Comprehensive quantitative radiogenomic evaluation reveals novel radiomic subtypes with distinct immune pattern in glioma.

BACKGROUND: Accurate classification of gliomas is critical to the selection of immunotherapy, and MRI contains a large number of radiomic features that may suggest some prognostic relevant signals. We aim to predict new subtypes of gliomas using radiomic features and characterize their survival, immune, genomic profiles and drug response. METHODS: We initially obtained 341 images of 36 patients from the CPTAC dataset for the development of deep learning models. Further 1812 images of 111 patients from TCGA_GBM and 152 images of 53 patients from TCGA_LGG were collected for testing and validation. A deep learning method based on Mask R-CNN was developed to identify new subtypes of glioma patients and compared the survival status, immune infiltration patterns, genomic signatures, specific drugs, and predictive models of different subtypes. RESULTS: 200 glioma patients (mean age, 33 years ± 19 [standard deviation]) were enrolled. The accuracy of the deep learning model for identifying tumor regions achieved 88.3 % (98/111) in the test set and 83 % (44/53) in the validation set. The sample was divided into two subtypes based on radiomic features showed different prognostic outcomes (hazard ratio, 2.70). According to the results of the immune infiltration analysis, the subtype with a poorer prognosis was defined as the immunosilencing radiomic (ISR) subtype (n = 43), and the other subtype was the immunoactivated radiomic (IAR) subtype (n = 53). Subtype-specific genomic signatures distinguished celllines into ISR celllines (n = 9) and control celllines (n = 13), and identified eight ISR-specific drugs, four of which were validated by the OCTAD database. Three machine learning-based classifiers showed that radiomic and genomic co-features better predicted the radiomic subtypes of gliomas. CONCLUSIONS: These findings provide insights into how radiogenomic could identify specific subtypes that predict prognosis, immune and drug sensitivity in a non-invasive manner.

Effect of different thermal processing methods on sensory, nutritional, physicochemical and structural properties of Penaeus vannamei.

The aim of this study was to investigate the effect of different thermal processing methods on the nutritional and physicochemical qualities of Penaeus vannamei. Three different thermal processing methods, namely, drying (DS, 120 °C/40 min), steaming (SS, 100 °C/2 min), and microwaving (MS, 600 W/2 min) were used to treat the shrimps. Low-field nuclear magnetic resonance data indicated that fixed water was the main component of Penaeus vannamei. The ratio of fatty acids in MS and DS samples was more in line with the FAO/WHO recommended health requirements; The myofibrillar protein carbonyl group increased, whereas sulfhydryl content decreased after thermal processing, indicating that the proteins were oxidized by thermal processing. The magnitude of oxidation is: MS > SS > DS. Different thermal processing methods can exert great influence on color texture and nutrition to Penaeus vannamei, which can provide a theoretical knowledge for consumers to choose the appropriate processing method.

Exploration of chiral drugs as references for chiral discrimination of valsartan and voriconazole by tandem mass spectrometry.

The use of mass spectrometry for chiral recognition and quantification has attracted great interest owing to its speed, sensitivity, specificity, and tolerance. However, searching for chiral selectors in chiral analyses using mass spectrometry is still problematic. In this study, chiral drugs could be applied as references for the chiral recognition and enantiomeric quantification of valsartan and voriconazole. Two novel pairs of metal-bound diastereomeric complex ions were detected by mass spectrometry, namely, nickel (II)-bound dimeric ions [NiII (2R,5S-emtricitabine) (S-valsartan)-H]+ and [NiII (2R,5S-emtricitabine) (R-valsartan)-H]+ and copper (II)-bound dimeric ions [CuII (S,S,S-enalaprilat) (2S,3R-voriconazole)-H]+ and [CuII (S,S,S-enalaprilat) (2R,3S-voriconazole)-H]+ . The resulting diastereomers were successfully identified based on the relative intensities of their characteristic fragments using tandem mass spectrometry. The logarithm of the characteristic fragment ion abundance ratio exhibited a good linear relationship with the enantiomeric excess. Density functional theory calculations were also performed to elucidate the mechanism of the structural differences observed in the MS results. This established approach proves that chiral drugs can serve as ligands for the rapid recognition and quantitative analysis of other chiral drugs without a chiral chromatographic column or complex sample pretreatment.

