Correlation between expression of oncogene products and resistance to anticancer drugs in cultured ovarian cancer cell lines

Despite recent advances in the application of chemotherapy to ovarian cancer, the development of alternative therapies that retain activity against drug-resistant-tumors remains a high priority. We analyzed a number of cultured ovarian cancer cell lines of different tissue types for the presence or absence of sensitivity to various anticancer drugs as well as expression patterns of oncogene products (erbB-2, EGFR, bcl-2). As a result, we identified oncogene products that were related to resistance. Using 9 cultured cell lines of ovarian cancers (serous, mucinous, endometrioid, clear, undifferentiated), sensitivities to anticancer drugs were investigated using the MTT assay. The phenotypes of oncogene products expressed by the above cultured cell lines were analyzed by Western blotting. The oncogene products involved in resistance to anticancer drugs were identified by multivariate analysis. Positive correlation between the resistance to anticancer drugs and the oncogene products was obtained by multivariate analysis for (a) CDDP and erbB-2 (b) x p-16 and erbB-2, and (c) MMC and EGFR. Correlation between resistance to anticancer drugs and expression of certain oncogene products was obtained in ovarian cancers, suggesting that sensitivity to anticancer drugs could be predicated prior to chemotherapy.     

转录因子及miRNA调控食管癌耐药机制研究

由于耐药性的存在,不同患者在使用相同药物时会导致治疗效果的差异.因此识别耐药性相关的关键生物学标记,有助于临床医生快速选择出适合的药物,延长患者的生存时间,对药物研发以及药物的作用机制的详细研究具有重要意义.首先在食管癌细胞系中筛选不同药物的耐药及敏感细胞系,从中找到不同药物耐药相关的基因,将这些计算得到的耐药相关基因...     

Generation of a predictive melphalan resistance index by drug screen of B-cell cancer cell lines

Background

Recent reports indicate that in vitro drug screens combined with gene expression profiles (GEP) of cancer cell lines may generate informative signatures predicting the clinical outcome of chemotherapy. In multiple myeloma (MM) a range of new drugs have been introduced and now challenge conventional therapy including high dose melphalan. Consequently, the generation of predictive signatures for response to melphalan may have a clinical impact. The hypothesis is that melphalan screens and GEPs of B-cell cancer cell lines combined with multivariate statistics may provide predictive clinical information.

Materials and Methods

Microarray based GEPs and a melphalan growth inhibition screen of 59 cancer cell lines were downloaded from the National Cancer Institute database. Equivalent data were generated for 18 B-cell cancer cell lines. Linear discriminant analyses (LDA), sparse partial least squares (SPLS) and pairwise comparisons of cell line data were used to build resistance signatures from both cell line panels. A melphalan resistance index was defined and estimated for each MM patient in a publicly available clinical data set and evaluated retrospectively by Cox proportional hazards and Kaplan-Meier survival analysis.

Principal Findings

Both cell line panels performed well with respect to internal validation of the SPLS approach but only the B-cell panel was able to predict a significantly higher risk of relapse and death with increasing resistance index in the clinical data sets. The most sensitive and resistant cell lines, MOLP-2 and RPMI-8226 LR5, respectively, had high leverage, which suggests their differentially expressed genes to possess important predictive value.

Conclusion

The present study presents a melphalan resistance index generated by analysis of a B-cell panel of cancer cell lines. However, the resistance index needs to be functionally validated and correlated to known MM biomarkers in independent data sets in order to better understand the mechanism underlying the preparedness to melphalan resistance.     

