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Abstract Herein, we rebut the critique of Patton et al. (2020), entitled, “No evidence that a transmissible cancer has shifted from emergence to endemism”, by Stammnitz et al. (2024). First and foremost, the authors do not conduct any phylogenetic or epidemiological analyses to rebut the inferences from the main results of the Patton et al. (2020) article, rendering the title of their rebuttal without evidence or merit. Additionally, Stammnitz et al. (2024) present a phylogenetic tree based on only 32 copy number variants (not typically used in phylogenetic analyses and evolve in a completely different way than DNA sequences) to “rebut” our tree that was inferred from 436.1 kb of sequence data and nearly two orders of magnitude more parsimony-informative sites (2520 SNPs). As such it is not surprising that their phylogeny did not have a similar branching pattern to ours, given that support for each branch of their tree was weak and the essentially formed a polytomy. That is, one could rotate their resulting tree in any direction and by nature, it would not match ours. While the authors are correct that we used suboptimal filtering of our raw whole genome sequencing data, re-analyses of the data with 30X coverage, as suggested, resulted in a mutation rate similar to that reported in Stammnitz et al. (2024). Most importantly, when we re-analyzed our data, as well as Stammnitz et al.’s own data, the results of the Patton et al. (2020) article are supported with both datasets. That is, the effective transmission rate of DFTD has transitioned over time to approach one, suggesting endemism; and, the spread of DFTD is rapid and omnidirectional despite the observed east-to-west wave of spread. Overall, Stammnitz et al. (2024) not only fail to provide evidence to contradict the findings of Patton et al. (2020), but rather help support the results with their own data. 

Coevolution is common and frequently governs host–pathogen interaction outcomes. Phenotypes underlying these interactions often manifest as the combined products of the genomes of interacting species, yet traditional quantitative trait mapping approaches ignore these intergenomic interactions. Devil facial tumor disease (DFTD), an infectious cancer afflicting Tasmanian devils (Sarcophilus harrisii), has decimated devil populations due to universal host susceptibility and a fatality rate approaching 100%. Here, we used a recently developed joint genome-wide association study (i.e., co-GWAS) approach, 15 y of mark-recapture data, and 960 genomes to identify intergenomic signatures of coevolution between devils and DFTD. Using a traditional GWA approach, we found that both devil and DFTD genomes explained a substantial proportion of variance in how quickly susceptible devils became infected, although genomic architectures differed across devils and DFTD; the devil genome had fewer loci of large effect whereas the DFTD genome had a more polygenic architecture. Using a co-GWA approach, devil–DFTD intergenomic interactions explained ~3× more variation in how quickly susceptible devils became infected than either genome alone, and the top genotype-by-genotype interactions were significantly enriched for cancer genes and signatures of selection. A devil regulatory mutation was associated with differential expression of a candidate cancer gene and showed putative allele matching effects with two DFTD coding sequence variants. Our results highlight the need to account for intergenomic interactions when investigating host–pathogen (co)evolution and emphasize the importance of such interactions when considering devil management strategies. 

Abstract Background Transmissible cancers lie at the intersection of oncology and infectious disease, two traditionally divergent fields for which gene expression studies are particularly useful for identifying the molecular basis of phenotypic variation. In oncology, transcriptomics studies, which characterize the expression of thousands of genes, have identified processes leading to heterogeneity in cancer phenotypes and individual prognoses. More generally, transcriptomics studies of infectious diseases characterize interactions between host, pathogen, and environment to better predict population-level outcomes. Tasmanian devils have been impacted dramatically by a transmissible cancer (devil facial tumor disease; DFTD) that has led to widespread population declines. Despite initial predictions of extinction, populations have persisted at low levels, due in part to heterogeneity in host responses, particularly between sexes. However, the processes underlying this variation remain unknown. Results We sequenced transcriptomes from healthy and DFTD-infected devils, as well as DFTD tumors, to characterize host responses to DFTD infection, identify differing host-tumor molecular interactions between sexes, and investigate the extent to which tumor gene expression varies among host populations. We found minimal variation in gene expression of devil lip tissues, either with respect to DFTD infection status or sex. However, 4088 genes were differentially expressed in tumors among our sampling localities. Pathways that were up- or downregulated in DFTD tumors relative to normal tissues exhibited the same patterns of expression with greater intensity in tumors from localities that experienced DFTD for longer. No mRNA sequence variants were associated with expression variation. Conclusions Expression variation among localities may reflect morphological differences in tumors that alter ratios of normal-to-tumor cells within biopsies. Phenotypic variation in tumors may arise from environmental variation or differences in host immune response that were undetectable in lip biopsies, potentially reflecting variation in host-tumor coevolutionary relationships among sites that differ in the time since DFTD arrival. 

Emerging infectious diseases pose one of the greatest threats to human health and biodiversity. Phylodynamics is often used to infer epidemiological parameters essential for guiding intervention strategies for human viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). Here, we applied phylodynamics to elucidate the epidemiological dynamics of Tasmanian devil facial tumor disease (DFTD), a fatal, transmissible cancer with a genome thousands of times larger than that of any virus. Despite prior predictions of devil extinction, transmission rates have declined precipitously from ~3.5 secondary infections per infected individual to ~1 at present. Thus, DFTD appears to be transitioning from emergence to endemism, lending hope for the continued survival of the endangered Tasmanian devil. More generally, our study demonstrates a new phylodynamic analytical framework that can be applied to virtually any pathogen.