A novel BLK-induced tumor model

Integrated multi-omics analysis of PBX1 in mouse adult neural stem- and progenitor cells identifies a transcriptional module that functionally links PBX1 to TCF3/4

Developmental transcription factors act in networks, but how these networks achieve cell- and tissue specificity is still poorly understood. Here, we explored pre-B cell leukemia homeobox 1 (PBX1) in adult neurogenesis combining genomic, transcriptomic, and proteomic approaches. ChIP-seq analysis uncovered PBX1 binding to numerous genomic sites. Integration of PBX1 ChIP-seq with ATAC-seq data predicted interaction partners, which were subsequently validated by mass spectrometry. Whole transcriptome spatial RNA analysis revealed shared expression dynamics of Pbx1 and interacting factors. Among these were class I bHLH proteins TCF3 and TCF4. RNA-seq following Pbx1, Tcf3 or Tcf4 knockdown identified proliferation- and differentiation associated genes as shared targets, while sphere formation assays following knockdown argued for functional cooperativity of PBX1 and TCF3 in progenitor cell proliferation. Notably, while physiological PBX1-TCF interaction has not yet been described, chromosomal translocation resulting in genomic TCF3::PBX1 fusion characterizes a subtype of acute lymphoblastic leukemia. Introducing Pbx1 into Nalm6 cells, a pre-B cell line expressing TCF3 but lacking PBX1, upregulated the leukemogenic genes BLK and NOTCH3, arguing that functional PBX1-TCF cooperativity likely extends to hematopoiesis. Our study hence uncovers a transcriptional module orchestrating the balance between progenitor cell proliferation and differentiation in adult neurogenesis with potential implications for leukemia etiology.

Identification of genomic regions and pathways associated with traits related to rumen acidosis in feedlot Nellore cattle

There may be an increased risk of metabolic disorders, such as rumen acidosis, in cattle fed high-concentrate diets, particularly those from Bos taurus indicus genotypes, which have shown to be more sensitive to ruminal acidification. Therefore, this study aimed to estimate (co)variance components and identify genomic regions and pathways associated with ruminal acidosis in feedlot Nellore cattle fed high-concentrate diets. It was utilized a dataset containing a total of 642 Nellore bulls that were genotyped from seven feedlot nutrition studies. The GGP Indicus 35k panel was used with the single step genome-wide association study methodology in which the effects of the markers were obtained from the genomic values estimated by the GBLUP model. A bivariate model to estimate genetic correlations between the economically important traits and indicator traits for acidosis was used. The traits evaluated in this study that were nutritionally related to rumen acidosis included average daily gain (ADG), final body weight, time spent eating (TSE), time spent ruminating, rumenitis score (RUM), rumen absorptive surface area (ASA), rumen keratinized layer thickness (KER) and hot carcass weight (HCW). The identified candidate genes were mainly involved in the negative or non-regulation of the apoptotic process, salivary secretion, and transmembrane transport. The genetic correlation between HCW and ASA was low positive (0.27 ± 0.23), and between ADG and ASA was high moderate (0.58 ± 0.59). A positive genetic correlation between RUM and all performance traits was observed, and TSE correlated negatively with HCW (-0.33 ± 0.21), ASA (-0.75 ± 0.48), and KER (-0.40 ± 0.27). The genetic association between economically important traits and indicator traits for acidosis suggested that Nellore cattle may be more sensitive to acidosis in feedlot systems.

Construction and analysis of a lysosome-dependent cell death score-based prediction model for non-small cell lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) is the most common type of tumor globally and the leading cause of cancer-related deaths. Although treatment strategies such as immune checkpoint inhibitors and chemotherapy have advanced, the heterogeneity among NSCLC patients results in significant variability in treatment outcomes. Studies have shown that certain patients respond poorly to immune checkpoint inhibitors, indicating that treatment response is closely related to multiple factors. Therefore, it is necessary to develop predictive models to stratify patients based on gene expression and clinical characteristics, aiming for precision therapy.

OBJECTIVE

This study aims to construct a stratified prognostic model for NSCLC patients based on lysosome-dependent cell death (LDCD) scoring by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data. By analyzing the immune-related characteristics of high-risk and low-risk groups, we further explored the impact of cell death patterns on lung cancer and identified potential therapeutic targets.

