ABSTRACT
BACKGROUND: Human papillomavirus (HPV) is the primary cause of invasive cervical cancer (ICC). The prevalence of various HPV genotypes, ranging from oncogenically low- to high-risk, may be influenced by geographic and demographic factors, which could have critical implications for the screening and prevention of HPV infection and ICC incidence. However, many technical factors may influence the identification of high-risk genotypes associated with ICC in different populations. METHODS: We used high-throughput sequencing of a single amplicon within the HPV L1 gene to assess the influence of patient age, race/ethnicity, histological subtype, sample type, collection date, experimental factors, and computational parameters on the prevalence of HPV genotypes detected in archived DNA (n = 34), frozen tissue (n = 44), and formalin-fixed paraffin-embedded (FFPE) tissue (n = 57) samples collected in the Los Angeles metropolitan area. RESULTS: We found that the percentage of off-target human reads and the concentration of DNA amplified from each sample varied by HPV genotype and by archive type. After accounting for the percentage of human reads and excluding samples with especially low levels of amplified DNA, the HPV prevalence was 95% across all ICC samples: HPV16 was the most common genotype (in 56% of all ICC samples), followed by HPV18 (in 21%). Depending upon the genotyping parameters, the prevalence of HPV58 varied up to twofold in our cohort. In archived DNA and frozen tissue samples, we detected previously established differences in HPV16 and HPV18 frequencies based on histological subtype, but we could not reproduce those findings using our FFPE samples. CONCLUSIONS: In this pilot study, we demonstrate that sample collection, preparation, and analysis methods can influence the detection of certain HPV genotypes and must be carefully considered when drawing any biological conclusions based on HPV genotyping data from ICC samples.
ABSTRACT
PURPOSE: Thyroid cancer is frequently difficult to diagnose due to an overlap of cytologic features between malignant and benign nodules. This overlap leads to unnecessary removal of the thyroid in patients without cancer. While providing some improvement over cytopathologic diagnostics, molecular methods frequently fail to provide a correct diagnosis for thyroid nodules. These approaches are based on the difference between cancer and adjacent thyroid tissue and assume that adjacent tissues are the same as benign nodules. However, in contrast to adjacent tissues, benign thyroid nodules can contain genetic alterations that can be found in cancer.Experimental Design: For the development of a new molecular diagnostic test for thyroid cancer, we evaluated DNA methylation in 109 thyroid tissues by using genome-wide single-base resolution DNA methylation analysis. The test was validated in a retrospective cohort containing 65 thyroid nodules. RESULTS: By conducting reduced representation bisulfite sequencing in 109 thyroid specimens, we found significant differences between adjacent tissue, benign nodules, and cancer. These tissue-specific signatures are strongly linked to active enhancers and cancer-associated genes. Based on these signatures, we developed a new epigenetic approach for thyroid diagnostics. According to the validation cohort, our test has an estimated specificity of 97% [95% confidence interval (CI), 81-100], sensitivity of 100% (95% CI, 87-100), positive predictive value of 97% (95% CI, 83-100), and negative predictive value of 100% (95% CI, 86-100). CONCLUSIONS: These data show that epigenetic testing can provide outstanding diagnostic accuracy for thyroid nodules.See related commentary by Mitmaker et al., p. 457.