Reconstructing the immunosenescence core pathway reveals global characteristics in pan-cancer.

Immunosenescence has been demonstrated to play an important role in tumor progression. However, there is lacking comprehensive analyses of immunosenescence-related pathways. Meanwhile, the sex disparities of immunosenescence in cancer are still poorly understood. In this study, we analyzed the multi-omics data of 12,836 tumor samples, including genomics, transcriptomics, epigenomics, proteomics, and metabolomics. We systematically identified immunosenescence pathways that were disordered across cancer types. The mutations and copy number variations of immunosenescence pathways were found to be more active in pan-cancer. We reconstructed the immunosenescence core pathways (ISC-pathways) to improve the ability of prognostic stratification in 33 cancer types. We also found the head and neck squamous carcinoma (HNSC) contained abundant sex-specific immunosenescence features and showed sex differences in survival. We found that OSI-027 was a potential sex-specific drug in HNSC tumors, which tended to be more effective in male HNSC by targeting the MTOR gene in the PI3K-Akt signaling pathway. In conclusion, our study provided a systematic understanding of immunosenescence pathways and revealed the global characteristics of immunosenescence in pan-cancer. We highlighted MTOR gene could be a powerful immunosenescence biomarker of HNSC that helps to develop sex-specific immunosenescence drugs.

CRS: a circadian rhythm score model for predicting prognosis and treatment response in cancer patients.

BACKGROUND: Circadian rhythm regulates complex physiological activities in organisms. A strong link between circadian dysfunction and cancer has been identified. However, the factors of dysregulation and functional significance of circadian rhythm genes in cancer have received little attention. METHODS: In 18 cancer types from The Cancer Genome Atlas (TCGA), the differential expression and genetic variation of 48 circadian rhythm genes (CRGs) were examined. The circadian rhythm score (CRS) model was created using the ssGSEA method, and patients were divided into high and low groups based on the CRS. The Kaplan-Meier curve was created to assess the patient survival rate. Cibersort and estimate methods were used to identify the infiltration characteristics of immune cells between different CRS subgroups. Gene Expression Omnibus (GEO) dataset is used as verification queue and model stability evaluation queue. The CRS model's ability to predict chemotherapy and immunotherapy was assessed. Wilcoxon rank-sum test was used to compare the differences of CRS among different patients. We use CRS to identify potential "clock-drugs" by the connective map method. RESULTS: Transcriptomic and genomic analyses of 48 CRGs revealed that most core clock genes are up-regulated, while clock control genes are down-regulated. Furthermore, we show that copy number variation may affect CRGs aberrations. Based on CRS, patients can be classified into two groups with significant differences in survival and immune cell infiltration. Further studies showed that patients with low CRS were more sensitive to chemotherapy and immunotherapy. Additionally, we identified 10 compounds (e.g. flubendazole, MLN-4924, ingenol) that are positively associated with CRS, and have the potential to modulate circadian rhythms. CONCLUSIONS: CRS can be utilized as a clinical indicator to predict patient prognosis and responsiveness to therapy, and identify potential "clock-drugs".

Rapid Detection of Estrogens in Cosmetics by Chemical Derivatization and Paper-Spray Ionization Mass-Spectrometry.

Estrogens in personal care products are harmful to customers. Conventional methods such as HPLC and LC-MS require tedious sample pretreatment and long analytical time. Paper-spray ionization mass spectrometry (PSI-MS) is a powerful tool for the determination of compounds with little time and minimal pretreatment procedures. Since most estrogens show poor responses in PSI-MS, we developed a chemical derivatization and PSI-MS method to determinate three estrogens: estradiol, estriol and ethinyloestradiol with estradiol valerate as the internal standard (I.S.). After derivatization with 2-fluoro-1-methyl-pyridinium-p-toluene-sulfonate, the three estrogens could be quantified in seconds. This method showed good linearity in the range of 0.1~30 µg·mL-1, with R2 > 0.999. Their recovery results were all between 85%~115%. The limits of detection (LOD) were 0.04 µg·mL-1, 0.02 µg·mL-1 and 0.02 µg·mL-1 for estradiol, estriol and ethinyloestradiol respectively, which improved around 200, 2000, and 900 times compared to non-derivative PSI-MS. The method could quantitatively determine estrogens in cosmetics.

