The knockdown of endogenous replication factor C4 decreases the growth and enhances the chemosensitivity of hepatocellular carcinoma cells

Zaki M, Soltan MA, Noreldin AE. Oncogenic Potential of Replication Factor C Subunit 4: Correlations with Tumor Progression and Assessment of Potential Inhibitors

Replication Factor C Subunit 4 (RFC4), an oncogene implicated in many human cancers, has yet to be extensively studied in many cancer types to determine its expression patterns and tumor tissue function. Various bioinformatics tools were used to analyze RFC4 as a potential oncogene and therapeutic target across many cancers. We first examined RFC4 expression levels in several human tumor types to determine relationships with tumor grade, stage, metastasis, and patient survival. We also examined RFC4's genetic changes, epigenetic methylation, and effect on tumor microenvironment (TME) immune cell infiltration. We also analyzed RFC4's connections with immunological checkpoints to identify potential molecular pathways involved in carcinogenesis. Our findings show that RFC4 is upregulated in several tumor types and associated with poor prognoses in many human cancers. This study shows that RFC4 significantly affects the tumor immunological microenvironment, specifically immune cell populations. Finally, we screened for RFC4-inhibiting pharmacological compounds with anti-cancer potential. This study fully elucidates RFC4's carcinogenic activities, emphasizing its potential as a prognostic biomarker and a target for anti-cancer therapy.

RFC3 serves as a novel prognostic biomarker and target for head and neck squamous cell carcinoma

OBJECTIVE

Head and neck squamous cell carcinoma (HNSCC) is a prevalent cancer that originates from the squamous cells. The role of the replication factor C subunit 3 (RFC3) in HNSCC progression remains elusive. The aim of this study was to uncover RFC3 significance in HNSCC.

METHODS

The Cancer Genome Atlas (TCGA-HNSCC) dataset was initially used to assess RFC3 expression and its association with HNSCC clinical features. Subsequently, quantitative reverse transcription PCR (RT-qPCR) confirmed RFC3 mRNA expression in oral squamous cell carcinoma (OSCC), a primary HNSCC type. Survival rates were evaluated using the Kaplan-Meier plot, while the Tumor Immune Estimation Resource (TIMER) database probed RFC3-immune cell interaction. Additionally, in silico tools were used to examine the RFC3 protein network and engagement in HNSCC pathways.

RESULTS

RFC3 expression is significantly upregulated in HNSCC, including OSCC. Upregulated RFC3 expression was significantly correlated with the clinicopathological features of HNSCC, including tumor stage, grade, metastasis, and patient survival. RFC3 is also associated with immune cell infiltration. Functional analysis has highlighted its involvement in DNA replication, mismatch repair, and cell cycle pathways. Interestingly, RFC3 high expression is linked to well-known oncogenic signaling pathways, such as MYC/MYCN, HIPPO, and mTOR.

CONCLUSIONS

In conclusion, RFC3 can be considered a novel prognostic biomarker for HNSCC, and further studies on its functional mechanisms may help to use RFC3 as a therapeutic target for HNSCC.

CLINICAL RELEVANCE

The clinical relevance of this study lies in identifying RFC3 as a novel biomarker and prognostic indicator for HNSCC, offering insights that could impact future clinical approaches.

Knockdown of RFC4 inhibits the cell proliferation of nasopharyngeal carcinoma in vitro and in vivo

Nasopharyngeal carcinoma (NPC) is a malignant tumor that mainly occurs in East and Southeast Asia. Although patients benefit from the main NPC treatments (e.g., radiotherapy and concurrent chemotherapy), persistent and recurrent diseases still occur in some NPC patients. Therefore, investigating the pathogenesis of NPC is of great clinical significance. In the present study, replication factor c subunit 4 (RFC4) is a key potential target involved in NPC progression via bioinformatics analysis. Furthermore, the expression and mechanism of RFC4 in NPC were investigated in vitro and in vivo. Our results revealed that RFC4 was more elevated in NPC tumor tissues than in normal tissues. RFC4 knockdown induced G2/M cell cycle arrest and inhibited NPC cell proliferation in vitro and in vivo. Interestingly, HOXA10 was confirmed as a downstream target of RFC4, and the overexpression of HOXA10 attenuated the silencing of RFC4-induced cell proliferation, colony formation inhibition, and cell cycle arrest. For the first time, this study reveals that RFC4 is required for NPC cell proliferation and may play a pivotal role in NPC tumorigenesis.

Integrative analysis of expression, prognostic significance and immune infiltration of RFC family genes in human sarcoma

Objective: To reveal the expression and prognostic value of replication factor C family genes (RFCs) in patients with sarcoma.

Results: The results showed that the mRNA expression levels of RFC2, RFC3, RFC4, and RFC5 were increased in sarcoma tissues. In addition, Cancer Cell Line Encyclopedia (CCLE) dataset analysis indicated that RFC1, RFC2, RFC3, RFC4, and RFC5 were elevated expressed in sarcoma cell lines. Moreover, Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier Plotter showed that highly expressed RFC2-5 were associated with poor overall survival (OS) or relapse-free survival (RFS) in sarcoma patients. The results of the Tumor Immune Estimation Resource (TIMER) database indicated that the expression of RFCs was negatively correlated with the infiltration of CD4+ T cells and macrophages.

Conclusions: There were significant differences in the expression of RFCs between normal tissue and sarcoma tissue, and RFC2, RFC3, RFC4, and RFC5 might be promising prognostic biomarkers for sarcoma.

Methods: The expression of RFCs was analyzed using the ONCOMINE dataset and GEPIA dataset. CCLE dataset was used to assess the expression of RFCs in the cancer cell line. The prognostic value of RFCs was evaluated by GEPIA and Kaplan-Meier analysis. Furthermore, the association between RFCs and their co-expressed genes were explored via ONCOMINE and GEPIA datasets. We used the TIMER dataset to analyze the immune cell infiltration of RFCs in sarcoma.

