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Background: Pancreatic ductal adenocarcinoma (PDAC) remains a formidable health challenge due to its detection at a late stage and a lack of reliable biomarkers for early detection. Although levels of carbohydrate antigen 19-9 are often used in conjunction with imaging-based tests to aid in the diagnosis of PDAC, there is still a need for more sensitive and specific biomarkers for early detection of PDAC., Methods: We obtained serum samples from 88 subjects (patients with PDAC (n = 58) and controls (n = 30)). We carried out a multi-omics analysis to measure cytokines and related proteins using proximity extension technology and lipidomics and metabolomics using tandem mass spectrometry. Statistical analysis was carried out to find molecular alterations in patients with PDAC and a machine learning model was used to derive a molecular signature of PDAC., Results: We quantified 1,462 circulatory proteins along with 873 lipids and 1,001 metabolites. A total of 505 proteins, 186 metabolites and 33 lipids including bone marrow stromal antigen 2 (BST2), keratin 18 (KRT18), and cholesteryl ester(20:5) were found to be significantly altered in patients. We identified different levels of sphingosine, sphinganine, urobilinogen and lactose indicating that glycosphingolipid and galactose metabolisms were significantly altered in patients compared to controls. In addition, elevated levels of diacylglycerols and decreased cholesteryl esters were observed in patients. Using a machine learning model, we identified a signature of 38 biomarkers for PDAC, composed of 21 proteins, 4 lipids, and 13 metabolites., Conclusions: Overall, this study identified several proteins, metabolites and lipids involved in various pathways including cholesterol and lipid metabolism to be changing in patients. In addition, we discovered a multi-analyte signature that could be further tested for detection of PDAC., Competing Interests: Declarations. Conflict of interest: The authors declare that they have no conflict of interest., (© 2024. Japanese Society of Gastroenterology.)

Drug resistance poses a significant obstacle to the success of anti-cancer therapy in head and neck cancers (HNCs). We aim to develop a platform for visualizing and analyzing molecular expression alterations associated with HNC drug resistance. Through data mining, we convened differentially expressed molecules and context-specific signaling events involved in drug resistance. The driver genes, interaction networks and transcriptional regulations were explored using bioinformatics approaches. A total of 2364 differentially expressed molecules were identified in 78 distinct drug-resistant cells against 14 anti-cancer drugs, comprising 1131 mRNAs, 746 proteins, 62 lncRNAs, 257 miRNAs, 1 circRNA, and 166 post-translational modifications. Among these, 255 molecules were considerably, the signature driver genes of HNC drug resistance. Further, we also developed a landscape of signaling pathways and their cross-talk with diverse signaling modules involved in drug resistance. Additionally, a publicly-accessible database named "HNCDrugResDb" was designed with browse, query, and pathway explorer options to fetch and enrich molecular alterations and signaling pathways altered in drug resistance. HNCDrugResDb is also enabled with a Drug Resistance Analysis tool as an initial platform to infer the likelihood of resistance based on the expression pattern of driver genes. HNCDrugResDb is anticipated to have substantial implications for future advancements in drug discovery and optimization of personalized medicine approaches., (© 2024. The Author(s).)

Interleukin-26 (IL-26) is a cytokine that belongs to the IL-20 subfamily and is primarily expressed in T helper 1 cells and Th17 memory CD4 + cells. Its receptor complex, consisting of IL-20R1 and IL-10R2, activates a signaling pathway involving several proteins such as Janus kinase 1 and tyrosine-protein kinase, signal transducer and activator of transcription (STAT) 1, and STAT3. This leads to the initiation of downstream signaling cascades that play a crucial role in various biological processes, including inflammation, immune response regulation, atopic dermatitis, macrophage differentiation, osteoclastogenesis, antibacterial host defense, anti-apoptosis, and tumor growth. In this study, we curated literature data pertaining to IL-26 signaling. The curated map includes a total of seven activation/inhibition events, 16 catalysis events, 33 gene regulation events, 25 protein expression types, two transport events, and three molecular associations.

