Identification of genes with differential expression in acquired drug-resistant gastric cancer cells using high-density oligonucleotide microarrays

Radiogenomic analysis to identify imaging phenotypes associated with drug response gene expression programs in hepatocellular carcinoma

PURPOSE

To determine whether conventional contrast-enhanced computed tomography (CT) could be used to identify imaging phenotypes associated with a doxorubicin drug response gene expression program in hepatocellular carcinoma (HCC) by using an integrated imaging-genomic approach.

MATERIALS AND METHODS

Thirty HCCs were analyzed and scored individually across six predefined imaging phenotypes. Unsupervised and supervised bioinformatics analyses were performed to correlate the imaging scores with the corresponding tumor microarray data (each microarray contained gene expression measurements across approximately 18,000 genes) to identify relationships between the imaging traits and underlying tumor gene expression. Enrichment for a predefined doxorubicin-response gene expression program was then performed against the imaging phenotype-associated genes and enrichment determined.

RESULTS

An imaging phenotype related to tumor margins on arterial phase images demonstrated significant correlation with the doxorubicin-response transcriptional program (P < .05, q < 0.1). It was also significantly associated with HCC venous invasion and tumor stage (P < .05, q < 0.1). Tumors with higher tumor margin scores were more strongly associated with the doxorubicin resistance transcriptional program and had a greater prevalence of venous invasion and worse stage. Tumors with lower tumor margin scores, however, demonstrated a converse relationship.

CONCLUSIONS

It is possible to identify HCC imaging phenotypes at CT that correlate with a doxorubicin drug response gene expression program. Given the role of doxorubicin in regional therapies for HCC management, it is possible that such an approach could be used to guide HCC therapy on a tumor-by-tumor basis on the basis of underlying tumor gene expression patterns.

Identification of consensus genes and key regulatory elements in 5-fluorouracil resistance in gastric and colon cancer

BACKGROUND

5-fluorouracil (5-FU) is widely used in the treatment of gastric and colorectal cancer. Recent microrarray studies associated different gene lists with 5-FU resistance. A major challenge in the genomic era is to find the most validated genes, and to decipher the regulatory networks responsible for the expression changes in a set of co-regulated transcripts. Our aim was to find genes repeatedly associated with 5-FU resistance, and to identify transcription factors (TFs) having overrepresented binding sites (TFBSs) in the promoter regions of genes associated with 5-FU resistance.

MATERIALS AND METHODS

The analyzed data originated from 5 different publications describing genome-wide gene expression patterns associated with 5- FU resistance in gastric and colorectal cancer. First, a data warehouse containing all genes associated with resistance was set up. 39 genes were identified which were repeatedly associated with resistance. Of these, using the EZ-Retrieve web service, proximal promoter sequences were available for 33 genes. The MotifScanner software was used to detect TFBSs in this set of sequences.

RESULTS

A total of 200 different TFBSs were identified. Using the statistics tool of the Java program TOUCAN, 4 binding sites were found to be significantly overrepresented: NFKappaB50 (p = 0.01), EGR2 (p = 0.027), EGR3 (p = 0.007), and NGFIC (or EGR4) (p = 0.001). These genes intercept apoptotic pathways at multiple locations in the tumor cells.

CONCLUSION

We identified a consensus gene list associated with 5-FU resistance, performed an in silico comparative promoter analysis, and highlighted the potential implication of some TFs in the development of chemoresistance.

Microarray gene expression profiling for predicting complete response to preoperative chemoradiotherapy in patients with advanced rectal cancer

PURPOSE

Preoperative chemoradiotherapy is widely used to improve local control and sphincter preservation in patients with locally advanced rectal cancer. In the present study, we investigated whether microarray gene expression analysis could predict complete response to preoperative chemoradiotherapy in rectal cancer.

METHODS

Tumor tissues were obtained from 46 patients with rectal cancer (31 for training and 15 for validation testing). All patients underwent preoperative chemoradiotherapy involving 50.4 gray radiotherapy, followed by surgical excision 6 weeks later. Response to chemoradiotherapy was evaluated according to Dworak's tumor regression grade. Tumor regression Grades 1, 2, and 3 were considered partial responses, and tumor regression Grade 4 was considered a complete response. By using the 31 training samples, genes differentially expressed between partial response and complete response were identified, and clustering analysis was performed. Prediction analysis of response to chemoradiotherapy was performed on the 31 training samples by using a selected set of 95 "predictor" genes. Those findings were validated by independent analysis of the 15 test samples.

RESULTS

The 31 training samples comprised 20 partial response and 11 complete response cases. A primary set of 261 genes was identified as differentiating between partial response and complete response. By supervised clustering using these 261 genes, 30 of 31 training samples were clustered correctly according to tumor response. A gene set comprising the top-ranked 95 genes displaying differential expression between partial response and complete response was applied to predict response to chemoradiotherapy. Complete response and partial response were accurately predicted in 84 percent (26/31) of training samples and 87 percent (13/15) of validation samples.

CONCLUSIONS

Microarray gene expression analysis was successfully used to predict complete responses to preoperative chemoradiotherapy in patients with advanced rectal cancer.

Identification of molecular determinants of tumor sensitivity and resistance to anticancer drugs

Resistance to drugs is a major problem in cancer chemotherapy. Various cellular mechanisms of drug resistance have been identified in cultured tumor cell lines selected for growth in the presence of sublethal concentrations of various anticancer drugs. They involve drug transport and detoxification, qualitative or quantitative alterations of the drug target, repair of drug-induced DNA lesions, and alterations in signaling or execution of apoptosis. More recently, the possibility to simultaneously analyze the expression of thousands of genes using DNA microarrays has allowed exploring the relationships between gene expression and sensitivity to several anticancer drugs. A number of studies using microarrays for identifying genes governing tumor chemosensitivity focused on tumor cell lines. Some clinical studies have also been carried out to investigate whether tumor gene expression patterns could predict clinical response to chemotherapy. Results of these studies are encouraging, indicating that individualization of drug treatment based on multigenic response-predictive markers is feasible.

Resistance-associated signatures in breast cancer

A major obstacle in the treatment of breast cancer is the lack of adequate methods for predicting patient response to a particular chemotherapy regime. To date, single tumour markers have provided limited success. DNA array technologies identifying thousands of genes simultaneously can help to solve this problem. We investigated cancer cell lines sensitive and resistant to the topoisomerase inhibitors doxorubicin and mitoxantrone. These drugs are used in several different breast cancer treatment protocols. We have identified the top genes best associated with resistance against each cytostatic agent. We applied our gene expression signatures to a set of pre-characterised patients receiving doxorubicin monotherapy. The patients classified as sensitive to chemotherapy exhibited longer survival than the resistant ones. In summary, in our study we have successfully transferred experimental results to a clinical problem, and managed to perform a predictive test for a selected monotherapy protocol. However, many different studies have been performed using microarrays, each producing a different gene list for the same classification problem. It is likely that future diagnostic tools will include the results of several different laboratories, focus on genes validated on different technological platforms and use large cohorts of patients.

