Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology

High-throughput biological assays such as microarrays let us ask very detailed questions about how diseases operate, and promise to let us personalize therapy. Data processing, however, is often not described well enough to allow for exact reproduction of the results, leading to exercises in "forensic bioinformatics" where aspects of raw data and reported results are used to infer what methods must have been employed. Unfortunately, poor documentation can shift from an inconvenience to an active danger when it obscures not just methods but errors. In this report we examine several related papers purporting to use microarray-based signatures of drug sensitivity derived from cell lines to predict patient response. Patients in clinical trials are currently being allocated to treatment arms on the basis of these results. However, we show in five case studies that the results incorporate several simple errors that may be putting patients at risk. One theme that emerges is that the most common errors are simple (e.g., row or column offsets); conversely, it is our experience that the most simple errors are common. We then discuss steps we are taking to avoid such errors in our own investigations.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS291 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Protein and phosphoprotein levels in glioma and adenocarcinoma cell lines grown in normoxia and hypoxia in monolayer and three-dimensional cultures

<p>Abstract</p> <p>Background</p> <p>Three dimensional (3D) growths of cancer cells in vitro are more reflective of in situ cancer cell growth than growth in monolayer (2D). The present study is designed to determine changes in protein and phosphoprotein that reflect adaptation of tumor cells to 3D as compared to 2D. Since relative hypoxia is a common feature of most solid tumors, the present study also aims to look at the impact of transition from normoxia to hypoxia in these two growth conditions.</p> <p>Results</p> <p>Using reverse-phase protein arrays, we compared levels of 121 different phosphorylated and non-phosphorylated proteins in 5 glioma and 6 adenocarcinoma lines under conditions of 3D and monolayer culture in normoxia and hypoxia. A three-way analysis of variance showed levels of 82 antibodies differed between media (2D vs. 3D) and 49 differed between treatments (hypoxia vs. normoxia). Comparing 2D to 3D growth, 7 proteins were commonly (i.e., > 50% of tumors) elevated in 3D: FAK, AKT, Src, GSK3αβ, TSC2, p38, and NFκβp65. Conversely, 7 other proteins are commonly decreased: ATRIP, ATR, β-catenin, BCL-X, cyclin B1, Egr-1, and HIF-1α. Comparing normoxia to hypoxia, only NCKIPSD was commonly elevated in hypoxia; 6 proteins were decreased: cyclin B1, 4EBP1(Ser65), c-Myc, SMAD3(Ser423), S6(Ser235), and S6(Ser240). Hypoxia affected glioma cell lines differently from adenocarcinoma cell lines: 8 proteins were increased in gliomas (BAX, caspase 7, HIF-1α, c-JUN, MEK1, PARP 1 cleaved, Src, and VEGFR2) and none in adenocarcinomas.</p> <p>Conclusions</p> <p>We identified subsets of proteins with clearly concordant/discordant behavior between gliomas and adenocarcinomas. In general, monolayer to 3D culture differences are clearer than normoxia to hypoxia differences, with anti-apoptotic, cytoskeletal rearrangement and cell survival pathways emphasized in the former and mTOR pathway, transcription, cell-cycle arrest modulation, and increased cell motility in the latter.</p

Overdispersed logistic regression for SAGE: Modelling multiple groups and covariates

BACKGROUND: Two major identifiable sources of variation in data derived from the Serial Analysis of Gene Expression (SAGE) are within-library sampling variability and between-library heterogeneity within a group. Most published methods for identifying differential expression focus on just the sampling variability. In recent work, the problem of assessing differential expression between two groups of SAGE libraries has been addressed by introducing a beta-binomial hierarchical model that explicitly deals with both of the above sources of variation. This model leads to a test statistic analogous to a weighted two-sample t-test. When the number of groups involved is more than two, however, a more general approach is needed. RESULTS: We describe how logistic regression with overdispersion supplies this generalization, carrying with it the framework for incorporating other covariates into the model as a byproduct. This approach has the advantage that logistic regression routines are available in several common statistical packages. CONCLUSIONS: The described method provides an easily implemented tool for analyzing SAGE data that correctly handles multiple types of variation and allows for more flexible modelling

Integrated MicroRNA-mRNA Profiling Identifies Oncostatin M as a Marker of Mesenchymal-Like ER-Negative/HER2-Negative Breast Cancer

MicroRNAs (miRNAs) simultaneously modulate different oncogenic networks, establishing a dynamic system of gene expression and pathway regulation. In this study, we analyzed global miRNA and messenger RNA (mRNA) expression profiles of 17 cell lines representing different molecular breast cancer subtypes. Spearman's rank correlation test was used to evaluate the correlation between miRNA and mRNA expression. Hierarchical clustering and pathway analysis were also performed. Publicly available gene expression profiles (n = 699) and tumor tissues (n = 80) were analyzed to assess the relevance of key miRNA-regulated pathways in human breast cancer. We identified 39 significantly deregulated miRNAs, and the integration between miRNA and mRNA data revealed the importance of immune-related pathways, particularly the Oncostatin M (OSM) signaling, associated with mesenchymal-like breast cancer cells. OSM levels correlated with genes involved in the inflammatory response, epithelial-to-mesenchymal transition (EMT), and epidermal growth factor (EGF) signaling in human estrogen receptor (ER)-negative/human epidermal growth factor receptor 2 (HER2)-negative breast cancer. Our results suggest that the deregulation of specific miRNAs may cooperatively impair immune and EMT pathways. The identification of the OSM inflammatory pathway as an important mediator of EMT in triple-negative breast cancer (TNBC) may provide a novel potential opportunity to improve therapeutic strategies