METHODS

This study obtained single-cell RNA sequencing data and gene expression data of NSCLC patients and normal lung tissues from the GEO and TCGA databases. We used R packages such as Seurat and CellChat for data preprocessing and analysis, and performed dimensionality reduction and visualization through Principal Component Analysis (PCA) and UMAP algorithms. LASSO regression analysis was used to construct the predictive model, followed by cross-validation and ROC curve analysis. The model's effectiveness was validated through survival analysis and immune microenvironment analysis.

RESULTS

The study showed a significant increase in the proportion of monocytes in NSCLC tissues, suggesting their important role in cancer progression. Cell communication analysis indicated that macrophages, smooth muscle cells, and myeloid cells exhibit strong intercellular communication during cancer progression. Using the constructed prognostic model based on 12 LDCD-related genes, we found significant differences in overall survival and immune microenvironment between the high-risk and low-risk groups.

Desmoplastic small round cell tumor: from genomics to targets, potential paths to future therapeutics

Desmoplastic Small Round Cell Tumor (DSRCT) is a highly aggressive pediatric cancer caused by a reciprocal translocation between chromosomes 11 and 22, leading to the formation of the EWSR1::WT1 oncoprotein. DSRCT presents most commonly in the abdominal and pelvic peritoneum and remains refractory to current treatment regimens which include chemotherapy, radiotherapy, and surgery. As a rare cancer, sample and model availability have been a limiting factor to DSRCT research. However, the establishment of rare tumor banks and novel cell lines have recently propelled critical advances in the understanding of DSRCT biology and the identification of potentially promising targeted therapeutics. Here we review model and dataset availability, current understanding of the EWSR1::WT1 oncogenic mechanism, and promising preclinical therapeutics, some of which are now advancing to clinical trials. We discuss efforts to inhibit critical dependencies including NTRK3, EGFR, and CDK4/6 as well as novel immunotherapy strategies targeting surface markers highly expressed in DSRCT such as B7-H3 or neopeptides either derived from or driven by the fusion oncoprotein. Finally, we discuss the prospect of combination therapies and strategies for prioritizing clinical translation.

Transcriptomic analysis identifies B-lymphocyte kinase as a therapeutic target for desmoplastic small round cell tumor cancer stem cell-like cells

Desmoplastic small round cell tumor (DSRCT) is an aggressive pediatric cancer caused by the EWSR1-WT1 fusion oncoprotein. The tumor is refractory to treatment with a 5-year survival rate of only 15-25%, necessitating the development of novel therapeutics, especially those able to target chemoresistant subpopulations. Novel in vitro cancer stem cell-like (CSC-like) culture conditions increase the expression of stemness markers (SOX2, NANOG) and reduce DSRCT cell line susceptibility to chemotherapy while maintaining the ability of DSRCT cells to form xenografts. To gain insights into this chemoresistant model, RNA-seq was performed to elucidate transcriptional alterations between DSRCT cells grown in CSC-like spheres and normal 2-dimensional adherent state. Commonly upregulated and downregulated genes were identified and utilized in pathway analysis revealing upregulation of pathways related to chromatin assembly and disassembly and downregulation of pathways including cell junction assembly and extracellular matrix organization. Alterations in chromatin assembly suggest a role for epigenetics in the DSRCT CSC-like state, which was further investigated with ATAC-seq, identifying over 10,000 differentially accessible peaks, including 4444 sphere accessible peaks and 6,120 adherent accessible peaks. Accessible regions were associated with higher gene expression, including increased accessibility of the CSC marker SOX2 in CSC-like culture conditions. These analyses were further utilized to identify potential CSC therapeutic targets, leading to the identification of B-lymphocyte kinase (BLK) as a CSC-enriched, EWSR1-WT1-regulated, druggable target. BLK inhibition and knockdown reduced CSC-like properties, including abrogation of tumorsphere formation and stemness marker expression. Importantly, BLK knockdown reduced DSRCT CSC-like cell chemoresistance, making its inhibition a promising target for future combination therapy.

