Dataset Information

Single-Patient Molecular Testing with NanoString nCounter Data Using a Reference-Based Strategy for Batch Effect Correction.

ABSTRACT: A major weakness in many high-throughput genomic studies is the lack of consideration of a clinical environment where one patient at a time must be evaluated. We examined generalizable and platform-specific sources of variation from NanoString gene expression data on both ovarian cancer and Hodgkin lymphoma patients. A reference-based strategy, applicable to single-patient molecular testing is proposed for batch effect correction. The proposed protocol improved performance in an established Hodgkin lymphoma classifier, reducing batch-to-batch misclassification while retaining accuracy and precision. We suggest this strategy may facilitate development of NanoString and similar molecular assays by accelerating prospective validation and clinical uptake of relevant diagnostics.

SUBMITTER: Talhouk A

PROVIDER: S-EPMC4838303 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Single-Patient Molecular Testing with NanoString nCounter Data Using a Reference-Based Strategy for Batch Effect Correction.

Talhouk Aline A Kommoss Stefan S Mackenzie Robertson R Cheung Martin M Leung Samuel S Chiu Derek S DS Kalloger Steve E SE Huntsman David G DG Chen Stephanie S Intermaggio Maria M Gronwald Jacek J Chan Fong C FC Ramus Susan J SJ Steidl Christian C Scott David W DW Anglesio Michael S MS

PloS one 20160420 4

A major weakness in many high-throughput genomic studies is the lack of consideration of a clinical environment where one patient at a time must be evaluated. We examined generalizable and platform-specific sources of variation from NanoString gene expression data on both ovarian cancer and Hodgkin lymphoma patients. A reference-based strategy, applicable to single-patient molecular testing is proposed for batch effect correction. The proposed protocol improved performance in an established Hodg ...[more]

PMID: 27096160

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Project description:BackgroundWith the development of new drug combinations and targeted treatments for multiple types of cancer, the ability to stratify categories of patient populations and to develop companion diagnostics has become increasingly important. A panel of 325 RNA biomarkers was selected based on cancer-related biological processes of healthy cells and gene expression changes over time during nonmalignant epithelial cell organization. This "cancer in reverse" approach resulted in a panel of biomarkers relevant for at least 7 cancer types, providing gene expression profiles representing key cellular signaling pathways beyond mutations in "driver genes." Objective. To further investigate this biomarker panel, the objective of the current study is to (1) validate the assay reproducibility for the 325 RNA biomarkers and (2) compare gene expression profiles side by side using two technology platforms.Methods and resultsWe have mapped the 325 RNA transcripts and in a custom NanoString nCounter expression panel to be compared to all potential probe sets in the Affymetrix Human Genome U133 Plus 2.0. The experiments were conducted with 10 unique biological formalin-fixed paraffin-embedded (FFPE) breast tumor samples. Each site extracted RNA from four sections of 10-micron thick FFPE tissue over three different days by two different operators using an optimized standard operating procedure and quality control criteria. Samples were analyzed using mas5 in BioConductor and NanoStringNorm in R. Pearson correlation showed reproducibility between sites for all 60 samples with r = 0.995 for Affymetrix and r = 0.999 for NanoString. Correlation in multiple days and multiple users was for Affymetrix r = (0.962 - 0.999) and for NanoString r = (0.982 - 0.991).ConclusionThe 325 RNA biomarkers showed reproducibility in two technology platforms with moderate to high concordance. Future directions include performing clinical validation studies and generating rationale for patient selection in clinical trials using the technically validated assay.

Dataset Information

Single-Patient Molecular Testing with NanoString nCounter Data Using a Reference-Based Strategy for Batch Effect Correction.

Publications

Single-Patient Molecular Testing with NanoString nCounter Data Using a Reference-Based Strategy for Batch Effect Correction.

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