Domestic dog breeds are characterized by an unrivaled diversity of morphologic traits and breed-associated behaviors resulting from human selective pressures. To identify the genetic underpinnings of such traits, we analyze 722 canine whole genome sequences (WGS), documenting over 91 million single nucleotide and small indels, creating a large catalog of genomic variation for a companion animal species. We undertake both selective sweep analyses and genome wide association studies (GWAS) inclusive of over 144 modern breeds, 54 wild canids and a hundred village dogs. Our results identify variants of strong impact associated with 16 phenotypes, including body weight variation which, when combined with existing data, explain greater than 90% of body size variation in dogs. We thus demonstrate that GWAS and selection scans performed with WGS are powerful complementary methods for expanding the utility of companion animal systems for the study of mammalian growth and biology.

/pdf/whole-genome-sequencing-of-canids-reveals-genomic-regions-3g4e2jfbwf.pdf

Whole genome sequencing of canids reveals genomic regions under selection and variants influencing morphology

Abstract Chemotherapy elicits tumor immune evasion with poorly characterized mechanisms. Here, we demonstrate that chemotherapy markedly enhances the expression levels of CD47 in osteosarcoma tissues, which are positively associated with patient mortality. We reveal that macrophages in response to chemotherapy secrete interleukin-18, which in turn upregulates expression of L-amino acid transporter 2 (LAT2) in tumor cells for substantially enhanced uptakes of leucine and glutamine, two potent stimulators of mTORC1. The increased levels of leucine and enhanced glutaminolysis activate mTORC1 and subsequent c-Myc-mediated transcription of CD47. Depletion of LAT2 or treatment of tumor cells with a LAT inhibitor downregulates CD47 with enhanced macrophage infiltration and phagocytosis of tumor cells, and sensitizes osteosarcoma to doxorubicin treatment in mice. These findings unveil a mutual regulation between macrophage and tumor cells that plays a critical role in tumor immune evasion and underscore the potential to intervene with the LAT2-mediated amino acid uptake for improving cancer therapies. 

/pdf/metabolic-control-of-cd47-expression-through-lat2-mediated-1yjr3txs.pdf

Metabolic control of CD47 expression through LAT2-mediated amino acid uptake promotes tumor immune evasion

Osteosarcoma is a common malignant bone tumor with a propensity for drug resistance, recurrence, and metastasis. A growing number of studies have elucidated the dual role of pyroptosis in the development of cancer, which is a gasdermin-regulated novel inflammatory programmed cell death. However, the interaction between pyroptosis and the overall survival (OS) of osteosarcoma patients is poorly understood. This study aimed to construct a prognostic model based on pyroptosis-related genes to provide new insights into the prognosis of osteosarcoma patients. We identified 46 differentially expressed pyroptosis-associated genes between osteosarcoma tissues and normal control tissues. A total of six risk genes affecting the prognosis of osteosarcoma patients were screened to form a pyroptosis-related signature by univariate and LASSO regression analysis and verified using GSE21257 as a validation cohort. Combined with other clinical characteristics, including age, gender, and metastatic status, we found that the pyroptosis-related signature score, which we named “PRS-score,” was an independent prognostic factor for patients with osteosarcoma and that a low PRS-score indicated better OS and a lower risk of metastasis. The result of ssGSEA and ESTIMATE algorithms showed that a lower PRS-score indicated higher immune scores, higher levels of tumor infiltration by immune cells, more active immune function, and lower tumor purity. In summary, we developed and validated a pyroptosis-related signature for predicting the prognosis of osteosarcoma, which may contribute to early diagnosis and immunotherapy of osteosarcoma.

A Novel Pyroptosis-Related Signature for Predicting Prognosis and Indicating Immune Microenvironment Features in Osteosarcoma

Osteosarcoma (OS) is a common bone malignancy in children and adolescents. Although histological subtyping followed by improved OS treatment regimens have helped achieve favorable outcomes, a lack of understanding of the molecular subtypes remains a challenge to characterize its genetic heterogeneity and subsequently to identify diagnostic and prognostic biomarkers for developing effective treatments. In the present study, global analysis of DNA methylation, and mRNA and miRNA gene expression in OS patient samples were correlated with their clinical characteristics. The mucin family of genes, MUC6, MUC12, and MUC4, were found to be highly mutated in the OS patients. Results revealed the enrichment of molecular pathways including Wnt signaling, Calcium signaling, and PI3K-Akt signaling in the OS tumors. Survival analyses showed that the expression levels of several genes such as RAMP1, CRIP1, CORT, CHST13, and DDX60L, miRNAs and lncRNAs were associated with survival of OS patients. Molecular subtyping using Cluster-Of-Clusters Analysis (COCA) for mRNA, lncRNA, and miRNA expression; DNA methylation; and mutation data from the TARGET dataset revealed two distinct molecular subtypes, each with a distinctive gene expression profile. Between the two subtypes, three upregulated genes, POP4, HEY1, CERKL, and seven downregulated genes, CEACAM1, ABLIM1, LTBP2, ISLR, LRRC32, PTPRF, and GPX3, associated with OS metastasis were found to be differentially regulated. Thus, the molecular subtyping results provide a strong basis for classification of OS patients that could be used to develop better prognostic treatment strategies. 