Histone deacetylase 1 gene expression and sensitization of multidrug-resistant neuroblastoma cell lines to cytotoxic agents by depsipeptide

BACKGROUND

Genes that are overexpressed in multidrug-resistant neuroblastomas relative to drug-sensitive neuroblastomas may provide targets for modulating drug resistance.

METHODS

We used microarrays to compare the gene expression profile of two drug-sensitive neuroblastoma cell lines with that of three multidrug-resistant neuroblastoma cell lines. RNA expression of selected overexpressed genes was quantified in 17 neuroblastoma cell lines by reverse transcription-polymerase chain reaction (RT-PCR). Small-interfering RNAs (siRNAs) were used for silencing gene expression. Cytotoxicity of melphalan, carboplatin, etoposide, and vincristine and cytotoxic synergy (expressed as combination index calculated by CalcuSyn software, where combination index < 1 indicates synergy and > 1 indicates antagonism) were measured in cell lines with a fluorescence-based assay of cell viability. All statistical tests were two-sided.

RESULTS

A total of 94 genes were overexpressed in the multidrug-resistant cell lines relative to the drug-sensitive cell lines. Nine genes were selected for RT-PCR analysis, of which four displayed higher mRNA expression in the multidrug-resistant lines than in the drug-sensitive lines: histone deacetylase 1 (HDAC1; 2.3-fold difference, 95% confidence interval [CI] = 1.0-fold to 3.5-fold, P = .025), nuclear transport factor 2-like export factor (4.2-fold difference, 95% CI = 1.7-fold to 7.6-fold, P = .0018), heat shock 27-kDa protein 1 (2.5-fold difference, 95% CI = 1.0-fold to 87.7-fold, P = .028), and TAF12 RNA polymerase II, TATA box-binding protein-associated factor, 20 kDa (2.2-fold, 95% CI = 0.9-fold to 6.0-fold, P = .051). siRNA knockdown of HDAC1 gene expression sensitized CHLA-136 neuroblastoma cells to etoposide up to fivefold relative to the parental cell line or scrambled siRNA-transfected cells (P<.001). Cytotoxicity of the histone deacetylase inhibitor depsipeptide was tested in combination with melphalan, carboplatin, etoposide, or vincristine in five multidrug-resistant neuroblastoma cell lines, and synergistic cytotoxicity was demonstrated at a 90% cell kill of treated cells (combination index < 0.8) in all cell lines.

CONCLUSION

High HDAC1 mRNA expression was associated with multidrug resistance in neuroblastoma cell lines, and inhibition of HDAC1 expression or activity enhanced the cytotoxicity of chemotherapeutic drugs in multidrug-resistant neuroblastoma cell lines. Thus, HDAC1 is a potential therapeutic target in multidrug-resistant neuroblastoma.

Establishment and gene analysis of an oxaliplatin-resistant colon cancer cell line THC8307/L-OHP

Oxaliplatin is widely used for chemotherapy of several malignancies, especially of colon cancer. As the mechanism of resistance to oxaliplatin is unclear, we established an oxaliplatin-resistant cell line, THC8307/L-OHP, from an oxaliplatin-sensitive colonic cancer cell line, THC8307. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium assay indicated that THC8307/L-OHP has 30.99-fold greater resistance to oxaliplatin than THC8307. Analyzing its gene expression profile using an in-house oligomicroarray, a number of genes were differentially expressed in the THC8307/L-OHP cells, compared with parental cells (THC8307). Proapoptotic genes such as STK17A and BNIP3 were significantly downregulated, whereas the genes PSAP and GDIA1, which were involved in antiapoptosis, were overexpressed. Moreover, the THC8307/L-OHP cells are also resistant to the other anticancer drug 5-fluorouracil, and the expression levels of the differentially regulated genes such as S100P, CAeta, STA15, TCF8 are constantly maintained. These results provide clues for understanding the oxaliplatin-resistant mechanisms and imply markers to predict drug sensitivities for 'personalized chemotherapy'.

Gene expression profiles as biomarkers for the prediction of chemotherapy drug response in human tumour cells

Genome profiling approaches such as cDNA microarray analysis and quantitative reverse transcription polymerase chain reaction are playing ever-increasing roles in the classification of human cancers and in the discovery of biomarkers for the prediction of prognosis in cancer patients. Increasing research efforts are also being directed at identifying set of genes whose expression can be correlated with response to specific drugs or drug combinations. Such genes hold the prospect of tailoring chemotherapy regimens to the individual patient, based on tumour or host gene expression profiles. This review outlines recent advances and challenges in using genome profiling for the identification of tumour or host genes whose expression correlates with response to chemotherapy drugs both in vitro and in clinical studies. Genetic predictors of response to a variety of anticancer agents are discussed, including the anthracyclines, taxanes, topoisomerase I and II inhibitors, nucleoside analogs, alkylating agents, and vinca alkaloids.

Comparative gene expression analysis of a chronic myelogenous leukemia cell line resistant to cyclophosphamide using oligonucleotide arrays and response to tyrosine kinase inhibitors

Acquired imatinib resistance in chronic myelogenous leukemia (CML) can be the consequence of mutations in the kinase domain of BCR-ABL or increased protein levels. However, as in other malignancies, acquired resistance to cytostatic drugs is a common reason for treatment failure or disease progression. As a model for drug resistance, we developed a CML cell line resistant to cyclophosphamide (CP). Using oligonucleotide arrays, we examined changes in global gene expression. Selected genes were also examined by real-time PCR and flow cytometry. Neither the parent nor the resistant lines had mutations in their ATP binding domain. Filtering genes with a low-base line expression, a total of 239 genes showed significant changes (162 up- and 77 down-regulated) in the resistant clone. Most of the up-regulated genes were associated with metabolism, signal transduction, or encoded enzymes. The gene for aldehyde dehydrogenase 1 was over-expressed more than 2000-fold in the resistant clone. BCR-ABL was expressed in both cell lines to a comparable extent. When exposed to the tyrosine kinase inhibitors imatinib and nilotinib, both lines were sensitive. In conclusion, we found multiple genetic changes in a CML cell line resistant to CP related to metabolism, signal transduction or apoptosis. Despite these changes, the resistant cells retained sensitivity to tyrosine kinase inhibitors.

