Familial Cervical Cancer: Case Reports, Review and Clinical Implications

We report three Dutch families with familial clustering of (pre)neoplastic cervical disease, review the literature on familial risks of cervical intraepithelial neoplasia (CIN) and cervical cancer, and discuss possible practical guidelines for women with a family history of cervical cancer. Daughters and sisters of women with cervical cancer have been reported to have a relative risk of 1.5-2.3 to develop this type of cancer. From a practical clinical point of view, we suggest that as in women with an increased non-genetic risk to develop cervical cancer (e.g. because of immunosuppressive therapy) increased surveillance to detect this tumour should be considered in women with an increased risk based on family history. Cessation of smoking should be advised. As the use of condoms at least prevents HPV re-infection its use can be recommended as a way to lower the cervical cancer risk. Future studies to determine the genetic contribution to the development of cervical cancer should include the paternal family history of cancer and, because genetic predisposition might express itself as a higher risk to develop precursors of cervical cancer, carcinoma in situ and CIN grade II-III

Genome-wide methylome analysis using MethylCap-seq uncovers 4 hypermethylated markers with high sensitivity for both adeno- and squamous-cell cervical carcinoma

Background: Cytology-based screening methods for cervical adenocarcinoma (ADC) and to a lesser extent squamous-cell carcinoma (SCC) suffer from low sensitivity. DNA hypermethylation analysis in cervical scrapings may improve detection of SCC, but few methylation markers have been described for ADC. We aimed to identify novel methylation markers for the early detection of both ADC and SCC. Results: Genome-wide methylation profiling for 20 normal cervices, 6 ADC and 6 SCC using MethylCap-seq yielded 53 candidate regions hypermethylated in both ADC and SCC. Verification and independent validation of the 15 most significant regions revealed 5 markers with differential methylation between 17 normals and 13 cancers. Quantitative methylation-specific PCR on cervical cancer scrapings resulted in detection rates ranging between 80% and 92% while between 94% and 99% of control scrapings tested negative. Four markers (SLC6A5, SOX1, SOX14 and TBX20) detected ADC and SCC with similar sensitivity. In scrapings from women referred with an abnormal smear (n = 229), CIN3+ sensitivity was between 36% and 71%, while between 71% and 93% of adenocarcinoma in situ (AdCIS) were detected; and CIN0/1 specificity was between 88% and 98%. Compared to hrHPV, the combination SOX1/SOX14 showed a similar CIN3+ sensitivity (80% vs. 75%, respectively, P>0.2), while specificity improved (42% vs. 84%, respectively, P < 10(-5)). Conclusion: SOX1 and SOX14 are methylation biomarkers applicable for screening of all cervical cancer types

A biological question and a balanced (orthogonal) design: the ingredients to efficiently analyze two-color microarrays with Confirmatory Factor Analysis

BACKGROUND: Factor analysis (FA) has been widely applied in microarray studies as a data-reduction-tool without any a-priori assumption regarding associations between observed data and latent structure (Exploratory Factor Analysis). A disadvantage is that the representation of data in a reduced set of dimensions can be difficult to interpret, as biological contrasts do not necessarily coincide with single dimensions. However, FA can also be applied as an instrument to confirm what is expected on the basis of pre-established hypotheses (Confirmatory Factor Analysis, CFA). We show that with a hypothesis incorporated in a balanced (orthogonal) design, including 'SelfSelf' hybridizations, dye swaps and independent replications, FA can be used to identify the latent factors underlying the correlation structure among the observed two-color microarray data. An orthogonal design will reflect the principal components associated with each experimental factor. We applied CFA to a microarray study performed to investigate cisplatin resistance in four ovarian cancer cell lines, which only differ in their degree of cisplatin resistance. RESULTS: Two latent factors, coinciding with principal components, representing the differences in cisplatin resistance between the four ovarian cancer cell lines were easily identified. From these two factors 315 genes associated with cisplatin resistance were selected, 199 genes from the first factor (False Discovery Rate (FDR): 19%) and 152 (FDR: 24%) from the second factor, while both gene sets shared 36. The differential expression of 16 genes was validated with reverse transcription-polymerase chain reaction. CONCLUSION: Our results show that FA is an efficient method to analyze two-color microarray data provided that there is a pre-defined hypothesis reflected in an orthogonal design

Kinome capture sequencing of high-grade serous ovarian carcinoma reveals novel mutations in the JAK3 gene.

