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ObjectiveEnhancer aberrations are beginning to emerge as a key epigenetic feature of colorectal cancers (CRC), however, a comprehensive knowledge of chromatin state patterns in tumour progression, heterogeneity of these patterns and imparted therapeutic opportunities remain poorly described.DesignWe performed comprehensive epigenomic characterisation by mapping 222 chromatin profiles from 69 samples (33 colorectal adenocarcinomas, 4 adenomas, 21 matched normal tissues and 11 colon cancer cell lines) for six histone modification marks: H3K4me3 for Pol II-bound and CpG-rich promoters, H3K4me1 for poised enhancers, H3K27ac for enhancers and transcriptionally active promoters, H3K79me2 for transcribed regions, H3K27me3 for polycomb repressed regions and H3K9me3 for heterochromatin.ResultsWe demonstrate that H3K27ac-marked active enhancer state could distinguish between different stages of CRC progression. By epigenomic editing, we present evidence that gains of tumour-specific enhancers for crucial oncogenes, such asASCL2andFZD10,was required for excessive proliferation. Consistently, combination of MEK plus bromodomain inhibition was found to have synergistic effects in CRC patient-derived xenograft models. Probing intertumour heterogeneity, we identified four distinct enhancer subtypes (EPIgenome-based Classification, EpiC), three of which correlate well with previously defined transcriptomic subtypes (consensus molecular subtypes, CMSs). Importantly, CMS2 can be divided into two EpiC subgroups with significant survival differences. Leveraging such correlation, we devised a combinatorial therapeutic strategy of enhancer-blocking bromodomain inhibitors with pathway-specific inhibitors (PARPi, EGFRi, TGFβi, mTORi and SRCi) for EpiC groups.ConclusionOur data suggest that the dynamics of active enhancer underlies CRC progression and the patient-specific enhancer patterns can be leveraged for precision combination therapy.

The feasibility of applying magnetic resonance imaging (MRI) for conducting prospective studies of intraperitoneal (i.p.) tumor treatment response to chemotherapy and resultant effects on survival in human ovarian carcinoma/nude mouse orthotopic xenograft models was evaluated. Female nude mice were implanted i.p. with either NMP-1 or SKOV-3ip. human ovarian carcinoma cells on day 0. Initial T2-weighted magnetic resonance (MR) images of the abdomens of NMP-1–implanted mice were obtained on day 7 to confirm the presence of nascent tumors; similar confirmations were made on day 14 with mice bearing SKOV-3ip. xenografts. On the initial imaging days, a multiple-dose regimen of cisplatin (CDDP; qd7 ×3) was commenced, using 4 or 6 mg/kg treatments with the NMP-1 model and using 6 mg/kg treatments with the SKOV-3ip. model. Mice were reimaged multiple times, 2 days following each CDDP injection and at later times as well, depending on host survival. The images for each mouse from the last imaging day (day 30 for NMP-1, day 44 for SKOV-3ip.) were used in a blinded fashion to attempt to visually distinguish control from treated mice and to determine whether MRI could predict a survival benefit. For SKOV-3ip. mice, ten out of ten mice were correctly segregated into the control or the CDDP treatment group based solely on these blinded, nonquantified MR results. In this model, the 6 mg/kg multiple-dose regimen achieved a modest response, improving life span by ∼24%. However, for the NMP-1 mice, only six out of nine evaluable mice were correctly segregated into the control or one of the treatment groups by similar MRI criteria, a virtually random distribution; further, neither CDDP treatment regimen achieved a significant improvement in survival in this model. In another study, NMP-1–implanted mice were treated on day 7 after tumor implantation with a single injection of a hyaluronic acid–paclitaxel copolymer. Control and treated mice were MR imaged on day 28, which revealed marked reductions in tumor burden in treated mice, correlating well with a subsequently observed improved survival of ∼40%. Our results suggest that MRI can be used to serially and noninvasively monitor treatment response and predict ongoing treatment effects on survival.