TY - JOUR T1 - Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance JF - bioRxiv DO - 10.1101/136564 SP - 136564 AU - Genevieve Stein-O’Brien AU - Luciane T Kagohara AU - Sijia Li AU - Manjusha Thakar AU - Ruchira Ranaweera AU - Hiroyuki Ozawa AU - Haixia Cheng AU - Michael Considine AU - Sandra Schmitz AU - Alexander V Favorov AU - Ludmila V Danilova AU - Joseph A Califano AU - Evgeny Izumchenko AU - Daria A Gaykalova AU - Christine H Chung AU - Elana J Fertig Y1 - 2018/01/01 UR - http://biorxiv.org/content/early/2018/02/27/136564.abstract N2 - BACKGROUND Targeted therapies specifically act by blocking the activity of proteins that are encoded by genes critical for tumorigenesis. However, most cancers acquire resistance and long-term disease remission is rarely observed. Understanding the time course of molecular changes responsible for the development of acquired resistance could enable optimization of patients’ treatment options. Clinically, acquired therapeutic resistance can only be studied at a single time point in resistant tumors. To determine the dynamics of these molecular changes, we obtained high throughput omics data weekly during the development of cetuximab resistance in a head and neck cancer in vitro model.RESULTS An unsupervised algorithm, CoGAPS, was used to quantify the evolving transcriptional and epigenetic changes. Applying a PatternMarker statistic to the results from CoGAPS enabled novel heatmap-based visualization of the dynamics in these time course omics data. We demonstrate that transcriptional changes result from immediate therapeutic response or resistance, whereas epigenetic alterations only occur with resistance. Integrated analysis demonstrates delayed onset of changes in DNA methylation relative to transcription, suggesting that resistance is stabilized epigenetically.CONCLUSIONS Genes with epigenetic alterations associated with resistance that have concordant expression changes are hypothesized to stabilize resistance. These genes include FGFR1, which was associated with EGFR inhibitor resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. Our findings provide a relevant towards better understanding of the time course progression of changes resulting in acquired resistance to targeted therapies. This is an important contribution to the development of alternative treatment strategies that would introduce new drugs before the resistant phenotype develops.List of abbreviationsAKTAKT serine/threonine kinaseATCCAmerican Type Culture CollectionCoGAPSCoordianted Gene Activity in Pattern SetsCTXcetuximabCTXRsingle cell cetuximab resistant cloneDNAdeoxyribonucleic acidEGFREndogenous Growth Factor ReceptorFDAFood and Drug AdministrationFGFR1Fibroblast Growth Factor Receptor 1GEOGene Expression OmnibusGSTP1Glutathione S-Transferase pi 1GWCoGAPSGenome Wide Coordinated Gene Activity in Pattern SetsHNSCCHead and neck squamous cell carcinomaHRASHRAS proto-oncogeneJHMIJohns Hopkins Medical InstitutionsLPFSLong-progression-free survivalMAPKMitogen activated kinase-like proteinNSCLCNon-small cell lung cancerPBSPhosphate buffered salinePI3KPhosphoinositide-3-kinase regulatory subunit 1RINRNA integrity numberRNARibonucleic acidRNA-seqRibonucleic acid sequencingrRNARibosomal ribonucleic acidSNPSingle nucleotide polymorphismSPFSShort-progression-free survivalSTRShort tandem repeatTCGAThe Cancer Genome AtlasTFAP2ATranscription factor AP-2 alpha ER -