13 research outputs found

    Microarray Glycoprofiling of CA125 Improves Differential Diagnosis of Ovarian Cancer

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    The CA125 biomarker assay plays an important role in the diagnosis and management of primary invasive epithelial ovarian/tubal cancer (iEOC). However, a fundamental problem with CA125 is that it is not cancer-specific and may be elevated in benign gynecological conditions such as benign ovarian neoplasms and endometriosis. Aberrant O-glycosylation is an inherent and specific property of cancer cells and could potentially aid in differentiating cancer from these benign conditions, thereby improving specificity of the assay. We report on the development of a novel microarray-based platform for profiling specific aberrant glycoforms, such as Neu5Acα2,6GalNAc (STn) and GalNAc (Tn), present on CA125 (MUC16) and CA15-3 (MUC1). In a blinded cohort study of patients with an elevated CA125 levels (30–500 kU/L) and a pelvic mass from the UK Ovarian Cancer Population Study (UKOPS), we measured STn-CA125, ST-CA125 and STn-CA15-3. The combined glycoform profile was able to distinguish benign ovarian neoplasms from invasive epithelial ovarian/tubule cancer (iEOCs) with a specificity of 61.1% at 90% sensitivity. The findings suggest that microarray glycoprofiling could improve differential diagnosis and significantly reduce the number of patients elected for further testing. The approach warrants further investigation in other cancers

    Additional file 1: Figure S1. of Methylation patterns in serum DNA for early identification of disseminated breast cancer

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    Samples from the SUCCESS trial analyzed within this study. Figure S2. Samples from the UKCTOCS cohort analyzed within this study (nested case/control setting). Figure S3. Absolute pattern counts for all patterns detected in the region of marker EFC#93 in Serum Set 1 samples. Figure S4. Pattern frequency of EFC#93 serum DNAme in two prospectively independently collected cohorts. Figure S5. DNA amount per mL serum in the prospectively collected serum (Set 1 and 2), SUCCESS cohort, and UKCTOCS cohort. Figure S6. Pattern frequency for EFC#93 measured in SUCCESS serum set samples from women with no, 1–4 or ≥ 5 CTCs in the matched blood sample before (A) or after (B) chemotherapy. Figure S7. Impact of the presence (+ve, ≥ 1 cancer cell in blood sample) or absence (-ve) of CTCs on patient outcome. Figure S8. Impact of the presence (+ve, EFC#93 pattern frequency ≥ 0.00008) or absence (-ve) of serum DNA methylation in CTC + ve (≥1 cancer cell in pre-chemotherapy blood sample) or absence CTC-ve patients. Figure S9. Relapse-free and overall survival according to samples taken after chemotherapy. Figure S10. Relapse-free and overall survival according to samples taken after chemotherapy. Figure S11. Average serum DNA amount correlates with average UK temperature. Figure S12. Average serum DNA fragment size correlates with average UK temperature. Figure S13. Correlation of DNA fragment size and DNA amount. Figure S14. Overall survival of women whose samples were taken before and after chemotherapy and before anti-hormonal treatment in hormone receptor-negative and -positive SUCCESS participants. Figure S15. Overall survival of women whose samples were taken before and after chemotherapy and before anti-hormonal treatment in hormone receptor-negative and -positive SUCCESS participants. (PDF 2123 kb

    Association of rs2256787 in the <i>ARHGEF10L</i> gene with invasive endometrioid EOC risk by study site and combined.

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    <p>Squares represent the estimated per-allele odds ratio (OR) and are proportional to sample size for each study; lines indicate its 95% confidence interval (CI); source indicates contributing study;[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197561#pone.0197561.ref011" target="_blank">11</a>] MAF, control minor allele frequency; PVal, per-allele p-value adjusted for age, site, and principal components to account for residual differences in European ancestry.</p
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