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Abstract Background Although cholesterol metabolism is a common pathway for the development of antitumor drugs, there are no specific targets and drugs for clinical use. Here, based on our previous study of sterol O-acyltransferase 1 (SOAT1) in hepatocelluar carcinoma, we sought to screen an effective targeted drug for precise treatment of hepatocelluar carcinoma and, from the perspective of cholesterol metabolism, clarify the relationship between cholesterol regulation and tumorigenesis and development. Methods In this study, we developed a virtual screening integrated affinity screening technology for target protein drug screening. A series of in vitro and in vivo experiments were used for drug activity verification. Multi-omics analysis and flow cytometry analysis were used to explore antitumor mechanisms. Comparative analysis of proteome and transcriptome combined with survival follow-up information of patients reveals the clinical therapeutic potential of screened drugs. Results We screened three compounds, nilotinib, ABT-737, and evacetrapib, that exhibited optimal binding with SOAT1. In particular, nilotinib displayed a high affinity for SOAT1 protein and significantly inhibited tumor activity both in vitro and in vivo. Multi-omics analysis and flow cytometry analysis indicated that SOAT1-targeting compounds reprogrammed the cholesterol metabolism in tumors and enhanced CD8+ T cells and neutrophils to suppress tumor growth. Conclusions Taken together, we reported several high-affinity SOAT1 ligands and demonstrated their clinical potential in the precision therapy of liver cancer, and also reveal the potential antitumor mechanism of SOAT1-targeting compounds. Graphical Abstract

The presence of lymph node metastasis (LNM) affects treatment strategy decisions in T1NxM0 colorectal cancer (CRC), but the currently used clinicopathological-based risk stratification cannot predict LNM accurately. In this study, we detected proteins in formalin-fixed paraffin-embedded (FFPE) tumor samples from 143 LNM-negative and 78 LNM-positive patients with T1 CRC and revealed changes in molecular and biological pathways by label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) and established classifiers for predicting LNM in T1 CRC. An effective 55-proteins prediction model was built by machine learning and validated in a training cohort (N=132) and two validation cohorts (VC1, N=42; VC2, N=47), achieved an impressive AUC of 1.00 in the training cohort, 0.96 in VC1 and 0.93 in VC2, respectively. We further built a simplified classifier with nine proteins, and achieved an AUC of 0.824. The simplified classifier was performed excellently in two external validation cohorts. The expression patterns of 13 proteins were confirmed by immunohistochemistry, and the IHC score of five proteins was used to build an IHC predict model with an AUC of 0.825. RHOT2 silence significantly enhanced migration and invasion of colon cancer cells. Our study explored the mechanism of metastasis in T1 CRC and can be used to facilitate the individualized prediction of LNM in patients with T1 CRC, which may provide a guidance for clinical practice in T1 CRC.

PROTAC is a rapidly developing engineering technology for targeted protein degradation using the ubiquitin–proteasome system, which has promising applications for inflammatory diseases, neurodegenerative diseases, and malignant tumors. This paper gives a brief overview of the development and design principles of PROTAC, with a special focus on PROTAC-based explorations in recent years aimed at achieving controlled protein degradation and improving the bioavailability of PROTAC, as well as TPD technologies that use other pathways such as autophagy and lysosomes to achieve targeted protein degradation.

Abstract A comprehensive analysis of the humoral immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential in understanding COVID-19 pathogenesis and developing antibody-based diagnostics and therapy. In this work, we performed a longitudinal analysis of antibody responses to SARS-CoV-2 proteins in 104 serum samples from 49 critical COVID-19 patients using a peptide-based SARS-CoV-2 proteome microarray. Our data show that the binding epitopes of IgM and IgG antibodies differ across SARS-CoV-2 proteins and even within the same protein. Moreover, most IgM and IgG epitopes are located within nonstructural proteins (nsps), which are critical in inactivating the host’s innate immune response and enabling SARS-CoV-2 replication, transcription, and polyprotein processing. IgM antibodies are associated with a good prognosis and target nsp3 and nsp5 proteases, whereas IgG antibodies are associated with high mortality and target structural proteins (Nucleocapsid, Spike, ORF3a). The epitopes targeted by antibodies in patients with a high mortality rate were further validated using an independent serum cohort (n = 56) and using global correlation mapping analysis with the clinical variables that are associated with COVID-19 severity. Our data provide fundamental insight into humoral immunity during SARS-CoV-2 infection. SARS-CoV-2 immunogenic epitopes identified in this work could also help direct antibody-based COVID-19 treatment and triage patients.

