Network architecture of signaling from uncoupled helicase-polymerase to cell cycle checkpoints and trans-lesion DNA synthesis

When replication is blocked by a template lesion or polymerase inhibitor while helicase continues unwinding the DNA, single stranded DNA (ssDNA) accumulates and becomes coated with RPA, which then initiates signals via PCNA mono-ubiquitination to activate trans-lesion polymerases and via ATR and Chk1 to inhibit Cdk2-dependent cell cycle progression. The signals are conveyed by way of a complex network of molecular interactions. To clarify those complexities, we have constructed a molecular interaction map (MIM) using a novel hierarchical assembly procedure. Molecules were arranged on the map in hierarchical levels according to interaction step distance from the DNA region of stalled replication. The hierarchical MIM allows us to disentangle the network's interlocking pathways and loops and to suggest functionally significant features of network architecture. The MIM shows how parallel pathways and multiple feedback loops can provide failsafe and robust switch-like responses to replication stress. Within the central level of hierarchy ATR and Claspin together appear to function as a nexus that conveys signals from many sources to many destinations. We noted a division of labor between those two molecules, separating enzymatic and structural roles. In addition, the network architecture disclosed by the hierarchical map, suggested a speculative model for how molecular crowding and the granular localization of network components in the cell nucleus can facilitate function.

Evaluation of current methods used to analyze the expression profiles of ATP-binding cassette transporters yields an improved drug-discovery database

The development of multidrug resistance (MDR) to chemotherapy remains a major challenge in the treatment of cancer. Resistance exists against every effective anticancer drug and can develop by multiple mechanisms. These mechanisms can act individually or synergistically, leading to MDR, in which the cell becomes resistant to a variety of structurally and mechanistically unrelated drugs in addition to the drug initially administered. Although extensive work has been done to characterize MDR mechanisms in vitro, the translation of this knowledge to the clinic has not been successful. Therefore, identifying genes and mechanisms critical to the development of MDR in vivo and establishing a reliable method for analyzing highly homologous genes from small amounts of tissue is fundamental to achieving any significant enhancement in our understanding of MDR mechanisms and could lead to treatments designed to circumvent it. In this study, we use a previously established database that allows the identification of lead compounds in the early stages of drug discovery that are not ATP-binding cassette (ABC) transporter substrates. We believe this can serve as a model for appraising the accuracy and sensitivity of current methods used to analyze the expression profiles of ABC transporters. We found two platforms to be superior methods for the analysis of expression profiles of highly homologous gene superfamilies. This study also led to an improved database by revealing previously unidentified substrates for ABCB1, ABCC1, and ABCG2, transporters that contribute to MDR.

CellMiner: a relational database and query tool for the NCI-60 cancer cell lines

Background

Advances in the high-throughput omic technologies have made it possible to profile cells in a large number of ways at the DNA, RNA, protein, chromosomal, functional, and pharmacological levels. A persistent problem is that some classes of molecular data are labeled with gene identifiers, others with transcript or protein identifiers, and still others with chromosomal locations. What has lagged behind is the ability to integrate the resulting data to uncover complex relationships and patterns. Those issues are reflected in full form by molecular profile data on the panel of 60 diverse human cancer cell lines (the NCI-60) used since 1990 by the U.S. National Cancer Institute to screen compounds for anticancer activity. To our knowledge, CellMiner is the first online database resource for integration of the diverse molecular types of NCI-60 and related meta data.

Description

CellMiner enables scientists to perform advanced querying of molecular information on NCI-60 (and additional types) through a single web interface. CellMiner is a freely available tool that organizes and stores raw and normalized data that represent multiple types of molecular characterizations at the DNA, RNA, protein, and pharmacological levels. Annotations for each project, along with associated metadata on the samples and datasets, are stored in a MySQL database and linked to the molecular profile data. Data can be queried and downloaded along with comprehensive information on experimental and analytic methods for each data set. A Data Intersection tool allows selection of a list of genes (proteins) in common between two or more data sets and outputs the data for those genes (proteins) in the respective sets. In addition to its role as an integrative resource for the NCI-60, the CellMiner package also serves as a shell for incorporation of molecular profile data on other cell or tissue sample types.

