miR-9-5p Exerts a Dual Role in Cervical Cancer and Targets Transcription Factor TWIST1

Squamous cell carcinoma (SCC) and adenocarcinoma (AC) represent the major cervical cancer histotypes. Both histotypes are caused by infection with high-risk HPV (hrHPV) and are associated with deregulated microRNA expression. Histotype-dependent expression has been observed for miR-9-5p, showing increased expression in SCC and low expression in AC. Here, we studied the regulation and functionality of miR-9-5p in cervical SCCs and ACs using cervical tissue samples and hrHPV-containing cell lines. Expression and methylation analysis of cervical tissues revealed that low levels of miR-9-5p in ACs are linked to methylation of its precursor genes, particularly miR-9-1. Stratification of tissue samples and hrHPV-containing cell lines suggested that miR-9-5p depends on both histotype and hrHPV type, with higher expression in SCCs and HPV16-positive cells. MiR-9-5p promoted cell viability and anchorage independence in cervical cancer cell lines SiHa (SCC, HPV16) and CaSki (metastasized SCC, HPV16), while it played a tumor suppressive role in HeLa (AC, HPV18). TWIST1, a transcription factor involved in epithelial-to-mesenchymal transition (EMT), was established as a novel miR-9-5p target. Our results show that miR-9-5p plays a dual role in cervical cancer in a histotype- and hrHPV type-dependent manner. MiR-9-5p mediated silencing of TWIST1 suggests two distinct mechanisms towards EMT in cervical cancer

Complementarity between miRNA expression analysis and DNA methylation analysis in hrHPV-positive cervical scrapes for the detection of cervical disease

Cervical screening by high-risk HPV (hrHPV) testing requires additional risk stratification (triage), as most infections are transient and only a subset of hrHPV-positive women harbours clinically relevant disease. Molecular triage markers such as microRNAs (miRNAs) and DNA methylation markers are particularly promising, as they can be objectively tested directly on hrHPV-positive scrapes and cervicovaginal self-samples. Here, we evaluated the marker potential of 10 candidate miRNAs in 209 hrHPV-positive scrapes of women with underlying precancer (cervical intraepithelial neoplasia, grade 2–3 (CIN2-3)), cancer, or without disease (CIN0/1). A predictive miRNA classifier for CIN3 detection was built using logistic regression, which was compared to and combined with DNA methylation marker FAM19A4. Markers were correlated to histology parameters and hrHPV genotype. A miRNA classifier consisting of miR-149, miR-20a, and miR-93 achieved an area under the curve (AUC) of 0.834 for CIN3 detection, which was not significantly different to that of FAM19A4 methylation (AUC: 0.862, p = 0.591). Combining miRNA and methylation analysis demonstrated complementarity between both marker types (AUC: 0.939). While the miRNA classifier seemed more predictive for CIN2, FAM19A4 methylation was particularly high in HPV16-positive and histologically advanced CIN3, i.e. CIN3 with high lesion volume. The miRNA classifier, FAM19A4 methylation, and the miRNA/methylation combination were highest in cancer-associated scrapes. In conclusion, a panel of three miRNAs is discriminatory for CIN3 in hrHPV-positive scrapes and can complement DNA methylation analysis for the efficient detection of cervical disease. Combined analysis of the two marker types warrants further evaluation as triage strategy in hrHPV-based screening

FAM19A4/miR124-2 methylation analysis as a triage test for HPV-positive women: cross-sectional and longitudinal data from a Dutch screening cohort

Objectives: The aim was to evaluate the cross-sectional and long-term triage performance of FAM19A4/miR124-2 methylation analysis in human papillomavirus (HPV)-based cervical screening. Methods: We conducted a post hoc analysis within a Dutch population-based HPV-positive study cohort of women aged 30–60 years (n = 979). Cross-sectional cervical intraepithelial neoplasia (CIN) 3+ sensitivity, specificity, positive predictive value and negative predictive value as well as cumulative CIN3+ or cervical cancer risks after 9 and 14 years were compared for three baseline triage strategies: (1) cytology, (2) FAM19A4/miR124-2 methylation analysis and (3) combined FAM19A4/miR124-2 methylation with cytology. Results: CIN3+ sensitivity of FAM19A4/miR124-2 methylation analysis was similar to that of cytology (71.3% vs 76.0%, ratio 0.94, 95% CI 0.84 to 1.05), at a lower specificity (78.3% vs 87.0%, ratio 0.90, 95% CI 0.86 to 0.94). Combining FAM19A4/miR124-2 methylation analysis with cytology resulted in a CIN3+ sensitivity of 84.6% (95% CI 78.3 to 90.8) at a specificity of 69.6% (95% CI 66.5 to 72.7). Similar 9- and 14-year CIN3+ risks for baseline cytology-negative women and baseline FAM19A4/miR12

Validation of the FAM19A4/mir124-2 DNA methylation test for both lavage- and brush-based self-samples to detect cervical (pre)cancer in HPV-positive women

Objectives DNA methylation analysis of cancer-related genes is a promising tool for HPV-positive women to identify those with cervical (pre)cancer (CIN3+) in need of treatment. However, clinical performance of methylation markers can be influenced by the sample type utilized. We describe a multiplex quantitative methylation-specific PCR that targets FAM19A4 and mir124-2 loci, to detect CIN3+ using both HPV-positive lavage- and brush self-samples. Methods We determined methylation thresholds for clinical classification using HPV-positive training sets comprising lavage self-samples of 182 women (including 40 with CIN3+) and brush self-samples of 224 women (including 61 with CIN3+). Subsequently, independent HPV-positive validation sets of 389 lavage self-samples (including 78 with CIN3+), and 254 brush self-samples (including 72 with CIN3+) were tested using the preset thresholds. Furthermore, the clinical performance of combined methylation analysis and HPV16/18 genotyping was determined. Results Training set analysis revealed similar FAM19A4 and mir124-2 thresholds for both self-sample types to yield highest CIN3+ sensitivity at 70% specificity. Validation set analysis resulted in a CIN3+ sensitivity of 70.5% (95%CI: 60.4-80.6) at a specificity of 67.8% (95%CI: 62.7-73.0) for lavage self-samples, and a CIN3+ sensitivity of 69.4% (95%CI: 58.8-80.1) at a 76.4% (95%CI: 70.2-82.6) specificity for brush self-samples. In combination with HPV16/18 genotyping, CIN3+ sensitivity and specificity were 88.5% (95%CI: 81.4-95.6) and 46.0% (95%CI: 40.4-51.5) for lavage self-samples, and 84.7% (95%CI: 76.4-93.0) and 54.9% (95%CI: 47.7-62.2) for brush self-samples. Conclusions FAM19A4/mir124-2 methylation analysis performs equally well in HPV-positive la

FAM19A4 methylation analysis in self-samples compared with cervical scrapes for detecting cervical (pre)cancer in HPV-positive women

Background:High-risk human papillomavirus (hrHPV)-positive women require triage to identify those with cervical high-grade intraepithelial neoplasia and cancer (≥CIN3 (cervical intraepithelial neoplasia grade 3)). FAM19A4 methylation analysis, which detects advanced CIN and cancer, is applicable to different sample types. However, studies comparing the performance of FAM19A4 methylation analysis in hrHPV-positive self-samples and paired physician-taken scrapes are lacking.Methods:We compared the performance of FAM19A4 methylation analysis (and/or HPV16/18 genotyping) in self-samples and paired physician-taken scrapes for ≥CIN3 detection in hrHPV-positive women (n=450,18-66 years).Results:Overall FAM19A4 methylation levels betw

DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000