Abstract
BackgroundMicroarray diagnostics of tumour samples is based on measurement of prognostic and/or predictive gene expression profiles. Typically, diagnostic profiles have been developed using bulk tumour samples with a sufficient amount of tumour cells (usually >50%). Consequentially, a diagnostic results depends on the minimal percentage of tumour cells within a sample. Currently, tumour cell percentage is assessed by conventional histopathological review. However, even for experienced pathologists, such scoring remains subjective and time consuming and can lead to ambiguous results.MethodsIn this study we investigated whether we could use transcriptional activity of a specific set of genes instead of histopathological review to identify samples with sufficient tumour cell content. Genome-wide gene expression measurements were used to develop a transcriptional gene profile that could accurately assess a sample's tumour cell percentage.ResultsSupervised analysis across 165 breast tumour samples resulted in the identification of a set of 13 genes which expression correlated with presence of tumour cells. The developed gene profile showed a high performance (AUC 0.92) for identification of samples that are suitable for microarray diagnostics. Validation on 238 additional breast tumour samples indicated a robust performance for correct classification with an overall accuracy of 91 percent and a kappa score of 0.63 (95%CI 0.47–0.73).ConclusionThe developed 13-gene profile provides an objective tool for assessment whether a breast cancer sample contains sufficient tumour cells for microarray diagnostics. It will improve the efficiency and throughput for diagnostic gene expression profiling as it no longer requires histopathological analysis for initial tumour percentage scoring. Such profile will also be very use useful for assessment of tumour cell percentage in biopsies where conventional histopathology is difficult, such as fine needle aspirates.
Highlights
Microarray diagnostics of tumour samples is based on measurement of prognostic and/or predictive gene expression profiles
A 3-fold cross validation (CV) method was used to identify a gene expression profile that showed a strong association with pathological tumour cell percentage (TCP)
Pathological tumour cell percentage related gene expression in breast cancer To determine the variation in histopathological tumour cell percentage scoring, H/E stained tumour sections were repeatably analysed in a period of six months by five different pathologists (Figure 1)
Summary
Microarray diagnostics of tumour samples is based on measurement of prognostic and/or predictive gene expression profiles. Microarray diagnostics of tumour specimens is based on gene expression measurement of a specific set of predictive or prognostic genes. Tumour stroma likely plays an important role in tumour development and metastasis [1,2,3], gene expression profiles are typically generated using tissue that contains sufficient amount of tumour cells, not stroma. Most prognostic gene profiles were originally identified using samples containing at least 50% tumour cells and are, likely based on gene expression of the neoplastic tissue in question. Even for experienced pathologists, histopathological tumour scoring remains subjective and time consuming and can lead to inconclusive results [6,7,8] and variable tumour cell percentage scoring. A tumour percentage scoring method based on tumour cell mRNA transcription levels would provide an additional method to more reliably determine tumour cell content in a reduced time frame
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