The tumor immune microenvironment of primary and metastatic HER2- positive breast cancers utilizing gene expression and spatial proteomic profiling

BACKGROUND

The characterization of the immune component of the tumor microenvironment (TME) of human epidermal growth factor receptor 2 positive (HER2+) breast cancer has been limited. Molecular and spatial characterization of HER2+ TME of primary, recurrent, and metastatic breast tumors has the potential to identify immune mediated mechanisms and biomarker targets that could be used to guide selection of therapies.

METHODS

We examined 15 specimens from eight patients with HER2+ breast cancer: 10 primary breast tumors (PBT), two soft tissue, one lung, and two brain metastases (BM). Using molecular profiling by bulk gene expression TME signatures, including the Tumor Inflammation Signature (TIS) and PAM50 subtyping, as well as spatial characterization of immune hot, warm, and cold regions in the stroma and tumor epithelium using 64 protein targets on the GeoMx Digital Spatial Profiler.

RESULTS

PBT had higher infiltration of immune cells relative to metastatic sites and higher protein and gene expression of immune activation markers when compared to metastatic sites. TIS scores were lower in metastases, particularly in BM. BM also had less immune infiltration overall, but in the stromal compartment with the highest density of immune infiltration had similar levels of T cells that were less activated than PBT stromal regions suggesting immune exclusion in the tumor epithelium.

CONCLUSIONS

Our findings show stromal and tumor localized immune cells in the TME are more active in primary versus metastatic disease. This suggests patients with early HER2+ breast cancer could have more benefit from immune-targeting therapies than patients with advanced disease.

Visualizing in deceased COVID-19 patients how SARS-CoV-2 attacks the respiratory and olfactory mucosae but spares the olfactory bulb

Anosmia, the loss of smell, is a common and often the sole symptom of COVID-19. The onset of the sequence of pathobiological events leading to olfactory dysfunction remains obscure. Here, we have developed a postmortem bedside surgical procedure to harvest endoscopically samples of respiratory and olfactory mucosae and whole olfactory bulbs. Our cohort of 85 cases included COVID-19 patients who died a few days after infection with SARS-CoV-2, enabling us to catch the virus while it was still replicating. We found that sustentacular cells are the major target cell type in the olfactory mucosa. We failed to find evidence for infection of olfactory sensory neurons, and the parenchyma of the olfactory bulb is spared as well. Thus, SARS-CoV-2 does not appear to be a neurotropic virus. We postulate that transient insufficient support from sustentacular cells triggers transient olfactory dysfunction in COVID-19. Olfactory sensory neurons would become affected without getting infected.

The CD155/TIGIT axis promotes and maintains immune evasion in neoantigen-expressing pancreatic cancer

The CD155/TIGIT axis can be co-opted during immune evasion in chronic viral infections and cancer. Pancreatic adenocarcinoma (PDAC) is a highly lethal malignancy, and immune-based strategies to combat this disease have been largely unsuccessful to date. We corroborate prior reports that a substantial portion of PDAC harbors predicted high-affinity MHC class I-restricted neoepitopes and extend these findings to advanced/metastatic disease. Using multiple preclinical models of neoantigen-expressing PDAC, we demonstrate that intratumoral neoantigen-specific CD8+ T cells adopt multiple states of dysfunction, resembling those in tumor-infiltrating lymphocytes of PDAC patients. Mechanistically, genetic and/or pharmacologic modulation of the CD155/TIGIT axis was sufficient to promote immune evasion in autochthonous neoantigen-expressing PDAC. Finally, we demonstrate that the CD155/TIGIT axis is critical in maintaining immune evasion in PDAC and uncover a combination immunotherapy (TIGIT/PD-1 co-blockade plus CD40 agonism) that elicits profound anti-tumor responses in preclinical models, now poised for clinical evaluation.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

Cryptic chytridiomycosis linked to climate and genetic variation in amphibian populations of the southeastern United States

North American amphibians have recently been impacted by two major emerging pathogens, the fungus Batrachochytrium dendrobatidis (Bd) and iridoviruses in the genus Ranavirus (Rv). Environmental factors and host genetics may play important roles in disease dynamics, but few studies incorporate both of these components into their analyses.

Here, we investigated the role of environmental and genetic factors in driving Bd and Rv infection prevalence and severity in a biodiversity hot spot, the southeastern United States.

We used quantitative PCR to characterize Bd and Rv dynamics in natural populations of three amphibian species: Notophthalmus perstriatus, Hyla squirella and Pseudacris ornata. We combined pathogen data, genetic diversity metrics generated from neutral markers, and environmental variables into general linear models to evaluate how these factors impact infectious disease dynamics. Occurrence, prevalence and intensity of Bd and Rv varied across species and populations, but only one species, Pseudacris ornata, harbored high Bd intensities in the majority of sampled populations. Genetic diversity and climate variables both predicted Bd prevalence, whereas climatic variables alone predicted infection intensity.

We conclude that Bd is more abundant in the southeastern United States than previously thought and that genetic and environmental factors are both important for predicting amphibian pathogen dynamics. Incorporating both genetic and environmental information into conservation plans for amphibians is necessary for the development of more effective management strategies to mitigate the impact of emerging infectious diseases.

