Chromatin state dynamics confers specific therapeutic strategies in enhancer subtypes of colorectal cancer

Abstract

Objective: Enhancer 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.

Design: We 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.

Results: We 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 as ASCL2 and FZD10, 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.

Conclusion: Our data suggest that the dynamics of active enhancer underlies CRC progression and the patient-specific enhancer patterns can be leveraged for precision combination therapy.

Keywords: adenocarcinoma; cancer genetics; colon carcinogenesis; colorectal cancer.

Fig. 1.. H3K27ac-identified global enhancer pattern could differentiate colorectal cancer from normal colon.

A. Emission probabilities of ChromHMM-based 10-chromatin state calls, which is based on the global distribution of combinatorial patterns of 6 histone marks (H3K4me1, H3K27ac, H3K4me3, H3K27me3, H3K79me2, and H3K9me3) from 13 adenocarcinomas and 12 adjacent normal tissues. Each row is representative of a combinatorial chromatin state pattern, which is annotated on the right based on the constituent histone mark and neighborhood plot (Supplementary Fig. S1B). Columns represent each histone mark. Colors represent the frequency of occurrence of that mark in the corresponding chromatin state on a scale of 0 (white) to 1 (blue). B. Multidimensional scaling (MDS) plot for chromatin state 5 between normal tissues (blue) and adenocarcinoma samples (red). C. MDS plot for global H3K27ac patterns in the adenomas (A), adenocarcinomas (T), adjacent normal colon (N) and cancer cell lines. Adenoma samples are spread over normal and tumor samples and cannot be distinguished with use of H3K27ac. Red, Green, Blue and Purple colors were used for Tumor, Adenoma, Normal Colon and CRC cell lines respectively. D. Venn diagram showing overlaps between total number of H3K27ac-defined active enhancer peaks in normal samples (blue), adenomas (green) and CRC tumors (red). E. Venn diagram showing overlaps between total number of super-enhancer peaks (called using ROSE) in normal samples (blue), adenomas (green) and CRC tumors (red). F. List of significantly enriched pathways in genes targeted by enhancers specific to CRC tumors (T), adenomas (A), and normal colon tissue (N). q-values are shown and are color-coded based on the level of significance. G. Integrative Genomics Viewer (IGV) images showing enrichment of H3K27ac peaks around ASCL2, SALL4 and FZD10 genes using aggregate ChIP-seq profiles of normal colon, adenoma and CRC tumors. H. Violin plots showing mRNA expression levels for ASCL2, SALL4 and FZD10 in adenomas, the adenocarcinoma cohort used in this study (labeled as MDACC) and TCGA adenocarcinoma cohort. The reported p-values were calculated using the DESeq2. I. List of enriched transcription factor (TF) motifs in CRC- or normal tissue-specific active enhancers. Motifs are identified using HOMER on the basis of the shared H3K27ac peak in each group.

Fig. 2.. Inactivation of top tumor-specific enhancers leads to transcriptional downregulation and loss of cell proliferation.

