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Sartini, S.

Publications and source records attributed to Sartini, S..

2 recordsLinked to original sources

The landscape of drug sensitivity and resistance in sarcoma

Sarcomas are a family of rare malignancies composed of over 100 distinct histological subtypes. The rarity of sarcoma poses significant challenges in conducting clinical trials to identify effective therapies, to the point that many rarer subtypes of sarcoma do not have standard-of-care treatment. Even for established regimens, there can be substantial heterogeneity in responses. Overall, novel, personalized approaches for identifying effective treatments are needed to improve patient out-comes. Patient-derived tumor organoids (PDTOs) are clinically relevant models representative of the physiological behavior of tumors across an array of malignancies. Here, we use PDTOs as a tool to better understand the biology of individual tumors and characterize the landscape of drug resistance and sensitivity in sarcoma. We collected n=194 specimens from n=126 sarcoma patients, spanning 24 distinct subtypes. We characterized PDTOs established from over 120 biopsy, resection, and metastasectomy samples. We leveraged our organoid high-throughput drug screening pipeline to test the efficacy of chemotherapeutics, targeted agents, and combination therapies, with results available within a week from tissue collection. Sarcoma PDTOs showed patient-specific growth characteristics and subtype-specific histopathology. Organoid sensitivity correlated with diagnostic subtype, patient age at diagnosis, lesion type, prior treatment history, and disease trajectory for a subset of the compounds screened. We found 90 biological pathways that were implicated in response to treatment of bone and soft tissue sarcoma organoids. By comparing functional responses of organoids and genetic features of the tumors, we show how PDTO drug screening can provide an orthogonal set of information to facilitate optimal drug selection, avoid ineffective therapies, and mirror patient outcomes in sarcoma. In aggregate, we were able to identify at least one effective FDA-approved or NCCN-recommended regimen for 59% of the specimens tested, providing an estimate of the proportion of immediately actionable information identified through our pipeline. HighlightsO_LIStandardized organoid culture preserve unique sarcoma histopathological features C_LIO_LIDrug screening on patient-derived sarcoma organoids provides sensitivity information that correlates with clinical features and yields actionable information for treatment guidance C_LIO_LIHigh-throughput screenings provide orthogonal information to genetic sequencing C_LIO_LISarcoma organoid response to treatment correlates with patient response to therapy C_LIO_LILarge scale, functional precision medicine programs for rare cancers are feasible within a single institution C_LI

cancer biology↗

Mutated clones driving leukemic transformation are already detectable at the single cell level in CD34-positive cells in the chronic phase of primary myelofibrosis

Disease progression of myeloproliferative neoplasms is the result of increased genomic complexity. Since the ability to predict disease evolution is crucial for clinical decision, we studied single cell genomics and transcriptomics of CD34-positive cells from a primary myelofibrosis (PMF) patient who progressed to acute myeloid Leukemia (AML) while receiving Ruxolitinib. Single cell genomics allowed the reconstruction of clonal hierarchy and demonstrated that TET2 was the first mutated gene while FLT3 was the last one. Disease evolution was accompanied by increased clonal heterogeneity and mutational rate, but clones carrying TP53 and FLT3 mutations were already present in chronic phase. Single cell transcriptomics unraveled repression of interferon signaling suggesting an immunosuppressive effect exerted by Ruxolitinib. Moreover, AML transformation was associated with a differentiative block and immune escape. These results suggest that single cell analysis can unmask tumor heterogeneity and provide meaningful insights about PMF progression that might guide personalized therapy.

cancer biology↗