Journal of Signal Transduction

Journal of Signal Transduction / 2014 / Article

Review Article | Open Access

Volume 2014 |Article ID 962962 | 16 pages | https://doi.org/10.1155/2014/962962

A Network Map of FGF-1/FGFR Signaling System

Academic Editor: Shoukat Dedhar
Received20 Nov 2013
Accepted03 Mar 2014
Published16 Apr 2014

Abstract

Fibroblast growth factor-1 (FGF-1) is a well characterized growth factor among the 22 members of the FGF superfamily in humans. It binds to all the four known FGF receptors and regulates a plethora of functions including cell growth, proliferation, migration, differentiation, and survival in different cell types. FGF-1 is involved in the regulation of diverse physiological processes such as development, angiogenesis, wound healing, adipogenesis, and neurogenesis. Deregulation of FGF-1 signaling is not only implicated in tumorigenesis but also is associated with tumor invasion and metastasis. Given the biomedical significance of FGFs and the fact that individual FGFs have different roles in diverse physiological processes, the analysis of signaling pathways induced by the binding of specific FGFs to their cognate receptors demands more focused efforts. Currently, there are no resources in the public domain that facilitate the analysis of signaling pathways induced by individual FGFs in the FGF/FGFR signaling system. Towards this, we have developed a resource of signaling reactions triggered by FGF-1/FGFR system in various cell types/tissues. The pathway data and the reaction map are made available for download in different community standard data exchange formats through NetPath and NetSlim signaling pathway resources.

1. Introduction

Fibroblast growth factor (FGF) superfamily consists of structurally related polypeptides most of which function through its high affinity fibroblast growth factor receptors (FGFRs). In addition to FGFRs, they also bind to heparan sulfate proteoglycans (HPSGs) and their analog, heparin. These interactions influence the stability of FGFs in the extracellular matrix and also regulate their binding and activation of FGFRs [19]. In humans, FGFs are encoded by 22 genes, FGF-1-14 and FGF-16-23, and are divided into 7 subfamilies. FGFs 1–10 and 16–23 are FGFR ligands, while FGFs 11–14 are intracellular FGF homologous factors which act in a receptor-independent fashion [10]. Knock-out mice of different FGFs exhibit diverse developmental and physiological disorders [11]. For instance, FGF-9 is involved in the development of lung and testes [12, 13], FGF-3 is critical for inner ear development [14], and FGF-18 is important in bone and lung development [1517]. Moreover, knock-out of FGFs 4, 8, 9, 10, 15, 18, or 23 was found to be lethal in mice [18]. FGFs are also involved in wound healing, tissue repair [19, 20], and angiogenesis [21]. Facilitating cell proliferation, migration, and differentiation [16, 2226], FGFs are implicated in diverse pathological conditions including cancer [27] as well as metabolic and developmental disorders [18].

Most FGFs have an N-terminal signal peptide and are thus secreted. FGFs 1, 2, 9, 16, and 20 do not have signal peptides. FGFs 9, 16, and 20 may be released through classical secretory pathway; however, FGF-1 and FGF-2 are released from damaged cells or through endoplasmic reticulum-golgi independent exocytotic pathway [10]. FGF-1 along with FGF-2 was initially isolated from bovine pituitary extracts based on their ability to induce proliferation in 3T3 fibroblasts [28, 29]. Also known as acidic FGF, FGF-1 is a 155 amino acid long non-glycosylated polypeptide. FGF-1 is not released from the cells under normal physiological conditions, but it was secreted in response to stress conditions such as heat shock, hypoxia [30, 31], serum starvation [32], and exposure to low-density lipoproteins [33]. Stress induces the release of inactive disulfide bond-linked homodimeric form of FGF-1, which is dependent on p40-Syt1, S100A13, and Cu2+ ions [3437]. FGF-1 has been shown to reduce apoptosis in vascular injury [3840]. Administration of FGF-1 has shown promise as a therapeutic strategy against human cervical spinal cord injury [41] and ischemic conditions [4244]. Increased expression of FGF-1 was observed in ovarian [45] and prostate cancers [46]. Taken together, FGF1 is involved in different cellular functions that are mediated through its interaction with the four FGF receptors [47, 48]. A pathway resource representing these diverse functions and the underlying mechanisms that regulate these processes would be immensely useful.