Abstract Interestingly, some protein domains are intrinsically disordered (abbreviated as IDD), and the disorder degree of same domains may differ in different contexts. However, the evolutionary causes and biological significance of these phenomena are unclear. Here, we address these issues by genome-wide analyses of the evolutionary and functional features of IDDs in 1,870 species across the three superkingdoms. As the result, there is a significant positive correlation between the proportion of IDDs and organism complexity with some interesting exceptions. These phenomena may be due to the high disorder of clade-specific domains and the different disorder degrees of the domains shared in different clades. The functions of IDDs are clade-specific and the higher proportion of post-translational modification sites may contribute to their complex functions. Compared with metazoans, fungi have more IDDs with a consecutive disorder region but a low disorder ratio, which reflects their different functional requirements. As for disorder variation, it’s greater for domains among different proteins than those within the same proteins. Some clade-specific ‘no-variation’ or ‘high-variation’ domains are involved in clade-specific functions. In sum, intrinsic domain disorder is related to both the organism complexity and clade-specific functions. These results deepen the understanding of the evolution and function of IDDs.

Macrophages are highly heterogeneous immune cells that fulfill tissue-specific functions. Tissue-derived signals play a critical role in determining macrophage heterogeneity. However, these signals remain largely unknown. The BMP receptor activin receptor–like kinase 1 (ALK1) is well known for its role in blood vessel formation; however, its role within the immune system has never been revealed to our knowledge. Here, we found that BMP9/BMP10/ALK1 signaling controlled the identity and self-renewal of Kupffer cells (KCs) through a Smad4-dependent pathway. In contrast, ALK1 was dispensable for the maintenance of macrophages located in the lung, kidney, spleen, and brain. Following ALK1 deletion, KCs were lost over time and were replaced by monocyte-derived macrophages. These hepatic macrophages showed significantly reduced expression of the complement receptor VSIG4 and alterations in immune zonation and morphology, which is important for the tissue-specialized function of KCs. Furthermore, we found that this signaling pathway was important for KC-mediated Listeria monocytogenes capture, as the loss of ALK1 and Smad4 led to a failure of bacterial capture and overwhelming disseminated infections. Thus, ALK1 signaling instructs a tissue-specific phenotype that allows KCs to protect the host from systemic bacterial dissemination.

Background: Molecular subtyping of cancer aimed to predict patient overall survival (OS) and nominate drug targets for patient treatments is central to precision oncology. Owing to the rapid development of phosphoproteomics, we can now measure thousands of phosphoproteins in human cancer tissues. However, limited studies report how to analyse the complex phosphoproteomic data for cancer subtyping and to nominate druggable kinase candidates. Findings: In this work, we reanalysed the phosphoproteomic data of high-grade serous ovarian cancer (HGSOC) from the Clinical Proteomic Tumour Analysis Consortium (CPTAC). Our analysis classified HGSOC into 5 major subtypes that were associated with different OS and appeared to be more accurate than that achieved with protein profiling. We provided a workflow to identify 29 kinases whose increased activities in tumours are associated with poor survival. The altered kinase signalling landscape of HGSOC included the PI3K/AKT/mTOR, cell cycle and MAP kinase signalling pathways. We also developed a “patient-specific” hierarchy of clinically actionable kinases and selected kinase inhibitors by considering kinase activation and kinase inhibitor selectivity. Interpretation: Our study offered a global phosphoproteomics data analysis workflow to aid in cancer molecular subtyping, determining phosphorylation-based cancer hallmarks and facilitating nomination of kinase inhibition in cancer. Keywords: Ovarian cancer, Phosphoproteomics, Druggable kinase

