Development and Independent Validation of a Prognostic Assay for Stage II Colon Cancer using Formalin Fixed Paraffin Embedded Tissue_Training Set
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Peter Hey
PROVIDER: E-MTAB-863 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Publications
Development and independent validation of a prognostic assay for stage II colon cancer using formalin-fixed paraffin-embedded tissue.
Kennedy Richard D RD Bylesjo Max M Kerr Peter P Davison Timothy T Black Julie M JM Kay Elaine W EW Holt Robert J RJ Proutski Vitali V Ahdesmaki Miika M Farztdinov Vadim V Goffard Nicolas N Hey Peter P McDyer Fionnuala F Mulligan Karl K Mussen Julie J O'Brien Eamonn E Oliver Gavin G Walker Steven M SM Mulligan Jude M JM Wilson Claire C Winter Andreas A O'Donoghue Diarmuid D Mulcahy Hugh H O'Sullivan Jacintha J Sheahan Kieran K Hyland John J Dhir Rajiv R Bathe Oliver F OF Winqvist Ola O Manne Upender U Shanmugam Chandrakumar C Ramaswamy Sridhar S Leon Eduardo J EJ Smith William I WI McDermott Ultan U Wilson Richard H RH Longley Daniel D Marshall John J Cummins Robert R Sargent Daniel J DJ Johnston Patrick G PG Harkin D Paul DP
Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20111107 35
<h4>Purpose</h4>Current prognostic factors are poor at identifying patients at risk of disease recurrence after surgery for stage II colon cancer. Here we describe a DNA microarray-based prognostic assay using clinically relevant formalin-fixed paraffin-embedded (FFPE) samples.<h4>Patients and methods</h4>A gene signature was developed from a balanced set of 73 patients with recurrent disease (high risk) and 142 patients with no recurrence (low risk) within 5 years of surgery.<h4>Results</h4>The ...[more]
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Project description:Current prognostic factors are poor at identifying patients at risk of disease recurrence following surgery for stage II colon cancer. Here we describe a DNA microarray based prognostic assay using clinically relevant formalin fixed paraffin embedded (FFPE) samples.
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Project description:Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: We adapted and applied the previously-published COXEN algorithm to develop molecular predictors for therapeutic responses of patients' tumors based on expression signatures derived from the NCI-60 in vitro drug activities and genomic expression data. Genome-wide candidate biomarkers were first triaged by examining expression patterns of frozen and formalin-fixed paraffin embedded (FFPE) tissue samples. We then identify initial drug sensitivity biomarkers for carboplatin and paclitaxel, respectively. These biomarkers were further narrowed by examining concordant expression patterns between cell lines and a historical set of ovarian cancer patients. Multivariate predictors were obtained from the NCI-60 cell lines and refined using historical patient cohorts. To independent validate these molecular predictors, we performed genome-wide profiling on FFPE samples of 58 ovarian cancer patients obtained prior to adjuvant chemotherapy. Results: Carboplatin predictor significantly stratified platinum sensitive and resistant patients (p = 0.019) with sensitivity = 93%, specificity = 33%, PPV = 65%, and NPV = 78%. Paclitaxel predictor also significantly stratified patients' responses (p = 0.033) with sensitivity = 96%, specificity = 26%, PPV = 61%, and NPV = 86%. The combination predictor for platinum-taxane combination demonstrated a significant survival difference between the predicted responders and nonresponders with median survival of 12.9 months vs. 8.1 months (p = 0.045). Conclusions: COXEN predictors successfully stratified platinum resistance and taxane response in this retrospective cohort, especially based on their FFPE tumor samples. Accurate prediction of chemotherapeutic response, especially to platinum agents is highly clinically relevant and could alter primary management of ovarian cancer. Gene expression data from 58 stage III-IV ovarian cancer patients treated with Carboplatin and Taxol agents
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2019-01-31 | E-MTAB-6969 | biostudies-arrayexpress
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2011-09-14 | E-GEOD-31735 | biostudies-arrayexpress
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2010-06-09 | E-GEOD-19246 | biostudies-arrayexpress
Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer. 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.