Gene and pathway based burden analyses in familial lymphoid cancer cases: Rare variants in immune pathway genes

Genome-wide association studies have revealed common genetic variants with small effect sizes associated with diverse lymphoid cancers. Family studies have uncovered rare variants with high effect sizes. However, these variants explain only a portion of the heritability of these cancers. Some of the missing heritability may be attributable to rare variants with small effect sizes. We aim to identify rare germline variants associated with familial lymphoid cancers using exome sequencing. One case per family was selected from 39 lymphoid cancer families based on early onset of disease or rarity of subtype. Control data was from Non-Finnish Europeans in gnomAD exomes (N = 56,885) or ExAC (N = 33,370). Gene and pathway-based burden tests for rare variants were performed using TRAPD. Five putatively pathogenic germline variants were found in four genes: INTU, PEX7, EHHADH, and ASXL1. Pathway-based association tests identified the innate and adaptive immune systems, peroxisomal pathway and olfactory receptor pathway as associated with lymphoid cancers in familial cases. Our results suggest that rare inherited defects in the genes involved in immune system and peroxisomal pathway may predispose individuals to lymphoid cancers.

Loss of BLK expression as a potential predictor of poor prognosis and immune checkpoint blockade response in NSCLC and contribute to tumor progression

BACKGROUND

Immune checkpoint blockade (ICB) has been proved to have significant anti-tumor effect in the clinical treatment of non-small cell lung cancer (NSCLC). Therefore, biomarkers predicting ICB response can provide better treatment for patients with NSCLC.

METHODS

Differential expression genes (DEGs) were identified by ImmuCellAI database. Copy number alteration (CNA) was analyzed by cBioPortal. The predicted efficiency of 4 genes on cancer immunotherapy was assessed by ROC analysis. The survival value of BLK was analyzed by Kaplan-Meier plotter and Prognoscan analysis. Clinical significance of BLK IHC-TMA score in NSCLC was also explored. The CCK-8 assay, wound healing assay, western blot assay in vitro and subcutaneous xenograft experiments in vivo were used for investigating the functions of BLK. The RNA-sequencing were performed to screen BLK regulated genes and conducted for GO/KEGG enrichment analysis. The transcriptional regulatory factor of BLK promoter region was predicted by ChIP-seq analysis.

RESULTS

39 common DEGs between ICB Response (R) group and No Response (NR) group with NSCLC were identified, in which the CNA frequency of BLK deletion (> 6%) was found. The predicted efficiency of BLK on immunotherapy was performed best in NSCLC (AUC>0.7). Low expression of BLK was related to NSCLC with significantly poor prognosis. BLK overexpression can inhibit growth of NSCLC via activating apoptosis pathway, inhibiting the G2M checkpoint and Glycolysis pathway. The enrichment analysis indicated that BLK regulated genes related to oncogenic potential in NSCLC. Besides, BLK expression was inhibited via H3K27me3 modification in A549 and H1299 cells. BLK mRNA level was negatively correlated with methylation and positively correlated with the tumor purity in NSCLC.

CONCLUSION

Our study provides strong evidence that low expression of BLK may serve as a biomarker for poor prognosis in NSCLC, while response to ICB therapy and contributes to NSCLC tumor progression.

The survival rate of laryngeal squamous cell carcinoma: impact of IL1RAP rs4624606, IL1RL1 rs1041973, IL-6 rs1800795, BLK rs13277113, and TIMP3 rs9621532 single nucleotide polymorphisms

PURPOSE

Results of laryngeal squamous cell carcinoma (LSCC) treatment and the 5 year survival rate of these patients remain poor. To purify therapeutic targets, investigation of new specific and prognostic blood-based markers for LSCC development is essential.

METHODS

In the present study, we evaluated five single nucleotide polymorphisms (SNPs): IL1RAP rs4624606, IL1RL1 rs1041973, IL-6 rs1800795, BLK rs13277113, and TIMP3 rs9621532, and determined their associations with the patients' 5 year survival rate. Also, we performed a detailed statistical analysis of different LSCC patients' characteristics impact on their survival rate.

