Thomas R. Pisanic

Dynamic and Ongoing De Novo L1 Retrotransposition Contributes to Genome Plasticity and Intrapatient Heterogeneity in Ovarian Cancer

Abstract Long interspersed element-1 (L1) retrotransposons are the only protein-coding active transposable elements in the human genome. Although typically silenced in normal cells, they are highly expressed in many human epithelial cancers, including high-grade serous ovarian cancer (HGSC), and can integrate into the genome through retrotransposition. De novo L1 insertions are known to contribute to genomic instability and cancer evolution in epithelial malignancies, including HGSC, suggesting that they might also play a role in intrapatient tumor heterogeneity. In this study, we quantified de novo L1 insertions in clinical HGSC specimens and uncovered high heterogeneity in total L1 insertion events (L1 burden) between patients. HGSC tumors with high L1 burden were highly proliferative, whereas tumors with low or no L1 insertions showed enrichment of immune response and cell death pathways. Although the overall L1 burden was similar across different tumor sites within the same patient, the specific L1 insertions (L1 profiles) diverged significantly more than their single-nucleotide variants profiles. Taken together, these findings demonstrate that L1 activity and retrotransposition are highly dynamic in vivo and can contribute substantially to tumor genome plasticity, especially at late stages of cancer progression. The patient-specific propensity of acquiring L1 insertions (L1 burden) could be driven by molecular properties of the progenitor tumor. Retrotransposition-associated DNA damage and/or replication stress could be a potential molecular vulnerability for precision cancer medicine approaches. Significance: L1 retrotransposition is a dynamic process that continues at late stages of high-grade serous ovarian cancer and can substantially contribute to intrapatient tumor heterogeneity.

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

AbstractRecent 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.

Integrated Spatial Analysis Reveals the Molecular Landscape of Ovarian Precancerous Lesions

Abstract Studying precancerous lesions is essential for improving early detection and prevention, particularly in aggressive cancers such as ovarian carcinoma. In this study, we conducted integrated and spatial analyses of transcriptomes, aneuploidy, and clinicopathologic features in 166 ovarian precancerous lesions. Four precancerous transcriptomic subtypes were identified: proliferative, immunoreactive, dormant, and mixed. These subtypes varied in their frequency of germline BRCA1/2 mutations, aneuploidy, CCNE1/MYC amplification, proliferative activity, immunoregulatory gene expression, and histologic features. Notably, the immunoreactive subtype upregulated immunoregulatory genes, exhibited chronic inflammation, and was enriched in cases with germline BRCA1/2 mutations and deletions of chromosomes 17 (harboring TP53 and BRCA1) and 13 (harboring BRCA2), leading to a double “two-hit” involving TP53 and BRCA1/2. Tumor invasion was associated with the activation of interferon response pathways, epithelial–mesenchymal transition, and extracellular matrix remodeling. In summary, these results elucidate the earliest molecular landscape of ovarian precancerous lesions, serving as the foundation for future risk stratification to identify aggressive precancerous lesions. Significance: Integrated spatial multiomics analysis of ovarian precancerous lesions reveals molecular subtypes and mechanisms underlying tumor initiation, offering a foundation for future risk stratification and prevention. See related commentary by Soong et al. p. 1537