PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.

In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapid identification of causative genes. Since the interpretations of ES data require comprehensive clinical analyses, taking clinical expertise into consideration can speed the molecular diagnoses of Mendelian disorders. To leverage clinical expertise to prioritize candidate genes, we developed PhenoApt, a phenotype-driven gene prioritization tool that allows users to assign a customized weight to each phenotype, via a machine-learning algorithm. Using the ability to rank causative genes in top-10 lists as an evaluation metric, baseline analysis demonstrated that PhenoApt outperformed previous phenotype-driven gene prioritization tools by a relative increase of 22.7%-140.0% in three independent, real-world, multi-center cohorts (cohort 1, n = 185; cohort 2, n = 784; and cohort 3, n = 208). Additional trials showed that, by adding weights to clinical indications, which should be explained by the causative gene, PhenoApt performance was improved by a relative increase of 37.3% in cohort 2 (n = 471) and 21.4% in cohort 3 (n = 208). Moreover, PhenoApt could assign an intrinsic weight to each phenotype based on the likelihood of its being a Mendelian trait using term frequency-inverse document frequency techniques. When clinical indications were assigned with intrinsic weights, PhenoApt performance was improved by a relative increase of 23.7% in cohort 2 and 15.5% in cohort 3. For the integration of PhenoApt into clinical practice, we developed a user-friendly website and a command-line tool.

Rare variant association analyses reveal the significant contribution of carbohydrate metabolic disturbance in severe adolescent idiopathic scoliosis.

BACKGROUND: Adolescent idiopathic scoliosis (AIS), the predominant genetic-influenced scoliosis, results in spinal deformities without vertebral malformations. However, the molecular aetiology of AIS remains unclear. METHODS: Using genome/exome sequencing, we studied 368 patients with severe AIS (Cobb angle >40°) and 3794 controls from a Han Chinese cohort. We performed gene-based and pathway-based weighted rare variant association tests to assess the mutational burden of genes and established biological pathways. Differential expression analysis of muscle tissues from 14 patients with AIS and 15 controls was served for validation. RESULTS: SLC16A8, a lactate transporter linked to retinal glucose metabolism, was identified as a novel severe AIS-associated gene (p=3.08E-06, false discovery rate=0.009). Most AIS cases with deleterious SLC16A8 variants demonstrated early onset high myopia preceding scoliosis. Pathway-based burden test also revealed a significant enrichment in multiple carbohydrate metabolism pathways, especially galactose metabolism. Patients with deleterious variants in these genes demonstrated a significantly larger spinal curve. Genes related to catabolic processes and nutrient response showed divergent expression between AIS cases and controls, reinforcing our genomic findings. CONCLUSION: This study uncovers the pivotal role of genetic variants in carbohydrate metabolism in the development of AIS, unveiling new insights into its aetiology and potential treatment.

Dissection of mendelian predisposition and complex genetic architecture of craniovertebral junction malformation.

The craniovertebral junction (CVJ) is an anatomically complex region of the axial skeleton that provides protection of the brainstem and the upper cervical spinal cord. Structural malformation of the CVJ gives rise to life-threatening neurological deficits, such as quadriplegia and dyspnea. Unfortunately, genetic studies on human subjects with CVJ malformation are limited and the pathogenesis remains largely elusive. In this study, we recruited 93 individuals with CVJ malformation and performed exome sequencing. Manual interpretation of the data identified three pathogenic variants in genes associated with Mendelian diseases, including CSNK2A1, MSX2, and DDX3X. In addition, the contribution of copy number variations (CNVs) to CVJ malformation was investigated and three pathogenic CNVs were identified in three affected individuals. To further dissect the complex mutational architecture of CVJ malformation, we performed a gene-based rare variant association analysis utilizing 4371 in-house exomes as control. Rare variants in LGI4 (carrier rate = 3.26%, p = 3.3 × 10-5) and BEST1 (carrier rate = 5.43%, p = 5.77 × 10-6) were identified to be associated with CVJ malformation. Furthermore, gene set analyses revealed that extracellular matrix- and RHO GTPase-associated biological pathways were found to be involved in the etiology of CVJ malformation. Overall, we comprehensively dissected the genetic underpinnings of CVJ malformation and identified several novel disease-associated genes and biological pathways.