Abstract Plant grafting has been practiced widely in horticulture and proved as a useful tool in science. However, the mechanisms of graft healing or graft incompatibility remain poorly understood. In this study, Litchi chinensis cv. ‘Jingganghongnuo’ homograft (‘J/J’) and ‘Jingganghongnuo’/‘zhuangyuanhong’ heterograft (‘J/Z’) as compatible and incompatible combination, respectively, was used to study transcriptional changes between incompatible and compatible graft during graft union formation. Anatomical observation indicated that three stages (2 h, 14 d and 21 d after grafting) were critical for graft union formation and selected for high-throughput sequencing. Results indicated 6060 DEGs were differentially expressed in the compatible combination and 5267 DEGs exhibiting in the incompatible one. KEGG pathway enrichment analysis revealed that DEGs were involved in metabolism, wound response, phenylpropanoid biosynthesis and plant hormone signal transduction. The expression of 9 DEGs annotated in auxin pathway was up-regulated in compatible combination than that in incompatible combination. The IAA concentration confirmed that the IAA might promote the graft compatibility. In addition, 13 DEGs related to lignin biosynthesis were differentially expressed during graft healing process. Overall, our results provide abundant sequence resources for studying mechanisms underlying graft compatibility and establish a platform for further studies of litchi and other evergreen fruit trees.

Urine as a true non-invasive sampling source holds great potential for biomarker discovery. While approximately 2000 proteins can be detected by mass spectrometry in urine from healthy people, the amount of these proteins vary considerably. A systematic evaluation of a large number of samples is needed to determine the range of the variations. Current biomarker studies often measure limited number of urine samples in the discovery phase, which makes it difficult to determine whether proteins differentially expressed between control and disease groups represent actual difference, or are just physiological variations among the individuals, leads to failures in the validation phase with the increased sample numbers. Here, we report a streamlined workflow with capacity of measuring 8 urine proteomes per day at the coverage of >1500 proteins. With this workflow, we evaluated variations in 497 urine proteomes from 167 healthy donors, establishing reference intervals (RIs) that covered urine protein variations. We demonstrated that RIs could be used to monitor physiological changes by detecting transient outlier proteins. Furthermore, we provided a RIs-based algorithm for biomarker discovery and validation to screen for diseases such as cancer. This study provided a proof-of-principle workflow for the use of urine proteome for health monitoring and disease screening.

Background Osteoporosis is a common, complex disease of bone with a strong heritable component, characterized by low bone mineral density, microarchitectural deterioration of bone tissue and an increased risk of fracture. Due to limited drug selection for osteoporosis and increasing morbidity, mortality of osteoporotic fractures, osteoporosis has become a major health burden in aging societies. Current researches for identifying specific loci or genes involved in osteoporosis contribute to a greater understanding of the pathogenesis of osteoporosis and the development of better diagnosis, prevention and treatment strategies. However, little is known about how most causal genes work and interact to influence osteoporosis. Therefore, it is greatly significant to collect and analyze the studies involved in osteoporosis-related genes. Unfortunately, the information about all these osteoporosis-related genes is scattered in a large amount of extensive literature. Currently, there is no specialized database for easily accessing relevant information about osteoporosis-related genes and miRNAs. Methods We extracted data from literature abstracts in PubMed by text-mining and manual curation. Moreover, a local MySQL database containing all the data was developed with PHP on a Windows server. Results OsteoporosAtlas (http://biokb.ncpsb.org/osteoporosis/), the first specialized database for easily accessing relevant information such as osteoporosis-related genes and miRNAs, was constructed and served for researchers. OsteoporosAtlas enables users to retrieve, browse and download osteoporosis-related genes and miRNAs. Gene ontology and pathway analyses were integrated into OsteoporosAtlas. It currently includes 617 human encoding genes, 131 human non-coding miRNAs, and 128 functional roles. We think that OsteoporosAtlas will be an important bioinformatics resource to facilitate a better understanding of the pathogenesis of osteoporosis and developing better diagnosis, prevention and treatment strategies.