Conclusion

CellMiner is a relational database tool for storing, querying, integrating, and downloading molecular profile data on the NCI-60 and other cancer cell types. More broadly, it provides a template to use in providing such functionality for other molecular profile data generated by academic institutions, public projects, or the private sector. CellMiner is available online at .

DNA fingerprinting of the NCI-60 cell line panel

The National Cancer Institute's NCI-60 cell line panel, the most extensively characterized set of cells in existence and a public resource, is frequently used as a screening tool for drug discovery. Because many laboratories around the world rely on data from the NCI-60 cells, confirmation of their genetic identities represents an essential step in validating results from them. Given the consequences of cell line contamination or misidentification, quality control measures should routinely include DNA fingerprinting. We have, therefore, used standard DNA microsatellite short tandem repeats to profile the NCI-60, and the resulting DNA fingerprints are provided here as a reference. Consistent with previous reports, the fingerprints suggest that several NCI-60 lines have common origins: the melanoma lines MDA-MB-435, MDA-N, and M14; the central nervous system lines U251 and SNB-19; the ovarian lines OVCAR-8 and OVCAR-8/ADR (also called NCI/ADR); and the prostate lines DU-145, DU-145 (ATCC), and RC0.1. Those lines also show that the ability to connect two fingerprints to the same origin is not affected by stable transfection or by the development of multidrug resistance. As expected, DNA fingerprints were not able to distinguish different tissues-of-origin. The fingerprints serve principally as a barcodes.

Asparagine synthetase: a new potential biomarker in ovarian cancer

L-Asparaginase (L-ASP) is an enzyme drug that has been an asset to leukemia treatment regimens for four decades. Variability in its clinical efficacy, however, has prompted the search for biomarkers capable of distinguishing responders from non-responders. In that regard, the NCI-60 cell line panel has served as a biomarker discovery platform and has led to the identification of a correlation between L-ASP efficacy and asparagine synthetase (ASNS) expression in cultured cells. The presence of that correlation in the ovarian subpanel of the NCI-60 has made a case for repositioning L-ASP to ovarian cancer. This review presents an overview of the biomarker development process, summarizes the efforts that have been invested thus far in developing ASNS as a biomarker for ovarian cancer treatment, highlights the role of RNAi and the limitations of the NCI-60 in that process, and addresses important considerations for next steps in the development of ASNS as a predictive biomarker.

Asparagine synthetase is a predictive biomarker of L-asparaginase activity in ovarian cancer cell lines

We recently used RNA interference to show that a negative correlation of L-asparaginase (L-ASP) chemotherapeutic activity with asparagine synthetase (ASNS) expression in the ovarian subset of the NCI-60 cell line panel is causal. To determine whether that relationship would be sustained in a larger, more diverse set of ovarian cell lines, we have now measured ASNS mRNA expression using microarrays and a branched-DNA RNA assay, ASNS protein expression using an electrochemiluminescent immunoassay, and L-ASP activity using an MTS assay on 19 human ovarian cancer cell lines. Contrary to our previous findings, L-ASP activity was only weakly correlated with ASNS mRNA expression; Pearson's correlation coefficients were r = -0.21 for microarray data and r = -0.39 for the branched-DNA RNA assay, with just the latter being marginally statistically significant (P = 0.047, one-tailed). ASNS protein expression measured by liquid-phase immunoassay exhibited a much stronger correlation (r = -0.65; P = 0.0014, one-tailed). We conclude that ASNS protein expression measured by immunoassay is a strong univariate predictor of L-ASP activity in ovarian cancer cell lines. These findings provide rationale for evaluation of ASNS protein expression as a predictive biomarker of clinical L-ASP activity in ovarian cancer.

