Single-cell analysis of hepatoblastoma identifies tumor signatures that predict chemotherapy susceptibility using patient-specific tumor spheroids

肝母细胞瘤的单细胞分析利用患者特异性肿瘤球体识别可预测化疗敏感性的肿瘤特征

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作者:Hanbing Song #, Simon Bucher #, Katherine Rosenberg, Margaret Tsui, Deviana Burhan, Daniel Hoffman, Soo-Jin Cho, Arun Rangaswami, Marcus Breese, Stanley Leung, María V Pons Ventura, E Alejandro Sweet-Cordero, Franklin W Huang, Amar Nijagal, Bruce Wang

Abstract

Pediatric hepatoblastoma is the most common primary liver cancer in infants and children. Studies of hepatoblastoma that focus exclusively on tumor cells demonstrate sparse somatic mutations and a common cell of origin, the hepatoblast, across patients. In contrast to the homogeneity these studies would suggest, hepatoblastoma tumors have a high degree of heterogeneity that can portend poor prognosis. In this study, we use single-cell transcriptomic techniques to analyze resected human pediatric hepatoblastoma specimens, and identify five hepatoblastoma tumor signatures that may account for the tumor heterogeneity observed in this disease. Notably, patient-derived hepatoblastoma spheroid cultures predict differential responses to treatment based on the transcriptomic signature of each tumor, suggesting a path forward for precision oncology for these tumors. In this work, we define hepatoblastoma tumor heterogeneity with single-cell resolution and demonstrate that patient-derived spheroids can be used to evaluate responses to chemotherapy.

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