DNA microarray analysis of the correlation between gene expression patterns and acquired resistance to 5-FU/cisplatin in gastric cancer

Systematic review of comparative transcriptomic studies of cellular resistance to genotoxic stress

The development of resistance by tumor cells to various types of therapy is a significant problem that decreases the effectiveness of oncology treatments. For more than two decades, comparative transcriptomic studies of tumor cells with different sensitivities to ionizing radiation and chemotherapeutic agents have been conducted in order to identify the causes and mechanisms underlying this phenomenon. However, the results of such studies have little in common and often contradict each other. We have assumed that a systematic analysis of a large number of such studies will provide new knowledge about the mechanisms of development of therapeutic resistance in tumor cells. Our comparison of 123 differentially expressed gene (DEG) lists published in 98 papers suggests a very low degree of consistency between the study results. Grouping the data by type of genotoxic agent and tumor type did not increase the similarity. The most frequently overexpressed genes were found to be those encoding the transport protein ABCB1 and the antiviral defense protein IFITM1. We put forward a hypothesis that the role played by the overexpression of the latter in the development of resistance may be associated not only with the stimulation of proliferation, but also with the limitation of exosomal communication and, as a result, with a decrease in the bystander effect. Among down regulated DEGs, BNIP3 was observed most frequently. The expression of BNIP3, together with BNIP3L, is often suppressed in cells resistant to non-platinum genotoxic chemotherapeutic agents, whereas it is increased in cells resistant to ionizing radiation. These observations are likely to be mediated by the binary effects of these gene products on survival, and regulation of apoptosis and autophagy. The combined data also show that even such obvious mechanisms as inhibition of apoptosis and increase of proliferation are not universal but show multidirectional changes.

A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer

BACKGROUND

Currently, pathological examination of gastroscopy biopsy specimens is the gold standard for gastric cancer (GC) diagnosis. However, it has a false-negative rate of 10-20% due to inaccurate sampling locations and/or insufficient sampling amount. A signature should be developed to aid the early diagnosis of GC using biopsy specimens even when they are sampled from inaccurate locations.

METHODS

We extracted a robust qualitative transcriptional signature, based on the within-sample relative expression orderings (REOs) of gene pairs, to discriminate both GC tissues and adjacent-normal tissues from non-GC gastritis, intestinal metaplasia and normal gastric tissues.

RESULTS

A signature consisting of two gene pairs for GC diagnosis was identified and validated in data of both biopsy specimens and surgical resection specimens pooled from publicly available datasets measured by different laboratories with different platforms. For gastroscopy biopsy specimens, 96.20% of 79 non-GC tissues were correctly identified as non-GC, and 96.84% of 158 GC tissues and six of seven adjacent-normal tissues were correctly identified as GC. For surgical resection specimens, 98.37% of 2560 GC tissues and 97.28% of 221 adjacent-normal tissues were correctly identified as GC. Especially, 97.67% of the 257 GC patients at stage I were exactly diagnosed as GC. We additionally measured 21 GC tissues from seven different GC patients, each with three specimens sampled from three tumor locations with different proportions of the tumor epithelial cell. All these GC tissues were correctly identified as GC, even when the proportion of the tumor epithelial cell was as low as 14%.

CONCLUSIONS

The qualitative transcriptional signature can distinguish both GC and adjacent-normal tissues from normal, gastritis and intestinal metaplasia tissues of non-GC patients even using inaccurately sampled biopsy specimens, which can be applied robustly at the individual level to aid the early GC diagnosis.

SPARC expression in gastric cancer predicts poor prognosis: Results from a clinical cohort, pooled analysis and GSEA assay

Background

The prognostic role of Secreted Protein Acidic and Rich in Cysteine (SPARC) in gastric cancer (GC) remains controversial. We investigated the clinical significance, the survival relevance, and potential function of SPARC in GC with resected samples, online gene set GSE62254, and cell line SGC7901.

