Single-molecule epiallelic profiling of DNA derived from routinely collected Pap specimens for noninvasive detection of ovarian cancer

Abstract

	•We present a microfluidic platform for detection and analysis of rare, heterogeneously methylated DNA within Pap specimens towards detection of ovarian cancer.
	•The platform achieves high sensitivity (fractions <0.00005%) at a suitably low cost (~$25) for routine screening applications.
	•Furthermore, it provides molecule-by-molecule quantitative analysis to facilitate further study on the effect of heterogeneous methylation on cancer development.

Keywords

digital melt / DNA methylation / microfluidics / ovarian cancer / Pap smear

References

[1] TorreLA, Trabert B, DeSantisCE, et al. Ovarian cancer statistics, 2018. CA Cancer J Clin. 2018;68(4):284-296.

[2] ChoKR, ShihIM. Ovarian cancer. Annu Rev Pathol Mech Dis. 2009;4:287-313.

[3] National Cancer Institute. SEER*Explorer Application. Accessed May 2, 2023. Available from: https://seer.cancer.gov/statistics-network/explorer/

[4] MattesonKA, Members S, GundersonC, RichardsonDL. The role of the obstetrician-gynecologist in the early detection of epithelial ovarian cancer in women at Average Risk Committee on Gynecologic Practice Society of Gynecologic Oncology Recommendations and Conclusions. Replace Comm Opin Number. 2017:716.

[5] HendersonJT, WebberEM, SawayaGF. Screening for ovarian cancer updated evidence report and systematic review for the US Preventive Services Task Force. JAMA. 2018;319(6):595-606.

[6] KindeI, Bettegowda C, WangY, et al. Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Sci Transl Med. 2013;5(167):167ra4.

[7] WangY, LiL, DouvilleC, et al. Evaluation of liquid from the Papanicolaou test and other liquid biopsies for the detection of endometrial and ovarian cancers. Sci Transl Med. 2018;10(433):eaap8793.

[8] ZhangL, HuC, HuangZ, Li Z, ZhangQ, HeY. In silico screening of circulating tumor DNA, circulating microRNAs, and long non-coding RNAs as diagnostic molecular biomarkers in ovarian cancer: a comprehensive meta-analysis. PLoS One. 2021;16(4):e0250717.

[9] GiannopoulouL, Chebouti I, PavlakisK, et al. RASSF1A promoter methylation in high-grade serous ovarian cancer: a direct comparison study in primary tumors, adjacent morphologically tumor cell-free tissues and paired circulating tumor DNA. Oncotarget. 2017;8(13):21429-21443.

[10] SwisherEM, WollanM, MahtaniSM, et al. Tumor-specific p53 sequences in blood and peritoneal fluid of women with epithelial ovarian cancer. Am J Obstet Gynecol. 2005;193(3):662-667.

[11] LeeY, MironA, DrapkinR, et al. A candidate precursor to serous carcinoma that originates in the distal fallopian tube. J Pathol. 2007;211(1):26-35.

[12] EckertMA, PanS, HernandezKM, et al. Genomics of ovarian cancer progression reveals diverse metastatic trajectories including intraepithelial metastasis to the fallopian tube. Cancer Discov. 2016;6(12):1342.

[13] Labidi-GalySI, PappE, HallbergD, et al. High grade serous ovarian carcinomas originate in the fallopian tube. Nat Commun. 2017;8:1093.

[14] ShihIM, WangY, WangTL. The origin of ovarian cancer species and precancerous landscape. Am J Pathol. 2021;191(1):26-39.

[15] WuRC, WangP, LinSF, et al. Genomic landscape and evolutionary trajectories of ovarian cancer precursor lesions. J Pathol. 2019;248(1):41-50.

[16] SchnatzPF, GuileM, O’SullivanDM, SoroskyJI. Clinical significance of atypical glandular cells on cervical cytology. Obstet Gynecol. 2006;107(3):701-708.

[17] ChangCC, WangHC, LiaoYP, et al. The feasibility of detecting endometrial and ovarian cancer using DNA methylation biomarkers in cervical scrapings. J Gynecol Oncol. 2018;29(1):17.

[18] EarpMA, Cunningham JM. DNA methylation changes in epithelial ovarian cancer histotypes. Genomics. 2015;106(6):311-321.

[19] Sánchez-VegaF, Gotea V, PetrykowskaHM, et al. Recurrent patterns of DNA methylation in the ZNF154, CASP8, and VHL promoters across a wide spectrum of human solid epithelial tumors and cancer cell lines. Epigenetics. 2013;8(12):1355-1372.

[20] SinghA, GuptaS, BadarukhiyaJA, SachanM. Detection of aberrant methylation of HOXA9 and HIC1 through multiplex MethyLight assay in serum DNA for the early detection of epithelial ovarian cancer. Int J Cancer. 2020;147(6):1740-1752.

[21] PisanicTR, CopeLM, LinSFSF, et al. Methylomic analysis of ovarian cancers identifies tumor-specific alterations readily detectable in early precursor lesions. Clin Cancer Res. 2018;24(24):6536-6547.