Litchi (Litchi chinesis Sonn.) is the most economically significant member of Sapindaceae family, especially in sub-tropical regions. However, its tall tree body often brings many inconveniences to production management. In order to modify the tree size or growth for productivity optimization and simplifying management, it is urgent to reveal the dwarf mechanism of litchi for dwarfing rootstocks or cultivar breeding. However, to date, the mechanisms on litchi dwarfism is still poor known. In the present study, transcriptome profiling were performed on L. chinensis cv. 'Feizixiao' (FZX, vigorous cultivar) and 'Ziniangxi' (ZNX, dwarf cultivar). A total of 55,810 unigenes were obtained, and 9,190 unigenes were differentially expressed between vigorous and dwarf litchi samples. Gene functional enrichment analysis indicated that the differentially expressed unigenes (DEGs) were related to phytohormone metabolism and signal transduction, and energy metabolism pathways. In particular, GA2ox were only up-regulated in ZNX samples, indicating GA might play an important role in regulating huge difference between vigorous and dwarf litchi cultivars. In addition, the 35S::LcGA2ox transgenic tobacco plants were dwarf and had smaller leaves or branches than wild type plants. Our study provided a series of candidate genes to reveal the mechanism of litchi dwarf.

HJURP (Holliday Junction-Recognizing Protein) plays dual roles in DNA repair and in accurate chromosome segregation during mitosis. We examined whether the single nucleotide polymorphisms (SNPs) of HJURP were associated with the risk of occurrence of hepatocellular carcinoma (HCC) among chronic hepatitis B virus (HBV) carriers from well-known high-risk regions for HCC in China.Twenty-four haplotype-tagging SNPs across HJURP were selected from HapMap data using the Haploview software. We genotyped these 24 SNPs using the using Sequenom's iPLEX assay in the Fusui population, consisting of 348 patients with HCC and 359 cancer-free controls, and further investigated the significantly associated SNP using the TaqMan assay in the Haimen population, consisting of 100 cases and 103 controls. The genetic associations with the risk of HCC were analyzed by logistic regression.We observed an increased occurrence of HCC consistently associated with A/C or C/C genotypes of the non-synonymous SNP rs3771333 compared with the A/A genotype in both the Fusui and Haimen populations, with a pooled odds ratio 1.82 (95% confidence interval, 1.33-2.49; P = 1.9 × 10-4). Case-only analysis further indicated that carriers of the at-risk C allele were younger than those carrying the A/A genotype (P = 0.0016). In addition, the expression levels of HJURP in C allele carriers were lower than that in A/A genotype carriers (P = 0.0078 and 0.0010, for mRNA and protein levels, respectively).Our findings suggest that rs3771333 in HJURP may play a role in mediating the susceptibility to HCC among Chinese.

Phosphatase and tensin homolog (PTEN), v-akt murine thymoma viral oncogene homolog 1 (AKT1), mouse double minute 2 (MDM2) and p53 play important roles in the development of cancer. We examined whether the single nucleotide polymorphisms (SNPs) in the PTEN, AKT1, MDM2 and p53 genes were related to the risk and severity of nasopharyngeal carcinoma (NPC) in the Chinese population. Seven SNPs [p53 rs1042522, PTEN rs11202592, AKT1 SNP1-5 (rs3803300, rs1130214, rs3730358, rs1130233 and rs2494732)] were genotyped in 593 NPC cases and 480 controls by PCR direct sequencing or PCR-RFLP analysis. Multivariate logistic regression analysis was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). None of the polymorphisms alone was associated with the risk or severity of NPC. However, haplotype analyses indicated that a two-SNP core haplotype (SNP4-5, AA) in AKT1 was associated with a significantly increased susceptibility to NPC risk (adjusted OR = 3.87, 95% CI = 1.96-7.65; P