Results

High immunostaining of SPARC significantly correlated with tumor differentiation (P = 0.004), and independently predicted shorter overall survival (OS) (HR = 1.446, P = 0.022), based on the current IHC evaluation. The accuracy of the results was further validated with 1000 times bootstrapping and the time-dependent receiver-operating characteristics (ROC) curves. The meta-analysis (pooled HR = 1.60, 95% CI: 1.01−2.53) confirmed SPARC as the predictor for reduced OS in GC. Moreover, the association between enhanced SPARC expression and Adriamycin (Adr) sensitivity was revealed by GSEA, and then confirmed by comparative cellular experiments, such as the protein level analysis of SGC7901and SGC7901/Adr cell line.

Materials and Methods

Immunohistochemistry (IHC) method was used to detect SPARC expression in 137 GC cases. Meta-analysis was performed based on 5 studies published in English on PubMed up to March 2016. GSEA was performed using online data set GSE62254 and GC-related functional gene sets derived from molecular signatures database (MSigDB). Western Blot was carried out to compare protein-level differences between gastric carcinoma SGC7901 cell line and Adr resistant SGC7901/Adr cell line. MTT assay was done to confirm the induction of SPARC on Adr sensitivity

Conclusions

Increased SPARC expression in GC led to a worse clinical outcome of patients and might induce Adr sensitivity of GC cells.

Molecular classification and prediction in gastric cancer

Gastric cancer, a highly heterogeneous disease, is the second leading cause of cancer death and the fourth most common cancer globally, with East Asia accounting for more than half of cases annually. Alongside TNM staging, gastric cancer clinic has two well-recognized classification systems, the Lauren classification that subdivides gastric adenocarcinoma into intestinal and diffuse types and the alternative World Health Organization system that divides gastric cancer into papillary, tubular, mucinous (colloid), and poorly cohesive carcinomas. Both classification systems enable a better understanding of the histogenesis and the biology of gastric cancer yet have a limited clinical utility in guiding patient therapy due to the molecular heterogeneity of gastric cancer. Unprecedented whole-genome-scale data have been catalyzing and advancing the molecular subtyping approach. Here we cataloged and compared those published gene expression profiling signatures in gastric cancer. We summarized recent integrated genomic characterization of gastric cancer based on additional data of somatic mutation, chromosomal instability, EBV virus infection, and DNA methylation. We identified the consensus patterns across these signatures and identified the underlying molecular pathways and biological functions. The identification of molecular subtyping of gastric adenocarcinoma and the development of integrated genomics approaches for clinical applications such as prediction of clinical intervening emerge as an essential phase toward personalized medicine in treating gastric cancer.

miRNA signature associated with outcome of gastric cancer patients following chemotherapy

Background

Identification of patients who likely will or will not benefit from cytotoxic chemotherapy through the use of biomarkers could greatly improve clinical management by better defining appropriate treatment options for patients. microRNAs may be potentially useful biomarkers that help guide individualized therapy for cancer because microRNA expression is dysregulated in cancer. In order to identify miRNA signatures for gastric cancer and for predicting clinical resistance to cisplatin/fluorouracil (CF) chemotherapy, a comprehensive miRNA microarray analysis was performed using endoscopic biopsy samples.

Methods

Biopsy samples were collected prior to chemotherapy from 90 gastric cancer patients treated with CF and from 34 healthy volunteers. At the time of disease progression, post-treatment samples were additionally collected from 8 clinical responders. miRNA expression was determined using a custom-designed Agilent microarray. In order to identify a miRNA signature for chemotherapy resistance, we correlated miRNA expression levels with the time to progression (TTP) of disease after CF therapy.