Genome-wide screening of loci associated with drug resistance to 5-fluorouracil-based drugs

Resistance to chemotherapeutic agents represents the chief cause of mortality in cancer patients with advanced disease. Chromosomal aberration and altered gene expression are the main genetic mechanisms of tumor chemoresistance. In this study, we have established an algorithm to calculate DNA copy number using the Affymetrix 10K array, and performed a genome-wide correlation analysis between DNA copy number and antitumor activity against 5-fluorouracil (5-FU)-based drugs (S-1, tegafur + uracil [UFT], 5'-DFUR and capecitabine) to screen for loci influencing drug resistance using 27 human cancer xenografts. A correlation analysis confirmed that the single nucleotide polymorphism (SNP) showing significant associations with drug sensitivity were concentrated in some cytogenetic regions (18p, 17p13.2, 17p12, 11q14.1, 11q11 and 11p11.12), and we identified some genes that have been indicated their relations to drug sensitivity. Among these regions, 18p11.32 at the location of the thymidylate synthase gene (TYMS) was strongly associated with resistance to 5-FU-based drugs. A change in copy number of the TYMS gene was reflected in the TYMS expression level, and showed a significant negative correlation with sensitivity against 5-FU-based drugs. These results suggest that amplification of the TYMS gene is associated with innate resistance, supporting the possibility that TYMS copy number might be a predictive marker of drug sensitivity to fluoropyrimidines. Further study is necessary to clarify the functional roles of other genes coded in significant cytogenetic regions. These promising data suggest that a comprehensive DNA copy number analysis might aid in the quest for optimal markers of drug response.

Molecular markers for gastric adenocarcinoma: an update

Gastric cancer is the second most common cancer worldwide. Treatment of localized gastric cancer relies primarily on surgical intervention, although growing evidence suggests that the addition of chemoradiation may improve disease-free intervals and overall survival. In this regard, the current high rates of recurrence and subsequent poor survival have prompted an ever-increasing use of multimodal strategies, even for early-stage disease. However, these therapies are often limited by debilitating toxicities and varying degrees of response efficacy. As a result, pharmacogenomics, the study of specific genetic and molecular signatures that may be predictive of treatment outcomes, has gained considerable interest. For example, studies have demonstrated that the expression of enzymes involved in the metabolism or conjugation of commonly used chemotherapy agents, such as fluoropyrimidines and cisplatin, can serve as surrogate markers predictive of chemotherapy response. Polymorphisms in the genes encoding these enzymes have also been identified and may further account for altered expression patterns, resulting in varied clinical responses. Future work is necessary to further refine the list of molecular genetic markers and to identify novel markers for prognostic and predictive purposes. Technologies such as microarray analysis may be useful in identifying new molecular genetic markers, and further work may determine whether these markers can be employed to help stratify patients into different multimodal treatment regimens.

Development of resistance to chemotherapeutic drugs in human osteosarcoma cell lines largely depends on up-regulation of Clusterin/Apolipoprotein J

Clusterin/Apolipoprotein J (CLU) is differentially regulated during in vivo cancer progression. We have addressed the role of CLU during the acquisition and maintenance of human cancer cells resistance to chemotherapeutic drugs. We used two osteosarcoma (OS) cell lines, namely U-2 OS and KH OS, and selected three generations of doxorubicin (DXR)-resistant cells (R1, R2 and R3; resistant to 0.0035, 0.035 and 0.35 microM DXR, respectively) by continuous exposure to increasing, clinically relevant, DXR concentrations. Our studies showed that the DXR-resistant OS cell lines were cross-resistant to a variety of unrelated cytotoxic agents. Analysis of the CLU mRNA and protein expression levels revealed a minimal CLU up-regulation in the U-2 OS R2 cells and a significant, more than 4-fold, induction in the KH OS R2 and R3 cells. Antibody-mediated neutralization of the extracellular CLU, or silencing of CLU gene expression via small interfering RNA (siRNA) partially sensitized KH OS R2 cells to the drugs assayed. Moreover, siRNA-mediated CLU knock down in the absence of DXR induced high levels of endogenous spontaneous apoptosis in both the parental and R2 OS cell lines. This effect was enhanced by more than 60% in the KH OS R2 cells as compared to their parental counterparts, indicating that the high CLU levels in the KH OS R2 cells are essential for survival. Overall, we suggest that CLU up-regulation in the multi-drug resistant OS cells relates to enhanced drug resistance. Therefore, CLU may represent a predictive marker, which correlates to response of cancer cells to chemotherapy.

Gene expression response to cisplatin treatment in drug-sensitive and drug-resistant ovarian cancer cells

The molecular pathways activated in response to acute cisplatin exposure, as well as the mechanisms involved in the long-term development of cisplatin-resistant cancer cells remain unclear. Using whole genome oligonucleotide microarrays, we have examined the kinetics of gene expression changes in a cisplatin-sensitive cell line, A2780, and its cisplatin-resistant derivative, ACRP. Both sensitive and resistant cell lines exhibited a very similar response of p53-inducible genes as early as 16 h after treatment. This p53 response was further increased at the 24-h time point. These experiments identify p53 as the main pathway producing a large-scale transcriptional response after cisplatin treatment in these cells containing wild-type p53. Consistent with a role for the p53 response in cisplatin sensitivity, knockdown of the p53 protein with small interfering RNA led to a twofold decrease in cell survival in the resistant cells. In addition, our analysis also allowed the identification of several genes that are differentially expressed between sensitive and resistant cells. These genes include GJA1 (encoding connexin 43 (Cx43)) and TWIST1, which are highly upregulated in cisplatin-resistant cells. The importance of Cx43 in drug resistance was demonstrated through functional analyses, although paradoxically, inhibition of Cx43 function in high expressing cells led to an increase in drug resistance. The pathways important in cisplatin response, as well as the genes found differentially expressed between cisplatin-resistant and -sensitive cells, may represent targets for therapy aimed at reversing drug resistance.

Identification of genes associated with cisplatin resistance in human oral squamous cell carcinoma cell line

Background

Cisplatin is widely used for chemotherapy of head and neck squamous cell carcinoma. However, details of the molecular mechanism responsible for cisplatin resistance are still unclear. The aim of this study was to identify the expression of genes related to cisplatin resistance in oral squamous cell carcinoma cells.

Methods

A cisplatin-resistant cell line, Tca/cisplatin, was established from a cisplatin-sensitive cell line, Tca8113, which was derived from moderately-differentiated tongue squamous cell carcinoma. Global gene expression in this resistant cell line and its sensitive parent cell line was analyzed using Affymetrix HG-U95Av2 microarrays. Candidate genes involved in DNA repair, the MAP pathway and cell cycle regulation were chosen to validate the microarray analysis results. Cell cycle distribution and apoptosis following cisplatin exposure were also investigated.