RESULTS

Three hundred fifty-three LSCC patients and 538 control subjects were included in this study. The multivariable Cox regression analysis revealed a significant association between patients' survival rate and distribution of IL1RAP rs4624606 variants: patients carrying AT genotype at IL1RAP rs4624606 had a lower risk of death (p = 0.044). Also, it was revealed that tumor size (T) (p = 0.000), tumor differentiation grade (G) (p = 0.015), and IL1RAP rs4624606 genotype (p = 0.044) were effective variables in multivariable Cox regression analysis prognosing survival of LSCC patients. The specific-LSCC 5 year survival rate was 77%.

CONCLUSIONS

In summary, our findings indicate that the genotypic distribution of IL1RAP rs4624606 influences the 5 year survival rate of LSCC patients. The results of the present study facilitate a more complete understanding of LSCC at the biological level, thus providing the base for the identification of new specific and prognostic blood-based markers for LSCC development.

Prognostic significance of BLK expression in R-CHOP treated diffuse large B-cell lymphoma

Background

The aim of the present study was to evaluate the prognostic significance of B-cell lymphocyte kinase (BLK) expression for survival outcomes in diffuse large B-cell lymphoma (DLBCL) patients treated with R-CHOP.

Methods

We retrospectively analyzed the medical records of 89 patients from two tertiary referral hospitals. The expression of BLK, SYK, and CDK1 were evaluated in a semi-quantitative method using an H-score, and the proportions of BCL2 and C-MYC were evaluated.

Results

A total of 89 patients received R-CHOP chemotherapy as a first-line chemotherapy. The expression rates of BLK in tumor cells was 39.2% (n = 34). BLK expression status was not significantly associated with clinical variables; however, BLK expression in tumor cells was significantly associated with the expression of both C-MYC and BCL2 (p = .003). With a median follow-up of 60.4 months, patients with BLK expression had significantly lower 5-year progression-free survival (PFS) and overall survival rates (49.8% and 60.9%, respectively) than patients without BLK expression (77.3% and 86.7%, respectively). In multivariate analysis for PFS, BLK positivity was an independent poor prognostic factor (hazard ratio, 2.208; p = .040).

Conclusions

Here, we describe the clinicopathological features and survival outcome according to expression of BLK in DLBCL. Approximately 39% of DLBCL patients showed BLK positivity, which was associated as a predictive marker for poor prognosis in patients who received R-CHOP chemotherapy.

Oncogenic properties via MAPK signaling of the SOX5-RAF1 fusion gene identified in a wild-type NRAS/BRAF giant congenital nevus

We recently reported an RAF rearrangement without NRAS or BRAF mutations in lesions from Giant Congenital Melanocytic Nevi (CMN). The new gene fusion involves the 5'-end of the promoter-containing N terminus of the SOX5 gene fused to exons 7-16 of the 3'-end of RAF1 gene leading to a SOX5-RAF1 fusion transcript which loses the auto-inhibitory CR1 domain but retains the complete in-frame coding sequence for the C-Terminal kinase domain of the RAF1. Stable expression of SOX5-RAF1 fusion induced growth factor-independent cell growth in murine hematopoietic Ba/F3 cells and melan-a immortalized melanocytes. Besides, it led to the transformation of both Ba/F3 and NIH 3T3 cells as revealed by colony formation assays. Furthermore, its expression results in MAPK activation assessed by increased levels of p-ERK protein in the cytosol of transduced cells. Treatment with Sorafenib and UO126 inhibited proliferation of Ba/F3-SOX5-RAF1 cells in the absence of IL3 but not the PLX 4720, a specific inhibitor of BRAF. Moreover, the tumorigenic and metastatic capacities of SOX5-RAF1 were assessed in vivo. These results indicate that SOX5-RAF1, a driver event for CMN development, has oncogenic capacity. Thus, sequencing of CMN transcriptomes may lead to the identification of this druggable fusion and interfere with the progression toward melanoma.

Integrating multi-omics data through deep learning for accurate cancer prognosis prediction

BACKGROUND

Genomic information is nowadays widely used for precise cancer treatments. Since the individual type of omics data only represents a single view that suffers from data noise and bias, multiple types of omics data are required for accurate cancer prognosis prediction. However, it is challenging to effectively integrate multi-omics data due to the large number of redundant variables but relatively small sample size. With the recent progress in deep learning techniques, Autoencoder was used to integrate multi-omics data for extracting representative features. Nevertheless, the generated model is fragile from data noises. Additionally, previous studies usually focused on individual cancer types without making comprehensive tests on pan-cancer. Here, we employed the denoising Autoencoder to get a robust representation of the multi-omics data, and then used the learned representative features to estimate patients' risks.

