Initial Characterization of Canine T-cell Receptor Repertoires Using RNA-seq Data from Different Diseases and Tissues.

The dog serves as a key translational model in cancer immunotherapy. Understanding the T cell receptor (TCR) repertoire is needed for various cancer immunotherapies. Compared to humans where >300 million TCRs have been identified, <100 canine TCRs are reported. To address this deficiency, we assembled >200,000 complete TCR complementarity-determining region 3 (CDR3) sequences from RNA-seq data published for ~2,000 canine samples of blood, lymph node, and other tissues, of which 613 are tumors. We collected 1,324 human RNA-seq samples to compare the similarities and differences in T-cell repertoires between humans and dogs. Notably, our analysis revealed distinct variable gene usage patterns between blood samples and solid tissues in both canine and human samples for TRA and TRB loci. Moreover, our investigation led to the discovery of novel V gene and allele candidates in the canine genome. Our findings also revealed that the canine CDR3 resembled human CDR3 in terms of length and motifs. Additionally, our study unveiled shared traits in cancer TCRs between dogs and humans, including longer lengths and higher hydrophobicity of private CDR3s. Our results indicated the diversity of canine to be more comparable to that of humans than mice. Our study provides an initial landscape of the canine TCR repertoire, highlighting both its similarities and differences with the human counterpart, thus laying the groundwork for future research in comparative immunology and vaccine development.

Canine major histocompatibility complex class I (MHC-I) diversity landscape.

The genes of the Major Histocompatibility Complex class I (MHC-I) are among the most diverse in the mammalian genome, playing a crucial role in immunology. Understanding the diversity landscape of MHC-I is therefore of paramount importance. The dog is a key translational model in various biomedical fields. However, our understanding of the canine MHC-I diversity landscape lags significantly behind that of humans. To address this deficiency, we used our newly developed software, KPR de novo assembler and genotyper, to genotype 1,325 samples from 1,025 dogs with paired-end RNA-seq data from 43 BioProjects, after extensive quality control. Among 926 dogs that pass the QC, 591 dogs (64%) have at least one allele genotyped, and a total of 97 known alleles and 52 putative new alleles were identified. Further analysis reveals that DLA-I gene expression levels vary among the tissues, with lowest for testis and brain tissues and highest for blood, corpus luteum, and spleen. We identified dominant alleles in each of the 17 canine breeds, as well as among the entire canine population. Furthermore, our analysis also identifies breed-specific alleles and mutually co-occurred/exclusive alleles. Our study indicates that canine DLA-88 is as diversified as human HLA-A/B/C genes within the entire population, but less diversified within a breed than with HLA-A/B/C within an ethnic group. Lastly, we examined the hypervariable regions (HVR) within or across human/canine MHC-I alleles and found that 80% of the HVRs overlap between the two species. We further noted that 80% of the HVRs are within 4A contact with the peptides, and that the dog-human difference overlaps with only 20% HVRs. Our research offers valuable insights for immunological studies involving dogs.

Human basal-like breast cancer is represented by one of the two mammary tumor subtypes in dogs.