Identification of biomarkers for acute leukemia via machine learning-based stemness index

Traditional methods to understand leukemia stem cell (LSC)'s biological characteristics include constructing LSC-like cells and mouse models by transgenic or knock-in methods. However, there are some potential pitfalls in using this method, such as retroviral insertion mutagenesis, non-physiological level gene expression, non-physiological expansion, and difficulty to construct. The mRNAsi index for each sample of the Cancer Genome Atlas (TCGA) could avoid these potential pitfalls by machine learning. In this work, we aimed to construct a network of LSC genes utilizing the mRNAsi. First, mRNAsi value was analyzed with expressions distributions, survival analysis, age, and gender in acute myeloid leukemia (AML) samples. Then, we used the weighted gene co-expression network analysis (WGCNA) to construct modules of stemness genes. The correlation of the LSC genes transcription and interplay among LSC proteins was analyzed. We performed functional and pathway enrichment analysis to annotate stemness genes. Survival analysis further identified prognostic biomarkers by clinical data of TCGA and the Gene Expression Omnibus (GEO) database. We found that the result of mRNAsi overall survival is not significant, which may be due to the heterogeneity of AML in the stage of myeloid differentiation, French-American-British (FAB) classification systems. Enrichment analysis indicated that the stemness genes were biologically clustered as a group and mainly associated with cell cycle and mitosis. Moreover, 10 key genes (SNRNP40, RFC4, RFC5, CDC6, HSPE1, PA2G4, SNAP23P, DARS2, MIS18A, and HPRT1) were screened by survival analysis with the data from TCGA and GEO. Among them, RFC4 and RFC5 were the distinguished biomarkers for their double-validated prognostic value in both databases. Additionally, the expression of RFC4 and RFC5 had the same trend as mRNAsi score in FAB subtypes. In conclusion, our result demonstrated that mRNAsi based LSC-related genes were found to have strong interactions as a cluster. These genes, especially RFC4 and RFC5, could be the therapeutic targets for inhibiting the stemness characteristics of AML. This work is also a comprehensive pipeline for future cancer stem cell studies.

The upregulated expression of RFC4 and GMPS mediated by DNA copy number alteration is associated with the early diagnosis and immune escape of ESCC based on a bioinformatic analysis

Esophageal squamous cell carcinoma (ESCC) is a malignant tumor that commonly occurs worldwide. Usually, Asia, especially China, has a high incidence of esophageal cancer. ESCC often has a poor outcome because of a late diagnosis and lack of effective treatments.

To build foundations for the early diagnosis and treatment of ESCC, we used the gene expression datasets GSE20347 and GSE17351 from the GEO database and a private dataset to uncover differentially expressed genes (DEGs) and key genes in ESCC. Notably, we found that replication factor C subunit 4 (RFC4) and guanine monophosphate synthase (GMPS) were upregulated but have been rarely studied in ESCC. In particular, to the best of our knowledge, our study is the first to explore GMPS and ESCC. Furthermore, we found that high levels of RFC4 and GMPS expression may result from an increase in DNA copy number alterations. Furthermore, RFC4 and GMPS were both upregulated in the early stage and early nodal metastases of esophageal carcinoma. The expression of RFC4 was strongly correlated with GMPS. In addition, we explored the relationship between RFC4 and GMPS expression and tumor-infiltrating immune cells (TILs) in esophageal carcinoma. The results showed that the levels of RFC4 and GMPS increased with a decrease in some tumor-infiltrating cells. Upregulated RFC4 and GMPS with high TILs indicate a worse prognosis.

In summary, our study shows that RFC4 and GMPS have potential as biomarkers for the early diagnosis of ESCC and may played a crucial role in the process of tumor immunity in ESCC.

Replication Factor C4 in human hepatocellular carcinoma: A potent prognostic factor associated with cell proliferation

Replication Factor c4 (RFC4) has been found to play important roles in many carcinomas and is correlated with poor prognosis. The present study was performed to investigate the specific role of RFC4 in hepatocellular carcinoma (HCC) and the underlying molecular mechanism. Public datasets including TCGA and GTEx were applied to explore the expression of RFC4 in HCC and its association with HCC prognosis. The results of bioinformatics analysis showed that RFC4 was overexpressed in HCC tissues compared with noncancerous tissues and significantly correlated with poor prognosis for HCC. Through immunohistochemistry, the association between RFC4 expression and clinical-pathological features of HCC patients was evaluated. Western blots were applied to investigate relative protein expression. Then in vivo and in vitro experiments were performed to explore the function of RFC4 in HCC tumor cells. The present results suggest that high level expression of RFC4 is associated with tumor size. In addition, RFC4 knockdown suppressed the cell proliferation and sphere formation of hepatoma cells in vitro. Moreover, silencing of RFC4 significantly decreased the growth of tumors in a xenograft tumor model. In conclusion, our study indicates that RFC4 is a potential prognostic predictor associated with poor outcomes for HCC patients. Furthermore, knocking down RFC4 could significantly inhibit tumor progression both in vitro and in vivo. Therefore, the present study can shed new light on the understanding of molecular mechanisms of HCC and may provide molecular targets and diagnostic biomarkers for the treatment of HCC.

RFC4 promotes the progression and growth of Oral Tongue squamous cell carcinoma in vivo and vitro

OBJECTIVE

Currently, many studies have found that RFC4 was up-regulated in various cancers, and related to the progression and development. While the effects of RFC4 in oral tongue squamous cell carcinoma remain unclear, the main purpose of this research is to explore the role of RFC4 in oral tongue squamous cell carcinoma.

METHODS

The expression of RFC4 in various cancers was analyzed in GEPIA database, and the results were further verified by IHC assay. The relationship between RFC4 and several clinical parameters was analyzed; the proliferation was further observed by knockdown RFC4 in vitro. Finally, we constructed related nude mouse models by planting cells subcutaneous of nude mice, and the discrepancy was observed.

RESULTS

Based on GEPIA database, RFC4 was up-regulated in various cancers, including colorectal cancer, breast cancer, prostate cancer, lung cancer, and liver cancer. RFC4 was up-regulated in oral tongue squamous cell carcinoma compared with the normal tissue from GEPIA online database; we further found that the expression of RFC4 was tightly associated with TNM stage (p = 0.005), but not with age, gender, and differentiation (p > 0.05). We further found that the proliferation of oral tongue squamous cell carcinoma was obviously restrained in vitro, and the carcinogenesis was also inhibited in vivo.

CONCLUSIONS

We found that RFC4 was up-regulated and related to the progression of oral tongue squamous cell carcinoma, and knockdown RFC4 could restrain the proliferation and progression. RFC4 might serve a potential biomarker and provide a new treatment strategy for lots of patients with oral tongue squamous cell carcinoma.

Molecular Profiling Associated with Calcium/Calmodulin-Dependent Protein Kinase Kinase 2 (CAMKK2)-Mediated Carcinogenesis in Gastric Cancer

Gastric cancer is the fifth most common cancer and the third leading cause of cancer-related death worldwide. We showed previously that calcium/calmodulin-dependent protein kinase kinase 2 (CAMKK2), a serine-threonine kinase, is highly expressed in gastric cancer and leads to progression. In the present study, we identified the molecular networks involved in CAMKK2-mediated progression of gastric adenocarcinoma. Treatment of gastric cancer cell lines with a CAMKK2 inhibitor, STO-609, resulted in decreased cell migration, invasion, and colony-forming ability and a G1/S-phase arrest. In addition, tandem mass tag (TMT)-based quantitative proteomic analysis resulted in the identification of 7609 proteins, of which 219 proteins were found to be overexpressed and 718 downregulated (1.5-fold). Our data identified several key downregulated proteins involved in cell division and cell proliferation, which included DNA replication licensing factors, replication factor C, origin recognition complex, replication protein A and GINS, and mesenchymal markers, upon CAMKK2 inhibition. Immunoblotting and immunofluorescence results showed concordance with our mass spectroscopy data. Taken together, our study supports CAMKK2 as a novel therapeutic target in gastric cancer.