Results

A miRNA signature distinguishing gastric cancer from normal stomach epithelium was identified. 30 miRNAs were significantly inversely correlated with TTP whereas 28 miRNAs were significantly positively correlated with TTP of 82 cancer patients (P<0.05). Prominent among the upregulated miRNAs associated with chemosensitivity were miRNAs known to regulate apoptosis, including let-7g, miR-342, miR-16, miR-181, miR-1, and miR-34. When this 58-miRNA predictor was applied to a separate set of pre- and post-treatment tumor samples from the 8 clinical responders, all of the 8 pre-treatment samples were correctly predicted as low-risk, whereas samples from the post-treatment tumors that developed chemoresistance were predicted to be in the high-risk category by the 58 miRNA signature, suggesting that selection for the expression of these miRNAs occurred as chemoresistance arose.

Conclusions

We have identified 1) a miRNA expression signature that distinguishes gastric cancer from normal stomach epithelium from healthy volunteers, and 2) a chemoreresistance miRNA expression signature that is correlated with TTP after CF therapy. The chemoresistance miRNA expression signature includes several miRNAs previously shown to regulate apoptosis in vitro, and warrants further validation.

Operating room to bench for gastric cancer

Gastric cancer is the most common cancer in Korea, with an age-standardized rate of 61.2 in males and 23.9 in females (in 2007), one of the highest in the world. Using a large gastric tissue depository and the extensive clinical experience gained from gastric cancer surgery, we work as a 'translational researcher' to apply basic research tools and results to the clinical field. We are also interested in providing answers to the questions in the operating room using the methods of basic research. I would like to introduce our research activities in this review paper.

Distinctions in gastric cancer gene expression signatures derived from laser capture microdissection versus histologic macrodissection

Background

Gastric cancer samples obtained by histologic macrodissection contain a relatively high stromal content that may significantly influence gene expression profiles. Differences between the gene expression signature derived from macrodissected gastric cancer samples and the signature obtained from isolated gastric cancer epithelial cells from the same biopsies using laser-capture microdissection (LCM) were evaluated for their potential experimental biases.

Methods

RNA was isolated from frozen tissue samples of gastric cancer biopsies from 20 patients using both histologic macrodissection and LCM techniques. RNA from LCM was subject to an additional round of T7 RNA amplification. Expression profiling was performed using Affymetrix HG-U133A arrays. Genes identified in the expression signatures from each tissue processing method were compared to the set of genes contained within chromosomal regions found to harbor copy number aberrations in the tumor samples by array CGH and to proteins previously identified as being overexpressed in gastric cancer.

Results

Genes shown to have increased copy number in gastric cancer were also found to be overexpressed in samples obtained by macrodissection (LS P value < 10^-5), but not in array data generated using microdissection. A set of 58 previously identified genes overexpressed in gastric cancer was also enriched in the gene signature identified by macrodissection (LS P < 10^-5), but not in the signature identified by microdissection (LS P = 0.013). In contrast, 66 genes previously reported to be underexpressed in gastric cancer were enriched in the gene signature identified by microdissection (LS P < 10^-5), but not in the signature identified by macrodissection (LS P = 0.89).

Conclusions

The tumor sampling technique biases the microarray results. LCM may be a more sensitive collection and processing method for the identification of potential tumor suppressor gene candidates in gastric cancer using expression profiling.

A gene expression signature of acquired chemoresistance to cisplatin and fluorouracil combination chemotherapy in gastric cancer patients

Background

We initiated a prospective trial to identify transcriptional alterations associated with acquired chemotherapy resistance from pre- and post-biopsy samples from the same patient and uncover potential molecular pathways involved in treatment failure to help guide therapeutic alternatives.

Methodology/Principal Findings

A prospective, high-throughput transcriptional profiling study was performed using endoscopic biopsy samples from 123 metastatic gastric cancer patients prior to cisplatin and fluorouracil (CF) combination chemotherapy. 22 patients who initially responded to CF were re-biopsied after they developed resistance to CF. An acquired chemotherapy resistance signature was identified by analyzing the gene expression profiles from the matched pre- and post-CF treated samples.

