Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, driven by profound molecular heterogeneity and resistance to current therapy. To support systematic target identification, we established a proteomics-anchored knowledge discovery framework integrating cross-model proteomics harmonization, network topology, high-confidence structural modeling, and large-scale in silico docking. From 1,975 proteins consistently detected across murine and human PDAC models, 32 immunohistochemically confirmed candidates were prioritized for structure-based screening against 7,509 clinically characterized compounds. Blind docking, refined pose sampling, ligand-efficiency scoring, and ADME filtering identified EIF2A, STAM, ANXA2, and AHNAK2 as robustly druggable targets. These proteins exhibited high-affinity interactions with zavegepant (a clinically approved CGRP receptor antagonist), omilancor, bemcentinib, conivaptan, and APTO-253. Docking validation (RMSD 1.98 to 2.56 Å) confirmed methodological reliability, and network analyses placed the 4 proteins within modules linked to endosomal/membrane trafficking and invasive phenotypes. Survival analyses in 176 PDAC patients further supported their clinical relevance. Thus, we suggest a systems-level platform for nominating ligandable PDAC targets and clinically actionable compounds. The framework highlights opportunities for rational drug repurposing and motivates future mechanistic studies at the intersection of proteomics and structure-based screening for targets to PDAC.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival rate of 10-15% due to late-stage diagnosis and limited efficacy of existing treatments. This study utilized proteomics-based systems modelling to generate multimodal datasets from various research models, including PDAC cells, spheroids, organoids, and tissues derived from murine and human samples. Identical mass spectrometry-based proteomics was applied across the different models. The preparation and validation of the research models and the proteomics were described in detail. The assembly datasets we present here contribute to the data collection on PDAC, which will be useful for systems modelling, data mining, knowledge discovery in databases, and bioinformatics of individual models. Further data analysis may lead to the generation of research hypotheses, predictions of targets for diagnosis and treatment, and relationships between data variables.

Background: Knowledge discovery in databases (KDD) can contribute to translational research, also known as translational medicine, by bridging the gap between in vitro and in vivo studies, and clinical applications. Here, we propose a ‘systems modeling’ workflow for KDD. Methods: This framework includes the data collection of a composition model (various research models), processing model (proteomics) and analytical model (bioinformatics, artificial intelligence/machine leaning and pattern evaluation), knowledge presentation, and feedback loops for hypothesis generation and validation. We applied this workflow to study pancreatic ductal adenocarcinoma (PDAC). Results: We identified the common proteins between human PDAC and various research models in vitro (cells, spheroids and organoids) and in vivo (mouse mice). Accordingly, we hypothesized potential translational targets on hub proteins and the related signaling pathways, PDAC-specific proteins and signature pathways, and high topological proteins. Conclusions: This systems modeling workflow can be a valuable method for KDD, facilitating knowledge discovery in translational targets in general, and in particular to PADA in this case.

Pancreatic ductal adenocarcinoma (PDAC) and gastric adenocarcinoma (GA) are aggressive cancers with poor prognoses, demanding innovative approaches to advance treatment strategies and prevention efforts. This article presents a methodology in connection with PhD thesis on PDAC and GA, including motivation and knowledge in literature (Paper I), various research models (Paper II), knowledge discovery (Papers III and IV), and thesis assessment and evaluation (dissertation). The four studies aimed to address the gaps between patients and researchers and between basic and clinical research. Patient and Public Involvement (PPI) was explored to align research priorities with patients’ needs. While PPI emphasized the importance of treatment-focused research, researchers and scientific journals prioritized basic science. Research guidance of “Findable, Accessible, Interoperable, and Reusable” (FAIR) was implanted in the studies, particularly proteomics datasets of different research models on PDAC. An analytic workflow for knowledge discovery with systems modeling was developed, leading to identification of translational targets of proteins and signaling networks on PDAC. Gastric intestinal metaplasia (GIM) is associated with GA. Multi-bioinformatics identified potential biomarkers for GA-related GIM, including genes and signaling networks. Potential repurposed drugs were also identified for both PDAC and GIM. In conclusion, the methodology was instructive in completing PhD thesis, whereas the findings in the original papers added new knowledge in translational research on PDAC and GA.