Pan-cancer transcriptomic analysis identified six classes of immunosenescence genes revealed molecular links between aging, immune system and cancer.

Aging is a complex process that significantly impacts the immune system. The aging-related decline of the immune system, termed immunosenescence, can lead to disease development, including cancer. The perturbation of immunosenescence genes may characterize the associations between cancer and aging. However, the systematical characterization of immunosenescence genes in pan-cancer remains largely unexplored. In this study, we comprehensively investigated the expression of immunosenescence genes and their roles in 26 types of cancer. We developed an integrated computational pipeline to identify and characterize immunosenescence genes in cancer based on the expression profiles of immune genes and clinical information of patients. We identified 2218 immunosenescence genes that were significantly dysregulated in a wide variety of cancers. These immunosenescence genes were divided into six categories based on their relationships with aging. Besides, we assessed the importance of immunosenescence genes in clinical prognosis and identified 1327 genes serving as prognostic markers in cancers. BTN3A1, BTN3A2, CTSD, CYTIP, HIF1AN, and RASGRP1 were associated with ICB immunotherapy response and served as prognostic factors after ICB immunotherapy in melanoma. Collectively, our results furthered the understanding of the relationship between immunosenescence and cancer and provided insights into immunotherapy for patients.

Immune Pathways with Aging Characteristics Improve Immunotherapy Benefits and Drug Prediction in Human Cancer.

(1) Background: Perturbation of immune-related pathways can make substantial contributions to cancer. However, whether and how the aging process affects immune-related pathways during tumorigenesis remains largely unexplored. (2) Methods: Here, we comprehensively investigated the immune-related genes and pathways among 25 cancer types using genomic and transcriptomic data. (3) Results: We identified several pathways that showed aging-related characteristics in various cancers, further validated by conventional aging-related gene sets. Genomic analysis revealed high mutation burdens in cytokines and cytokines receptors pathways, which were strongly correlated with aging in diverse cancers. Moreover, immune-related pathways were found to be favorable prognostic factors in melanoma. Furthermore, the expression level of these pathways had close associations with patient response to immune checkpoint blockade therapy in melanoma and non-small cell lung cancer. Applying a net-work-based method, we predicted immune- and aging-related genes in pan-cancer and utilized these genes for potential immunotherapy drug discovery. Mapping drug target data to our top-ranked genes identified potential drug targets, FYN, JUN, and SRC. (4) Conclusions: Taken together, our systematic study helped interpret the associations among immune-related pathways, aging, and cancer and could serve as a resource for promoting clinical treatment.

LncTarD 2.0: an updated comprehensive database for experimentally-supported functional lncRNA-target regulations in human diseases.

An updated LncTarD 2.0 database provides a comprehensive resource on key lncRNA-target regulations, their influenced functions and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD 2.0 is freely available at (http://bio-bigdata.hrbmu.edu.cn/LncTarD or https://lnctard.bio-database.com/). LncTarD 2.0 was updated with several new features, including (i) an increased number of disease-associated lncRNA entries, where the current release provides 8360 key lncRNA-target regulations, with 419 disease subtypes and 1355 lncRNAs; (ii) predicted 3312 out of 8360 lncRNA-target regulations as potential diagnostic or therapeutic biomarkers in circulating tumor cells (CTCs); (iii) addition of 536 new, experimentally supported lncRNA-target regulations that modulate properties of cancer stem cells; (iv) addition of an experimentally supported clinical application section of 2894 lncRNA-target regulations for potential clinical application. Importantly, LncTarD 2.0 provides RNA-seq/microarray and single-cell web tools for customizable analysis and visualization of lncRNA-target regulations in diseases. RNA-seq/microarray web tool was used to mining lncRNA-target regulations in both disease tissue samples and CTCs blood samples. The single-cell web tools provide single-cell lncRNA-target annotation from the perspectives of pan-cancer analysis and cancer-specific analysis at the single-cell level. LncTarD 2.0 will be a useful resource and mining tool for the investigation of the functions and mechanisms of lncRNA deregulation in human disease.