A. Volcano plot showing top CRC-enriched typical enhancers ranked based on fold-change and p-value. Top de novo gained enhancers among tumor (n = 33) as compared to adjacent normal (n = 15) samples are annotated according to their associated genes. Thresholds of log2FC > 1 and FDR < 0.05 are used to annotate de novo enhancer peaks. ASCL2 and FZD10 enhancers are among this subset of highly enriched regions. There are two top ranked enhancer peaks around FZD10 gene. B. Interaction map of active enhancers (E) with the gene promoter (P) around the ASCL2 locus as determined in SW480 cell line by HiChIP. Interactions were observed in a super-enhancer (E1–E3) region located ~70kb upstream of ASCL2 promoter (PET counts=9, q-value=3.2e⁻⁰⁷). These regions are among the highly enriched tumor-specific enhancers and were present in multiple CRC cell lines (Supplementary Fig. S4A). C. Bar graph showing relative enrichment of H3K27ac as derived from a ChIP-qPCR experiment on E1–E3 for ASCL2 super-enhancer (from panel B) in SW480 cells harboring specific or non-targeting (NT) gRNAs to these enhancers. Y-axis represents fold change in intensity of H3K27ac signal for each enhancer in gRNA harboring cell in comparison to the cells harboring NT gRNA. Asterisk * denotes p-value < 0.05. D. Bar graph showing relative ASCL2 mRNA expression in E1–E3 gRNAs for ASCL2 super-enhancer harboring SW480 cells in comparison to parental cells (ASCL2_NT). E. Growth curve showing relative viability of SW480 cells harboring E1–E3 for ASCL2 super-enhancer in comparison to parental cell (ASCL2_NT) showing lower rates of proliferation in cells with ASCL2-inactivated enhancers. F. Growth curves for LGR5-silenced SW480 cells (SW480^LGR5-KD) in comparison to the parental cells upon treatment with increasing concentrations of two preparations of antibody-drug conjugate (ADC) with bromodomain inhibitor (RVX208) conjugated to LGR5 antibody (ADC-Prep1 and ADC-Prep2) and RVX-208 alone. Y-axis shows percent viability of treated cells in comparison to control (DMSO) treated cells. G. Growth curves for a patient-derived CRC organoid upon treatment with LGR5-RVX208 conjugate (ADC). Y-axis shows percent viability of treated cells in comparison to control (DMSO) treated cells.

Fig. 3.. BRDi plus MEKi shows differential responses in different PDX models.

A. Tumor volume curves for C1138, F3053, F3008, and B8131 on treatment with MEK inhibitors (trametinib), BRD inhibitor (i-BET151), and a combination of MEK and BRD inhibitors (trametinib + i-BET151) along with the control vehicle group (n = 3–5 for each arm). P-values represent pairwise t test comparison between the experimental arm to vehicle treatment. *= p < 0.05; ** = p < 0.01; *** = p < 0.001; **** = p < 0.0001. Please refer to Supplementary Fig. S6B for all pair-wise comparisons of the p-values. B. Tumor volume curves for C1138, F3053, F3008, and B8131 on treatment with MEK inhibitor (binimetinib), BRD inhibitor (i-BET151), and a combination of MEK and BRD inhibitors (binimetinib + iBET151) along with the control vehicle group (n = 3–5 for each arm). P-values represent pairwise t test comparison between the experimental arm to vehicle treatment. * = p < 0.05; ** = p < 0.01; *** = p < 0.001; **** = p < 0.0001. Please refer to Supplementary Fig. S6B for all pair-wise comparisons of the p-values. C. Heatmap (top panel) and average intensity plot (bottom panel) for H3K27ac peaks in vehicle, trametinib, iBET-151 and combination (iBET-151 plus trametinib) treated PDXs, B8131 (responder) and C1138 (non-responder). D. Elsevier pathways (identified by Enricher) enriched in gene targets of H3K27ac peaks unique to C1138 versus B8131 PDXs. E. Box plots showing protein expression (RPPA) of GRB2, S6K1 and IGFBP2 enriched in C1138 versus B8131 PDXs. F. Differential pathways between those enriched in gene targets of lost H3K27ac-peaks in iBET-151 versus control treated B8131 and C1138. G. IGV snapshots of H3K27ac peaks around SMAD7, GRB2, AKT2 and FZD5 in vehicle, trametinib, iBET-151 and combination (iBET-151 plus trametinib) treated B8131 and C1138.

Fig. 4.. Reclassification of colorectal cancer tumors based on their global enhancer distribution leads to identification of enhancer-based subtypes.