Use of isogenic human cancer cells for high-throughput screening and drug discovery

Cell-based screening for novel tumor-specific drugs has been compromised by the lack of appropriate control cells. We describe a strategy for drug screening based on isogenic human cancer cell lines in which key tumorigenic genes have been deleted by targeted homologous recombination. As a test case, a yellow fluorescent protein (YFP) expression vector was introduced into the colon cancer cell line DLD-1, and a blue fluorescent protein (BFP) expression vector was introduced into an isogenic derivative in which the mutant K-Ras allele had been deleted. Co-culture of both cell lines allowed facile screening for compounds with selective toxicity toward the mutant Ras genotype. Among 30,000 compounds screened, a novel cytidine nucleoside analog was identified that displayed selective activity in vitro and inhibited tumor xenografts containing mutant Ras. The present data demonstrate a broadly applicable approach for mining therapeutic agents targeted to the specific genetic alterations responsible for cancer development.     

JFCR39, a panel of 39 human cancer cell lines, and its application in the discovery and development of anticancer drugs

Over the past few decades, panels of human cancer cell lines have made a significant contribution to the discovery and development of anticancer drugs. The National Cancer Institute 60 (NCI60), which consists of 60 cell lines from various human cancer types, remains the most powerful human cancer cell line panel for high throughput screening of anticancer drugs. The development of JFCR39, comprising a panel of 39 human cancer cell lines coupled with a drug-activity database, was based on NCI60. Like NCI60, JFCR39 not only provides disease-oriented information but can also predict the action mechanism or molecular target of a given antitumor agent by utilizing the COMPARE algorithm. The molecular targets of ZSTK474 as well as several other antitumor agents have been identified by using JFCR39 and some of these compounds have since entered clinical trials. In this review, we will describe human cancer cell line panels particularly JFCR39 and its application in the discovery and/or development of anticancer drug candidates.     

Proteomics in pancreatic cancer research

In this review, we give an overview of the actual role of proteomic technologies in the study of pancreatic cancers (PCs). We describe PC proteomics on the basis of sample origins, i.e. tissues, body fluids, and PC cell lines. As regards PC tissues, we report the identification of a number of candidate biomarkers of precursor lesions that may allow early diagnosis of this neoplasia. Moreover, we describe cytoskeletal and hypoxia-regulated proteins that confirm the involvement of cytoskeleton modifications and metabolism adaptations in carcinogenesis. We also discuss the most important biomarkers identified by proteomic analysis involved in local invasion and distant metastasis, and in the cross-talk between pancreatic tumor and the surrounding stroma. Furthermore, we report novel candidate biomarkers identified in serum, plasma, and pancreatic juice of cancer patients compared with cancer-free controls. Proteomic alterations in PC cell line models as compared to normal controls and studies on cell lines treated with drugs or new agents to understand their mechanism of pharmacological action or the onset of drug resistance are also presented. Finally, we discuss the recent improvements obtained in classical 2-DE and high-throughput proteomic strategies able to allow the overcoming of relevant proteomic drawbacks.     

The potential role of Alu Y in the development of resistance to SN38 (Irinotecan) or oxaliplatin in colorectal cancer

Background

Irinotecan (SN38) and oxaliplatin are chemotherapeutic agents used in the treatment of colorectal cancer. However, the frequent development of resistance to these drugs represents a considerable challenge in the clinic. Alus as retrotransposons comprise 11% of the human genome. Genomic toxicity induced by carcinogens or drugs can reactivate Alus by altering DNA methylation. Whether or not reactivation of Alus occurs in SN38 and oxaliplatin resistance remains unknown.

Results

We applied reduced representation bisulfite sequencing (RRBS) to investigate the DNA methylome in SN38 or oxaliplatin resistant colorectal cancer cell line models. Moreover, we extended the RRBS analysis to tumor tissue from 14 patients with colorectal cancer who either did or did not benefit from capecitabine + oxaliplatin treatment. For the clinical samples, we applied a concept of ‘DNA methylation entropy’ to estimate the diversity of DNA methylation states of the identified resistance phenotype-associated methylation loci observed in the cell line models. We identified different loci being characteristic for the different resistant cell lines. Interestingly, 53% of the identified loci were Alu sequences- especially the Alu Y subfamily. Furthermore, we identified an enrichment of Alu Y sequences that likely results from increased integration of new copies of Alu Y sequence in the drug-resistant cell lines. In the clinical samples, SOX1 and other SOX gene family members were shown to display variable DNA methylation states in their gene regions. The Alu Y sequences showed remarkable variation in DNA methylation states across the clinical samples.