Results

Cisplatin resistance in Tca/cisplatin cells was stable for two years in cisplatin-free culture medium. The IC50 for cisplatin in Tca/cisplatin was 6.5-fold higher than that in Tca8113. Microarray analysis identified 38 genes that were up-regulated and 25 that were down-regulated in this cell line. Some were novel candidates, while others are involved in well-characterized mechanisms that could be relevant to cisplatin resistance, such as RECQL for DNA repair and MAP2K6 in the MAP pathway; all the genes were further validated by Real-time PCR. The cell cycle-regulated genes CCND1 and CCND3 were involved in cisplatin resistance; 24-hour exposure to 10 μM cisplatin induced a marked S phase block in Tca/cisplatin cells but not in Tca8113 cells.

Conclusion

The Tca8113 cell line and its stable drug-resistant variant Tca/cisplatin provided a useful model for identifying candidate genes responsible for the mechanism of cisplatin resistance in oral squamous cell carcinoma. Our data provide a useful basis for screening candidate targets for early diagnosis and further intervention in cisplatin resistance.

Cancer proteomics and its application to discovery of therapy response markers in human cancer

The administration of chemotherapy either alone or in combination with radiotherapy is an important factor in reducing the mortality and morbidity of cancer patients. Resistance to both chemotherapy and radiotherapy represents a major obstacle to a successful outcome. The identification of novel biomarkers that can be used to predict treatment response would allow therapy to be tailored on an individual patient basis. Although the mechanisms are unclear, it is accepted that development of therapy resistance is a multifactorial phenomenon involving alterations in several cellular pathways. Proteome analysis methods are powerful tools for identifying factors associated with resistance to anticancer therapy because they facilitate the simultaneous analysis of whole proteomes. The current review describes the plethora of existing proteomic approaches and details the studies that have identified biomarkers that may be useful in the prediction of clinical response to anticancer therapy.

Function and chromosome location of differentially expressed genes in gastric cancer

Using Affymetrix U133A oligonucleotide microarrays, screening was done for genes that were differentially expressed in gastric cancer (T) and normal gastric mucosa (C), and their chromosome location was characterized by bioinformatics. A total of 270 genes were found to have a difference in expression levels of more than eight times. Of them 157 were up-regulated (Signal Log Ratio [SLR] > or = 3), and 113 were down-regulated (SLR< or = -3). Except for, four genes with unknown localization, a vast majority of the genes were sporadically distributed over every chromosome. However, chromosome 1 contained the most differentially expressed genes (26 genes, or 9.8%), followed by chromosomes 11 and 19 (both 24 genes, or 9.1%). These genes were also more likely to be on the short-arm of the chromosome (q), which had 173 (65%). When these genes were classified according to their functions, it was found that most (67 genes, 24.8%) belonged to the enzymes and their regulators groups. The next group was the signal transduction genes group (43 genes, 15.9%). The rest of the top three groups were nucleic acid binding genes (17, 6.3%), transporter genes (15, 5.5%), and protein binding genes (12, 4.4%). These made up 56.9% of all the differentially expressed genes. There were also 50 genes of unknown function (18.5%). Therefore it was concluded that differentially expressed genes in gastric cancer seemed to be sporadically distributed across the genome, but most were found on chromosomes 1, 11 and 19. The five groups associated genes abnormality were important genes for further study on gastric cancer.

Regulation of MDK expression in human cancer cells modulates sensitivities to various anticancer drugs: MDK overexpression confers to a multi-drug resistance

MDK is a heparin-binding growth factor associated with cancer development. Here, we sought to examine the association of MDK expression with resistance and sensitivity to different chemotherapeutic agents. We established stable HeLa cell transfectants (HeLa-MDK) and tested for decreased sensitivity to chemotherapeutic agents (5-FU, doxorubicin, and cisplatin). In addition, we used siRNA to block MDK expression in SNU-638 human gastric cancer cells and examined the chemosensitizing effect. HeLa-MDK cells treated with 5-FU, doxorubicin, and cisplatin showed a fold increase in the average IC(50) and an increased cell survival. siRNA-based knockdown of MDK expression in SNU-638 cells decreased the average IC(50) by 18-44% in cells treated with three drugs. Further investigations on the molecular mechanism should be clarified, but these results indicate that MDK up- and down-regulation appears to be capable of changing the chemosensitivities of cancer cells and MDK may have possible importance as a candidate therapeutic molecule.

Molecular profiling of platinum resistant ovarian cancer

The aim of this study is to discover a gene set that can predict resistance to platinum-based chemotherapy in ovarian cancer. The study was performed on 96 primary ovarian adenocarcinoma specimens from 2 hospitals all treated with platinum-based chemotherapy. In our search for genes, 24 specimens of the discovery set (5 nonresponders and 19 responders) were profiled in duplicate with 18K cDNA microarrays. Confirmation was done using quantitative RT-PCR on 72 independent specimens (9 nonresponders and 63 responders). Sixty-nine genes were differentially expressed between the nonresponders (n=5) and the responders (n=19) in the discovery phase. An algorithm was constructed to identify predictive genes in this discovery set. This resulted in 9 genes (FN1, TOP2A, LBR, ASS, COL3A1, STK6, SGPP1, ITGAE, PCNA), which were confirmed with qRT-PCR. This gene set predicted platinum resistance in an independent validation set of 72 tumours with a sensitivity of 89% (95% CI: 0.68-1.09) and a specificity of 59% (95% CI: 0.47-0.71)(OR=0.09, p=0.026). Multivariable analysis including patient and tumour characteristics demonstrated that this set of 9 genes is independent for the prediction of resistance (p<0.01). The findings of this study are the discovery of a gene signature that classifies the tumours, according to their response, and a 9-gene set that determines resistance in an independent validation set that outperforms patient and tumour characteristics. A larger independent multicentre study should further confirm whether this 9-gene set can identify the patients who will not respond to platinum-based chemotherapy and could benefit from other therapies.

Pharmacogenomic identification of novel determinants of response to chemotherapy in colon cancer

DNA microarray analysis was used to analyze the transcriptional profile of HCT116 colorectal cancer cells that were treated with 5-fluorouracil (5-FU) or oxaliplatin and selected for resistance to these agents. Bioinformatic analyses identified sets of genes that were constitutively dysregulated in drug-resistant cells and transiently altered following acute exposure of parental cells to drug. We propose that these genes may represent molecular signatures of sensitivity to 5-FU and oxaliplatin. Using real-time reverse transcription-PCR (RT-PCR), the robustness of our microarray data was shown with a strong overall concordance of expression trends for > or =82% (oxaliplatin) and > or =85% (5-FU) of a representative subset of genes. Furthermore, strong correlations between the microarray and real-time RT-PCR measurements of average fold changes in gene expression were observed for both the 5-FU (R(2) > or = 0.73) and oxaliplatin gene sets (R(2) > or = 0.63). Functional analysis of three genes identified in the microarray study [prostate-derived factor (PDF), calretinin, and spermidine/spermine N(1)-acetyl transferase (SSAT)] revealed their importance as novel regulators of cytotoxic drug response. These data show the power of this novel microarray-based approach to identify genes which may be important markers of response to treatment and/or targets for therapeutic intervention.