Hemigraphis alternata (H. alternata), commonly known as Red Flame Ivy, is widely recognized for its wound healing capabilities. However, the pharmacologically active plant components and their mechanisms of action in wound healing are yet to be determined. This study presents the mass spectrometry-based global metabolite profiling of aqueous and ethanolic extract of H. alternata leaves. The analysis identified 2285 metabolites from 24,203 spectra obtained in both positive and negative polarities. The identified metabolites were classified under ketones, carboxylic acids, primary aliphatic amines, steroids and steroid derivatives. We performed network pharmacology analysis to explore metabolite-protein interactions and identified 124 human proteins as targets for H. alternata metabolites. Among these, several of them were implicated in wound healing including prothrombin (F2), alpha-2A adrenergic receptor (ADRA2A) and fibroblast growth factor receptor 1 (FGFR1). Gene ontology analysis of target proteins enriched cellular functions related to glucose metabolic process, platelet activation, membrane organization and response to wounding. Additionally, pathway enrichment analysis revealed potential molecular network involved in wound healing. Moreover, in-silico docking analysis showed strong binding energy between H. alternata metabolites with identified protein targets (F2 and PTPN11). Furthermore, the key metabolites involved in wound healing were further validated by multiple reaction monitoring-based targeted analysis., (© 2024. The Author(s).)

Long non-coding-RNAs (lncRNAs) are an expanding set of cis-/trans-regulatory RNA genes that outnumber the protein-coding genes. Although being increasingly discovered, the functional role of the majority of lncRNAs in diverse biological conditions is undefined. Increasing evidence supports the critical role of lncRNAs in the emergence, regulation, and progression of various viral infections including influenza, hepatitis, coronavirus, and human immunodeficiency virus. Hence, the identification of signature lncRNAs would facilitate focused analysis of their functional roles accounting for their targets and regulatory mechanisms associated with infections. Towards this, we compiled 2803 lncRNAs identified to be modulated by 33 viral strains in various mammalian cell types and are provided through the resource named VirhostlncR (http://ciods.in/VirhostlncR/). The information on each of the viral strains, their multiplicity of infection, duration of infection, host cell name and cell types, fold change of lncRNA expression, and their specific identification methods are integrated into VirhostlncR. Based on the current datasets, we report 150 lncRNAs including differentiation antagonizing non-protein coding RNA (DANCR), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), maternally expressed gene 3 (MEG3), nuclear paraspeckle assembly transcript 1 (NEAT1), and plasmacytoma variant translocation 1 (PVT1) to be perturbed by two or more viruses. Analysis of viral protein interactions with human transcription factors (TFs) or TF-containing protein complexes identified that distinct viruses can transcriptionally regulate many of these lncRNAs through multiple protein complexes. Together, we believe that the current dataset will enable priority selection of lncRNAs for identification of their targets and serve as an effective platform for the analysis of noncoding RNA-mediated regulations in viral infections., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2023. Published by Elsevier Ltd.)

Trophoblast cell surface antigen 2 (TROP2) is a calcium-transducing transmembrane protein mainly involved in embryo development. The aberrant expression of TROP2 is observed in numerous cancers, including triple-negative breast cancer, gastric, colorectal, pancreatic, squamous cell carcinoma of the oral cavity, and prostate cancers. The main signaling pathways mediated by TROP2 are calcium signaling, PI3K/AKT, JAK/STAT, MAPKs, and β-catenin signaling. However, collective information about the TROP2-mediated signaling pathway is not available for visualization or analysis. In this study, we constructed a TROP2 signaling map with respect to its role in different cancers. The data curation was done manually by following the NetPath annotation criteria. The described map consists of different molecular events, including 8 activation/inhibition, 16 enzyme catalysis, 19 gene regulations, 12 molecular associations, 39 induced-protein expressions, and 2 protein translocation. The data of the TROP2 pathway map is made freely accessible through the WikiPathways Database ( https://www.wikipathways.org/index.php/Pathway:WP5300 ). Development of TROP2 signaling pathway map., (© 2023. The International CCN Society.)

Macrophage-stimulating protein (MSP), a serum-derived growth factor belonging to the plasminogen-related kringle domain family, is mainly produced by the liver and released into the blood. MSP is the only known ligand for RON ("Recepteur d'Origine Nantais", also known as MST1R), which is a member of the receptor tyrosine kinase (RTK) family. MSP is associated with many pathological conditions, including cancer, inflammation, and fibrosis. Activation of the MSP/RON system regulates main downstream signaling pathways, including phosphatidylinositol 3-kinase/ AKT serine/threonine kinase/ (PI3-K/AKT), mitogen-activated protein kinases (MAPK), c-Jun N-terminal kinase (JNK) & Focal adhesion kinase (FAK). These pathways are mainly involved in cell proliferation, survival, migration, invasion, angiogenesis & chemoresistance. In this work, we created a pathway resource of signaling events mediated by MSP/RON considering its contribution to diseases. We provide an integrated pathway reaction map of MSP/RON that is composed of 113 proteins and 26 reactions based on the curation of data from the published literature. The consolidated pathway map of MSP/RON mediated signaling events contains seven molecular associations, 44 enzyme catalysis, 24 activation/inhibition, six translocation events, 38 gene regulation events, and forty-two protein expression events. The MSP/RON signaling pathway map can be freely accessible through the WikiPathways Database URL: https://classic.wikipathways.org/index.php/Pathway:WP5353 ., (© 2023. The International CCN Society.)