Mechanistically derived patient-level framework for precision medicine identifies a personalized immune prognostic signature in high-grade serous ovarian cancer.

An accurate prognosis assessment for cancer patients could aid in guiding clinical decision-making. Reliance on traditional clinical features alone in a complex clinical environment is challenging and unsatisfactory in the era of precision medicine; thus, reliable prognostic biomarkers are urgently required to improve a patient staging system. In this study, we proposed a patient-level computational framework from mechanistic and translational perspectives to establish a personalized prognostic signature (named PLPPS) in high-grade serous ovarian carcinoma (HGSOC). The PLPPS composed of 68 immune genes achieved accurate prognostic risk stratification for 1190 patients in the meta-training cohort and was rigorously validated in multiple cross-platform independent cohorts comprising 792 HGSOC patients. Furthermore, the PLPPS was shown to be the better prognostic factor compared with clinical parameters in the univariate analysis and retained a significant independent association with prognosis after adjusting for clinical parameters in the multivariate analysis. In benchmark comparisons, the performance of PLPPS (hazard ratio (HR), 1.371; concordance index (C-index), 0.604 and area under the curve (AUC), 0.637) is comparable to or better than other published gene signatures (HR, 0.972 to 1.340; C-index, 0.495 to 0.592 and AUC, 0.48-0.624). With further validation in prospective clinical trials, we hope that the PLPPS might become a promising genomic tool to guide personalized management and decision-making of HGSOC in clinical practice.

An integrated strategy for the geographical origin traceability of Goji berries by antioxidants characteristic fingerprint based online ultra-performance liquid chromatography-2,2-diphenyl-1-picrylhydrazyl- photodiode array detector-mass spectrometry combined with multivariate statistics analysis.

Goji berries are now becoming increasingly popular in the human diet due to their potential health benefits. Unscrupulous traders deliberately mislabel with certain origins to gain illegal profits, which seriously affected the consumers' benefits. In this study, an online ultra-performance liquid chromatography-2,2-diphenyl-1 -picrylhydrazyl-photodiode array detector-electrospray ionization-quadrupole time of flight mass was developed for rapid screening and identification of the antioxidants from Goji berry; then, the antioxidants characteristic fingerprint was established and explored in the origins discrimination of Goji berries from China combined with multivariate statistics analysis. As a result, twenty-eight compounds were screened from Goji berry extract, 19 of which were identified by accurate molecular and ultraviolet information according to references. Principal components analysis and partial least squares discrimination analysis achieved the accurate classification from the four regions, eight compounds were selected as origin-related antioxidant markers with variable importance in projection >1 and one-way analysis of variance (P<0.05), including rutin, rutin di-hexose, P-coumaric acid tri-hexose, dicaffeoylquinic acid isomer, Quercetin-rhamno-di-hexoside, peak14, peak16, and peak27. This study provides a feasible strategy for the geographical origins discrimination of Goji berries based on antioxidant ingredients difference and will be helpful for improving the quality control level of Goji berries.

Comparison of Lycium barbarum fruits polysaccharide from different regions of China by acidic hydrolysate fingerprinting-based HILIC-ELSD-ESI-TOF-MS combined with chemometrics analysis.

INTRODUCTION: Lycium barbarum is an edible fruit widely used in herbal medicines and as a functional food. Polysaccharide is one of the most important active ingredients. Only L. barbarum grown in the Ningxia region of China are officially recognised as suitable for use in traditional Chinese medicine, but the systematic comparison of L. barbarum polysaccharide between Ningxia and the other growing regions of China has been rarely reported. OBJECTIVE: To compare the difference of L. barbarum polysaccharide from different grown regions of China. METHODS: A chemical fingerprint of L. barbarum polysaccharide hydrolysates was established based on controlled acidolysis combined with hydrophilic interaction liquid chromatography-evaporative light scattering detection-electrospray ionisation-time-of-flight-mass spectrometry (HILIC-ELSD-ESI-TOF-MS). Then, it was employed for the comparison of L. barbarum samples from different geographical origins of China combined with chemometrics analysis. RESULTS: Six monosaccharides [rhamnose (Rha), xylose (Xyl), arabinose (Ara), mannose (Man), glucose (Glu), galactose (Gal)] were qualitatively and quantitatively determined and four glycoconjugates were preliminarily identified from the hydrolysates. Content determination for the polysaccharide and monosaccharide indicated obvious geographical features. The HILIC-ELSD fingerprint combined with partial least squares-discriminant analysis (PLS-DA) was able to differentiate L. barbarum samples from Ningxia, Xinjiang, Gansu and Qinghai regions with 89.19% classification accuracy. Orthogonal projection to latent structure discriminant analysis (OPLS-DA) was able to differentiate between samples from Ningxia and those from the other three growing regions, polysaccharide and Ara were the potential chemical markers. CONCLUSIONS: These findings form the basis of a reliable method to trace the region of origin of L. barbarum sample and thereby, improve the quality control of L. barbarum therapeutic polysaccharides.

Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer.

Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.

A genotype-first analysis in a cohort of Mullerian anomaly.

Müllerian anomaly (M.A.) is a group of congenital anatomic abnormalities caused by aberrations of the development process of the Müllerian duct. M.A. can either be isolated or be involved in Mendelian syndromes, such as Dandy-Walker syndrome, Holt-Oram syndrome and Bardet-Biedl syndrome, which are often associated with both uterus and kidney malformations. In this study, we applied a genotype-first approach to analyze the whole-exome sequencing data of 492 patients with M.A. Six potential pathogenic variants were found in five genes previously related to female urogenital deformities (PKD1, SON, SALL1, BMPR1B, ITGA8), which are partially overlapping with our patients' phenotypes. We further identified eight incidental findings in seven genes related to Mendelian syndromes without known association with reproductive anomalies (TEK, COL11A1, ANKRD11, LEMD3, DLG5, SPTB, BMP2), which represent potential phenotype expansions of these genes.

Diagnostic yield and clinical impact of exome sequencing in early-onset scoliosis (EOS).

BACKGROUND: Early-onset scoliosis (EOS), defined by an onset age of scoliosis less than 10 years, conveys significant health risk to affected children. Identification of the molecular aetiology underlying patients with EOS could provide valuable information for both clinical management and prenatal screening. METHODS: In this study, we consecutively recruited a cohort of 447 Chinese patients with operative EOS. We performed exome sequencing (ES) screening on these individuals and their available family members (totaling 670 subjects). Another cohort of 13 patients with idiopathic early-onset scoliosis (IEOS) from the USA who underwent ES was also recruited. RESULTS: After ES data processing and variant interpretation, we detected molecular diagnostic variants in 92 out of 447 (20.6%) Chinese patients with EOS, including 8 patients with molecular confirmation of their clinical diagnosis and 84 patients with molecular diagnoses of previously unrecognised diseases underlying scoliosis. One out of 13 patients with IEOS from the US cohort was molecularly diagnosed. The age at presentation, the number of organ systems involved and the Cobb angle were the three top features predictive of a molecular diagnosis. CONCLUSION: ES enabled the molecular diagnosis/classification of patients with EOS. Specific clinical features/feature pairs are able to indicate the likelihood of gaining a molecular diagnosis through ES.

CFEA: a cell-free epigenome atlas in human diseases.

Epigenetic alterations, including 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) and nucleosome positioning (NP), in cell-free DNA (cfDNA) have been widely observed in human diseases, and many available cfDNA-based epigenome-wide profiles exhibit high sensitivity and specificity in disease detection and classification. However, due to the lack of efficient collection, standardized quality control, and analysis procedures, efficiently integrating and reusing these data remain considerable challenges. Here, we introduce CFEA (http://www.bio-data.cn/CFEA), a cell-free epigenome database dedicated to three types of widely adopted epigenetic modifications (5mC, 5hmC and NP) involved in 27 human diseases. We developed bioinformatic pipelines for quality control and standard data processing and an easy-to-use web interface to facilitate the query, visualization and download of these cell-free epigenome data. We also manually curated related biological and clinical information for each profile, allowing users to better browse and compare cfDNA epigenomes at a specific stage (such as early- or metastasis-stage) of cancer development. CFEA provides a comprehensive and timely resource to the scientific community and supports the development of liquid biopsy-based biomarkers for various human diseases.

Rapid authentication of Chaenomeles species by visual volatile components fingerprints based on headspace gas chromatography-ion mobility spectrometry combined with chemometric analysis.

