TY - JOUR
T1 - Ovarian cancer detection by DNA methylation in cervical scrapings
AU - Wu, Tzu I.
AU - Huang, Rui Lan
AU - Su, Po Hsuan
AU - Mao, Shih Peng
AU - Wu, Chen Hsuan
AU - Lai, Hung Cheng
N1 - Publisher Copyright:
© 2019 The Author(s).
PY - 2019/11/27
Y1 - 2019/11/27
N2 - Background: Ovarian cancer (OC) is the most lethal gynecological cancer, worldwide, largely due to its vague and nonspecific early stage symptoms, resulting in most tumors being found at advanced stages. Moreover, due to its relative rarity, there are currently no satisfactory methods for OC screening, which remains a controversial and cost-prohibitive issue. Here, we demonstrate that Papanicolaou test (Pap test) cervical scrapings, instead of blood, can reveal genetic/epigenetic information for OC detection, using specific and sensitive DNA methylation biomarkers. Results: We analyzed the methylomes of tissues (50 OC tissues versus 6 normal ovarian epithelia) and cervical scrapings (5 OC patients versus 10 normal controls), and integrated public methylomic datasets, including 79 OC tissues and 6 normal tubal epithelia. Differentially methylated genes were further classified by unsupervised hierarchical clustering, and each candidate biomarker gene was verified in both OC tissues and cervical scrapings by either quantitative methylation-specific polymerase chain reaction (qMSP) or bisulfite pyrosequencing. A risk-score by logistic regression was generated for clinical application. One hundred fifty-one genes were classified into four clusters, and nine candidate hypermethylated genes from these four clusters were selected. Among these, four genes fulfilled our selection criteria and were validated in training and testing set, respectively. The OC detection accuracy was demonstrated by area under the receiver operating characteristic curves (AUCs) in 0.80-0.83 of AMPD3, 0.79-0.85 of AOX1, 0.78-0.88 of NRN1, and 0.82-0.85 of TBX15. From this, we found OC-risk score, equation generated by logistic regression in training set and validated an OC-associated panel comprising AMPD3, NRN1, and TBX15, reaching a sensitivity of 81%, specificity of 84%, and OC detection accuracy of 0.91 (95% CI, 0.82-1) in testing set. Conclusions: Ovarian cancer detection from cervical scrapings is feasible, using particularly promising epigenetic biomarkers such as AMPD3/NRN1/TBX15. Further validation is warranted.
AB - Background: Ovarian cancer (OC) is the most lethal gynecological cancer, worldwide, largely due to its vague and nonspecific early stage symptoms, resulting in most tumors being found at advanced stages. Moreover, due to its relative rarity, there are currently no satisfactory methods for OC screening, which remains a controversial and cost-prohibitive issue. Here, we demonstrate that Papanicolaou test (Pap test) cervical scrapings, instead of blood, can reveal genetic/epigenetic information for OC detection, using specific and sensitive DNA methylation biomarkers. Results: We analyzed the methylomes of tissues (50 OC tissues versus 6 normal ovarian epithelia) and cervical scrapings (5 OC patients versus 10 normal controls), and integrated public methylomic datasets, including 79 OC tissues and 6 normal tubal epithelia. Differentially methylated genes were further classified by unsupervised hierarchical clustering, and each candidate biomarker gene was verified in both OC tissues and cervical scrapings by either quantitative methylation-specific polymerase chain reaction (qMSP) or bisulfite pyrosequencing. A risk-score by logistic regression was generated for clinical application. One hundred fifty-one genes were classified into four clusters, and nine candidate hypermethylated genes from these four clusters were selected. Among these, four genes fulfilled our selection criteria and were validated in training and testing set, respectively. The OC detection accuracy was demonstrated by area under the receiver operating characteristic curves (AUCs) in 0.80-0.83 of AMPD3, 0.79-0.85 of AOX1, 0.78-0.88 of NRN1, and 0.82-0.85 of TBX15. From this, we found OC-risk score, equation generated by logistic regression in training set and validated an OC-associated panel comprising AMPD3, NRN1, and TBX15, reaching a sensitivity of 81%, specificity of 84%, and OC detection accuracy of 0.91 (95% CI, 0.82-1) in testing set. Conclusions: Ovarian cancer detection from cervical scrapings is feasible, using particularly promising epigenetic biomarkers such as AMPD3/NRN1/TBX15. Further validation is warranted.
KW - Cancer detection
KW - Cervical scrapings
KW - DNA methylation
KW - Ovarian cancer
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U2 - 10.1186/s13148-019-0773-3
DO - 10.1186/s13148-019-0773-3
M3 - Article
C2 - 31775891
AN - SCOPUS:85075777176
SN - 1868-7075
VL - 11
JO - Clinical Epigenetics
JF - Clinical Epigenetics
IS - 1
M1 - 166
ER -