The calcium/calmodulin dependent protein kinase kinase 2 (CAMKK2) plays a key role in regulation of intracellular calcium levels and signaling pathways. It is involved in activation of downstream signaling pathways that regulate various cellular processes. Dysregulation of CAMKK2 activity has been linked to various diseases including cancer, suggesting that CAMKK2 inhibitors might be beneficial in oncological, metabolic and inflammatory indications. The most pressing issues in small molecule discovery are synthesis feasibility, novel chemical structure and desired biological characteristics. To circumvent this constraint, we employed 'DrugspaceX' for rapid lead identification, followed by repositioning seven FDA-approved drugs for CAMKK2 inhibition. Further, first-level transformation (Set1 analogues) was performed in 'DrugspaceX', followed by virtual screening. The t-SNE visualization revealed that the transformations surrounding Rucaparib, Treprostinil and Canagliflozin are more promising for developing CAMKK2 inhibitors. Second, using the top-ranked Set1 analogues, Set2 analogues were generated, and virtual screening revealed the top-ranked five analogues. Among the top five Set2 analogues, DE273038_5 had the lowest docking score of -11.034 kcal/mol and SA score of 2.59, retaining the essential interactions with Hotspot residues LYS194 and VAL270 across 250 ns simulation period. When compared to the other four compounds, the ligand effectiveness score was 0.409, and the number of rotatable penalties was only three. Further, DE273038_5 after two rounds of transformations was discovered to be novel and had not been previously described in other databases. These data suggest that the new candidate DE273038_5 is likely to have inhibitory activity at the CAMKK2 active site, implying potential therapeutic use.Communicated by Ramaswamy H. Sarma.

The Triton X-114-based solubilization and temperature-dependent phase separation of proteins is used for subcellular fractionation where, aqueous, detergent, and pellet fractions represents cytoplasmic, outer membrane (OM), and inner membrane proteins, respectively. Mass spectrometry-based proteomic analysis of Triton X-114 fractions of proteomic analysis of Leptospira interrogans identified 2957 unique proteins distributed across the fractions. The results are compared with bioinformatics predictions on their subcellular localization and pathogenic nature. Analysis of the distribution of proteins across the Triton X-114 fractions with the predicted characteristics is performed based on "number" of unique type of proteins, and "quantity" which represents the amount of unique protein. The highest number of predicted outer membrane proteins (OMPs) and pathogenic proteins are found in aqueous and pellet fractions, whereas detergent fraction representing the OM has the highest quantity of OMPs and pathogenic proteins though lower in number than the aqueous and pellet fractions. This leaves the possibility of an upsurge in pathogenic proteins and OMPs on the OM under pathogenic conditions suggesting their potential use to combat leptospirosis. Further, the Triton X-114 subcellular fractions are more correlated to enrichment of pathogenic proteins predicted by MP3 software than predicted localization., (© 2020 Wiley-VCH GmbH.)

Nontuberculous mycobacterial (NTM) species present a major challenge for global health with serious clinical manifestations ranging from pulmonary to skin infections. Multiomics research and its applications toward clinical microbial proteogenomics offer veritable potentials in this context. For example, the Mycobacterium abscessus, a highly pathogenic NTM, causes bronchopulmonary infection and chronic pulmonary disease. The rough variant of the M. abscessus UC22 strain is extremely virulent and causes lung upper lobe fibrocavitary disease. Although several whole-genome next-generation sequencing studies have characterized the genes in the smooth variant of M. abscessus, a reference genome sequence for the rough variant was generated only recently and calls for further clinical applications. We carried out whole-genome sequencing and proteomic analysis for a clinical isolate of M. abscessus UC22 strain obtained from a pulmonary tuberculosis patient. We identified 5506 single-nucleotide variations (SNVs), 63 insertions, and 76 deletions compared with the reference genome. Using a high-resolution LC-MS/MS-based approach (liquid chromatography tandem mass spectrometry), we obtained protein coding evidence for 3601 proteins, representing 71% of the total predicted genes in this genome. Application of proteogenomic approach further revealed seven novel protein-coding genes and enabled refinement of six computationally derived gene models. We also identified 30 variant peptides corresponding to 16 SNVs known to be associated with drug resistance. These new observations offer promise for clinical applications of microbial proteogenomics and next-generation sequencing, and provide a resource for future global health applications for NTM species.