Profiling SLCO and SLC22 genes in the NCI-60 cancer cell lines to identify drug uptake transporters

Molecular and pharmacologic profiling of the NCI-60 cell panel offers the possibility of identifying pathways involved in drug resistance or sensitivity. Of these, decreased uptake of anticancer drugs mediated by efflux transporters represents one of the best studied mechanisms. Previous studies have also shown that uptake transporters can influence cytotoxicity by altering the cellular uptake of anticancer drugs. Using quantitative real-time PCR, we measured the mRNA expression of two solute carrier (SLC) families, the organic cation/zwitterion transporters (SLC22 family) and the organic anion transporters (SLCO family), totaling 23 genes in normal tissues and the NCI-60 cell panel. By correlating the mRNA expression pattern of the SLCO and SLC22 family member gene products with the growth-inhibitory profiles of 1,429 anticancer drugs and drug candidate compounds tested on the NCI-60 cell lines, we identified SLC proteins that are likely to play a dominant role in drug sensitivity. To substantiate some of the SLC-drug pairs for which the SLC member was predicted to be sensitizing, follow-up experiments were performed using engineered and characterized cell lines overexpressing SLC22A4 (OCTN1). As predicted by the statistical correlations, expression of SLC22A4 resulted in increased cellular uptake and heightened sensitivity to mitoxantrone and doxorubicin. Our results indicate that the gene expression database can be used to identify SLCO and SLC22 family members that confer sensitivity to cancer cells.

SpliceCenter: a suite of web-based bioinformatic applications for evaluating the impact of alternative splicing on RT-PCR, RNAi, microarray, and peptide-based studies

Background

Over 60% of protein-coding genes in vertebrates express mRNAs that undergo alternative splicing. The resulting collection of transcript isoforms poses significant challenges for contemporary biological assays. For example, RT-PCR validation of gene expression microarray results may be unsuccessful if the two technologies target different splice variants. Effective use of sequence-based technologies requires knowledge of the specific splice variant(s) that are targeted. In addition, the critical roles of alternative splice forms in biological function and in disease suggest that assay results may be more informative if analyzed in the context of the targeted splice variant.

Results

A number of contemporary technologies are used for analyzing transcripts or proteins. To enable investigation of the impact of splice variation on the interpretation of data derived from those technologies, we have developed SpliceCenter. SpliceCenter is a suite of user-friendly, web-based applications that includes programs for analysis of RT-PCR primer/probe sets, effectors of RNAi, microarrays, and protein-targeting technologies. Both interactive and high-throughput implementations of the tools are provided. The interactive versions of SpliceCenter tools provide visualizations of a gene's alternative transcripts and probe target positions, enabling the user to identify which splice variants are or are not targeted. The high-throughput batch versions accept user query files and provide results in tabular form. When, for example, we used SpliceCenter's batch siRNA-Check to process the Cancer Genome Anatomy Project's large-scale shRNA library, we found that only 59% of the 50,766 shRNAs in the library target all known splice variants of the target gene, 32% target some but not all, and 9% do not target any currently annotated transcript.

Conclusion

SpliceCenter provides unique, user-friendly applications for assessing the impact of transcript variation on the design and interpretation of RT-PCR, RNAi, gene expression microarrays, antibody-based detection, and mass spectrometry proteomics. The tools are intended for use by bench biologists as well as bioinformaticists.

The EDGE hypothesis: epigenetically directed genetic errors in repeat-containing proteins (RCPs) involved in evolution, neuroendocrine signaling, and cancer

Trans-generational epigenetic phenomena, such as contamination with endocrine-disrupting chemicals (EDCs) that decrease fertility and the global methylation status of DNA in the offspring, are of great concern because they may affect health, particularly the health of children. However, of even greater concern is the possibility that trans-generational changes in the methylation status of the DNA might lead to permanent changes in the DNA sequence itself. By contaminating the environment with EDCs, mankind might be permanently affecting the health of future generations. In this section, we present evidence from our laboratory and others that trans-generational epigenetic changes in DNA might lead to mutations directed to genes encoding amino acid repeat-containing proteins (RCPs) that are important for adaptive evolution or cancer progression. Such epigenetic changes can be induced "naturally" by hormones or "unnaturally" by EDCs or environmental stress. To illustrate the phenomenon, we present new bioinformatic evidence that the only RCP ontological categories conserved from Drosophila to humans are "regulation of splicing," "regulation of transcription," and "regulation of synaptogenesis," which are classes of genes likely to be important for evolutionary processes. Based on that and other evidence, we propose a model for evolution that we call the EDGE (Epigenetically Directed Genetic Errors) hypothesis for the mechanism by which mutations are targeted at epigenetically modified "contingency genes" encoding RCPs. In the model, "epigenetic assimilation" of metastable epialleles of RCPs over many generations can lead to mutations directed to those genes, thereby permanently stabilizing the adaptive phenotype.

