Evolutionary and expression analyses reveal a pattern of ancient duplications and functional specializations in the diversification of the Downstream of Kinase (DOK) genes

DOK1 and DOK2 regulate CD8 T cell signaling and memory formation without affecting tumor cell killing

Targeting intracellular inhibiting proteins has been revealed to be a promising strategy to improve CD8+ T cell anti-tumor efficacy. Here, we are focusing on intracellular inhibiting proteins specific to TCR signaling: DOK1 and DOK2 expressed in T cells. We hypothesized that depletion of intracellular inhibition checkpoint DOK1 and DOK2 could improve CD8+ T-cell based cancer therapies. To evaluate the role of DOK1 and DOK2 depletion in physiology and effector function of CD8+ T lymphocytes and in cancer progression, we established a transgenic T cell receptor mouse model specific to melanoma antigen hgp100 (pmel-1 TCR Tg) in WT and Dok1/Dok2 DKO (double KO) mice. We showed that both DOK1 and DOK2 depletion in CD8+ T cells after an in vitro pre-stimulation induced a higher percentage of effector memory T cells as well as an up regulation of TCR signaling cascade- induced by CD3 mAbs, including the increased levels of pAKT and pERK, two major phosphoproteins involved in T cell functions. Interestingly, this improved TCR signaling was not observed in naïve CD8+ T cells. Despite this enhanced TCR signaling essentially shown upon stimulation via CD3 mAbs, pre-stimulated Dok1/Dok2 DKO CD8+ T cells did not show any increase in their activation or cytotoxic capacities against melanoma cell line expressing hgp100 in vitro. Altogether we demonstrate here a novel aspect of the negative regulation by DOK1 and DOK2 proteins in CD8+ T cells. Indeed, our results allow us to conclude that DOK1 and DOK2 have an inhibitory role following long term T cell stimulations.

Cross-species transcriptomics identifies obesity associated genes between human and mouse studies

BACKGROUND

Fundamentally defined by an imbalance in energy consumption and energy expenditure, obesity is a significant risk factor of several musculoskeletal conditions including osteoarthritis (OA). High-fat diets and sedentary lifestyle leads to increased adiposity resulting in systemic inflammation due to the endocrine properties of adipose tissue producing inflammatory cytokines and adipokines. We previously showed serum levels of specific adipokines are associated with biomarkers of bone remodelling and cartilage volume loss in knee OA patients. Whilst more recently we find the metabolic consequence of obesity drives the enrichment of pro-inflammatory fibroblast subsets within joint synovial tissues in obese individuals compared to those of BMI defined 'health weight'. As such this present study identifies obesity-associated genes in OA joint tissues which are conserved across species and conditions.

METHODS

The study utilised 6 publicly available bulk and single-cell transcriptomic datasets from human and mice studies downloaded from Gene Expression Omnibus (GEO). Machine learning models were employed to model and statistically test datasets for conserved gene expression profiles. Identified genes were validated in OA tissues from obese and healthy weight individuals using quantitative PCR method (N = 38). Obese and healthy-weight patients were categorised by BMI > 30 and BMI between 18 and 24.9 respectively. Informed consent was obtained from all study participants who were scheduled to undergo elective arthroplasty.

RESULTS

Principal component analysis (PCA) was used to investigate the variations between classes of mouse and human data which confirmed variation between obese and healthy populations. Differential gene expression analysis filtered on adjusted p-values of p < 0.05, identified differentially expressed genes (DEGs) in mouse and human datasets. DEGs were analysed further using area under curve (AUC) which identified 12 genes. Pathway enrichment analysis suggests these genes were involved in the biosynthesis and elongation of fatty acids and the transport, oxidation, and catabolic processing of lipids. qPCR validation found the majority of genes showed a tendency to be upregulated in joint tissues from obese participants. Three validated genes, IGFBP2 (p = 0.0363), DOK6 (0.0451) and CASP1 (0.0412) were found to be significantly different in obese joint tissues compared to lean-weight joint tissues.

CONCLUSIONS

The present study has employed machine learning models across several published obesity datasets to identify obesity-associated genes which are validated in joint tissues from OA. These results suggest obesity-associated genes are conserved across conditions and may be fundamental in accelerating disease in obese individuals. Whilst further validations and additional conditions remain to be tested in this model, identifying obesity-associated genes in this way may serve as a global aid for patient stratification giving rise to the potential of targeted therapeutic interventions in such patient subpopulations.

Comprehensive analysis of DOK family genes expression, immune characteristics, and drug sensitivity in human tumors

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The expression of DOK family genes is related to overall survival (OS), clinical stage, tumor mutation, methylation, CNV, and SNV.

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DOK family genes are significantly associated with poor prognosis of UVM.

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DOK1-DOK3 has obvious correlation with tumor immunity and tumor microenvironment.

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DOK family gene is significantly related to tumor stemness and drug sensitivity.

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The expression of DOK family genes is related to the activation of EMT and hormone ER pathways, and is related to the inhibition of DNA damage response, cell cycle, and hormone AR pathways.

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DOK1 and DOK3, DOK2 and DOK3 have the significant correlation.

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