To identify therapeutic targets for KRAS mutant pancreatic cancer, we conduct a druggable genome small interfering RNA (siRNA) screen and determine that suppression of BCAR1 sensitizes pancreatic cancer cells to ERK inhibition. Integrative analysis of genome-scale CRISPR-Cas9 screens also identify BCAR1 as a top synthetic lethal interactor with mutant KRAS. BCAR1 encodes the SRC substrate p130Cas. We determine that SRC-inhibitor-mediated suppression of p130Cas phosphorylation impairs MYC transcription through a DOCK1-RAC1-β-catenin-dependent mechanism. Additionally, genetic suppression of TUBB3, encoding the βIII-tubulin subunit of microtubules, or pharmacological inhibition of microtubule function decreases levels of MYC protein in a calpain-dependent manner and potently sensitizes pancreatic cancer cells to ERK inhibition. Accordingly, the combination of a dual SRC/tubulin inhibitor with an ERK inhibitor cooperates to reduce MYC protein and synergistically suppress the growth of KRAS mutant pancreatic cancer. Thus, we demonstrate that mechanistically diverse combinations with ERK inhibition suppress MYC to impair pancreatic cancer proliferation.

Human colorectal cancer (CRC) most often arises as a result of spontaneous genetic driver mutations such as APC, BRAF, KRAS, SMAD4, and TP53. These are among the most common drivers of CRC and are thought to contribute directly to cancer initiation and growth. CRC tumors harboring BRAFV600E mutation exhibit a CpG Island Methylator Phenotype (CIMP). Other drivers are also more weakly associated with distinct DNA methylation profiles. It is not clear whether these DNA methylation profiles are a result of differences in the cells-of-origin for these cancers, with pre-existing methylation patterns or whether there is selective pressure for various DNA methylation alterations that cooperate with each driver. To address this question, we have modeled this in mice by inducing colon tumors in a controlled cell population at the same age, with either BRAFF-V600E, KRASLSLG12D, Smad4, or Trp53 drivers in combination with Apc heterozygosity. We have profiled DNA methylation in tumors arising in these mice to determine the interaction between different driver mutations and the tumor methylome. Using a multiple linear regression model, we have identified DNA methylation alterations that are shared across all tumor samples, as well as changes that are specific to each of the different genetic drivers. The DNA methylation profiles accurately recapitulate well-established findings, including high levels of hypermethylation in KRASLSLG12D and BRAF F-V600E tumors reminiscent of CpG Island Methylator Phenotype (CIMP), universal tumor hypermethylation at binding sites for transcription factors involved in intestinal epithelial differentiation, and hypomethylation at AP1 complex component binding sites. Driver-specific histology findings broadly align with those observed in human cancers, such as sessile serrated morphology in BRAFF-V600E mutated tumors. The tumor models with different driver mutations also show variation in hypermethylation of polycomb repressive complex target sites and replicative history. We are using the differences in the DNA methylation profiles between the driver tumor models in conjunction with RNA-seq analysis and conservation of the alterations in human CRC to identify epigenetic events cooperative with the drivers and functionally relevant to tumorigenesis. Citation Format: Manpreet Kalkat, Toshinori Hinoue, Liang Kang, Peter W. Laird, Mary Olesnavich. Inducible mouse models of cancer driver mutations as a powerful tool for in vivo and epigenetic studies of colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Methylation, Clonal Hematopoiesis, and Cancer; 2025 Feb 1-4; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2025;85(3 Suppl):Abstract nr B025.

Abstract Phenotypic plasticity is thought to assist immune evasion, metastasis, and therapeutic resistance in tumor evolution. Epigenetic mechanisms such as DNA methylation provide for a more easily acquired and flexible, yet semi-stable adaptation by the tumor cell than hardwired genetic changes. Cancer-associated gain of DNA methylation at promoter CpG islands or distal regulatory elements is associated with transcriptional silencing, whereas loss of DNA methylation is observed at late-replicating, lamina-attached regions of the genome, tracking with cumulative cell divisions. One of the most well-documented genomic features predisposing to DNA hypermethylation is Polycomb Repressive Complex (PRC) occupancy in precursor cells, consistent with an epigenetic block to cellular differentiation as an early or predisposing event in carcinogenesis. A central question is whether this epigenetic switch from reversible PRC repression to more stable DNA hypermethylation occurs before onset of clonal expansion, or whether it represents an ongoing process during tumor evolution. Clonal expansion is a pivotal characteristic of cancer, and is thought to be initiated by a genetic alteration in a key gatekeeper driver gene. However, not all normal cells appear to be susceptible to malignant transformation following such an event. Multiple lines of evidence suggest that epigenetic heterogeneity among normal cells may affect their cancer-initiating potential. We have developed a tumor processing pipeline to deeply and comprehensively map DNA methylation patterns in primary human colorectal cancer (CRC) and adjacent tissues, while preserving spatial information, enabling inference of the temporal order of molecular alterations. We employ a suite of technologies to map the spatial heterogeneity of DNA methylation patterns in primary human CRC. These include a deep single-cell whole-genome bisulfite sequencing technique that improves genomic coverage several-fold over existing published protocols, providing DNA methylation measurements at the majority of CpGs in the genome in individual tumor cells. We have also calibrated and validated an epigenetic clock that allows us to accurately measure the relative replicative history of individual cells. We infer phylogenetic relationships among subclones, and relate these to their spatial distribution in the primary tumor. We find that some tumors have high proportions of PRC-associated clonal hypermethylation, indicating that these hypermethylation events were already present prior to clonal expansion, possibly contributing to susceptibility to malignant transformation in the cell-of-origin, whereas other tumors appear to have active PRC-associated CpG island hypermethylation ongoing during tumor expansion, generating subclonal heterogeneity, which may influence post-therapeutic recurrence potential. Citation Format: Peter W. Laird, Nathan J. Spix, Hsiao-yun Milliron, Manpreet Kalkat, Emily Eugster, David Sokol, Emily Jung, Paula Nolte, Kelly K. Krzyzanowski, Toshinori Hinoue, Hui Shen. Spatial reconstruction and temporal inference of DNA methylation alterations in primary human colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA023.

