Molecular Diagnosis & Therapy

Developing a DNA Methylation Signature to Differentiate High-Grade Serous Ovarian Carcinomas from Benign Ovarian Tumors

Epithelial ovarian cancer (EOC) represents a significant health challenge, with high-grade serous ovarian cancer (HGSOC) being the most common subtype. Early detection is hindered by nonspecific symptoms, leading to late-stage diagnoses and poor survival rates. Biomarkers are crucial for early diagnosis and personalized treatment OBJECTIVE: Our goal was to develop a robust statistical procedure to identify a set of differentially methylated probes (DMPs) that would allow differentiation between HGSOC and benign ovarian tumors. Using the Infinium EPIC Methylation array, we analyzed the methylation profiles of 48 ovarian samples diagnosed with HGSOC, borderline ovarian tumors, or benign ovarian disease. Through a multi-step statistical procedure combining univariate and multivariate logistic regression models, we aimed to identify CpG sites of interest. We discovered 21 DMPs and developed a predictive model validated in two independent cohorts. Our model, using a distance-to-centroid approach, accurately distinguished between benign and malignant disease. This model can potentially be used in other types of sample material. Moreover, the strategy of the model development and validation can also be used in other disease contexts for diagnostic purposes.

Evaluation of the Oncomine Comprehensive Assay Plus NGS Panel and the OncoScan CNV Assay for Homologous Recombination Deficiency Detection

Testing for homologous recombination deficiency (HRD) as a biomarker in relation to poly (ADP-ribose) polymerase inhibitor (PARPi) treatment in ovarian cancer is done by sequencing of the BRCA1/2 genes and/or by assessing a genomic instability signature. Here we present data obtained with two different methods for genomic instability testing: the Oncomine™ Comprehensive Assay Plus (OCA Plus) NGS panel and the OncoScan CNV assay. The retrospective analytical study included 80 ovarian cancer samples of patients previously referred to clinical Myriad testing (reference cohort), and 50 ovarian cancer samples from patients collected as part of the Pelvic Mass study. OCA Plus NGS libraries were sequenced with the Ion S5™XL Sequencer and analyzed with the Ion Reporter™ Software v5.20 for calculation of the genomic instability metric (GIM). In addition, all samples were tested with the OncoScan CNV FFPE Assay and analyzed with a previously published R-algorithm for generation of an in-house genomic instability score (in-house GIS). The OCA Plus assay had a concordance to the reference of 89% on samples with a tumor fraction ≥ 30% (auto-calculated or via molecular estimation). A total of 15 samples in the reference cohort had a calculated tumor fraction  30% tumor. QC steps should include careful tumor content evaluation, and results on samples with < 30% tumor should not be reported.

Human Papillomavirus Type and Viral Load in Relation to Circulating Cell-Free Tumour HPV DNA Level and Survival in Cervical Cancer

