Effects of Rituximab on JAK-STAT and NF-κB signaling pathways in acute lymphoblastic leukemia and chronic lymphocytic leukemia

Dalmizrak, Ayşegül; Günel, Nur Selvi; Kaymaz, Burçin Tezcanlı; Şahin, Fahri; Saydam, Güray; Kosova, Buket

doi:10.1515/tjb-2018-0321

Cited by 3 publications

(2 citation statements)

References 43 publications

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“…We first calculated the size of the original unperturbed network. Then the effects of the following drugs (respective targets), and their combinations, commonly used in RA were tested: methotrexate (STAT 1 (hsa6772) and STAT 5 (hsa6776)), prednisolone (interleukin 2 receptor subunit alpha (has 3559), JAK3 (hsa3718)), rituximab (STAT3 (hsa6774)), tocilizumab (interleukin-6 receptor (hsa3570)), tofacitinib (JAK1 (hsa3716), hsa3718) and baricitinib (hsa3716, JAK2 (hsa3717)) 15 – 17 . Following viral systems were also tested for their ability to evade the immune system through interference with the JAK/STAT pathway: Measles: interferon alpha receptor 1 (hsa3454), hsa6772; Influenza A: hsa3454, hsa6774; hsa3454, hsa6772, interferon gamma receptors 1 and 2 (hsa3459, hsa3460); West Nile virus (WNV), Japanese B virus (JBV) and Yellow Fever virus (YFV): hsa6772; dengue virus: hsa6772, STAT2 (has 6773); respiratory syncytial virus (RSV): Tyk2 (hsa7297), CREB binding protein (hsa1387), hsa6772, hsa6773; Kaposi’s sarcoma virus (KSV): hsa3716, hsa7297, hsa6773; Hepatitis B and C virus (HBV and HCV): hsa3716, hsa7297, hsa6772); cytomegalovirus (CMV): hsa6772, interferon regulatory factor 9 (hsa10379); Hendra and Nipah virus (HV and NV): hsa6772, hsa6773; Coronavirus: hsa3454, hsa6772, hsa6773 18 .…”

Section: Methodsmentioning

confidence: 99%

Network theoretic analysis of JAK/STAT pathway and extrapolation to drugs and viruses including COVID-19

Banerjee

Goswami

Chatterjee

2021

Sci Rep

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Whenever some phenomenon can be represented as a graph or a network it seems pertinent to explore how much the mathematical properties of that network impact the phenomenon. In this study we explore the same philosophy in the context of immunology. Our objective was to assess the correlation of “size” (number of edges and minimum vertex cover) of the JAK/STAT network with treatment effect in rheumatoid arthritis (RA), phenotype of viral infection and effect of immunosuppressive agents on a system infected with the coronavirus. We extracted the JAK/STAT pathway from Kyoto Encyclopedia of Genes and Genomes (KEGG, hsa04630). The effects of the following drugs, and their combinations, commonly used in RA were tested: methotrexate, prednisolone, rituximab, tocilizumab, tofacitinib and baricitinib. Following viral systems were also tested for their ability to evade the JAK/STAT pathway: Measles, Influenza A, West Nile virus, Japanese B virus, Yellow Fever virus, respiratory syncytial virus, Kaposi’s sarcoma virus, Hepatitis B and C virus, cytomegalovirus, Hendra and Nipah virus and Coronavirus. Good correlation of edges and minimum vertex cover with clinical efficacy were observed (for edge, rho = − 0.815, R2 = 0.676, p = 0.007, for vertex cover rho = − 0.793, R2 = 0.635, p = 0.011). In the viral systems both edges and vertex cover were associated with acuteness of viral infections. In the JAK/STAT system already infected with coronavirus, maximum reduction in size was achieved with baricitinib. To conclude, algebraic and combinatorial invariant of a network may explain its biological behaviour. At least theoretically, baricitinib may be an attractive target for treatment of coronavirus infection.

