Comprehensive diagnostics of acute myeloid leukemia by whole transcriptome RNA sequencing.

Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform.

Cervical cancer detection by DNA methylation analysis in urine.

Urine samples provide a potential alternative to physician-taken or self-collected cervical samples for cervical screening. Screening by primary hrHPV testing requires additional risk assessment (so-called triage) of hrHPV-positive women. Molecular markers, such as DNA methylation, have proven most valuable for triage when applied to cervical specimens. This study was set out to compare hrHPV and DNA methylation results in paired urine and cervical scrapes, and to evaluate the feasibility of DNA methylation analysis in urine to detect cervical cancer. Urine samples (n = 41; native and sediment) and paired cervical scrapes (n = 38) from cervical cancer patients, and urine from 44 female controls, were tested for hrHPV and 6 methylation markers. Results on native urine and sediment were highly comparable. A strong agreement was found between hrHPV testing on urine and scrapes (kappa = 0.79). Also, methylation levels in urine were moderately to strongly correlated to those detected in scrapes (r = 0.508-0.717). All markers were significantly increased in urine from cervical cancer patients compared to controls and showed a good discriminatory power for cervical cancer (AUC = 0.744-0.887). Our results show a good agreement of urine-based molecular analysis with reference cervical samples, and suggest that urine-based DNA methylation testing may provide a promising strategy for cervical cancer detection.

Genome-wide microRNA analysis of HPV-positive self-samples yields novel triage markers for early detection of cervical cancer.

Offering self-sampling for HPV testing improves the effectiveness of current cervical screening programs by increasing population coverage. Molecular markers directly applicable on self-samples are needed to stratify HPV-positive women at risk of cervical cancer (so-called triage) and to avoid over-referral and overtreatment. Deregulated microRNAs (miRNAs) have been implicated in the development of cervical cancer, and represent potential triage markers. However, it is unknown whether deregulated miRNA expression is reflected in self-samples. Our study is the first to establish genome-wide miRNA profiles in HPV-positive self-samples to identify miRNAs that can predict the presence of CIN3 and cervical cancer in self-samples. Small RNA sequencing (sRNA-Seq) was conducted to determine genome-wide miRNA expression profiles in 74 HPV-positive self-samples of women with and without cervical precancer (CIN3). The optimal miRNA marker panel for CIN3 detection was determined by GRridge, a penalized method on logistic regression. Six miRNAs were validated by qPCR in 191 independent HPV-positive self-samples. Classification of sRNA-Seq data yielded a 9-miRNA marker panel with a combined area under the curve (AUC) of 0.89 for CIN3 detection. Validation by qPCR resulted in a combined AUC of 0.78 for CIN3+ detection. Our study shows that deregulated miRNA expression associated with CIN3 and cervical cancer development can be detected by sRNA-Seq in HPV-positive self-samples. Validation by qPCR indicates that miRNA expression analysis offers a promising novel molecular triage strategy for CIN3 and cervical cancer detection applicable to self-samples.

Detection of hypermethylated genes as markers for cervical screening in women living with HIV.

INTRODUCTION: To evaluate the performance of hypermethylation analysis of ASCL1, LHX8 and ST6GALNAC5 in physician-taken cervical scrapes for detection of cervical cancer and cervical intraepithelial neoplasia (CIN) grade 3 in women living with HIV (WLHIV) in South Africa. METHODS: Samples from a prospective observational cohort study were used for these analyses. Two cohorts were included: a cohort of WLHIV who were invited for cervical screening (n = 321) and a gynaecologic outpatient cohort of women referred for evaluation of abnormal cytology or biopsy proven cervical cancer (n = 108, 60% HIV seropositive). Cervical scrapes collected from all subjects were analysed for hypermethylation of ASCL1, LHX8 and ST6GALNAC5 by multiplex quantitative methylation specific PCR (qMSP). Histology endpoints were available for all study subjects. RESULTS: Hypermethylation levels of ASCL1, LHX8 and ST6GALNAC5 increased with severity of cervical disease. The performance for detection of CIN3 or worse (CIN3+ ) as assessed by the area under the receiver operating characteristic (ROC) curves (AUC) was good for ASCL1 and LHX8 (AUC 0.79 and 0.81 respectively), and moderate for ST6GALNAC5 (AUC 0.71). At a threshold corresponding to 75% specificity, CIN3+ sensitivity was 72.1% for ASCL1 and 73.8% for LHX8 and all samples from women with cervical cancer scored positive for these two markers. CONCLUSIONS: Hypermethylation analysis of ASCL1 or LHX8 in cervical scrape material of WLHIV detects all cervical carcinomas with an acceptable sensitivity and good specificity for CIN3+ , warranting further exploration of these methylation markers as a stand-alone test for cervical screening in low-resource settings.

Host-cell DNA methylation patterns during high-risk HPV-induced carcinogenesis reveal a heterogeneous nature of cervical pre-cancer.