A gene module identification algorithm and its applications to identify gene modules and key genes of hepatocellular carcinoma

To further improve the effect of gene modules identification, combining the Newman algorithm in community detection and K-means algorithm framework, a new method of gene module identification, GCNA-Kpca algorithm, was proposed. The core idea of the algorithm was to build a gene co-expression network (GCN) based on gene expression data firstly; Then the Newman algorithm was used to initially identify gene modules based on the topology of GCN, and the number of clusters and clustering centers were determined; Finally the number of clusters and clustering centers were input into the K-means algorithm framework, and the secondary clustering was performed based on the gene expression profile to obtain the final gene modules. The algorithm took into account the role of modularity in the clustering process, and could find the optimal membership module for each gene through multiple iterations. Experimental results showed that the algorithm proposed in this paper had the best performance in error rate, biological significance and CNN classification indicators (Precision, Recall and F-score). The gene module obtained by GCNA-Kpca was used for the task of key gene identification, and these key genes had the highest prognostic significance. Moreover, GCNA-Kpca algorithm was used to identify 10 key genes in hepatocellular carcinoma (HCC): CDC20, CCNB1, EIF4A3, H2AFX, NOP56, RFC4, NOP58, AURKA, PCNA, and FEN1. According to the validation, it was reasonable to speculate that these 10 key genes could be biomarkers for HCC. And NOP56 and NOP58 are key genes for HCC that we discovered for the first time.

A Deep Look into the Program of Rapid Tumor Growth of Hepatocellular Carcinoma

BACKGROUND AND AIMS

Great efforts have been made towards increasing our understanding of the pathogenesis involved in hepatocellular carcinoma (HCC), but the rapid growth inherent to such tumor development remains to be explored.

METHODS

We identified distinct gene coexpression modes upon liver tumor growth using weighted gene coexpression network analysis. Modeling of tumor growth as signaling activity was employed to understand the main cascades responsible for the growth. Hub genes in the modules were determined, examined in vitro, and further assembled into the growth signature.

RESULTS

We revealed modules related to the different growth states in HCC, especially the fastest growth module, which is preserved among different HCC cohorts. Moreover, signaling flux in the cell cycle pathway was found to act as a driving force for rapid growth. Twenty hub genes in the module were identified and assembled into the growth signature, and two genes (NCAPH, and RAD54L) were tested for their growth potential in vitro. Genetic alteration of the growth signature affected the global gene expression. The activity of the signature was associated with tumor metabolism and immunity in HCC. Finally, the prognosis effect of the growth signature was reproduced in nine cancers.

CONCLUSIONS

These results collectively demonstrate the molecule organization of rapid tumor growth in HCC, which is a highly synergistic process, with implications for the future management of patients.

Exploration of Prognostic Biomarkers among Replication Factor C Family in the Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the common cancers with a high incidence and mortality. The human replication factor C (RFC) family contains 5 subunits that play an important role in DNA replication and DNA damage repair. RFCs are abnormally expressed in a variety of cancers; some of them are differentially expressed in HCC tissues and related to tumor growth. However, the expression, prognostic value, and effect targets of the whole RFC family in HCC are still unclear. To address these issues, we performed a multidimensional analysis of RFCs in HCC patients by Oncomine, UALCAN, GEPIA, Human protein atlas, Kaplan-Meier plotter, cBioPortal, GeneMANIA, String, and LinkedOmics. mRNA expression of RFCs was significantly increased in HCC tissues. There was a significant correlation between the expression of RFC2/3/4/5 and tumor stage of HCC patients. Besides, high mRNA expression of RFC2/4 was associated with worse overall survival (OS). Moreover, genetic alterations of RFCs were associated with worse OS in HCC patients. We found that genes co-expressed with RFC2/4 were mainly involved in biological processes, such as chromosome segregation, mitotic cell cycle phase transition, and telomere organization and they activated the cell cycle and spliceosome pathways. The gene set is mainly enriched in cancer-related kinases AURKA, ATR, CDK1, PLK1, and CHEK1. E2F family members were the key transcription factors for RFCs. Our results suggest that differentially expressed RFC2 and RFC4 are potential prognostic biomarkers in HCC and may act on E2F transcription factors and some kinase targets to dysregulate the cell cycle pathway. These efforts may provide new research directions for prognostic biomarkers and therapeutic targets in HCC.

Identification of Potential Hub Genes Related to Diagnosis and Prognosis of Hepatitis B Virus-Related Hepatocellular Carcinoma via Integrated Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA-mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data

Background

Cervical squamous cancer (CESC) is an intractable gynecological malignancy because of its high mortality rate and difficulty in early diagnosis. Several biomarkers have been found to predict the prognose of CESC using bioinformatics methods, but they still lack clinical effectiveness. Most of the existing bioinformatic studies only focus on the changes of oncogenes but neglect the differences on the protein level and molecular biology validation are rarely conducted.

Methods

Gene set data from the NCBI-GEO database were used in this study to compare the differences of gene and protein levels between normal and cancer tissues through significant pathway selection and core gene signature analysis to screen potential clinical biomarkers of CESC. Subsequently, the molecular and protein levels of clinical samples were verified by quantitative transcription PCR, western blot and immunohistochemistry.

Results

Three differentially expressed genes (RFC4, MCM2, TOP2A) were found to have a significant survival (P < 0.05) and highly expressed in CESC tissues. Molecular biological verification using quantitative reverse transcribed PCR, western blotting and immunohistochemistry assays exhibited significant differences in the expression of RFC4 between CESC and para-cancerous tissues (P < 0.05).

Conclusion

This study identified three potential biomarkers (RFC4, MCM2, TOP2A) of CESC which may be useful to clarify the underlying mechanisms of CESC and predict the prognosis of CESC patients.

Identification of Hub Genes Associated With Hepatocellular Carcinoma Using Robust Rank Aggregation Combined With Weighted Gene Co-expression Network Analysis

Background

Bioinformatics provides a valuable tool to explore the molecular mechanisms underlying pathogenesis of hepatocellular carcinoma (HCC). To improve prognosis of patients, identification of robust biomarkers associated with the pathogenic pathways of HCC remains an urgent research priority.

Methods

We employed the Robust Rank Aggregation method to integrate nine qualified HCC datasets from the Gene Expression Omnibus. A robust set of differentially expressed genes (DEGs) between tumor and normal tissue samples were screened. Weighted gene co-expression network analysis was applied to cluster DEGs and the key modules related to clinical traits identified. Based on network topology analysis, novel risk genes derived from key modules were mined and biological verification performed. The potential functions of these risk genes were further explored with the aid of miRNA–mRNA regulatory networks. Finally, the prognostic ability of these genes was assessed by constructing a clinical prediction model.