The dynamic dysregulated network identifies stage-specific markers during lung adenocarcinoma malignant progression and metastasis.

Brain metastasis occurs in approximately 30% of patients with lung adenocarcinoma (LUAD) and is closely associated with poor prognosis, recurrence, and death. However, dynamic gene regulation and molecular mechanism driving LUAD progression remain poorly understood. In this study, we performed a comprehensive single-cell transcriptome analysis using data from normal, early stage, advanced stage, and brain metastasis LUAD. Our single-cell-level analysis reveals the cellular composition heterogeneity at different stages during LUAD progression. We identified stage-specific risk genes that could contribute to LUAD progression and metastasis by reprogramming immune-related and metabolic-related functions. We constructed an early advanced metastatic dysregulated network and revealed the dynamic changes in gene regulations during LUAD progression. We identified 6 early advanced (HLA-DRB1, HLA-DQB1, SFTPB, SFTPC, PLA2G1B, and FOLR1), 8 advanced metastasis (RPS15, RPS11, RPL13A, RPS24, HLA-DRB5, LYPLA1, KCNJ15, and PSMA3), and 2 common risk genes in different stages (SFTPD and HLA-DRA) as prognostic markers in LUAD. Particularly, decreased expression of HLA-DRA, HLA-DRB1, HLA-DQB1, and HLA-DRB5 refer poor prognosis in LUAD by controlling antigen processing and presentation and T cell activation. Increased expression of PSMA3 and LYPLA1 refer poor prognosis by reprogramming fatty acid metabolism and RNA catabolic process. Our findings will help further understanding the pathobiology of brain metastases in LUAD.

Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data.

Breast cancer is a cancer of high complexity and heterogeneity, with differences in prognosis and survival among patients of different subtypes. Copy number variations (CNVs) within enhancers are crucial drivers of tumorigenesis by influencing expression of their targets. In this study, we performed an integrative approach to identify CNA-driven enhancers and their effect on expression of target genes in four breast cancer subtypes by integrating expression data, copy number data and H3K27ac data. We identified 672, 555, 531, 361 CNA-driven enhancer-gene pairs and 280, 189, 113 and 98 CNA-driven enhancer-lncRNA pairs in the Basal-like, Her2, LumA and LumB subtypes, respectively. We then reconstructed a CNV-driven enhancer-lncRNA-mRNA regulatory network in each subtype. Functional analysis showed CNA-driven enhancers play an important role in the progression of breast cancer subtypes by influencing P53 signaling pathway, PPAR signaling pathway, systemic lupus erythematosus and MAPK signaling pathway in the Basal-like, Her2, LumA and LumB subtypes, respectively. We characterized the potentially prognostic value of target genes of CNV-driven enhancer and lncRNA-mRNA pairs in the subtype-specific network. We identified MUM1 and AC016876.1 as prognostic biomarkers in LumA and Basal-like subtypes, respectively. Higher expression of MUM1 with an amplified enhancer exhibited poorer prognosis in LumA patients. Lower expression of AC016876.1 with a deleted enhancer exhibited poorer survival outcomes of Basal-like patients. We also identified enhancer-related lncRNA-mRNA pairs as prognostic biomarkers, including AC012313.2-MUM1 in the LumA, AC026471.4-PLK5 in the LumB, AC027307.2-OAZ1 in the Basal-like and AC022431.1-HCN2 in the Her2 subtypes. Finally, our results highlighted target genes of CNA-driven enhancers and enhancer-related lncRNA-mRNA pairs could act as prognostic markers and potential therapeutic targets in breast cancer subtypes.

Functional regulations between genetic alteration-driven genes and drug target genes acting as prognostic biomarkers in breast cancer.