Cervical cancer development following a persistent infection with high-risk human papillomavirus (hrHPV) is driven by additional host-cell changes, such as altered DNA methylation. In previous studies, we have identified 12 methylated host genes associated with cervical cancer and pre-cancer (CIN2/3). This study systematically analyzed the onset and DNA methylation pattern of these genes during hrHPV-induced carcinogenesis using a longitudinal in vitro model of hrHPV-transformed cell lines (n = 14) and hrHPV-positive cervical scrapings (n = 113) covering various stages of cervical carcinogenesis. DNA methylation analysis was performed by quantitative methylation-specific PCR (qMSP) and relative qMSP values were used to analyze the data. The majority of genes displayed a comparable DNA methylation pattern in both cell lines and clinical specimens. DNA methylation onset occurred at early or late immortal passage, and DNA methylation levels gradually increased towards tumorigenic cells. Subsequently, we defined a so-called cancer-like methylation-high pattern based on the DNA methylation levels observed in cervical scrapings from women with cervical cancer. This cancer-like methylation-high pattern was observed in 72% (38/53) of CIN3 and 55% (11/20) of CIN2, whereas it was virtually absent in hrHPV-positive controls (1/26). In conclusion, hrHPV-induced carcinogenesis is characterized by early onset of DNA methylation, typically occurring at the pre-tumorigenic stage and with highest DNA methylation levels at the cancer stage. Host-cell DNA methylation patterns in cervical scrapings from women with CIN2 and CIN3 are heterogeneous, with a subset displaying a cancer-like methylation-high pattern, suggestive for a higher cancer risk.

Identification and Validation of a 3-Gene Methylation Classifier for HPV-Based Cervical Screening on Self-Samples.

Purpose: Offering self-sampling of cervico-vaginal material for high-risk human papillomavirus (hrHPV) testing is an effective method to increase the coverage in cervical screening programs. Molecular triage directly on hrHPV-positive self-samples for colposcopy referral opens the way to full molecular cervical screening. Here, we set out to identify a DNA methylation classifier for detection of cervical precancer (CIN3) and cancer, applicable to lavage and brush self-samples.Experimental Design: We determined genome-wide DNA methylation profiles of 72 hrHPV-positive self-samples, using the Infinium Methylation 450K Array. The selected DNA methylation markers were evaluated by multiplex quantitative methylation-specific PCR (qMSP) in both hrHPV-positive lavage (n = 245) and brush (n = 246) self-samples from screening cohorts. Subsequently, logistic regression analysis was performed to build a DNA methylation classifier for CIN3 detection applicable to self-samples of both devices. For validation, an independent set of hrHPV-positive lavage (n = 199) and brush (n = 287) self-samples was analyzed.Results: Genome-wide DNA methylation profiling revealed 12 DNA methylation markers for CIN3 detection. Multiplex qMSP analysis of these markers in large series of lavage and brush self-samples yielded a 3-gene methylation classifier (ASCL1, LHX8, and ST6GALNAC5). This classifier showed a very good clinical performance for CIN3 detection in both lavage (AUC = 0.88; sensitivity = 74%; specificity = 79%) and brush (AUC = 0.90; sensitivity = 88%; specificity = 81%) self-samples in the validation set. Importantly, all self-samples from women with cervical cancer scored DNA methylation-positive.Conclusions: By genome-wide DNA methylation profiling on self-samples, we identified a highly effective 3-gene methylation classifier for direct triage on hrHPV-positive self-samples, which is superior to currently available methods. Clin Cancer Res; 24(14); 3456-64. ©2018 AACR.

Genome-wide DNA Methylation Profiling Reveals Methylation Markers Associated with 3q Gain for Detection of Cervical Precancer and Cancer.

Purpose: Epigenetic host cell changes involved in cervical cancer development following a persistent high-risk human papillomavirus (hrHPV) infection, provide promising markers for the management of hrHPV-positive women. In particular, markers based on DNA methylation of tumor suppressor gene promoters are valuable. These markers ideally identify hrHPV-positive women with precancer (CIN2/3) in need of treatment. Here, we set out to identify biologically relevant methylation markers by genome-wide methylation analysis of both hrHPV-transformed cell lines and cervical tissue specimens.Experimental Design and Results: Genome-wide discovery by next-generation sequencing (NGS) of methyl-binding domain-enriched DNA (MBD-Seq) yielded 20 candidate methylation target genes. Further verification and validation by multiplex-targeted bisulfite NGS and (quantitative) methylation-specific PCR (MSP) resulted in 3 genes (GHSR, SST, and ZIC1) that showed a significant increase in methylation with severity of disease in both tissue specimens and cervical scrapes (P < 0.005). The area under the ROC curve for CIN3 or worse varied between 0.86 and 0.89. Within the group of CIN2/3, methylation levels of all 3 genes increased with duration of lesion existence (P < 0.0005), characterized by duration of preceding hrHPV infection, and were significantly higher in the presence of a 3q gain (P < 0.05) in the corresponding tissue biopsy.Conclusions: By unbiased genome-wide DNA methylation profiling and comprehensive stepwise verification and validation studies using in vitro and patient-derived samples, we identified 3 promising methylation markers (GHSR, SST, and ZIC1) associated with a 3q gain for the detection of cervical (pre)cancer. Clin Cancer Res; 23(14); 3813-22. ©2017 AACR.

