Abstract High-grade serous ovarian cancer (HGSOC) is thought to progress from a series of precursor lesions in the fallopian tube epithelium (FTE). One of the preneoplastic lesions found in the FTE is called a secretory cell outgrowth (SCOUT), which is partially defined by a loss of paired box 2 (PAX2). In the present study, we developed PAX2-deficient murine cell lines in order to model a SCOUT and to explore the role of PAX2 loss in the etiology of HGSOC. Loss of PAX2 alone in the murine oviductal epithelium (MOE) did not induce changes in proliferation, migration and survival in hypoxia or contribute to resistance to first line therapies, such as cisplatin or paclitaxel. RNA sequencing of MOE PAX2shRNA cells revealed significant alterations in the transcriptome. Silencing of PAX2 in MOE cells produced a messenger RNA expression pattern that recapitulated several aspects of the transcriptome of previously characterized human SCOUTs. RNA-seq analysis and subsequent qPCR validation of this SCOUT model revealed an enrichment of genes involved in estrogen signaling and an increase in expression of estrogen receptor α. MOE PAX2shRNA cells had higher estrogen signaling activity and higher expression of putative estrogen responsive genes both in the presence and absence of exogenous estrogen. In summary, loss of PAX2 in MOE cells is sufficient to transcriptionally recapitulate a human SCOUT, and this model revealed an enrichment of estrogen signaling as a possible route for tumor progression of precursor lesions in the fallopian tube.

High-grade serous ovarian cancer (HGSOC) is the most lethal gynecological malignancy that is primarily detected at the metastatic stage. Most HGSOC originates from the fallopian tube epithelium (FTE) and metastasizes to the ovary before invading the peritoneum; therefore, it is crucial to study disease initiation and progression using FTE-derived models. We previously demonstrated that loss of PTEN from the FTE leads to ovarian cancer. In the present study, loss of PTEN in FTE led to the enrichment of cancer stem cell markers such as LGR5, WNT4, ALDH1, CD44. Interestingly, loss of the transcription factor PAX2, which is a common and early alteration in HGSOC, played a pivotal role in the expression of cancer stem-like cells (CSC) markers and cell function. In addition, loss of PTEN led to the generation of two distinct subpopulations of cells with different CSC marker expression, tumorigenicity, and chemoresistance profiles. Taken together, these data suggest that loss of PTEN induces reprogramming of the FTE cells into a more stem-like phenotype due to loss of PAX2 and provides a model to study early events during the FTE-driven ovarian cancer tumor formation.

Adenosine triphosphate (ATP) and its metabolites drive microglia migration and cytokine production by activating P2X- and P2Y- class purinergic receptors. Purinergic receptor activation gives rise to diverse intracellular calcium (Ca2+ signals, or waveforms, that differ in amplitude, duration, and frequency. Whether and how these characteristics of diverse waveforms influence microglia function is not well-established. We developed a computational model trained with data from published primary murine microglia studies. We simulate how purinoreceptors influence Ca2+ signaling and migration, as well as, how purinoreceptor expression modifies these processes. Our simulation confirmed that P2 receptors encode the amplitude and duration of the ATP-induced Ca2+ waveforms. Our simulations also implicate CD39, an ectonucleotidase that rapidly degrades ATP, as a regulator of purinergic receptor-induced Ca2+ responses. Namely, it was necessary to account for CD39 metabolism of ATP to align the model’s predicted purinoreceptor responses with published experimental data. In addition, our modeling results indicate that small Ca2+ transients accompany migration, while large and sustained transients are needed for cytokine responses. Lastly, as a proof-of-principal, we predict Ca2+ transients and cell membrane displacements in a BV2 microglia cell line using published P2 receptor mRNA data to illustrate how our computer model may be extrapolated to other microglia subtypes. These findings provide important insights into how differences in purinergic receptor expression influence microglial responses to ATP.