Figure 1.
SAM/SAH measurements (a) Levels of SAM and SAH (ng/mL) and their ratio (b) SAM/SAH in the lysates of AHCY-silenced and control cells, as measured by LC-MS/MS. ±SD is represented as vertical line and is based on three independent measurements. Statistical significance was analyzed using Student’s t tests at a * p < 0.05.
Figure 1.
SAM/SAH measurements (a) Levels of SAM and SAH (ng/mL) and their ratio (b) SAM/SAH in the lysates of AHCY-silenced and control cells, as measured by LC-MS/MS. ±SD is represented as vertical line and is based on three independent measurements. Statistical significance was analyzed using Student’s t tests at a * p < 0.05.
Figure 2.
Wnt Signaling pathway. The diagram provides an overview of the major components and interactions within the Wnt signaling pathway such as LEF1 and TCF/LEF1 complex. The color assignments in IPA are based on statistical analyses, such as the z-score. The z-score compares the observed gene expression changes in a given dataset to a reference dataset, assessing the significance and direction of those changes. Positive z-scores indicate upregulation = red, orange = activated, whereas negative z-scores indicate downregulation = green, blue = inhibited, and z-scores close to zero indicate no significant change = no color, and purple indicates interactions of two or more factors. The color scheme employed in this figure is consistent with the color scheme utilized in all presented figures.
Figure 2.
Wnt Signaling pathway. The diagram provides an overview of the major components and interactions within the Wnt signaling pathway such as LEF1 and TCF/LEF1 complex. The color assignments in IPA are based on statistical analyses, such as the z-score. The z-score compares the observed gene expression changes in a given dataset to a reference dataset, assessing the significance and direction of those changes. Positive z-scores indicate upregulation = red, orange = activated, whereas negative z-scores indicate downregulation = green, blue = inhibited, and z-scores close to zero indicate no significant change = no color, and purple indicates interactions of two or more factors. The color scheme employed in this figure is consistent with the color scheme utilized in all presented figures.
Figure 3.
IPA core analysis of the regulation of the Epithelial-Mesenchymal Transition Pathway in SW480 AHCY deficient cells, revealing the involvement of LEF1, a functional transcription factor forming part of the TCF/LEF complex, thereby exerting regulatory control over the expression of genes crucial for EMT.
Figure 3.
IPA core analysis of the regulation of the Epithelial-Mesenchymal Transition Pathway in SW480 AHCY deficient cells, revealing the involvement of LEF1, a functional transcription factor forming part of the TCF/LEF complex, thereby exerting regulatory control over the expression of genes crucial for EMT.
Figure 4.
IPA Core analysis of the Epithelial Adherens Junctions Signaling in SW480 AHCY deficient cells with increased expression of LEF1 protein. The accompanying
Table 5 provides valuable insights into the transcriptional alterations observed in pivotal genes associated with epithelial adherens junctions signaling following differential expression analysis such as: CDH1, CDH2, TCF/LEF1. Notably, there are changes in gene expression observed in the TCF/LEF complex, mirroring the patterns seen in the Wnt signaling pathway and the regulation of the epithelial-mesenchymal transition pathway.
Figure 4.
IPA Core analysis of the Epithelial Adherens Junctions Signaling in SW480 AHCY deficient cells with increased expression of LEF1 protein. The accompanying
Table 5 provides valuable insights into the transcriptional alterations observed in pivotal genes associated with epithelial adherens junctions signaling following differential expression analysis such as: CDH1, CDH2, TCF/LEF1. Notably, there are changes in gene expression observed in the TCF/LEF complex, mirroring the patterns seen in the Wnt signaling pathway and the regulation of the epithelial-mesenchymal transition pathway.
Figure 5.
IPA Core analysis of Differential Expression of Cyclins and Cell Cycle Regulation Signaling in SW480 AHCY deficient cells with increased expression of LEF1 protein. Notably, the transcript levels of Cyclin A, Cyclin B, and CDK1 were found to be significantly activated, indicating a potential modulation of cell cycle dynamics in response to AHCY deficiency. Cyclin B, in collaboration with CDK1, orchestrates the transition from the G2 phase to the mitotic phase, enabling successful cell division. The heightened expression of Cyclin B and CDK1 implies an augmented drive toward mitosis, possibly reflecting a compensatory mechanism triggered by AHCY deficiency.