Gene expression profiling of 30 cancer cell lines predicts resistance towards 11 anticancer drugs at clinically achieved concentrations

Cancer patients with tumors of similar grading, staging and histogenesis can have markedly different treatment responses to different chemotherapy agents. So far, individual markers have failed to correctly predict resistance against anticancer agents. We tested 30 cancer cell lines for sensitivity to 5-fluorouracil, cisplatin, cyclophosphamide, doxorubicin, etoposide, methotrexate, mitomycin C, mitoxantrone, paclitaxel, topotecan and vinblastine at drug concentrations that can be systemically achieved in patients. The resistance index was determined to designate the cell lines as sensitive or resistant, and then, the subset of resistant vs. sensitive cell lines for each drug was compared. Gene expression signatures for all cell lines were obtained by interrogating Affymetrix U133A arrays. Prediction Analysis of Microarrays was applied for feature selection. An individual prediction profile for the resistance against each chemotherapy agent was constructed, containing 42-297 genes. The overall accuracy of the predictions in a leave-one-out cross validation was 86%. A list of the top 67 multidrug resistance candidate genes that were associated with the resistance against at least 4 anticancer agents was identified. Moreover, the differential expressions of 46 selected genes were also measured by quantitative RT-PCR using a TaqMan micro fluidic card system. As a single gene can be correlated with resistance against several agents, associations with resistance were detected all together for 76 genes and resistance phenotypes, respectively. This study focuses on the resistance at the in vivo concentrations, making future clinical cancer response prediction feasible. The TaqMan-validated gene expression patterns provide new gene candidates for multidrug resistance.

Gene expression profiling of gastric cancer by microarray combined with laser capture microdissection

AIM

To examine the gene expression profile of gastric cancer (GC) by combination of laser capture microdissection (LCM) and microarray and to correlate the profiling with histological subtypes.

METHODS

Using LCM, pure cancer cells were procured from 45 cancerous tissues. After procurement of about 5000 cells, total RNA was extracted and the quality of RNA was determined before further amplification and hybridization. One microgram of amplified RNA was converted to cDNA and hybridized to cDNA microarray.

RESULTS

Among 45 cases, only 21 were qualified for their RNAs. A total of 62 arrays were performed. These included 42 arrays for cancer (21 cases with dye-swab duplication) and 20 arrays for non-tumorous cells (10 cases with dye-swab duplication) with universal reference. Analyzed data showed 504 genes were differentially expressed and could distinguish cancerous and non-cancerous groups with more than 99% accuracy. Of the 504 genes, trefoil factors 1, 2, and 3 were in the list and their expression patterns were consistent with previous reports. Immunohistochemical staining of trefoil factor 1 was also consistent with the array data. Analyses of the tumor group with these 504 genes showed that there were 3 subgroups of GC that did not correspond to any current classification system, including Lauren's classification.

CONCLUSION

By using LCM, linear amplification of RNA, and cDNA microarray, we have identified a panel of genes that have the power to discriminate between GC and non-cancer groups. The new molecular classification and the identified novel genes in gastric carcinogenesis deserve further investigations to elucidate their clinicopathological significance.

Acquired chemoresistance in pancreatic carcinoma cells: induced secretion of IL-1beta and NO lead to inactivation of caspases

Pancreatic cancer exhibits profound chemoresistance resulting either from pre-existing (intrinsic) mechanisms, or from anticancer drug treatment itself (acquired chemoresistance). To identify molecular alterations leading to acquired chemoresistance, the chemosensitive pancreatic carcinoma cell line PT45-P1 was exposed to low-dose treatment with etoposide for 6 weeks. Afterwards, these cells (PT45-P1res) were much more resistant to high-dose treatment with anticancer drugs than parental cells. Among several differentially expressed genes in PT45-P1res cells, IL-1beta was most significantly upregulated, a finding in line with our previous observation that IL-1beta accounts for intrinsic chemoresistance of pancreatic carcinoma cells. Elevated IL-1beta expression in PT45-P1res cells was confirmed by real-time PCR and ELISA, and treatment with the IL-1 receptor antagonist restored drug-induced apoptosis. The increased IL-1beta secretion was accompanied by an elevated formation of nitric oxide (NO) and a NO-dependent inhibition of the etoposide-induced caspase-3/-7/-8/-9 activity. Caspase activation was restored either by the iNOS inhibitor 1400W, the reducing agent dithiothreitol or the IL-1 receptor antagonist, resulting in greater sensitivity towards anticancer drug treatment. Conversely, IL-1beta or the NO-donor SNAP decreased caspase activation and apoptosis in etoposide-treated PT45-P1 cells. These data confirm IL-1beta and NO as determinants of chemoresistance in pancreatic cancer, and indicate that the intrinsic and acquired chemoresistance rely to some extent on common molecular targets beneficial for improved therapeutical strategies.

Transcriptome analysis of human gastric cancer

To elucidate the genetic events associated with gastric cancer, 124,704 cDNA clones were collected from 37 human gastric cDNA libraries, including 20 full-length enriched cDNA libraries of gastric cancer cell lines and tissues from Korean patients. An analysis of the collected ESTs revealed that 97,930 high-quality ESTs coalesced into 13,001 clusters, of which 11,135 clusters (85.6%) were annotated to known ESTs. The analysis of the full-length cDNAs also revealed that 4862 clusters (51.7%) contained at least one putative full-length cDNA clone with an initiation codon, with the average length of the 5' UTR of 140 bp. A large number appear to have a diverse transcription start site (TSS). An examination of the TSS of some genes, such as TEGT and GAPD, using 5' RACE revealed that the predicted TSSs are actually found in human gastric cancer cells and that several TSSs differ depending on the specific gastric cell line. Furthermore, of the human gastric ESTs, 766 genes (9.5%) were present as putative alternatively spliced variants. Confirmation of the predicted spliced isoforms using RT-PCR showed that the predicted isoforms exist in gastric cancer cells and some isoforms coexist in gastric cell lines. These results provide potentially useful information for elucidating the molecular mechanisms associated with gastric oncogenesis.

