selected publications

1. Clin. Cancer Res.

   Epigenetic Instability Based Metrics in Cell-Free DNA for Early Cancer Detection

   Thursby, Sara-Jayne, Jin, Zhicheng, Blum, Jacob, Gurau, Andrei, Noë, Michaël, Scharpf, Robert B., Velculescu, Victor E., Cope, Leslie, Brock, Malcolm, Baylin, Stephen,  Pisanic, Thomas, and Easwaran, Hariharan

   Clinical Cancer Research, 2026

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   Purpose: Cancers present significant DNA methylation changes, which arise in a stochastic manner, marked by extensive epigenetic variation, indicative of high epigenetic instability. We aimed to evaluate the utility of epigenetic instability for cell-free DNA (cfDNA)-based cancer detection. Experimental Design: Through analysis of cancer DNA methylation datasets (n=2,084), we identified a set of 269 CGI regions that robustly captures this instability in a cancer-specific manner. We developed metrics to measure this epigenetic instability, termed the Epigenetic Instability Index (EII), for cancer screening via cfDNA methylation. Results: Machine learning classifiers employing the EII of these 269 regions efficiently identified breast and lung cancer from cfDNA, differentiating even stage IA LUAD with  81% sensitivity and early-stage breast cancer with  68% sensitivity, both at 95% specificity. Conclusion: Our studies demonstrate that quantifying epigenetic instability is a novel, capable approach to distinguishing cancer from normal cases using cfDNA, performing better than standard approaches using absolute methylation changes. The epigenetic instability-based approaches for cancer detection developed here, along with their validation in independent datasets, support further development and the potential for future clinical application of these strategies in cancer screening.

   @article{RN109,
     author = {Thursby, Sara-Jayne and Jin, Zhicheng and Blum, Jacob and Gurau, Andrei and Noë, Michaël and Scharpf, Robert B. and Velculescu, Victor E. and Cope, Leslie and Brock, Malcolm and Baylin, Stephen and Pisanic, Thomas and Easwaran, Hariharan},
     title = {Epigenetic Instability Based Metrics in Cell-Free DNA for Early Cancer Detection},
     journal = {Clinical Cancer Research},
     issn = {1078-0432},
     doi = {10.1158/1078-0432.Ccr-25-3384},
     url = {https://doi.org/10.1158/1078-0432.CCR-25-3384},
     year = {2026},
   }

2. Sci. Adv.

   Multiplex digital profiling of DNA methylation heterogeneity for sensitive and cost-effective cancer detection in low-volume liquid biopsies

   Zhao, Yang, O’Keefe, Christine M., Hu, Jiumei, Allan, Conor M., Cui, Weiwen, Lei, Hanran, Chiu, Allyson, Hsieh, Kuangwen, Joyce, Sonali C., Herman, James G.,  Pisanic, Thomas R., and Wang, Tza-Huei

   Science Advances, 2024

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   Molecular alterations in cancerous tissues exhibit intercellular genetic and epigenetic heterogeneity, complicating the performance of diagnostic assays, particularly for early cancer detection. Conventional liquid biopsy methods have limited sensitivity and/or ability to assess epigenetic heterogeneity of rare epiallelic variants cost-effectively. We report an approach, named REM-DREAMing (Ratiometric-Encoded Multiplex Discrimination of Rare EpiAlleles by Melt), which leverages a digital microfluidic platform that incorporates a ratiometric fluorescence multiplex detection scheme and precise digital high-resolution melt analysis to enable low-cost, parallelized analysis of heterogeneous methylation patterns on a molecule-by-molecule basis for the detection of cancer in liquid biopsies. We applied the platform to simultaneously assess intermolecular epigenetic heterogeneity in five methylation biomarkers for improved, blood-based screening for early-stage non–small cell lung cancer. In a cohort of 48 low-volume liquid biopsy specimens from patients with indeterminant pulmonary nodules, we show that assessment of intermolecular methylation density distributions can notably improve the performance of multigene methylation biomarker panels for the early detection of cancer. Early-stage cancer diagnosis can be improved by detecting epigenetic density through analyzing heterogeneous DNA methylation.

