Development of a certified reference material for accurate determination of the leaching of Pb and Zn in solid waste.

Certified reference materials (CRMs) with high accuracy and traceability play a significant role in the calibration of equipment and validation of analytical methods. However, there is still a lack of suitable solid waste CRMs for quality assurance and quality control. Thus, a CRM (GBW(E)085538) was developed for accurate determination and reliable measurement of the leaching of Pb and Zn in solid waste according to the requirements of ISO 17034 and the recommendations of ISO Guide 35. This study describes the steps performed for the development of the CRM. These steps include material preparation, homogeneity, and stability during transport and storage, assignment of certified values, and their uncertainties. The material was dried, ground, sieved and well-mixed, and the final bulk material was bottled in 1 kg portions. Analytical techniques like inductively coupled plasma-mass spectrometry (ICP-MS), inductively coupled plasma-optical emission spectrometry (ICP-OES), and flame atomic absorption spectrometry (AAS) have been used for the characterization of property values. Concurrently, an inter-laboratory comparison study involving 9 qualified laboratories was implemented to support the certification study. The certified values of Pb and Zn were (4.66 ± 0.21) mg/L and (2.95 ± 0.14) mg/L with 7-month stability.

Recurrence Prediction by Circulating Tumor DNA in the Patient with Colorectal Liver Metastases After Hepatectomy: A Prospective Biomarker Study.

BACKGROUND: The recurrence rate after hepatic resection of colorectal liver metastases (CRLM) remains high. This study aimed to investigate postoperative circulating tumor DNA (ctDNA) based on ultra-deep next-generation sequencing (NGS) to predict patient recurrence and survival. METHODS: Using the high-throughput NGS method tagged with a dual-indexed unique molecular identifier, named the CRLM-specific 25-gene panel (J25), this study sequenced ctDNA in peripheral blood samples collected from 134 CRLM patients who underwent hepatectomy after postoperative day 6. RESULTS: Of 134 samples, 42 (31.3%) were shown to be ctDNA-positive, and 37 resulted in recurrence. Kaplan-Meier survival analysis showed that disease-free survival (DFS) in the ctDNA-positive subgroup was significantly shorter than in the ctDNA-negative subgroup (hazard ratio [HR], 2.96; 95% confidence interval [CI], 1.91-4.6; p < 0.05). When the 42 ctDNA-positive samples were further divided by the median of the mean allele frequency (AF, 0.1034%), the subgroup with higher AFs showed a significantly shorter DFS than the subgroup with lower AFs (HR, 1.98; 95% CI, 1.02-3.85; p < 0.05). The ctDNA-positive patients who received adjuvant chemotherapy longer than 2 months showed a significantly longer DFS than those who received treatment for 2 months or less (HR, 0.377; 95% CI, 0.189-0.751; p < 0.05). Uni- and multivariable Cox regression indicated two factors independently correlated with prognosis: ctDNA positivity and no preoperative chemotherapy. CONCLUSION: The study demonstrated that ctDNA status 6 days postoperatively could sensitively and accurately predict recurrence for patients with CRLM using the J25 panel.

Evaluation of infarct core and ischemic penumbra by absolute quantitative cerebral dynamic susceptibility contrast perfusion magnetic resonance imaging using self-calibrated echo planar imaging sequencing in patients with acute ischemic stroke.