Conclusion

Our findings imply a crucial role of Alu Y in colorectal cancer drug resistance. Our study underscores the complexity of colorectal cancer aggravated by mobility of Alu elements and stresses the importance of personalized strategies, using a systematic and dynamic view, for effective cancer therapy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1552-y) contains supplementary material, which is available to authorized users.     

NCI60 cancer cell line panel data and RNAi analysis help identify EAF2 as a modulator of simvastatin and lovastatin response in HCT-116 cells

Simvastatin and lovastatin are statins traditionally used for lowering serum cholesterol levels. However, there exists evidence indicating their potential chemotherapeutic characteristics in cancer. In this study, we used bioinformatic analysis of publicly available data in order to systematically identify the genes involved in resistance to cytotoxic effects of these two drugs in the NCI60 cell line panel. We used the pharmacological data available for all the NCI60 cell lines to classify simvastatin or lovastatin resistant and sensitive cell lines, respectively. Next, we performed whole-genome single marker case-control association tests for the lovastatin and simvastatin resistant and sensitive cells using their publicly available Affymetrix 125K SNP genomic data. The results were then evaluated using RNAi methodology. After correction of the p-values for multiple testing using False Discovery Rate, our results identified three genes (NRP1, COL13A1, MRPS31) and six genes (EAF2, ANK2, AKAP7, STEAP2, LPIN2, PARVB) associated with resistance to simvastatin and lovastatin, respectively. Functional validation using RNAi confirmed that silencing of EAF2 expression modulated the response of HCT-116 colon cancer cells to both statins. In summary, we have successfully utilized the publicly available data on the NCI60 cell lines to perform whole-genome association studies for simvastatin and lovastatin. Our results indicated genes involved in the cellular response to these statins and siRNA studies confirmed the role of the EAF2 in response to these drugs in HCT-116 colon cancer cells.     

A human IAP-family gene, apollon, expressed in human brain cancer cells.

IAP is a family of protein that has baculovirus IAP repeat (BIR) domains and inhibits apoptosis. We found a human IAP family gene, which we named Apollon, encoding a huge protein (530 kDa) that contains a single BIR domain and a ubiquitin-conjugating enzyme domain, that is a human homolog of BRUCE. Apollon protein was expressed in four of six brain cancers (gliomas), and one of five ovarian cancers in 38 human cancer cell lines that we examined. Among the brain cancer cell lines, SNB-78 expressed a high level of Apollon, and this cell line shows resistance against various anticancer drugs. Treating SNB-78 cells with antisense oligonucleotide against Apollon reduced the expression of Apollon protein, and significantly sensitized the cells to apoptosis induced by cisplatin and camptothecin. These results suggest that Apollon protects SNB-78 cells from undergoing apoptosis and, at least in part, plays a role in tumorigenesis and drug resistance of this cell line.     

In silico drug combination discovery for personalized cancer therapy

Background

Drug combination therapy, which is considered as an alternative to single drug therapy, can potentially reduce resistance and toxicity, and have synergistic efficacy. As drug combination therapies are widely used in the clinic for hypertension, asthma, and AIDS, they have also been proposed for the treatment of cancer. However, it is difficult to select and experimentally evaluate effective combinations because not only is the number of cancer drug combinations extremely large but also the effectiveness of drug combinations varies depending on the genetic variation of cancer patients. A computational approach that prioritizes the best drug combinations considering the genetic information of a cancer patient is necessary to reduce the search space.

