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Trichloroethylene (TCE) and inorganic arsenic (iAs) are environmental contaminants that can target the kidney. Chronic exposure to TCE is associated with increased incidence of renal cell carcinoma, while co-exposure to TCE and iAs likely occurs in exposed human populations, such as those near Superfund sites. In order to better understand the kidney health consequences of TCE and/or iAs exposure, a genetically heterogeneous mouse population derived from FVB/NJ and CAST/EiJ mouse strains and deficient for multidrug resistance genes (Abcb1atm1Bor, Abcb1btm1Bor) was chronically exposed for 52-weeks to varying concentrations of TCE and iAs. Although no exposure group resulted in primary renal cell tumors, kidneys from exposed mice did have significant increases in histologic and biochemical evidence of renal tubular disease with each toxicant alone and with combined exposure, with males having significantly higher levels of damage. Although no added increase in tubular disease was observed with combination exposure compared to single toxicants, molecular changes in kidneys from mice that had the combined exposure were similar to those previous observed in an embryonic stem cell assay for the P81S TCE-induced renal cell carcinoma mutation in the Von Hippel-Lindau syndrome (VHL) gene. While this model more accurately reflects human exposure conditions, development of primary renal tumors observed in humans following chronic TCE exposure was not reproduced even after inclusion of genetic heterogeneity and co-carcinogenic iAs.

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.

Although epidermal growth factor receptor (EGFR)-targeted therapies are approved for colorectal cancer (CRC) treatment, only 15% of CRC patients respond to EGFR inhibition. Here, we show that colorectal cancers (CRC) can initiate and grow faster through an EGFR-independent mechanism, irrespective of the presence of EGFR, in two different mouse models using tissue-specific ablation of Egfr. The growth benefit in the absence of EGFR is also independent of Kras status. An EGFR-independent gene expression signature, also observed in human CRCs, revealed that anergy-inducing genes are overexpressed in EGFR-independent polyps, suggesting increased infiltration of anergic lymphocytes promotes an accelerated growth rate that is partially caused by escape from cell-mediated immune responses. Many genes in the EGFR-independent gene expression signature are downstream targets of interleukin 10 receptor alpha (IL10RA). We further show that IL10 is detectable in serum from mice with EGFR-independent colon polyps. Using organoids in vitro and Src ablation in vivo, we show that IL10 contributes to growth of EGFR-independent CRCs, potentially mediated by the well-documented role of SRC in IL10 signaling. Based on these data, we show that the combination of an EGFR inhibitor with an anti-IL10 neutralizing antibody results in decreased cell proliferation in organoids and in decreased polyp size in pre-clinical models harboring EGFR-independent CRCs, providing a new therapeutic intervention for CRCs resistant to EGFR inhibitor therapies.

The immune system plays a pivotal role in the susceptibility to and progression of a variety of diseases. Due to a strong genetic basis, heritable differences in immune function may contribute to differential disease susceptibility between individuals. Genetic reference populations, such as the BXD (C57BL/6J × DBA/2J) panel of recombinant inbred (RI) mouse strains, provide unique models through which to integrate baseline phenotypes in healthy individuals with heritable risk for disease because of the ability to combine data collected from these populations across both multiple studies and time. We performed basic immunophenotyping (e.g., percentage of circulating B and T lymphocytes and CD4+and CD8+T cell subpopulations) in peripheral blood of healthy mice from 41 BXD RI strains to define the immunophenotypic variation in this strain panel and to characterize the genetic architecture that underlies these traits. Significant QTL models that explained the majority (50–77%) of phenotypic variance were derived for each trait and for the T:B cell and CD4+:CD8+ratios. Combining QTL mapping with spleen gene expression data uncovered two quantitative trait transcripts, Ptprk and Acp1, as candidates for heritable differences in the relative abundance of helper and cytotoxic T cells. These data will be valuable in extracting genetic correlates of the immune system in the BXD panel. In addition, they will be a useful resource for prospective, phenotype-driven model selection to test hypotheses about differential disease or environmental susceptibility between individuals with baseline differences in the composition of the immune system.