Human papillomavirus (HPV) is the cause of most cervical cancers and is released as circulating cell-free tumour HPV DNA (ctHPV DNA) into circulation. Earlier studies have indicated that ctHPV DNA is a promising biomarker for analysing treatment response and for recurrence surveillance. However, factors influencing the release of ctHPV DNA, including HPV type and HPV viral load, have not been extensively studied and additional biomarkers for prognosis are needed. Therefore, here we analysed ctHPV DNA, HPV type and viral load in relation to each other and to progression-free survival in patients with locally advanced or advanced cervical cancer. Pre-treatment biopsies and blood samples were collected from patients diagnosed with cervical cancer (Federation of Gynecology and Obstetrics [FIGO] stage IB-IV). One hundred and seventeen patients with HPV-positive tumours were included. Human papillomavirus type-specific, droplet digital polymerase chain reaction (ddPCR) assays were used to analyse previously genotyped biopsies for the viral load. Pre-treatment plasma from 92/117 patients were available and analysed for ctHPV DNA and total cell-free DNA levels. Results were related to patient and tumour characteristics and progression-free survival. Patients were grouped based on HPV species where alpha-9-species (including HPV16) and alpha-7-species (including HPV 18) constituted the majority of cases. Cell-free tumour HPV DNA was found in 83/92 (90.2%) of pre-treatment plasma samples. Higher biopsy viral load was significantly related to a higher ctHPV DNA level. Higher stage and larger primary tumour size were also associated with higher ctHPV DNA level. Alpha-9 species, including HPV16, had a significantly higher viral load (16×), a higher ctHPV DNA level (17×), and a higher detection rate in plasma than alpha-7 species, including HPV18. Alpha-9 species also had significantly better progression-free survival than alpha-7 species. Additional factors leading to better progression-free survival included a lower stage, a lower total cell-free DNA level, a viral load in the 90th percentile and, in the high-risk cervical cancer group, a higher pre-treatment ctHPV DNA level. Cell-free tumour HPV DNA, HPV type and viral load are promising biomarkers in cervical cancer. The lower sensitivity for ctHPV DNA detection for alpha-7 species, including HPV18, needs to be considered in future studies on ctHPV DNA, especially if used as a marker for relapse during surveillance when ctHPV DNA levels are very low.

Leveraging Multi-omics to Disentangle the Complexity of Ovarian Cancer

Cell-Free HPV-DNA in Screening, Diagnosis, Prognosis, and Treatment Response Monitoring of Cervical Cancer

Persistent infection with high-risk human papillomavirus (HPV) is a significant factor in cervical cancer (CC) development. Although CC screening programs have reduced the incidence of this neoplasm, the number of deaths remains high, especially in developing countries: CC remains the fourth most common neoplasm in the female population globally. Currently, an HPV test has been replacing cytological analysis because it is a more sensitive screening method. However, the collection of gynecological material is still necessary, which can be a barrier to adherence to testing in the target population. Host cells presenting with a viral infection release fragments of their DNA into circulation, known as cell-free DNA (cfDNA); this allows detection through venous puncture, a routine procedure in clinical laboratories. Thus, the objective of this review was to evaluate the role of cfDNA of HPV (cfHPV-DNA) as an alternative tool for CC screening, diagnosis, prognosis, and treatment response monitoring. Furthermore, the development of sensitive methods, such as droplet digital PCR (ddPCR) and next-generation sequencing (NGS), have proven useful in identifying tumor markers for CC. The specificity of the primers, the size of the target DNA fragments, and variables such as sample type and volume, in addition to the cfDNA extraction kit used, can influence the results of cfHPV-DNA detection. Although the detection of cfHPV-DNA in plasma and serum of patients with CC is feasible, there were conflicting results regarding cfHPV-DNA detection in the blood circulation of patients with premalignant lesions. On the other hand, when CC is already established, the detection and quantification of cfHPV-DNA have shown potential as a biomarker for tumor staging, prognosis definition, and treatment response monitoring.

Is the Homologous Recombination Repair Mutation Defined by a 15-Gene Panel Associated with the Prognosis of Epithelial Ovarian Cancer?

There is no consensus regarding the specific genes included in the homologous recombination repair (HRR) gene panel for identifying the HRR deficiency (HRD) status and predicting the prognosis of epithelial ovarian cancer (EOC) patients. We aimed to explore a 15-gene panel involving the HRR pathway as a predictive prognostic indicator in Chinese patients newly diagnosed with EOC. We reviewed the previously published reports about different HRR gene panels and prespecified the 15-gene panel. The genetic testing results in a 15-gene panel from 308 EOC patients diagnosed between 2014 and 2022 from six centers were collected. The association of clinicopathologic characteristics, the use of poly (adenosine diphosphate-ribose) polymerase inhibitors (PARPis) and progression-free survival (PFS) with 15-gene panel HRR mutations (HRRm) status was assessed. 43.2% (133/308) of patients were determined to carry 144 deleterious HRRm, among which 68.1% (98/144) were germline mutations and 32.8% (101/308) were BRCA1/2 gene lethal mutations. The hazard ratio (HR) (95% confidence interval, CI) for PFS (HRRm v HRR wild type, HRRwt) using the 15-gene panel HRRm was 0.42 (0.28-0.64) at all stages and 0.42 (0.27-0.65) at stages IIIC-IV. However, a prognostic difference was observed only between the BRCA mutation group and the HRRwt group, not between the non-BRCA HRRm group and the HRRwt group. For the subgroups of patients not using PARPis, the HR (95% CI) was 0.41 (0.24-0.68) at stages IIIC-IV. This study provides evidence that 15-gene panel HRRm can predict the prognosis of EOC, of these only the BRCA1/2 mutations, not non-BRCA HRRm, contribute to prognosis prediction. Among patients without PARPis, the HRRm group presented a better PFS. This is the first study of this kind in the Chinese population.

