Fuqiang Yin

Tumor suppressor genes associated with drug resistance in ovarian cancer (review).

Ovarian cancer is a fatal gynecological cancer and a major cause of cancer-related mortality worldwide. The main limitation to a successful treatment for ovarian cancer is the development of drug resistance to combined chemotherapy. Tumor suppressor genes (TSGs) are wild-type alleles of genes which play regulatory roles in diverse cellular activities, and whose loss of function contributes to the development of cancer. It has been demonstrated that TSGs contribute to drug resistance in several types of solid tumors. However, an overview of the contribution of TSGs to drug resistance in ovarian cancer has not previously been reported. In this study, 15 TSGs responding to drug resistance in ovarian cancer were reviewed to determine the relationship of TSGs with ovarian cancer drug resistance. Furthermore, gene/protein-interaction and bio-association analysis were performed to demonstrate the associations of these TSGs and to mine the potential drug resistance-related genes in ovarian cancer. We observed that the 15 TSGs had close interactions with each other, suggesting that they may contribute to drug resistance in ovarian cancer as a group. Five pathways/processes consisting of DNA damage, apoptosis, cell cycle, DNA binding and methylation may be the key ways with which TSGs participate in the regulation of drug resistance. In addition, ubiquitin C (UBC) and six additional TSGs including the adenomatous polyposis coli gene (APC), death associated protein kinase gene (DAPK), pleiomorphic adenoma gene-like 1 (PLAGL1), retinoblastoma susceptibility gene (RB1), a gene encoding an apoptosis-associated speck-like protein (PYCARD/ASC) and tumor protein 63 (TP63), which had close interactions with the 15 TSGs, are potential drug resistance-related genes in ovarian cancer.

Oncogenes associated with drug resistance in ovarian cancer

PurposeOncogenes play pivotal roles in the development of cancer, and disturbances in their expression have been implicated in drug resistance. However, an overview of the contribution of oncogenes to drug resistance in ovarian cancer has not previously been reported. This study aimed to review the drug resistance-related oncogenes in ovarian cancer and precisely determine their relationships.MethodsThe oncogenes associated with drug resistance in ovarian cancer from available papers were summarized, and a comprehensive bioinformatics analysis including pathway enrichment, biological processes annotation, protein/gene interaction and microRNA–mRNA interaction was performed.ResultsTotal of 25 oncogenes contributing to drug resistance in ovarian cancer was integrated and further analyzed. An oncogene-mediated drug resistance pathway that explains the associations of 21 of these oncogenes in drug resistance was drafted on the basis of previously published papers. The downstream location of v-akt murine thymoma viral oncogene (AKT) and B-cell CLL/lymphoma 2-associated X protein (BAX) with respect to many other oncogenes was determined, indicating that the two genes may play a central role, and the AKT- and BAX-mediated signaling are the main pathways accounting for the involvement of oncogenes in drug resistance in ovarian cancer. Besides, the annotation of biological process indicated that the apoptosis (cell death) and phosphorylation (phosphate metabolic process) might be the two major biological routes through which oncogenes contribute to drug resistance in ovarian cancer. In addition, on the basis of the comprehensive analysis of microRNA–mRNA interactions, 11 microRNAs were identified to be targeted at least 7 of the 25 oncogenes, indicating that those microRNAs could be an important regulator of the 25 oncogenes. Collectively, by integrating and further analyzing the available data on these oncogenes, this study contributes to improving our understanding of the mechanisms by which their expression leads to drug resistance in this ovarian cancer.