Gene expression signature of estrogen receptor α status in breast cancer

BACKGROUND: Estrogens are known to regulate the proliferation of breast cancer cells and to modify their phenotypic properties. Identification of estrogen-regulated genes in human breast tumors is an essential step toward understanding the molecular mechanisms of estrogen action in cancer. To this end we generated and compared the Serial Analysis of Gene Expression (SAGE) profiles of 26 human breast carcinomas based on their estrogen receptor α (ER) status. Thus, producing a breast cancer SAGE database of almost 2.5 million tags, representing over 50,000 transcripts. RESULTS: We identified 520 transcripts differentially expressed between ERα-positive (+) and ERα-negative (-) primary breast tumors (Fold change ≥ 2; p < 0.05). Furthermore, we identified 220 high-affinity Estrogen Responsive Elements (EREs) distributed on the promoter regions of 163 out of the 473 up-modulated genes in ERα (+) breast tumors. In brief, we observed predominantly up-regulation of cell growth related genes, DNA binding and transcription factor activity related genes based on Gene Ontology (GO) biological functional annotation. GO terms over-representation analysis showed a statistically significant enrichment of various transcript families including: metal ion binding related transcripts (p = 0.011), calcium ion binding related transcripts (p = 0.033) and steroid hormone receptor activity related transcripts (p = 0.031). SAGE data associated with ERα status was compared with reported information from breast cancer DNA microarrays studies. A significant proportion of ERα associated gene expression changes was validated by this cross-platform comparison. However, our SAGE study also identified novel sets of genes as highly expressed in ERα (+) invasive breast tumors not previously reported. These observations were further validated in an independent set of human breast tumors by means of real time RT-PCR. CONCLUSION: The integration of the breast cancer comparative transcriptome analysis based on ERα status coupled to the genome-wide identification of high-affinity EREs and GO over-representation analysis, provide useful information for validation and discovery of signaling networks related to estrogen response in this malignancy

Obtaining reliable information from minute amounts of RNA using cDNA microarrays

BACKGROUND: High density cDNA microarray technology provides a powerful tool to survey the activity of thousands of genes in normal and diseased cells, which helps us both to understand the molecular basis of the disease and to identify potential targets for therapeutic intervention. The promise of this technology has been hampered by the large amount of biological material required for the experiments (more than 50 μg of total RNA per array). We have modified an amplification procedure that requires only 1 μg of total RNA. Analyses of the results showed that most genes that were detected as expressed or differentially expressed using the regular protocol were also detected using the amplification protocol. In addition, many genes that were undetected or weakly detected using the regular protocol were clearly detected using the amplification protocol. We have carried out a series of confirmation studies by northern blotting, western blotting, and immunohistochemistry assays. RESULTS: Our results showed that most of the new information revealed by the amplification protocol represents real gene activity in the cells. CONCLUSION: We have confirmed a powerful and consistent cDNA microarray procedure that can be used to study minute amounts of biological tissue

Global analysis of aberrant pre-mRNA splicing in glioblastoma using exon expression arrays

<p>Abstract</p> <p>Background</p> <p>Tumor-predominant splice isoforms were identified during comparative <it>in silico </it>sequence analysis of EST clones, suggesting that global aberrant alternative pre-mRNA splicing may be an epigenetic phenomenon in cancer. We used an exon expression array to perform an objective, genome-wide survey of glioma-specific splicing in 24 GBM and 12 nontumor brain samples. Validation studies were performed using RT-PCR on glioma cell lines, patient tumor and nontumor brain samples.</p> <p>Results</p> <p>In total, we confirmed 14 genes with glioma-specific splicing; seven were novel events identified by the exon expression array (<it>A2BP1, BCAS1, CACNA1G, CLTA, KCNC2, SNCB</it>, and <it>TPD52L2</it>). Our data indicate that large changes (> 5-fold) in alternative splicing are infrequent in gliomagenesis (< 3% of interrogated RefSeq entries). The lack of splicing changes may derive from the small number of splicing factors observed to be aberrantly expressed.</p> <p>Conclusion</p> <p>While we observed some tumor-specific alternative splicing, the number of genes showing exclusive tumor-specific isoforms was on the order of tens, rather than the hundreds suggested previously by <it>in silico </it>mining. Given the important role of alternative splicing in neural differentiation, there may be selective pressure to maintain a majority of splicing events in order to retain glial-like characteristics of the tumor cells.</p