BACKGROUND: About 20% of breast cancers in humans are basal-like, a subtype that is often triple-negative and difficult to treat. An effective translational model for basal-like breast cancer is currently lacking and urgently needed. To determine whether spontaneous mammary tumors in pet dogs could meet this need, we subtyped canine mammary tumors and evaluated the dog-human molecular homology at the subtype level. METHODS: We subtyped 236 canine mammary tumors from 3 studies by applying various subtyping strategies on their RNA-seq data. We then performed PAM50 classification with canine tumors alone, as well as with canine tumors combined with human breast tumors. We identified feature genes for human BLBC and luminal A subtypes via machine learning and used these genes to repeat canine-alone and cross-species tumor classifications. We investigated differential gene expression, signature gene set enrichment, expression association, mutational landscape, and other features for dog-human subtype comparison. RESULTS: Our independent genome-wide subtyping consistently identified two molecularly distinct subtypes among the canine tumors. One subtype is mostly basal-like and clusters with human BLBC in cross-species PAM50 and feature gene classifications, while the other subtype does not cluster with any human breast cancer subtype. Furthermore, the canine basal-like subtype recaptures key molecular features (e.g., cell cycle gene upregulation, TP53 mutation) and gene expression patterns that characterize human BLBC. It is enriched in histological subtypes that match human breast cancer, unlike the other canine subtype. However, about 33% of canine basal-like tumors are estrogen receptor negative (ER-) and progesterone receptor positive (PR+), which is rare in human breast cancer. Further analysis reveals that these ER-PR+ canine tumors harbor additional basal-like features, including upregulation of genes of interferon-γ response and of the Wnt-pluripotency pathway. Interestingly, we observed an association of PGR expression with gene silencing in all canine tumors and with the expression of T cell exhaustion markers (e.g., PDCD1) in ER-PR+ canine tumors. CONCLUSIONS: We identify a canine mammary tumor subtype that molecularly resembles human BLBC overall and thus could serve as a vital translational model of this devastating breast cancer subtype. Our study also sheds light on the dog-human difference in the mammary tumor histology and the hormonal cycle.

Human basal-like breast cancer is represented by one of the two mammary tumor subtypes in dogs.

Background: About 20% of breast cancers in humans are basal-like, a subtype that is often triple negative and difficult to treat. An effective translational model for basal-like breast cancer (BLBC) is currently lacking and urgently needed. To determine if spontaneous mammary tumors in pet dogs could meet this need, we subtyped canine mammary tumors and evaluated the dog-human molecular homology at the subtype level. Methods: We subtyped 236 canine mammary tumors from 3 studies by applying various subtyping strategies on their RNA-seq data. We then performed PAM50 classification with canine tumors alone, as well as with canine tumors combined with human breast tumors. We investigated differential gene expression, signature gene set enrichment, expression association, mutational landscape, and other features for dog-human subtype comparison. Results: Our independent genome-wide subtyping consistently identified two molecularly distinct subtypes among the canine tumors. One subtype is mostly basal-like and clusters with human BLBC in cross-species PAM50 classification, while the other subtype does not cluster with any human breast cancer subtype. Furthermore, the canine basal-like subtype recaptures key molecular features (e.g., cell cycle gene upregulation, TP53 mutation) and gene expression patterns that characterize human BLBC. It is enriched histological subtypes that match human breast cancer, unlike the other canine subtype. However, about 33% of canine basal-like tumors are estrogen receptor negative (ER-) and progesterone receptor positive (PR+), which is rare in human breast cancer. Further analysis reveals that these ER-PR+ canine tumors harbor additional basal-like features, including upregulation of genes of interferon-γ response and of the Wnt-pluripotency pathway. Interestingly, we observed an association of PGR expression with gene silencing in all canine tumors, and with the expression of T cell exhaustion markers (e.g., PDCD1 ) in ER-PR+ canine tumors. Conclusions: We identify a canine mammary tumor subtype that molecularly resembles human BLBC overall, and thus could serve as a vital spontaneous animal model of this devastating breast cancer subtype. Our study also sheds light on the dog-human difference in the mammary tumor histology and the hormonal cycle.

Canine tumor mutational burden is correlated with TP53 mutation across tumor types and breeds.

Spontaneous canine cancers are valuable but relatively understudied and underutilized models. To enhance their usage, we reanalyze whole exome and genome sequencing data published for 684 cases of >7 common tumor types and >35 breeds, with rigorous quality control and breed validation. Our results indicate that canine tumor alteration landscape is tumor type-dependent, but likely breed-independent. Each tumor type harbors major pathway alterations also found in its human counterpart (e.g., PI3K in mammary tumor and p53 in osteosarcoma). Mammary tumor and glioma have lower tumor mutational burden (TMB) (median < 0.5 mutations per Mb), whereas oral melanoma, osteosarcoma and hemangiosarcoma have higher TMB (median ≥ 1 mutations per Mb). Across tumor types and breeds, TMB is associated with mutation of TP53 but not PIK3CA, the most mutated genes. Golden Retrievers harbor a TMB-associated and osteosarcoma-enriched mutation signature. Here, we provide a snapshot of canine mutations across major tumor types and breeds.