Cancer cells have been shown to exploit neurons to modulate their survival and growth, including through the establishment of neural circuits within the central nervous system1-3. Here we report a distinct pattern of cancer-nerve interactions between the peripheral nervous system and gastric cancer. In multiple mouse models of gastric cancer, nociceptive nerves demonstrated the greatest degree of nerve expansion in an NGF-dependent manner. Neural tracing identified CGRP+ peptidergic neurons as the primary gastric sensory neurons. Three-dimensional co-culture models showed that sensory neurons directly connect with gastric cancer spheroids. Chemogenetic activation of sensory neurons induced the release of calcium into the cytoplasm of cancer cells, promoting tumour growth and metastasis. Pharmacological ablation of sensory neurons or treatment with CGRP inhibitors suppressed tumour growth and extended survival. Depolarization of gastric tumour membranes through in vivo optogenetic activation led to enhanced calcium flux in jugular nucleus complex and CGRP release, defining a cancer cell-peptidergic neuronal circuit. Together, these findings establish the functional connectivity between cancer and sensory neurons, identifying this pathway as a potential therapeutic target.

Cancer cells have been shown to exploit neurons to modulate their survival and growth, including through establishment of neural circuits within the central nervous system (CNS) 1-3 . Here, we report a distinct pattern of cancer-nerve interactions between the peripheral nervous system (PNS) and gastric cancer (GC). In multiple GC mouse models, nociceptive nerves demonstrated the greatest degree of nerve expansion in an NGF-dependent manner. Neural tracing identified CGRP+ peptidergic neurons as the primary gastric sensory neurons. Three-dimensional co-culture models showed that sensory neurons directly connect with gastric cancer spheroids through synapse-like structures. Chemogenetic activation of sensory neurons induced the release of calcium into the cytoplasm of cancer cells, promoting tumor growth and metastasis. Pharmacological ablation of sensory neurons or treatment with CGRP inhibitors suppressed tumor growth and extended survival. Depolarization of gastric tumor membranes through in vivo optogenetic activation led to enhanced calcium flux in nodose ganglia and CGRP release, defining a cancer cell-peptidergic neuronal circuit. Together, these findings establish the functional connectivity between cancer and sensory neurons, identifying this pathway as a potential therapeutic target.

Biomarkers associated with the progression from gastric intestinal metaplasia (GIM) to gastric adenocarcinoma (GA), i.e., GA-related GIM, could provide valuable insights into identifying patients with increased risk for GA. The aim of this study was to utilize multi-bioinformatics to reveal potential biomarkers for the GA-related GIM and predict potential drug repurposing for GA prevention in patients. The multi-bioinformatics included gene expression matrix (GEM) by microarray gene expression (MGE), ScType (a fully automated and ultra-fast cell-type identification based solely on a given scRNA-seq data), Ingenuity Pathway Analysis, PageRank centrality, GO and MSigDB enrichments, Cytoscape, Human Protein Atlas and molecular docking analysis in combination with immunohistochemistry. To identify GA-related GIM, paired surgical biopsies were collected from 16 GIM-GA patients who underwent gastrectomy, yielding 64 samples (4 biopsies per stomach x 16 patients) for MGE. Co-analysis was performed by including scRNAseq and immunohistochemistry datasets of endoscopic biopsies of 37 patients. The results of the present study showed potential biomarkers for GA-related GIM, including GEM of individual patients, individual genes (such as RBP2 and CD44), signaling pathways, network of molecules, and network of signaling pathways with key topological nodes. Accordingly, potential treatment targets with repurposed drugs were identified including epidermal growth factor receptor, proto-oncogene tyrosine-protein kinase Src, paxillin, transcription factor Jun, breast cancer type 1 susceptibility protein, cellular tumor antigen p53, mouse double minute 2, and CD44.

The physiology of gastric acid secretion is one of the earliest subjects in medical literature and has been continuously studied since 1833. Starting with the notion that neural stimulation alone drives acid secretion, progress in understanding the physiology and pathophysiology of this process has led to the development of therapeutic strategies for patients with acid-related diseases. For instance, understanding the physiology of parietal cells led to the developments of histamine 2 receptor blockers, proton pump inhibitors (PPIs), and recently, potassium-competitive acid blockers. Furthermore, understanding the physiology and pathophysiology of gastrin has led to the development of gastrin/CCK2 receptor (CCK2 R) antagonists. The need for refinement of existing drugs in patients have led to second and third generation drugs with better efficacy at blocking acid secretion. Further understanding of the mechanism of acid secretion by gene targeting in mice has enabled us to dissect the unique role for each regulator to leverage and justify the development of new targeted therapeutics for acid-related disorders. Further research on the mechanism of stimulation of gastric acid secretion and the physiological significances of gastric acidity in gut microbiome is needed in the future.