Bioinformatic analysis of chemokine (C-C motif) ligand 21 and SPARC-like protein 1 revealing their associations with drug resistance in ovarian cancer

Chemokine (C-C motif) ligand 21 (CCL21) and SPARC-like protein 1 (SPARCL1/MAST9/hevin/SC-1) are associated with various biological behavior in the development of cancers. Although the expression of CCL21 and SPARCL1 is downregulated in many solid tumors, their roles in ovarian cancer and their associations with drug resistance have rarely been studied. We performed a comprehensive bioinformatic analysis consisting of motif analysis, literature co-occurrence, gene/protein-gene/protein interaction network, protein-small molecule interaction network, and microRNAs enrichments which revealed that CCL21 and SPARCL1 directly or indirectly interact with a number of genes, proteins, small molecules and pathways associated with drug resistance in ovarian and other cancers. These results suggested that CCL21 and SPARCL1 may contribute to drug resistance in ovarian cancer. This study provided important information for further investigation of drug resistance-related functions of CCL21 and SPARCL1 in ovarian cancer.

Upregulation of E2F transcription factor 3 is associated with poor prognosis in hepatocellular carcinoma

E2F transcription factor 3 (E2F3), a member of the E2F transcription factor family and a member of the genes involved in the regulation of cell cycle, is an oncogene with strong proliferative potential. E2F3 is involved in many processes and plays important roles in the development of several types of cancer, while its relationship with prognosis in hepatocellular carcinoma (HCC) has yet to be reported. In the present study, based on 4 independent microarray data sets which covered 385 cases of HCC and 327 cases of normal livers retrieved from the Oncomine database, we demonstrated that E2F3 was upregulated at least 1.5-fold and on average 2.3-fold in HCC when compared with normal controls. Comprehensive bioinformatics analysis consisting of protein-protein interaction, gene co-occurrence, microRNA-mRNA interaction and biological process annotation indicated that E2F3 interacted with a large number of genes, proteins and microRNAs which were all associated with poor prognosis in patients with HCC and other types of cancer, suggesting that E2F3 may also serve as a biomarker for poor prognosis. Taken together, for the first time, we show that the overexpression of E2F3 may be associated with unfavorable prognosis in HCC.

Novel microRNAs expression of patients with chemotherapy drug-resistant and chemotherapy-sensitive epithelial ovarian cancer

The aim of this study is to examine the microRNA (miRNA) expression of epithelial ovarian cancer (EOC) in both drug-resistant and drug-sensitive tissues and to explore the pathogenic characteristics of drug-resistant miRNAs in EOC. The samples with 10 cases of drug-resistant and drug-sensitive EOC tissue were obtained from undergoing surgical resection of ovarian cancer (OC). Total miRNAs were extracted and isolated, respectively. Hybridization was carried out on miRNA microarray chip. Real-time polymerase chain reaction (RT-PCR) was performed to confirm the difference of miRNA expression. Bioinformatic software was used to predict the possible target genes of each miRNA which expressed differently. The results indicated that four miRNAs related drug-resistance been identified, and the expression of hsa-miR-152 and hsa-miR-381 in drug-resistant OC tissue was significantly higher compared with those in drug-sensitive tissue (P < 0.01). However, expression of hsa-miR-200a-3p and hsa-miR-429 were downregulated in drug-resistant tissues (P < 0.01). The results obtained by miRNA microarrays of differential expression with hsa-miR-106b-3p, hsa-miR-152, hsa-miR-200a-3p, hsa-miR-381, and hsa-miR-429 were confirmed by real-time PCR. There were 62 significantly different miRNAs, including 42 significant upregulated miRNAs and 20 significant downregulated miRNAs in the drug-resistant tissue. Five databases, including Target Scan, miRanda, miRDB, PicTar5, and RNA22, were used for bioinformatics prediction. In conclusion, miRNA microarray analysis has become a fast and efficient molecular biological technology for the study of biological information. hsa-miR-152, hsa-miR-200a-3p, hsa-miR-381, and hsa-miR-429 may participate in the formation of drug resistance in EOC through the target genes predicted.

Discovery of microarray-identified genes associated with ovarian cancer progression.