In vitro differential sensitivity of melanomas to phenothiazines is based on the presence of codon 600 BRAF mutation

The panel of 60 human cancer cell lines (the NCI-60) assembled by the National Cancer Institute for anticancer drug discovery is a widely used resource. We previously sequenced 24 cancer genes in those cell lines. Eleven of the genes were found to be mutated in three or more of the lines. Using a pharmacogenomic approach, we analyzed the relationship between drug activity and mutations in those 11 genes (APC, RB1, KRAS, NRAS, BRAF, PIK3CA, PTEN, STK11, MADH4, TP53, and CDKN2A). That analysis identified an association between mutation in BRAF and the antiproliferative potential of phenothiazine compounds. Phenothiazines have been used as antipsychotics and as adjunct antiemetics during cancer chemotherapy and more recently have been reported to have anticancer properties. However, to date, the anticancer mechanism of action of phenothiazines has not been elucidated. To follow up on the initial pharmacologic observations in the NCI-60 screen, we did pharmacologic experiments on 11 of the NCI-60 cell lines and, prospectively, on an additional 24 lines. The studies provide evidence that BRAF mutation (codon 600) in melanoma as opposed to RAS mutation is predictive of an increase in sensitivity to phenothiazines as determined by 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt assay (Wilcoxon P = 0.007). That pattern of increased sensitivity to phenothiazines based on the presence of codon 600 BRAF mutation may be unique to melanomas, as we do not observe it in a panel of colorectal cancers. The findings reported here have potential implications for the use of phenothiazines in the treatment of V600E BRAF mutant melanoma.

A stromal gene signature associated with inflammatory breast cancer

The factors that determine whether a breast carcinoma will develop into inflammatory breast cancer (IBC) remain poorly understood. Recent evidence indicates that the tumor stroma influences cancer phenotypes. We tested the hypotheses that the gene expression signature of the tumor stroma is a distinctive feature of IBC. We used laser capture microdissection to obtain enriched populations of tumor epithelial cells and adjacent stromal cells from 15 patients with IBC and 35 patients with invasive, noninflammatory breast cancer (non-IBC). Their mRNA expression profiles were assessed using Affymetrix GeneChips. In addition, a previously established classifier for IBC was evaluated for the resulting data sets. The gene expression profile of the tumor stroma distinguished IBC from non-IBC, and a previously established IBC prediction signature performed better in classifying IBC using the gene expression profile of the tumor stroma than it did using the profile of the tumor epithelium. In a pathway analysis, the genes differentially expressed between IBC and non-IBC tumors clustered in distinct pathways. We identified multiple pathways related to the endoplasmic stress response that could be functionally significant in IBC. Our findings suggest that the gene expression in the tumor stroma may play a role in determining the IBC phenotype.

Integrating global gene expression and radiation survival parameters across the 60 cell lines of the National Cancer Institute Anticancer Drug Screen

The 60 cell lines of the National Cancer Institute Anticancer Drug Screen (NCI-60) constitute the most extensively characterized in vitro cancer cell model. They have been tested for sensitivity to more than 100,000 potential chemotherapy agents and have been profiled extensively at the DNA, RNA, protein, functional, and pharmacologic levels. We have used the NCI-60 cell lines and three additional lines to develop a database of responses of cancer cells to ionizing radiation. We compared clonogenic survival, apoptosis, and gene expression response by microarray. Although several studies have profiled relative basal gene expression in the NCI-60, this is the first comparison of large-scale gene expression changes in response to genotoxic stress. Twenty-two genes were differentially regulated in cells with low survival after 2-Gy gamma-rays; 14 genes identified lines more sensitive to 8 Gy. Unlike reported basal gene expression patterns, changes in expression in response to radiation showed little tissue-of-origin effect, except for differentiating the lymphoblastoid cell lines from other cell types. Basal expression patterns, however, discriminated well between radiosensitive and more resistant lines, possibly being more informative than radiation response signatures. The most striking patterns in the radiation data were a set of genes up-regulated preferentially in the p53 wild-type lines and a set of cell cycle regulatory genes down-regulated across the entire NCI-60 panel. The response of those genes to gamma-rays seems to be unaffected by the myriad of genetic differences across this diverse cell set; it represents the most penetrant gene expression response to ionizing radiation yet observed.

