The MexTAg collaborative cross: host genetics affects asbestos related disease latency, but has little influence once tumours develop

Our plain-English summary of The MexTAg collaborative cross: host genetics affects asbestos related disease latency, but has little influence once tumours develop, by S.A. Fisher, K. Patrick, T. Hoang, et al (Frontiers in Toxicology, 2024).

The study

• Authors: S.A. Fisher, K. Patrick, T. Hoang, E. Marcq, K. Behrouzfar, S. Young, T.J. Miller, B.W.S. Robinson, R. Bueno, A.K. Nowak, W.J. Lesterhuis, G. Morahan, R.A. Lake
• Journal: Frontiers in Toxicology
• Published: 2024;6:1373003
• Cited by: 4 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Objectives: This study combines two innovative mouse models in a major gene discovery project to assess the influence of host genetics on asbestos related disease (ARD). Conventional genetics studies provided evidence that some susceptibility to mesothelioma is genetic. However, the identification of host modifier genes, the roles they may play, and whether they contribute to disease susceptibility remain unknown. Here we report a study designed to rapidly identify genes associated with mesothelioma susceptibility by combining the Collaborative Cross (CC) resource with the well-characterised MexTAg mesothelioma mouse model. Methods: The CC is a powerful mouse resource that harnesses over 90% of common genetic variation in the mouse species, allowing rapid identification of genes mediating complex traits. MexTAg mice rapidly, uniformly, and predictably develop mesothelioma, but only after asbestos exposure. To assess the influence of host genetics on ARD, we crossed 72 genetically distinct CC mouse strains with MexTAg mice and exposed the resulting CC-MexTAg (CCMT) progeny to asbestos and monitored them for traits including overall survival, the time to ARD onset (latency), the time between ARD onset and euthanasia (disease progression) and ascites volume. We identified phenotype-specific modifier genes associated with these traits and we validated the role of human orthologues in asbestos-induced carcinogenesis using human mesothelioma datasets. Results: We generated 72 genetically distinct CCMT strains and exposed their progeny (2,562 in total) to asbestos. Reflecting the genetic diversity of the CC, there was considerable variation in overall survival and disease latency. Surprisingly, however, there was no variation in disease progression, demonstrating that host genetic factors do have a significant influence during disease latency but have a limited role once disease is established. Quantitative trait loci (QTL) affecting ARD survival/latency were identified on chromosomes 6, 12 and X. Of the 97-protein coding candidate modifier genes that spanned these QTL, eight genes (CPED1, ORS1, NDUFA1, HS1BP3, IL13RA1, LSM8, TES and TSPAN12) were found to significantly affect outcome in both CCMT and human mesothelioma datasets. Conclusion: Host genetic factors affect susceptibility to development of asbestos associated disease. However, following mesothelioma establishment, genetic variation in molecular or immunological mechanisms did not affect disease progression. Identification of multiple candidate modifier genes and their human homologues with known associations in other advanced stage or metastatic cancers highlights the complexity of ARD and may provide a pathway to identify novel therapeutic targets.

Copyright © 2024 Fisher, Patrick, Hoang, Marcq, Behrouzfar, Young, Miller, Robinson, Bueno, Nowak, Lesterhuis, Morahan and Lake.

