Biology subjects

Graves, J. L.

Publications and source records attributed to Graves, J. L..

5 recordsLinked to original sources

bioRxiv2025

Molecular Plasticity of T Cells Informs Their Possible Adaptation in 4T1 Tumors

BackgroundThe triple-negative breast cancer (TNBC) microenvironment (TME) undergoes progressive reprogramming, transitioning from an early immune-active state to a late immune-suppressed state. While tumor cell plasticity has been extensively studied, the molecular plasticity of T cells in vivo remains poorly defined. ObjectivesTo characterize transcriptional changes in T cells during TNBC progression and identify stage-specific shifts in T cell function, polarization, and antigen-presenting cell (APC)-T cell interactions. ResultsTranscriptional analysis of T cells from BALB/c mice bearing 4T1 tumors at 1, 3, and 6 weeks revealed a decline in T cell-associated genes from 194 at 1 week to 156 at 6 weeks, with a significant late-stage loss of TCR diversity and contraction of natural killer T (NKT)- and {gamma}{delta} T cell-related transcripts. Cytokine and transcription factor dynamics reflected temporal T cell polarization: early (1 week) IL-12/{beta}-STAT4 signaling supports CD4+ type 1 T helper cell (Th1) and type 1 CD8+ cytotoxic T cell (Tc1) responses; intermediate (3 weeks) IL-21 and BCL6 expression suggest transient CD8+ cytotoxic follicular T cell (Tfc) skewing; and late (6 weeks) AhR and IL-1{beta} induction reflect interleukin 17/22 producing CD8+ T cell (Tc17/Tc22) transition. Pro-inflammatory cytokines and chemokines increased over time, while immunosuppressive mediators (e.g., IL-10) declined significantly. Antigen-presenting cell (APC)-T cell crosstalk deteriorated at 6 weeks, characterized by a reduction in the expression of co-stimulatory and APC genes. Despite an early dominance of M1-like macrophage signals (e.g., IL-12/{beta}), persistent expression of arginase 1 (ARG1) and other M2-associated genes indicated a stable tolerogenic niche. ConclusionsTNBC progression is characterized by progressive T cell functional decline, narrowing of TCR diversity, impaired APC-T cell interactions, and sustained macrophage-driven immunosuppression. These temporally coordinated immune shifts suggest tumor-driven adaptation toward immune evasion and identify potential windows for stage-specific immunotherapeutic intervention.

cancer biology↗

bioRxiv2025

Molecular Phenotypic Plasticity Informs Possible Adaptive Change of Triple-Negative Breast Cancer Cells In Vivo

Background and ObjectivesCancer evolves via interconnected mechanisms, including changes in extrachromosomal DNA (ecDNA), genetic instability, and interactions with the tumor microenvironment (TME). These mechanisms allow for some clones to evolve metastatic traits, evade the immune system, and resist chemotherapy. However, how cancer cells evolve in vivo remains poorly understood. This study investigates the in vivo changes in gene expression of triple-negative breast cancer (TNBC) cells implanted in BALB/c mice. MethodologyWe analyzed RNA-seq data from 4T1 TNBC cells and tumors at different growth stages (1-, 3-, and 6-week) to identify differentially expressed genes, protein-protein interactions, and ecDNA alterations. We also assessed how ecDNA and genomic instability proteins interact with anti-TNBC drugs ResultsOur results reveal early transcriptional shifts within one week of tumor implantation, showing rapid acclimation. Changes in gene expression continued over time, with significant molecular reprogramming observed at six weeks under in vivo environmental pressures, including ecDNA alterations and immune evasion. The shift from the earlier generation (1 week) to the later generation (6 weeks) suggests cumulative alterations in key oncogenic pathways related to tumor progression. Additionally, we found that mutations in ecDNA and genomic instability proteins influence drug binding affinity, suggesting that adaptive changes may impact chemotherapy response. Conclusions and ImplicationsThis study provides new insights into how TNBC tumors may evolve over time and novel ecDNA-related mechanisms of possible tumor adaptation, highlighting potential biomarkers for tumor aggression and immune evasion, which could help develop more effective therapeutic strategies against TNBC.

cancer biology↗

bioRxiv2023

Body weight, gonadectomy, and other risk factors for diagnosis of osteoarthritis in companion dogs