   @article{RN95,
     author = {Zhao, Yang and O’Keefe, Christine M. and Hu, Jiumei and Allan, Conor M. and Cui, Weiwen and Lei, Hanran and Chiu, Allyson and Hsieh, Kuangwen and Joyce, Sonali C. and Herman, James G. and Pisanic, Thomas R. and Wang, Tza-Huei},
     title = {Multiplex digital profiling of DNA methylation heterogeneity for sensitive and cost-effective cancer detection in low-volume liquid biopsies},
     journal = {Science Advances},
     volume = {10},
     number = {47},
     pages = {eadp1704},
     doi = {doi:10.1126/sciadv.adp1704},
     url = {https://www.science.org/doi/abs/10.1126/sciadv.adp1704},
     year = {2024},
   }

3. Clin. & Transl. Med.

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

   O’Keefe, Christine M., Zhao, Yang, Cope, Leslie M., Ho, Chih-Ming, Fader, Amanda N., Stone, Rebecca, Ferris, James S., Beavis, Anna, Levinson, Kimberly, Wethington, Stephanie, Wang, Tian-Li,  Pisanic, Thomas R., Shih, Ie-Ming, and Wang, Tza-Huei

   Clinical and Translational Medicine, 2024

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   Recent advances in molecular analyses of ovarian cancer have revealed a wealth of promising tumour-specific biomarkers, including protein, DNA mutations and methylation; however, reliably detecting such alterations at satisfactorily high sensitivity and specificity through low-cost methods remains challenging, especially in early-stage diseases. Here we present PapDREAM, a new approach that enables detection of rare, ovarian-cancer-specific aberrations of DNA methylation from routinely-collected cervical Pap specimens. The PapDREAM approach employs a microfluidic platform that performs highly parallelized digital high-resolution melt to analyze locus-specific DNA methylation patterns on a molecule-by-molecule basis at or near single CpG-site resolution at a fraction (< 1/10th) of the cost of next-generation sequencing techniques. We demonstrate the feasibility of the platform by assessing intermolecular heterogeneity of DNA methylation in a panel of methylation biomarker loci using DNA derived from Pap specimens obtained from a cohort of 43 women, including 18 cases with ovarian cancer and 25 cancer-free controls. PapDREAM leverages systematic multidimensional bioinformatic analyses of locus-specific methylation heterogeneity to improve upon Pap-specimen-based detection of ovarian cancer, demonstrating a clinical sensitivity of 50% at 99% specificity in detecting ovarian cancer cases with an area under the receiver operator curve of 0.90. We then establish a logistic regression model that could be used to identify high-risk patients for subsequent clinical follow-up and monitoring. The results of this study support the utility of PapDREAM as a simple, low-cost screening method with the potential to integrate with existing clinical workflows for early detection of ovarian cancer. Key points 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.

   @article{RN93,
     author = {O'Keefe, Christine M. and Zhao, Yang and Cope, Leslie M. and Ho, Chih-Ming and Fader, Amanda N. and Stone, Rebecca and Ferris, James S. and Beavis, Anna and Levinson, Kimberly and Wethington, Stephanie and Wang, Tian-Li and Pisanic, Thomas R. and Shih, Ie-Ming and Wang, Tza-Huei},
     title = {Single-molecule epiallelic profiling of DNA derived from routinely collected Pap specimens for noninvasive detection of ovarian cancer},
     journal = {Clinical and Translational Medicine},
     volume = {14},
     number = {8},
     pages = {e1778},
     doi = {https://doi.org/10.1002/ctm2.1778},
     url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ctm2.1778},
     year = {2024},
   }

4. Cancers

   Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review

   Liberto, Juliane M., Chen, Sheng-Yin, Shih, Ie-Ming, Wang, Tza-Huei, Wang, Tian-Li, and Pisanic, Thomas R.

   Cancers, 2022

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   Ovarian high-grade serous carcinoma (HGSC) has a 5-year survival rate of less than 50%, making it one of the most lethal gynecological cancers for women in the developed world today. Delayed presentation of clinical symptoms and late-stage diagnosis drive the high mortality rate of this disease. Early detection is associated with significant improvements in survival, however, screening in the general population is currently not recommended at this time due to a notable lack of sensitive and specific biomarkers for early-stage disease. In this review, we provide an overview of the current landscape of ovarian cancer diagnostics, emphasizing emerging methodologies for the non-invasive detection of HGSC.

   @article{RN74,
     author = {Liberto, Juliane M. and Chen, Sheng-Yin and Shih, Ie-Ming and Wang, Tza-Huei and Wang, Tian-Li and Pisanic, Thomas R.},
     title = {Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review},
     journal = {Cancers},
     volume = {14},
     number = {12},
     pages = {2885},
     issn = {2072-6694},
     url = {https://www.mdpi.com/2072-6694/14/12/2885},
     year = {2022},
   }

5. Clin. Cancer Res.

   Methylomic Landscapes of Ovarian Cancer Precursor Lesions

   Pisanic, Thomas R., Wang, Yeh, Sun, Hanru, Considine, Michael, Li, Lihong, Wang, Tza-Huei, Wang, Tian-Li, and Shih, Ie-Ming

