Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance

Genevieve Stein-O'Brien, Luciane T. Kagohara, Sijia Li, Manjusha Thakar, Ruchira Ranaweera, Hiroyuki Ozawa, Haixia Cheng, Michael Considine, Sandra Schmitz, Alexander V. Favorov, Ludmila V. Danilova, Joseph A. Califano, Evgeny Izumchenko, Daria A. Gaykalova, Christine H. Chung, Elana J. Fertig

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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. Methods: To determine the dynamics of these molecular changes, we obtained high throughput omics data (RNA-sequencing and DNA methylation) weekly during the development of cetuximab resistance in a head and neck cancer in vitro model. The CoGAPS unsupervised algorithm was used to determine the dynamics of the molecular changes associated with resistance during the time course of resistance development. Results: 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 the resistant phenotype. These genes include FGFR1, which was associated with EGFR inhibitors resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. This understanding of the time course progression of molecular changes in acquired resistance is important for the development of alternative treatment strategies that would introduce appropriate selection of new drugs to treat cancer before the resistant phenotype develops.

Original languageEnglish
Article number37
JournalGenome Medicine
Volume10
Issue number1
DOIs
Publication statusPublished - 2018 May 23

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Epigenomics
DNA Methylation
Molecular Dynamics Simulation
RNA Sequence Analysis
Phenotype
Therapeutics
Neoplasms
Head and Neck Neoplasms
Genes
Carcinogenesis
Pharmaceutical Preparations
Proteins

Keywords

  • Acquired resistance
  • Data integration
  • Epigenetics
  • Genomics
  • Precision medicine
  • Time course analysis

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Genetics(clinical)

Cite this

Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance. / Stein-O'Brien, Genevieve; Kagohara, Luciane T.; Li, Sijia; Thakar, Manjusha; Ranaweera, Ruchira; Ozawa, Hiroyuki; Cheng, Haixia; Considine, Michael; Schmitz, Sandra; Favorov, Alexander V.; Danilova, Ludmila V.; Califano, Joseph A.; Izumchenko, Evgeny; Gaykalova, Daria A.; Chung, Christine H.; Fertig, Elana J.

In: Genome Medicine, Vol. 10, No. 1, 37, 23.05.2018.

Research output: Contribution to journalArticle

Stein-O'Brien, G, Kagohara, LT, Li, S, Thakar, M, Ranaweera, R, Ozawa, H, Cheng, H, Considine, M, Schmitz, S, Favorov, AV, Danilova, LV, Califano, JA, Izumchenko, E, Gaykalova, DA, Chung, CH & Fertig, EJ 2018, 'Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance', Genome Medicine, vol. 10, no. 1, 37. https://doi.org/10.1186/s13073-018-0545-2
Stein-O'Brien, Genevieve ; Kagohara, Luciane T. ; Li, Sijia ; Thakar, Manjusha ; Ranaweera, Ruchira ; Ozawa, Hiroyuki ; Cheng, Haixia ; Considine, Michael ; Schmitz, Sandra ; Favorov, Alexander V. ; Danilova, Ludmila V. ; Califano, Joseph A. ; Izumchenko, Evgeny ; Gaykalova, Daria A. ; Chung, Christine H. ; Fertig, Elana J. / Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance. In: Genome Medicine. 2018 ; Vol. 10, No. 1.
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AU - Kagohara, Luciane T.

AU - Li, Sijia

AU - Thakar, Manjusha

AU - Ranaweera, Ruchira

AU - Ozawa, Hiroyuki

AU - Cheng, Haixia

AU - Considine, Michael

AU - Schmitz, Sandra

AU - Favorov, Alexander V.

AU - Danilova, Ludmila V.

AU - Califano, Joseph A.

AU - Izumchenko, Evgeny

AU - Gaykalova, Daria A.

AU - Chung, Christine H.

AU - Fertig, Elana J.

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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. Methods: To determine the dynamics of these molecular changes, we obtained high throughput omics data (RNA-sequencing and DNA methylation) weekly during the development of cetuximab resistance in a head and neck cancer in vitro model. The CoGAPS unsupervised algorithm was used to determine the dynamics of the molecular changes associated with resistance during the time course of resistance development. Results: 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 the resistant phenotype. These genes include FGFR1, which was associated with EGFR inhibitors resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. This understanding of the time course progression of molecular changes in acquired resistance is important for the development of alternative treatment strategies that would introduce appropriate selection of new drugs to treat cancer before the resistant phenotype develops.

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KW - Precision medicine

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