Prognostic Biomarker-Based Identification of Drugs for Managing the Treatment of Endometrial Cancer

Uterine corpus endometrial carcinoma (UCEC) causes thousands of deaths per year. To improve the overall survival of patients with UCEC, there is a need to identify prognostic biomarkers and potential drugs. The aim of this study was twofold: the identification of prognostic gene signatures from expression profiles of pattern recognition receptor (PRR) genes and identification of the most effective existing drugs using the prognostic gene signature. This study was based on the expression profile of PRR genes of 541 patients with UCEC obtained from The Cancer Genome Atlas. Key prognostic signatures were identified using various approaches, including survival analysis, network, and clustering. Hub genes were identified by constructing a co-expression network. Representative genes were identified using k-means and k-medoids-based clustering. Univariate Cox proportional hazard (PH) analysis was used to identify survival-associated genes. 'cmap2' was used to identify potential drugs that can suppress/enhance the expression of prognostic genes. Models were developed using hub genes and achieved a maximum hazard ratio (HR) of 1.37 (p = 0.294). Then, a clustering-based model was developed using seven genes (HR 9.14; p = 1.49 × 10 We identified potential immunotherapeutic agents based on prognostic gene signature: hexamethonium bromide and isoflupredone. Several novel candidate drugs were suggested, including human interferon-α-2b, paclitaxel, imiquimod, MESO-DAP1, and mifamurtide. These biomolecules and repurposed drugs may be utilised for prognosis and treatment for better survival.

Hyperactivating p53 in Human Papillomavirus-Driven Cancers: A Potential Therapeutic Intervention

Despite a vaccine being available, human papillomavirus virus (HPV)-driven cancers remain the ninth most prevalent cancers globally. Current therapies have significant drawbacks and often still lead to poor prognosis and underwhelming survival rates. With gene therapy becoming more available in the clinic, it poses a new front for therapeutic development. A characteristic of HPV-driven cancers is the ability to encode oncoproteins that aberrate normal p53 function without mutating this tumour-suppressor gene. The HPV E6 oncoprotein degrades p53 to allow the HPV-driven carcinogenic process to proceed. This review aimed to investigate the use of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) gene-editing technology and how it may be used to overcome HPV-mediated silencing of p53 by hyper-expressing the p53 promoter. Increasing p53 bioavailability may have promising potential as a therapy and has been a goal in the context of HPV-driven cancers. Clinical trials and proof-of-concept pre-clinical work have shown positive outcomes and tumour death when p53 levels are increased. Despite previous successes of RNA-based medicines, including the knockout of HPV oncogenes, the use of CRISPR activation is yet to be investigated as a promising potential therapy. This short review summarises key developments on attempts that have been made to increase p53 expression in the context of HPV cancer therapy, but leaves open the possibility for other cancers bearing a p53 wild-type gene.

