A diversity outbred F1 mouse model identifies host-intrinsic genetic regulators of response to immune checkpoint inhibitors

Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response in mice and humans

Identifying host genetic factors modulating immune checkpoint inhibitor (ICI) efficacy has been experimentally challenging because of variations in both host and tumor genomes, differences in the microbiome, and patient life exposures. Utilizing the Collaborative Cross (CC) multi-parent mouse genetic resource population, we developed an approach that fixes the tumor genomic configuration while varying host genetics. With this approach, we discovered that response to anti-PD-1 (aPD1) immunotherapy was significantly heritable in four distinct murine tumor models (H2 between 0.18-0.40). For the MC38 colorectal carcinoma system (H2 = 0.40), we mapped four significant ICI response quantitative trait loci (QTL) localized to mouse chromosomes (mChr) 5, 9, 15 and 17, and identified significant epistatic interactions between specific QTL pairs. Differentially expressed genes within these QTL were highly enriched for immune genes and pathways mediating allograft rejection and graft vs host disease. Using a cross species analytical approach, we found a core network of 48 genes within the four QTLs that showed significant prognostic value for overall survival in aPD1 treated human cohorts that outperformed all other existing validated immunotherapy biomarkers, especially in human tumors of the previously defined immune subtype 4. Functional blockade of two top candidate immune targets within the 48 gene network, GM-CSF and high affinity IL-2/IL-15 signaling, completely abrogated the MC38 tumor transcriptional response to aPD1 therapy in vivo. Thus, we have established a powerful cross species in vivo platform capable of uncovering host genetic factors that establish the tumor immune microenvironment configuration propitious for ICI response.

Modeling Brain Gene Expression in Alcohol Use Disorder with Genetic Animal Models

Animal genetic models have and will continue to provide important new information about the behavioral and physiological adaptations associated with alcohol use disorder (AUD). This chapter focuses on two models, ethanol preference and drinking in the dark (DID), their usefulness in interrogating brain gene expression data and the relevance of the data obtained to interpret AUD-related GWAS and TWAS studies. Both the animal and human data point to the importance for AUD of changes in synaptic transmission (particularly glutamate and GABA transmission), of changes in the extracellular matrix (specifically including collagens, cadherins and protocadherins) and of changes in neuroimmune processes. The implementation of new technologies (e.g., cell type-specific gene expression) is expected to further enhance the value of genetic animal models in understanding AUD.

Integrative analysis of hepatic transcriptional profiles reveals genetic regulation of atherosclerosis in hyperlipidemic Diversity Outbred-F1 mice

Atherogenesis is an insipidus but precipitating process leading to serious consequences of many cardiovascular diseases (CVD). Numerous genetic loci contributing to atherosclerosis have been identified in human genome-wide association studies, but these studies have limitations in the ability to control environmental factors and to decipher cause/effect relationships. To assess the power of hyperlipidemic Diversity Outbred (DO) mice in facilitating quantitative trait loci (QTL) analysis of complex traits, we generated a high-resolution genetic panel of atherosclerosis susceptible (DO-F1) mouse cohort by crossing 200 DO females with C57BL/6J males carrying two human genes: encoding apolipoprotein E3-Leiden and cholesterol ester transfer protein. We examined atherosclerotic traits including plasma lipids and glucose in the 235 female and 226 male progeny before and after 16 weeks of a high-fat/cholesterol diet, and aortic plaque size at 24 weeks. We also assessed the liver transcriptome using RNA-sequencing. Our QTL mapping for atherosclerotic traits identified one previously reported female-specific QTL on Chr10 with a narrower interval of 22.73 to 30.80 Mb, and one novel male-specific QTL at 31.89 to 40.25 Mb on Chr19. Liver transcription levels of several genes within each QTL were highly correlated with the atherogenic traits. A majority of these candidates have already known atherogenic potential in humans and/or mice, but integrative QTL, eQTL, and correlation analyses further pointed Ptprk as a major candidate of the Chr10 QTL, while Pten and Cyp2c67 of the Chr19 QTL in our DO-F1 cohort. Finally, through additional analyses of RNA-seq data we identified genetic regulation of hepatic transcription factors, including Nr1h3, contributes to atherogenesis in this cohort. Thus, an integrative approach using DO-F1 mice effectively validates the influence of genetic factors on atherosclerosis in DO mice and suggests an opportunity to discover therapeutics in the setting of hyperlipidemia.