Background: It has been hypothesized that an absolute quantitative dynamic susceptibility contrast (DSC) cerebral perfusion-weighted imaging (PWI) technique based on self-calibrated echo-planar imaging (EPI) could be a reliable measurement of quantitative cerebral blood flow (qCBF) and quantitative cerebral blood volume (qCBV). This study aimed to investigate the clinical value of this technique in offering a unique insight into ischemic stroke (IS) pathophysiology and improving the sensitivity of IS diagnosis. Methods: A total of 14 patients with IS who underwent routine magnetic resonance imaging (MRI) and Self-CALibrated EPI Perfusion-Weighted Imaging (SCALE-PWI) scanning were prospectively recruited as a consecutive convenience sample. qCBF and qCBV maps were processed immediately online after the scan. Then, 2 radiologists independently drew the region of interest (ROI) of the infarct core, ischemic penumbra, and the contralateral normal tissues on each map for the statistical analyses. The paired-samples t-test, Wilcoxon signed-rank test, independent-samples t-test, and receiver operating characteristic (ROC) curve were performed. A value of P<0.05 was considered statistically significant with 95% confidence intervals (CI). Results: All the values of qCBF and qCBV in the lesions were lower than those in the contralateral normal tissues (all P<0.05). The values of qCBF and qCBV in the infarct core were lower than those in the ischemic penumbra (mean values: 16.42 vs. 21.54 mL/100 g/min, P=0.013; 1.23 vs. 1.47 mL/100 g, P=0.049, respectively). The qCBF threshold of the infarct core was 18.18 mL/100 g/min (sensitivity, 71.40%; specificity, 64.30%) and the qCBF threshold of the ischemic penumbra was 28.09 mL/100 g/min (sensitivity, 78.60%; specificity, 85.70%). Conclusions: Different from the previous semi-quantitative measurement, the SCALE-PWI technique has the potential to provide absolute quantitative hemodynamic information which may be used to detect the infarct core and ischemic penumbra in a relatively short scan time.

Retinoic Acid Supplementation Rescues the Social Deficits in Fmr1 Knockout Mice.

Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder with the underlying etiology yet incompletely understood and no cure treatment. Patients of fragile X syndrome (FXS) also manifest symptoms, e.g. deficits in social behaviors, that are core traits with ASD. Several studies demonstrated that a mutual defect in retinoic acid (RA) signaling was observed in FXS and ASD. However, it is still unknown whether RA replenishment could pose a positive effect on autistic-like behaviors in FXS. Herein, we found that RA signaling was indeed down-regulated when the expression of FMR1 was impaired in SH-SY5Y cells. Furthermore, RA supplementation rescued the atypical social novelty behavior, but failed to alleviate the defects in sociability behavior or hyperactivity, in Fmr1 knock-out (KO) mouse model. The repetitive behavior and motor coordination appeared to be normal. The RNA sequencing results of the prefrontal cortex in Fmr1 KO mice indicated that deregulated expression of Foxp2, Tnfsf10, Lepr and other neuronal genes was restored to normal after RA treatment. Gene ontology terms of metabolic processes, extracellular matrix organization and behavioral pathways were enriched. Our findings provided a potential therapeutic intervention for social novelty defects in FXS.

Epidemiology and Evolution of Emerging Porcine Circovirus-like Viruses in Pigs with Hemorrhagic Dysentery and Diarrhea Symptoms in Central China from 2018 to 2021.

Porcine circovirus-like virus (PCLV) is a type of circular Rep-encoding single-stranded DNA virus and may be associated with the development of diarrheal symptoms in pigs. In this study, we retrospectively analyzed three years of past cases in Anhui, China, and reported a case of hemorrhagic enteritis and death in a pregnant sow possibly caused by PCLV. In addition, we analyzed the evolutionary characteristics of PCLV and found that mutation, recombination and selective pressure all played an important role in the evolution of PCLV. We identified N15D and T17S as well as L56T, T58R, K59Q, M62R, L75I and R190K mutations in two different branches, and we noted recombination events in the Rep of a group of Chinese strains. Analysis of selection pressure revealed that PCLV gained more positive selection, indicating that the virus is in a continuous evolutionary state. The PR2 plot, ENC-plot and neutrality analysis showed a greater role of natural selection than that of mutational pressure in the formation of codon usage patterns. This study is the first to identify PCLV in sows with hemorrhagic dysentery and death, and it provides new epidemiological information on PCLV infection in pigs in China.

Multiomics interrogation into HBV (Hepatitis B virus)-host interaction reveals novel coding potential in human genome, and identifies canonical and non-canonical proteins as host restriction factors against HBV.

