Mathematical Discovery and Computational Validation of Two Orthogonal Mechanistically-Driven Whole-Genome Genotype–Survival Phenotype Relationships in Pediatric Neuroblastoma Nerve Cancer
DescriptionPrediction, together with understanding and management, of pediatric neuroblastoma (NBL) outcomes, from spontaneous regression to relapse and death, remain limited, and rely mostly on age, stage, and the one-gene test for MYCN amplification, none of which are NBL specific. Here, we use the generalized singular value decomposition (GSVD), formulated as a multi-tensor decomposition [1], to model whole genomes of patient-matched NBL and blood DNA. The GSVD discovers two orthogonal genome-wide patterns of copy-number alterations (CNAs) in the tumors that are correlated with survival. First, as in previous, experimentally validated, models of, e.g., adult brain astrocytoma [2], one pattern is exclusive to the tumors. Previously unseen is a pattern that is common to both the blood and tumor genomes. Second, both patterns predict survival better than and independent of the existing predictors as well as independent of each other. In both patterns, differential RNA expression consistently map to the DNA CNAs. Third, the GSVD separates these patterns from normal variations that are conserved in the tumors but do not predict outcome, e.g., the male-specific X-chromosome deletion relative to the autosome. We computationally validate both patterns by using – and demonstrating for the first time – the pseudoinverse projection for transfer learning from the ≈3M-bin whole-genome to ≈10K-bin target-capture sequencing profiles of a mutually-exclusive set of patients [3]. We show that the two patterns describe independent, yet complementary cellular mechanisms that transform human normal to tumor cells, predict new personalized therapies, and may predict the response to existing therapies. The tumor-exclusive pattern includes co-occurrence of MYCN amplification with previously unrecognized druggable CNAs, including amplifications of genes encoding for extra-embryonic transcripts, to jointly predict survival. The pattern that is common to the blood and tumor genomes describes an earlier stage in NBL development, where the embryonic program is hijacked toward aneuploidy and where the subsequent tumor development can spontaneously regress via embryonic self-correction.
[1] M. W. Bradley, K. A. Aiello, S. P. Ponnapalli,* H. A. Hanson* and O. Alter, "GSVD- and Tensor GSVD-Uncovered Patterns of DNA Copy-Number Alterations Predict Adenocarcinomas Survival in General and in Response to Platinum," Applied Physics Letters (APL) Bioengineering 3 (3), article 036104 (August 2019);
[2] S. P. Ponnapalli, M. W. Bradley, K. Devine, J. Bowen, S. E. Coppens, K. M. Leraas, B. A. Milash, F. Li, H. Luo, S. Qiu, K. Wu, H. Yang, C. T. Wittwer, C. A. Palmer, R. L. Jensen, J. M. Gastier-Foster, H. A. Hanson, J. S. Barnholtz-Sloan and O. Alter, "Retrospective Clinical Trial Experimentally Validates Glioblastoma Genome-Wide Pattern of DNA Copy-Number Alterations Predictor of Survival," Applied Physics Letters (APL) Bioengineering 4 (2), article 026106 (May 2020);
[3] O. Alter and G. H. Golub, "Integrative Analysis of Genome-Scale Data by Using Pseudoinverse Projection Predicts Novel Correlation between DNA Replication and RNA Transcription," Proceedings of the National Academy of Sciences (PNAS) USA 101 (47), pp. 16577–16582 (November 2004);
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TimeSunday, 13 November 20229:15am - 9:30am CST
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