Abstract Aberrant patterns of DNA methylation (DNAme) have long been noted in colorectal cancer (CRC). Early studies found overall hypomethylation of the cancer genome, while subsequent work revealed focal hypermethylation at specific loci, especially CpG-rich promoters. Loci occupied by polycomb repressive complex 2 in stem cells are remarkably enriched in cancer-specific hypermethylation events. These Polycomb Target Genes (PTGs) include important transcriptional regulators of lineage specification and differentiation, suggesting that hypermethylation-mediated silencing of PTGs could play an active role in CRC initiation or progression. Despite these findings, we have limited knowledge of when, where, and how this hypermethylation arises. Preliminary evidence from bulk tumor samples in the Cancer Genome Atlas suggests that many of these PTG hypermethylation events may be almost completely clonal. Additionally, we have noted rare, densely methylated reads covering PTGs in cancer-adjacent, histologically normal tissue. These observations suggest that PTG hypermethylation may be a very early event in carcinogenesis and may play a permissive or even active role in that process. To better understand the timing and evolution of PTG hypermethylation events in CRC, we have developed a protocol that allows us to extract dozens of small (20µL), spatially annotated mini-bulk samples from live tumors. These mini-bulks may be frozen or dissociated to viable single-cell suspensions. Remaining tumor tissue is preserved in the form of spatially annotated FFPE blocks, which can be used for analyses such as high-plex immunofluorescence or spatial transcriptomics. Using this process, we have collected over 500 spatially annotated samples from 6 CRC cases, including 196 micro-bulk samples profiled using the Infinium MethylationEPIC array. Additionally, we have profiled DNAme in 147 single cells using a dramatically improved single-cell whole-genome bisulfite sequencing protocol developed in our lab. Analysis of EPIC array data reveals wide variation in DNAme heterogeneity between tumors. While in some tumors, the vast majority of DNA hypermethylation events are clonal, other tumors reveal significant intra-tumor heterogeneity, including two or more prominent DNAme subclones as well as a substantial number of ‘private’ hypermethylation events that occur in only one sample. Mapping DNAme information back onto our spatial data reveals that in at least one case, DNAme clones are spatially partitioned and are associated with distinct histology. Ongoing work includes inference of phylogenetic trees from DNA hypermethylation events using non-reversible models of methylation accumulation, allowing us to measure the relative timing of hypermethylation events, as well as integration of array, whole-genome, and single-cell methylation data to more completely characterize DNAme subclones, characterize cellular DNAme heterogeneity at variably methylated sites, and shed further light on the evolution of cancer-related DNA hypermethylation. Citation Format: Nathan J. Spix, Hsiao-yun Milliron, Manpreet Kalkat, Emily Eugster, David W. Chesla, David Sokol, Emily Jung, Paula Nolte, Kelly K. Krzyzanowski, Toshinori Hinoue, Hui Shen, Peter W. Laird. Mapping subclonal epigenetic evolution in colorectal cancer by spatial analysis of DNA hypermethylation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B033.

XLS file, 3148K, Compiled expression array and ChIP-on-chip data.

XLS file, 319K, Expression array analysis of MCF10A 3D cultures at 4 days.

Supplementary Figure 1. A drug screen reveals dipyridamole as potentiating the anti-proliferative effects of atorvastatin and fluvastatin. Supplementary Figure 2. Dipyridamole enhances the effects of statin-induced MVA pathway inhibition. Supplementary Figure 3. The relative sensitivity to doxorubicin in 8226DOX and 8226 parental cells is not significantly altered in response to dipyridamole exposure. Supplementary Figure 4. Dipyridamole prevents the statin induced upregulation of HMGCR and HMGCS1. Supplementary Figure 5. Dipyridamole prevents the statin induced upregulation of HMGCR and HMGCS1 through inhibition of SREBP2 cleavage in OCI-AML2 cells. Supplementary Figure 6: Working model of how dipyridamole potentiates the anticancer effects of statins. Supplementary Table 1. Composition of the chemical library.