The acquired resistance signature was able to segregate a separate cohort of 101 newly-diagnosed gastric cancer patients according to the time to progression after CF. Hierarchical clustering using a 633-gene acquired resistance signature (feature selection at P<0.01) separated the 101 pretreatment patient samples into two groups with significantly different times to progression (2.5 vs. 4.7 months). This 633-gene signature included the upregulation of AKT1, EIF4B, and RPS6 (mTOR pathway), DNA repair and drug metabolism genes, and was enriched for genes overexpressed in embryonic stem cell signatures. A 72-gene acquired resistance signature (a subset of the 633 gene signature also identified in ES cell-related gene sets) was an independent predictor for time to progression (adjusted P = 0.011) and survival (adjusted P = 0.034) of these 101 patients.

Conclusion/Significance

This signature may offer new insights into identifying new targets and therapies required to overcome the acquired resistance of gastric cancer to CF.

A functional and transcriptomic analysis of NET1 bioactivity in gastric cancer

BACKGROUND

NET1, a RhoA guanine exchange factor, is up-regulated in gastric cancer (GC) tissue and drives the invasive phenotype of this disease. In this study, we aimed to determine the role of NET1 in GC by monitoring the proliferation, motility and invasion of GC cells in which NET1 has been stably knocked down. Additionally, we aimed to determine NET1-dependent transcriptomic events that occur in GC.

METHODS

An in vitro model of stable knockdown of NET1 was achieved in AGS human gastric adenocarcinoma cells via lentiviral mediated transduction of short-hairpin (sh) RNA targeting NET1. Knockdown was assessed using quantitative PCR. Cell proliferation was assessed using an MTS assay and cell migration was assessed using a wound healing scratch assay. Cell invasion was assessed using a transwell matrigel invasion assay. Gene expression profiles were examined using affymetrix oligonucleotide U133A expression arrays. A student's t test was used to determine changes of statistical significance.

RESULTS

GC cells were transduced with NET1 shRNA resulting in a 97% reduction in NET1 mRNA (p < 0.0001). NET1 knockdown significantly reduced the invasion and migration of GC cells by 94% (p < 0.05) and 24% (p < 0.001) respectively, while cell proliferation was not significantly altered following NET1 knockdown. Microarray analysis was performed on non-target and knockdown cell lines, treated with and without 10 μM lysophosphatidic acid (LPA) allowing us to identify NET1-dependent, LPA-dependent and NET1-mediated LPA-induced gene transcription. Differential gene expression was confirmed by quantitative PCR. Shortlisted NET1-dependent genes included STAT1, TSPAN1, TGFBi and CCL5 all of which were downregulatd upon NET1 downregulation. Shortlisted LPA-dependent genes included EGFR and PPARD where EGFR was upregulated and PPARD was downregulated upon LPA stimulation. Shortlisted NET1 and LPA dependent genes included IGFR1 and PIP5K3. These LPA induced genes were downregulated in NET1 knockdown cells.

CONCLUSIONS

NET1 plays an important role in GC cell migration and invasion, key aspects of GC progression. Furthermore, the gene expression profile further elucidates the molecular mechanisms underpinning NET1-mediated aggressive GC cell behaviour.

Three-gene predictor of clinical outcome for gastric cancer patients treated with chemotherapy

To identify transcriptional profiles predictive of the clinical benefit of cisplatin and fluorouracil (CF) chemotherapy to gastric cancer patients, endoscopic biopsy samples from 96 CF-treated metastatic gastric cancer patients were prospectively collected before therapy and analyzed using high-throughput transcriptional profiling and array comparative genomic hybridization. Transcriptional profiling identified 917 genes that are correlated with poor patient survival after CF at P<0.05 (poor prognosis signature), in which protein synthesis and DNA replication/recombination/repair functional categories are enriched. A survival risk predictor was then constructed using genes, which are included in the poor prognosis signature and are contained within identified genomic amplicons. The combined expression of three genes—MYC, EGFR and FGFR2—was an independent predictor for overall survival of 27 CF-treated patients in the validation set (adjusted P=0.017), and also for survival of 40 chemotherapy-treated gastric cancer patients in a published data set (adjusted P=0.026). Thus, combined expression of MYC, EGFR and FGFR2 is predictive of poor survival in CF-treated metastatic gastric cancer patients.