High-grade serous ovarian carcinoma (HGSOC) remains the deadliest form of epithelial ovarian cancer and despite major efforts little improvement in overall survival has been achieved. Identification of recurring "driver" genetic lesions has the potential to enable design of novel therapies for cancer. Here, we report on a study to find such new therapeutic targets for HGSOC using exome-capture sequencing approach targeting all kinase genes in 127 patient samples. Consistent with previous reports, the most frequently mutated gene was TP53 (97% mutation frequency) followed by BRCA1 (10% mutation frequency). The average mutation frequency of the kinase genes mutated from our panel was 1.5%. Intriguingly, after BRCA1, JAK3 was the most frequently mutated gene (4% mutation frequency). We tested the transforming properties of JAK3 mutants using the Ba/F3 cell-based in vitro functional assay and identified a novel gain-of-function mutation in the kinase domain of JAK3 (p.T1022I). Importantly, p.T1022I JAK3 mutants displayed higher sensitivity to the JAK3-selective inhibitor Tofacitinib compared to controls. For independent validation, we re-sequenced the entire JAK3 coding sequence using tagged amplicon sequencing (TAm-Seq) in 463 HGSOCs resulting in an overall somatic mutation frequency of 1%. TAm-Seq screening of CDK12 in the same population revealed a 7% mutation frequency. Our data confirms that the frequency of mutations in kinase genes in HGSOC is low and provides accurate estimates for the frequency of JAK3 and CDK12 mutations in a large well characterized cohort. Although p.T1022I JAK3 mutations are rare, our functional validation shows that if detected they should be considered as potentially actionable for therapy. The observation of CDK12 mutations in 7% of HGSOC cases provides a strong rationale for routine somatic testing, although more functional and clinical characterization is required to understand which nonsynonymous mutations alterations are associated with homologous recombination deficiency

Discovery of DNA methylation markers in cervical cancer using relaxation ranking

<p>Abstract</p> <p>Background</p> <p>To discover cancer specific DNA methylation markers, large-scale screening methods are widely used. The pharmacological unmasking expression microarray approach is an elegant method to enrich for genes that are silenced and re-expressed during functional reversal of DNA methylation upon treatment with demethylation agents. However, such experiments are performed in <it>in vitro </it>(cancer) cell lines, mostly with poor relevance when extrapolating to primary cancers. To overcome this problem, we incorporated data from primary cancer samples in the experimental design. A strategy to combine and rank data from these different data sources is essential to minimize the experimental work in the validation steps.</p> <p>Aim</p> <p>To apply a new relaxation ranking algorithm to enrich DNA methylation markers in cervical cancer.</p> <p>Results</p> <p>The application of a new sorting methodology allowed us to sort high-throughput microarray data from both cervical cancer cell lines and primary cervical cancer samples. The performance of the sorting was analyzed <it>in silico</it>. Pathway and gene ontology analysis was performed on the top-selection and gives a strong indication that the ranking methodology is able to enrich towards genes that might be methylated. Terms like regulation of progression through cell cycle, positive regulation of programmed cell death as well as organ development and embryonic development are overrepresented. Combined with the highly enriched number of imprinted and X-chromosome located genes, and increased prevalence of known methylation markers selected from cervical (the highest-ranking known gene is <it>CCNA1</it>) as well as from other cancer types, the use of the ranking algorithm seems to be powerful in enriching towards methylated genes.</p> <p>Verification of the DNA methylation state of the 10 highest-ranking genes revealed that 7/9 (78%) gene promoters showed DNA methylation in cervical carcinomas. Of these 7 genes, 3 (<it>SST</it>, <it>HTRA3 </it>and <it>NPTX1</it>) are not methylated in normal cervix tissue.</p> <p>Conclusion</p> <p>The application of this new relaxation ranking methodology allowed us to significantly enrich towards methylation genes in cancer. This enrichment is both shown <it>in silico </it>and by experimental validation, and revealed novel methylation markers as proof-of-concept that might be useful in early cancer detection in cervical scrapings.</p