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Section: Methodsmentioning

confidence: 99%

Network theoretic analysis of JAK/STAT pathway and extrapolation to drugs and viruses including COVID-19

Banerjee

Goswami

Chatterjee

2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Then the effects of the following drugs (respective targets), and their combinations, commonly used in RA were tested: methotrexate (STAT 1 (hsa6772) and STAT 5 (hsa6776)), prednisolone (interleukin 2 receptor subunit alpha (has 3559), JAK3 (hsa3718)), rituximab (STAT3 (hsa6774)), tocilizumab (interleukin-6 receptor (hsa3570)), tofacitinib (JAK1 (hsa3716), hsa3718) and baricitinib (hsa3716, JAK2 (hsa3717)). [12][13][14] Following viral systems were also tested for their ability to evade the immune system through interference with the JAK/STAT pathway: Measles: interferon alpha receptor 1 (hsa3454), hsa6772; Influenza A: hsa3454, hsa6774; hsa3454, hsa6772, interferon gamma receptors 1 and 2 (hsa3459, hsa3460); West Nile virus (WNV), Japanese B virus (JBV) and Yellow Fever virus (YFV): hsa6772; dengue virus: hsa6772, STAT2 (has 6773); respiratory syncytial virus (RSV): Tyk2 (hsa7297), CREB binding protein (hsa1387), hsa6772, hsa6773; Kaposi's sarcoma virus (KSV):…”

Section: Methodsmentioning

confidence: 99%

Network theoretic analysis of JAK/STAT pathway and extrapolation to drugs and viruses including COVID-19

Banerjee

Goswami

Chatterjee

2020

Preprint

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Whenever some phenomenon can be represented as a graph or a network it seems pertinent to explore how much the mathematical properties of that network impact the phenomenon. In this study we explore the same philosophy in the context of immunology. Our objective was to assess the correlation of “size” (number of edges and minimum vertex cover) of the JAK/STAT network with treatment effect in rheumatoid arthritis (RA), phenotype of viral infection and effect of immunosuppressive agents on a system infected with the coronavirus. We extracted the JAK/STAT pathway from Kyoto Encyclopedia of Genes and Genomes (KEGG, hsa04630). The effects of the following drugs, and their combinations, commonly used in RA were tested: methotrexate, prednisolone, rituximab, tocilizumab, tofacitinib and baricitinib. Following viral systems were also tested for their ability to evade the JAK/STAT pathway: Measles, Influenza A, West Nile virus, Japanese B virus, Yellow Fever virus, respiratory syncytial virus, Kaposi’s sarcoma virus, Hepatitis B and C virus, cytomegalovirus, Hendra and Nipah virus and Coronavirus. Good correlation of edges and minimum vertex cover with clinical efficacy were observed (for edge, rho= -0.815, R2= 0.676, p=0.007, for vertex cover rho= -0.793, R2= 0.635, p=0.011). In the viral systems both edges and vertex cover were associated with acuteness of viral infections. In the JAK/STAT system already infected with coronavirus, maximum reduction in size was achieved with baricitinib. To conclude, algebraic and combinatorial invariant of a network may explain its biological behaviour. At least theoretically, baricitinib may be an attractive target for treatment of coronavirus infection.

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The effect of specific therapeutic agents on inflammation in sepsis-induced neonatal rats

İlhan

Gül

Susam

et al. 2019

Turkish Journal of Biochemistry

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Objective The aim of this study was to investigate the effect of Thalidomide and Etanercept on inflammation parameters in a neonatal rat sepsis model induced with Lipopolysaccharide (LPS). Materials and methods Four-week-old male Wistar Albino rats were used in the experiment. LPS (5 mg/kg) was administered to rats as sepsis-inducing agent and two anti-inflammatory drugs, Thalidomide and Etanercept were given intraperitoneally as chemotherapeutic agents. The septic neonatal rats were treated with Thalidomide (0.5 mg/kg), Etanercept (1 mg/kg), and a combination of the two. All therapeutic agents were injected half an hour after injecting LPS. It took 24 h to perform the entire experiment. Whereupon, liver tissues of the animals were removed, presepsin of liver tissue and NF-κB levels were measured by ELISA analysis and NF-κB protein expression levels were determined by Western blotting. Results A significant increase was detected in presepsin and NF-κB levels in LPS group compared to sham and treatment groups. In Western Blot evaluations, there was a significant decrease in the expression of NF-κB protein in treatment groups compared to sepsis group. Conclusions It was observed that Thalidomide and Etanercept had potential effects on the treatment of neonatal sepsis.

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Effects of Rituximab on JAK-STAT and NF-κB signaling pathways in acute lymphoblastic leukemia and chronic lymphocytic leukemia

Cited by 3 publications

References 43 publications

Network theoretic analysis of JAK/STAT pathway and extrapolation to drugs and viruses including COVID-19

Network theoretic analysis of JAK/STAT pathway and extrapolation to drugs and viruses including COVID-19

Network theoretic analysis of JAK/STAT pathway and extrapolation to drugs and viruses including COVID-19

The effect of specific therapeutic agents on inflammation in sepsis-induced neonatal rats

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