   Clinical Cancer Research, 2020

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   Purpose: The current paradigm in the development of high-grade serous ovarian carcinoma (HGSC) proposes that the majority of HGSCs arise from precursor serous tubal intraepithelial carcinoma (STIC) lesions of the fallopian tube. Here we survey genome-wide methylation in HGSC precursor lesions to identify genomic regions that exhibit high-specificity differential hypermethylation for potential use as biomarkers for detecting STIC and HGSC at stages when curative intervention likely remains feasible.Experimental Design: We first identified quality control criteria for performing reliable methylomic analysis of DNA-limited tubal precursor lesions with the Illumina Infinium MethylationEPIC array. We then used this platform to compare genome-wide methylation among 12 STICs with paired adjacent-normal epithelia, one p53 signature lesion and two samples of concurrent HGSC. The resulting methylomic data were analyzed by unsupervised hierarchical clustering and multidimensional analysis. Regions of high-confidence STIC-specific differential hypermethylation were identified using selective bioinformatic criteria and compared with published MethylationEPIC data from 23 HGSC tumors and 11 healthy fallopian tube mucosae.Results: Unsupervised analysis showed that STICs largely clustered with HGSCs, but were clearly distinct from adjacent-normal fallopian tube epithelia. Forty-two genomic regions exhibited high-confidence STIC-specific differential hypermethylation, of which 17 (40.5%) directly overlapped with HGSC-specific differentially methylated regions. Methylation at these shared loci was able to completely distinguish STIC and HGSC samples from normal and adjacent-normal specimens.Conclusions: Our results suggest that most STICs are epigenetically similar to HGSCs and share regions of differential hypermethylation that warrant further evaluation for potential use as biomarkers for early detection of ovarian HGSC.See related commentary by Ishak and De Carvalho, p. 6083

   @article{RN50,
     author = {Pisanic, Thomas R. and Wang, Yeh and Sun, Hanru and Considine, Michael and Li, Lihong and Wang, Tza-Huei and Wang, Tian-Li and Shih, Ie-Ming},
     title = {Methylomic Landscapes of Ovarian Cancer Precursor Lesions},
     journal = {Clinical Cancer Research},
     volume = {26},
     number = {23},
     pages = {6310-6320},
     doi = {10.1158/1078-0432.Ccr-20-0270},
     year = {2020},
   }

6. Nucleic Acids Res.

   DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies

   Pisanic II, Thomas R., Athamanolap, Pornpat, Poh, Weijie, Chen, Chen, Hulbert, Alicia, Brock, Malcolm V., Herman, James G., and Wang, Tza-Huei

   Nucleic Acids Research, 2015

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   Many cancers comprise heterogeneous populations of cells at primary and metastatic sites throughout the body. The presence or emergence of distinct subclones with drug-resistant genetic and epigenetic phenotypes within these populations can greatly complicate therapeutic intervention. Liquid biopsies of peripheral blood from cancer patients have been suggested as an ideal means of sampling intratumor genetic and epigenetic heterogeneity for diagnostics, monitoring and therapeutic guidance. However, current molecular diagnostic and sequencing methods are not well suited to the routine assessment of epigenetic heterogeneity in difficult samples such as liquid biopsies that contain intrinsically low fractional concentrations of circulating tumor DNA (ctDNA) and rare epigenetic subclonal populations. Here we report an alternative approach, deemed DREAMing (Discrimination of Rare EpiAlleles by Melt), which uses semi-limiting dilution and precise melt curve analysis to distinguish and enumerate individual copies of epiallelic species at single-CpG-site resolution in fractions as low as 0.005%, providing facile and inexpensive ultrasensitive assessment of locus-specific epigenetic heterogeneity directly from liquid biopsies. The technique is demonstrated here for the evaluation of epigenetic heterogeneity at p14ARF and BRCA1 gene-promoter loci in liquid biopsies obtained from patients in association with non-small cell lung cancer (NSCLC) and myelodysplastic/myeloproliferative neoplasms (MDS/MPN), respectively.

   @article{RN75,
     author = {Pisanic II, Thomas R. and Athamanolap, Pornpat and Poh, Weijie and Chen, Chen and Hulbert, Alicia and Brock, Malcolm V. and Herman, James G. and Wang, Tza-Huei},
     title = {DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies},
     journal = {Nucleic Acids Research},
     volume = {43},
     number = {22},
     pages = {e154-e154},
     issn = {0305-1048},
     doi = {10.1093/nar/gkv795},
     url = {https://doi.org/10.1093/nar/gkv795},
     year = {2015},
   }