Widespread Non-Canonical Epigenetic Modifications in MMTV-NeuT Breast Cancer

Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective

Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer makes finding a research model that mirrors the disparate intrinsic features challenging. With advances in multi-omics technologies, establishing parallels between the various models and human tumors is increasingly intricate. Here we review the various model systems and their relation to primary breast tumors using available omics data platforms. Among the research models reviewed here, breast cancer cell lines have the least resemblance to human tumors since they have accumulated many mutations and copy number alterations during their long use. Moreover, individual proteomic and metabolomic profiles do not overlap with the molecular landscape of breast cancer. Interestingly, omics analysis revealed that the initial subtype classification of some breast cancer cell lines was inappropriate. In cell lines the major subtypes are all well represented and share some features with primary tumors. In contrast, patient-derived xenografts (PDX) and patient-derived organoids (PDO) are superior in mirroring human breast cancers at many levels, making them suitable models for drug screening and molecular analysis. While patient derived organoids are spread across luminal, basal- and normal-like subtypes, the PDX samples were initially largely basal but other subtypes have been increasingly described. Murine models offer heterogenous tumor landscapes, inter and intra-model heterogeneity, and give rise to tumors of different phenotypes and histology. Murine models have a reduced mutational burden compared to human breast cancer but share some transcriptomic resemblance, and representation of many breast cancer subtypes can be found among the variety subtypes. To date, while mammospheres and three- dimensional cultures lack comprehensive omics data, these are excellent models for the study of stem cells, cell fate decision and differentiation, and have also been used for drug screening. Therefore, this review explores the molecular landscapes and characterization of breast cancer research models by comparing recent published multi-omics data and analysis.

Stochastic changes in gene expression promote chaotic dysregulation of homeostasis in clonal breast tumors

Cells within tumors vary in phenotype as a result of changes in gene expression caused by a variety of mechanisms, permitting cancers to evolve under selective pressures from immune and other homeostatic processes. Earlier, we traced apparent losses in heterozygosity (LOH) of spontaneous breast tumors from first generation (F1) intercrossed mice to atypical epigenetic modifications in the structure of DNA across the tumor genomes. Here, we describe a parallel pattern of LOH in gene expression, revealed through quantitation of parental alleles across a population of clonal tumors. We found variegated patterns of LOH, based on allelic ratio outliers in hundreds of genes, enriched in regulatory pathways typically co-opted by tumors. The frequency of outliers was correlated with transcriptional repression of a large set of homozygous genes. These findings suggest stochastic losses in gene expression across the genome of tumors generate phenotypic variation among cells, allowing clonal selection during tumor development.

Breaking tolerance with engineered class I antigen-presenting molecules

Successful efforts to activate T cells capable of recognizing weak cancer-associated self-antigens have employed altered peptide antigens to activate T cell responses capable of cross-reacting on native tumor-associated self. A limitation of this approach is the requirement for detailed knowledge about the altered self-peptide ligands used in these vaccines. In the current study we considered allorecognition as an approach for activating CTL capable of recognizing weak or self-antigens in the context of self-MHC. Nonself antigen-presenting molecules typically contain polymorphisms that influence interactions with the bound peptide and TCR interface. Recognition of these nonself structures results in peptide-dependent alloimmunity. Alloreactive T cells target their inducing alloantigens as well as third-party alloantigens but generally fail to target self-antigens. Certain residues located on the alpha-1/2 domains of class I antigen-presenting molecules primarily interface with TCR. These residues are more conserved within and across species than are residues that determine peptide antigen binding properties. Class I variants designed with amino acid substitutions at key positions within the conserved helical structures are shown to provide strong activating signals to alloreactive CD8 T cells while avoiding changes in naturally bound peptide ligands. Importantly, CTL activated in this manner can break self-tolerance by reacting to self-peptides presented by native MHC. The ability to activate self-tolerant T cells capable of cross-reacting on self-peptide-MHC in vivo represents an approach for inducing autoimmunity, with possible application in cancer vaccines.