Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance. (Methylation)

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. DNA methylation profiling was performed for 23 samples including 2 replicates of parental SCC25 cetuximab sensitive cell line, generations of SCC25 cell lines treated with either cetuximab or PBS over weeks (each week of treatment labeled C1 to C11), and a set of 11 stable cetuximab resistant clones derived from SCC25. Sequencing was performed at the Johns Hopkins Medical Institutions (JHMI) Deep Sequencing & Microarray Core Facility. Total RNA was isolated from a total of 1x106 cells using the AllPrep DNA/RNA Mini Kit (Qiagen, Hilden, Germany) following manufacturer’s instructions. The RNA concentration was determined by the spectrophotometer Nanodrop (Thermo Fisher Scientific, Waltham, MA) and quality was assessed using the 2100 Bioanalyzer (Agilent, Santa Clara, CA) system. An RNA Integrity Number (RIN) of 7.0 was considered as the minimum to be used in the subsequent steps for RNAseq. Library preparation was performed using the TrueSeq Stranded Total RNAseq Poly A1 Gold Kit (Illumina, San Diego, CA), according to manufacturer’s recommendations, followed by mRNA enrichment using poly(A) enrichment for ribosomal RNA (rRNA) removal. Sequencing was performed using the HiSeq platform (Illumina) for 2X100bp sequencing. Reads were aligned to hg19 with MapSplice16 and gene expression counts were quantified with RSEM17. Gene counts were upper-quartile normalized and log transformed for analysis following the RSEM v2 pipeline used to normalize TCGA RNA-seq data.