INTRODUCTION: Chaenomeles, including Chaenomeles speciosa (ZP), Chaenomeles sinensis (GP), Chaenomeles tibetica (XZ), and Chaenomeles japonica (RB), has been widely used as food in China for thousands of years. However, only ZP, was recorded to be the authentic medicinal Chaenomeles. Therefore, the rapid and accurate method for the authenticity identification of Chaenomeles species is urgently needed. OBJECTIVE: To develop a method for rapid differentiation of Chaenomeles species. METHODS: The visual volatile components fingerprints based on headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with chemometric analysis, including principal component analysis (PCA), linear discriminant analysis (LDA) and partial least-squares discriminant analysis (PLS-DA), were utilised for the authentication of Chaenomeles species. RESULTS: The visual volatile components fingerprints by the GC-IMS intuitively showed the distribution features of the volatile components for different Chaenomeles samples. The LDA and PLS-DA models successfully discriminated Chaenomeles species with original discrimination accuracy of 100%. Fifteen volatile compounds (VOCs) (peaks 9, 12, 13, 19, 23, 24, 35, 48, 57, 65, 67, 76, 79, 80, 83) were selected as the potential species-specific markers of Chaenomeles via variable importance of projection (VIP > 1.2) and one-way analysis of variance (P < 0.05). CONCLUSIONS: This study showed that the visual volatile components fingerprints by HS-GC-IMS combined with chemometric analysis is a meaningful method in the Chaenomeles species authentication.

Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer.

Early detection is crucial to improve breast cancer (BC) patients' outcomes and survival. Mammogram and ultrasound adopting the Breast Imaging Reporting and Data System (BI-RADS) categorization are widely used for BC early detection, while suffering high false-positive rate leading to unnecessary biopsy, especially in BI-RADS category-4 patients. Plasma cell-free DNA (cfDNA) carrying on DNA methylation information has emerged as a non-invasive approach for cancer detection. Here we present a prospective multi-center study with whole-genome bisulfite sequencing data to address the clinical utility of cfDNA methylation markers from 203 female patients with breast lesions suspected for malignancy. The cfDNA is enriched with hypo-methylated genomic regions. A practical computational framework was devised to excavate optimal cfDNA-rich DNA methylation markers, which significantly improved the early diagnosis of BI-RADS category-4 patients (AUC from 0.78-0.79 to 0.93-0.94). As a proof-of-concept study, we performed the first blood-based whole-genome DNA methylation study for detecting early-stage breast cancer from benign tumors at single-base resolution, which suggests that combining the liquid biopsy with the traditional diagnostic imaging can improve the current clinical practice, by reducing the false-positive rate and avoiding unnecessary harms.

Analysis of long noncoding RNAs highlights region-specific altered expression patterns and diagnostic roles in Alzheimer's disease.

Increasing evidence has revealed the multiple roles of long noncoding RNAs (lncRNAs) in neurodevelopment, brain function and aging, and their dysregulation was implicated in many types of neurological diseases. However, expression pattern and diagnostic role of lncRNAs in Alzheimer's disease (AD) remain largely unknown and has gained significant attention. In this study, we performed a comparative analysis for lncRNA expression profiles in four brain regions in brain aging and AD. Our analysis revealed age- and disease-dependent region-specific lncRNA expression patterns in aging and AD. Moreover, we identified a panel of nine lncRNAs (termed LncSigAD9) in a discovery cohort of 114 samples using supervised machine learning and stepwise selection method. The LncSigAD9 was able to differentiate between AD and healthy controls with high diagnostic sensitivity and specificity both in the discovery cohort (86.3 and 89.5%) and the additional independent AD cohort (90.8 and 83.8%). The receiver operating characteristic curves for the LncSigAD9 were 0.863 and 0.939 for discovery and independent cohorts, respectively. Furthermore, the LncSigAD9 demonstrated higher diagnostic performance than nine-minus-one lncRNA signature and mRNA-based signature with a similar number of genes. In silico functional analysis indicated the involvement of lncRNA expression variation in brain development- and metabolism-related biological processes. Taken together, our study highlights the importance of lncRNAs in brain aging and AD, and demonstrated the utility of lncRNAs as a promising biomarker for early AD diagnosis and treatment.

MetSigDis: a manually curated resource for the metabolic signatures of diseases.