Curated pathway maps are invaluable resources for scientific community. Such comprehensive pathway datasets are being increasingly used in bioinformatics efforts directed towards analysis of high-throughput datasets from various disease contexts. Repositories including Pathway Interaction Database of the National Cancer Institute (http://pid.nci.nih.gov/), Database of Cell Signaling (http://stke.sciencemag.org/cm/), KEGG Pathway Database (http://www.genome.jp/kegg/pathway.html), and INOH Pathway Database (http://inoh.org/) have cataloged basic components of FGF signaling. We have expanded the scope of this by providing a comprehensive representation of FGF1 signaling pathway and its diverse roles in regulating various cellular processes.

2. Methodology

Documentation of specific pathway reactions scattered in the literature into an organized, user-friendly, query-enabled platform is primary to the analysis of signaling pathways. We used NCBI PubMed database to carry out an extensive literature search to retrieve research articles where molecular events triggered by the FGF-1/FGFR signaling system were studied. Specific molecular events screened include (a) physical associations between proteins, (b) posttranslational modifications (PTMs), (c) change in subcellular localization of proteins, (d) activation or inhibition of specific proteins, and (e) regulation of gene expression. Relevant information from research articles were manually documented using the curation tool, PathBuilder. To streamline and organize data collection from literature, we followed the previously described criteria for the inclusion/exclusion of pathway specific reactions [49, 50]. The data accumulated was submitted to the NetPath signaling pathway resource developed by our group [51]. We then generated a signaling map for this pathway using PathVisio pathway visualization software. We also applied additional criteria to filter out low confidence reactions from the gathered data [52] and generated a NetSlim map. In addition to curation of molecular level information, we have also cataloged physiological effects brought about by FGF-1 in different cell types/tissues.

3. Results and Discussion

Canonical FGF/FGFR signaling reactions have been documented in a few public repositories and review articles. Vast amount of literature in the last few years have revealed several novel pathway intermediates of FGF/FGFR signaling system. In order to generate a comprehensive view of FGF/FGFR signaling pathway, we carried out extensive literature search on PubMed for articles pertaining to FGF-1 signaling. Of a total of 3275 articles that were screened, 237 of them had molecular reactions reported downstream of FGF-1 in various cell types/tissues. Manual curation from these research articles revealed 109 molecules involved in FGF-1 induced physical associations, modulation by PTMs, activity, and subcellular or cell surface translocation events. Of the 42 physical associations that were cataloged, 29 were “binary” and 13 were “complex” interactions inclusive of the ligand/receptor interactors. We could record a total of 87 catalysis events, 15 activation/inhibition, and 21 translocation events. The 87 catalysis events include 19 events, where the enzymes directly catalyzing the reactions were studied and reported, and 68 events for which the enzymes which post-translationally modified the proteins are not studied under FGF-1 stimulation. Apart from these molecular reactions, we have also cataloged 117 genes whose expression is reported to be either upregulated or downregulated by FGF-1 treatment. However, only a total of 25 genes were reported to be differentially regulated at mRNA level by FGF-1 stimulation in different human cell types. A list of genes reported to be regulated by FGF-1 in different mammalian systems at the mRNA and/or the protein level is provided in Table 1. After the annotation process, all the entries were reviewed and approved by internal reviewers. Internally reviewed pathways were further reviewed and approved by an external pathway authority (LC, who is an author in this paper).


Gene symbolUp-/down regulationmRNA/ProteinExperimentOrganismTissue/cell line/typePubMed IDTranscriptional regulatorRegulator Gene IDPubMed ID

