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Borgenvik A, Holmberg KO, Bolin S, Zhao M, Savov V, Rosén G, Hutter S, Garancher A, Suryo Rahmanto A, Bergström T, Olsen TK, Mainwaring OJ, Sattanino D, Verbaan AD, Rusert JM, Sundstrom A, Ballester Bravo M, Dang Y, Wenz AS, Richardson S, Fotaki G, Hill RM, Dubuc AM, Kalushkova A, Remke M, Cancer M, Jernberg-Wiklund H, Giraud G, Chen X, Taylor MD, Sangfelt O, Clifford SC, Schuller U, Wechsler-Reya RJ, Weishaupt H, Swartling FJ
Cancer Res. - (-) - [2022-10-11; online 2022-10-11]
Relapse is the leading cause of death in patients with medulloblastoma, the most common malignant pediatric brain tumor. A better understanding of the mechanisms underlying recurrence could lead to more effective therapies for targeting tumor relapses. Here, we observed that SOX9, a transcription factor and stem cell/glial fate marker, is limited to rare, quiescent cells in high-risk medulloblastoma with MYC amplification. In paired primary-recurrent patient samples, SOX9-positive cells accumulated in medulloblastoma relapses. SOX9 expression anti-correlated with MYC expression in murine and human medulloblastoma cells. However, SOX9-positive cells were plastic and could give rise to a MYC high state. To follow relapse at the single-cell level, an inducible dual Tet model of medulloblastoma was developed, in which MYC expression was redirected in vivo from treatment-sensitive bulk cells to dormant SOX9-positive cells using doxycycline treatment. SOX9 was essential for relapse initiation and depended on suppression of MYC activity to promote therapy resistance, epithelial-mesenchymal transition, and immune escape. p53 and DNA repair pathways were downregulated in recurrent tumors, while MGMT was upregulated. Recurrent tumor cells were found to be sensitive to treatment with an MGMT inhibitor and doxorubicin. These findings suggest that recurrence-specific targeting coupled with DNA repair inhibition comprises a potential therapeutic strategy in patients affected by medulloblastoma relapse.
Bioinformatics Support for Computational Resources [Service]
NGI Uppsala (SNP&SEQ Technology Platform) [Service]
National Genomics Infrastructure [Service]
PubMed 36219398
DOI 10.1158/0008-5472.CAN-22-2108
Crossref 10.1158/0008-5472.CAN-22-2108
pii: 709709