Results

Two key modules showed significant association with clinical traits. In combination with protein–protein interaction analysis, 29 hub genes were identified. Among these genes, 19 from one module showed a pattern of upregulation in HCC and were associated with the tumor node metastasis stage, and 10 from the other module displayed the opposite trend. Survival analyses indicated that all these genes were significantly related to patient prognosis. Based on the miRNA-mRNA regulatory network, 29 genes strongly linked to tumor activity were identified. Notably, five of the novel risk genes, ABAT, DAO, PCK2, SLC27A2, and HAO1, have rarely been reported in previous studies. Gene set enrichment analysis for each gene revealed regulatory roles in proliferation and prognosis of HCC. Least absolute shrinkage and selection operator regression analysis further validated DAO, PCK2, and HAO1 as prognostic factors in an external HCC dataset.

Conclusion

Analysis of multiple datasets combined with global network information presents a successful approach to uncover the complex biological mechanisms of HCC. More importantly, this novel integrated strategy facilitates identification of risk hub genes as candidate biomarkers for HCC, which could effectively guide clinical treatments.

RFC2, a direct target of miR-744, modulates the cell cycle and promotes the proliferation of CRC cells

Colorectal cancer (CRC) is a common digestive tract malignancy, which is characterized by high mortality, morbidity, and poor prognosis. Replication factor C subunit 2 (RFC2), one RFC family member, was reported to be related to various malignancies and plays an important role in proliferation, invasion, and metastasis. Nonetheless, the RFC2 biological role within CRC is still unknown. RFC2 expression profiles in CRC tissues were collected based on The Cancer Genome Atlas database, whereas miR-744 and RFC2 expression levels were detected in human CRC tissues. miR-744 and RFC2 effects on the proliferation of CRC were assessed both in vivo and in vitro. RFC2 was recognized to be a direct miR-744 target through luciferase reporter assay. RFC2 upregulation was observed within CRC tissues, and a high RFC2 level showed a correlation with poor clinicopathological symptoms. RFC2 knockdown inhibited CRC cell proliferation through promoting cell cycle arrest at the G1 phase, which was achieved by cyclin E2 (CCNE2) downregulation in vivo and in vitro. miR-744 was identified to be the tumor suppressor microRNA, which targeted RFC2 directly for inhibiting the proliferation of CRC cells both in vivo and in vitro. miR-744 downregulation was detected within CRC tissue, and messenger RNA expression showed a negative correlation with RFC2 expression within CRC tissues. Our study demonstrates that the miR-744/RFC2/CCNE2 axis potentially provides a candidate for a treatment strategy for CRC.

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

BACKGROUND

Large-cell neuroendocrine carcinoma of the lung (LCNEC) and small-cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC.

METHODS

GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein-protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re-analyzed, and potential interactions between these genes and miRNAs were explored via FunRich.

RESULTS

A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug-resistance, radio-sensitivity, or autophagy in lung cancer.

CONCLUSION

This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.

RFC3 induces epithelial‑mesenchymal transition in lung adenocarcinoma cells through the Wnt/β‑catenin pathway and possesses prognostic value in lung adenocarcinoma

Lung cancer is a malignant tumor responsible for the highest mortality rate in humans. The identification of novel functional genes is of great importance in the treatment of lung cancer. The reported roles of replication factor C subunit 3 (RFC3) in tumorigenesis are contradictory. The present study aimed to explore the role and mechanism of RFC3 in lung cancer cells. An immunohistochemical study of 165 lung cancer and adjacent tissues was conducted (123 lung adenocarcinoma tissues and 42 lung squamous cell carcinoma tissues). Kaplan-Meier analysis and Cox multivariate analysis were employed to explore the relationship between RFC3 and patient prognosis. In addition, the proliferation, cell cycle distribution and apoptosis of A549 and H1299 cells were determined by MTT assay and flow cytometry, respectively, following cell transfection to induce overexpression and knockdown of RFC3. A Boyden chamber assay and wound-healing assay were conducted to determine the invasive and migratory abilities of A549 and H1299 cells. Western blotting was used to analyze the effects of RFC3 overexpression and RFC3 small interfering RNA-induced knockdown, and to explore the potential mechanism and pathway underlying the effects of RFC3. Positive expression of RFC3 was detected in lung adenocarcinoma, and overexpression of RFC3 shortened the survival time of patients with lung adenocarcinoma. Furthermore, overexpression of RFC3 increased the invasion and migration of A549 cells, whereas knockdown of RFC3 significantly reduced the invasion and migration of H1299 cells. Ectopic expression of RFC3 induced epithelial-mesenchymal transition (EMT), as determined by downregulation of E-cadherin, and upregulation of N-cadherin, vimentin and Wnt signaling target genes, including c-MYC, Wnt1 and β-catenin, and the ratio of phosphorylated-glycogen synthase kinase 3 (GSK3)-β (Ser9)/GSK3-β. In conclusion, RFC3 may be considered a coactivator that promotes the Wnt/β-catenin signaling pathway, and induces EMT and metastasis in lung adenocarcinoma.

Five Core Genes Related to the Progression and Prognosis of Hepatocellular Carcinoma Identified by Analysis of a Coexpression Network

The molecular mechanism of tumorigenesis of the prevalent cancer hepatocellular carcinoma (HCC) is unclear. In this study, through weighted gene coexpression network analysis, a coexpression network was constructed by selecting the top 25% most variant genes in the dataset GSE62232. The average linkage hierarchical clustering identified 24 modules, and among them, the pink module associated with prognosis of HCC was screened. Five gene candidates (PCNA, RFC4, PTTG1, H2AFZ, and RRM1) with a common network in the module were screened after the protein-protein interaction network complex was combined with the coexpression network. After progression and survival analysis, all candidates were identified as real core genes. According to the Human Protein Atlas and the Oncomine database, these genes were dysregulated in HCC samples. The receiver operating characteristic curve proved that the expression levels of the core genes had high diagnostic efficacy. The results of gene set enrichment analysis and functional enrichment analysis demonstrated the importance of the cell cycle-related pathways in HCC progression and prognosis. In conclusion, the five real core genes and cell cycle-related pathways identified in this study could greatly improve the knowledge about HCC progression and contribute to HCC treatment.

Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis

Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and GSE60502), and used them to identify 409 differentially expressed genes (DEGs), including 142 and 267 up- and down-regulated genes, respectively. The DAVID database was used to look for functionally enriched pathways among DEGs, and the STRING database and Cytoscape platform were used to generate a protein-protein interaction (PPI) network for these DEGs. The cytoHubba plug-in was utilized to detect 185 hub genes, and three key clustering modules were constructed with the MCODE plug-in. Gene functional enrichment analyses of these three key clustering modules were further performed, and nine core genes including BIRC5, DLGAP5, DTL, FEN1, KIAA0101, KIF4A, MCM2, MKI67, and RFC4, were identified in the most critical cluster. Subsequently, the hierarchical clustering and expression of core genes in TCGA liver cancer tissues were analyzed using the UCSC Cancer Genomics Browser, and whether elevated core gene expression was linked to a poor prognosis in HCC patients was assessed using the GEPIA database. The PPI of the nine core genes revealed an interaction between FEN1, MCM2, RFC4, and BIRC5. Furthermore, the expression of FEN1 was positively correlated with that of three other core genes in TCGA liver cancer tissues. FEN1 expression in HCC and other tumor types was assessed with the FIREBROWSE and ONCOMINE databases, and results were verified in HCC samples and hepatoma cells. FEN1 levels were also positively correlated with tumor size, distant metastasis and vascular invasion. In conclusion, we identified nine core genes associated with HCC development, offering novel insight into HCC progression. In particular, the aberrantly elevated FEN1 may represent a potential biomarker for HCC diagnosis and treatment.

Key Molecular Events in Cervical Cancer Development

Cervical cancer is the fourth most common cancer among women. Infection by high-risk human papillomavirus (HPV) is the main aetiology for the development of cervical cancer. Infection by high-risk human papillomavirus (HPV) and the integration of the HPV genome into the host chromosome of cervical epithelial cells are key early events in the neoplastic progression of cervical lesions. The viral oncoproteins, mainly E6 and E7, are responsible for the initial changes in epithelial cells. The viral proteins inactivate two main tumour suppressor proteins, p53, and retinoblastoma (pRb). Inactivation of these host proteins disrupts both the DNA repair mechanisms and apoptosis, leading to rapid cell proliferation. Multiple genes involved in DNA repair, cell proliferation, growth factor activity, angiogenesis, as well as mitogenesis genes become highly expressed in cervical intraepithelial neoplasia (CIN) and cancer. This genomic instability encourages HPV-infected cells to progress towards invasive carcinoma. The key molecular events involved in cervical carcinogenesis will be discussed in this review.

Identification of Potential Key Genes for Hepatitis B Virus-Associated Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatitis B virus-associated (HBV(+)) hepatocellular carcinoma (HCC) accounts for a large proportion of liver cancer with poor clinical outcomes and treatment options. However, the underlying molecular mechanisms are still poorly understood. To explore potential key genes in the development of HBV(+)HCC, four series of data (GSE14520, GSE94660, GSE25599, and GSE55092) derived from Gene Expression Omnibus database were analyzed. Totally, 84 upregulated and 46 downregulated common differentially expressed genes (DEGs) were discovered. Gene ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses showed that these DEGs were mainly enriched in cell division and DNA replication biological processes, nucleoplasm and microtubule cellular components, protein-binding molecular functions, and cell cycle and DNA replication pathways. Through protein-protein interaction analysis, 10 hub DEGs with the highest degree of connectivity were indicated, including TOP2A, CDC20, MAD2L1, BUB1B, RFC4, CCNB1, CDKN3, CCNB2, TPX2, and FEN1. Kaplan-Meier analysis revealed that high expression of TOP2A and CDC20 was associated with poor overall survival, relapse-free survival, and high serum alpha-fetoprotein level in HBV(+)HCC. In conclusion, TOP2A and CDC20 were two potential key genes for HBV(+)HCC. Their value in the diagnosis and treatment of HBV(+)HCC requires further investigation.

Identification of key candidate genes and small molecule drugs in cervical cancer by bioinformatics strategy

Purpose

Cervical cancer (CC) is one of the most common malignant tumors among women. The present study aimed at integrating two expression profile datasets to identify critical genes and potential drugs in CC.

Materials and methods

Expression profiles, GSE7803 and GSE9750, were integrated using bioinformatics methods, including differentially expressed genes analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and protein–protein interaction (PPI) network construction. Subsequently, survival analysis was performed among the key genes using Gene Expression Profiling Interactive Analysis websites. Connectivity Map (CMap) was used to query potential drugs for CC.

Results

A total of 145 upregulated genes and 135 downregulated genes in CC were identified. The functional changes of these differentially expressed genes related to CC were mainly associated with cell cycle, DNA replication, p53 signaling pathway, and oocyte meiosis. A PPI network was identified by STRING with 220 nodes and 2,111 edges. Thirteen key genes were identified as the intersecting genes of the enrichment pathways and the top 20 nodes in PPI network. Survival analysis revealed that high mRNA expression of MCM2, PCNA, and RFC4 was significantly associated with longer overall survival, and the survival was significantly better in the low-expression RRM2 group. Moreover, CMap predicted nine small molecules as possible adjuvant drugs to treat CC.

Conclusion

Our study found key dysregulated genes involved in CC and potential drugs to combat it, which might provide insights into CC pathogenesis and might shed light on potential CC treatments.

Identification of RFC5 as a novel potential prognostic biomarker in lung cancer through bioinformatics analysis

Lung cancer is the leading cause of mortalities among all types of cancer. Therefore, the screening of biomarkers that are related with the progression of lung cancer is crucial for early diagnosis and efficient therapy of lung cancer. In the present study, bioinformatic analysis identified replication factor C 5 (RFC5) as a potential novel oncogene in lung cancer. RFC5 functions as a clamp loader and is involved in DNA replication and repair. Analysis of public databases and reverse transcription-quantitative polymerase chain reaction indicated that RFC5 was significantly increased in tumor tissues compared with adjacent normal tissues. A high RFC5 expression was observed to be associated with more aggressive malignant clinicopathological features, including higher T stage, more advanced regional lymph node metastasis and a higher probability of relapse. Notably, there were notable differences in overall survival (OS), first progression and post-progression survival between the high RFC5 expression group and low RFC5 expression group. Univariate and multivariate Cox regression analyses indicated that RFC5 was an independent risk factor that was associated with poorer OS and disease-free survival. According to GSEA, several gene sets that are associated with cell cycle and DNA damage were enriched in the RFC5 overexpression group, which indicated that RFC5 might promote the proliferation of lung cancer cells. Our finding indicated that RFC5 might be a novel prognostic biomarker of lung cancer, and it might be serve as a potential diagnosis and therapy target for lung cancer in the future.