Complex diseases cannot be understood only on the basis of single gene, single mRNA transcript or single protein but the effect of their collaborations. The combination consequence in molecular level can be captured by the alterations of metabolites. With the rapidly developing of biomedical instruments and analytical platforms, a large number of metabolite signatures of complex diseases were identified and documented in the literature. Biologists' hardship in the face of this large amount of papers recorded metabolic signatures of experiments' results calls for an automated data repository. Therefore, we developed MetSigDis aiming to provide a comprehensive resource of metabolite alterations in various diseases. MetSigDis is freely available at http://www.bio-annotation.cn/MetSigDis/. By reviewing hundreds of publications, we collected 6849 curated relationships between 2420 metabolites and 129 diseases across eight species involving Homo sapiens and model organisms. All of these relationships were used in constructing a metabolite disease network (MDN). This network displayed scale-free characteristics according to the degree distribution (power-law distribution with R2 = 0.909), and the subnetwork of MDN for interesting diseases and their related metabolites can be visualized in the Web. The common alterations of metabolites reflect the metabolic similarity of diseases, which is measured using Jaccard index. We observed that metabolite-based similar diseases are inclined to share semantic associations of Disease Ontology. A human disease network was then built, where a node represents a disease, and an edge indicates similarity of pair-wise diseases. The network validated the observation that linked diseases based on metabolites should have more overlapped genes.

Mutational landscape and genetic signatures of cell-free DNA in tumour-induced osteomalacia.

Tumour-induced osteomalacia (TIO) is a very rare paraneoplastic syndrome with bone pain, fractures and muscle weakness, which is mostly caused by phosphaturic mesenchymal tumours (PMTs). Cell-free DNA (cfDNA) has been regarded as a non-invasive liquid biopsy for many malignant tumours. However, it has not been studied in benign tumours, which prompted us to adopt the targeted next-generation sequencing approach to compare cfDNAs of 4 TIO patients, four patients with bone metastasis (BM) and 10 healthy controls. The mutational landscapes of cfDNA in TIO and BM groups were similar in the spectrum of allele frequencies and mutation types. Markedly, deleterious missense mutations in FGFR1 and loss-of-function mutations in MED12 were found in 3/4 TIO patients but none of BM patients. The gene ontology analysis strongly supported that these mutated genes found in TIOs would play a potential role in PMTs' process. The genetic signatures and corresponding change in expression of FGFR1 and FGF23 were further validated in PMT tissues from a test cohort of another three TIO patients. In summary, we reported the first study of the mutational landscape and genetic signatures of cfDNA in TIO/PMTs.

Identification of novel FBN1 variations implicated in congenital scoliosis.

Congenital scoliosis (CS) is a form of scoliosis caused by congenital vertebral malformations. Genetic predisposition has been demonstrated in CS. We previously reported that TBX6 loss-of-function causes CS in a compound heterozygous model; however, this model can explain only 10% of CS. Many monogenic and polygenic CS genes remain to be elucidated. In this study, we analyzed exome sequencing (ES) data of 615 Chinese CS from the Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) project. Cosegregation studies for 103 familial CS identified a novel heterozygous nonsense variant, c.2649G>A (p.Trp883Ter) in FBN1. The association between FBN1 and CS was then analyzed by extracting FBN1 variants from ES data of 574 sporadic CS and 828 controls; 30 novel variants were identified and prioritized for further analyses. A mutational burden test showed that the deleterious FBN1 variants were significantly enriched in CS subjects (OR = 3.9, P = 0.03 by Fisher's exact test). One missense variant, c.2613A>C (p.Leu871Phe) was recurrent in two unrelated CS subjects, and in vitro functional experiments for the variant suggest that FBN1 may contribute to CS by upregulating the transforming growth factor beta (TGF-ß) signaling. Our study expanded the phenotypic spectrum of FBN1, and provided nove insights into the genetic etiology of CS.

Decreased level of peripheral CD8+CD28+ T cells is associated with lymph node metastasis in patients with breast cancer.

Background: Lymph node metastasis (LNM) is an independent risk factor for prognosis in patients with early breast cancer (EBC). Here we explored whether peripheral lymphocyte subtypes could be used as surrogate markers for LNM in patients with EBC. Materials & methods: The lymphocyte subpopulations in peripheral blood were measured in 152 EBC patients and 43 patients with benign breast tumors. Results: The cytotoxic T cell count was significantly lower in patients with EBC than in patients with benign tumors (244.17 ± 105.83 vs 289.97 ± 121.72; p = 0.02), especially in patients with LNM (218.36 ± 86.21; p = 0.04). Conclusion: A decreased level of peripheral CD8+CD28+ T lymphocytes is associated with LNM in patients with EBC and could be used as a potential therapeutic target for breast cancer.