Results

We propose an in-silico method for personalized drug combination therapy discovery. We predict the synergy between two drugs and a cell line using genomic information, targets of drugs, and pharmacological information. We calculate and predict the synergy scores of 583 drug combinations for 31 cancer cell lines. For feature dimension reduction, we select the mutations or expression levels of the genes in cancer-related pathways. We also used various machine learning models. Extremely Randomized Trees (ERT), a tree-based ensemble model, achieved the best performance in the synergy score prediction regression task. The correlation coefficient between the synergy scores predicted by ERT and the actual observations is 0.738. To compare with an existing drug combination synergy classification model, we reformulate the problem as a binary classification problem by thresholding the synergy scores. ERT achieved an F1 score of 0.954 when synergy scores of 20 and -20 were used as the threshold, which is 8.7% higher than that obtained by the state-of-the-art baseline model. Moreover, the model correctly predicts the most synergistic combination, from approximately 100 candidate drug combinations, as the top choice for 15 out of the 31 cell lines. For 28 out of the 31 cell lines, the model predicts the most synergistic combination in the top 10 of approximately 100 candidate drug combinations. Finally, we analyze the results, generate synergistic rules using the features, and validate the rules through the literature survey.

Conclusion

Using various types of genomic information of cancer cell lines, targets of drugs, and pharmacological information, a drug combination synergy prediction pipeline is proposed. The pipeline regresses the synergy level between two drugs and a cell line as well as classifies if there exists synergy or antagonism between them. Discovering new drug combinations by our pipeline may improve personalized cancer therapy.

     

Carcinoembryonic antigen expression level as a predictive factor for response to 5-fluorouracil in colorectal cancer

Carcinoembryonic antigen (CEA) expression has been shown to protect cancer cell lines from apoptosis and anoikis. The aim of this study was to further elucidate the role of CEA expression on resistance to anticancer drugs in human colorectal cancer (CRC). We transfected CEA negative CRC cell line SW742 as well as CHO cells to overexpress CEA and their chemoresistance were assessed by MTT assay. In comparison to the parental cell lines, transfected cells had significantly increased resistance to 5-fluorouracil (5-FU). The results also showed a direct correlation between the amount of cellular CEA protein and 5-FU resistance in CEA expressing cells. We found no significant difference in sensitivity to cisplatin and methotrexate between CEA-transfected cells and their counter parental cells. We also compared the association between CEA expression and chemoresistance of 4 CRC cell lines which differed in the levels of CEA production. The CEA expression levels in monolayer cultures of these cell lines did not correlate with the 5-FU resistance. However, 5-FU treatment resulted in the selection of sub-populations of resistant cells that displayed increased CEA expression levels by increasing drug concentration. We analyzed the effect of 5-FU in a 3D multicellular culture generated from the two CRC cell lines, LS180 and HT29/219. Compared with monolayer culture, CEA production and 5-FU resistance in both cell lines were stimulated by 3D growth. In comparison to the 3D spheroids of parental CHO, we observed a significantly elevated 5-FU resistance in 3D culture of the CEA-expressing CHO transfectants. Our findings suggest that the CEA level may be a suitable biomarker for predicting tumor response to 5-FU-based chemotherapy in CRC.     

Glycoproteomics of paclitaxel resistance in human epithelial ovarian cancer cell lines: Towards the identification of putative biomarkers

Glycosylation, one of the most common post translational modifications (PTMs) of proteins, is often associated with carcinogenesis and tumor malignancy. Ovarian cancer is the sixth cause of cancer-related death in Western countries. Currently, it is treated by debulking surgery followed by chemotherapy based on paclitaxel, alone or in combination with other drugs. However, chemoresistance represents a major obstacle to positive clinical outcome. We used two approaches, Multiplexed Proteomics (MP) technology and Multilectin Affinity Chromatography (MAC) to characterize the glycoproteome of the human ovarian cancer cell line A2780 and its paclitaxel resistant counterpart A2780TC1. Furthermore proteins were separated by traditional 2DE or DIGE and identified by MS (MALDI TOF or LC MS/MS). Seventy glycoproteins were successfully identified in ovarian cancer cells and 10 were found to be differentially expressed between sensitive and resistant cell lines. We focused on four glycoproteins (tumor rejection antigen (gp96) 1, triose phosphate isomerase, palmitoyl-protein thioesterase 1 precursor and ER-associated DNAJ) which were remarkably upregulated in A2780TC1 compared to A2780 cell line and which may represent biomarkers for paclitaxel resistance in ovarian cancer.     