1APOEUpmRNA and proteinRT-PCR, Western blotRatAstrocytes18216067, 19229075, 17548887, 15627653
2BAMBIDownmRNA and proteinRT-PCR, Western blotHumanPreadipocytes22187378
3CCND1UpmRNA and proteinGene chip array, Western blotHuman, ratMG63 osteoblastic cells, Rat Wister bladder tumor cells (NBT-II)15572039, 18189245
4CDK5R1UpmRNA and proteinQ-PCR, Western blotRatPC12 cells19249349
5CDKN1AUpmRNA and proteinRT-PCR, Western blotHuman, mouse, ratChondrocytes, REtsAF cells16091747, 16153144, 11779141, 10364154STAT1677211779141, 10364154
6CEBPAUpmRNA and proteinRT-PCR, Western blotHuman, mousePreadipocytes, 3T3-L1 cells17068114
7CEBPBUpmRNA and proteinRT-PCR, Western blotHuman, mousePreadipocytes, 3T3-L1 cells17068114
8COX2UpmRNA and proteinNorthern blot, ELISAHuman, rabbitCardiac muscle microvessel endothelial cells8790580, 2107185
9EGR1UpmRNA and proteinQ-PCR, Western blotMouse, ratPC12 cells, Hippocampal neuronal cell line HT22, human periodontal ligament cells19249349, 20649566, 18179472, 24396070STAT3, SP16774, 666724396070
10FOSUpmRNA and proteinRT-PCR, northern blot (mouse and rat), Immunohistochemistry, Western blotMouse, rat, human3T3 cells, Adipocytes, ENU1564 cell, Astrocytes of periventricular zone of third ventricle, SUM-52PE cells16309174, 2507555, 18041768, 11172932, 20388777
11JUNUpmRNA and proteinRT-PCR, Western blotRatENU1564 cells18041768
12JUNBUpmRNA and proteinGene chip array (Rat), Western blotRat, humanRat Wister bladder tumor cells (NBT-II), SUM-52PE cells18189245, 20388777
13MDM2UpmRNA and proteinRT-PCR, Western blotRatREtsAF cells16091747
14MMP14UpmRNA and proteinNorthern blot, Gene chip array, Western blotHuman, ratProstate cancer cell line, LNCaP, Rat Wister bladder tumor cells (NBT-II) 14673954, 18189245STAT3677414673954
15MMP9UpmRNA and proteinRT-PCR, Gene chip array, Western blotRatENU1564 cells, Rat Wister bladder tumor cells (NBT-II)18041768, 18189245RELA, JUN, FOS5970, 3725, 235318041768
16MYCUpmRNA and proteinNorthern blot (Mouse), Western blotMouse, human3T3 cells, SUM-52PE cells16309174, 20388777
17NOS2UpmRNA and proteinRT-PCR, Western blotRatAstrocytes16524372
18PLAUUpmRNA and proteinRT-PCR, ELISAHumanFibroblasts12008951
19PPARGUpmRNA and proteinRT-PCR, Western blotHuman, mousePreadipocytes, 3T3-L1 cells17068114, 22187378
20SLC2A4UpmRNA and proteinRT-PCR, Western blotHuman, mousePreadipocytes, 3T3-L1 cells22187378, 17068114
21THY1UpmRNA and proteinNorthern blot, Western blotRatPC12 cell lines11084019
22TNFRSF12AUpmRNA and proteinRT-PCR, ImmunoblotRatCardiomyocytes19629561
23NGFUpmRNA and ProteinRT-PCR, Enzyme Immuno assayRatHippocampal astrocytes, skin fibroblasts, Primary spinal cord astrocyte1377078, 15773903
24VEGFAUpmRNA and proteinReal time PCR, ELISAHumanPrimary human airway smooth muscle cells22205500
25ACPL2DownmRNAMicroarrayMouseOsteoblast cells18505824
26ARG1UpmRNAGene chip array, Q-PCRRatRat Wister bladder tumor cells (NBT-II) 18189245