Hepatitis B Virus (HBV) constitutes a major threat to global public health. Current understanding of HBV-host interaction is yet limited. Here, ribosome profiling, quantitative mass spectrometry and RNA-sequencing were conducted on a recently established HBV replication system, through which we identified multiomic differentially expressed genes (DEGs) that HBV orchestrated to remodel host proteostasis networks. Our multiomics interrogation revealed that HBV induced significant changes in both transcription and translation of 35 canonical genes including PPP1R15A, PGAM5 and SIRT6, as well as the expression of at least 15 non-canonical open reading frames (ncORFs) including ncPON2 and ncGRWD1, thus revealing an extra coding potential of human genome. Overexpression of these five genes but not the enzymatically deficient SIRT6 mutants suppressed HBV replication while knockdown of SIRT6 had opposite effect. Furthermore, the expression of SIRT6 was down-regulated in patients, cells or animal models of HBV infection. Mechanistic study further indicated that SIRT6 directly binds to mini-chromosome and deacetylates histone H3 lysine 9 (H3K9ac) and histone H3 lysine 56 (H3K56ac), and chemical activation of endogenous SIRT6 with MDL800 suppressed HBV infection in vitro and in vivo. By generating the first multiomics landscape of host-HBV interaction, our work is thus opening a new avenue to facilitate therapeutic development against HBV infection.

The Immune Landscape of Chinese Head and Neck Adenoid Cystic Carcinoma and Clinical Implication.

Novel systemic agents and effective treatment strategies for recurrence adenoid cystic carcinoma (ACC) of the head and neck are still worthy of further exploration. Here, we analyzed the mutations and expression profiles of 75 Chinese ACC patients, characterized the prognostic value of the immune signature for recurrence or distant metastasis, and explored the potential of immunotherapeutic biomarkers in ACC. In general, MYB fusion and somatic mutations accounted for a high proportion, which was 46.7% (35/75). ACCs displayed an overall low mutation burden and lack of programmed cell death ligand-1 (PD-L1) expression. The antigen-presenting machinery (APM) expression score and immune infiltration score (IIS) were the lowest among ACC patients, compared with other cancer types. For 61 primary cases, the locoregional recurrence-free survival (LRRFS) was statistically significantly correlated with the IIS [univariate analysis; hazard ratio (HR) = 0.32; 95% CI, 0.11-0.92; p = 0.035] and T-cell infiltration score (TIS) (univariate analysis; HR = 0.33; 95% CI, 0.12-0.94; p = 0.037]. Patients with lower IIS (log-rank p = 0.0079) or TIS (log-rank p = 0.0079) had shorter LRRFS. Additionally, solid pattern was also a prognostic factor related to locoregional recurrence, whereas postoperative radiotherapy (PORT) exerted its beneficial effects. We further evaluated the pretreatment immune profile of five ACC patients treated with PD-1 inhibitors. Patients who responded to camrelizumab or pembrolizumab observed elevated APM and TIS, compared with patients with progressive disease. Our study highlights the immune infiltration pattern and messenger RNA (mRNA) signatures of Chinese ACC patients, which has the potential value for prognosis and immunotherapy.

Melatonin enhances radiofrequency-induced NK antitumor immunity, causing cancer metabolism reprogramming and inhibition of multiple pulmonary tumor development.

Surgery is the common treatment for early lung cancer with multiple pulmonary nodules, but it is often accompanied by the problem of significant malignancy of other nodules in non-therapeutic areas. In this study, we found that a combined treatment of local radiofrequency ablation (RFA) and melatonin (MLT) greatly improved clinical outcomes for early lung cancer patients with multiple pulmonary nodules by minimizing lung function injury and reducing the probability of malignant transformation or enlargement of nodules in non-ablated areas. Mechanically, as demonstrated in an associated mouse lung tumor model, RFA not only effectively remove treated tumors but also stimulate antitumor immunity, which could inhibit tumor growth in non-ablated areas. MLT enhanced RFA-stimulated NK activity and exerted synergistic antitumor effects with RFA. Transcriptomics and proteomics analyses of residual tumor tissues revealed enhanced oxidative phosphorylation and reduced acidification as well as hypoxia in the tumor microenvironment, which suggests reprogrammed tumor metabolism after combined treatment with RFA and MLT. Analysis of residual tumor further revealed the depressed activity of MAPK, NF-kappa B, Wnt, and Hedgehog pathways and upregulated P53 pathway in tumors, which was in line with the inhibited tumor growth. Combined RFA and MLT treatment also reversed the Warburg effect and decreased tumor malignancy. These findings thus demonstrated that combined treatment of RFA and MLT effectively inhibited the malignancy of non-ablated nodules and provided an innovative non-invasive strategy for treating early lung tumors with multiple pulmonary nodules. Trial registration: www.chictr.org.cn , identifier ChiCTR2100042695, http://www.chictr.org.cn/showproj.aspx?proj=120931 .