A proteome of the bio-entity, including cell, tissue, organ, and organism, consists of proteins of diverse abundance. The principle that determines the abundance of different proteins in a proteome is of fundamental significance for an understanding of the building blocks of the bio-entity. Here, we report three regular patterns in the proteome-wide distribution of protein abundance across species such as human, mouse, fly, worm, yeast, and bacteria: in most cases, protein abundance is positively correlated with the protein's origination time or sequence conservation during evolution; it is negatively correlated with the protein's domain number and positively correlated with domain coverage in protein structure, and the correlations became stronger during the course of evolution; protein abundance can be further stratified by the function of the protein, whereby proteins that act on material conversion and transportation (mass category) are more abundant than those that act on information modulation (information category). Thus, protein abundance is intrinsically related to the protein's inherent characters of evolution, structure, and function.

STAT3 is a key transcription factor that mediates various cellular and organismal processes, such as cell growth, apoptosis, immune response and cancer. However, the molecular mechanisms of STAT3 regulation remain poorly understood. Here, we identified TRAF6 as a new STAT3 interactor. TRAF6 augmented the ubiquitination of STAT3 and deactivated its transcriptional activity induced by IFNα stimulation or overexpressed with JAK2. Both the RING domain and the TRAF-type zinc finger domain of TRAF6 were indispensable for STAT3 deactivation. Accordingly, TRAF6 also down-regulated the expression of two known STAT3 target genes, CRP and ACT. Therefore, we showed that TRAF6 is a new regulator of JAK/STAT signaling and provide a new mechanistic explanation for the crosstalk between the NF-κB and the JAK-STAT pathways.

BACKGROUND:Baculoviral inhibitor of apoptosis repeat-containing 5 (BIRC5, also called as survivin) is a member of the inhibitor of apoptosis protein (IAP) family, which plays an important role in the occurrence and progression of cancer. Recently, a polymorphism in the promoter of BIRC5, -31C/G (rs9904341), was shown to influence BIRC5 expression. METHODS:We examined whether the -31C/G was related to the risk of developing nasopharyngeal carcinoma (NPC) in a case-control population from Guangxi province in southern China, which consists of 855 patients with NPC and 1036 controls. This polymorphism was genotyped by TaqMan assay. The genetic associations with the occurrence and progression of NPC were estimated by logistic regression. RESULTS:We observed a statistically significant increased occurrence of NPC associated with the CC genotype (odds ratio [OR], 1.40; 95% confidence interval [CI], 1.13-1.73; P=0.0020) compared with the genotypes containing G allele (CG + GG genotype). However, no significant association was observed for the -31C/G with the severity of NPC (as measured by tumor-node-metastasis staging system). CONCLUSION:Our findings suggest that the functional polymorphism -31C/G in the promoter of BIRC5 gene may play a role in mediating the susceptibility to NPC among Chinese.