RESULTS

By applying to 15 cancers from The Cancer Genome Atlas (TCGA), our method was shown to improve the C-index values over previous methods by 6.5% on average. Considering the difficulty to obtain multi-omics data in practice, we further used only mRNA data to fit the estimated risks by training XGboost models, and found the models could achieve an average C-index value of 0.627. As a case study, the breast cancer prognosis prediction model was independently tested on three datasets from the Gene Expression Omnibus (GEO), and shown able to significantly separate high-risk patients from low-risk ones (C-index>0.6, p-values<0.05). Based on the risk subgroups divided by our method, we identified nine prognostic markers highly associated with breast cancer, among which seven genes have been proved by literature review.

CONCLUSION

Our comprehensive tests indicated that we have constructed an accurate and robust framework to integrate multi-omics data for cancer prognosis prediction. Moreover, it is an effective way to discover cancer prognosis-related genes.

Src-family Protein Tyrosine Kinases: A promising target for treating Cardiovascular Diseases

The Src-family protein tyrosine kinases (SFKs), a subfamily of non-receptor tyrosine kinases, are ubiquitously expressed in various cell types. Numerous studies have suggested that SFKs are related to signal transduction in major cardiac physiological and pathological processes, it is the activity of SFKs that is connected with the maintenance of cardiovascular homeostasis. Upon stimulation of various injury factors or stress, the phosphorylation state of SFKs is changed, which has been found to modulate different cardiac pathological conditions, such as hypertension, coronary heart disease, ischemic heart disease, myocardial ischemia-reperfusion injury, arrhythmia and cardiomyopathy via regulating cell growth, differentiation, movement and function, electrophysiologic signals. This review summarizes the basic information about SFKs, updates its role in the different processes underlying the development of multiple cardiovascular diseases (CVDs), and highlights their potential role as disease biomarkers and therapeutic targets, which would help understand the pathophysiology of CVDs and promote the further potential clinical adhibition.

Emerging Kinase Therapeutic Targets in Pancreatic Ductal Adenocarcinoma and Pancreatic Cancer Desmoplasia

Kinase drug discovery represents an active area of therapeutic research, with previous pharmaceutical success improving patient outcomes across a wide variety of human diseases. In pancreatic ductal adenocarcinoma (PDAC), innovative pharmaceutical strategies such as kinase targeting have been unable to appreciably increase patient survival. This may be due, in part, to unchecked desmoplastic reactions to pancreatic tumors. Desmoplastic stroma enhances tumor development and progression while simultaneously restricting drug delivery to the tumor cells it protects. Emerging evidence indicates that many of the pathologic fibrotic processes directly or indirectly supporting desmoplasia may be driven by targetable protein tyrosine kinases such as Fyn-related kinase (FRK); B lymphoid kinase (BLK); hemopoietic cell kinase (HCK); ABL proto-oncogene 2 kinase (ABL2); discoidin domain receptor 1 kinase (DDR1); Lck/Yes-related novel kinase (LYN); ephrin receptor A8 kinase (EPHA8); FYN proto-oncogene kinase (FYN); lymphocyte cell-specific kinase (LCK); tec protein kinase (TEC). Herein, we review literature related to these kinases and posit signaling networks, mechanisms, and biochemical relationships by which this group may contribute to PDAC tumor growth and desmoplasia.

Predicting breast cancer risk using interacting genetic and demographic factors and machine learning

Breast cancer (BC) is a multifactorial disease and the most common cancer in women worldwide. We describe a machine learning approach to identify a combination of interacting genetic variants (SNPs) and demographic risk factors for BC, especially factors related to both familial history (Group 1) and oestrogen metabolism (Group 2), for predicting BC risk. This approach identifies the best combinations of interacting genetic and demographic risk factors that yield the highest BC risk prediction accuracy. In tests on the Kuopio Breast Cancer Project (KBCP) dataset, our approach achieves a mean average precision (mAP) of 77.78 in predicting BC risk by using interacting genetic and Group 1 features, which is better than the mAPs of 74.19 and 73.65 achieved using only Group 1 features and interacting SNPs, respectively. Similarly, using interacting genetic and Group 2 features yields a mAP of 78.00, which outperforms the system based on only Group 2 features, which has a mAP of 72.57. Furthermore, the gene interaction maps built from genes associated with SNPs that interact with demographic risk factors indicate important BC-related biological entities, such as angiogenesis, apoptosis and oestrogen-related networks. The results also show that demographic risk factors are individually more important than genetic variants in predicting BC risk.