Predicting human immunodeficiency virus protease cleavage sites in nonlinear projection space

HIV-1 protease has a broad and complex substrate specificity. The discovery of an accurate, robust, and rapid method for predicting the cleavage sites in proteins by HIV protease would greatly expedite the search for inhibitors of HIV protease. During the last two decades, various methods have been developed to explore the specificity of HIV protease cleavage activity. However, because little advancement has been made in the understanding of HIV-1 protease cleavage site specificity, not much progress has been reported in either extracting effective methods or maintaining high prediction accuracy. In this article, a theoretical framework is developed, based on the kernel method for dimensionality reduction and prediction for HIV-1 protease cleavage site specificity. A nonlinear dimensionality reduction kernel method, based on manifold learning, is proposed to reduce the high dimensions of protease specificity. A support vector machine is applied to predict the protease cleavage. Superior performance in comparison to that previously published in literature is obtained using numerical simulations showing that the basic specificities of the HIV-1 protease are maintained in reduction feature space, and by combining the nonlinear dimensionality reduction algorithm with a support vector machine classifier.

APM2 is a novel mediator of cisplatin resistance in a variety of cancer cell types regardless of p53 or MMR status

Cisplatin is one of the most widely used chemotherapeutics in the world today. Unfortunately, chemoresistance often develops hindering the effectiveness of the drug. Mismatch-repair (MMR) and p53 have previously been shown to be important determinants of cisplatin resistance and can contribute to cisplatin resistance clinically. Here, we have used cDNA microarray to identify several genes as up or downregulated in a previously described, cisplatin resistant, clone of the HCT116 cell line (HCT116-K). On follow-up, one gene, APM2, was found to promote cisplatin resistance when overexpressed in sensitive HCT116 clones. Furthermore, silencing APM2 in a panel of cell lines encompassing all combinations of p53 status and MMR proficiency (HCT116-K, HCT116, SW620, MCF7, PC-3 and OV2008) resulted in sensitization regardless of these 2 factors. In addition, silencing APM2 stably using shRNA also resulted in the sensitization of cells to cisplatin. More importantly, cisplatin inhibited the growth of APM2 silenced tumor xenografts (HCT116-K or OV2008 cells) significantly better than it inhibited the growth of xenografts carrying nontargeting control shRNAs. These findings represent a novel strategy that could be exploited to overcome cisplatin resistance in patients regardless of p53 status or ability to perform MMR.

5-Fluorouracil: mechanisms of resistance and reversal strategies

The purpose of this work is to review the published studies on the mechanisms of action and resistance of 5-fluorouracil. The review is divided into three main sections: mechanisms of anti-tumor action, studies of the resistance to the drug, and procedures for the identification of new genes involved in resistance with microarray techniques. The details of the induction and reversal of the drug resistance are also described.

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.

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.

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.

Multi-level gene expression profiles affected by thymidylate synthase and 5-fluorouracil in colon cancer

Background

Thymidylate synthase (TS) is a critical target for cancer chemotherapy and is one of the most extensively studied biomarkers for fluoropyrimidine-based chemotherapy. In addition to its critical role in enzyme catalysis, TS functions as an RNA binding protein to regulate the expression of its own mRNA translation and other cellular mRNAs, such as p53, at the translational level. In this study, a comprehensive gene expression analysis at the levels of both transcriptional and post-transcriptional regulation was conducted to identify response markers using human genome array with TS-depleted human colon cancer HCT-C18 (TS-) cells and HCT-C18 (TS+) cells stably transfected with the human TS cDNA expression plasmid.