Figure 5.
IPA Core analysis of Differential Expression of Cyclins and Cell Cycle Regulation Signaling in SW480 AHCY deficient cells with increased expression of LEF1 protein. Notably, the transcript levels of Cyclin A, Cyclin B, and CDK1 were found to be significantly activated, indicating a potential modulation of cell cycle dynamics in response to AHCY deficiency. Cyclin B, in collaboration with CDK1, orchestrates the transition from the G2 phase to the mitotic phase, enabling successful cell division. The heightened expression of Cyclin B and CDK1 implies an augmented drive toward mitosis, possibly reflecting a compensatory mechanism triggered by AHCY deficiency.
Figure 6.
MYC network; IPA Analysis indicates MYC dependent regulation of several proteins including, AHCY, SOX5, SON, OLR1, LGR5, and COL4A1, which expression levels were found to be significantly associated with MYC activity, indicating MYC as a potential master regulator.
Figure 6.
MYC network; IPA Analysis indicates MYC dependent regulation of several proteins including, AHCY, SOX5, SON, OLR1, LGR5, and COL4A1, which expression levels were found to be significantly associated with MYC activity, indicating MYC as a potential master regulator.
Figure 7.
STAT3 Signaling in SW480 AHCY deficient cells. The figure summarizes the upregulation and activation of STAT3, MYC, CDC25A, and BCL2, highlighting potential implications for cellular responses and signaling crosstalk.
Figure 7.
STAT3 Signaling in SW480 AHCY deficient cells. The figure summarizes the upregulation and activation of STAT3, MYC, CDC25A, and BCL2, highlighting potential implications for cellular responses and signaling crosstalk.
Figure 8.
IPA Core analysis of the Tumor Microenvironment Pathway in SW480 AHCY deficient cells with increased expression of LEF1 protein.
Figure 8.
IPA Core analysis of the Tumor Microenvironment Pathway in SW480 AHCY deficient cells with increased expression of LEF1 protein.
Figure 9.
Human Embryonic Stem Cell Pluripotency Signaling. STAT3 plays a critical role in regulating the self-renewal and proliferation of embryonic stem cells (ESCs). The figure illustrates the involvement of STAT3 in maintaining the pluripotent state of ESCs and promoting their proliferation, highlighting key downstream effectors and signaling pathways.
Figure 9.
Human Embryonic Stem Cell Pluripotency Signaling. STAT3 plays a critical role in regulating the self-renewal and proliferation of embryonic stem cells (ESCs). The figure illustrates the involvement of STAT3 in maintaining the pluripotent state of ESCs and promoting their proliferation, highlighting key downstream effectors and signaling pathways.
Figure 10.
IPA Core analysis of signaling by Rho Family GTPases in SW480 AHCY deficient cells with increased expression of LEF1 protein. The figure depicts the increased activation of cytoskeletal reorganization, cell trafficking, and migration/invasion-related processes in response to AHCY deficiency and increased levels of LEF1 protein. Rho GTPases, including Rho, PIP5K, and ROCK, are shown as key regulators of cytoskeletal dynamics.
Figure 10.
IPA Core analysis of signaling by Rho Family GTPases in SW480 AHCY deficient cells with increased expression of LEF1 protein. The figure depicts the increased activation of cytoskeletal reorganization, cell trafficking, and migration/invasion-related processes in response to AHCY deficiency and increased levels of LEF1 protein. Rho GTPases, including Rho, PIP5K, and ROCK, are shown as key regulators of cytoskeletal dynamics.
Figure 11.
Integration of Differential Gene Expression, LEF1 Protein Levels, Wnt Signaling, and Cellular Responses in AHCY-deficient SW480 Cells. Differential gene expression analysis in AHCY-deficient SW480 cells revealed significant alterations in genes associated with tumor cell invasion. TGFβ1, ROAR, DAB2, BMP6, NOS2, PLXN2, and CADPS exhibited significant upregulation, while TCF4 and AHCY were significantly downregulated. These gene expression changes were connected with increased LEF1 protein levels, activated Wnt signaling, and potential implications for enhanced cell invasion and proliferation through the upregulation of Cyclin A and Cyclin B. Top of FormBottom of Form.
