Zhijian Song

Background: Proteins represent the dynamic downstream products of genes, and have the potential to substantially increase understanding of the complexities of cancer biology. Undifferentiated pleomorphic sarcoma (UPS) is a rare disease, the proteomic landscape of which has not been fully investigated. Methods: We performed isobaric TMT-based proteomic analysis for 80 UPS tumor and 28 corresponding adjacent non-tumor muscle tissues. The underlying molecular subtypes, therapeutic targets, local recurrence, and lung metastasis were uncovered. The integration of previous single-cell RNA sequencing data with proteomics was further employed to characterize the specific cell type linked to lung metastasis. Results: Our analyses revealed a catalog of proteins that were dysregulated in UPS. The UPS cohort was stratified into three molecular subtypes S-I, S-II, and S-III. S-I was characterized by the high expression of spliceosome-related proteins and protumor cytokines, and was associated with the lowest overall rate of survival. S-II was characterized with the highest ImmuneScore. S-III with the highest StromaScore had the best outcomes. Protein-based disease classification was better than the recommended AJCC staging system for UPS. PRMT6 protein was overexpressed, and associated with adverse outcomes. PRMT6 inhibitor significantly inhibited tumor growth in two patient-derived xenograft models. Analysis of local recurrence-associated proteins showed that PAWR was negatively associated with UPS recurrence. Additionally, CD163 was a negative predictive marker for lung metastasis. Combined with scRNA-seq data, CD163 + macrophages represented phagocytosis phenotype with high expression of the signature markers (CD163, MRC1, MERTK, and C1QB). Furthermore, CD163 + macrophages were enriched in the endocytosis, phagocytosis, and lysosome compared with CD163- macrophages. Conclusions: Our study highlights the utility of proteomics for characterizing UPS, providing a framework for understanding the biological basis of its clinical features and paving the way for a new era of proteomics-driven precision medicine in sarcoma research.

Recent advances in next-generation sequencing (NGS) technology have greatly accelerated the need for efficient annotation to accurately interpret clinically relevant genetic variants in human diseases. Therefore, it is crucial to develop appropriate analytical tools to improve the interpretation of disease variants. Given the unique genetic characteristics of mitochondria, including haplogroup, heteroplasmy, and maternal inheritance, we developed a suite of variant analysis toolkits specifically designed for primary mitochondrial diseases: the Mitochondrial Missense Variant Annotation Tool (MmisAT) and the Mitochondrial Missense Variant Pathogenicity Predictor (MmisP). MmisAT can handle protein-coding variants from both nuclear DNA and mtDNA and generate 349 annotation types across six categories. It processes 4.78 million variant data in 76 min, making it a valuable resource for clinical and research applications. Additionally, MmisP provides pathogenicity scores to predict the pathogenicity of genetic variations in mitochondrial disease. It has been validated using cross-validation and external datasets and demonstrated higher overall discriminant accuracy with a receiver operating characteristic (ROC) curve area under the curve (AUC) of 0.94, outperforming existing pathogenicity predictors. In conclusion, the MmisAT is an efficient tool that greatly facilitates the process of variant annotation, expanding the scope of variant annotation information. Furthermore, the development of MmisP provides valuable insights into the creation of disease-specific, phenotype-specific, and even gene-specific predictors of pathogenicity, further advancing our understanding of specific fields.

Background: Acute Respiratory Infections (ARIs) are a major cause of morbidity and mortality worldwide. Human Adenovirus (HAdV), responsible for 5%–10% of children's ARIs, is one of the most prevalent pathogens. Our study aimed to analyze the epidemiology and phylogenesis of HAdV in pediatric patients with ARIs in Hangzhou during the COVID-19 pandemic.Method: Between November 2020 and March 2021, we collected 1,442 nasopharyngeal swabs from children with ARIs at Children's Hospital, Zhejiang University School of Medicine. Epidemiological statistics, phylogenetic and amino acid (AA) mutation analysis were conducted.Results: Our findings revealed that 386 (26.77%) samples tested positive for HAdV, with the highest rate in children aged 6–18 years and the lowest in children aged 0–1 year, indicating a different age preference of HAdV compared with pre-pandemic period. Outpatients had a significantly higher positive rate than inpatients. Moreover, patients with HAdV-coinfection exhibited more severe clinical symptoms than those with HAdV-single infection. Our phylogenetic analysis demonstrated that species HAdV-C (type 1, 2, 6) were the predominant circulating strains in Hangzhou during the COVID-19 pandemic. Further AA mutation analysis identified seventeen mutations of particular concern for biological characterization.Conclusion: In conclusion, our study provides valuable epidemiological and molecular data that will aid in epidemiological surveillance, antiviral therapies and the development of specific vaccine types, leading to improve public health.