Genetic background may play an important role in the process of SARS-CoV infection and SARS development. We found several proteins that could interact with the nucleocapsid protein of the SARS coronavirus (SARS-CoV). α-2-Heremans-Schmid Glycoprotein (AHSG), which is required for macrophage deactivation by endogenous cations, is associated with inflammatory regulation. Cytochrome P450 Family 3A (CYP4F3A) is an ω-oxidase that inactivates Leukotriene B4 (LTB4) in human neutrophils and the liver. We investigated the association between the polymorphisms of these two inflammation-associated genes and SARS development. The linkage disequilibrium (LD) maps of these two genes were built with Haploview using data on CHB+JPT (version 2) from the HapMap. A total of ten tag SNPs were selected and genotyped. In the Guangzhou cohort study, after adjusting for age and sex, two AHSG SNPs and one CYP4F3 SNP were found to be associated with SARS susceptibility: rs2248690 (adjusted odds ratio [AOR] 2.42; 95% confidence interval [CI] 1.30-4.51); rs4917 (AOR 1.84; 95% CI 1.02-3.34); and rs3794987 (AOR 2.01; 95% CI 1.10-3.68). To further validate the association, the ten tag SNPs were genotyped in the Beijing cohort. After adjusting for age and sex, only rs2248690 (AOR, 1.63; 95% CI, 1.30-2.04) was found to be associated with SARS susceptibility. The combined analysis of the two studies confirmed tag SNP rs2248690 in AHSG as a susceptibility variant (AOR 1.70; 95% CI 1.37-2.09). The statistical analysis of the rs2248690 genotype data among the patients and healthy controls in the HCW cohort, who were all similarly exposed to the SARS virus, also supported the findings. Further, the SNP rs2248690 affected the transcriptional activity of the AHSG promoter and thus regulated the AHSG serum level. Therefore, our study has demonstrated that the AA genotype of rs2268690, which leads to a higher AHSG serum concentration, was significantly associated with protection against SARS development.

AIM: The diagnosis of hepatocellular carcinoma (HCC) in the early stage is crucial to the application of curative treatments which are the only hope for increasing the life expectancy of patients. Recently, several large-scale studies have shed light on this problem through analysis of gene expression profiles to identify markers correlated with HCC progression. However, those marker sets shared few genes in common and were poorly validated using independent data. Therefore, we developed a systems biology based classifier by combining the differential gene expression with topological features of human protein interaction networks to enhance the ability of HCC diagnosis. METHODS AND RESULTS: In the Oncomine platform, genes differentially expressed in HCC tissues relative to their corresponding normal tissues were filtered by a corrected Q value cut-off and Concept filters. The identified genes that are common to different microarray datasets were chosen as the candidate markers. Then, their networks were analyzed by GeneGO Meta-Core software and the hub genes were chosen. After that, an HCC diagnostic classifier was constructed by Partial Least Squares modeling based on the microarray gene expression data of the hub genes. Validations of diagnostic performance showed that this classifier had high predictive accuracy (85.88∼92.71%) and area under ROC curve (approximating 1.0), and that the network topological features integrated into this classifier contribute greatly to improving the predictive performance. Furthermore, it has been demonstrated that this modeling strategy is not only applicable to HCC, but also to other cancers. CONCLUSION: Our analysis suggests that the systems biology-based classifier that combines the differential gene expression and topological features of human protein interaction network may enhance the diagnostic performance of HCC classifier.

In fetal hematopoietic organs, the switch from hematopoiesis is hypothesized to be a critical time point for organogenesis, but it is not yet evidenced. The transient coexistence of hematopoiesis will be useful to understand the development of fetal liver (FL) around this time and its relationship to hematopoiesis. Here, the temporal and the comparative transcriptomic and proteomic profiles were observed during the critical time points corresponding to the initiation (E11.5), peak (E14.5), recession (E15.5), and disappearance (3 ddp) of mouse FL hematopoiesis. We found that E11.5-E14.5 corresponds to a FL hematopoietic expansion phase with distinct molecular features, including the expression of new transcription factors, many of which are novel KRAB (Kruppel-associated box)-containing zinc finger proteins. This time period is also characterized by extensive depression of some liver functions, especially catabolism/utilization, immune and defense, classical complement cascades, and intrinsic blood coagulation. Instead, the other liver functions increased, such as xenobiotic and sterol metabolism, synthesis of carbohydrate and glycan, the alternate and lectin complement cascades and extrinsic blood coagulation, and etc. Strikingly, all of the liver functions were significantly increased at E14.5-E15.5 and thereafter, and the depression of the key pathways attributes to build the hematopoietic microenvironment. These findings signal hematopoiesis emigration is the key to open the door of liver maturation.