Figure 11.
Integration of Differential Gene Expression, LEF1 Protein Levels, Wnt Signaling, and Cellular Responses in AHCY-deficient SW480 Cells. Differential gene expression analysis in AHCY-deficient SW480 cells revealed significant alterations in genes associated with tumor cell invasion. TGFβ1, ROAR, DAB2, BMP6, NOS2, PLXN2, and CADPS exhibited significant upregulation, while TCF4 and AHCY were significantly downregulated. These gene expression changes were connected with increased LEF1 protein levels, activated Wnt signaling, and potential implications for enhanced cell invasion and proliferation through the upregulation of Cyclin A and Cyclin B. Top of FormBottom of Form.
Figure 12.
Western blotting results. For all experiments, GAPDH was used as a loading control, and detected by a rabbit polyclonal antibody (ab9458, Abcam). Then, 30 μg of whole cell proteins retrieved from SW480 AHCY-deficient or SW480 control cells were loaded per well. (a) Detection of AHCY protein (b) Detection of LEF1 protein, (c) Detection of STAT3 protein 2 + 4 signifies the group of cells in which AHCY expression has been silenced, while SCR represents the control group with normal AHCY expression. Western blot analysis of LEF1 protein expression confirmed the transcriptomic data predictions and revealed increased LEF1 protein in AHCY-deficient cells.
Figure 12.
Western blotting results. For all experiments, GAPDH was used as a loading control, and detected by a rabbit polyclonal antibody (ab9458, Abcam). Then, 30 μg of whole cell proteins retrieved from SW480 AHCY-deficient or SW480 control cells were loaded per well. (a) Detection of AHCY protein (b) Detection of LEF1 protein, (c) Detection of STAT3 protein 2 + 4 signifies the group of cells in which AHCY expression has been silenced, while SCR represents the control group with normal AHCY expression. Western blot analysis of LEF1 protein expression confirmed the transcriptomic data predictions and revealed increased LEF1 protein in AHCY-deficient cells.
Table 1.
Summary of IPA analysis; Molecular and Cellular Functions wt-vs-siAHCY.
Table 1.
Summary of IPA analysis; Molecular and Cellular Functions wt-vs-siAHCY.
Name | p-Value Range | Molecules |
---|
Cellular movement | 6.00 × 10−4–2.48 × 10−13 | 73 |
Cell death and survival | 6.18 × 10−4–2.31 × 10−8 | 66 |
Cellular development | 5.77 × 10−4–2.45 × 10−7 | 76 |
Cellular growth and proliferation | 5.77 × 10−4–2.45 × 10−7 | 70 |
Cell morphology | 4.14 × 10−4–3.07 × 10−7 | 48 |
Table 2.
Summary of IPA analysis; Molecular and Cellular Functions scr-vs-siAHCY.
Table 2.
Summary of IPA analysis; Molecular and Cellular Functions scr-vs-siAHCY.
Name | p-Value Range | Molecules |
---|
Cellular movement | 2.11 × 10−12–5.74 × 10−41 | 523 |
Cell death and survival | 3.76 × 10−13–8.59 × 10−28 | 553 |
Cellular functions and maintenance | 2.30 × 10−12–1.96 × 10−25 | 520 |
Cellular development | 1.51 × 10−8–3.38 × 10−23 | 605 |
Cellular growth and proliferation | 1.11 × 10−4–8.38 × 10−23 | 600 |
Table 3.
Differentially Expressed Genes in Wnt Signaling Pathway based on acquired RNAseq data. The table is summarizing the differentially expressed genes identified in the Wnt signaling pathway using IPA (ingenuity pathway analysis) software after performing differential expression analysis. The table provides insights into the transcriptional changes observed in key genes associated with Wnt signaling in SW480 AHCY deficient cells.
Table 3.