Oligonucleotide microarray analysis of distinct gene expression patterns in colorectal cancer tissues harboring BRAF and K- ras mutations

Various types of human cancers harbor BRAF somatic mutations, leading researchers to seek molecular targets for BRAF inhibitors. A mutually exclusive relationship has been observed between the BRAF-V600E mutation and K-ras mutations, suggesting that the BRAF-V600E mutation may differ from the other BRAF mutant types. Here, we used microarray analysis to examine differences between the BRAF and K-ras mutant colorectal samples and within the BRAF group (V600E versus non-V600E), in the hope that the identified gene sets could form the basis for new target development. Eleven colorectal cancers (CRCs) with BRAF mutations and nine with K-ras mutations were examined by high-density microarray analysis. We also tested whether other significant genetic or clinical status involved in CRC development, such as APC and TP53 mutations, MSI and TNM-Duke's staging, were related with the observed BRAF- or K-ras associated expression profiles. Unsupervised two-way hierarchical clustering and multidimensional scaling revealed that the differentially expressed genes clustered according to the mutation status of BRAF and K-ras, and that samples with the BRAF-V600E and non-V600E mutants could be distinguished from each other by gene profiling. Examination of TNM-Duke's staging, MSI and mutations in APC and TP53 revealed that these significant mutations could not account for the hierarchical clustering results observed in our study. We herein identified distinct gene expression patterns and gene sets that may form the basis for identification of BRAF-targeting molecules or provide researchers with a better understanding of the molecular pathogenesis underlying RAS-RAF signaling.

Global analysis of gene expression in gastric ischemia-reperfusion: a future therapeutic direction for mucosal protective drugs

Gastric ischemia-reperfusion is a relatively common condition leading to mucosal injury and may affect mucosal repair via modulating the gene expression of growth factors. Therefore, precise understanding of the molecular mechanism of ischemia or ischemia-reperfusion may lead to the discovery of new mucosal protective drugs. DNA microarray analysis followed by powerful data analysis has the potential to uncover previously undescribed genes involved in gastric injury and lead to an increased understanding of gastric mucosal cytoprotection. We introduced the laser-assisted microdissection to obtain cell-specific RNA from gastric mucosa in vivo and obtained sufficient amounts of cRNA for GeneChip analysis. This comprehensive approach enabled the simultaneous analysis of many genes, including transcriptional factors, as well as the generation of novel hypothesis on the mechanism of action of gastro-protective agents.

Gene deregulation in gastric cancer

Despite its decreasing frequency in the Western world during recent decades, gastric cancer is still one of the leading causes of cancer-related deaths worldwide. Due to the oligosymptomatic course of early gastric cancer, most cases are diagnosed in the advanced stages of the disease. The curative potential of current standard treatment continues to be unsatisfactory, despite multimodal approaches involving surgery, chemotherapy and radiotherapy. Novel therapeutics including small molecules and monoclonal antibodies are being developed and have been partially introduced into clinical use in connection with neoplastic diseases such as chronic myeloid leukemia, non-Hodgkin's lymphoma and colorectal cancer. Thorough understanding of the changes in gene expression occurring during gastric carcinogenesis may help to develop targeted therapies and improve the treatment of this disease. Novel molecular biology techniques have generated a wealth of data on up- and down-regulation, activation and inhibition of specific pathways in gastric cancer. Here, we provide an overview of the different aspects of aberrant gene expression patterns in gastric cancer.

A Novel Group of Genes Regulates Susceptibility to Antineoplastic Drugs in Highly Tumorigenic Breast Cancer Cells

Doxorubicin is an anthracycline antibiotic used for cancer chemotherapy. The utility of doxorubicin is limited by its inability to kill all of the cells within a tumor and by resistant cells emerging from the treated population. We have screened for genes that regulate doxorubicin susceptibility in highly tumorigenic breast cancer cells by cDNA microarray and RNA interference (RNAi) analysis, and we have identified genes associated with both proliferation and cell cycle arrest after doxorubicin treatment. We confirmed that MDA-MB-231 cells treated with doxorubicin induce the expression of carbonic anhydrase II (CAII), inhibitor of differentiation/DNA binding 2 (Id2), activating transcription factor 3 (Atf3), and the phosphatidylinositol 3-kinase 55-kDa regulatory subunit p55PIK. These genes were induced at different times and with varying specificities to different chemotherapeutic drugs. In addition to being induced at the transcriptional level, the CAII and clusterin proteins were elevated after doxorubicin treatment. CAII, Id2, p55PIK, and clusterin were not altered by doxorubicin in MCF-7 cells, a weakly tumorigenic cell line used in previous studies of doxorubicin-regulated gene expression. By inhibiting gene expression using RNAi, we found that CAII and clusterin increase cell survival after doxorubicin treatment, whereas Id2 increases susceptibility to doxorubicin. Our results support a model in which highly tumorigenic breast cancer cells induce a transcriptional response to doxorubicin that is distinct from less malignant cells. The induced genes regulate drug susceptibility positively and negatively and may be novel targets for therapeutic intervention.

Identification of midkine as a mediator for intercellular transfer of drug resistance

Resistance to cytotoxic agents is a major limitation for their clinical use to treat human cancers. Tumors become resistant to chemotherapy when a subset of cells undergoes molecular changes leading to overexpression of drug transport proteins, alterations in drug-target interactions or reduced ability to commit apoptosis. However, such changes may not be sufficient to explain why both resistant and nonresistant cells survive drug's action in tumors that ultimately become drug resistant. We hypothesized that, in such tumors, a cytoprotective relationship may exist between drug-resistant and neighboring drug-sensitive cells. The present study addresses the possibility that drug-resistant cells secrete in their culture medium factors able to protect sensitive cells from drug toxicity. A survival molecule, midkine, was identified by cDNA array to be expressed only in drug-resistant cells. Midkine-enriched fractions obtained by affinity chromatography exert a significant cytoprotective effect against doxorubicin in the wild-type drug-sensitive cells. Moreover, transfection of these cells with the midkine gene caused a decreased response to doxorubicin. The underlying mechanism of this cytoprotection appeared to imply activation of the Akt pathway and inhibition of drug-induced proliferation arrest as well as apoptotic cell death. These findings provide evidence for the existence of intercellular cytoprotective signals such as the one mediated by midkine, originating from cells with acquired drug resistance to protect neighboring drug-sensitive cells and thus contribute to development of resistance to chemotherapy.

Characterization of RhoA-mediated chemoresistance in gastric cancer cells

PURPOSE

RhoA is a critical transducer of extracellular signals, which leads to organization of actin cytoskeleton, motility, adhesion and gene regulation. The present study aimed to explore whether RhoA influences the susceptibility of gastric cancer cells to chemotherapeutic drugs.

MATERIALS AND METHODS

SNU638 cells were transfected with a mock vector (pcDNA3.1), RhoA (pcDNA/RhoA), or constitutively active RhoA (pcDNA/caRhoA). MTT assay and Western blot analysis were performed to study the growth response to several chemotherapeutic drugs in the gastric cancer cell line, SNU638, with different RhoA levels.