Characterization of genomic alterations in Chinese colorectal cancer patients with liver metastases.

BACKGROUND: The exploration of genomic alterations in Chinese colorectal liver metastasis (CRLM) is limited, and corresponding genetic biomarkers for patient's perioperative management are still lacking. This study aims to understand genome diversification and complexity that developed in CRLM. METHODS: A custom-designed IDT capture panel including 620 genes was performed in the Chinese CRLM cohort, which included 396 tumor samples from metastatic liver lesions together with 133 available paired primary tumors. RESULTS: In this Chinese CRLM cohort, the top-ranked recurrent mutated genes were TP53 (324/396, 82%), APC (302/396, 76%), KRAS (166/396, 42%), SMAD4 (54/396, 14%), FLG (52/396, 13%) and FBXW7 (43/396, 11%). A comparison of CRLM samples derived from left- and right-sided primary lesions confirmed that the difference in survival for patients with different primary tumor sites could be driven by variations in the transforming growth factor ß (TGF-ß), phosphatidylinositol 3-kinase (PI3K) and RAS signaling pathways. Certain genes had a higher variant rate in samples with metachronous CRLM than in samples with simultaneous metastasis. Overall, the metastasis and primary tumor samples displayed highly consistent genomic alterations, but there were some differences between individually paired metastases and primary tumors, which were mainly caused by copy number variations. CONCLUSION: We provide a comprehensive depiction of the genomic alterations in Chinese patients with CRLM, providing a fundamental basis for further personalized therapy applications.

Application of magnetic resonance fingerprinting to differentiate grade I transitional and fibrous meningiomas from meningothelial meningiomas.

BACKGROUND: The choice of surgical treatment for meningiomas is affected by the subtype and clinical characteristics. Therefore, an accurate preoperative diagnosis is essential. Current magnetic resonance imaging (MRI) technology is unable to distinguish between meningioma subtypes. In the present study, we compared and evaluated the utility of conventional MRI, magnetic resonance fingerprinting (MRF), and diffusion-weighted imaging (DWI) in differentiating World Health Organization grade I transitional and fibrous meningiomas from meningothelial meningiomas. METHODS: Forty-six patients with pathologically confirmed meningiomas (15 meningothelial, 18 transitional, and 13 fibrous) were enrolled in the present study. All patients underwent conventional MRI, MRF, and DWI scans before surgery using a 3T scanner. The Jonckheere-Terpstra test was used to analyze differences in the signal and enhancement characteristics of the three groups from T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI). To investigate the difference in quantitative T1 and T2 values derived from MRF and apparent diffusion coefficient (ADC) values between the three groups using the Kruskal-Wallis test, regions of interest (ROIs) were manually drawn on the parenchymal portion of the tumors; P<0.017 was considered statistically significant after Bonferroni correction for multiple comparison. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performances of the different parameters. RESULTS: Meningothelial meningiomas had significantly higher T1 and T2 values than transitional and fibrous meningiomas (all P<0.017). ROC analysis results revealed that the combination of T1 and T2 values had the largest area under the curve (AUC). The AUC for the combination of T1 and T2 values was 0.826 between meningothelial and transitional meningiomas, and the AUC for the combination of T1 and T2 values between meningothelial and fibrous meningiomas was 0.903. No significant differences were found in the T1 and T2 values between transitional and fibrous meningiomas. There were also no statistically significant differences in the conventional MRI (including T1WI, T2WI, and contrast-enhanced T1WI) and ADC values between the three meningioma subtypes (all P>0.05). CONCLUSIONS: MRF may provide more quantitative information than either conventional MRI or DWI for differentiating transitional and fibrous meningiomas from meningothelial meningiomas. T1 and T2 values derived from MRF may distinguish transitional and fibrous meningiomas from meningothelial meningiomas, and the combination of T1 and T2 values provides the highest diagnostic efficacy.