Results

A total of 38 genes were found to be significantly affected by TS based on the expression profiles of steady state mRNA transcripts. However, based on the expression profiles of polysome associated mRNA transcripts, over 149 genes were affected by TS overexpression. This indicates that additional post-transcriptionally controlled genes can be captured with profiling polysome associated mRNA population. This unique approach provides a comprehensive overview of genes affected by TS. Additional novel post-transcriptionally regulated genes affected by 5-fluorouracil (5-FU) treatment were also discovered via similar approach.

Conclusion

To our knowledge, this is the first time that a comprehensive gene expression profile regulated by TS and 5-FU was analyzed at the multiple steps of gene regulation. This study will provide candidate markers that can be potentially used for predicting therapeutic outcomes for fluoropyrimidine-based cancer chemotherapy.

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.

Role of GADD34 in modulation of cisplatin cytotoxicity

Cisplatin and carboplatin are widely used clinical chemotherapeutic agents, especially against testicular, ovarian, and head and neck cancers. O(6)-Benzylguanine (BG) has been shown to result in enhanced cytotoxicity, apoptosis, and DNA platination when used in conjunction with cisplatin and carboplatin in head and neck cancer cell lines. Microarray expression data indicated overexpression of 19 genes and underexpression of 22 genes specific to treatment with the combination of BG+/-cisplatin compared to cisplatin alone treatment in SQ20b head and neck cancer cells (p<0.05) using the Affymetrix HG-U133A GeneChip((R)). Among the overexpressed probe sets were genes involved in DNA damage and apoptosis, including GADD34, DDIT4, ATF4, and PTHLH. A similarly structured analog, 9-CH(3)-BG, does not enhance cisplatin-induced cytotoxicity or apoptosis nor is there enhanced expression of GADD34 in cisplatin or 9-CH(3)-BG+/-cisplatin-treated cells compared to control cells. Analysis of cells exposed to 9-CH(3)-BG+/-cisplatin allowed us to focus our array list on 32 probe sets specific to BG+cisplatin versus cisplatin, ruling out differentially expressed probe sets common to 9-CH(3)-BG+cisplatin versus cisplatin. Similarly, 14 probe sets were specific to BG+/-cisplatin versus BG, ruling out differentially expressed probe sets common to 9-CH(3)-BG+/-cisplatin versus 9-CH(3)-BG. Quantitative real-time PCR demonstrated a dose dependent increase in GADD34 expression in cells exposed to BG+/-cisplatin with levels approximately >2-fold for cells exposed to BG+cisplatin compared to cisplatin alone. Levels of GADD34 transcripts were determined with both cisplatin and BG+cisplatin at several different time points concomitant with and following drug treatment. At all timepoints, GADD34 transcript levels are approximately two-fold elevated in cells treated with BG+cisplatin compared to cisplatin alone. Furthermore, significant changes in GADD34 expression levels in SQ20b, SCC35, and SCC61 cells, with approximately three-fold, two-fold, and 3.5-fold increases in expression, respectively, upon treatment with BG+/-cisplatin compared with control. Elucidation of these molecular pathways will aid in our goal of synthesizing more powerful modulators to increase efficacy of platinum 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.

Using microarrays to predict resistance to chemotherapy in cancer patients

Chemotherapy resistance remains a major obstacle to successful treatment and better outcome in cancer patients. The advent of whole genome experimental strategies, such as DNA microarrays, has transformed the way researchers approach cancer research. There is considerable hope that microarray technology will lead to the identification of new targets for therapeutic intervention, a better understanding of the disease process, and, ultimately, to higher survival rates and more personalized medicine. The question at hand is what is the best approach to apply these new technologies to the study of anticancer drug resistance, and how can the results obtained in the laboratory be quickly moved to a clinical setting? This review offers an overview of the microarray technology, including its recently associated strategies, such as array comparative genomic hybridization and promoter arrays. It also highlights some recent examples of microarray studies, which represent a first step toward a better understanding of drug resistance in cancer and, ultimately, personalized medicine.

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.