VennMaster: area-proportional Euler diagrams for functional GO analysis of microarrays

Background

Microarray experiments generate vast amounts of data. The functional context of differentially expressed genes can be assessed by querying the Gene Ontology (GO) database via GoMiner. Directed acyclic graph representations, which are used to depict GO categories enriched with differentially expressed genes, are difficult to interpret and, depending on the particular analysis, may not be well suited for formulating new hypotheses. Additional graphical methods are therefore needed to augment the GO graphical representation.

Results

We present an alternative visualization approach, area-proportional Euler diagrams, showing set relationships with semi-quantitative size information in a single diagram to support biological hypothesis formulation. The cardinalities of sets and intersection sets are represented by area-proportional Euler diagrams and their corresponding graphical (circular or polygonal) intersection areas. Optimally proportional representations are obtained using swarm and evolutionary optimization algorithms.

Conclusion

VennMaster's area-proportional Euler diagrams effectively structure and visualize the results of a GO analysis by indicating to what extent flagged genes are shared by different categories. In addition to reducing the complexity of the output, the visualizations facilitate generation of novel hypotheses from the analysis of seemingly unrelated categories that share differentially expressed genes.

Predicting cisplatin and trabectedin drug sensitivity in ovarian and colon cancers

Molecular profiling of markers involved in the activity of chemotherapeutic agents can shed light on the successes and failures of treatment in patients and can also provide a basis for individualization of therapy. Toward those ends, we have used reverse-phase protein lysate microarrays to evaluate expression of protein components of the nucleotide excision repair (NER) pathways. Those pathways strongly influence the anticancer activities of numerous drugs, including those that are the focus here, cisplatin and ecteinascidin 743 (Et-743; Yondelis, Trabectedin). Cisplatin is generally more active in cell types deficient in NER, whereas Et-743 tends to be less active in those cells. We measured protein expression and sensitivity to those drugs in 17 human ovarian and colon cancer cell lines (13 of them from the NCI-60 panel) and five xeroderma pigmentosum (XP) patient cell types, each containing a different NER defect. Of the NER proteins giving reliable signals, XPF and XPG showed the highest correlations of protein expression with drug activity across all three tissue-of-origin groups. When we compared protein expression data with mRNA expression data from Affymetrix U133A chips, we found no consistent correlation between the two across the cell lines studied, which reinforces the conclusion that protein measurements can give more interpretable mechanistic information than can transcript measurements. The work reported here provides motivation for larger proteomic studies with more cell types focused on potential biomarkers in additional pharmacologically pertinent pathways.

UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation

Global transcriptomic and proteomic profiling platforms have yielded important insights into the complex response to ionizing radiation (IR). Nonetheless, little is known about the ways in which small cellular metabolite concentrations change in response to IR. Here, a metabolomics approach using ultraperformance liquid chromatography coupled with electrospray time-of-flight mass spectrometry was used to profile, over time, the hydrophilic metabolome of TK6 cells exposed to IR doses ranging from 0.5 to 8.0 Gy. Multivariate data analysis of the positive ions revealed dose- and time-dependent clustering of the irradiated cells and identified certain constituents of the water-soluble metabolome as being significantly depleted as early as 1 h after IR. Tandem mass spectrometry was used to confirm metabolite identity. Many of the depleted metabolites are associated with oxidative stress and DNA repair pathways. Included are reduced glutathione, adenosine monophosphate, nicotinamide adenine dinucleotide, and spermine. Similar measurements were performed with a transformed fibroblast cell line, BJ, and it was found that a subset of the identified TK6 metabolites were effective in IR dose discrimination. The GEDI (Gene Expression Dynamics Inspector) algorithm, which is based on self-organizing maps, was used to visualize dynamic global changes in the TK6 metabolome that resulted from IR. It revealed dose-dependent clustering of ions sharing the same trends in concentration change across radiation doses. "Radiation metabolomics," the application of metabolomic analysis to the field of radiobiology, promises to increase our understanding of cellular responses to stressors such as radiation.