Differentially Expressed Genes in Wnt Signaling Pathway based on acquired RNAseq data. The table is summarizing the differentially expressed genes identified in the Wnt signaling pathway using IPA (ingenuity pathway analysis) software after performing differential expression analysis. The table provides insights into the transcriptional changes observed in key genes associated with Wnt signaling in SW480 AHCY deficient cells.
Symbol | Expr Log Ratio | q-Value | Type(s) |
---|
CDH12 | −11.706 | 6.97 × 10−13 | Other |
HNF1A | −13.408 | 3.71 × 10−17 | Transcription regulator |
MAP2K6 | −6.754 | 2.01 × 10−39 | kinase |
TCF4 | −3.915 | 2.45 × 10−3 | Transcription regulator |
Table 4.
Differentially Expressed Genes in Regulation of the Epithelial-Mesenchymal Transition Pathway. The table provides insights into the transcriptional changes observed in key genes associated with Regulation of the epithelial-mesenchymal transition pathway under AHCY deficient conditions. Differentially expressed changes concerning the TCF/LEF complex, similar as in the Wnt signaling pathway analysis are present.
Table 4.
Differentially Expressed Genes in Regulation of the Epithelial-Mesenchymal Transition Pathway. The table provides insights into the transcriptional changes observed in key genes associated with Regulation of the epithelial-mesenchymal transition pathway under AHCY deficient conditions. Differentially expressed changes concerning the TCF/LEF complex, similar as in the Wnt signaling pathway analysis are present.
Symbol | Expr Log Ratio | q-Value | Type(s) |
---|
APC2 | 3.428 | 1.35 × 10−2 | Enzyme |
CDH12 | −11.706 | 6.97 × 10−13 | other |
DKK1 | −3.416 | 2.55 × 10−5 | Growth factor |
DKK3 | 3.316 | 5.54 × 10−8 | Cytokine |
DKK4 | −3.791 | 1.81 × 10−8 | Other |
FZD7 | 4.134 | 5.66 × 10−20 | G-protein coupled receptor |
GJA1 | −5.544 | 5.66 × 10−6 | Transporter |
HNF1A | −13.408 | 3.71 × 10−17 | Transcription regulator |
POU5F1 | −5.964 | 9.76 × 10−3 | Transcription regulator |
RARB | −7.753 | 1.00 × 10−3 | Nuclear receptor |
SFRP5 | 3.362 | 5.03 × 10−12 | Transmembrane receptor |
SOX5 | −8.898 | 3.15 × 10−6 | Transcription regulator |
SOX6 | −3.842 | 3.33 × 10−6 | Transcription regulator |
TCF4 | −3.915 | 2.45 × 10−3 | Transcription regulator |
TLE1 | 4.455 | 4.53 × 10−11 | Transcription regulator |
TLE4 | 4.145 | 2.28 × 10−25 | Transcription regulator |
WNT6 | 4.078 | 1.28 × 10−21 | other |
Table 5.
The table presents a systematic analysis of the diverse functions of the Epithelial Adherens Junctions Signaling based on RNAseq data and IPA Core analysis. It highlights roles of epithelial adherens junctions signaling in cellular processes such as: cell adhesion, cell to cell contact formation, and remodeling of actin cytoskeleton.
Table 5.
The table presents a systematic analysis of the diverse functions of the Epithelial Adherens Junctions Signaling based on RNAseq data and IPA Core analysis. It highlights roles of epithelial adherens junctions signaling in cellular processes such as: cell adhesion, cell to cell contact formation, and remodeling of actin cytoskeleton.