Host genetic background regulates the capacity for anti-tumor antibody-dependent phagocytosis

Background

Antitumor antibody, or targeted immunotherapy, has revolutionized cancer treatment and markedly improved patient outcomes. A prime example is the monoclonal antibody (mAb) trastuzumab, which targets human epidermal growth factor receptor 2 (HER2). However, like many targeted immunotherapies, only a subset of patients benefit from trastuzumab long-term. In addition to tumor-intrinsic factors, we hypothesize that host genetics may influence subsequent immune activation.

Methods

To model the human population, we produced F1 crosses of genetically heterogeneous Diversity Outbred (DO) mice with BALB/c mice (DOCF1). Distinct DOCF1 mice were orthotopically implanted with the BALB/c-syngeneic TUBO mammary tumor line, which expresses the HER2 ortholog rat neu. Treatment with anti-neu mAb clone 7.16.4 began once tumors reached ∼200 mm ³ . Genetic linkage and quantitative trait locus (QTL) effects analyses in R/qtl2 identified loci associated with tumor growth rates. Locus validation was performed with BALB/c F1 crosses with recombinant-inbred Collaborative Cross (CC) strains selected for therapy-associated driver genetics (CCxCF1). The respective roles of natural killer (NK) cells and macrophages were investigated by selective depletion in vivo. Ex vivo macrophage antibody-dependent phagocytosis (ADCP) assays were evaluated by confocal microscopy using 7.16.4-opsonized E2Crimson-expressing TUBO tumor cells.

Results

We observed a divergent response to anti-tumor antibody therapy in DOCF1 mice. Genetic linkage analysis detected a locus on chromosome 10 that correlates to a robust response to therapy, which was validated in CCxCF1 models. Single-cell RNA sequencing of tumors from responder and non-responder models identified key differences in tumor immune infiltrate composition, particularly within macrophage (Mφ) subsets. This is further supported by ex vivo analysis showing Mφ ADCP capacity correlates to in vivo treatment outcomes in both DOCF1 and CCxCF1 models.

Conclusions

Host genetics play a key regulatory role in targeted immunotherapy outcomes, and putative causal genes are identified in murine chromosome 10 which may govern Mφ function during ADCP.

Mouse models for immuno-oncology

Realizing the clinical promise of cancer immunotherapy is hindered by gaps in our knowledge of in vivo mechanisms underlying treatment response as well as treatment limiting toxicity. Preclinical in vivo model systems and technologies are required to address these knowledge gaps and to surmount the challenges faced in the clinical application of immunotherapy. Mice are commonly used for basic and translational research to support development and testing of immune interventions, including for cancer. Here, we discuss the advantages and the limitations of current models as well as future developments.

Mouse population genetics phenocopies heterogeneity of human Chd8 haploinsufficiency

Preclinical models of neurodevelopmental disorders typically use single inbred mouse strains, which fail to capture the genetic diversity and symptom heterogeneity that is common clinically. We tested whether modeling genetic background diversity in mouse genetic reference panels would recapitulate population and individual differences in responses to a syndromic mutation in the high-confidence autism risk gene, CHD8. We measured clinically relevant phenotypes in >1,000 mice from 33 strains, including brain and body weights and cognition, activity, anxiety, and social behaviors, using 5 behavioral assays: cued fear conditioning, open field tests in dark and bright light, direct social interaction, and social dominance. Trait disruptions mimicked those seen clinically, with robust strain and sex differences. Some strains exhibited large effect-size trait disruptions, sometimes in opposite directions, and-remarkably-others expressed resilience. Therefore, systematically introducing genetic diversity into models of neurodevelopmental disorders provides a better framework for discovering individual differences in symptom etiologies.

