ArticleCancer science2021
Forecasting sensitive targets of the kynurenine pathway in pancreatic adenocarcinoma using mathematical modeling.
Article in Cancer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- GPR35-mediated metabolic reprogramming promotes tumorigenesis in digestive cancers.Frontiers in immunology · 2025Review
- Recent advances in GPR35 pharmacology; 5-HIAA serotonin metabolite becomes a ligand.Archives of pharmacal research · 2023Review
- Mathematical modeling and application of IL-1β/TNF signaling pathway in regulating chondrocyte apoptosis.Frontiers in cell and developmental biology · 2023Article
- Forecasting sensitive targets of the kynurenine pathway in pancreatic adenocarcinoma using mathematical modeling.Cancer science · 2021Article
- Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States.Frontiers in public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
In this study, a new mathematical model was established and validated to forecast and define sensitive targets in the kynurenine pathway (Kynp) in pancreatic adenocarcinoma (PDAC). Using the Panc-1 cell line, genetic profiles of Kynp molecules were tested. qPCR data were implemented in the algorithm programming (fmincon and lsqnonlin function) to estimate 35 parameters of Kynp variables by Matlab 2017b. All tested parameters were defined as non-negative and bounded. Then, based on experimental data, the function of the fmincon equation was employed to estimate the approximate range of each parameter. These calculations were confirmed by qPCR and Western blot. The correlation coefficient (R) between model simulation and experimental data (72 hours, in intervals of 6 hours) of every variable was >0.988. The analysis of reliability and predictive accuracy depending on qPCR and Western blot data showed high predictive accuracy of the model; R was >0.988. Using the model calculations, kynurenine (x3, a6), GPR35 (x4, a8), NF-kβp105 (x7, a16), and NF-kβp65 (x8, a18) were recognized as sensitive targets in the Kynp. These predicted targets were confirmed by testing gene and protein expression responses. Therefore, this study provides new interdisciplinary evidence for Kynp-sensitive targets in the treatment of PDAC.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.