XLSX file, 16K, Gene expression changes common to all gain-of-function MYC phosphorylation mutants (158 genes).

XLS file, 2439K, MYC ChIP-on-chip data in MCF10A cells.

XLS file, 160K, GO Analysis of significant genes expression changes.

XLS file, 403K, Expression comparison between wild-type MYC and MYC phosphorylation mutants (from Venn diagram)

XLS file, 98K, GO analysis of common gene expression changes.

PDF file, 498K, Supplementary Figures S1-6 Supplementary Figure S1: Phosphorylation mutants increase Myc-induced transformation in MCF10A cells. Supplementary Figure S2: Phosphorylation mutants increase Myc-induced transformation in SH-EP cells. Supplementary Figure S3: Phosphorylation mutants do not effect MYC protein stability. Supplementary Figure S4: Serum starvation of MCF10A-GFP and MCF10A-MYC cells. Supplementary Figure S5: MYC protein expression through morphogenesis of MCF10A cells in 3D culture. Supplementary Figure S6: Characterization of day 4 acini for mRNA expression array analysis.

XLSX file, 14K, Gene expression changes common to wild type MYC and all phosphorylation mutants (112 genes).

XLS file, 14K, Phosphopeptide analysis for ectopic MYC in 293Tv cells.

We have developed a mouse DNA methylation array that contains 296,070 probes representing the diver-sity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex mem-bers. ApcMin/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.

SUMMARY We have developed a mouse Infinium DNA methylation array that contains 297,415 probes to capture the diversity of mouse DNA methylation biology. We present a mouse DNA methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, age, sex, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, PDX assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This MM285 mouse array is widely accessible to the research community, and will accelerate future high sample-throughput studies in this important model organism.

The potent MYC oncoprotein is deregulated in many human cancers, including breast carcinoma, and is associated with aggressive disease. To understand the mechanisms and vulnerabilities of MYC-driven breast cancer, we have generated an in vivo model that mimics human disease in response to MYC deregulation. MCF10A cells ectopically expressing a common breast cancer mutation in the phosphoinositide 3 kinase pathway (PIK3CAH1047R) led to the development of organised acinar structures in mice. Expressing both PIK3CAH1047R and deregulated MYC led to the development of invasive ductal carcinoma. Therefore, the deregulation of MYC expression in this setting creates a MYC-dependent normal-to-tumour switch that can be measured in vivo These MYC-driven tumours exhibit classic hallmarks of human breast cancer at both the pathological and molecular level. Moreover, tumour growth is dependent upon sustained deregulated MYC expression, further demonstrating addiction to this potent oncogene and regulator of gene transcription. We therefore provide a MYC-dependent model of breast cancer, which can be used to assay invivo tumour signalling pathways, proliferation and transformation from normal breast acini to invasive breast carcinoma. We anticipate that this novel MYC-driven transformation model will be a useful research tool to better understand the oncogenic function of MYC and for the identification of therapeutic vulnerabilities.

Abstract One of the most acclaimed features of the MYC oncogene family ( MYC, MYCL1 and MYCN ) is their prolific deregulation in cancer, which is often associated with poor prognosis and refractory disease. Multiple mechanisms can deregulate their expression in cancer, including chromosomal translocation, enhanced messenger ribonucleic acid (mRNA) and protein stability, gene amplification or enhancer hijacking. This MYC family of nuclear transcription factors regulates the expression of a multitude of target genes to control many critically important fundamental biological processes, including cellular proliferation, metabolism, apoptosis and embryonic development. MYC proteins are highly regulated, and many factors have been reported to control stability and activity via post‐translational modifications (PTMs). Decades of research into this potent oncogene family have revealed that while directly inhibiting MYC proteins in cancer remains challenging, there are multiple strategies to indirectly inhibit MYC in cancer. Developing such inhibitors to target MYC would have profound impact on patient care and outcome. Key Concepts The MYC family of oncogenes, composed of MYC, MYCN and MYCL1 , encode nuclear basic helix‐loop‐helix transcription factors. MYC family proteins contain highly conserved regions termed MYC boxes. MYC regulates many transcriptional targets and can have wide‐reaching effects on the epigenome and total cellular RNA content. MYC is essential for cellular proliferation and is a potent oncogene when it is deregulated in cancer. Deregulated, often elevated, MYC levels have been shown to drive tumourigenesis in many in vivo models. MYC activity and stability is regulated by post‐translational modifications, including phosphorylation, ubiquitylation, SUMOylation and acetylation.