From Molecule(s) | Relationship Type | To Molecules |
---|
14-3-3 | protein–protein interactions | YAP1 |
AFDN | causation | Recruitment of actin cytoskeleton |
AKT | causation | Cell proliferation |
AKT | causation | TC proliferation |
ARHGAP35 | inhibition | RHOA |
ARHGEF17 | activation | RHOA |
α-catenin | activation | Central spindling |
α-catenin | activation | NF2 |
α-catenin | activation | VCL |
α-catenin | causation | AJ organization |
α-catenin | causation | Recruitment of actin cytoskeleton |
α-catenin | inhibition | PP2A |
α-catenin | protein–protein interactions | 14-3-3 |
α-catenin | protein–protein interactions | NF2 |
α-catenin | protein–protein interactions | VCL |
Ampk | activation | RHOA |
Arp2-3 | causation | Actin polymerization |
Arp2-3 | membership | ACTR2 |
Arp2-3 | membership | ACTR3 |
BAIAP2 | activation | WAS |
BAIAP2 | activation | WASF1 |
BAIAP2 | protein–protein interactions | WASF1 |
CDC42 | activation | BAIAP2 |
CDC42 | activation | PAK |
CDC42 | activation | WAS |
CDC42 | inhibition | IQGAP1 |
CDC42 | protein–protein interactions | IQGAP1 |
CDH1 | activation | RAPGEF1 |
CDH1 | activation | STK11 |
CDH1 | causation | Cell adhesion |
CDH1 | inhibition | EGFR |
CDH1 | inhibition | IGF1R |
CDH1 | inhibition | MET |
CDH1 | protein–protein interactions | RAPGEF1 |
CDH2 | activation | PRKAA1 |
CDH2 | protein–protein interactions | CDH2 |
CDH2 | protein–protein interactions | CTNNB1 |
CDH2 | protein–protein interactions | PRKAA1 |
CRK | activation | RAPGEF1 |
CTNNB1 | activation | α-catenin |
CTNNB1 | activation | CDH1 |
CTNNB1 | activation | MAGI1 |
CTNNB1 | activation | MAGI2 |
CTNNB1 | activation | NF2 |
CTNNB1 | activation | TNS1 |
CTNNB1 | molecular cleavage | CDH1 |
CTNNB1 | protein–protein interactions | α-catenin |
CTNNB1 | protein–protein interactions | CDH1 |
CTNNB1 | protein–protein interactions | MAGI1 |
CTNNB1 | protein–protein interactions | MAGI2 |
CTNNB1 | protein–protein interactions | TNS1 |
CTNNB1 | reaction | α-catenin, FER |
CTNNB1 | reaction | α-catenin, FYN |
CTNNB1 | reaction | CTNNB1, EGFR; MET |
CTNNB1 | reaction | MAGI2, VCL |
CTNND1 | activation | CDH1 |
CTNND1 | molecular cleavage | CDH1 |
CTNND1 | protein–protein interactions | CDH1 |
CTNND1 | protein–protein interactions | RHOA |
CTNND1 | reaction | CTNND1, CDH1 |
CTNND1 | reaction | CTNND1, NANOS1 |
CTNND1 | translocation | CTNND1 |
CTNN,β-CDHE/N | activation | ARHGEF17 |
CTNN,β-CDHE/N | activation | TIAM1 |
CTNN,β-CDHE/N | causation | Cell adhesion |
CTNN,β-CDHE/N | causation | Cell-cell contact formation |
CTNN,β-CDHE/N | membership | CDH1 |
CTNN,β-CDHE/N | membership | CDH2 |
CTNN,β-CDHE/N | membership | CTNNB1 |
CTNN,β-CDHE/N | membership | CTNND1 |
CTNN,β-CDHE/N | protein–protein interactions | CDH1 |
Ca2+ | activation | CDH1 |
Ca2+ | chemical–protein interactions | CDH1 |
Central spindlin | activation | ECT2 |
Central spindlin | inhibition | ARHGAP35 |
Cofilin | causation | Stabilization of actin network |
DIAPH1 | causation | Stress fiber formation |
DLL1 | activation | NOTCH |
ECT2 | activation | RHOA |
EGF | activation | EGFR |
EGFR | activation | FER |
EGFR | activation | FYN |
EGFR | activation | RAS |
EGFR | causation | Epithelial barrier disruption |
EGFR | causation | Proliferation of cell |
EGFR | inhibition | CTNND1 |
EGFR | phosphorylation | CTNND1 |
EGFR | phosphorylation | FER |