27ATP2A2UpmRNARNA gel blotMouseNIH 3T3 cells7506544
28AXIN2DownmRNAMicroarrayMouseOsteoblast cells18505824
29BGLAPUpmRNAin situ hybridizationMouseMouse calvaria cells (coronal sutures)12674336
30CTSCUpmRNAGene chip arrayRatRat wister bladder tumor cells (NBT-II)18189245
31DKK3DownmRNAMicroarrayMouseOsteoblast cells18505824
32DLL1DownmRNANorthern blotMouseNeuroepithelial precursor (E10)11466430
33DUSP1UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
34DYNC2LI1UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
35EDNRAUpmRNANorthern blotRatArterial smooth muscle cells12851419
36EFNB1UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
37ELF4UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
38FASNUpmRNARNA gel blotMouseNIH 3T3 cells7506544
39FGF1UpmRNART-PCRRatPheochromocytoma cells8576258
40FGF7UpmRNART-PCRMouseEmbryonic lung mesenchymal cells10446271
41FN1UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
42FZD1DownmRNAMicroarrayMouseOsteoblast cells18505824
43FZD2DownmRNAMicroarrayMouseOsteoblast cells18505824
44FZD7DownmRNAMicroarrayMouseOsteoblast cells18505824
45FZD8DownmRNAMicroarrayMouseOsteoblast cells18505824
46F3DownmRNANorthern blotHumanHuman umbilical vein endothelial cells9157959
47GADD45ADownmRNAMicroarrayMouseOsteoblast cells18505824
48HBEGFUpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
49HMGA2DownmRNANorthern blotRat3T3-L1 cells10490844
50IBSPUpmRNAin situ hybridizationMouseMouse calvaria cells (coronal sutures)12674336
51IGF1DownmRNART-PCRHumanFibroblasts12008951
52IGF2DownmRNART-PCRHumanFibroblasts12008951
53IGF1RDownmRNART-PCRHumanFibroblasts12008951
54IGF2RDownmRNART-PCRHumanFibroblasts12008951
55IGFBP4DownmRNART-PCRHumanFibroblasts12008951
56IL4UpmRNAQ-PCRRatTransected spinal cord tissue21411654
57IRS1DownmRNAMicroarrayMouseOsteoblast cells18505824
58LAMA3UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
59LRRC17DownmRNAMicroarrayMouseOsteoblast cells18505824
60MITFUpmRNAMicroarrayMouseOsteoblast cells18505824
61MMP13UpmRNAGene chip array, Q-PCRRatRat Wister bladder tumor cells (NBT-II)18189245
62MMP3UpmRNANorthern blotRatPC12 cell lines11084019
63MSH6UpmRNARNA gel blotMouseNIH 3T3 cells8870641
64MSX2UpmRNAin situ hybridizationMouseMouse calvaria cells12674336
65NID2UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II) 18189245
66NOTCH1UpmRNANorthern blot, Gene chip array, Q-PCRMouse, ratNeuroepithelial precursor (E10), bladder tumor cells (NBT-II) 11466430, 18189245
67NR1H3UpmRNART-PCRRatAstrocytes19229075
68ODC1UpmRNANorthern blotMouseNIH 3T3 cells9223379
69PDGFAUpmRNARNA gel blotHumanHUVE cells1689299
70PFKLUpmRNARNA gel blotMouseNIH 3T3 cells7506544
71PLATUpmRNART-PCRHumanFibroblasts12008951
72PLAURUpmRNART-PCRHumanFibroblasts12008951
73PLFUpmRNANorthern blotMouseNIH 3T3 cells9223379
74PMEPA1DownmRNAMicroarrayMouseOsteoblast cells18505824
75PNRC1UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
