Octreotide Nanoparticles Showed Affinity for In Vivo MIA Paca-2 Inducted Pancreas Ductal Adenocarcinoma Mimicking Pancreatic Polypeptide-Secreting Tumor of the Distal Pancreas (PPoma)

Braga, Thaís Gleice Martins; Pinto, Suyene Rocha; Reis, Sara Rhaissa Rezende dos; Portilho, Filipe Leal; Silva, Aline Oliveira da; Bernardes, Emerson Soares; Santos, Sofia Nascimento dos; Alencar, Luciana Magalhães Rebêlo; Ricci-Júnior, Eduardo; Santos-Oliveira, Ralph

doi:10.1007/s11095-019-2678-4

Cited by 10 publications

(5 citation statements)

References 47 publications

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“…Recent studies highlight the affinity of Octreotide nanoparticles for in vivo induction of pancreas ductal adenocarcinoma using MIA Paca-2, indicating its potential utility in targeted therapy for pancreatic cancer. [121], [178], [187], [188] Leucovorin, classified as a folic acid analog, shares similarities with the vitamin folic acid, crucial for new cell production and maintenance. When combined with specific chemotherapy drugs, Leucovorin enhances their efficacy in eradicating cancer cells or mitigating adverse side effects.…”

Section: Other Treatment Strategymentioning

confidence: 99%

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Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN Protocol

Parichehreh,

Kiaei,

Boush

et al. 2024

Preprint

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BackgroundMalignant neoplasm of the pancreas (MNP), a highly lethal illness with bleak outlook and few therapeutic avenues, entails numerous cellular transformations. These include irregular proliferation of ductal cells, activation of stellate cells, initiation of epithelial-to-mesenchymal transition, and changes in cell shape, movement, and attachment. Discovering potent drug cocktails capable of addressing the genetic and protein factors underlying pancreatic cancer’s development is formidable due to the disease’s intricate and varied nature.MethodIn this study, we introduce a fresh model utilizing Graph Attention Networks (GATs) to pinpoint potential drug pairings with synergistic effects for MNP, following the RAIN protocol. This protocol comprises three primary stages: Initially, employing Graph Neural Network (GNN) to suggest drug combinations for disease management by acquiring embedding vectors of drugs and proteins from a diverse knowledge graph encompassing various biomedical data types, such as drug-protein interactions, gene expression, and drug-target interactions. Subsequently, leveraging natural language processing to gather pertinent articles from clinical trials incorporating the previously recommended drugs. Finally, conducting network meta-analysis to assess the relative effectiveness of these drug combinations.ResultWe implemented our approach on a network dataset featuring drugs and genes as nodes, connected by edges representing their respective p-values. Our GAT model identified Gemcitabine, Pancrelipase Amylase, and Octreotide as the optimal drug combination for targeting the human genes/proteins associated with this cancer. Subsequent scrutiny of clinical trials and literature confirmed the validity of our findings. Additionally, network meta-analysis confirmed the efficacy of these medications concerning the pertinent genes.ConclusionBy employing GAT within the RAIN protocol, our approach represents a novel and efficient method for recommending prominent drug combinations to target proteins/genes associated with pancreatic cancer. This technique has the potential to aid healthcare professionals and researchers in identifying optimal treatments for patients while also unveiling underlying disease mechanisms.HighlightsGraph Attention Networks (GATs) used to recommend drug combinations for pancreatic cancerRAIN protocol applied to extract relevant information from clinical trials and literatureGemcitabine, Pancrelipase Amylase, and Octreotide identified as optimal drug combinationNetwork meta-analysis confirmed the effectiveness of the drug combination on gene targetsNovel and efficient method for drug discovery and disease mechanism elucidationAbstract Figure

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Section: Other Treatment Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN Protocol

