25 research outputs found

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

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    <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

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    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

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    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

    Direct bisulphite conversion of cervical samples for DNA methylation analysis

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    Sodium bisulphite conversion of DNA to separate methylated from unmethylated cytosines is a standard for methylation analysis. This study evaluated a direct cell conversion protocol on cervical samples as alternative to isolated genomic DNA as input. Clinician-collected cervical samples (n = 120) were subjected to a direct conversion protocol, or genomic DNA was isolated with a fixed amount used for subsequent bisulphite conversion. Converted samples were compared for ACTB control gene and methylation of FAM19A4 and miR124-2 genes using quantitative methylation-specific PCR (QIAsure Methylation Test). Direct conversion resulted in a high success rate, i.e., 119/120 (99.2%) samples reported a valid test result. ΔΔCq values of FAM19A4 and miR124-2 were significantly correlated between both protocols (Spearman Rho 0.708 and 0.763, respectively, all p-values = 0.000). Agreement between both the bisulphite protocols was demonstrated by Bland–Altman plots. A direct cell conversion protocol shows good technical and analytical performance and offers a streamlined workflow for methylation analysis

    The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1–3 positive lymph nodes in an independent validation study

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    International audienceThe 70-gene prognosis-signature has shown to be a valid prognostic tool in node-negative breast cancer. Although axillary lymph node status is considered to be one of the most important prognostic factors, still 25–30% of node-positive breast cancer patients will remain free of distant metastases, even without adjuvant systemic therapy. We therefore investigated whether the 70-gene prognosis-signature can accurately identify patients with 1–3 positive lymph nodes who have an excellent disease outcome. Frozen tumour samples from 241 patients with operable T1-3 breast cancer, and 1–3 positive axillary lymph nodes, with a median follow-up of 7.8 years, were selected from 2 institutes. Using a customized microarray, tumour samples were analysed for the 70-gene tumour expression signature. In addition, we reanalysed part of a previously described cohort ( = 106) with extended follow-up. The 10-year distant metastasis-free (DMFS) and breast cancer specific survival (BCSS) probabilities were 91% (SE 4%) and 96% (SE 2%), respectively for the good prognosis-signature group (99 patients), and 76% (SE 4%) and 76% (SE 4%), respectively for the poor prognosis-signature group (142 patients). The 70-gene signature was significantly superior to the traditional prognostic factors in predicting BCSS with a multivariate hazard ratio (HR) of 7.17 (95% CI 1.81 to 28.43;  = 0.005). The 70-gene prognosis-signature outperforms traditional prognostic factors in predicting disease outcome in patients with 1–3 positive nodes. Moreover, the signature can accurately identify patients with an excellent disease outcome in node-positive breast cancer, who may be safely spared adjuvant chemotherapy

    Impact of Collection Volume and DNA Extraction Method on the Detection of Biomarkers and HPV DNA in First-Void Urine

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    The potential of first-void (FV) urine as a non-invasive liquid biopsy for detection of human papillomavirus (HPV) DNA and other biomarkers has been increasingly recognized over the past decade. In this study, we investigated whether the volume of this initial urine stream has an impact on the analytical performance of biomarkers. In parallel, we evaluated different DNA extraction protocols and introduced an internal control in the urine preservative. Twenty-five women, diagnosed with high-risk HPV, provided three home-collected FV urine samples using three FV urine collection devices (Colli-Pee) with collector tubes that differ in volume (4, 10, 20 mL). Each collector tube was prefilled with Urine Conservation Medium spiked with phocine herpesvirus 1 (PhHV-1) DNA as internal control. Five different DNA extraction protocols were compared, followed by PCR for GAPDH and PhHV-1 (qPCR), HPV DNA, and HBB (HPV-Risk Assay), and ACTB (methylation-specific qPCR). Results showed limited effects of collection volume on human and HPV DNA endpoints. In contrast, significant variations in yield for human endpoints were observed for different DNA extraction methods (p < 0.05). Additionally, the potential of PhHV-1 as internal control to monitor FV urine collection, storage, and processing was demonstrated
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