Better prediction by use of co-data: adaptive group-regularized ridge regression.

For many high-dimensional studies, additional information on the variables, like (genomic) annotation or external p-values, is available. In the context of binary and continuous prediction, we develop a method for adaptive group-regularized (logistic) ridge regression, which makes structural use of such 'co-data'. Here, 'groups' refer to a partition of the variables according to the co-data. We derive empirical Bayes estimates of group-specific penalties, which possess several nice properties: (i) They are analytical. (ii) They adapt to the informativeness of the co-data for the data at hand. (iii) Only one global penalty parameter requires tuning by cross-validation. In addition, the method allows use of multiple types of co-data at little extra computational effort. We show that the group-specific penalties may lead to a larger distinction between 'near-zero' and relatively large regression parameters, which facilitates post hoc variable selection. The method, termed GRridge, is implemented in an easy-to-use R-package. It is demonstrated on two cancer genomics studies, which both concern the discrimination of precancerous cervical lesions from normal cervix tissues using methylation microarray data. For both examples, GRridge clearly improves the predictive performances of ordinary logistic ridge regression and the group lasso. In addition, we show that for the second study, the relatively good predictive performance is maintained when selecting only 42 variables.

Somatic mutation in PIK3CA is a late event in cervical carcinogenesis.

Somatic mutations in cervical intraepithelial neoplasia (CIN) are largely unknown. Here, we profiled 35 cervical carcinomas and 23 CIN grade 2/3 (CIN2/3) for mutations in 48 cancer-related genes using a Next Generation Sequencing-based cancer panel. PIK3CA exon 9 was the most frequently mutated locus in cervical carcinoma and the only mutated locus detected in CIN2/3. These PIK3CA exon 9 mutation findings were verified in a large, independent series (n = 647) covering all stages of cervical carcinogenesis using high resolution melting-guided Sanger sequencing. PIK3CA exon 9 mutation frequency was 37.1% (13/35; 95%CI 21.2-54.0%) in cervical carcinoma, and 2.4% (5/209; 95%CI 0.5-4.7%) in CIN3. No PIK3CA exon 9 mutations were detected in CIN2 (0/144), CIN1 (0/154) and normal cervix (0/105). In a third series of 46 CIN2/3 lesions from women with a known 5-year history of preceding high-risk human papillomavirus (hrHPV) infection, detection of PIK3CA exon 9 mutation was confined to 2 (5.4%; 95%CI 0.0-13.2%) CIN3 lesions with preceding hrHPV infection ≥5 years, and was absent in those with a short duration (<5 years) of preceding hrHPV infection. In conclusion, somatic mutation in PIK3CA represents a late event during cervical carcinogenesis, detected in a substantial subset of cervical carcinoma, but only in a minority of CIN3.

Methylation-mediated transcriptional repression of microRNAs during cervical carcinogenesis.

Deregulated expression of microRNAs (miRNAs) is common and biologically relevant in cervical carcinogenesis and appears only partly related to chromosomal changes. We recently identified 32 miRNAs showing decreased expression in high-grade cervical intraepithelial neoplasia (CIN) and carcinomas not associated with a chromosomal loss, 6 of which were located within a CpG island. This study aimed to investigate to what extent these miRNAs are subject to DNA methylation-mediated transcriptional repression in cervical carcinogenesis.   Methylation-specific PCR (MSP) analysis on a cell line panel representing different stages of human papillomavirus (HPV) induced transformation revealed an increase in methylation of hsa-miR-149, -203 and -375 with progression to malignancy, whereas expression of these miRNAs was restored upon treatment with a demethylating agent. All three miRNAs showed significantly increased levels of methylation in cervical carcinomas, whereas methylation levels of hsa-miR-203 and -375 were also significantly increased in high-grade CIN. A pilot analysis showed that increased hsa-miR-203 methylation was also detectable in HPV-positive cervical scrapes of women with high-grade CIN compared with controls. Similar to recent findings on hsa-miR-375, ectopic expression of hsa-miR-203 in cervical cancer cells decreased both the proliferation rate and anchorage independent growth. We found evidence for methylation-mediated transcriptional repression of hsa-miR-149, -203 and -375 in cervical cancer. Methylation of the latter two was already apparent in precancerous lesions and represent functionally relevant events in HPV-mediated transformation. Increased hsa-miR-203 methylation was detectable in scrapes of women with high-grade CIN, indicating that methylated miRNAs may provide putative markers to assess the presence of (pre)cancerous lesions.