Low expression of ANT1 confers oncogenic properties to rhabdomyosarcoma tumor cells by modulating metabolism and death pathways
Rhabdomyosarcoma (RMS) is the most frequent form of pediatric soft-tissue sarcoma. It is divided into two main subtypes: ERMS (embryonal) and ARMS (alveolar). Current treatments are based on chemotherapy, surgery, and radiotherapy. The 5-year survival rate has plateaued at 70% since 2000, despite several clinical trials. RMS cells are thought to derive from the muscle lineage. During development, myogenesis includes the expansion of muscle precursors, the elimination of those in excess by cell death and the differentiation of the remaining ones into myofibers. The notion that these processes may be hijacked by tumor cells to sustain their oncogenic transformation has emerged, with RMS being considered as the dark side of myogenesis. Thus, dissecting myogenic developmental programs could improve our understanding of RMS molecular etiology. We focused herein on ANT1, which is involved in myogenesis and is responsible for genetic disorders associated with muscle degeneration. ANT1 is a mitochondrial protein, which has a dual functionality, as it is involved both in metabolism via the regulation of ATP/ADP release from mitochondria and in regulated cell death as part of the mitochondrial permeability transition pore. Bioinformatics analyses of transcriptomic datasets revealed that ANT1 is expressed at low levels in RMS. Using the CRISPR-Cas9 technology, we showed that reduced ANT1 expression confers selective advantages to RMS cells in terms of proliferation and resistance to stress-induced death. These effects arise notably from an abnormal metabolic switch induced by ANT1 downregulation. Restoration of ANT1 expression using a Tet-On system is sufficient to prime tumor cells to death and to increase their sensitivity to chemotherapy. Based on our results, modulation of ANT1 expression and/or activity appears as an appealing therapeutic approach in RMS management.Keywords: Cell death; Paediatric cancer.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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