A. Non-negative matrix factorization (NMF) clustering of CRC adenocarcinoma (n = 33) and adenoma (n = 4) samples identified four EPIgenome-based Classification (EpiC) clusters of CRC, shown in the color-coded matrix on the top panel. Consensus molecular subtype (CMS) classification of each tumor sample is identified by using a 498 gene–based random forest approach and is overlaid with the EpiC clusters. Clinical data corresponding to the tumor samples in each cluster, including tumor stage, site, pathological grade, race, and gender of the patients, are provided in the lower panels. B. Table Showing enriched major signaling pathways for genes targeted by EpiC-specific enhancers using GREAT. False Discovery Rate (FDR) values are color-coded. C. IGV images showing enrichment of H3K27ac peaks around CTLA4 for EpiC1, TGFβR3 in EpiC2, FGF19 in EpiC3, and NPTX2 in EpiC4 using aggregate ChIP-seq profiles of EpiC1, EpiC2, EpiC3 and EpiC4 group tumors. D. KDE (Kernel Density Estimate) plot with peak lengths (x-axis) and densities (y-axis) of EpiC3 and EpiC3-specific enhancers. Peaks with length more than 5kbs were annotated as Broad whereas those with < 3kb in length were called as Sharp. E. Motif enrichment analysis for enhancers unique to different EpiC groups using HOMER.

Fig. 5.. Correlation between CRC molecular subtypes and EpiCs can predict combinatorial treatments with high clinical significance.

A–C. Summary of IC₅₀ values for 19 small molecule inhibitors (Y-axis) in cell lines with similar expression features to CMS1/EPIC1 (HCT116 or SW480) (A), CMS2/EPIC3 or EPIC4 (T84) (B), and CMS4/EPIC2 (SW620) (C). −Log(IC₅₀) values are demonstrated on X-axis for each of the compounds. Drugs with higher −Log(IC₅₀) are highlighted and were further used in combinatorial experiments. D–F. Growth curves showing responses of CMS-specific CRC cell lines for the drug combinations identified based on the IC₅₀ and AUC indices (panels A–C and Figures S8–S11): CMS1 lines with PARPi (olaparib) + BRDi (iBET-151) (D), CMS2 with EGFRi (gefitinib) + BRDi (RVX-208) (E), and CMS4 with TGFβi (SB431542) + BRDi (ISOX-DUAL) (F). G–L. Tumor volume curves for xenografts in NUDE mice generated from transplantation of EpiC1/CMS1 (G-H), EpiC3–4/CMS2 (I-J), and EpiC2/CMS4 (K-L) cell lines upon treatment with inhibitors of EGFR (gefitinib, 100mg/kg), PARP (olaparib, 50mg/kg), TGF-β (SB431542, 10mg/kg), BRDi (i-BET151, 15mg/kg), or the combination of EGFRi + BRDi, the combination of PARPi + BRDi, and the combination of TGF-βi + BRDi along with the control vehicle group. Mice were treated every other day. Best treatment response was observed in the PARPi + BRDi combination in EpiC1/CMS1, EGFRi + BRDi combination in EpiC3–4/CMS2, and TGF-βi + BRDi combination in EpiC2/CMS4 lines. * shows p-values <0.05, and ** shows p-values <0.01.

Fig. 6.. Functional and clinical significance of EpiC3 and EpiC4 classification.

A. Kaplan-Meier plot of survival of CMS2 samples in the TCGA, comparing EpiC4-like patients (n = 37) and EpiC3-like patients (n = 63). The log-rank (Mantel-Cox) p-value is shown for the difference in survival. B. Pathway analysis for genes in Clusters 2 and 3 from NMF clustering (see Supplementary Fig. S9) of 115 CMS2 TCGA CRC tumors that overlap with EpiC3 and EpiC4-unique genes (LogFC >0.5 and p-value < 0.05). Based on the pathway enrichment, Cluster 2 was annotated as “EpiC4-like” whereas Cluster 3 was annotated as “EpiC3-like”. C. Violin plots showing protein expression of 4EBP1_pT70, PTEN, p70S6K1, SRC_pY527 and CKIT in EpiC3-like or EpIC4-like TCGA samples. F. Tumor volume curves for xenografts in NUDE mice generated from transplantation of EpiC3 (left panels, SW948 and SW480) or EpiC4 (right panels, T84 and SW-403) cell lines upon treatment with inhibitors of mTOR (rapamycin, 4mg/kg), SRC/KIT (Dasatinib, 30mg/kg), BRDi (i-BET151, 15mg/kg), or the combination of Rapamycin + iBET-151 or the combination of Dasatinib + iBET-151 or the control vehicle group. Mice were treated every other day. Asterisks show p-values. * <0.05, ** <0.01 and *** <0.001.