Differences in genetic molecular features including mutation, copy number alterations and DNA methylation, can explain interindividual variability in response to anti-cancer drugs in cancer patients. However, identifying genetic alteration-driven genes and characterizing their functional mechanisms in different cancer types are still major challenges for cancer studies. Here, we systematically identified functional regulations between genetic alteration-driven genes and drug target genes and their potential prognostic roles in breast cancer. We identified two mutation and copy number-driven gene pairs (PARP1-ACSL1 and PARP1-SRD5A3), three DNA methylation-driven gene pairs (PRLR-CDKN1C, PRLR-PODXL2 and PRLR-SRD5A3), six gene pairs between mutation-driven genes and drug target genes (SLC19A1-SLC47A2, SLC19A1-SRD5A3, AKR1C3-SLC19A1, ABCB1-SRD5A3, NR3C2-SRD5A3 and AKR1C3-SRD5A3), and four copy number-driven gene pairs (ADIPOR2-SRD5A3, CASP12-SRD5A3, SLC39A11-SRD5A3 and GALNT2-SRD5A3) that all served as prognostic biomarkers of breast cancer. In particular, RARP1 was found to be upregulated by simultaneous copy number amplification and gene mutation. Copy number deletion and downregulated expression of ACSL1 and upregulation of SRD5A3 both were observed in breast cancers. Moreover, copy number deletion of ACSL1 was associated with increased resistance to PARP inhibitors. PARP1-ACSL1 pair significantly correlated with poor overall survival in breast cancer owing to the suppression of the MAPK, mTOR and NF-kB signaling pathways, which induces apoptosis, autophagy and prevents inflammatory processes. Loss of SRD5A3 expression was also associated with increased sensitivity to PARP inhibitors. The PARP1-SRD5A3 pair significantly correlated with poor overall survival in breast cancer through regulating androgen receptors to induce cell proliferation. These results demonstrate that genetic alteration-driven gene pairs might serve as potential biomarkers for the prognosis of breast cancer and facilitate the identification of combination therapeutic targets for breast cancers.

Chiral probe for mass spectrometric identification and quantitation of levodropropizine and its enantiomer, dextrodropropizine.

Acyl chlorides react rapidly with hydroxyl and amino groups in the absence of catalysts and therefore hold great promise for chiral mass spectrometry. Herein, a tandem mass spectrometry method based on derivatization with (-)-camphanic acid chloride as a simple chiral probe was developed for the highly sensitive detection and quantitation of levodropropizine and its enantiomer, namely, dextrodropropizine. The diastereomeric derivatization products were quantified based on the relative abundances of their fragment ions produced upon collision-induced dissociation in positive-ion mode. The reactive site was elucidated using nuclear magnetic resonance spectroscopy and two-dimensional total correlation spectroscopy, and the reaction mechanism was proved by stoichiometry studies. The degree of isomer recognition was investigated at different collision energies and determined as Rchiral  ≈ 1.5. Thus, this study gives the way to the mass spectrometric identification and quantitation of levodropropizine and its enantiomer, and the developed method represents a new and practical technique for rapid and sensitive determination and quality control of enantiomers of chiral drugs.

Complete genome sequence of Pseudomonas stutzeri S116 owning bifunctional catalysis provides insights into affecting performance of microbial fuel cells.

BACKGROUND: Pseudomonas stutzeri S116 is a sulfur-oxidizing bacteria isolated from marine sludge. It exhibited excellent electricity generation as bioanode and biocathode applied in microbial fuel cells (MFCs). Complete genome sequencing of P. stutzeri and cyclic voltammetry method were performed to reveal its mechanism in microbial fuel cells system. RESULTS: This study indicated that the MFCs generated a maximum output voltage of 254.2 mV and 226.0 mV, and maximum power density of 765 mW/m2 and 656.6 mW/m2 respectively. Complete genome sequencing of P. stutzeri S116 was performed to indicate that most function genes showed high similarities with P. stutzeri, and its primary annotations were associated with energy production and conversion (6.84%), amino acid transport and metabolism (6.82%) and inorganic ion transport and metabolism (6.77%). Homology of 36 genes involved in oxidative phosphorylation was detected, which suggests the strain S116 possesses an integrated electron transport chain. Additionally, many genes encoding pilus-assembly proteins and redox mediators (riboflavin and phenazine) were detected in the databases. Thiosulfate oxidization and dissimilatory nitrate reduction were annotated in the sulfur metabolism pathway and nitrogen metabolism pathway, respectively. Gene function analysis and cyclic voltammetry indicated that P. stutzeri probably possesses cellular machinery such as cytochrome c and redox mediators and can perform extracellular electron transfer and produce electricity in MFCs. CONCLUSION: The redox mediators secreted by P. stutzeri S116 were probably responsible for performance of MFCs. The critical genes and metabolic pathways involved in thiosulfate oxide and nitrate reduction were detected, which indicated that the strain can treat wastewater containing sulfide and nitrite efficiently.