EGFR | phosphorylation | FYN |
FARP2 | activation | CDC42 |
FGF1 | activation | FGFR1 |
FGFR1 | activation | RAS |
HGF | activation | MET |
IGF1R | causation | Proliferation of cell |
IQGAP1 | inhibition | CTNNB1 |
IQGAP1 | protein–protein interactions | CTNNB1 |
LATS | inhibition | YAP1 |
LIMK | inhibition | Cofilin |
LIMK | phosphorylation | Cofilin |
LPS | causation | Endothelial barrier function |
MAGI1 | activation | DLL1 |
MAGI1 | protein–protein interactions | DLL1 |
MAGI2 | activation | PTEN |
MAGI2 | molecular cleavage | PTEN |
MAGI2 | protein–protein interactions | PTEN |
MER-WWC1-FRMD6 | activation | MST/KRS |
MER-WWC1-FRMD6 membership | membership | NF2 |
MET | activation | RAS |
MET | causation | Proliferation of cell |
MET | inhibition | CDH1 |
MET | phosphorylation | CDH1 |
MST/KRS | activation | LATS |
Myosin2 | causation | AJ stabilization |
Myosin | causation | Cell adhesion structure clustering |
NF2 | inhibition | EGFR |
NOTCH | causation | Neuron differentiation |
Nectin | activation | AFDN |
Nectin | activation | SRC |
Nectin | causation | Cell adhesion |
Nectin | protein–protein interactions | AFDN |
Nectin | protein–protein interactions | Nectin |
Nectin | protein–protein interactions | SRC |
PAK | activation | LIMK |
PAK | phosphorylation | LIMK |
PIP2 | inhibition | AKT |
PIP3 | reaction | PIP2 PTEN |
PRKAA1 | causation | Endothelia barrier function |
RAC1 | activation | BAIAP2 |
RAC1 | activation | PAK |
RAC1 | activation | WASF1 |
RAC1 | inhibition | IQGAP1 |
RAC1 | protein–protein interactions | IQGAP1 |
RAP1 | activation | CTNND1 |
RAP1 | activation | FARP2 |
RAPGEF1 | activation | RAP1 |
RAS | expression | SNAI1 |
RAS | expression | SNAI2 |
RHOA | activation | DIAPH1 |
RHOA | activation | Myosin2 |
RHOA | activation | ROCK |
ROCK | activation | LIMK |
ROCK | phosphorylation | LIMK |
SNAI1 | expression | CDH1 |
SNAI2 | expression | CDH1 |
SRC | activation | CRK |
SRC | activation | FARP2 |
SRC | activation | VAV2 |
SRC | phosphorylation | FARP2 |
SRC | phosphorylation | VAV2 |
STK11 | activation | Ampk |
STK11 | phosphorylation | Ampk |
TCF/LEF | causation | Cell differentiation |
TCF/LEF | causation | Cell proliferation |
TGFB2 | activation | TGFBR |
TGFBR | expression | SNAI1 |
TIAM1 | activation | RAC1 |
TNS1 | causation | Recruitment of actin cytoskeleton |
VAV2 | activation | CDC42 |
VAV2 | activation | RAC1 |
WAS | activation | Arp2-3 |
WASF1 | activation | Arp2-3 |
YAP1 | reaction | YAP1 LATS |
YAP1 | reaction | YAP1 PP2A |
ZBTB33 | inhibition | TCF/LEF |
Table 6.
Differentially Expressed Genes in the Tumor Cell Microenvironment Pathway in AHCY-Downregulated SW480 Cells. The table summarizes the differentially expressed genes, highlighting upregulated and downregulated genes involved in extracellular matrix re-modeling, immune cell recruitment, cell migration, and cell survival. Significant changes in genes associated with the tumor cell microenvironment pathway are revealed.
Table 6.
Differentially Expressed Genes in the Tumor Cell Microenvironment Pathway in AHCY-Downregulated SW480 Cells. The table summarizes the differentially expressed genes, highlighting upregulated and downregulated genes involved in extracellular matrix re-modeling, immune cell recruitment, cell migration, and cell survival. Significant changes in genes associated with the tumor cell microenvironment pathway are revealed.
