Liisa Kauppi

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.

Tracing back primed resistance in cancer via sister cells

Abstract Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. Here, we present ReSisTrace that uses shared transcriptomic features of sister cells to predict the states priming treatment resistance. Applying ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells reveals pre-resistant phenotypes defined by proteostatic and mRNA surveillance features, reflecting traits enriched in the upcoming subclonal selection. Furthermore, we show that DNA repair deficiency renders cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leverage the obtained pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.

Ex Vivo Immuno-Oncology Platform Reveals Spatial T-cell Infiltration Patterns Linked to ATR Inhibition Responses in High-Grade Serous Ovarian Cancer

Abstract Identifying new therapeutic approaches in high-grade serous ovarian cancer (HGSC) requires the development of more accurate preclinical models that replicate the patient-specific tumor and its microenvironment. To address this, we established immunocompetent patient-derived cultures (iPDC) for HGSC, cultured on a physiologically relevant human omentum gel matrix. We developed a high-throughput platform that combines drug testing, histologic analysis, genomic profiling, single-cell studies, and spatial biomarker discovery. Our results from 47 tumors showed that iPDCs recapitulated the tumor genomic and histologic characteristics while also retaining the intratumoral immune cells. The iPDC treatment responses correlated significantly with the patients’ clinical treatment responses. Using iPDCs and single-cell RNA sequencing, we identified potentially effective therapeutic options for patients with recurrent HGSC linked to distinct tumor cell states and mechanisms of resistance. High-throughput drug response profiling with single-cell imaging identified ataxia telangiectasia and Rad3-related inhibitor (ATRi) combined with an immunotherapy targeting autotaxin as a promising new combination treatment for HGSC. Using hyperplexed imaging and spatial analysis, we discovered that ATRi responses were associated with significant increases in both intra- and peritumoral T-cell infiltration, particularly in PD-1+ CD8+ T cells. Additionally, the ATRi-induced reactivation of CD8+ T cells was linked to spatial interactions with replication stress–positive tumor cells. Thus, our iPDC platform presents a representative high-throughput ex vivo model to advance precision oncology in HGSC, uncovering the ATRi-immunotherapy combination as a potentially effective therapeutic option for clinical translation.