76POSTNUpmRNANorthern blotRatPulmonary arterial smooth muscle cells15121739
77PPIAUpmRNANorthern blotRatPC12 cell lines11084019
78PRICKLE1DownmRNAMicroarrayMouseOsteoblast cells18505824
79PRPHUpmRNANorthern blotRatPC12 cell lines11084019
80PTPREUpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
81RUNX2UpmRNAin situ hybridizationMouseMouse calvaria cells (coronal sutures)12674336
82SCGB1A1UpmRNART-PCRMouseMouse lung epithelium12242715
83SDC1UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
84SERPINB1DownmRNAMicroarrayMouseOsteoblast cells18505824
85SERPINB2UpmRNART-PCRHumanFibroblasts12008951
86SERPINE1UpmRNART-PCRHumanFibroblasts12008951
87SFRP1DownmRNAMicroarrayMouseOsteoblast cells18505824
88SFTPCUpmRNART-PCRMouseMouse lung epithelium, Embryonic stem cell (mESC) line E14-Tg2a12242715, 20497026
89SOCS1UpmRNANorthern blotRatMouse lens epithelium14985304
90SOCS3UpmRNANorthern blotRatMouse lens epithelium14985304
91SOX2UpmRNAMicroarrayMouseOsteoblast cells18505824
92SPP1UpmRNAQuantitative northern blotRatPulmonary arterial smooth muscle cells15121739
93SPRY1UpmRNARNA gel blotMouseMC3T3-E1 osteoblasts16604287
94SPRY2UpmRNARNA gel blotMouseMC3T3-E1 osteoblasts16604287
95SPRY4UpmRNARNA gel blotMouseMC3T3-E1 osteoblasts16604287
96S1PR3UpmRNANorthern blotHumanHuman umbilical vein endothelial cells9315732
97TCF3DownmRNAMicroarrayMouseOsteoblast cells18505824
98TCF4DownmRNART-PCRHumanPreadipocytes22187378
99TGFAUpmRNANorthern blotMouseCultured keratinocytes7535082
100TGFB2DownmRNAMicroarrayMouseOsteoblast cells18505824
101TGFBR3DownmRNAMicroarrayMouseOsteoblast cells18505824
102THBS1DownmRNAMicroarrayMouseOsteoblast cells18505824
103THBS1UpmRNANorthern blotMouseNIH 3T3 cells9223379
104TIMP1UpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
105TIMP3DownmRNAMicroarrayMouseOsteoblast cells18505824
106VIMUpmRNAGene chip arrayRatRat Wister bladder tumor cells (NBT-II)18189245
107ADIPOQUpProteinRadioimmunoassayHumanPreadipocytes17068114
108CCNE1UpProteinWestern blotHumanMG63 osteoblastic cells15572039
109CTNNB1DownProteinWestern blotHumanSimpson Golabi Behmel syndrome (SGBS), Preadipocytes22187378
110HMOX1UpProteinWestern blotHumanSpinal cord astrocytes16524372
111MMP7UpProteinELISAHumanLNCaP cells11922392STAT3677411922392
112PKMYT1UpProteinImmunoblotRatChondrosarcoma cells21051949
113PLIN1UpProteinWestern blotHuman, mousePreadipocytes, 3T3-L1 cells17068114
114PTGISDownProteinELISAHumanEndothelial cells2107185
115PTGS2DownProteinELISAHumanEndothelial cells2107185
116RELAUpProteinWestern blotRatENU1564 cells18041768
117RHOAUpProteinImmunoblotRatCardiomyocytes19629561
118SOX9UpProteinWestern blotMouseCostal chondrocytes 10655493
119WEE1UpProteinImmunoblotRatChondrosarcoma cells21051949
120CDH2UpProteinWestern blotRatPC12 cells24396070STAT3, SP16774, 666724396070
121GAP43UpProteinWestern blotRatPC12 cells24396070STAT3677424396070