Parichehreh,

Kiaei,

Boush

et al. 2024

Preprint

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“…It is reported MST1/2 is involved in Treg cells [ 37 ] to maintain the balance between the activation and the tolerance of the immune [ 48 ], which affects the autoimmune inflammation and the normal immune function [ 14 , 29 ]. In addition, MST1 improves the differentiation and the function of Treg cells [ 14 ] by regulating the activities of Forkhead box o1/3 (Foxo1/3) [ 2 ], Sirt1 [ 50 ], TEAD1 [ 51 ], and Akt [ 14 ], meanwhile maintains the immune tolerance [ 29 ] by regulating the activation of STAT5 [ 52 , 53 ]. MST1 directly or indirectly enhances the stability of Foxo1/3 by phosphorylating Foxo1/3 or inhibiting activity of Akt mediated by antigen-specific T cell antibody (TCR) in the peripheral T cells, thereby increasing the expression of Foxp3 in the mice to regulate Treg cells [ 14 ].…”

Section: Structure and Function Of Mst1/2mentioning

confidence: 99%

MST1/2 in inflammation and immunity

Li,

Wen,

et al. 2023

Cell Adhesion & Migration

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The mammalian Sterile 20-like kinase 1/2 (MST1/2) belongs to the serine/threonine (GC) protein kinase superfamily. Collective studies confirm the vital role MST1/2 in inflammation and immunity. MST1/2 is closely related to the progress of inflammation. Generally, MST1/2 aggravates the inflammatory injury through MST1-JNK, MST1-mROS, MST1-Foxo3, and NF-κB pathways, as well as several regulatory factors such as tumor necrosis factor-α (TNF-α), mitochondrial extension factor 1 (MIEF1), and lipopolysaccharide (LPS). Moreover, MST1/2 is also involved in the regulation of immunity to balance immune activation and tolerance by regulating MST1/2-Rac, MST1-Akt1/c-myc, MST1-Foxos, MST1-STAT, Btk pathways, and lymphocyte function-related antigen 1 (LFA-1), which subsequently prevents immunodeficiency syndrome and autoimmune diseases. This article reviews the effects of MST1/2 on inflammation and immunity.

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“…The radiolabelling of the NPs with a direct method can also be performed with a short incubation between SnCl 2 and the NPs, followed by the addition of 99m Tc in the solution. This method was used to radiolabel several types of NPs: octreotide NPs, cerium oxide NPs (CeO 2 -NPs), mesoporous silica NPs, poly-γ-glutamic acid NPs conjugated with folic acid, carbon-based mesoporous NPs, zirconium NPs, serum albumin nanoparticles, polymeric NPs, and dendrimer glycoconjugate [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ]. All the studies showed a high final LE, but the formation of radiocolloids often requires further purification of the solution.…”

Section: Radiolabelling Of Nps For Spect Imagingmentioning

confidence: 99%

Methods for Radiolabelling Nanoparticles: SPECT Use (Part 1)

et al. 2022

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The use of nanoparticles (NPs) is rapidly increasing in nuclear medicine for diagnostic and therapeutic purposes. Their wide use is due to their chemical–physical characteristics and possibility to deliver several molecules. NPs can be synthetised by organic and/or inorganic materials and they can have different size, shape, chemical composition, and char. These factors influence their biodistribution, clearance, and targeting ability in vivo. NPs can be designed to encapsulate inside the core or bind to the surface on several molecules, including radionuclides, for different clinical applications. Either diagnostic or therapeutic radioactive NPs can be synthetised, making a so-called theragnostic tool. To date, there are several methods for radiolabelling NPs that vary depending on both the physical and chemical properties of the NPs and on the isotope used. In this review, we analysed and compared different methods for radiolabelling NPs for single-photon emission computed tomography (SPECT) use.

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Octreotide Nanoparticles Showed Affinity for In Vivo MIA Paca-2 Inducted Pancreas Ductal Adenocarcinoma Mimicking Pancreatic Polypeptide-Secreting Tumor of the Distal Pancreas (PPoma)

Cited by 10 publications

References 47 publications

Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN Protocol

Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN Protocol

MST1/2 in inflammation and immunity

Methods for Radiolabelling Nanoparticles: SPECT Use (Part 1)

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