Associations of IL6 rs1800795, BLK rs13277113, TIMP3 rs9621532, IL1RL1 rs1041973 and IL1RAP rs4624606 single gene polymorphisms with laryngeal squamous cell carcinoma

OBJECTIVE

Survival rate of laryngeal squamous cell carcinoma (LSCC) patients is not improving. To understand more complete biology of LSCC, studies focused on identification of new specific and prognostic markers are performed. The aim of current study was to evaluate the impact of five different single nucleotide polymorphisms (SNP) (IL6 rs1800795, BLK rs13277113, TIMP3 rs9621532, IL1RL1 rs1041973 and IL1RAP rs4624606) on LSCC development.

MATERIAL AND METHODS

A total of 891 subjects (353 histologically verified LSCC patients and 538 healthy controls) were involved in this study. The genotyping was carried out using the real-time-PCR.

RESULTS

Statistical analysis revealed statistically significant associations between TIMP3 rs96215332 variants and LSCC in the codominant (OR = 0.600; 95% CI: 0.390-0.922; p = 0.020), overdominant (OR = 0.599; 95% CI: 0.390-0.922; p = 0.020) and additive (OR = 0.675; 95% CI: 0.459-0.991; p = 0.045) models. Also, significant variants of IL1RAP rs4624606 were determined in the codominant (OR = 1.372; 95% CI: 1.031-1.827; p = 0.030), overdominant (OR = 1.353; 95% CI: 1.018-1.798; p = 0.037) and additive (OR = 1.337; 95% CI: 1.038-1.724; p = 0.025) models.

CONCLUSION

Results of the current study indicate significant associations between TIMP3 rs9621532 and IL1RAP rs4624606 gene polymorphisms and LSCC development.

Nuclear Functions of the Tyrosine Kinase Src

Src is the representative member of the Src-family kinases (SFKs), a group of tyrosine kinases involved in several cellular processes. Its main function has been for long confined to the plasma membrane/cytoplasm compartment, being a myristoylated protein anchored to the cell membrane and functioning downstream to receptors, most of them lacking intrinsic kinase activity. In the last decades, new roles for some SFKs have been described in the nuclear compartment, suggesting that these proteins can also be involved in directly regulating gene transcription or nucleoskeleton architecture. In this review, we focused on those nuclear functions specifically attributable to Src, by considering its function as both tyrosine kinase and adapting molecule. In particular, we addressed the Src involvement in physiological as well as in pathological conditions, especially in tumors.

Identification of recurrent noncoding mutations in B-cell lymphoma using capture Hi-C

The identification of driver mutations is fundamental to understanding oncogenesis. Although genes frequently mutated in B-cell lymphoma have been identified, the search for driver mutations has largely focused on the coding genome. Here we report an analysis of the noncoding genome using whole-genome sequencing data from 117 patients with B-cell lymphoma. Using promoter capture Hi-C data in naive B cells, we define cis-regulatory elements, which represent an enriched subset of the noncoding genome in which to search for driver mutations. Regulatory regions were identified whose mutation significantly alters gene expression, including copy number variation at cis-regulatory elements targeting CD69, IGLL5, and MMP14, and single nucleotide variants in a cis-regulatory element for TPRG1 We also show the commonality of pathways targeted by coding and noncoding mutations, exemplified by MMP14, which regulates Notch signaling, a pathway important in lymphomagenesis and whose expression is associated with patient survival. This study provides an enhanced understanding of lymphomagenesis and describes the advantages of using chromosome conformation capture to decipher noncoding mutations relevant to cancer biology.