Background: Alternative splicing (AS) is important in the regulation of gene expression and aberrant AS is emerging as a major factor in the pathogenesis of human conditions, including cancer. Triple-negative breast cancer (TNBC) is the most challenging subtype of breast cancer with strong invasion, high rate of metastasis, and poor prognosis. Here we report a systematic profiling of aberrant AS in TNBC. Methods: The percent spliced in (PSI) values for AS events in 151 TNBC patients were obtained from The Cancer Genome Atlas (TCGA) SpliceSeq database. Univariate Cox and stepwise Multivariate Cox regression analyses were conducted to find the best prognostic AS model. Splicing regulatory networks were constructed by prognosis-related spliceosome and aberrant AS events. Additionally, pathway enrichment and gene set enrichment analysis (GSEA) were further employed to reveal the significant pathways for prognosis-related AS genes. Finally, splicing regulatory networks were constructed via Spearman’s rank correlation coefficients between prognosis-related AS events and splicing factor expressions. Results: A total of 1,397 prognosis-associated AS events were identified in TNBC. The majority of the parent genes of prognostic AS events exhibited direct interactions to each other in the STRING gene network. Pathways of focal adhesion (p < 0.001), RNA splicing (p = 0.007), homologous recombination (p = 0.042) and ECM-receptor interaction (p = 0.046) were found to be significantly enriched for prognosis-related AS. Additionally, the area under curve (AUC) of the best AS prognostic predictor model reached 0.949, showing a powerful capability to predict outcomes. The Exon Skip (ES) type of AS events displayed more robust and efficient capacity in predicting performance than any other specific AS events type in terms of prognosis. The ES AS signature might confer a strong oncogenic phenotype in the high-risk group with elevated activities in cell cycle and SUMOylating pathways of tumorigenesis, while programmed cell death and metabolism pathways were found to be enriched in the low-risk group of TNBC. The splicing correlation network also revealed a regulatory mode of prognostic splicing factors (SFs) in TNBC. Conclusion: Our analysis of AS events in TNBC could not only contribute to elucidating the tumorigenesis mechanism of AS but also provide clues to uncovering underlying prognostic biomarkers and therapeutic targets for further study.

Gout is a common arthritic disease resulting from elevated serum uric acid (SUA) level. A large meta-analysis including 28,141 individuals identified nine single nucleotide polymorphisms (SNPs) associated with altered SUA level in a Caucasian population. However, raised SUA level alone is not sufficient for the development of gout arthritis and most of these SNPs have not been studied in a Han Chinese population. Here, we performed a case–control association analysis to investigate the relationship between these SUA correlated SNPs and gout arthritis in Han Chinese. A total of 622 ascertained gout p9atients and 917 healthy controls were genotyped. Genome-wide significant SNPs, rs12129861, rs780094, rs734553, rs742132, rs1183201, rs12356193, rs17300741 and rs505802 in the previous SUA study, were selected for our analysis. No deviation from the Hardy–Weinberg equilibrium was observed either in the case or control cohorts (corrected p > 0.05). Three SNPs, rs780094 (located in GCKR, corrected p = 1.78E−4, OR = 0.723), rs1183201 (located in SLC17A1, corrected p = 1.39E−7, OR = 0.572) and rs505802 (located in SLC22A12, corrected p = 0.007, OR = 0.747), were significantly associated with gout on allelic level independent of potential cofounding traits. While the remaining SNPs were not replicated. We also found significant associations of uric acid concentrations with these three SNPs (rs780094 in GCKR, corrected p = 3.94E−5; rs1183201 in SLC17A1, corrected p = 0.005; rs505802 in SLC22A12, corrected p = 0.003) and of triglycerides with rs780094 (located in GCKR, corrected p = 2.96E−4). Unfortunately, SNP-SNP interactions for these three significant SNPs were not detected (rs780094 vs rs1183201, p = 0.402; rs780094 vs rs505802, p = 0.434; rs1183201 vs rs505802, p = 0.143). Three SUA correlated SNPs in Caucasian population, rs780094 in GCKR, rs1183201 in SLC17A1 and rs505802 in SLC22A12 were confirmed to be associated with gout arthritis and uric acid concentrations in Han Chinese males. Considering genetic differences among populations and complicated pathogenesis of gout arthritis, more validating tests in independent populations and relevant functional experiments are suggested in future.

Refractive errors and high myopia are the most common ocular disorders, and both of them are leading causes of blindness in the world. Recently, genetic association studies in European and Japanese population identified that common genetic variations located in 15q14 and 15q25 were associated with high myopia. To validate whether the same variations conferred risk to high myopia in the Han Chinese population, we genotyped 1,461 individuals (940 controls and 521 cases samples) recruited of Han Chinese origin.