OBJECTIVE:Identify whether there were gaps between needs of end-users and interests of researchers focusing on pancreatic cancer. METHODS:A questionnaire for end-users (patients, close family, others) and researchers was developed to measure value from the perspective of different stakeholder groups. Two separate literature analyses were conducted to assess the prevalence and impact of patient and public involvement (PPI). RESULTS:Significant gaps were found between end-users and researchers in valuing basic research (15 vs 25 points, p = 0.005) and treatment (36 vs. 26 points, p = 0.015), but not in early diagnosis, risk factors, or quality of life. PPI was absent from the top 100 cited publications on pancreatic cancer research and was featured in 0.1% of all studies within the field. CONCLUSIONS:Gaps existed between needs of end-users and interests of researchers on basic research and treatment. PPI constituted an insignificant part of the overall pancreatic cancer research literature and had negligible impact in terms of citations. PRACTICAL IMPLICATIONS:To help close the gaps, PPI should be incorporated throughout the research process. The impact of PPI can be enhanced by prestigious journals in consideration of journal policies and encouragements and by dissemination at academic conferences.

This brief communication presented a dissertation of PhD thesis on translational research using state-of-the-art methods of multi-disciplinary integrations between basic and clinical research and between dry- (computational) and wet- (experimental and clinical) investigations. The findings showed possible causal association between neural innervation and tumorigenesis of gastric cancer via Wnt signaling and metabolic reprogramming within the tumor microenvironment. Accordingly, selective vagotomy, Botulinum neurotoxin type A (injection into the tumor areas), RAD001 (also known as Everolimus), CPI-613 (devimistat) and ivermectin were found to be potential for treatment of gastric cancer. The assessment showed that this translational research approach guaranteed the efficient development of novel knowledge in fundamental medical sciences, and that the identification of the role of vagal innervation and the possibilities of its modulation during gastric tumorigenesis represented valuable contributions to the fields of gastroenterology and cancer research. Possible roles of angiogenesis vs neurogenesis and brain-gut axis would be worth exploring in further research.

EDITORIAL article Front. Pharmacol., 20 December 2022Sec. Gastrointestinal and Hepatic Pharmacology Volume 13 - 2022 | https://doi.org/10.3389/fphar.2022.1116643

Objective: The aim of the present study was repositioning of ivermectin in treatment of gastric cancer (GC) by computational prediction based on gene expression profiles of human and mouse model of GC and validations with in silico, in vitro and in vivo approaches. Methods: Computational drug repositioning was performed using connectivity map (cMap) and data/pathway mining with the Ingenuity Knowledge Base. Tissue samples of GC were collected from 16 patients and 57 mice for gene expression profiling. Additional seven independent datasets of gene expression of human GC from the TCGA database were used for validation. In silico testing was performed by constructing interaction networks of ivermectin and the downstream effects in targeted signaling pathways. In vitro testing was carried out in human GC cell lines (MKN74 and KATO-III). In vivo testing was performed in a transgenic mouse model of GC (INS-GAS mice). Results: GC gene expression “signature” and data/pathway mining but not cMAP revealed nine molecular targets of ivermectin in both human and mouse GC associated with WNT/β-catenin signaling as well as cell proliferation pathways. In silico inhibition of the targets of ivermectin and concomitant activation of ivermectin led to the inhibition of WNT/β-catenin signaling pathway in “dose-depended” manner. In vitro, ivermectin inhibited cell proliferation in time- and concentration-depended manners, and cells were arrested in the G1 phase at IC50 and shifted to S phase arrest at >IC50. In vivo, ivermectin reduced the tumor size which was associated with inactivation of WNT/β-catenin signaling and cell proliferation pathways and activation of cell death signaling pathways. Conclusion: Ivermectin could be recognized as a repositioning candidate in treatment of gastric cancer.

Tumors comprise cancer cells and the associated stromal and immune/inflammatory cells, i.e., tumor microenvironment (TME). Here, we identify a metabolic signature of human and mouse model of gastric cancer and show that vagotomy in the mouse model reverses the metabolic reprogramming, reflected by metabolic switch from glutaminolysis to OXPHOS/glycolysis and normalization of the energy metabolism in cancer cells and TME. We next identify and validate SNAP25, mTOR, PDP1/α-KGDH, and glutaminolysis as drug targets and accordingly propose a therapeutic strategy to target the nerve-cancer metabolism. We demonstrate the efficacy of nerve-cancer metabolism therapy by intratumoral injection of BoNT-A (SNAP25 inhibitor) with systemic administration of RAD001 and CPI-613 but not cytotoxic drugs on overall survival in mice and show the feasibility in patients. These findings point to the importance of neural signaling in modulating the tumor metabolism and provide a rational basis for clinical translation of the potential strategy for gastric cancer.

