4 research outputs found
Additional file 1: Figure S1. of The potential of circulating tumor DNA methylation analysis for the early detection and management of ovarian cancer
Design of the nested case-control study based on the UKCTOCS Cohort. Figure S2. DMR discovery with Illumina 450 K methylation arrays. Figure S3. Pattern counts for informative regions. Figure S4. Pattern frequencies for the different regions analyzed in serum set 1 samples. Figure S5. Pattern frequencies for the different regions analyzed in serum set 2 samples. Figure S6. DNA methylation for regions #144, #204, and #228 according to OC stages. Figure S7. Coverage (number of reads) for the three different regions analyzed in serum set 3 samples. Figure S8. CA125 levels measured in NACT serum set samples. Figure S9. Pattern frequencies for the top three reactions measured in NACT serum set samples. Figure S10. Coverage (number of reads) for the top three reactions measured in NACT serum set samples. Figure S11. Average DNA amount extracted correlates with average UK temperature. Figure S12 The fraction (%) of small fragment (50–250 bp) DNA in the serum DNA preparation for 171 UKCTOCS samples analyzed in the study. Figure S13. Box plots comparing the average beta values for 450 k array probes within regions #204 and #228 between each normal (N), cancer (C) group, and white blood cell (WBC) data for OC and other 19 TCGA cancer types. (DOCX 3024 kb
Additional file 1: Figure S1. of Methylation patterns in serum DNA for early identification of disseminated breast cancer
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
Additional file 3: Table S1. of Methylation patterns in serum DNA for early identification of disseminated breast cancer
Coordinates and primers used to amplify the identified target regions using bisulfite sequencing. (PDF 578 kb
The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples
Genetic and non-genetic factors contribute to breast cancer development. An epigenome-based signature capturing these components in easily accessible samples could identify women at risk. Here, we analyse the DNA methylome in 2,818 cervical, 357 and 227 matched buccal and blood samples respectively, and 42 breast tissue samples from women with and without breast cancer. Utilising cervical liquid-based cytology samples, we develop the DNA methylation-based Women's risk IDentification for Breast Cancer index (WID-BC-index) that identifies women with breast cancer with an AUROC (Area Under the Receiver Operator Characteristic) of 0.84 (95% CI: 0.80-0.88) and 0.81 (95% CI: 0.76-0.86) in internal and external validation sets, respectively. CpGs at progesterone receptor binding sites hypomethylated in normal breast tissue of women with breast cancer or in BRCA mutation carriers are also hypomethylated in cervical samples of women with poor prognostic breast cancer. Our data indicate that a systemic epigenetic programming defect is highly prevalent in women who develop breast cancer. Further studies validating the WID-BC-index may enable clinical implementation for monitoring breast cancer risk