Identification of key genes and pathways for esophageal squamous cell carcinoma by bioinformatics analysis

The aim of the present study was to identify the differentially expressed genes (DEGs) in esophageal squamous-cellcarcinoma (ESCC) and provide potential therapeutic targets. The microarray dataset GSE20347 was downloaded from the Gene Expression Omnibus (GEO) database, and included 17 tissue samples and 13 normal adjacent tissue samples from patients with ESCC. A total of 22,277 DEGs were identified. A heat map for the DEGs was constructed with the Morpheus online tool and the top 200 genes (100 upregulated and 100 downregulated) were selected for further bioinformatics analysis, including analysis of gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, protein-protein interaction networks and Spearman's correlation tests. The results of the GO analysis indicated that the upregulated DEGs were most significantly enriched in membrane-bounded vesicles in the cellular component (CC) category, but were not significantly enriched in any GO terms of the categories biological process (BP) or molecular function (MF); furthermore, the downregulated DEGs were most significantly enriched in regulation of DNA metabolic processes, nucleotide binding and chromosomes in the categories BP, MF and CC, respectively. The KEGG analysis indicated that the downregulated DEGs were enriched in the regulation of cell cycle pathways. The top 10 hub proteins in the protein-protein interaction network were cyclin-dependent kinase 4, budding uninhibited by benzimidazoles 1, cyclin B2, heat shock protein 90AA1, aurora kinase A, H2A histone family member Z, replication factor C subunit 4, and minichromosome maintenance complex component 2, −4 and −7. These proteins are mainly involved in regulating tumor progression. The genes in the four top modules were mainly implicated in regulating cell cycle pathways. Secreted Ly-6/uPAR-related protein (SLURP) was the hub gene, and SLURP and its interacting genes were most enriched in the chromosomal part in the CC category, organelle organization in the BP category and protein binding in the MF category, and were involved in pathways including DNA replication, cell cycle and P53 signaling. The expression of SLURP-1 in fifteen patients with esophageal carcinoma was detected using quantitative polymerase chain reaction analysis, and the results indicated that SLURP-1 expression was significantly decreased in the tumor samples relative to that in normal adjacent tissues. These results suggest that several hub proteins and the hub gene SLURP-1 may serve as potential therapeutic targets, and that gene dysfunction may be involved in the tumorigenesis of ESCC.

Identification of key pathways and genes in the progression of cervical cancer using bioinformatics analysis

The aim of the present study was to investigate the key pathways and genes in the progression of cervical cancer. The gene expression profiles GSE7803 and GSE63514 were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using GEO2R and the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery. The hub genes were identified using Cytoscape and protein-protein interaction (PPI) networks were constructed using the STRING database. A total of 127 and 99 DEGs were identified in the pre-invasive and invasive stages of cervical cancer, respectively. GO enrichment analysis indicated that the DEGs in pre-invasive cervical cancer were primarily associated with the ‘protein binding’, ‘single-stranded DNA-dependent ATPase activity’, ‘DNA replication origin binding’ and ‘microtubule binding’ terms, whereas the DEGs in invasive cervical cancer were associated with the ‘extracellular matrix (ECM) structural constituent’, ‘heparin binding’ and ‘integrin binding’. KEGG enrichment analysis revealed that the pre-invasive DEGs were significantly enriched in the ‘cell cycle’, ‘DNA replication’ and ‘p53 signaling pathway’ terms, while the invasive DEGs were enriched in the ‘amoebiasis’, ‘focal adhesion’, ‘ECM-receptor interaction’ and ‘platelet activation’ terms. The PPI network identified 4 key genes (PCNA, CDK2, VEGFA and PIK3CA), which were hub genes for pre-invasive and invasive cervical cancer. In conclusion, bioinformatics analysis identified 4 key genes in cervical cancer progression (PCNA, CDK2, VEGFA and PIK3CA), which may be potential biomarkers for differentiating normal cervical epithelial tissue from cervical cancer.

Proteomic Investigation to Identify Anticancer Targets of Nemopilema nomurai Jellyfish Venom in Human Hepatocarcinoma HepG2 Cells

Nemopilema nomurai is a giant jellyfish that blooms in East Asian seas. Recently, N. nomurai venom (NnV) was characterized from a toxicological and pharmacological point of view. A mild dose of NnV inhibits the growth of various kinds of cancer cells, mainly hepatic cancer cells. The present study aims to identify the potential therapeutic targets and mechanism of NnV in the growth inhibition of cancer cells. Human hepatocellular carcinoma (HepG2) cells were treated with NnV, and its proteome was analyzed using two-dimensional gel electrophoresis, followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI/TOF/MS). The quantity of twenty four proteins in NnV-treated HepG2 cells varied compared to non-treated control cells. Among them, the amounts of fourteen proteins decreased and ten proteins showed elevated levels. We also found that the amounts of several cancer biomarkers and oncoproteins, which usually increase in various types of cancer cells, decreased after NnV treatment. The representative proteins included proliferating cell nuclear antigen (PCNA), glucose-regulated protein 78 (GRP78), glucose-6-phosphate dehydrogenase (G6PD), elongation factor 1γ (EF1γ), nucleolar and spindle-associated protein (NuSAP), and activator of 90 kDa heat shock protein ATPase homolog 1 (AHSA1). Western blotting also confirmed altered levels of PCNA, GRP78, and G6PD in NnV-treated HepG2 cells. In summary, the proteomic approach explains the mode of action of NnV as an anticancer agent. Further characterization of NnV may help to unveil novel therapeutic agents in cancer treatment.

Arabidopsis replication factor C4 is critical for DNA replication during the mitotic cell cycle

Replication factor C (RFC) is a conserved eukaryotic complex consisting of RFC1/2/3/4/5. It plays important roles in DNA replication and the cell cycle in yeast and fruit fly. However, it is not very clear how RFC subunits function in higher plants, except for the Arabidopsis (At) subunits AtRFC1 and AtRFC3. In this study, we investigated the functions of AtRFC4 and found that loss of function of AtRFC4 led to an early sporophyte lethality that initiated as early as the elongated zygote stage, all defective embryos arrested at the two- to four-cell embryo proper stage, and the endosperm possessed six to eight free nuclei. Complementation of rfc4-1/+ with AtRFC4 expression driven through the embryo-specific DD45pro and ABI3pro or the endosperm-specific FIS2pro could not completely restore the defective embryo or endosperm, whereas a combination of these three promoters in rfc4-1/+ enabled the aborted ovules to develop into viable seeds. This suggests that AtRFC4 functions simultaneously in endosperm and embryo and that the proliferation of endosperm is critical for embryo maturation. Assays of DNA content in rfc4-1/+ verified that DNA replication was disrupted in endosperm and embryo, resulting in blocked mitosis. Moreover, we observed a decreased proportion of late S-phase and M-phase cells in the rfc4-1/-^{FIS2;DD45;ABI3pro::AtRFC4} seedlings, suggesting that incomplete DNA replication triggered cell cycle arrest in cells of the root apical meristem. Therefore, we conclude that AtRFC4 is a crucial gene for DNA replication.

Understanding the functional impact of copy number alterations in breast cancer using a network modeling approach

We apply a network approach to identify genes associated incisor intranswith copy-number alterations in breast cancer pathogenesis.

Levels of human replication factor C4, a clamp loader, correlate with tumor progression and predict the prognosis for colorectal cancer

BACKGROUND

Human replication factor C4 (RFC4) is involved in DNA replication as a clamp loader and is aberrantly regulated across a range of cancers. The current study aimed to investigate the function of RFC4 in colorectal cancer (CRC).