MKRN3-mediated ubiquitination of Poly(A)-binding proteins modulates the stability and translation of GNRH1 mRNA in mammalian puberty.

The family of Poly(A)-binding proteins (PABPs) regulates the stability and translation of messenger RNAs (mRNAs). Here we reported that the three members of PABPs, including PABPC1, PABPC3 and PABPC4, were identified as novel substrates for MKRN3, whose deletion or loss-of-function mutations were genetically associated with human central precocious puberty (CPP). MKRN3-mediated ubiquitination was found to attenuate the binding of PABPs to the poly(A) tails of mRNA, which led to shortened poly(A) tail-length of GNRH1 mRNA and compromised the formation of translation initiation complex (TIC). Recently, we have shown that MKRN3 epigenetically regulates the transcription of GNRH1 through conjugating poly-Ub chains onto methyl-DNA bind protein 3 (MBD3). Therefore, MKRN3-mediated ubiquitin signalling could control both transcriptional and post-transcriptional switches of mammalian puberty initiation. While identifying MKRN3 as a novel tissue-specific translational regulator, our work also provided new mechanistic insights into the etiology of MKRN3 dysfunction-associated human CPP.

Translatomic profiling reveals novel self-restricting virus-host interactions during HBV infection.

BACKGROUND & AIMS: HBV remains a global threat to human health. It remains incompletely understood how HBV self-restricts in the host during most adult infections. Thus, we performed multi-omics analyses to systematically interrogate HBV-host interactions and the life cycle of HBV. METHODS: RNA-sequencing and ribosome profiling were conducted with cell-based models for HBV replication and gene expression. The novel translational events or products hereby detected were then characterized, and functionally assessed in both cell and mouse models. Moreover, quasi-species analyses of HBV subpopulations were conducted with patients at immune tolerance or activation phases, using next- or third-generation sequencing. RESULTS: We identified EnhI-SL (Enhancer I-stem loop) as a new cis element in the HBV genome; mutations disrupting EnhI-SL were found to elevate viral polymerase expression. Furthermore, while re-discovering HpZ/P', a previously under-explored isoform of HBV polymerase, we also identified HBxZ, a novel short isoform of HBX. Having confirmed their existence, we functionally characterized them as potent suppressors of HBV gene expression and genome replication. Mechanistically, HpZ/P' was found to repress HBV gene expression partially by interacting with, and sequestering SUPV3L1. Activation of the host immune system seemed to reduce the abundance of HBV mutants deficient in HpZ/P' or with disruptions in EnhI-SL. Finally, SRSF2, a host RNA spliceosome protein that is downregulated by HBV, was found to promote the splicing of viral pre-genomic RNA and HpZ/P' biogenesis. CONCLUSION: This study has identified multiple self-restricting HBV-host interactions. In particular, SRSF2-HpZ/P' appeared to constitute another negative feedback mechanism in the HBV life cycle. Targeting host splicing machinery might thus represent a strategy to intervene in HBV-host interactions. LAY SUMMARY: There remain many unknowns about the natural history of HBV infection in adults. Herein, we identified new HBV-host mechanisms which could be responsible for self-restricting infections. Targeting these mechanisms could be a promising strategy for the treatment of HBV infections.

ProGeo-neo: a customized proteogenomic workflow for neoantigen prediction and selection.

BACKGROUND: Neoantigens can be differentially recognized by T cell receptor (TCR) as these sequences are derived from mutant proteins and are unique to the tumor. The discovery of neoantigens is the first key step for tumor-specific antigen (TSA) based immunotherapy. Based on high-throughput tumor genomic analysis, each missense mutation can potentially give rise to multiple neopeptides, resulting in a vast total number, but only a small percentage of these peptides may achieve immune-dominant status with a given major histocompatibility complex (MHC) class I allele. Specific identification of immunogenic candidate neoantigens is consequently a major challenge. Currently almost all neoantigen prediction tools are based on genomics data. RESULTS: Here we report the construction of proteogenomics prediction of neoantigen (ProGeo-neo) pipeline, which incorporates the following modules: mining tumor specific antigens from next-generation sequencing genomic and mRNA expression data, predicting the binding mutant peptides to class I MHC molecules by latest netMHCpan (v.4.0), verifying MHC-peptides by MaxQuant with mass spectrometry proteomics data searched against customized protein database, and checking potential immunogenicity of T-cell-recognization by additional screening methods. ProGeo-neo pipeline achieves proteogenomics strategy and the neopeptides identified were of much higher quality as compared to those identified using genomic data only. CONCLUSIONS: The pipeline was constructed based on the genomics and proteomics data of Jurkat leukemia cell line but is generally applicable to other solid cancer research. With massively parallel sequencing and proteomics profiling increasing, this proteogenomics workflow should be useful for neoantigen oriented research and immunotherapy.