3.1. Signaling Modules Activated by FGF-1

Signaling modules comprise a well-characterized group of molecules and their interactions downstream of activation of a receptor. We documented the following signaling modules to be activated upon stimulation with FGF-1.

3.1.1. Ras/Raf/Mek/Erk Pathway

The Ras/Raf/Mek/Erk pathway has been implicated in cellular processes including cell growth, proliferation, and migration. Stimulation of different cell types with FGF-1 resulted in the formation of multiple complexes involving FRS2, GAB1, SOS1, PTPN11, SHC1, SH2B1, and GRB2 [5360]. These complexes are critical to the subsequent activation of Ras [53, 56]. Association of Ras with Raf kinase [53] induces autophosphorylation and activation of Raf. Activation of Raf leads to phosphorylation dependent activation of Map kinases 1/2 (MAP2K1/2) and subsequently Erk2/1 (MAPK1/3) [6062]. In the context of FGF-1 signaling, this module was reported to be involved in a number of processes including neurogenesis, adipocyte differentiation, cell proliferation, cholesterogenesis, cardioprotection, and tumor invasion and metastasis [6267].

3.1.2. Pi3k/Akt Pathway

The complexes mentioned above also lead to the activation of Pi3k/Akt pathway, another signaling module that regulates various processes including cell growth, survival, cell proliferation, and cell migration [68]. A number of studies have shown FGF-1 induced phosphorylation of Akt [63, 64, 69]. Pi3k inhibitor-based functional assays also proved the involvement of FGF-1 pathway in diverse physiological conditions including angiogenesis [70], lung development [71], maintenance of neuronal phenotype [72], neuroprotection [73], and ApoE-HDL secretion [69].

3.1.3. Jnk and p38 Mapk Pathway

The c-jun N-terminal kinase (Jnk) pathway is implicated in the regulation of cell cycle, cell survival and apoptosis. FGF-1 stimulates the phosphorylation of p38 Mapk (MAPK14) as well as Jnk1/2 (MAPK8/9). The Jnk1/2 was also found to be crucial to neurogenesis and vascular remodeling [63, 74]. The specific functions of FGF-1 signaling mediated by p38 Mapk include growth arrest, promotion of apoptosis in response to oxidative stress, and formation of actin stress fibers [7577].

3.1.4. STAT3 and Nf-kb Pathway

FGF-1 also stimulates STATs (STAT1 and STAT3) and Nf-kB signaling modules. FGFR signaling is reported to be regulated through several downstream molecules including JAK2, SRC, SH2B1, MAPK1/3, MAPK8/9, and STAT3. This signaling axis is known to regulate various cellular processes including neurite outgrowth, cell proliferation, and increased cancer cell invasion [7880]. In addition, FGF-1 is also reported to induce MMP9 expression in mammary adenocarcinoma cells through the Nf-kb pathway [81].

3.2. Physiological Effects Mediated by FGF-1

FGF-1 was found to be involved in a number of biological processes. It is associated with the development of heart [82], lens [83], lung, and liver [8486]. Its crucial roles in neurogenesis as well as adipogenesis [65, 87, 88] have also been reported. FGF-1 induces growth arrest and differentiation in chondrocytes [8992]. It is implicated in angiogenesis [9395] and wound healing [9599]. Multiple studies have also shown the role of FGF-1 in cardioprotection [99101] and neuroprotection [22, 102]. FGF-1 also induces migration [103105] and proliferation [106108] in different types of cancer cells. It is also involved in the regulation of epithelial-to-mesenchymal transition [109, 110], and tumorigenesis [111] as well as invasion and metastasis [64, 112]. A list of functional effects of FGF-1 studied in different cell types/tissues is provided in Table 2.