Epigenome signature as an immunophenotype indicator prompts durable clinical immunotherapy benefits in lung adenocarcinoma.

Intertumoral immune heterogeneity is a critical reason for distinct clinical benefits of immunotherapy in lung adenocarcinoma (LUAD). Tumor immunophenotype (immune 'Hot' or 'Cold') suggests immunological individual differences and potential clinical treatment guidelines. However, employing epigenome signatures to determine tumor immunophenotypes and responsive treatment is not well understood. To delineate the tumor immunophenotype and immune heterogeneity, we first distinguished the immune 'Hot' and 'Cold' tumors of LUAD based on five immune expression signatures. In terms of clinical presentation, the immune 'Hot' tumors usually had higher immunoactivity, lower disease stages and better survival outcomes than 'Cold' tumors. At the epigenome levels, we observed that distinct DNA methylation patterns between immunophenotypes were closely associated with LUAD development. Hence, we identified a set of five CpG sites as the immunophenotype-related methylation signature (iPMS) for tumor immunophenotyping and further confirmed its efficiency based on a machine learning framework. Furthermore, we found iPMS and immunophenotype-related immune checkpoints (IPCPs) could contribute to the risk of tumor progression, implying IPCP has the potential to be a novel immunotherapy blockade target. After further parsing of the role of iPMS-predicted immunophenotypes, we found immune 'Hot' was a protective factor leading to better survival outcomes when patients received the anti-PD-1/PD-L1 immunotherapy. And iPMS was also a well-performed signature (AUC = 0.752) for predicting the durable/nondurable clinical benefits. In summary, our study explored the role of epigenome signature in clinical tumor immunophenotyping. Utilizing iPMS to characterize tumor immunophenotypes will facilitate developing personalized epigenetic anticancer approaches.

Comprehensive landscape of epigenetic-dysregulated lncRNAs reveals a profound role of enhancers in carcinogenesis in BC subtypes.

Aberrant expression of long non-coding RNAs (lncRNA) is associated with altered DNA methylation and histone modifications during carcinogenesis. However, identifying epigenetically dysregulated lncRNAs and characterizing their functional mechanisms in different cancer subtypes are still major challenges for cancer studies. In this study, we systematically analyzed the epigenetic alterations of lncRNAs at important regulatory elements in three breast cancer subtypes. We identified 87, 691, and 1,197 epigenetically dysregulated lncRNAs in luminal, basal, and claudin-low subtypes of breast cancer, respectively. The landscape of epigenetically dysregulated lncRNAs at enhancer elements revealed that epigenetic changes of the majority of lncRNAs occurred in a subtype-specific manner and contributed to subtype-specific biological functions. We identified six acetylation of lysine 27 on histone H3 (H3K27ac)-dysregulated lncRNAs and three DNA methylation-dysregulated lncRNAs (CTC-303L1.2, RP11-738B7.1, and SLC26A4-AS1) as prognostic biomarkers of basal subtype. These lncRNAs were involved in immune response-related biological functions. Treatment of the basal breast cancer cell line MDA-MB-468 with CREBBP/EP300 bromodomain inhibitors downregulated H3K27 acetylation levels and caused a decrease in the expression of five H3K27ac-dysregulated lncRNAs (LINC00393, KB-1836B5.1, RP1-140K8.5, AC005162.1, and AC020916.2) and inhibition of the growth of breast cancer cells. One epigenetically dysregulated lncRNA (LINC01983) and four lncRNA regulators (UCA1, RP11-221J22.2, RP11-221J22.1, and RP1-212P9.3) were identified as prognostic biomarkers of the luminal molecular subtype of breast cancer by controlling the tumor necrosis factor (TNF) signaling pathway, T helper (Th)17 cell differentiation, and T cell migration. Finally, our results highlighted a profound role of enhancer-related H3K27ac-dysregulated lncRNAs, DNA methylation-dysregulated lncRNAs, and lncRNA regulators in breast cancer subtype carcinogenesis and their potential prognostic value.