Vibrational spectra of small methylamine clusters accessed by an ab initio anharmonic approach.

Methylamine (MMA) is one of the simplest amines, and the vibrational spectra of its dimer have recently been obtained experimentally. The vibrational spectra of NH stretch modes were well resolved, but the complex features of the CH3 group could not be fully accounted for even with the assistance of ab initio molecular dynamics (AIMD) with various density functional methods. In this study, we carried out anharmonic vibrational calculations on MMA clusters up to tetramers using MP2/aug-cc-pVDZ to examine vibrational coupling among CH/NH and compute the vibrational spectra of these clusters between 2800 and 3500 cm-1. We found that the main origin of the complexity between 2800 and 3000 cm-1 was caused by Fermi resonance (FR) between the stretching and bending overtones of the CH3 group. This spectral feature becomes simpler in trimers and tetramers. Furthermore, Fermi resonance in the NH2 group is found to be very strong. In the MMA dimer, no noticeable FR features can be found; however, in its trimers and tetramers, the enhancement of hydrogen bond strength due to the cooperative effect will cause the N-H stretching mode to red-shift to revert the energy order of the fundamental of the N-H stretch and overtone of N-H bending between n = 3 and n = 4. Therefore, significant re-distribution of the intensities of the bands at 3200 and 3300 cm-1 should be seen.

Exploration of hydrogen bond networks and potential energy surfaces of methanol clusters using a two-stage clustering algorithm.

The potential energy surface (PES), structures and thermal properties of methanol clusters (MeOH)n with n = 8-15 were explored by replica-exchange molecular dynamics (REMD) simulations with an empirical model and refined using density functional theory (DFT) methods. For a given size, local minima structures were sampled from REMD trajectories and archived by a newly developed molecular database via a two-stage clustering algorithm (TSCA). Our TSCA utilizes both the topology of O-HO hydrogen bonding networks and the similarity of the shapes to filter out duplicates. The screened molecular database contains only distinct conformers sampled from REMD and their structures are further optimized by the two DFT methods with and without dispersion correction to examine the influence of dispersion on their structures and binding energies. Inspecting different O-HO networks, the binding energies of methanol clusters are highly degenerated. The degeneracy is more significant with the dispersion effect that introduces weaker but more complex C-HO bonds. Based on the structures we have searched, we were able to extract general trends and these datasets can serve as a starting point for further high-level ab initio calculations to reveal the true energy landscape of methanol clusters.

An ab initio anharmonic approach to study vibrational spectra of small ammonia clusters.

Fermi resonance between the N-H stretching (ν1 and ν3) and the overtone of N-H bending (2ν4) in ammonia has hindered the interpretation and assignments of experimental spectra of small ammonia clusters. In this work, we carried out anharmonic vibrational calculations using MP2/aug-cc-pVDZ to examine the vibrational spectra of (NH3)n=1-5 with a focus on the size evolution. The enhancement of hydrogen bond strength due to cooperative effects will cause ν1 and ν4 to red-shift and blue-shift, respectively, when the size of the cluster increases. Our calculations show that the energy order of fundamental of ν1 and overtone of ν4 is reversed between n = 3 and n = 4. Therefore, while the resultant mixed levels do not show remarkable shifts in their peak positions, the main identity of these mixed levels changes and this causes significant re-distribution of their intensities. Furthermore, our ab initio anharmonic calculation scheme can directly evaluate the coupling strength between different N-H stretching and overtone of N-H bending without any experimental parameters, thus leading us to a simpler picture to understand the Fermi resonance in (NH3)n.