Symbol | Expr Log Ratio | q-Value | Type(s) |
---|
CSF2 | −4.435 | 7.37 × 10−13 | Cytokine |
CXCLR8 | −3.762 | 6.67 × 10−10 | Cytokine |
CXCR4 | 3.8 | 2.03 × 10−25 | G-protein coupled receptor |
FGF21 | −3.51 | 4.09 × 10−3 | Growth factor |
IL10 | 4.254 | 4.40 × 10−14 | Cytokine |
MMP16 | −6.32 | 4.43 × 10−3 | Peptidase |
MMP17 | −3.808 | 9.57 × 10−9 | Peptidase |
MMP19 | 3.196 | 1.33 × 10−3 | Peptidase |
MMP24 | 3.114 | 9.03 × 10−7 | Peptidase |
NOS2 | 3.881 | 1.34 × 10−19 | Enzyme |
PDGFC | −3.482 | 1.34 × 10−6 | Growth factor |
PIK3R5 | 4.778 | 1.5 × 10−2 | Kinase |
PLAU | 3.487 | 6.53 × 10−11 | Peptidase |
SLC2A3 | 3.254 | 1.67 × 10−12 | Transporter |
TIAM1 | 3.836 | 5.84 × 10−27 | other |
Table 7.
The table presents a systematic analysis of the diverse functions of STAT3 signaling based on RNAseq data and IPA Core analysis. It highlights roles of STAT3 signaling in cellular processes such as proliferation, survival, and differentiation.
Table 7.
The table presents a systematic analysis of the diverse functions of STAT3 signaling based on RNAseq data and IPA Core analysis. It highlights roles of STAT3 signaling in cellular processes such as proliferation, survival, and differentiation.
From Molecule(s) | Relationship Type | To Molecules(s) |
---|
BCL2 | Causation | Anti-Apoptosis |
BCR-ABL1 | activation | STAT3 |
CDKN1A | Inhibition | Stat3-Stat3 |
Cytokine | activation | Cytokinereceptor |
Cytokine | protein–protein interactions | Cytokinereceptor |
Cytokinereceptor | activation | JAK2 |
Cytokinereceptor | activation | SRC |
Cytokinereceptor | activation | TYK2 |
Cytokinereceptor | protein–protein interactions | JAK2 |
Cytokinereceptor | protein–protein interactions | TYK2 |
ERK1/2 | activation | JAK2 |
ERK1/2 | translocation | TYK2 |
Growthfactor | chemical–protein interactions | Stat3-stat3 |
Growthfactor | activation | ERK ½ |
Growthfactor receptor | protein–protein interaction | RAS |
Growthfactor receptor | activation | Growthfactor receptor |
Growthfactor receptor | activation | Growth factor receptor |
Growthfactor receptor | protein–protein interaction | JAK2 |
JAK2 | protein–protein interaction | SRC |
JAK2 | activation | JAK2 |
JNK | reaction | SRC |
MAP2K1/2 | activation | STAT3 |
MLK | activation | STAT3 |
MYC | activation | Stat3-Stat3 |
Mapkkinase | activation | ERK ½ |
Mapkkinase | activation | Mapkkinase |
NDUFA13 | activation | CDC25A |
P38MAPK | activation | JNK |
PIAS3 | protein–protein interactions | P38MAPK |
PIAS3 | activation | STAT3 |
PIM1 | inhibition | Stat3-stat3 |
PTPN2 | protein–protein interactions | Stat3-stat3 |
PTPN6 | activation | Stat3-stat3 |
RAC1 | inhibition | BCL2 |
RAF1 | inhibition | Stat3-stat3 |
RAS | activation | JAK2 |
RAS | activation | MLK |
SOCS | activation | MAP2K1/2 |
SRC | activation | RAC1 |
SRC | inhibition | RAF1 |
STAT3 | activation | JAK2 |
STAT3 | activation | RAS |
Stat3-stat3 | reaction | STAT3 |
Stat3-stat3 | translocation | Stat3-stat3 |
Stat3-stat3 | activation | STAT3 |
Stat3-stat3 | activation | CDKN1A |
Stat3-stat3 | activation | MYC |
Stat3-stat3 | causation | PIM1 |
TYK2 | membership | Transcription |