Selection of metastatic breast cancer cells based on adaptability of their metabolic state

A small subpopulation of highly adaptable breast cancer cells within a vastly heterogeneous population drives cancer metastasis. Here we describe a function-based strategy for selecting rare cancer cells that are highly adaptable and drive malignancy. Although cancer cells are dependent on certain nutrients, e.g., glucose and glutamine, we hypothesized that the adaptable cancer cells that drive malignancy must possess an adaptable metabolic state and that such cells could be identified using a robust selection strategy. As expected, more than 99.99% of cells died upon glutamine withdrawal from the aggressive breast cancer cell line SUM149. The rare cells that survived and proliferated without glutamine were highly adaptable, as judged by additional robust adaptability assays involving prolonged cell culture without glucose or serum. We were successful in isolating rare metabolically plastic glutamine-independent (Gln-ind) variants from several aggressive breast cancer cell lines that we tested. The Gln-ind cells overexpressed cyclooxygenase-2, an indicator of tumor aggressiveness, and they were able to adjust their glutaminase level to suit glutamine availability. The Gln-ind cells were anchorage-independent, resistant to chemotherapeutic drugs doxorubicin and paclitaxel, and resistant to a high concentration of a COX-2 inhibitor celecoxib. The number of cells being able to adapt to non-availability of glutamine increased upon prior selection of cells for resistance to chemotherapy drugs or resistance to celecoxib, further supporting a linkage between cellular adaptability and therapeutic resistance. Gln-ind cells showed indications of oxidative stress, and they produced cadherin11 and vimentin, indicators of mesenchymal phenotype. Gln-ind cells were more tumorigenic and more metastatic in nude mice than the parental cell line as judged by incidence and time of occurrence. As we decreased the number of cancer cells in xenografts, lung metastasis and then primary tumor growth was impaired in mice injected with parental cell line, but not in mice injected with Gln-ind cells.     

Targeted Casp8AP2 methylation increases drug resistance in mesenchymal stem cells and cancer cells

Casp8AP2 contains a FLASH functional domain and is critical for the formation of death complex and the relay of death signal into the cells. Genetic defects in Casp8AP2 are associated with several diseases. A CpG island within the Casp8AP2 promoter is differentially regulated during somatic stem cell differentiation, and aberrant DNA methylation within the Casp8AP2 promoter has been reported in cancers. We hypothesized that abnormal DNA methylation of Casp8AP2 promoter might contribute to prolonged cellular survival or drug resistance in cancer. The epigenetic state within the Casp8AP2 promoter was then determined in different cancer cell lines and patient samples by methylation-specific PCR. Targeted Casp8AP2 methylation within normal and tumor cells was performed to see whether methylation promoted drug resistance. We found differential Casp8AP2 methylation among the normal and tumoral samples. Global demethylation in a platinum drug-resistant human gastric cancer cell line reversed Casp8AP2 methylation and diminished drug resistance. Targeted methylation of the Casp8AP2 promoter in somatic stem cells and cancer cells increased their resistance to drugs including platinum drugs. These data demonstrate that methylation within the Casp8AP2 promoter correlates with the development of drug resistance and might serve as a biomarker and treatment target for drug resistance in cancer cells.     