Ovarian cancer is the most lethal cancer of female reproductive system. There is a consistent and urgent need to better understand its mechanism. In this study, we retrieved 186 genes that were dysregulated by at least 4-fold in 594 ovarian serous cystadenocarcinomas in comparison with eight normal ovaries, according to The Cancer Genome Atlas Ovarian Statistics data deposited in Oncomine database. DAVID analysis of these genes enriched two biological processes indicating that the cell cycle and microtubules might play critical roles in ovarian cancer progression. Among these 186 genes, 46 were dysregulated by at least 10-fold and their expression was further confirmed by the Bonome Ovarian Statistics data deposited in Oncomine, which covered 185 cases of ovarian carcinomas and 10 cases of normal ovarian surface epithelium. Six genes, including aldehyde dehydrogenase 1 family, member A2 (ALDH1A2), alcohol dehydrogenase 1B (class I), β polypeptide (ADH1B), NEL-like 2 (chicken) (NELL2), hemoglobin, β (HBB), ATP-binding cassette, sub-family A (ABC1), member 8 (ABCA8) and hemoglobin, α1 (HBA1) were identified to be downregulated by at least 10-fold in 779 ovarian cancers compared with 18 normal controls. Using mRNA expression profiles retrieved from microarrays deposited in the Gene Expression Omnibus Profiles database, RT-qPCR measurement and bioinformatics analysis, we further indicated that high expression of HBB might predict a poorer 5-year survival, high expression of ALDH1A2 and ABCA8 might predict a poor outcome; while ALDH1A2, ADH1B, HBB and ABCA8, in particular the former two genes, might be associated with drug resistance, and ALDH1A2 and NELL2 might contribute to invasiveness and metastasis in ovarian cancer. This study thus contributes to our understanding of the mechanism of ovarian cancer progression and development, and the six identified genes may be potential therapeutic targets and biomarkers for diagnosis and prognosis.

Downregulation of tumor suppressor gene ribonuclease T2 and gametogenetin binding protein 2 is associated with drug resistance in ovarian cancer.

Ribonuclease T2 (RNASET2) and gametogenetin binding protein 2 (GGNBP2) are tumor suppressor genes whose expression is downregulated in ovarian and other types of cancer. However, whether the proteins encoded by these genes are associated with drug resistance has rarely been studied. Using real-time quantitative polymerase chain reaction, in the present study we showed that RNASET2 and GGNBP2 mRNA levels were significantly lower in A2780-CBP (carboplatin-resistant) and A2780-DDP (cisplatin-resistant) ovarian cancer cells than in the parental A2780 cells and were downregulated in drug-resistant ovarian cancer tissues compared with their drug-sensitive counterparts. These findings were consistent with the expression profiles determined from microarray data retrieved from the Gene Expression Omnibus Profiles database. Accordingly, we hypothesized that the downregulation of RNASET2 and GGNBP2 is involved in the development of drug resistance in ovarian cancer. A comprehensive bioinformatics analysis of the two genes was therefore conducted, including gene/protein-gene/protein interactions, biological process annotation, pathway enrichment of co-expressed genes and microRNA-mRNA analyses. The integrated results suggested that RNASET2 and GGNBP2 contributed to drug resistance in ovarian cancer, via direct or indirect interactions with a number of microRNAs, genes and proteins involved in a wide range of biological processes and pathways. The information provided in the present study provides insight for further investigations of the drug resistance-related functions of RNASET2 and GGNBP2.

Downregulation of NEK11 is associated with drug resistance in ovarian cancer

NEKs [NIMA (never in mitosis gene A)-related expressed kinase] are involved in ovarian cancer development and progression, while their association with drug resistance is limited, especially NEK11, and its relationship with drug resistance has never been reported. In this study, on the basis of comprehensive bioinformatic analyses, including mRNA expression according to microarray data, protein/gene interaction, protein-small molecule interaction, annotation of biological process and microRNA-mRNA interaction analysis, we revealed that the NEK11 mRNA was significantly downregulated in 586 cases of ovarian serous cystadenocarcinomas and cisplatin-resistant A2780 ovarian cancer cells, and interacted with 22 proteins and 4 small molecules which all were contributed to drug resistance in ovarian cancer. Furthermore, seven cell cycle-related biological processes were annotated with NEK11, drug resistance and ovarian cancer, suggesting that NEK11 potentially was involved in the drug resistance in ovarian cancer via its regulatory roles in the cell cycle. In addition, among the eight microRNAs predicted to be most strongly targeting NEK11, the majority were involved in drug resistance in ovarian and other cancers. All those results provide a very strong possibility that the notable downregulation of NEK11 in cisplatin-resistant ovarian cancer cells was involved in drug resistance, via its interactions with drug resistance-related genes, proteins, small molecules, microRNAs and biological processes, particularly the cell cycle-related processes. To our knowledge, this is the first report of the association of NEK11 with drug resistance in cancer, and it would pave the way for further investigation of the drug resistance-related functions of this gene.

Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths. The average survival and 5-year survival rates of HCC patients still remains poor. Thus, there is an urgent need to better understand the mechanisms of cancer progression in HCC and to identify useful biomarkers to predict prognosis.MethodsPublic data portals including Oncomine, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) profiles were used to retrieve the HCC-related microarrays and to identify potential genes contributed to cancer progression. Bioinformatics analyses including pathway enrichment, protein/gene interaction and text mining were used to explain the potential roles of the identified genes in HCC. Quantitative real-time polymerase chain reaction analysis and Western blotting were used to measure the expression of the targets. The data were analysed by SPSS 20.0 software.ResultsWe identified 80 genes that were significantly dysregulated in HCC according to four independent microarrays covering 386 cases of HCC and 327 normal liver tissues. Twenty genes were consistently and stably dysregulated in the four microarrays by at least 2-fold and detection of gene expression by RT-qPCR and western blotting showed consistent expression profiles in 11 HCC tissues compared with corresponding paracancerous tissues. Eleven of these 20 genes were associated with disease-free survival (DFS) or overall survival (OS) in a cohort of 157 HCC patients, and eight genes were associated with tumour pathologic PT, tumour stage or vital status. Potential roles of those 20 genes in regulation of HCC progression were predicted, primarily in association with metastasis. INTS8 was specifically correlated with most clinical characteristics including DFS, OS, stage, metastasis, invasiveness, diagnosis, and age.ConclusionThe significantly dysregulated genes identified in this study were associated with cancer progression and prognosis in HCC, and might be potential therapeutic targets for HCC treatment or potential biomarkers for diagnosis and prognosis.

Downregulation of transient receptor potential cation channel, subfamily C, member 1 contributes to drug resistance and high histological grade in ovarian cancer

Transient receptor potential cation channel, subfamily C, member 1 (TRPC1) participates in many physiological functions but has also been implicated in cancer development. However, little is known about the role of TRPC1 in ovarian cancer (OC), including the drug resistance of these tumors. In the present study, a significant and consistent downregulation of TRPC1 in drug-resistant OC tissues/cells was determined using real-time quantitative polymerase chain reaction assays and the microarrays deposited in Oncomine and Gene Expression Omnibus (GEO) profiles. Protein/gene-protein/gene and protein-chemical interactions indicated that TRPC1 interacts with 14 proteins/genes and 6 chemicals, all of which are involved in the regulation of drug resistance in OC. Biological process annotation of TRPC1, OC, and drug resistance indicated a role for TRPC1 in drug-resistance-related functions in OC, mainly via the cell cycle, gene expression and cell growth and cell death. Analysis of mRNA-microRNA interactions showed that 8 out of 11 major pathways enriched from 38 predominant microRNAs targeting TRPC1 were involved in the regulation of drug resistance in OC, and 8 out of these top 10 microRNAs were implicated in the drug resistance in ovarian and other cancers. In a clinical analysis using data obtained from The Cancer Genome Atlas project (TCGA) cohort on 341 OC patients, TRPC1 expression was found to differ significantly between grade 2 and grade 3 tumors, with low-level expression correlating with higher tumor grade. This is the first report to show a potential association between the downregulation of TRPC1 and both drug resistance and high histological tumor grade in OC. Our results provide the basis for further investigations of the drug-resistance-related functions of TRPC1 in OC and other forms of cancer.