OBJECTIVETo evaluate age, sex, body weight, breed, neuter status, and age at neutering as risk factors for diagnosis of osteoarthritis in companion dogs ANIMALSDogs seen as patients at Banfield Pet Hospital in the United States from 1998-2019 with a date of death in 2019. The final cohort consisted of 131,140 dogs. METHODSIn this retrospective cohort study, Cox proportional hazard models were used to test for associations between osteoarthritis incidence and age at baseline, sex, maximum body weight, maximum body condition score, neuter status, and age at neutering. The same model was used to test these associations in 12 representative breeds, chosen based on breed weight and sample size. RESULTSOlder age, higher adult body weight, gonadectomy, and younger age at gonadectomy were significantly associated with higher risks of osteoarthritis in the total cohort and in all 12 breeds evaluated. Higher body condition score and sex were also significantly associated with osteoarthritis but with minimal effect sizes in the overall cohort, and these risk factors were not consistently significant in all breeds tested. CLINICAL RELEVANCEThese results will assist veterinarians in identifying dogs at higher risk for osteoarthritis and applying appropriate diagnostic, preventative, and treatment interventions. An understanding of potentially modifiable risk factors, such as body condition, and neutering, will support evidence-based discussions with dog owners about risk management in individual patients.

systems biology↗

bioRxiv2022

Evaluating instruments for assessing healthspan: a multi-center cross-sectional study on health-related quality of life (HRQL) and frailty in the companion dog

Developing valid tools that assess key determinants of canine healthspan such as frailty and health-related quality of life (HRQL) is essential to characterizing and understanding aging in dogs. Additionally, because the companion dog is an excellent translational model for humans, such tools can be applied to evaluate gerotherapeutics and investigate mechanisms underlying longevity in both dogs and humans. In this multi-center, cross sectional study, we investigated the use of a clinical questionnaire (Canine Frailty Index; CFI; Banzato et al., 2019) to assess frailty and an owner assessment tool (VetMetrica HRQL) to evaluate HRQL in 451 adult companion dogs. Results demonstrated validity of the tools by confirming expectations that frailty and HRQL deteriorate with age. CFI scores were significantly higher (higher frailty) and HRQL scores significantly lower (worse HRQL) in old dogs ([≥] 7 years of age) compared to young dogs ([≥] 2 and < 6 years of age). Body size (small < 25lbs or large > 50lbs) was not associated with CFI or total HRQL score. However, older, larger dogs showed faster age-related decline in HRQL scores specific to owner-reported activity and comfort. Findings suggest that the clinician-assessed CFI and owner-reported VetMetrica HRQL are useful tools to evaluate two determinants of healthspan in dogs: the accumulation of frailty and the progressive decline in quality of life. Establishing validated tools that operationalize the assessment of canine healthspan is critical for the advancement of geroscience and the development of gerotherapeutics that benefit both human and veterinary medicine. Graphical abstractGraphical summary of the design, results, and conclusions of the study. O_FIG O_LINKSMALLFIG WIDTH=179 HEIGHT=200 SRC="FIGDIR/small/500746v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1d70950org.highwire.dtl.DTLVardef@a4748borg.highwire.dtl.DTLVardef@df6892org.highwire.dtl.DTLVardef@14a7aed_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2020

Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli

Antibiotic resistance is a growing health concern. Efforts to control resistance would benefit from an improved ability to forecast when and how it will evolve. Epistatic interactions between mutations can promote divergent evolutionary trajectories, which complicates our ability to predict evolution. We recently showed that differences between genetic backgrounds can lead to idiosyncratic responses in the evolvability of phenotypic resistance, even among closely related Escherichia coli strains. In this study, we examined whether a strains genetic background also influences the genotypic evolution of resistance. Do lineages founded by different genotypes take parallel or divergent mutational paths to achieve their evolved resistance states? We addressed this question by sequencing the complete genomes of antibiotic-resistant clones that evolved from several different genetic starting points during our earlier experiments. We first validated our statistical approach by quantifying the specificity of genomic evolution with respect to antibiotic treatment. As expected, mutations in particular genes were strongly associated with each drug. Then, we determined that replicate lines evolved from the same founding genotypes had more parallel mutations at the gene level than lines evolved from different founding genotypes, although these effects were more subtle than those showing antibiotic specificity. Taken together with our previous work, we conclude that historical contingency can alter both genotypic and phenotypic pathways to antibiotic resistance. SignificanceA fundamental question in evolution is the repeatability of adaptation. Will independently evolving populations respond similarly when facing the same environmental challenge? This question also has important public-health implications related to the growing problem of antibiotic resistance. For example, efforts to control resistance might benefit from accurately predicting mutational paths to resistance. However, this goal is complicated when a lineages prior history alters its subsequent evolution. We recently found that differences between genetic backgrounds can lead to unpredictable responses in phenotypic resistance. Here, we report that genetic background can similarly alter genotypic paths to resistance. This historical contingency underscores the importance of accounting for stochasticity, in the past as well as at present, when designing evolutionarily informed treatment strategies.

evolutionary biology↗