METHODS

The mRNA levels of RFC4 were assessed in 30 paired primary CRC tissues and matched normal colonic tissues by quantitative PCR. The protein expression levels of RFC4 were evaluated by western blotting (n = 16) and immunohistochemistry (IHC; n = 49), respectively. Clinicopathological features and survival data were correlated with the expression of RFC4 by IHC analysis in a tissue microarray comprising 331 surgically resected CRC. The impact of RFC4 on cell proliferation and the cell cycle was assessed using CRC cell lines.

RESULTS

RFC4 expression was significantly increased in CRC specimens as compared to adjacent normal colonic tissues (P <0.05). High levels of RFC4, determined on a tissue microarray, were significantly associated with differentiation, an advanced stage by the Tumor-Node-Metastasis (TNM) staging system, and a poor prognosis, as compared to low levels of expression (P <0.05). However, in multivariate analysis, RFC4 was not an independent predictor of poor survival for CRC. In vitro studies, the loss of RFC4 suppressed CRC cell proliferation and induced S-phase cell cycle arrest.

CONCLUSION

RFC4 is frequently overexpressed in CRC, and is associated with tumor progression and worse survival outcome. This might be attributed to the regulation of CRC cell proliferation and cell cycle arrest by RFC4.

Overexpression of RFC3 is correlated with ovarian tumor development and poor prognosis

Replication factor C3 (RFC3) is an oncogene that can potentially predict prognosis in a variety of human cancers. RFC3 expression in ovarian carcinoma has not yet been determined. In this study, we evaluated the messenger RNA (mRNA) and protein expression levels of RFC3 in normal ovarian and ovarian carcinoma tissues using reverse transcription-polymerase chain reaction (RT-PCR), immunohistochemistry, and Western blots (WB). Results showed that higher RFC3 mRNA and protein levels were detected in ovarian carcinoma tissues by RT-PCR and WB. High RFC3 expression was defined as positive staining in >70 % of each tumor cell. High RFC3 expression was detected in 28.1, 17.6, 11.1, and 5.0 % of invasive carcinomas, borderline tumors, cystadenomas, and in normal ovary cells, respectively. Overexpression of RFC3 was associated with later pN status (p = 0.001), pM status (p = 0.001), and advanced International Federation of Gynecology and Obstetrics (FIGO) stage (p = 0.012) in ovarian carcinomas. Univariate survival analyses showed that RFC3 overexpression was also associated with shortened patient survival (mean 7.7 months in tumors with RFC3 overexpression vs 92.9 months in tumors with normal RFC3 levels; p < 0.001). In multivariate analyses, RFC3 protein levels were a significant prognostic factor for ovarian carcinoma (p < 0.001). In conclusion, our findings suggest that RFC3 protein is an important and independent biomarker with prognostic implications for patients with ovarian carcinoma.

Sine oculis homeobox homolog 1 promotes DNA replication and cell proliferation in cervical cancer

Malignant proliferation is the fundamental trait of tumor cells. The initiation of DNA replication represents a key process for cell proliferation, and has a marked impact on tumorigenesis and progression. Here we report that Sine oculis homeobox homolog 1 (SIX1) functions as a master regulator in DNA replication of cervical cancer cells. The expression of SIX1 was induced by the E7 oncoprotein of human papillomaviruses in cervical intraepithelial neoplasia and cervical cancer. The increase of SIX1 expression resulted in the upregulation of multiple genes related to the initiation of DNA replication, including the genes coding for the proteins in minichromosome maintenance complex (MCM2, MCM3, MCM6), DNA polymerase α-primase complex (POLA1, PRIM1, PRIM2), clamp loader (RFC3, RFC4, RFC5), DNA polymerase δ complex (POLD3) and DNA polymerase ε complex (POLE2). In line with this, the increase of SIX1 expression enhanced DNA synthesis, accelerated G1 to S phase progression, and promoted the proliferation of cervical cancer cells and the growth of cervical cancer. Consistently, knockdown of SIX1 could hamper DNA synthesis, slow down G1 to S phase progression, and suppress tumor cell proliferation and tumor growth. Importantly, SIX1 could more efficiently promote anchorage-independent cell growth. These results suggest that the increase of SIX1 expression could promote tumorigenesis, progression and invasive growth of cervical cancer by promoting DNA replication, and that targeting SIX1 may have significant therapeutic value in cervical cancer treatment.

Genomic profiling reveals distinctive molecular relapse patterns in IDH1/2 wild-type glioblastoma

Molecular changes associated with the progression of glioblastoma after standard radiochemotherapy remain poorly understood. We compared genomic profiles of 27 paired primary and recurrent IDH1/2 wild-type glioblastomas by genome-wide array-based comparative genomic hybridization. By bioinformatic analysis, primary and recurrent tumor profiles were normalized and segmented, chromosomal gains and losses identified taking the tumor cell content into account, and difference profiles deduced. Seven of 27 (26%) pairs lacked DNA copy number differences between primary and recurrent tumors (equal pairs). The recurrent tumors in 9/27 (33%) pairs contained all chromosomal imbalances of the primary tumors plus additional ones, suggesting a sequential acquisition of and/or selection for aberrations during progression (sequential pairs). In 11/27 (41%) pairs, the profiles of primary and recurrent tumors were divergent, i.e., the recurrent tumors contained additional aberrations but had lost others, suggesting a polyclonal composition of the primary tumors and considerable clonal evolution (discrepant pairs). Losses on 9p21.3 harboring the CDKN2A/B locus were significantly more common in primary tumors from sequential and discrepant (nonequal) pairs. Nonequal pairs showed ten regions of recurrent genomic differences between primary and recurrent tumors harboring 46 candidate genes associated with tumor recurrence. In particular, copy numbers of genes encoding apoptosis regulators were frequently changed at progression. In summary, approximately 25% of IDH1/2 wild-type glioblastoma pairs have stable genomic imbalances. In contrast, approximately 75% of IDH1/2 wild-type glioblastomas undergo further genomic aberrations and alter their clonal composition upon recurrence impacting their genomic profile, a process possibly facilitated by 9p21.3 loss in the primary tumor. © 2014 Wiley Periodicals, Inc.

Ménage à trois: an evolutionary interplay between human papillomavirus, a tumor, and a woman

Cervical cancer is the third most common cancer in women with human papillomavirus (HPV) being a key etiologic factor of this devastating disease. In this article, we describe modern advances in the genomics and transcriptomics of cervical cancer that led to uncovering the key gene drivers. We also introduce, herein, a model of cervical carcinogenesis that explains how the interplay between virus, tumor, and woman results in the selection of clones that simultaneously harbor genomic amplifications for genes that drive cell cycle, antiviral response, and inhibit cell differentiation. The new model may help researchers understand the controversies in antiviral therapy and immunogenetics of this cancer and may provide a basis for future research directions in early diagnostics and personalization of therapy.

