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

FAM19A4/miR124-2 methylation testing and HPV16/18 genotyping in HPV-positive women under the age of 30 years

INTRODUCTION: HSIL or CIN2/3 lesions in HPV-positive women <30 years have high spontaneous regression rates. To reduce overtreatment, biomarkers are needed to delineate advanced CIN lesions that require treatment. We analysed the FAM19A4/miR124-2 methylation test and HPV16/18 genotyping in HPV-positive women <30 years aiming to identify CIN2/3 lesions in need of treatment. METHODS: A European multicentre retrospective study was designed evaluating the FAM19A4/miR124-2 methylation test and HPV16/18 genotyping in cervical scrapes of 1,061 HPV-positive women aged 15-29 years (690 ≤CIN1, 166 CIN2 and 205 CIN3+). A subset of 62 CIN2 and 103 CIN3 were immunohistochemically characterized by HPV E4 expression, a marker for a productive HPV infection and p16ink4a and Ki-67, markers indicative for a transforming infection. CIN2/3 lesions with low HPV E4 expression and high p16ink4a/Ki-67 expression were considered as non-productive, transforming CIN, compatible with advanced CIN2/3 lesions in need of treatment. RESULTS: FAM19A4/miR124-2 methylation positivity increased significantly with CIN grade and age groups (<25, 25-29 and ≥30 years), while HPV16/18 positivity was comparable across age groups. FAM19A4/miR124-2 methylation positivity was HPV type independent. Methylation-positive CIN2/3 lesions had higher p16ink4a/Ki-67-immunoscores (p = 0.003) and expressed less HPV E4 (p = 0.033) compared with methylation-negative CIN2/3 lesions. These differences in HPV E4 and p16ink4a/Ki-67 expression were not found between HPV16/18-positive and non-16/18 HPV-positive lesions. CONCLUSIONS: Compared with HPV16/18 genotyping, the FAM19A4/miR124-2 methylation test detects non-productive, transforming CIN2/3 lesions with high specificity in women <30 years, providing clinicians supportive information about the need for treatment of CIN2/3 in young HPV-positive women

Are ATM mutations 7271T-->G and IVS10-6T-->G really high-risk breast cancer-susceptibility alleles?

Two mutations of the ATM gene were recently suggested to confer breast cancer risks similar to mutations of BRCA1 or BRCA2. Here, we set out to confirm these findings in 961 families with non-BRCA1/BRCA2 breast cancer from diverse geographical regions. We did not detect the ATM 7271T-->G mutation in any family. The ATM IVS10-6T-->G mutation was detected in eight families, which was similar to its frequency among population-matched control individuals (pooled Mantel-Haenszel odds ratio = 1.60; 95% confidence interval = 0.48 to 5.35; P = 0.44). Bayesian analysis of linkage in the ATM IVS10-6T-->G-positive families showed an overall posterior probability of causality for this mutation of 0.008. We conclude that the ATM IVS10-6T-->G mutation does not confer a significantly elevated breast cancer risk and that ATM 7271T-->G is a rare event in familial breast cance

FAM19A4/miR124-2 methylation in invasive cervical cancer: A retrospective cross-sectional worldwide study

Widespread adoption of primary human papillomavirus (HPV)-based screening has encouraged the search for a triage test which retains high sensitivity for the detection of cervical cancer and precancer, but increases specificity to avoid overtreatment. Methylation analysis of FAM19A4 and miR124-2 genes has shown promise for the triage of high-risk (hr) HPV-positive women. In our study, we assessed the consistency of FAM19A4/miR124-2 methylation analysis in the detection of cervical cancer in a series of 519 invasive cervical carcinomas (n = 314 cervical scrapes, n = 205 tissue specimens) from over 25 countries, using a quantitative methylation-specific PCR (qMSP)-based assay (QIAsure Methylation Test®). Positivity rates stratified per histotype, FIGO stage, hrHPV status, hrHPV genotype, sample type and geographical region were calculated. In total, 510 of the 519 cervical carcinomas (98.3%; 95% CI: 96.7–99.2) tested FAM19A4/miR124-2 methylation-positive. Test positivity was consistent across the different subgroups based on cervical cancer histotype, FIGO stage, hrHPV status, hrHPV genotype, sample type and geographical region. In conclusion, FAM19A4/miR124-2 methylation analysis detects nearly all cervical carcinomas, including rare histotypes and hrHPV-negative carcinomas. These results indicate that a negative FAM19A4/miR124-2 methylation assay result is likely to rule out the presence of cervical cancer

Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: a prospective community-based feasibility study (RASTER)

Background: A microarray-based 70-gene prognosis signature might improve the selection of patients with node-negative breast cancer for adjuvant systemic treatment. The main aims of this MicroarRAy PrognoSTics in Breast CancER (RASTER) study were to assess prospectively the feasibility of implementation of the 70-gene prognosis signature in community-based settings and its effect on adjuvant systemic treatment decisions when considered with treatment advice formulated from the Dutch Institute for Healthcare Improvement (CBO) and other guidelines. Methods: Between January, 2004 and December, 2006, 812 women aged under 61 years with primary breast carcinoma (clinical T1–4N0M0) were enrolled. Fresh tumour samples were collected in 16 hospitals in the Netherlands within 1 h after surgery. Clinicopathological factors were collected and microarray analysis was done with a custom-designed array chip that assessed the mRNA expression index of the 70 genes previously identified for the prognostic signature. Patients with a “good” signature were deemed to have a good prognosis and, therefore, could be spared adjuvant systemic treatment with its associated adverse effects, whereas patients with a “poor” signature were judged to have a poor prognosis and should be considered for adjuvant systemic treatment. Concordance between risk predicted by the prognosis signature and risk predicted by commonly used clinicopathological guidelines (ie, St Gallen guidelines, Nottingham Prognostic Index, and Adjuvant! Online) was assessed. Findings: Of 585 eligible patients, 158 patients were excluded because of sampling failure (n=128) and incorrect procedure (n=30). Prognosis signatures were assessed in 427 patients. The 70-gene prognosis signature identified 219 (51%) patients with good prognosis and 208 (49%) patients with poor prognosis. The Dutch CBO guidelines identified 184 patients (43%) with poor prognosis, which was discordant with those findings obtained with the prognosis signature in 128 (30%) patients. Oncologists recommended adjuvant treatment in 203 (48%) patients based on Dutch CBO guidelines, in 265 (62%) patients if the guidelines were used with the prognosis signature, and in 259 (61%) patients if Dutch CBO guidelines, prognosis signature, and patients' preferences for treatment were all taken into account. Adjuvant! Online guidelines identified more patients with poor prognosis than did the signature alone (294 [69%]), and discordance with the signature occurred in 160 (37%) patients. St Gallen guidelines identified 353 (83%) patients with poor prognosis with the signature and discordance in 168 (39%) patients. Nottingham Prognostic Index recorded 179 (42%) patients with poor prognosis with the signature and discordance in 117 (27%) patients. Interpretation: Use of the prognosis signature is feasible in Dutch community hospitals. Adjuvant systemic treatment was advised less often when the more restrictive Dutch CBO guidelines were used compared with that finally given after use of the prognosis signature. For the other guidelines assessed, less adjuvant chemotherapy would be given when the data based on prognosis signature alone are used, which might spare patients from adverse effects and confirms previous findings. Future studies should assess whether use of the prognosis signature could improve survival or equal survival while avoiding unnecessary adjuvant systemic treatment without affecting patients' survival, and further assess the factors that physicians use to recommend adjuvant systemic treatment