A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers.

Lung adenocarcinoma (LUAD) is caused by multiple biological factors. Therefore, it will be more meaningful to study the prognosis from the perspective of omics integration. Given the significance of epigenetic modification and immunity in tumorigenesis and development, we tried to combine aberrant methylation and tumor infiltration CD8 T cell-related genes to build a prognostic model, to explore the key biomarkers of early-stage LUAD. On the basis of RNA-seq and methylation microarray data downloaded from The Cancer Genome Atlas (TCGA), differentially expressed genes and aberrant methylated genes were calculated with "DEseq2" and "ChAMP" packages, respectively. A Chi-square test was performed to obtain methylation driver genes. Weighted correlation network analysis (WGCNA) was utilized to mine cancer biomarkers related to CD8 T cells. With the consequences of univariate Cox proportional hazards analysis and least absolute shrinkage and selection operator (LASSO) COX regression analysis, the prognostic index based on 17 methylation driver genes (ZNF677, FAM83A, TRIM58, CLDN6, NKD1, NFE2L3, FKBP5, ITGA5, ASCL2, SLC24A4, WNT3A, TMEM171, PTPRH, ITPKB, ITGA2, SLC6A17, and CCDC81) and four CD8 T cell-related genes (SPDL1, E2F7, TK1, and TYMS) was successfully established, which could make valuable predictions for the survival risk of patients with early-stage LUAD.

Evaluating the HER-2 status of breast cancer using mammography radiomics features.

PURPOSE: The aim of our study was to evaluate the HER-2 status in breast cancer patients using mammography (MG) radiomics features. METHODS: A total of 306 Chinese female patients with invasive ductal carcinoma of no special type (IDC-NST) enrolled from January 2013 to July 2018 were divided into a training set (n = 244) and a testing set (n = 62). One hundred and eighty-six radiomics features were extracted from digital MG images based on the training set. The least absolute shrinkage and selection operator (LASSO) method was used to select the optimal predictive features for HER-2 status from the training set. Both support vector machine (SVM) and logistic regression models were employed based on the selected features. The area under the receiver operating characteristic (ROC) curves (AUCs) of the training set and testing set were used to evaluate the predictive performance of the models. RESULTS: Compared with the SVM model, the performance of the logistic regression model using a combination of cranial caudal (CC) and mediolateral oblique (MLO) MG views was optimal. In the training set, the sensitivity, specificity, accuracy and area under the curve (AUC) values of the logistic regression model for evaluating HER-2 status based on quantitative radiomics features were 87.29%, 58.73%, 80.00% and 0.846 (95% confidence interval (CI), 0.800-0.887), respectively, and in the testing set, the values were 73.91%, 68.75%, 77.00% and 0.787 (95% CI, 0.673-0.885), respectively. CONCLUSIONS: Radiomics features could be an efficient tool for the preoperative evaluation of HER-2 status in patients with breast cancer.

Proteomics identifies new therapeutic targets of early-stage hepatocellular carcinoma.

