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Lupia, M.

Publications and source records attributed to Lupia, M..

3 recordsLinked to original sources

Matrix Gla Protein acts as a driver of stemness and tumor initiation in ovarian cancer

Ovarian cancer (OC) displays the highest mortality among gynecological tumors, mainly due to early peritoneal dissemination, the high frequency of tumor relapse following primary debulking and the development of chemoresistance. All these events are thought to be initiated and sustained by a subpopulation of neoplastic cells, termed ovarian cancer stem cells (OCSC), that are endowed with self-renewing and tumor-initiating properties. This implies that interfering with OCSC function should offer novel therapeutic perspectives to defeat OC progression. To this aim, a better understanding of the molecular and functional makeup of OCSC in clinically relevant model systems is essential. We have profiled the transcriptome of OCSC vs. their bulk cell counterpart from a panel of patient-derived OC cell cultures. This revealed that Matrix Gla Protein (MGP), classically known as a calcification-preventing factor in cartilage and blood vessels, is markedly enriched in OCSC. Functional assays showed that MGP confers several stemness-associated traits to OC cells, including a transcriptional reprogramming. Patient-derived organotypic cultures pointed to the peritoneal microenvironment as a major inducer of MGP expression in OC cells. Furthermore, MGP was found to be necessary and sufficient for tumor initiation in OC mouse models, by shortening tumor latency and increasing dramatically the frequency of tumor-initiating cells. Mechanistically, MGP-driven OC stemness was mediated by the stimulation of Hedgehog signaling, in particular through the induction of the Hedgehog effector GLI1, thus highlighting a novel MGP/Hedgehog pathway axis in OCSC. Finally, MGP expression was found to correlate with poor prognosis in OC patients, and was increased in tumor tissue after chemotherapy, supporting the clinical relevance of our findings. Thus, MGP is a novel driver in OCSC pathophysiology, with a major role in stemness and in tumor initiation.

cancer biology↗

A cell-of-origin epigenetic tracer reveals clinically distinct subtypes of high grade serous ovarian cancer

High grade serous ovarian cancer (HGSOC) is a major unmet need in oncology. The persistent uncertainty on its originating tissue has contributed to hamper the discovery of oncogenic pathways and effective therapies. Here we define the DNA methylation print that distinguishes the human fimbrial (FI) and ovarian surface epithelia (OSE) and develop a robust epigenetic cell-of-origin tracer that stratifies HGSOC in FI-and OSE-originated tumors across all available cohorts. We translate this origin-based stratification into a clinically actionable transcriptomic signature, demonstrating its prognostic impact on patients survival and identifying novel network level dysregulations specific for the two disease subtypes.

cancer biology↗

Single cell derived organoids capture the self-renewing subpopulations of metastatic ovarian cancer

High Grade Serous Ovarian cancer (HGSOC) is a major unmet need in oncology, due to its precocious dissemination and the lack of meaningful human models for the investigation of disease pathogenesis in a patient-specific manner. To overcome this roadblock, we present a new method to isolate and grow single cells directly from patients ascites, establishing the conditions for propagating them as single-cell derived ovarian cancer organoids (scOCOs). By single cell RNA sequencing (scRNAseq) we define the cellular composition of metastatic ascites and trace its propagation in 2D and 3D culture paradigms, finding that scOCOs retain and amplify key subpopulations from the original patients samples and recapitulate features of the original metastasis that do not emerge from classical 2D culture, including retention of individual patients specificities. By enabling the enrichment of uniquely informative cell subpopulations from HGSOC metastasis and the clonal interrogation of their diversity at the functional and molecular level, this method transforms the prospects of precision oncology for ovarian cancer.

cancer biology↗