[22] BelinskySA, NikulaKJ, PalmisanoWA, et al. Aberrant methylation of p16(INK4a) is an early event in lung cancer and a potential biomarker for early diagnosis. Proc Natl Acad Sci U S A. 1998;95(20):11891-11896.

[23] HermanJG, BaylinSB. Gene silencing in cancer in association with promoter hypermethylation. N Engl J Med. 2003;34921349:2042-2054. Accessed June 15, 2017.

[24] PisanicTR, Athamanolap P, PohW, et al. DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies. Nucleic Acids Res. 2015;43(22):e154.

[25] O’KeefeCM, Pisanic TR, ZecH, OvermanMJ, HermanJG, WangTH. Facile profiling of molecular heterogeneity by microfluidic digital melt. Sci Adv. 2018;4(9):6459-6485.

[26] LandanG, CohenNM, MukamelZ, et al. Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues. Nat Genet. 2012;44(11):1207-1214.

[27] TimpW, Feinberg AP. Cancer as a dysregulated epigenome allowing cellular growth advantage at the expense of the host. Nat Rev Cancer. 2013;13(7):497-510.

[28] TeschendorffAE, JonesA, FieglH, et al. Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation. Genome Med. 2012;4(3).

[29] SheffieldNC, Pierron G, KlughammerJ, et al. DNA methylation heterogeneity defines a disease spectrum in Ewing sarcoma. Nat Med. 2017;23(3):386-395.

[30] KlughammerJ, KieselB, RoetzerT, et al. The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space. Nat Med 2018 2410. 2018;24(10):1611-1624.

[31] HuX, Estecio MR, ChenR, et al. Evolution of DNA methylome from precancerous lesions to invasive lung adenocarcinomas. Nat Commun. 2021;12(1):687.

[32] BatraRN, Lifshitz A, VidakovicAT, et al. DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation. Nat Commun. 2021;12(1).

[33] YakovchukP, Protozanova E, Frank-KamenetskiiMD. Base-stacking and base-pairing contributions into thermal stability of the DNA double helix. Nucleic Acids Res. 2006;34(2):564-574.

[34] PisanicTR, WangY, SunH, et al. Methylomic landscapes of ovarian cancer precursor lesions. Clin Cancer Res. 2020;26(23):6310.

[35] MillerBF, Pisanic TR, MargolinG, et al. Leveraging locus-specific epigenetic heterogeneity to improve the performance of blood-based DNA methylation biomarkers. Clin Epigenetics. 2020;12(1).

[36] TeschendorffAE, Widschwendter M. Differential variability improves the identification of cancer risk markers in DNA methylation studies profiling precursor cancer lesions. Bioinformatics. 2012;28(11):1487-1494.

[37] KitchenerHC, Gittins M, DesaiM. In: Walley T, ed. A Study of Cellular Counting to Determine Minimum Thresholds for Adequacy for Liquid-Based Cervical Cytology Using a Survey and Counting Protocol. NIH Journals Library; 2015.

[38] Krimmel-MorrisonJD, Ghezelayagh TS, LianS, et al. Characterization of TP53 mutations in Pap test DNA of women with and without serous ovarian carcinoma. Gynecol Oncol. 2020;156(2):407.

[39] TorreLA, Trabert B, DeSantisCE, et al. Ovarian cancer statistics, 2018. CA Cancer J Clin. 2018;68(4):284-296.

[40] SalkJJ, Loubet-Senear K, MaritschneggE, et al. Ultra-sensitive TP53 sequencing for cancer detection reveals progressive clonal selection in normal tissue over a century of human lifespan. Cell Rep. 2019;28(1):132-144.

[41] MaritschneggE, WangY, PechaN, et al. Lavage of the uterine cavity for molecular detection of Müllerian duct carcinomas: a proof-of-concept study. J Clin Oncol. 2015;33(36):4293.

[42] LockeWJ, Guanzon D, MaC, et al. DNA methylation cancer biomarkers: translation to the clinic. Front Genet. 2019;10:1150.

[43] HarrellFE, LeeKL, MarkDB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15(4):361-387.

[44] ZhaoY, O’Keefe CM, HsiehK, et al. Multiplex digital methylation-specific PCR for noninvasive screening of lung cancer. Adv Sci. 2023;10(16):2206518.

[45] LuJ, Johnston A, BerichonP, RuKL, KorbieD, TrauM. PrimerSuite: a high-throughput web-based primer design program for multiplex bisulfite PCR. Sci Rep. 2017;7(January):1-12.

[46] WoodsRP, Grafton ST, WatsonJDG, SicotteNLMJ. Automated image registration: II. Intersubject validation of linear and nonlinear models. J Comput Assist Tomogr. 1998;2:153-165.

[47] DwightZ, PalaisR, WittwerCT. uMELT: prediction of high-resolution melting curves and dynamic melting profiles of PCR products in a rich web application. Bioinformatics. 2011;27(7):1019-1020.

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2024 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.