Nonclassic functions of human topoisomerase I: genome-wide and pharmacologic analyses

The biological functions of nuclear topoisomerase I (Top1) have been difficult to study because knocking out TOP1 is lethal in metazoans. To reveal the functions of human Top1, we have generated stable Top1 small interfering RNA (siRNA) cell lines from colon and breast carcinomas (HCT116-siTop1 and MCF-7-siTop1, respectively). In those clones, Top1 is reduced approximately 5-fold and Top2alpha compensates for Top1 deficiency. A prominent feature of the siTop1 cells is genomic instability, with chromosomal aberrations and histone gamma-H2AX foci associated with replication defects. siTop1 cells also show rDNA and nucleolar alterations and increased nuclear volume. Genome-wide transcription profiling revealed 55 genes with consistent changes in siTop1 cells. Among them, asparagine synthetase (ASNS) expression was reduced in siTop1 cells and in cells with transient Top1 down-regulation. Conversely, Top1 complementation increased ASNS, indicating a causal link between Top1 and ASNS expression. Correspondingly, pharmacologic profiling showed L-asparaginase hypersensitivity in the siTop1 cells. Resistance to camptothecin, indenoisoquinoline, aphidicolin, hydroxyurea, and staurosporine and hypersensitivity to etoposide and actinomycin D show that Top1, in addition to being the target of camptothecins, also regulates DNA replication, rDNA stability, and apoptosis. Overall, our studies show the pleiotropic nature of human Top1 activities. In addition to its classic DNA nicking-closing functions, Top1 plays critical nonclassic roles in genomic stability, gene-specific transcription, and response to various anticancer agents. The reported cell lines and approaches described in this article provide new tools to perform detailed functional analyses related to Top1 function.

Chromatin challenges during DNA replication: a systems representation

In a recent review, A. Groth and coworkers presented a comprehensive account of nucleosome disassembly in front of a DNA replication fork, assembly behind the replication fork, and the copying of epigenetic information onto the replicated chromatin. Understanding those processes however would be enhanced by a comprehensive graphical depiction analogous to a circuit diagram. Accordingly, we have constructed a molecular interaction map (MIM) that preserves in essentially complete detail the processes described by Groth et al. The MIM organizes and elucidates the information presented by Groth et al. on the complexities of chromatin replication, thereby providing a tool for system-level comprehension of the effects of genetic mutations, altered gene expression, and pharmacologic intervention.

A strategy for predicting the chemosensitivity of human cancers and its application to drug discovery

The U.S. National Cancer Institute has used a panel of 60 diverse human cancer cell lines (the NCI-60) to screen >100,000 chemical compounds for anticancer activity. However, not all important cancer types are included in the panel, nor are drug responses of the panel predictive of clinical efficacy in patients. We asked, therefore, whether it would be possible to extrapolate from that rich database (or analogous ones from other drug screens) to predict activity in cell types not included or, for that matter, clinical responses in patients with tumors. We address that challenge by developing and applying an algorithm we term "coexpression extrapolation" (COXEN). COXEN uses expression microarray data as a Rosetta Stone for translating from drug activities in the NCI-60 to drug activities in any other cell panel or set of clinical tumors. Here, we show that COXEN can accurately predict drug sensitivity of bladder cancer cell lines and clinical responses of breast cancer patients treated with commonly used chemotherapeutic drugs. Furthermore, we used COXEN for in silico screening of 45,545 compounds and identify an agent with activity against human bladder cancer.

AffyProbeMiner: a web resource for computing or retrieving accurately redefined Affymetrix probe sets

MOTIVATION

Affymetrix microarrays are widely used to measure global expression of mRNA transcripts. That technology is based on the concept of a probe set. Individual probes within a probe set were originally designated by Affymetrix to hybridize with the same unique mRNA transcript. Because of increasing accuracy in knowledge of genomic sequences, however, a substantial number of the manufacturer's original probe groupings and mappings are now known to be inaccurate and must be corrected. Otherwise, analysis and interpretation of an Affymetrix microarray experiment will be in error.