Brain gene expression differences related to ethanol preference in the collaborative cross founder strains

The collaborative cross (CC) founder strains include five classical inbred laboratory strains [129S1/SvlmJ (S129), A/J (AJ), C57BL/6J (B6), NOD/ShiLtJ (NOD), and NZO/HILtJ (NZO)] and three wild-derived strains [CAST/EiJ (CAST), PWK/PhJ (PWK), and WSB/EiJ (WSB)]. These strains encompass 89% of the genetic diversity available in Mus musculus and ∼10-20 times more genetic diversity than found in Homo sapiens. For more than 60 years the B6 strain has been widely used as a genetic model for high ethanol preference and consumption. However, another of the CC founder strains, PWK, has been identified as a high ethanol preference/high consumption strain. The current study determined how the transcriptomes of the B6 and PWK strains differed from the 6 low preference CC strains across 3 nodes of the brain addiction circuit. RNA-Seq data were collected from the central nucleus of the amygdala (CeA), the nucleus accumbens core (NAcc) and the prelimbic cortex (PrL). Differential expression (DE) analysis was performed in each of these brain regions for all 28 possible pairwise comparisons of the CC founder strains. Unique genes for each strain were identified by selecting for genes that differed significantly [false discovery rate (FDR) < 0.05] from all other strains in the same direction. B6 was identified as the most distinct classical inbred laboratory strain, having the highest number of total differently expressed genes (DEGs) and DEGs with high log fold change, and unique genes compared to other CC strains. Less than 50 unique DEGs were identified in common between B6 and PWK within all three brain regions, indicating the strains potentially represent two distinct genetic signatures for risk for high ethanol-preference. 338 DEGs were found to be commonly different between B6, PWK and the average expression of the remaining CC strains within all three regions. The commonly different up-expressed genes were significantly enriched (FDR < 0.001) among genes associated with neuroimmune function. These data compliment findings showing that neuroimmune signaling is key to understanding alcohol use disorder (AUD) and support use of these 8 strains and the highly heterogeneous mouse populations derived from them to identify alcohol-related brain mechanisms and treatment targets.

Using the Collaborative Cross and Diversity Outbred Mice in Immunology

The Collaborative Cross (CC) and the Diversity Outbred (DO) stock mouse panels are the most powerful murine genetics tools available to the genetics community. Together, they combine the strength of inbred animal models with the diversity of outbred populations. Using the 63 CC strains or a panel of DO mice, each derived from the same 8 parental mouse strains, researchers can map genetic contributions to exceptionally complex immunological and infectious disease traits that would require far greater powering if performed by genome-wide association studies (GWAS) in human populations. These tools allow genes to be studied in heterozygous and homozygous states and provide a platform to study epistasis between interacting loci. Most importantly, once a quantitative phenotype is investigated and quantitative trait loci are identified, confirmatory genetic studies can be performed, which is often problematic using the GWAS approach. In addition, novel stable mouse models for immune phenotypes are often derived from studies utilizing the DO and CC mice that can serve as stronger model systems than existing ones in the field. The CC/DO systems have contributed to the fields of cancer immunology, autoimmunity, vaccinology, infectious disease, allergy, tissue rejection, and tolerance but have thus far been greatly underutilized. In this article, we present a recent review of the field and point out key areas of immunology that are ripe for further investigation and awaiting new CC/DO research projects. We also highlight some of the strong computational tools that have been developed for analyzing CC/DO genetic and phenotypic data. Additionally, we have formed a centralized community on the CyVerse infrastructure where immunogeneticists can utilize those software tools, collaborate with groups across the world, and expand the use of the CC and DO systems for investigating immunogenetic phenomena. © 2022 Wiley Periodicals LLC.