Robust interlaboratory reproducibility of a gene expression signature measurement consistent with the needs of a new generation of diagnostic tools

The increasing use of DNA microarrays in biomedical research, toxicogenomics, pharmaceutical development, and diagnostics has focused attention on the reproducibility and reliability of microarray measurements. While the reproducibility of microarray gene expression measurements has been the subject of several recent reports, there is still a need for systematic investigation into what factors most contribute to variability of measured expression levels observed among different laboratories and different experimenters.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

A gene expression profile for detection of sufficient tumour cells in breast tumour tissue: microarray diagnosis eligibility

<p>Abstract</p> <p>Background</p> <p>Microarray 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.</p> <p>Methods</p> <p>In 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.</p> <p>Results</p> <p>Supervised 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).</p> <p>Conclusion</p> <p>The 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.</p

Converting a breast cancer microarray signature into a high-throughput diagnostic test

BACKGROUND: A 70-gene tumor expression profile was established as a powerful predictor of disease outcome in young breast cancer patients. This profile, however, was generated on microarrays containing 25,000 60-mer oligonucleotides that are not designed for processing of many samples on a routine basis. RESULTS: To facilitate its use in a diagnostic setting, the 70-gene prognosis profile was translated into a customized microarray (MammaPrint) containing a reduced set of 1,900 probes suitable for high throughput processing. RNA of 162 patient samples from two previous studies was subjected to hybridization to this custom array to validate the prognostic value. Classification results obtained from the original analysis were then compared to those generated using the algorithms based on the custom microarray and showed an extremely high correlation of prognosis prediction between the original data and those generated using the custom mini-array (p < 0.0001). CONCLUSION: In this report we demonstrate for the first time that microarray technology can be used as a reliable diagnostic tool. The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is therefore an excellent tool to predict outcome of disease in breast cancer patients

Validation and Clinical Utility of a 70-Gene Prognostic Signature for Women With Node-Negative Breast Cancer

Background: A 70-gene signature was previously shown to have prognostic value in patients with node-negative breast cancer. Our goal was to validate the signature in an independent group of patients. Methods: Patients (n = 307, with 137 events after a median follow-up of 13.6 years) from five European centers were divided into high- and low-risk groups based on the gene signature classification and on clinical risk classifications. Patients were assigned to the gene signature low-risk group if their 5-year distant metastasis-free survival probability as estimated by the gene signature was greater than 90%. Patients were assigned to the clinicopathologic low-risk group if their 10-year survival probability, as estimated by Adjuvant! software, was greater than 88% (for estrogen receptor [ER]-positive patients) or 92% (for ER-negative patients). Hazard ratios (HRs) were estimated to compare time to distant metastases, disease-free survival, and overall survival in high- versus low-risk groups. Results: The 70-gene signature outperformed the clinicopathologic risk assessment in predicting all endpoints. For time to distant metastases, the gene signature yielded HR = 2.32 (95% confidence interval [CI] = 1.35 to 4.00) without adjustment for clinical risk and hazard ratios ranging from 2.13 to 2.15 after adjustment for various estimates of clinical risk; clinicopathologic risk using Adjuvant! software yielded an unadjusted HR = 1.68 (95% CI = 0.92 to 3.07). For overall survival, the gene signature yielded an unadjusted HR = 2.79 (95% CI = 1.60 to 4.87) and adjusted hazard ratios ranging from 2.63 to 2.89; clinicopathologic risk yielded an unadjusted HR = 1.67 (95% CI = 0.93 to 2.98). For patients in the gene signature high-risk group, 10-year overall survival was 0.69 for patients in both the low- and high-clinical risk groups; for patients in the gene signature low-risk group, the 10-year survival rates were 0.88 and 0.89, respectively. Conclusions: The 70-gene signature adds independent prognostic information to clinicopathologic risk assessment for patients with early breast cance

Intra- and inter-laboratory agreement of the FAM19A4/mir124-2 methylation test: results from an international study

BACKGROUND: HPV-based cervical screening detects women at an increased risk of cervical cancer and precancer. To differentiate among HPV-positive women those with (pre)cancer, triage testing is necessary. The detection of cancer-associated host-cell DNA methylation (FAM19A4 and hsa-mir124-2) in cervical samples has shown valuable as triage test. This multicenter study from 6 collaborating European laboratories and one reference laboratory was set out to determine the intra- and inter-laboratory agreement of FAM19A4/mir124-2 DNA methylation analysis utilizing the QIAsure Methylation Test. METHODS: Agreement analysis for the QIAsure Methylation Test was assessed on high-risk HPV-positive cervical specimens (n = 1680) both at the level of the assay and at the full workflow, including bisulfite conversion. RESULTS: Intra- and inter-laboratory assay agreement were 91.4% (534/584; 95% CI 88.9-93.5; κ = 0.82) and 92.5% (369/399; 95% CI 90.0-94.7; κ = 0.83), respectively. The inter-laboratory workflow (bisulfite conversion and assay combined) agreement was 90.0% (627/697; 95% CI 87.5%-92.0%; κ = 0.76). CONCLUSION: These data show that the QIAsure Methylation Test performs robust and reproducible in different laboratory contexts. These results support the use of the QIAsure Methylation Test for full molecular screening for cervical cancer, including primary HPV testing and triage testing by methylation analysis

Estrogen receptor splice variants as a potential source of false-positive estrogen receptor status in breast cancer diagnostics

It is well established that only estrogen receptor (ER)-positive tumors benefit from hormonal therapies. We hypothesized that a subgroup of breast cancer patients expresses estrogen receptor α (ERα), but fails to respond to hormonal therapy due to the expression of a non-functional receptor. We analyzed a series of 2,658 ERα-positive HER2-negative breast tumors for ERα and progesterone receptor (PR) status as determined by mRNA expression and for their molecular subtypes (Luminal type vs Basal type, assessed by BluePrint™ molecular subtyping assay). In addition, we assessed the recurrence risk (low vs high) using the 70-gene MammaPrint™ signature. We found that 55 out of 2,658 (2.1 %) tumors that are ERα positive by mRNA analysis also demonstrate a Basal molecular subtype, indicating that they lack expression of estrogen-responsive genes. These ERα-positive Basal-type tumors express significantly lower levels of both ERα and PR mRNA as compared to Luminal-type tumors (P < 0.0001) and almost invariably (94.5 %) have a high-risk MammaPrint™ profile. Twelve of the MammaPrint™ genes are directly ERα responsive, indicating that MammaPrint™ assesses ERα function in breast cancer without considering ERα mRNA levels. We find a relatively high expression of the dominant negative ERα splice variant ERΔ7 in ERα-positive Basal-type tumors as compared to ERα-positive Luminal-type tumors (P < 0.0001). Expression of the dominant negative ERα variant ERΔ7 provides a rationale as to why tumors are of the Basal molecular subtype while staining ERα positive by immunohistochemistry. These tumors may lack a functional response to estrogen and consequently may not respond to hormonal therapy. Our data indicate that such patients are of MammaPrint™ high recurrence risk and might benefit from adjuvant chemotherapy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-013-2648-1) contains supplementary material, which is available to authorized users