LncTarD: a manually-curated database of experimentally-supported functional lncRNA-target regulations in human diseases.

Long non-coding RNAs (lncRNAs) are associated with human diseases. Although lncRNA-disease associations have received significant attention, no online repository is available to collect lncRNA-mediated regulatory mechanisms, key downstream targets, and important biological functions driven by disease-related lncRNAs in human diseases. We thus developed LncTarD (http://biocc.hrbmu.edu.cn/LncTarD/ or http://bio-bigdata.hrbmu.edu.cn/LncTarD), a manually-curated database that provides a comprehensive resource of key lncRNA-target regulations, lncRNA-influenced functions, and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD offers (i) 2822 key lncRNA-target regulations involving 475 lncRNAs and 1039 targets associated with 177 human diseases; (ii) 1613 experimentally-supported functional regulations and 1209 expression associations in human diseases; (iii) important biological functions driven by disease-related lncRNAs in human diseases; (iv) lncRNA-target regulations responsible for drug resistance or sensitivity in human diseases and (v) lncRNA microarray, lncRNA sequence data and transcriptome data of an 11 373 pan-cancer patient cohort from TCGA to help characterize the functional dynamics of these lncRNA-target regulations. LncTarD also provides a user-friendly interface to conveniently browse, search, and download data. LncTarD will be a useful resource platform for the further understanding of functions and molecular mechanisms of lncRNA deregulation in human disease, which will help to identify novel and sensitive biomarkers and therapeutic targets.

A rapid assay of identification for glimepiride and its cis-isomer by tandem mass spectrometry.

A simple and rapid identification method of glimepiride and its cis-isomer was established for the first time. The collision-induced dissociation (CID) mass spectrometry method was used in this study. Under negative ion mode, the CID mass spectra of the deprotonated molecule ion showed two characteristic ions, m/z 364 and m/z 376, which are confirmed by the method of energy-resolved mass spectrometry (ERMS). The relative abundance of the m/z 364 of glimepiride showed lower than that of its cis-isomer, which is related to the stereo structure of glimepiride and its isomer. Zinc ion was chosen to adduct to the glimepiride and its isomer, which experimental results showed the zinc ions enhanced the degree of recognition. The RIsomer values, which evaluate the degree of the isomer recognition, were investigated at different collision energy. The quantitative determination of glimepiride was performed by using MS/MS. Aiming at the recognition of geometric isomers; this methodology shows huge potential of extended mass spectrometry method to a large number of chiral drugs and their impurity.

[The impurity profiling of paclitaxel and its injection by UPLC-MS/MS].

An ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS-MS) method was developed to elucidate the impurity profiles of paclitaxel and paclitaxel injections from different Chinese pharmaceutical companies. The fragmentation patterns for paclitaxel and the related impurities were analyzed and summarized. To remove the interference from auxiliary materials, such as hydrogenated castor oil, paclitaxel was dissolved in ethanol for acid, base, peroxide, and light induced forced degradation analysis, which could produce all the impurities exist in the paclitaxel injection. A total of 10 impurities were characterized, such as cephalomannine (1), 7-epi-10-deacetylpaclitaxel (2), 7-epipaclitaxel (3), baccatin Ⅲ (4), ethyl ester side chain (5), 7-epi-baccatin Ⅲ (6), 10-deacetylpaclitaxel (7), paclitaxel isomer(C3-C11 bridge) (8), paclitaxel isomer (9), and N-benzoyl-(2R,3S)-3-phenylisoserine (10), respectively. Among them, compounds 1-3 could be introduced during manufacture processing. In the forced degradation studies, while acid induced degradation products included 3-7, base induced degradation could produce 2-7 and 10; while 7 is the main compound produced by hydrogen peroxide treatment, 4 compounds (3-5 and 7) were produced by high temperature environment and 5 compounds (2-5 and 9 which is the first reported) from intensity light exposure. Furthermore, 8 was the main impurity came from intensity light exposed paclitaxel powder. The results from this study provide an important reference in processing, optimization, quality control and evaluation of paclitaxel.