TY - JOUR
T1 - Methylomic analysis of ovarian cancers identifies tumor-specific alterations readily detectable in early precursor lesions
AU - Pisanic, Thomas R.
AU - Cope, Leslie M.
AU - Lin, Shiou Fu
AU - Yen, Ting Tai
AU - Athamanolap, Pornpat
AU - Asaka, Ryoichi
AU - Nakayama, Kentaro
AU - Fader, Amanda N.
AU - Wang, Tza Huei
AU - Shih, Ie Ming
AU - Wang, Tian Li
N1 - Funding Information:
This work was supported by The Honorable Tina Brozman Foundation, The Department of Defense CDMRP (grant number W81XWH-11-2-0230), The NIH/NIC (grant numbers EDRN UO1CA200469, RO1CA215483, P50CA228991), The Teal award, The Gray Foundation, Colleen's Dream Foundation, The Johns Hopkins Discovery Team Award, and The Richard W. TeLinde Endowment, Johns Hopkins University. The authors would also like to thank Drs. Herman Chui and Tiffany Chu for their assistance in sequencing and sequencing analysis, respectively, as well as Dr. Karime Kalil Machado and Ye Zhang for their technical help and assistance in biosta-tistical analyses, respectively.
Funding Information:
This work was supported by The Honorable Tina Brozman Foundation, The Department of Defense CDMRP (grant number W81XWH-11-2-0230), The NIH/NIC (grant numbers EDRN UO1CA200469, RO1CA215483, P50CA228991), The Teal award, The Gray Foundation, Colleen's Dream Foundation, The Johns Hopkins Discovery Team Award, and The Richard W. TeLinde Endowment, Johns Hopkins University. The authors would also like to thank Drs. Herman Chui and Tiffany Chu for their assistance in sequencing and sequencing analysis, respectively, as well as Dr. Karime Kalil Machado and Ye Zhang for their technical help and assistance in biostatistical analyses, respectively.
Funding Information:
Sample quality assessment and microarray analysis were conducted at The Sidney Kimmel Cancer Center Microarray Core Facility at Johns Hopkins University, supported by NIH grant P30 CA006973 entitled Regional Oncology Research Center.
Publisher Copyright:
© 2018 American Association for Cancer Research.
PY - 2018/12/15
Y1 - 2018/12/15
N2 - Purpose: High-grade serous ovarian carcinoma (HGSOC) typically remains undiagnosed until advanced stages when peritoneal dissemination has already occurred. Here, we sought to identify HGSOC-specific alterations in DNA methylation and assess their potential to provide sensitive and specific detection of HGSOC at its earliest stages. Experimental Design: MethylationEPIC genome-wide methylation analysis was performed on a discovery cohort comprising 23 HGSOC, 37 non-HGSOC malignant, and 36 histologically unremarkable gynecologic tissue samples. The resulting data were processed using selective bioinformatic criteria to identify regions of high-confidence HGSOC-specific differential methylation. Quantitative methylation-specific real-time PCR (qMSP) assays were then developed for 8 of the top-performing regions and analytically validated in a cohort of 90 tissue samples. Lastly, qMSP assays were used to assess and compare methylation in 30 laser-capture microdissected (LCM) fallopian tube epithelia samples obtained from cancer-free and serous tubal intraepithelial carcinoma (STIC) positive women. Results: Bioinformatic selection identified 91 regions of robust, HGSOC-specific hypermethylation, 23 of which exhibited an area under the receiver-operator curve (AUC) value 0.9 in the discovery cohort. Seven of 8 top-performing regions demonstrated AUC values between 0.838 and 0.968 when analytically validated by qMSP in a 90-patient cohort. A panel of the 3 top-performing genes (c17orf64, IRX2, and TUBB6) was able to perfectly discriminate HGSOC (AUC 1.0). Hypermethylation within these loci was found exclusively in LCM fallopian tube epithelia from women with STIC lesions, but not in cancer-free fallopian tubes. Conclusions: A panel of methylation biomarkers can be used to accurately identify HGSOC, even at precursor stages of the disease.
AB - Purpose: High-grade serous ovarian carcinoma (HGSOC) typically remains undiagnosed until advanced stages when peritoneal dissemination has already occurred. Here, we sought to identify HGSOC-specific alterations in DNA methylation and assess their potential to provide sensitive and specific detection of HGSOC at its earliest stages. Experimental Design: MethylationEPIC genome-wide methylation analysis was performed on a discovery cohort comprising 23 HGSOC, 37 non-HGSOC malignant, and 36 histologically unremarkable gynecologic tissue samples. The resulting data were processed using selective bioinformatic criteria to identify regions of high-confidence HGSOC-specific differential methylation. Quantitative methylation-specific real-time PCR (qMSP) assays were then developed for 8 of the top-performing regions and analytically validated in a cohort of 90 tissue samples. Lastly, qMSP assays were used to assess and compare methylation in 30 laser-capture microdissected (LCM) fallopian tube epithelia samples obtained from cancer-free and serous tubal intraepithelial carcinoma (STIC) positive women. Results: Bioinformatic selection identified 91 regions of robust, HGSOC-specific hypermethylation, 23 of which exhibited an area under the receiver-operator curve (AUC) value 0.9 in the discovery cohort. Seven of 8 top-performing regions demonstrated AUC values between 0.838 and 0.968 when analytically validated by qMSP in a 90-patient cohort. A panel of the 3 top-performing genes (c17orf64, IRX2, and TUBB6) was able to perfectly discriminate HGSOC (AUC 1.0). Hypermethylation within these loci was found exclusively in LCM fallopian tube epithelia from women with STIC lesions, but not in cancer-free fallopian tubes. Conclusions: A panel of methylation biomarkers can be used to accurately identify HGSOC, even at precursor stages of the disease.
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U2 - 10.1158/1078-0432.CCR-18-1199
DO - 10.1158/1078-0432.CCR-18-1199
M3 - Article
C2 - 30108103
AN - SCOPUS:85058436557
SN - 1078-0432
VL - 24
SP - 6536
EP - 6547
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 24
ER -