Genome-wide association studies of 74 plasma metabolites of German shepherd dogs reveal two metabolites associated with genes encoding their enzymes

INTRODUCTION

German shepherd dogs (GSDs) are a popular breed affected by numerous disorders. Few studies have explored genetic variations that influence canine blood metabolite levels.

OBJECTIVES

To investigate genetic variants affecting the natural metabolite variation in GSDs.

METHODS

A total of 82 healthy GSDs were genotyped on the Illumina CanineHD Beadchip, assaying 173,650 markers. For each dog, 74 metabolites were measured through liquid and gas chromatography mass spectrometry (LC-MS and GC-MS) and were used as phenotypes for genome-wide association analyses (GWAS). Sliding window and homozygosity analyses were conducted to fine-map regions of interest, and to identify haplotypes and gene dosage effects.

RESULTS

Summary statistics for 74 metabolites in this population of GSDs are reported. Forty-one metabolites had significant associations at a false discovery rate of 0.05. Two associations were located around genes which encode for enzymes for the relevant metabolites: 4-hydroxyproline was significantly associated to D-amino acid oxidase (DAO), and threonine to L-threonine 3-dehydrogenase (LOC477365). Three of the top ten haplotypes associated to 4-hydroxyproline included at least one SNP on DAO. These haplotypes occurred only in dogs with the highest 15 measurements of 4-hydroxyproline, ranging in frequency from 16.67 to 20%. None of the dogs were homozygous for these haplotypes. The top two haplotypes associated to threonine included SNPs on LOC477365 and were also overrepresented in dogs with the highest 15 measurements of threonine. These haplotypes occurred at a frequency of 90%, with 80% of these dogs homozygous for the haplotypes. In dogs with the lowest 15 measurements of threonine, the haplotypes occurred at a frequency of 26.67% and 0% homozygosity.

CONCLUSION

DAO and LOC477365 were identified as candidate genes affecting the natural plasma concentration of 4-hydroxyproline and threonine, respectively. Further investigations are needed to validate the effects of the variants on these genes.

Non-receptor tyrosine kinase signaling in autoimmunity and therapeutic implications

Autoimmune diseases are characterized by impaired immune tolerance towards self-antigens, leading to enhanced immunity to self by dysfunctional B cells and/or T cells. The activation of these cells is controlled by non-receptor tyrosine kinases (NRTKs), which are critical mediators of antigen receptor and cytokine receptor signaling pathways. NRTKs transduce, amplify and sustain activating signals that contribute to autoimmunity, and are counter-regulated by protein tyrosine phosphatases (PTPs). The function of and interaction between NRTKs and PTPs during the development of autoimmunity could be key points of therapeutic interference against autoimmune diseases. In this review, we summarize the current state of knowledge of the functions of NRTKs and PTPs involved in B cell receptor (BCR), T cell receptor (TCR), and cytokine receptor signaling pathways that contribute to autoimmunity, and discuss their targeting for therapeutic approaches against autoimmune diseases.

Nuclear cGAS suppresses DNA repair and promotes tumorigenesis

Accurate repair of DNA double-stranded breaks by homologous recombination preserves genome integrity and inhibits tumorigenesis. Cyclic GMP-AMP synthase (cGAS) is a cytosolic DNA sensor that activates innate immunity by initiating the STING-IRF3-type I IFN signalling cascade1,2. Recognition of ruptured micronuclei by cGAS links genome instability to the innate immune response3,4, but the potential involvement of cGAS in DNA repair remains unknown. Here we demonstrate that cGAS inhibits homologous recombination in mouse and human models. DNA damage induces nuclear translocation of cGAS in a manner that is dependent on importin-α, and the phosphorylation of cGAS at tyrosine 215-mediated by B-lymphoid tyrosine kinase-facilitates the cytosolic retention of cGAS. In the nucleus, cGAS is recruited to double-stranded breaks and interacts with PARP1 via poly(ADP-ribose). The cGAS-PARP1 interaction impedes the formation of the PARP1-Timeless complex, and thereby suppresses homologous recombination. We show that knockdown of cGAS suppresses DNA damage and inhibits tumour growth both in vitro and in vivo. We conclude that nuclear cGAS suppresses homologous-recombination-mediated repair and promotes tumour growth, and that cGAS therefore represents a potential target for cancer prevention and therapy.