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Project description:Alzheimer's disease (AD) is a devastating neurodegenerative disorder that threatens to reach epidemic proportions as our population ages. Although much research has examined molecular pathways associated with AD, relatively few studies have focused on critical early stages. Our prior microarray study correlated gene expression in human hippocampus with AD markers. Results suggested a new model of early-stage AD in which pathology spreads along myelinated axons, orchestrated by upregulated transcription and epigenetic factors related to growth and tumor suppression (Blalock et al., 2004). However, the microarray analyses were performed on RNA from fresh frozen hippocampal tissue blocks containing both gray and white matter, potentially obscuring region-specific changes. In the present study, we used laser capture microdissection to exclude major white matter tracts and selectively collect CA1 hippocampal gray matter from formalin-fixed, paraffin-embedded (FFPE) hippoc ampal sections of the same subjects assessed in our prior study. Microarray analyses of this gray matter-enriched tissue revealed many correlations similar to those seen in our prior study, particularly for neuron-related genes. Nonetheless, in the laser-captured tissue, we found a striking paucity of the AD-associated epigenetic and transcription factor genes that had been strongly overrepresented in the prior tissue block study. In addition, we identified novel pathway alterations that may have considerable mechanistic implications, including downregulation of genes stabilizing ryanodine receptor Ca2+ release and upregulation of vascular development genes. We conclude that FFPE tissue can be a reliable resource for microarray studies, that upregulation of growth-related epigenetic/ transcription factors with incipient AD is predominantly localized to white matter, further supporting our prior findings and model, and that alterations in vascular and ryanodine receptor-relat ed pathways in gray matter are closely associated with incipient AD. RNA was extracted using RecoverAll Total Nucleic Acid Isolation Kit for FFPE (Ambion) according to manufacturer’s instructions (3h incubation at 55 C followed by glass fiber filtration). This system has recently been shown to outperform other FFPE methods/ kits regarding yield of amplifiable RNA (Okello et al., 2010). Quality assessment of extracted material was performed with the Paradise Reagent Quality Assessment Kit (Molecular Devices), as well as via NanoDrop (Thermoscientific). All samples yielded sufficient genetic material (>50 ng) for subsequent reactions. 50 ng of extracted purified nucleic acid underwent RNA amplification using WT-Ovation FFPE System (NuGen) followed by FL-Ovation cDNA Biotin Module V2 (NuGen) for labeling and microarray (Affymetrix HGU133 v2) hybridization. All 30 microarrays (one per specimen) performed within acceptable limits (Scaling factor: 32.6 +/- 3.7; RawQ: 1.28 +/- 0.01; GapDH 3’:5’: 1.48 +/- 0.08; % present 35.4 +/- 1.5) and were not significantly different across treatment (p < 0.5 for all measures, 1-ANOVA). In general, these results indicate a smaller signal in laser captured FFPE samples than in prior fresh frozen samples (Scaling factor: 5.9 +/- 0.6; RawQ 2.7 +/- 0.04; GapDH 3’:5’: 3.65 +/- 0.55; % present: 44.6 +/- 1.1) with an increased scaling factor decreased RawQ and reduced % present all indicating reduced signal volume, while the smaller GapDH ratio suggests more degraded material- consistent with other reports of the dynamics of small FFPE sample results. Further, the % present call, while lower than found in fresh frozen tissue, is much greater than would be expected by chance (5%).This suggests that the extracted genetic material still contains a large amount of valid data. Probe sets were annotated, and transcriptional profiles were generated, using the MAS5 algorithm and annotation data sets (Affymetrix Expression Console v. 1.1; HGU133 annotation October, 2003) in order to facilitate comparison with prior work. Results were filtered for presence, redundancy, and annotation status and analyzed by Pearson’s test for correlation with each subject’s Mini-Mental Status Exam (MMSE) score and Neurofibrillary Tangle (NFT) counts. The false discovery rate (FDR) (Hochberg and Benjamini, 1990) was used to estimate the error of multiple testing’s contribution to False Positives and the DAVID suite of bioinformatic tools was used to identify transcriptional pathways using the ‘table cluster’ option.
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