RESULTS

RhoA significantly enhanced the resistance to lovastatin, 5-FU, taxol and vincristine, but did not affect the sensitivity to cisplatin or etoposide in SNU638. In the Western blot analysis, RhoA decreased the PARP cleavage, which was accompanied by a concurrent reduction in cell death. The gene expression profile after a cDNA microarray analysis demonstrated that RhoA was associated with the differential expression of 19 genes, including those involved in anti-oxidant defense, glucose metabolism, anti-apoptosis and protein turnover.

CONCLUSION

Gastric cancer cells with a high expression of RhoA could be resistant to chemotherapeutic drugs, such as taxol or vincristine, implying that treatment strategies aimed at inactivation of RhoA might be promising for improving the efficacy of these chemotherapeutic drugs.

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Prediction of doxorubicin sensitivity in breast tumors based on gene expression profiles of drug-resistant cell lines correlates with patient survival

Up to date clinical tests for predicting cancer chemotherapy response are not available and individual markers have shown little predictive value. We hypothesized that gene expression patterns attributable to chemotherapy-resistant cells can predict response and cancer prognosis. We contrasted the expression profiles of 13 different human tumor cell lines of gastric (EPG85-257), pancreatic (EPP85-181), colon (HT29) and breast (MCF7 and MDA-MB-231) origin and their counterparts resistant to the topoisomerase inhibitors daunorubicin, doxorubicin or mitoxantrone. We interrogated cDNA arrays with 43 000 cDNA clones ( approximately 30 000 unique genes) to study the expression pattern of these cell lines. We divided gene expression profiles into two sets: we compared the expression patterns of the daunorubicin/doxorubicin-resistant cell lines and the mitoxantrone-resistant cell lines independently to the parental cell lines. For identifying predictive genes, the Prediction Analysis for Mircorarrays algorithm was used. The analysis revealed 79 genes best correlated with doxorubicin resistance and 70 genes with mitoxantrone resistance. In an independent classification experiment, we applied our model of resistance for predicting the sensitivity of 44 previously characterized breast cancer samples. The patient group characterized by the gene expression profile similar to those of doxorubicin-sensitive cell lines exhibited longer survival (49.7+/-26.1 months, n=21, P=0.034) than the resistant group (32.9+/-18.7 months, n=23). The application of gene expression signatures derived from doxorubicin-resistant and -sensitive cell lines allowed to predict effectively clinical survival after doxorubicin monotherapy. Our approach demonstrates the significance of in vitro experiments in the development of new strategies for cancer response prediction.

Chemosensitivity profile of cancer cell lines and identification of genes determining chemosensitivity by an integrated bioinformatical approach using cDNA arrays

We have established a panel of 45 human cancer cell lines (JFCR-45) to explore genes that determine the chemosensitivity of these cell lines to anticancer drugs. JFCR-45 comprises cancer cell lines derived from tumors of three different organs: breast, liver, and stomach. The inclusion of cell lines derived from gastric and hepatic cancers is a major point of novelty of this study. We determined the concentration of 53 anticancer drugs that could induce 50% growth inhibition (GI50) in each cell line. Cluster analysis using the GI50s indicated that JFCR-45 could allow classification of the drugs based on their modes of action, which coincides with previous findings in NCI-60 and JFCR-39. We next investigated gene expression in JFCR-45 and developed an integrated database of chemosensitivity and gene expression in this panel of cell lines. We applied a correlation analysis between gene expression profiles and chemosensitivity profiles, which revealed many candidate genes related to the sensitivity of cancer cells to anticancer drugs. To identify genes that directly determine chemosensitivity, we further tested the ability of these candidate genes to alter sensitivity to anticancer drugs after individually overexpressing each gene in human fibrosarcoma HT1080. We observed that transfection of HT1080 cells with the HSPA1A and JUN genes actually enhanced the sensitivity to mitomycin C, suggesting the direct participation of these genes in mitomycin C sensitivity. These results suggest that an integrated bioinformatical approach using chemosensitivity and gene expression profiling is useful for the identification of genes determining chemosensitivity of cancer cells.

Karyotypic imbalances and differential gene expressions in the acquired doxorubicin resistance of hepatocellular carcinoma cells

Administration of doxorubicin has been shown to prolong survival of patients with hepatocellular carcinoma (HCC). However, treatment regimen is often complicated by the emergence of drug resistance. The goal of our study is to enhance our understanding on the genetic changes that confer cellular chemoresistance to doxorubicin. To model this insensitive response, we established five doxorubicin-resistant (DOR) sublines through repeated exposure of escalating doses of doxorubicin to HCC cell lines (HKCI-2, -3, -4, -C1 and -C2). The DOR sublines developed displayed an average approximately 17-fold higher IC(50) value than their sensitive parental cell lines. The resistant phenotype displayed was investigated by the genome-wide analyses of comparative genomic hybridization (CGH) and complementary DNA microarray for the affected genomic anomalies and deregulated genes expressed, respectively. Over-representations of regional chr. 7q11-q21, 8q22-q23 and 10p13-pter were indicated in the DOR sublines from CGH analysis. Of particular interest was the finding of amplicon augmentations from regional or whole chromosome gains during the clonal expansion of resistant sublines. Most notably, recurring amplicon 7q11.2-q21 identified coincided with the location of the multi-drug-resistant gene, MDR1. The potential involvement of MDR1 was examined by quantitative reverse transcription-polymerase chain reaction RT-PCR (qRT-PCR), which indicated an upregulation in all DOR sublines (P=0.015). Consistent overexpression of the translated MDR1 gene, P-glycoprotein, in all five DOR sublines was further confirmed in Western blot analysis. Two distinct cluster dendrograms were achieved between the DOR sublines and their sensitive parental counterparts in expression profiling. Within the doxorubicin-resistant group, distinct features of candidate genes overexpressions including ABC transporting proteins, solute carriers and TOP2A were suggested. Further assessment of TOP2A messenger RNA levels by qRT-PCR confirmed array findings and pinpointed to a common up-regulation of TOP2A in DOR sublines. Our present study highlighted areas of genomic imbalances and candidate genes in the acquired doxorubicin-resistance behavior of HCC cells.

Gene expression profile differences in gastric cancer, pericancerous epithelium and normal gastric mucosa by gene chip

AIM: To study the difference of gene expression in gastric cancer (T), pericancerous epithelium (P) and normal tissue of gastric mucosa (C), and to screen an associated novel gene in early gastric carcinogenesis by oligonucleotide microarray.

METHODS: U133A (Affymetrix, Santa Clara, CA) gene chip was used to detect the gene expression profile difference in T, P and C, respectively. Bioinformatics was used to analyze the detected results.