Integrative analysis from multi-centre studies identifies a function-derived personalized multi-gene signature of outcome in colorectal cancer.

Colorectal cancer (CRC) is highly heterogeneous leading to variable prognosis and treatment responses. Therefore, it is necessary to explore novel personalized and reproducible prognostic signatures to aid clinical decision-making. The present study combined large-scale gene expression profiles and clinical data of 1828 patients with CRC from multi-centre studies and identified a personalized gene prognostic signature consisting of 46 unique genes (called function-derived personalized gene signature [FunPGS]) from an integrated statistics and function-derived perspective. In the meta-training and multiple independent validation cohorts, the FunPGS effectively discriminated patients with CRC with significantly different prognosis at the individual level and remained as an independent factor upon adjusting for clinical covariates in multivariate analysis. Furthermore, the FunPGS demonstrated superior performance for risk stratification with respect to other recently reported signatures and clinical factors. The complementary value of the molecular signature and clinical factors was further explored, and it was observed that the composite signature called IMCPS greatly improved the predictive performance of survival estimation relative to molecular signatures or clinical factors alone. With further prospective validation in clinical trials, the FunPGS may become a promising and powerful personalized prognostic tool for stratifying patients with CRC in order to achieve an optimal systemic therapy.

A novel lncRNA-focus expression signature for survival prediction in endometrial carcinoma.

BACKGROUND: Endometrial cancer (UCEC) is a complex malignant tumor characterized by both genetic level and clinical trial. Patients with UCEC exhibit the similar clinical features, however, they have distinct outcomes due to molecular heterogeneity. The aim of this study was to access the prognostic value of long non-coding RNAs (lncRNAs) in UCEC patients and to identify potential lncRNA signature for predicting patients' survival and improving patient-tailored treatment. METHODS: We performed a comprehensive genome-wide analysis of lncRNA expression profiles and clinical data in a large cohort of 301 UCEC patients. UCEC patients were randomly divided into the discovery cohort (n = 150) and validation cohort (n = 151). A novel lncRNA-focus expression signature was identified in the discovery cohort, and independently accessed in the validation cohort. Additionally, the lncRNA signature was evaluated by multivariable Cox regression and stratification analysis as well as functional enrichment analysis. RESULTS: We detected a novel lncRNA-focus expression signature (LFES) consisting of 11 lncRNAs that were associated with survival based on risk scoring strategy in UCEC. The risk score based on the LFES was able to separate patients of discovery cohort into high-risk and low-risk groups with significantly different overall survival and progression-free survival, and has been successfully confirmed in the validation cohort. Furthermore, the LFES is an independent prognostic predictor of survival and demonstrates superior prognostic performance compared with the clinical covariates for predicting 5-year survival (AUC = 0.887). Functional analysis has linked the expression of prognostic lncRNAs to well-known tumor suppressor or ontogenetic pathways in endometrial carcinogenesis. CONCLUSIONS: Our study revealed a novel 11-lncRNA signature to predict survival of UCEC patient. This lncRNA signature may be a valuable and alternative marker for risk evaluation to aid patient-tailored treatment and improve the outcome of patients with UCEC.

A comprehensive screening shows that ergothioneine is the most abundant antioxidant in the wild macrofungus Phylloporia ribis Ryvarden.

The polar and non-polar extracts from the authenticated wild mushroom Phylloporia ribis were separated by hydrophilic interaction liquid chromatography (HILIC) and by reverse phase (RP)-HPLC, respectively. A split valve separated the eluents into two fractions for free-radical scavenging analysis and for structural identification. Forty-six compounds showed scavenging activity of the stable-free radical 2,2-diphenyl-1-picrylhydrazyl (DPPH). The structures of 8 antioxidants (inosine, caffeic acid, ergothioneine, p-hydroxybenzoic acid, adenosine, 3,4-dihydroxybenzaldehyde, apigenin, and naringenin) are characterized by Mass Spectrometer. Among them, ergothioneine was the most abundant (>65%) and most active antioxidant in P. ribis.