RESULTS

AffyProbeMiner is a computationally efficient platform-independent tool that uses all RefSeq mature RNA protein coding transcripts and validated complete coding sequences in GenBank to (1) regroup the individual probes into consistent probe sets and (2) remap the probe sets to the correct sets of mRNA transcripts. The individual probes are grouped into probe sets that are 'transcript-consistent' in that they hybridize to the same mRNA transcript (or transcripts) and, therefore, measure the same entity (or entities). About 65.6% of the probe sets on the HG-U133A chip were affected by the remapping. Pre-computed regrouped and remapped probe sets for many Affymetrix microarrays are made freely available at the AffyProbeMiner web site. Alternatively, we provide a web service that enables the user to perform the remapping for any type of short-oligo commercial or custom array that has an Affymetrix-format Chip Definition File (CDF). Important features that differentiate AffyProbeMiner from other approaches are flexibility in the handling of splice variants, computational efficiency, extensibility, customizability and user-friendliness of the interface.

AVAILABILITY

The web interface and software (GPL open source license), are publicly-accessible at http://discover.nci.nih.gov/affyprobeminer.

Signal pathway profiling of epithelial and stromal compartments of colonic carcinoma reveals epithelial-mesenchymal transition

Molecular crosstalk, including reciprocal stimulation, is theorized to take place between epithelial cancer cells and surrounding non-neoplastic stromal cells. This is the rationale for stromal therapy, which could eliminate support of a cancer by its genetically stable stroma. Epithelial-stromal crosstalk is so far poorly documented in vivo, and cell cultures and animal experiments may not provide accurate models. The current study details stromal-epithelial signalling pathways in 35 human colon cancers, and compares them with matched normal tissues using quantitative proteomic microarrays. Lysates prepared from separately microdissected epithelium and stroma were analysed using antibodies against 61 cell signalling proteins, most of which recognize activated phospho-isoforms. Analyses using unsupervised and supervised statistical methods suggest that cell signalling pathway profiles in stroma and epithelium appear more similar to each other in tumours than in normal colon. This supports the concept that coordinated crosstalk occurs between epithelium and stroma in cancer and suggests epithelial-mesenchymal transition. Furthermore, the data herein suggest that it is driven by cell proliferation pathways and that, specifically, several key molecules within the mitogen-activated protein kinase pathway may play an important role. Given recent findings of epithelial-mesenchymal transition in therapy-resistant tumour epithelium, these findings could have therapeutic implications for colon cancer.

Informed patient choice: patient-centered valuing of surgical risks and benefits

The risks and benefits of any health care intervention are valued differently by stakeholders. One of the ethical imperatives of patient-centered care is the balanced, evidence-based presentation of risks and benefits by providers to patients. Using the example of musculoskeletal surgery with devices, we advocate the use of shared decision-making tools and processes known to improve knowledge, adjust unrealistic expectations, and elicit values about benefits desired and the degree of acceptable risks for individual patients. We describe feasibility and efficacy within our organization and address ways to foster the further adoption of this approach.

MicroRNA expression profiles for the NCI-60 cancer cell panel

Advances in the understanding of cancer cell biology and response to drug treatment have benefited from new molecular technologies and methods for integrating information from multiple sources. The NCI-60, a panel of 60 diverse human cancer cell lines, has been used by the National Cancer Institute to screen >100,000 chemical compounds and natural product extracts for anticancer activity. The NCI-60 has also been profiled for mRNA and protein expression, mutational status, chromosomal aberrations, and DNA copy number, generating an unparalleled public resource for integrated chemogenomic studies. Recently, microRNAs have been shown to target particular sets of mRNAs, thereby preventing translation or accelerating mRNA turnover. To complement the existing NCI-60 data sets, we have measured expression levels of microRNAs in the NCI-60 and incorporated the resulting data into the CellMiner program package for integrative analysis. Cell line groupings based on microRNA expression were generally consistent with tissue type and with cell line clustering based on mRNA expression. However, mRNA expression seemed to be somewhat more informative for discriminating among tissue types than was microRNA expression. In addition, we found that there does not seem to be a significant correlation between microRNA expression patterns and those of known target transcripts. Comparison of microRNA expression patterns and compound potency patterns showed significant correlations, suggesting that microRNAs may play a role in chemoresistance. Combined with gene expression and other biological data using multivariate analysis, microRNA expression profiles may provide a critical link for understanding mechanisms involved in chemosensitivity and chemoresistance.