ZFX protein. Then chi-square test was conducted to verify the association between ZFX expression and clinical parameters. Next, we explored the overall survival rate of RCC patients with Kaplan-Meier analysis. Finally, the correlation between ZFX expression and the prognosis of RCC patients was evaluated by Cox regression analysis.

Results

The qRT-PCR result showed that the ZFX was significantly up-regulated in RCC tissues. As for the IHC consequence, the positive rate of ZFX expression in RCC specimens was 79.2%, while that in the normal control tissues was only 17.6%. Chi-square test showed that ZFX expression shared no close relationship with age, sex, or smoking (P>0.05), but was tightly associated with TNM stage, tumor size, and lymph node metastasis (P<0.05). Kaplan-Meier analysis showed that patients with ZFX positive expression had higher mortality than those with negative expression (P<0.05). Cox regression analysis revealed that ZFX expression had tight correlation with prognosis of RCC patients (HR=4.997, P=0.045, 95%CI=1.033–24.180).

Conclusions

Our findings show that ZFX could be considered as a predictor for prognosis of RCC patients.

R.E.N.A.L. nephrometry score predicts postoperative recurrence of localized renal cell carcinoma treated by radical nephrectomy

Background

We investigated the association between the R.E.N.A.L. nephrometry score (RNS) and the postoperative recurrence of localized renal cell carcinoma (RCC).

Methods

We retrospectively analyzed a database comprising 91 patients with non-small localized RCC (pT1b–T2b) treated by radical nephrectomy at our hospital from January 2002 to March 2010. RNS was scored based on imaging findings at diagnosis. The Cox proportional hazards model was used to predict recurrence-free survival (RFS) and to calculate hazard ratio (HR).

Results

The median age at operation was 63 years (range, 30–85 years). Postoperative recurrence occurred in 19 patients (21 %). Median RNS sum was 9 (range, 5–11). High RNS sum (10–12) was significantly associated with RFS (P = 0.0012). Multivariate analysis revealed that high RNS sum [HR, 9.05; 95 % confidence interval (CI), 2.11–63.9; P = 0.0019] were significantly associated with RFS. Regarding each component of RNS, only the L component, which referred to tumor location relative to the polar line, was associated with RFS (HR, 15.0; 95 % CI, 2.68–396; P = 0.0006).

Conclusions

RNS was associated with RFS in cases of non-small localized RCC (pT1b–2b), thus supporting its utility as a prognostic factor.