FunctionPubMed IDCell type/tissueOrganism

Adipogenesis22187378, 17068114PreadipocytesHuman
Apoptosis20657013Hepatoma cells, HEK293 cellsHuman
15773903Motor neuronRat
9681989Peroxynitrite-induced apoptosis in PC12 cellsRat
Cell cycle arrest16153144cellsHuman
Cell migration9108375Skin fibroblastsHuman
11019781FibroblastsMouse
Cell proliferation9182757Embryo fibroblastsRat
2441696Arterial smooth muscle cellsHuman
14966081AT2 alveolar cellsHuman
15094393Human long-bone growth plate chondrocytesHuman
1699952Umbilical vein endothelial ceilsHuman
15767480Y79 cellsHuman
2303528Epidermal keratinocytes (BALB-MK1)Mouse
2303528Keratinocytes (BALB/MK-1)Mouse
2383402Leydig cells (TM3)Mouse
1379845Megakaryocyte progenitor cellsMouse
1379845MegakaryocytesMouse
14985304Murine lens epithelial cell lines CRLE2, 1AMLE6, TN4-1 and NKR11Mouse
15574884NIH-3T3 cellsMouse
3272188Adrenal chromaffin cellsRat
2566605AstroblastsRat
1377078Hippocampal astrocytesRat
2153969Rat bladder carcinoma cell line (NBT-II)Rat
8622701PC12 cellsRat
8732667Prostate cancer cellsRat
1638984Retinal cellsRat
1377078Skin fibroblastsRat
12907464Aortic smooth muscle cellsHuman, rat
1638984Retinal cellsRats
22108586Periodontal fibroblastsRat
3272188Adrenal chromaffin cellsRat
22108586Periodontal ligament fibroblastsRat
20388777SUM-52PE cellsHuman
Cell rounding, growth inhibition11779141ATDC5 cells, chondroprogenitor cell linesMouse
Cholesterol biosynthesis19713443Mouse fibroblasts and rat astrocytesMouse, rat
19229075AstrocytesRat
18216067AstrocytesRat
17548887AstrocytesRat
Differentiation20497026Embryonic stem cell (mESC) line E14-Tg2aMouse
Epithelial-mesenchymal transition2153969NBT-II cells (Rat bladder carcinoma cell line)Rat
7593195NBT-IIRat
2153969NBT-IIRat
Fiber cell differentiation7539358Lens epithelial cellsMouse
G0/G1 arrest21051949Chondrosarcoma cellsRat
G2 arrest21051949Chondrosarcoma cellsRat
G2/M transition20044603Breast cancer cellsHuman
Growth arrest14593093Rat chondrosarcoma (RCS) cellsRat
Inhibition of apoptosis16524372AstrocytesRat
17473910, 16091747PC12 and RetsAF cellsRat
Inhibition of cell growth17363592TAKA-1 cellsHamster
Inhibition of neurogenesis11466430NEP cellsMouse
Inhibition of proliferation10364154Chondrosarcoma cells (RCS)Rat
Membrane ruffling7534069Human ductal breast epithelial tumor cell line (T47D)Human
Neurite outgrowth20175207TREX 293 cellsHuman
3272188Adrenal chromaffin cellsRat
8764646PC12 cellsRat
19249349PC12 cellsRat
3316527, 8576258PC12 cellsRat
12127979, 9182757, 2157719PC12 cellsRat
Neuronal differentiation16716298Primary astrocyte from human fetal brainHuman
7514169, 8622701, 2157719PC12 cellsRat
Osteoblast proliferation18041768ENU1564 cellsRat
Osteoblast differentiation18505824OsteoblastsMouse
Osteogenic differentiation12674336Sutural mesenchyme in mouse calvariaMouse
Protection from apoptosis19765618, 8576258PC12 cellsRat
Repression of myogenic differentiation1379245Skeletal muscle myoblasts (MM14)Mouse
Retinal cell proliferation15978261Retinal cellsMouse
Skeletal muscle development8601591Skeletal muscle myoblasts (MM14)Mouse
Synaptic plasticity20649566Hippocampal neuronal cell line HT22Mouse
Tumorigenesis20889570JMSU1 urothelial carcinoma cell linesHuman
9038374NBD-IIRat
Vascular remodeling15121739Pulmonary arterial smooth muscle cells (PASMCs)Rat
22205500ASM (Airway Smooth Muscle cells)Human
Regeneration3353388Retinal ganglion cellsRat
Astrocyte activation15773903Primary spinal cord astrocyteRat
Neurogenesis20429889Embryonic stem cellsMouse
Wound healing9036931Mouse
Cord Formation16631103Rat
Decrease in food intake7692459Rat
Facilitation of memory7692459Rat
Increase in sleep duration8985960Rabbit
Maintenance of the integrity of the organ of corti, initiation of protective recovery and repair processes following damaging auditory stimuli7568115Rat
Arteriole dilation8853345Rat
Feeding suppressor function11172932Rat
Hair-cell innervation during the terminal development of the sensory epithelium12792312Rat
Lens regeneration3792708Bovine
Lung morphogenesis and differentiation12242715Rat
Metastasis1707175Rat
Muscle regeneration1384586Mouse
Myocardial remodeling19629561Rat
Neuroprotection12095987Rat
Prevention of premature angiogenesis and inflammatory responses17643421Mouse
Protection against hypoxic-ischemic injury16635575Rat
Spinal cord injury repair21411654Rat
Cardioprotection15337227, 12176126Mouse

