bioRxivCancer Biology
Characterization of the minimal residual disease state reveals distinct evolutionary trajectories of human glioblastoma
M. A. Qazi, S. K. Salim, K. R. Brown, N. Mikolajewicz, N. Savage, H. Han, M. K. Subapanditha, D. Bakhshinyan, A. Nixon, P. Vora, K. Desmond, C. Chokshi, M. Singh, A. Khoo, A. Macklin, S. Khan, N. Tatari, N. Winegarden, L. M. Richards, T. Pugh, N. Bock, A. Mansouri, C. Venugopal, T. R. Kislinger, S. Goyal, , S. K. Singh
Abstract
Recurrence of solid tumors renders patients vulnerable to a distinctly advanced, highly treatment-refractory disease state that has an increased mutational burden and novel oncogenic drivers not detected at initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cancer cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profiled barcoded tumor stem cell populations through therapy at tumor initiation/engraftment, MRD and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors showed distinct patterns of recurrence in which clonal populations exhibited either an a priori, pre-existing fitness advantage, or a priori equipotency fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing revealed a tumor-intrinsic immunomodulatory signature with strong prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from GBM patients at all stages of disease. Our results provide insight into the innate and therapy-driven dynamics of human GBM, and the prognostic value of interrogating the MRD state in solid cancers.
- organism: human
- assay: bulk RNA-seq
- assay: scRNA-seq
- assay: proteomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: protein structure prediction
- approach: experimental assay
- approach: statistical model
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