TY - JOUR
T1 - Combining gene mutation with gene expression data improves outcome prediction in myelodysplastic syndromes
AU - Gerstung, Moritz
AU - Pellagatti, Andrea
AU - Malcovati, Luca
AU - Giagounidis, Aristoteles
AU - Della Porta, Matteo G.
AU - Jädersten, Martin
AU - Dolatshad, Hamid
AU - Verma, Amit
AU - Cross, Nicholas C.P.
AU - Vyas, Paresh
AU - Killick, Sally
AU - Hellström-Lindberg, Eva
AU - Cazzola, Mario
AU - Papaemmanuil, Elli
AU - Campbell, Peter J.
AU - Boultwood, Jacqueline
N1 - Publisher Copyright:
© 2015 Macmillan Publishers Limited. All rights reserved.
PY - 2015/1/9
Y1 - 2015/1/9
N2 - Cancer is a genetic disease, but two patients rarely have identical genotypes. Similarly, patients differ in their clinicopathological parameters, but how genotypic and phenotypic heterogeneity are interconnected is not well understood. Here we build statistical models to disentangle the effect of 12 recurrently mutated genes and 4 cytogenetic alterations on gene expression, diagnostic clinical variables and outcome in 124 patients with myelodysplastic syndromes. Overall, one or more genetic lesions correlate with expression levels of ∼20% of all genes, explaining 20-65% of observed expression variability. Differential expression patterns vary between mutations and reflect the underlying biology, such as aberrant polycomb repression for ASXL1 and EZH2 mutations or perturbed gene dosage for copy-number changes. In predicting survival, genomic, transcriptomic and diagnostic clinical variables all have utility, with the largest contribution from the transcriptome. Similar observations are made on the TCGA acute myeloid leukaemia cohort, confirming the general trends reported here.
AB - Cancer is a genetic disease, but two patients rarely have identical genotypes. Similarly, patients differ in their clinicopathological parameters, but how genotypic and phenotypic heterogeneity are interconnected is not well understood. Here we build statistical models to disentangle the effect of 12 recurrently mutated genes and 4 cytogenetic alterations on gene expression, diagnostic clinical variables and outcome in 124 patients with myelodysplastic syndromes. Overall, one or more genetic lesions correlate with expression levels of ∼20% of all genes, explaining 20-65% of observed expression variability. Differential expression patterns vary between mutations and reflect the underlying biology, such as aberrant polycomb repression for ASXL1 and EZH2 mutations or perturbed gene dosage for copy-number changes. In predicting survival, genomic, transcriptomic and diagnostic clinical variables all have utility, with the largest contribution from the transcriptome. Similar observations are made on the TCGA acute myeloid leukaemia cohort, confirming the general trends reported here.
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U2 - 10.1038/ncomms6901
DO - 10.1038/ncomms6901
M3 - Article
C2 - 25574665
AN - SCOPUS:84928348527
SN - 2041-1723
VL - 6
JO - Nature communications
JF - Nature communications
M1 - 5901
ER -