Genomics and introgression: Discovery and mapping of thousands of species-diagnostic SNPs using RAD sequencing

Invasive hybridization and introgression pose a serious threat to the persistence of many native species. Understanding the effects of hybridization on native populations (e.g., fitness consequences) requires numerous species-diagnostic loci distributed genome-wide. Here we used RAD sequencing to discover thousands of single-nucleotide polymorphisms (SNPs) that are diagnostic between rainbow trout (RBT, Oncorhynchus mykiss), the world’s most widely introduced fish, and native westslope cutthroat trout (WCT, O. clarkii lewisi) in the northern Rocky Mountains, USA. We advanced previous work that identified 4,914 species-diagnostic loci by using longer sequence reads (100 bp vs. 60 bp) and a larger set of individuals (n = 84). We sequenced RAD libraries for individuals from diverse sampling sources, including native populations of WCT and hatchery broodstocks of WCT and RBT. We also took advantage of a newly released reference genome assembly for RBT to align our RAD loci. In total, we discovered 16,788 putatively diagnostic SNPs, 10,267 of which we mapped to anchored chromosome locations on the RBT genome. A small portion of previously discovered putative diagnostic loci (325 of 4,914) were no longer diagnostic (i.e., fixed between species) based on our wider survey of non-hybridized RBT and WCT individuals. Our study suggests that RAD loci mapped to a draft genome assembly could provide the marker density required to identify genes and chromosomal regions influencing selection in admixed populations of conservation concern and evolutionary interest.

Genetic regulatory network motifs constrain adaptation through curvature in the landscape of mutational (co)variance

Systems biology is accumulating a wealth of understanding about the structure of genetic regulatory networks, leading to a more complete picture of the complex genotype-phenotype relationship. However, models of multivariate phenotypic evolution based on quantitative genetics have largely not incorporated a network-based view of genetic variation. Here we model a set of two-node, two-phenotype genetic network motifs, covering a full range of regulatory interactions. We find that network interactions result in different patterns of mutational (co)variance at the phenotypic level (the M-matrix), not only across network motifs but also across phenotypic space within single motifs. This effect is due almost entirely to mutational input of additive genetic (co)variance. Variation in M has the effect of stretching and bending phenotypic space with respect to evolvability, analogous to the curvature of space-time under general relativity, and similar mathematical tools may apply in each case. We explored the consequences of curvature in mutational variation by simulating adaptation under divergent selection with gene flow. Both standing genetic variation (the G-matrix) and rate of adaptation are constrained by M, so that G and adaptive trajectories are curved across phenotypic space. Under weak selection the phenotypic mean at migration-selection balance also depends on M.

Goldilocks Meets Santa Rosalia: An Ephemeral Speciation Model Explains Patterns of Diversification Across Time Scales

Understanding the rate at which new species form is a key question in studying the evolution of life on earth. Here we review our current understanding of speciation rates, focusing on studies based on the fossil record, phylogenies, and mathematical models. We find that speciation rates estimated from these different studies can be dramatically different: some studies find that new species form quickly and often, while others find that new species form much less frequently. We suggest that instead of being contradictory, differences in speciation rates across different scales can be reconciled by a common model. Under the "ephemeral speciation model", speciation is very common and very rapid but the new species produced almost never persist. Evolutionary studies should therefore focus on not only the formation but also the persistence of new species.

Machine learning identifies specific habitats associated with genetic connectivity in Hyla squirella

The goal of this study was to identify and differentiate the influence of multiple habitat types that span a spectrum of suitability for Hyla squirella, a widespread frog species that occurs in a broad range of habitat types. We collected microsatellite data from 675 samples representing 20 localities from the southeastern USA and used machine-learning methodologies to identify significant habitat features associated with genetic structure. In simulation, we confirm that our machine-learning algorithm can successfully identify landscape features responsible for generating between-population genetic differentiation, suggesting that it can be a useful hypothesis-generating tool for landscape genetics. In our study system, we found that H. squirella were spatially structured and models including specific habitat types (i.e. upland oak forest and urbanization) consistently explained more variation in genetic distance (median pR(2)  = 47.78) than spatial distance alone (median pR(2)  = 23.81). Moreover, we estimate the relative importance that spatial distance, upland oak and urbanized habitat have in explaining genetic structure of H. squirella. We discuss how these habitat types may mechanistically facilitate dispersal in H. squirella. This study provides empirical support for the hypothesis that habitat-use can be an informative correlate of genetic differentiation, even for species that occur in a wide range of habitats.

Fat frogs, mobile genes: unexpected phylogeographic patterns for the ornate chorus frog (Pseudacris ornata)

The southeastern coastal plain of the United States is a region marked by extraordinary phylogeographic congruence that is frequently attributed to the changing sea levels that occurred during the glacial-interglacial cycles of the Pleistocene epoch. A phylogeographic break corresponding to the Apalachicola River has been suggested for many species studied to date that are endemic to this region. Here, we used this pattern of phylogeographic congruence to develop and test explicit hypotheses about the genetic structure in the ornate chorus frog (Pseudacris ornata). Using 1299 bp of mtDNA sequence and seven nuclear microsatellite markers in 13 natural populations of P. ornata, we found three clades corresponding to geographically distinct regions; one spans the Apalachicola River (Southern Clade), one encompasses Georgia and South Carolina (Central Clade) and a third comprises more northerly individuals (Northern Clade). However, it does not appear that typical phylogeographic barriers demarcate these clades. Instead, isolation by distance across the range of the entire species explained the pattern of genetic variation that we observed. We propose that P. ornata was historically widespread in the southeastern United States, and that a balance between genetic drift and migration was the root of the genetic divergence among populations. Additionally, we investigated fine-scale patterns of genetic structure and found the spatial scale at which there was significant genetic structure varied among the regions studied. Furthermore, we discuss our results in light of other phylogeographic studies of southeastern coastal plain organisms and in relation to amphibian conservation and management.