/pdf/molecular-subtyping-and-survival-analysis-of-osteosarcoma-2vmq8nfh.pdf

Molecular Subtyping and Survival Analysis of Osteosarcoma Reveals Prognostic Biomarkers and Key Canonical Pathways

The dynamic changes of RNA N6-methyladenosine (m6A) during cancer progression participate in various cellular processes. However, less is known about a possible direct connection between upstream regulator and m6A modification, and therefore affects oncogenic progression. Here, we have identified that a key enzyme in N4-acetylcytidine (ac4C) acetylation NAT10 is highly expressed in human osteosarcoma tissues, and its knockdown enhanced m6A contents and significantly suppressed osteosarcoma cell growth, migration and invasion. Further results revealed that NAT10 silence inhibits mRNA stability and translation of m6A reader protein YTHDC1, and displayed an increase in glucose uptake, a decrease in lactate production and pyruvate content. YTHDC1 recognizes differential m6A sites on key enzymes of glycolysis phosphofructokinase (PFKM) and lactate dehydrogenase A (LDHA) mRNAs, which suppress glycolysis pathway by increasing mRNA stability of them in an m6A methylation-dependent manner. YTHDC1 partially abrogated the inhibitory effect caused by NAT10 knockdown in tumor models in vivo, lentiviral overexpression of YTHDC1 partially restored the reduced stability of YTHDC1 caused by lentiviral depleting NAT10 at the cellular level. Altogether, we found ac4C driven RNA m6A modification can positively regulate the glycolysis of cancer cells and reveals a previously unrecognized signaling axis of NAT10/ac4C-YTHDC1/m6A-LDHA/PFKM in osteosarcoma. Video Abstract. 

pdf/nat10-mediated-ac4c-acetylation-driven-m6a-modification-via-47m3j6yi1d.pdf

NAT10 mediated ac4C acetylation driven m6A modification via involvement of YTHDC1-LDHA/PFKM regulates glycolysis and promotes osteosarcoma.

Osteosarcoma is a common bone tumor which is affected by E2, the most representative estrogen. Gene regulation function of E2 is highly dependent on estrogen receptor. The purpose of this study was to explore the gene regulation patterns of E2 through estrogen receptor α (ESR1) in osteosarcoma based on the combined analysis of ChIP-seq and gene microarray. All of the datasets were downloaded from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) in E2 treated U2OS cells expressing ESR1 (U2OS-ERα) compared with those treated with vehicle were obtained based on R programming software. ESR1-specific binding sites (peaks) in E2 treated U2OS cells were identified through MACS. Overlaps between DEGs and ESR1 target genes which contained peaks in promoters were considered as reliable E2-mediated genes through ESR1 in osteosarcoma. Moreover, we conducted miRNA-Gene regulation analysis for those genes through miRWalk database to identify potential therapeutic targets for the genes. Functional enrichment analysis of DEGs indicated their potential involvement in cancer, and cell activity-related processes. Fifteen overlaps were identified between DEGs and target genes of ESR1, of which 12 were found to be regulated by miRNA. Several known estrogen response genes and novel genes were obtained in this study and they might provide potential therapeutic targets for osteosarcoma.

/pdf/combined-analysis-of-chip-seq-and-gene-microarray-datasets-3dve4ogsai.pdf

Combined analysis of ChIP-seq and gene microarray datasets identify the E2-mediated genes in ERα-dependent manner in osteosarcoma

Background: Osteosarcoma is a common malignancy of bone with inferior survival outcome. Autophagy can exert multifactorial influence on tumorigenesis and tumor progression. However, the specific function of genes related to autophagy in the prognosis of osteosarcoma patients remains unclear. Herein, we aimed to explore the association of genes related to autophagy with the survival outcome of osteosarcoma patients. Methods: The autophagy-associated genes that were related to the prognosis of osteosarcoma were optimized by LASSO Cox regression analysis. The survival of osteosarcoma patients was forecasted by multivariate Cox regression analysis. The immune infiltration status of 22 immune cell types in osteosarcoma patients with high and low risk scores was compared by using the CIBERSORT tool. Results: The risk score model constructed according to 14 autophagy-related genes (ATG4A, BAK1, BNIP3, CALCOCO2, CCL2, DAPK1, EGFR, FAS, GRID2, ITGA3, MYC, RAB33B, USP10, and WIPI1) could effectively predict the prognosis of patients with osteosarcoma. A nomogram model was established based on risk score and metastasis. Conclusion: Autophagy-related genes were identified as pivotal prognostic signatures, which could guide the clinical decision making in the treatment of osteosarcoma.

/pdf/prognostic-signature-of-osteosarcoma-based-on-14-autophagy-470n88fyc0.pdf

Prognostic Signature of Osteosarcoma Based on 14 Autophagy-Related Genes.

Signature constructed by glycolysis-immune-related genes can predict the prognosis of osteosarcoma patients

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Combined analysis of ChIP-seq and gene microarray datasets identify the E2-mediated genes in ERα-dependent manner in osteosarcoma

Prognostic Signature of Osteosarcoma Based on 14 Autophagy-Related Genes.

Signature constructed by glycolysis-immune-related genes can predict the prognosis of osteosarcoma patients