3.3. Pathway Visualization, Data Formats, and Availability

User-friendly visualization of pathways is an important aspect to provide a concise view. A number of tools are available for visualization and analysis of pathway data including Cytoscape [113], ChisioBioPAX Editor (ChiBE) [114], visualization and layout services for BioPAX pathway models (VISIBIOweb) [115], and ingenuity pathway analysis. These tools use pathway and molecular interaction data in different XML-based community standard data exchange formats as input. These standard formats, which include Proteomics Standards Initiative for Molecular Interaction (PSI-MI version 2.5), Biological Pathway eXchange (BioPAX level 3), and Systems Biology Markup Language (SBML version 2.1), enable easy data exchange and interoperability with multiple software. We have provided the annotated pathway data in the standard formats mentioned above. This data can be downloaded and used from NetPath [51], an open source resource for signal transduction pathways developed by our group (http://www.netpath.org/index.html). Additionally, we have drawn a map of FGF-1/FGFR signaling using the data accumulated in NetPath. This network map represents the molecules and their reactions organized by topology and excludes the molecules identified through phosphoproteomics approaches for which topology could not be assigned (Figure 1). The map was manually drawn using freely available software, PathVisio [116]. The topology of the molecules and their reactions in the pathway was arranged based on (i) inhibitor-based assays, (ii) mutation-based assays, (iii) knock-out studies, (iv) prior knowledge of canonical modules, and/or (v) with reference to multiple review articles. Another map, which incorporated high confidence reactions in accordance with NetSlim criteria [52], is submitted to the NetSlim database. These maps can be visualized and downloaded in gpml, GenMAPP, png, and pdf formats from http://www.netpath.org/netslim/FGF-1_pathway.html. Each node in the map is linked to their molecule page in NetPath, thereby to other pathways in NetPath, and to HPRD [117] and RefSeq protein accessions. In the “map with citation” option, the edges connecting the nodes are linked to the corresponding articles in PubMed that report the FGF-1 stimulated reaction(s). Direct reactions are represented by solid edges. Indirect reactions are represented with dashed edges. The edges which represent the protein-protein interactions, enzyme-substrate reactions and translocation events are distinguished by different colors.

4. Conclusions

Availability of specific ligand-receptor mediated signaling data in community approved formats is crucial to the understanding of proteins and their reactions in diverse biological processes. Analysis of high-throughput data obtained from microarray- and mass spectrometry-based platforms essentially relies on enrichment of biological function or signaling pathways available in databases to obtain insights into their physiological functions. Although some resources have cataloged FGF signaling in general, this is the first attempt to provide a comprehensive view of FGF-1 signaling. This will be extended to other FGF ligands and/or specific FGFRs in the future to facilitate the analysis of differences between different FGFs and/or FGFRs. The pathway information has been made available through NetPath and NetSlim resources in multiple community standard data formats. The FGF-1 signaling pathway data will be periodically updated in NetPath. We have cataloged multiple signaling modules that are activated upon activation of FGFR and their implications in diverse physiological and pathophysiological processes. We believe that the data presented here will boost further research in this area and will help identify novel therapeutically important molecules that could be targeted in pathological conditions involving aberrant FGF-1 signaling.

Abbreviations

S100A13:S100 calcium binding protein A13
FRS2:Fibroblast growth factor receptor substrate 2
GAB1:GRB2-associated binding protein 1
SOS1:Son of sevenless homolog 1
PTPN11:Protein tyrosine phosphatase, non-receptor type 11
SHC1:Src homology 2 domain containing transforming protein 1
GRB2:Growth factor receptor-bound protein 2
Mapk:Mitogen activated protein kinase
Pi3k:Phosphatidylinositide 3-kinase
Akt:v-akt murine thymoma viral oncogene homolog
HDL:High density lipoprotein
Jnk:Jun N-terminal kinase
STAT3:Signal transducer and activator of transcription 3.

Conflict of Interests

The authors have no conflict of interests.

Authors’ Contribution

Shyam Mohan Palapetta, Varot K. Sandhya, and Apeksha Sahu contributed equally to the paper.

Acknowledgments

The authors thank the Department of Biotechnology (DBT), Government of India, for research support to the Institute of Bioinformatics, Bangalore. Shyam Mohan Palapetta is supported by a Senior Research Fellowship from the Council of Scientific and Industrial Research (CSIR), India. Varot K. Sandhya is a recipient of Inspire Fellowship from the Department of Science and Technology (DST), Government of India. Harsha Gowda is a Wellcome Trust/DBT India Alliance Early Career Fellow.

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Copyright © 2014 Rajesh Raju et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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