Naturally occurring isothiocyanates (ITCs) from edible vegetables have shown potential as chemopreventive agents against several types of cancer. The aims of the present study were to study the potential of ITCs in chemoprevention and in potentiating the efficacy of cytotoxic drugs in gastric cancer treatment. The chemoprevention was studied in chemically induced mouse model of gastric cancer, namely N-methyl-N-nitrosourea (MNU) in drinking water, and in a genetically engineered mouse model of gastric cancer (the so-called INS-GAS mice). The pharmacological effects of ITCs with or without cisplatin were studied in human gastric cell lines MKN45, AGS, MKN74 and KATO-III, which were derived from either intestinal or diffused types of gastric carcinoma. The results showed that dietary phenethyl isothiocyanate (PEITC) reduced the tumor size when PEITC was given simultaneously with MNU, but neither when administrated after MNU nor in INS-GAS mice. Treatments of gastric cancer cells with ITCs resulted in a time- and concentration-dependent inhibition on cell proliferation. Pretreatment of gastric cancer cells with ITCs enhanced the inhibitory effects of cisplatin (but not 5-fluorouracil) in time- and concentration-dependent manners. Treatments of gastric cancer cells with PEITC plus cisplatin simultaneously at different concentrations of either PEITC or cisplatin exhibited neither additive nor synergetic inhibitory effect. Furthermore, PEITC depleted glutathione and induced G2/M cell cycle arrest in gastric cancer cells. In conclusion, the results of the present study showed that PEITC displayed anti-cancer effects, particularly when given before the tumor initiation, suggesting a chemopreventive effect in gastric cancer, and that pretreatment of PEITC potentiated the anti-cancer effects of cisplatin, possibly by reducing the intracellular pool of glutathione, suggesting a possible combination strategy of chemotherapy with pretreatment with PEITC.

Recently, there has been a resurgence in regulatory peptide science as a result of three converging trends. The first is the increasing population of the drug pipeline with peptide‐based therapeutics, mainly in, but not restricted to, incretin‐like molecules for treatment of metabolic disorders such as diabetes. The second is the development of genetic and optogenetic tools enabling new insights into how peptides actually function within brain and peripheral circuits to accomplish homeostatic and allostatic regulation. The third is the explosion in defined structures of the G‐protein coupled receptors to which most regulatory peptides bind and exert their actions. These trends have closely wedded basic systems biology to drug discovery and development, creating a “two‐way street” on which translational advances travel from basic research to the clinic, and, equally importantly, “reverse‐translational” information is gathered, about the molecular, cellular and circuit‐level mechanisms of action of regulatory peptides, comprising information required for the fine‐tuning of drug development through testing in animal models. This review focuses on a small group of ‘influential’ peptides, including oxytocin, vasopressin, pituitary adenylate cyclase‐activating polypeptide, ghrelin, relaxin‐3 and glucagon‐like peptide‐1, and how basic discoveries and their application to therapeutics have intertwined over the past decade.

Recently, there has been a resurgence in regulatory peptide science as a result of three converging trends. The first is the increasing population of the drug pipeline with peptide-based therapeutics, mainly in, but not restricted to, incretin-like molecules for treatment of metabolic disorders such as diabetes. The second is the development of genetic and optogenetic tools enabling new insights into how peptides actually function within brain and peripheral circuits to accomplish homeostatic and allostatic regulation. The third is the explosion in defined structures of the G-protein coupled receptors to which most regulatory peptides bind and exert their actions. These trends have closely wedded basic systems biology to drug discovery and development, creating a "two-way street" on which translational advances travel from basic research to the clinic, and, equally importantly, "reverse-translational" information is gathered, about the molecular, cellular and circuit-level mechanisms of action of regulatory peptides, comprising information required for the fine-tuning of drug development through testing in animal models. This review focuses on a small group of 'influential' peptides, including oxytocin, vasopressin, pituitary adenylate cyclase-activating polypeptide, ghrelin, relaxin-3 and glucagon-like peptide-1, and how basic discoveries and their application to therapeutics have intertwined over the past decade.