Hepatocellular carcinoma is the third leading cause of deaths from cancer worldwide. Infection with the hepatitis B virus is one of the leading risk factors for developing hepatocellular carcinoma, particularly in East Asia1. Although surgical treatment may be effective in the early stages, the five-year overall rate of survival after developing this cancer is only 50-70%2. Here, using proteomic and phospho-proteomic profiling, we characterize 110 paired tumour and non-tumour tissues of clinical early-stage hepatocellular carcinoma related to hepatitis B virus infection. Our quantitative proteomic data highlight heterogeneity in early-stage hepatocellular carcinoma: we used this to stratify the cohort into the subtypes S-I, S-II and S-III, each of which has a different clinical outcome. S-III, which is characterized by disrupted cholesterol homeostasis, is associated with the lowest overall rate of survival and the greatest risk of a poor prognosis after first-line surgery. The knockdown of sterol O-acyltransferase 1 (SOAT1)-high expression of which is a signature specific to the S-III subtype-alters the distribution of cellular cholesterol, and effectively suppresses the proliferation and migration of hepatocellular carcinoma. Finally, on the basis of a patient-derived tumour xenograft mouse model of hepatocellular carcinoma, we found that treatment with avasimibe, an inhibitor of SOAT1, markedly reduced the size of tumours that had high levels of SOAT1 expression. The proteomic stratification of early-stage hepatocellular carcinoma presented in this study provides insight into the tumour biology of this cancer, and suggests opportunities for personalized therapies that target it.

Comparative transcriptomic analysis reveals genes regulating the germination of morphophysiologically dormant Paris polyphylla seeds during a warm stratification.

We previously analyzed the expression of genes associated with Paris polyphylla var. yunnanensis seed maturation and dormancy release; however, we were unable to clarify the relationship between gene expression levels and these processes. To reveal the molecular mechanisms underlying P. polyphylla var. yunnanensis seed dormancy release during a warm stratification, the transcriptomes of dormant and germinating P. polyphylla var. yunnanensis seeds were separately analyzed by RNA sequencing and were also compared with the transcriptomes of stem-leaf and root tissues harvested during the seed maturation stage. The RNA sequencing of five tissues generated 234,331 unigenes, of which 10,137 (4.33%) were differentially expressed among the analyzed tissues. The 6,619 unigenes whose expression varied among mature dormant, sprouted, and germinated seeds included 95 metabolic and 62 signaling genes related to abscisic acid, gibberellin, auxin, brassinosteroid, cytokinin, ethylene, jasmonic acid and salicylic acid. Additionally, 243 differentially expressed genes were annotated as known seed dormancy/germination-related genes. Among these genes, 109 were regulated by hormones or involved in hormone signal transduction. Finally, 310 transcription factor unigenes, including 71 homologs of known seed dormancy/ germination-related genes, were observed to be differentially expressed during a warm stratification. These results confirm that multiple hormones and transcription factors influence P. polyphylla var. yunnanensis seed dormancy release and germination during a warm stratification. This study identified candidate genes (e.g., ABI5) that should be cloned and functionally characterized regarding their effects on the release of P. polyphylla var. yunnanensis seed morphophysiological dormancy.

PhoPepMass: A database and search tool assisting human phosphorylation peptide identification from mass spectrometry data.

Protein phosphorylation, one of the most important protein post-translational modifications, is involved in various biological processes, and the identification of phosphorylation peptides (phosphopeptides) and their corresponding phosphorylation sites (phosphosites) will facilitate the understanding of the molecular mechanism and function of phosphorylation. Mass spectrometry (MS) provides a high-throughput technology that enables the identification of large numbers of phosphosites. PhoPepMass is designed to assist human phosphopeptide identification from MS data based on a specific database of phophopeptide masses and a multivariate hypergeometric matching algorithm. It contains 244,915 phosphosites from several public sources. Moreover, the accurate masses of peptides and fragments with phosphosites were calculated. It is the first database that provides a systematic resource for the query of phosphosites on peptides and their corresponding masses. This allows researchers to search certain proteins of which phosphosites have been reported, to browse detailed phosphopeptide and fragment information, to match masses from MS analyses with defined threshold to the corresponding phosphopeptide, and to compare proprietary phosphopeptide discovery results with results from previous studies. Additionally, a database search software is created and a "two-stage search strategy" is suggested to identify phosphopeptides from tandem mass spectra of proteomics data. We expect PhoPepMass to be a useful tool and a source of reference for proteomics researchers. PhoPepMass is available at https://www.scbit.org/phopepmass/index.html.

The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for further refinement towards addressing a large clinical need.