FOXM1 mediates Dox resistance in breast cancer by enhancing DNA repair

Transcription factors are direct effectors of altered signaling pathways in cancer and frequently determine clinical outcomes in cancer patients. To uncover new transcription factors that would determine clinical outcomes in breast cancer, we systematically analyzed gene expression data from breast cancer patients. Our results revealed that Forkhead box protein M1 (FOXM1) is the top-ranked survival-associated transcription factor in patients with triple-negative breast cancer. Surprisingly, silencing FOXM1 expression led breast cancer cells to become more sensitive to doxorubicin (Dox). We found that FOXM1-dependent resistance to Dox is mediated by regulating DNA repair genes. We further demonstrated that NFκB1 interacts with FOXM1 in the presence of Dox to protect breast cancer cells from DNA damage. Finally, silencing FOXM1 expression in breast cancer cells in a mouse xenograft model significantly sensitized the cells to Dox. Our systematic approaches identified an unexpected role of FOXM1 in Dox resistance by regulating DNA repair genes, and our findings provide mechanistic insights into how FOXM1 mediates resistance to Dox and evidence that FOXM1 may be a promising therapeutic target for sensitizing breast cancer cells to Dox.

Integrative genomics identified RFC3 as an amplified candidate oncogene in esophageal adenocarcinoma

PURPOSE

Esophageal adenocarcinoma (EAC) is a lethal malignancy that can develop from the premalignant condition, Barrett's esophagus (BE). Currently, there are no validated simple methods to predict which patients will progress to EAC. A better understanding of the genetic mechanisms driving EAC tumorigenesis is needed to identify new therapeutic targets and develop biomarkers capable of identifying high-risk patients that would benefit from aggressive neoadjuvant therapy. We employed an integrative genomics approach to identify novel genes involved in EAC biology that may serve as useful clinical markers.

EXPERIMENTAL DESIGN

Whole genome tiling-path array comparative genomic hybridization was used to identify significant regions of copy number alteration in 20 EACs and 10 matching BE tissues. Copy number and gene expression data were integrated to identify candidate oncogenes within regions of amplification and multiple additional sample cohorts were assessed to validate candidate genes.

RESULTS

We identified RFC3 as a novel, candidate oncogene activated by amplification in approximately 25% of EAC samples. RFC3 was also amplified in BE from a patient whose EAC harbored amplification and was differentially expressed between nonmalignant and EAC tissues. Copy number gains were detected in other cancer types and RFC3 knockdown inhibited proliferation and anchorage-independent growth of cancer cells with increased copy number but had little effect on those without. Moreover, high RFC3 expression was associated with poor patient outcome in multiple cancer types.

CONCLUSIONS

RFC3 is a candidate oncogene amplified in EAC. RFC3 DNA amplification is also prevalent in other epithelial cancer types and RFC3 expression could serve as a prognostic marker.

Multiplexed, high-throughput analysis of 3D microtissue suspensions

Three-dimensional (3D) tissue models have significantly improved our understanding of structure/function relationships and promise to lead to new advances in regenerative medicine. However, despite the expanding diversity of 3D tissue fabrication methods, approaches for functional assessment have been relatively limited. Here, we describe the fabrication of microtissue (μ-tissue) suspensions and their quantitative evaluation with techniques capable of analyzing large sample numbers and performing multiplexed parallel analysis. We applied this platform to 3D μ-tissues representing multiple stages of liver development and disease including: embryonic stem cells, bipotential hepatic progenitors, mature hepatocytes, and hepatoma cells photoencapsulated in polyethylene glycol hydrogels. Multiparametric μ-tissue cytometry enabled quantitation of fluorescent reporter expression within populations of intact μ-tissues (n≥ 10²-10³) and sorting-based enrichment of subsets for subsequent studies. Further, 3D μ-tissues could be implanted in vivo, respond to systemic stimuli, retrieved and quantitatively assessed. In order to facilitate multiplexed 'pooled' experimentation, fluorescent labeling strategies were developed and utilized to investigate the impact of μ-tissue composition and exposure to soluble factors. In particular, examination of drug/gene interactions on collections of 3D hepatoma μ-tissues indicated synergistic influence of doxorubicin and siRNA knockdown of the anti-apoptotic gene BCL-XL. Collectively, these studies highlight the broad utility of μ-tissue suspensions as an enabling approach for high n, populational analysis of 3D tissue biology in vitro and in vivo.

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

BACKGROUND

Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse.

METHODS

We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models.

RESULTS

An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database.

CONCLUSIONS

This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples.

Molecular targets for liver cancer therapy: From screening of target genes to clinical trials

Cancer arises from the accumulation of genetic alterations, and the inactivation of oncogenes, or recovery of suppressor genes, are promising strategies for cancer treatment. Genome-based drug research starts with identification of target genes and is accomplished by exploitation of target-based drugs such as monoclonal antibodies, small molecules and antisense drugs. Recently, clinical trials for treatment of advanced hepatocellular carcinoma (HCC) have been performed, and the effectiveness of sorafenib, an oral multikinase inhibitor of the vascular endothelial growth factor receptor and Ras kinase, has been demonstrated. In addition to known target genes, microarray technology has enabled us to constitute novel therapeutic targets, and many researchers have applied this technology in studies of HCC and have identified candidate target genes, validated to affect cell growth. In addition, promoter arrays for whole-genome epigenetic aberration analysis, ChIP-chip analysis using tiling arrays, and high-throughput sequencing systems have been applied to drug discovery. To elucidate the status of therapeutic target genes in vivo, development of diagnostic markers for stratification of patients is a pressing need. Here, we review recent advances in microarray technology for liver cancer, discuss the innovations and approaches to therapeutic target discovery, and present data regarding the outcome of gene target therapy using monoclonal antibodies and molecular diagnostic markers in our laboratory.

Transcriptional analysis of doxorubicin-induced cytotoxicity and resistance in human hepatocellular carcinoma cell lines

BACKGROUND/AIMS

Hepatoma is either intrinsically resistant to chemotherapy or response to it but later develop resistance. The aim of this study was to clarify the relationship of treatment with doxorubicin (Dox) in hepatoma HepG2 cells and drug resistance developed by Dox.

METHODS

We have analysed the bioactivities and gene expression profiles of multidrug resistant (MDR) HepG2/DR cell line and its parental HepG2 cell, which were exposure to Dox.

RESULTS

We confirmed that Dox-induced apoptosis of HepG2 cells in a time-dependent manner; cDNA microarray and hierarchical cluster analysis demonstrate that the features of the transcriptional programme of the later response to Dox in HepG2 cells and MDR HepG2/DR cells have a common character, which is upregulation of stress response, cytoskeleton, ubiquitin-proteasome pathway and repressed G-protein signal transduction system; differentially expressed genes in MDR HepG2/DR such as drug transporters and tumour-associated antigens were verified at the levels of mRNA by semiquantitative reverse transcriptase-polymerase chain reaction.

CONCLUSIONS

These results reveal novel co-ordinated changes that occurred in resistant HepG2 cells to survive from cell apoptosis elicited by Dox treatment.