RESULTS: When gastric cancer was compared with normal gastric mucosa, 766 genes were found, with a difference of more than four times in expression levels. Of the 766 genes, 530 were up-regulated (Signal Log Ratio [SLR]>2), and 236 were down-regulated (SLR<-2). When pericancerous epithelium was compared with normal gastric mucosa, 64 genes were found, with a difference of more than four times in expression levels. Of the 64 genes, 50 were up-regulated (SLR>2), and 14 were down-regulated (SLR<-2). Compared with normal gastric mucosa, a total of 143 genes with a difference in expression levels (more than four times, either in cancer or in pericancerous epithelium) were found in gastric cancer (T) and pericancerous epithelium (P). Of the 143 genes, 108 were up-regulated (SLR>2), and 35 were down-regulated (SLR<-2).

CONCLUSION: To apply a gene chip could find 143 genes associated with the genes of gastric cancer in pericancerous epithelium, although there were no pathological changes in the tissue slices. More interesting, six genes of pericancerous epithelium were up-regulated in comparison with genes of gastric cancer and three genes were down-regulated in comparison with genes of gastric cancer. It is suggested that these genes may be related to the carcinogenesis and development of early gastric cancer.

Biology of SNU cell lines

SNU (Seoul National University) cell lines have been established from Korean cancer patients since 1982. Of these 109 cell lines have been characterized and reported, i.e., 17 colorectal carcinoma, 12 hepatocellular carcinoma, 11 gastric carcinoma, 12 uterine cervical carcinoma, 17 B-lymphoblastoid cell lines derived from cancer patients, 5 ovarian carcinoma, 3 malignant mixed Mllerian tumor, 6 laryngeal squamous cell carcinoma, 7 renal cell carcinoma, 9 brain tumor, 6 biliary tract, and 4 pancreatic carcinoma cell lines. These SNU cell lines have been distributed to biomedical researchers domestic and worldwide through the KCLB (Korean Cell Line Bank), and have proven to be of value in various scientific research fields. The characteristics of these cell lines have been reported in over 180 international journals by our laboratory and by many other researchers from 1987. In this paper, the cellular and molecular characteristics of SNU human cancer cell lines are summarized according to their genetic and epigenetic alterations and functional analysis.

Tumoral drug metabolism: overview and its implications for cancer therapy

Drug-metabolizing enzymes (DME) in tumors are capable of biotransforming a variety of xenobiotics, including antineoplastics, resulting in either their activation or detoxification. Many studies have reported the presence of DME in tumors; however, heterogeneous detection methodology and patient cohorts have not generated consistent, firm data. Nevertheless, various gene therapy approaches and oral prodrugs have been devised, taking advantage of tumoral DME. With the need to target and individualize anticancer therapies, tumoral processes such as drug metabolism must be considered as both a potential mechanism of resistance to therapy and a potential means of achieving optimal therapy. This review discusses cytotoxic drug metabolism by tumors, through addressing the classes of the individual DME, their relevant substrates, and their distribution in specific malignancies. The limitations of preclinical models relative to the clinical setting and lack of data on the changes of DME with disease progression and host response will be discussed. The therapeutic implications of tumoral drug metabolism will be addressed-in particular, the role of DME in predicting therapeutic response, the activation of prodrugs, and the potential for modulation of their activity for gain are considered, with relevant clinical examples. The contribution of tumoral drug metabolism to cancer therapy can only be truly ascertained through large-scale prospective studies and supported by new technologies for tumor sampling and genetic analysis such as microarrays. Only then can efforts be concentrated in the design of better prodrugs or combination therapy to improve drug efficacy and individualize therapy.

Microarray analysis of gene regulation in the Hepa1c1c7 cell line following exposure to the DNA methylation inhibitor 5-aza-2′-deoxycytidine and 2,3,7,8-tetrachlorodibenzo-p-dioxin

Differential expression of various genes was observed in the Hepa1c1c7 cell line following exposure to the DNA methylation inhibitor 5-aza-2'-deoxycytidine (AzaC) and to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). AzaC treatment generally affected genes induced by TCDD by modulating their induction levels. Induction of several genes, such as receptor (calcitonin) activity modifying protein 3 (Ramp3) by TCDD was enhanced by AzaC, although AzaC by itself was without effect. Some genes, such as frequently rearranged in advanced T-cell lymphomas (Frat1), were up-regulated by AzaC alone, with this induction being negatively affected by TCDD. Other genes were induced by AzaC, TCDD and their co-treatment. In contrast, many genes such as small proline-rich protein 1A (Sprr1a) and 2A (Sprr1a) were up-regulated by AzaC, but not significantly affected by TCDD. In addition, a group of genes was down-regulated by AzaC, TCDD and their co-treatment. These findings suggest the TCDD-dependent regulation of various genes to be influenced by cellular DNA methylation status.

Microarray applications in cancer research

DNA microarray technology permits simultaneous analysis of thousands of DNA sequences for genomic research and diagnostics applications. Microarray technology represents the most recent and exciting advance in the application of hybridization-based technology for biological sciences analysis. This review focuses on the classification (oligonucleotide vs. cDNA) and application (mutation-genotyping vs. gene expression) of microarrays. Oligonucleotide microarrays can be used both in mutation-genotyping and gene expression analysis, while cDNA microarrays can only be used in gene expression analysis. We review microarray mutation analysis, including examining the use of three oligonucleotide microarrays developed in our laboratory to determine mutations in RET, beta-catenin and K-ras genes. We also discuss the use of the Affymetrix GeneChip in mutation analysis. We review microarray gene expression analysis, including the classifying of such studies into four categories: class comparison, class prediction, class discovery and identification of biomarkers.

Induction and characterization of taxol-resistance phenotypes with a transiently expressed artificial transcriptional activator library

Phenotype-based functional genomic methods are useful for the identification of genes that are related to a particular biological function or disease. Essential to this approach is the ability to regulate the expression of selected genes. Artificial transcription factors (ATFs) are key molecular tools that selectively regulate gene expression in vivo. Here, we use an ATF library to identify genes that participate in rendering a cell resistant to the drug Taxol, a potent anti-cancer drug that binds to tubulin and inhibits cell division. The library, which encodes ATFs that activate (rather than inhibit) transcription, was introduced into a HeLa cell line, and Taxol-resistant cells were selected. After eight rounds of selection, we identified two ATFs that significantly increased the level of Taxol resistance (TR) in HeLa cells. Gene expression microarray experiments using these ATFs identified 37 co-regulated genes, including genes already known to participate in TR. This study demonstrates that ATF libraries can be used to induce phenotypic alterations in eukaryotic cells and then identify specific genes that are associated with the phenotype of choice.