Somatic mRNA Analysis of BRCA1 Splice Variants Provides a Direct Theranostic Impact on PARP Inhibitors

The identification of pretherapeutic somatic BRCA variants can have considerable clinical impact given that they affect response to the new poly (ADP-ribose) polymerase (PARP)-targeted therapy. One major issue with this type of testing is the identification of splicing variants of uncertain significance (VUS) on degraded somatic messenger RNA. It is therefore important to be able to quickly characterize these splice variants. As part of PARP inhibitor targeted therapy, we have investigated a method for the direct confirmation of potential pathogenic somatic splice variants of BRCA1 found in fixed tumor samples. Previously these VUS have commonly only been tested by in silico analysis. Five BRCA1 variants affecting splicing were characterized from formalin-fixed, paraffin-embedded (FFPE) ovarian carcinoma tissues by next-generation sequencing (NGS). Three patient samples had already been functionally characterized and were used as controls. Total somatic RNA from samples was extracted, reverse-transcribed, and amplified with several primer pairs encompassing the target exon. The polymerase chain reaction (PCR) products were analyzed by capillary gel electrophoresis to assess possible changes in size due to splicing alterations. Finally, we confirmed our results by cloning, followed by Sanger sequencing, and analyzed the expression of the aberrant forms. Our molecular approach made it possible to visualize the splicing outcomes of three variants (c.5194-2A>G, c.5434C>G, and c.547+1G>A) already identified and present in databases and/or identified with prediction tools (ClinVar, UMD, ARUP Utah database, and Human Splice Finder splices sites prediction) and to confirm their exon skipping consequences, their expression in tumors, and thus their pathogenicity. The c.4484+5G>A variant was not found in databases and was predicted to have no impact on splicing, but was found to display altered processing in tumor tissue. This variant also had a major detrimental impact on transcriptional expression. In a break from purely in silico approaches, we propose a simple and rapid pretherapeutic functional analysis of somatic BRCA1 variants potentially involved in splicing alterations. This approach will allow more ovarian cancer patients to benefit from new therapies targeting PARP.

Diagnostic Performance of the ASCL1/ZNF582 Methylation Test for Detection of High-Grade Vulvar Intraepithelial Neoplasia and Vulvar Cancer

High-grade vulvar intraepithelial neoplasia (VIN), the precursor lesion to vulvar cancer, comprises human papillomavirus (HPV)-associated high-grade squamous intraepithelial lesion (HSIL) and HPV-independent VIN (HPVi-VIN), differing in pathogenesis and cancer risk. HSIL typically develops from low-grade squamous intraepithelial lesion (LSIL), and HPVi-VIN from lichen sclerosus (LS). The PreCursor-M AnoGYN Methylation test, targeting ASCL1/ZNF582, may improve diagnostic accuracy and risk stratification in high-grade VIN patients. This study assessed its diagnostic performance to detect high-grade VIN and cancer. ASCL1/ZNF582 methylation was analyzed in 170 vulvar formalin-fixed paraffin-embedded (FFPE) tissue samples from healthy controls, LS, LSIL, HSIL, HPVi-VIN and vulvar cancer patients by quantitative methylation-specific polymerase chain reaction (qMSP). Logistic regression analysis was used to evaluate its diagnostic performance and compare it to the previously established ZNF582/SST/miR124-2 marker panel. Methylation levels increased with disease severity, from low in controls, LS and LSIL to high in HSIL, HPVi-VIN and vulvar cancer. The ASCL1/ZNF582 marker panel detected 92% and 84% of HSIL at 70% and 80% specificity, respectively, and 96% of HPVi-VIN and 100% of vulvar cancer at both specificities. Both marker panels (ASCL1/ZNF582 and ZNF582/SST/miR124-2) showed comparable excellent diagnostic performance for high-grade VIN detection, with an area under the curve (AUC) of 0.93 (95% confidence interval [CI] 0.88-0.98) and AUC 0.91 (95% CI 0.86-0.97), respectively. In conclusion, the ASCL1/ZNF582 methylation assay accurately detects high-grade VIN and vulvar cancer, while minimizing the detection of benign and low-grade lesions, indicating its clinical value.