GE-17ALTERATION OF THE p53 PATHWAY AND ANCESTRAL PROGENITORS ARE ASSOCIATED WITH TUMOR RECURRENCE IN GLIOBLASTOMA.
2014
To evaluate evolutionary patterns of GBM recurrence, we analyzed whole genome sequencing (WGS) and multi-sector exome sequencing data from pairs of primary and posttreatment GBM. WGS on ten primary-recurrent pairs detected a median number of 12,214 mutations which we utilized to uncover clonal structures, by analyzing the distribution of mutation cellular frequencies (the fraction of tumor cells harboring a mutation). On average, 41 % of the mutations were shared by primary and recurrence. The majority of shared mutations were clonal in both primary and recurrence, but we also observed many clonal mutations that were uniquely detected in either the primary or the recurrence. This raises the intriguing possibility that major tumor clones in the primary tumor and disease relapse both evolved from a shared ancestral tumor cell population. At least one subclone was identified in the majority of WGS samples, and we observed groups of mutations that were at low cancer cell fractions in both primary and recurrence, suggesting that both subclones evolved from the same ancestral tumor cells separate from the major clone ancestral cells. To address the possibility that the lack of overlap between subsequent tumors was due to intratumoral heterogeneity, we analyzed exome sequencing from a second tumor sector of seven primary and six recurrent tumors. We found that the majority of "second biopsy" mutations were not conserved between time points, suggesting that intratumoral heterogeneity did not explain the large number of mutations uniquely detected in primary and recurrence. The limited overlap of mutations in primary and recurrence provides evidence for ancestral tumor cell populations that could not be eradicated by therapy, while offspring cell populations contained unique mutations, were selectively killed by treatment and could therefore no longer be detected after disease relapse. This study has provided new insights into patterns and dynamics of tumor evolution.
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