CUL4B increases platinum‐based drug resistance in colorectal cancer through EMT: A study in its mechanism

Platinum‐based chemotherapy drugs play a very important role in the treatment of patients with advanced colorectal cancer, but the drug resistance of platinum‐based chemotherapy drugs is an important topic that puzzles us. If we can find mechanisms of resistance, it will be revolutionary for us. We analysed the differential genes, core genes and their enrichment pathways in platinum‐resistant and non‐resistant patients through a public database. Platinum‐resistant cell lines were cultured in vitro for in vitro colony and Transwell analysis. Tumorigenesis analysis of nude mice in vivo. Verify the function of core genes. Through differential gene and enrichment analysis, we found that CUL4B was the main factor affecting platinum drug resistance and EMT. Our hypothesis was further verified by in vitro drug‐resistant and wild‐type cell lines and in vivo tumorigenesis analysis of nude mice. CUL4B leads to platinum drug resistance in colorectal cancer by affecting tumour EMT.     

Resistance to targeted cancer drugs through hepatocyte growth factor signaling

Cancer therapeutics that target a signaling pathway to which the cancer cells are addicted can deliver dramatic initial responses, but resistance is nearly always inevitable. A variety of mechanisms that cancer cells employ to escape from targeted cancer drugs have been described. We review here the role of Hepatocyte Growth Factor (HGF) and its receptor MET in drug resistance. We present data demonstrating that HGF can confer resistance to a number of kinase inhibitors in a variety of cancer cell lines and discuss our results in relation to the findings of others. Together, these data point at a major role for HGF/MET signaling in resistance to a variety of targeted cancer drugs.     

Relation between cytochrome P450IA1 expression and estrogen receptor content of human breast cancer cells

Multidrug resistance (MDR) in an MCF-7 human breast cancer cell line (MCF7/Adr) is associated with decreased drug accumulation and overexpression of P-glycoprotein as well as alterations in the levels of specific drug-metabolizing enzymes, including decreased activity of the phase I drug-metabolizing enzyme aryl hydrocarbon hydroxylase (AHH) and increased expression of the anionic form of the phase II drug-metabolizing enzyme glutathione S-transferase. Since the development of MDR in this MCF-7 cell line is also associated with a loss of estrogen receptors (ER), we have examined the expression of cytochrome P450IA 1, the gene encoding AHH activity, in other breast cancer cell lines not selected for drug resistance but expressing various levels of ER. These studies show that a relationship exists between 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-inducible AHH activity and the ER content in a series of breast cancer cell lines. In these cell lines expression of AHH activity is regulated, at least in part, at the level of P450IA 1 RNA. While TCDD-specific binding proteins (Ah receptors) were found in each of the breast cancer cell lines, there was no apparent relation between the level of nuclear TCDD-binding proteins and the level of TCDD-inducible P450IA 1 expression. Previous studies from our laboratory have described an inverse relationship between levels of the anionic form of glutathione S-transferase and ER in breast cancer.(ABSTRACT TRUNCATED AT 250 WORDS)     

Identification of replication competent murine gammaretroviruses in commonly used prostate cancer cell lines

A newly discovered gammaretrovirus, termed XMRV, was recently reported to be present in the prostate cancer cell line CWR22Rv1. Using a combination of both immunohistochemistry with broadly-reactive murine leukemia virus (MLV) anti-sera and PCR, we determined if additional prostate cancer or other cell lines contain XMRV or MLV-related viruses. Our study included a total of 72 cell lines, which included 58 of the 60 human cancer cell lines used in anticancer drug screens and maintained at the NCI-Frederick (NCI-60). We have identified gammaretroviruses in two additional prostate cancer cell lines: LAPC4 and VCaP, and show that these viruses are replication competent. Viral genome sequencing identified the virus in LAPC4 and VCaP as nearly identical to another known xenotropic MLV, Bxv-1. We also identified a gammaretrovirus in the non-small-cell lung carcinoma cell line EKVX. Prostate cancer cell lines appear to have a propensity for infection with murine gammaretroviruses, and we propose that this may be in part due to cell line establishment by xenograft passage in immunocompromised mice. It is unclear if infection with these viruses is necessary for cell line establishment, or what confounding role they may play in experiments performed with these commonly used lines. Importantly, our results suggest a need for regular screening of cancer cell lines for retroviral "contamination", much like routine mycoplasma testing.