In plain English

This was an animal gene-discovery experiment. Female homozygous 266-MexTAg mice were crossed with males from 71 distinct Collaborative Cross strains, and the resulting CC-MexTAg (CCMT) progeny, with a heterozygous 266-MexTAg control group (2,565 mice), each received 6 mg of crocidolite asbestos as two intraperitoneal injections four weeks apart and were followed for up to 18 months. The authors recorded overall survival, disease latency (first exposure to first signs of disease), disease progression (first signs to euthanasia) and ascites volume. Median survival differed 3.75-fold between CCMT groups, and asbestos related disease incidence had a cohort median of 87% (range 50%-100%). Survival correlated almost perfectly with latency (Pearson r = 0.9988) and only weakly and inversely with progression (r = -0.1291). Quantitative trait loci for survival/latency were found on chromosomes 6, 12 and X, spanning 97 protein-coding candidate genes. The authors reported eight human homologues as significant for outcome in two mesothelioma datasets, though one, NDUFA1, is printed with p = 0.35, above their 0.05 cutoff. The authors concluded host genetics affects disease development but not progression once disease is established.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: experimental mouse study (genetic mapping in a Collaborative Cross x MexTAg mesothelioma model) with validation in two human mesothelioma transcriptomic datasets
• Who was studied: 2,565 asbestos-exposed mice: 71 groups of CC-MexTAg progeny plus one group of heterozygous 266-MexTAg controls (median 37 mice per group, range 18-45), bred and studied at the University of Western Australia; histology reviewed in 403 mice from 12 CCMT groups; human validation used the Bueno (211 patients) and TCGA-MESO (74 patients) datasets
• Exposure: 6 mg crocidolite asbestos (IUCC reference sample, Wittenoom Gorge) given as two intraperitoneal injections of 3 mg in 0.5 mL PBS at weeks 0 and 4
• Main results:
  • Overall survival varied significantly between asbestos-exposed CCMT groups, with a 3.75-fold difference between the groups with the shortest and longest median survival (the article prints the p-value as 'p > 0.001')
  • Across CCMT groups, asbestos related disease incidence had a median of 87% (range 50%-100%); progeny of four CC strains (SEH 50%, LIV 62.5%, ZIE2 66.7%, LUF 67.5%) fell more than two standard deviations below the cohort mean
  • In the asbestos-exposed CCMT mice, variation in disease latency matched variation in overall survival (Pearson r = 0.9988), while overall survival and disease progression showed a weak inverse correlation (r = -0.1291)
  • The heterozygous parental 266-MexTAg control group had a median survival of 536.5 days and 93.8% incidence, similar to the longest-surviving CCMT groups (548 days; 87.5% ± 5%)
  • Major-effect QTL for survival/latency were mapped to chromosomes 6 (LOD 6.6), 12 (LOD 5.8) and X (LOD 6.4), spanning 97 protein-coding candidate modifier genes; no QTL was found for disease progression
  • In the histological subset of 403 mice, paucicellular regions were associated with better overall survival on univariate and multivariate analysis (HR 0.66; 95%CI 0.52-0.84; p less than 0.001)
  • The human analyses used age at surgery (Bueno cohort) or age at diagnosis (TCGA-MESO cohort) as the outcome measure, described by the authors as surrogates for disease latency
  • In the human Bueno cohort, expression of OSR1 (HR 1.4, p = 0.026) and CPED1 (HR 1.5, p = 0.016) was significantly associated with poorer outcome
  • In the TCGA-MESO cohort, the authors reported HS1BP3 (HR 2, p = 0.016), IL13RA1 (HR 2.1, p = 0.0057), LSM8 (HR 1.9, p = 0.021), NDUFA1 (HR 1.8) and TES (HR 2.1, p = 0.0075) as associated with poorer outcome, and TSPAN12 (HR 0.55, p = 0.03) with improved outcome; the NDUFA1 p-value is printed as 0.35, above the p less than 0.05 cutoff the authors used for selection
• The authors' conclusion: The authors concluded that host genetics influences the development of asbestos related disease but not its progression once established, and that the candidate modifier genes identified support the feasibility of this gene-discovery approach
• Limitations the authors state:
  • The authors state that the mouse QTL were derived from disease latency whereas the two human mesothelioma datasets essentially represent established disease, and that few publicly available mesothelioma datasets contain sufficient disease latency data

Topics

Medical terms in this study, explained in our Lexicon: Latency, Discovery, Mesothelioma, Asbestos Exposure, Overall Survival, Disease Progression, Ascites, Carcinogenesis.

Related studies

• How to Better Understand the Influence of Host Genetics on Developing an Effective Immune Response to Thoracic Cancers — K. Behrouzfar, K. Burton, et al. (2021)
• MexTAg mice exposed to asbestos develop cancer that faithfully replicates key features of the pathogenesis of human mesothelioma — C. Robinson, A. Walsh, et al. (2011)
• Disease Latency according to Asbestos Exposure Characteristics among Malignant Mesothelioma and Asbestos-Related Lung Cancer Cases in South Korea — D.A. Huh, W.R. Chae, et al. (2022)
• Chest physician-reported, work-related, long-latency respiratory disease in Great Britain — M. Carder, A. Darnton, et al. (2017)
• Asbestos-related disease in railroad workers. A cross-sectional study — L.C. Oliver, E.A. Eisen, et al. (1985)
• Is living close to ophiolites related to asbestos related diseases? Cross-sectional study — I. Döngel, M. Bayram, et al. (2013)

Browse more research in Frontiers in Toxicology, or return to medical research.