Skip to main content
NCBI home page
Discover Oncology logoLink to Discover Oncology
. 2025 Mar 25;16:386. doi: 10.1007/s12672-025-02121-1

Mapping growth differentiation factor-15 (GDF15)-mediated signaling pathways in cancer: insights into its role across different cancer types

Akhila Balakrishna Rai 1, Jalaluddin Akbar Kandel Codi 2,✉, Giridhara Prema Suchitha 1, Kadabagere Narayanaswamy Hemavathi 1, Shobha Dagamajalu 1,✉, Chandran S Abhinand 1, Rajesh Raju 1,3, Thottethodi Subrahmanya Keshava Prasad 1,✉
PMCID: PMC11933546  PMID: 40128491

Abstract

Growth differentiation factor-15 (GDF15) is a cytokine/growth factor that belongs to the Transforming growth factor-ß (TGF-ß) protein family. The expression of GDF15 is low in most human organs under normal conditions. GDF15 is a stress-responsive cytokine primarily produced by macrophages in response to inflammatory stimuli. The altered expression of GDF15 is associated with many cancers due to the inflammation caused by the disease. GDF15 triggers the activity through its receptor Glial-derived neurotrophic factor-family receptor α-like (GFRAL) and mediates multiple downstream signaling cascades, which are involved in the progression of cancers. Considering the biological importance of GDF15 in different cancers, we applied data mining techniques to systematically compile and analyze the signaling events associated with GDF15 using NetPath criteria. This resulted in constructing a detailed GDF15-mediated signaling pathway map, enhancing our understanding of its molecular mechanisms in cancer. Furthermore, proteins linked to colorectal and breast cancer identified in our pathway map were cross-referenced with established cancer pathway databases to identify unannotated proteins, highlighting gaps in the current annotations. To investigate potential therapeutic strategies, we performed molecular docking simulations and identified Vitisifuran B as a novel inhibitor that could block the GDF15-GFRAL interaction. These findings suggest that Vitisifuran B could effectively modulate GDF15 signaling, offering a promising avenue for cancer therapeutics. This study underscores the power of computational approaches, such as data mining and molecular docking, in enhancing our understanding of GDF15 signaling in cancer and identifying potential inhibitors for therapeutic development.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12672-025-02121-1.

Keywords: GDF15, Cancer, Signaling pathway, Data mining, Bioinformatics, Molecular interactions

Introduction

Growth Differentiation Factor 15 (GDF15), a stress-responsive cytokine, belongs to the Transforming growth factor-β (TGF-β) family of proteins. It is also referred to as macrophage inhibitory cytokine-1 (MIC-1), prostate-derived factor (PDF), NSAID activated 1 gene (Non-Steroidal Anti-Inflammatory Drug-activated gene, NAG-1), placental bone morphogenetic protein (PLAB), and placental transforming growth factor beta (PTGFB) [1, 2]. In humans, the GDF15 is encoded by a gene GDF15 located on chromosome 19p13.11. The GDF15 mRNA codes for a precursor protein consisting of 308 amino acids (aa). This includes a 29-aa signal sequence, a 167-aa propeptide, and a 112-aa mature protein [3, 4]. The propeptide of ~ 40 kDa is cleaved by proprotein convertase subtilisin/kexin (PCSK) type 3, 5 and 6 at the N-terminus of the RXXR furine-like cleavage site to form a mature protein (25 kDa). Two mature proteins linked through a disulfide bond to form an active circulating homodimer GDF15 protein [4–6].

Recently, it has been found that GDF15 specifically binds to GDNF family receptor-like (GFRAL), with a co-receptor Rearranged during Transfection (RET) to induce intracellular signaling for the activation [7]. In response to inflammatory stimuli, GDF15 is primarily produced by macrophages [8, 9]. Under normal physiological states, GDF15 mRNA is produced at low levels in various cells and tissues, including the kidney, lung, pancreas, heart, skeletal muscle, adipose tissue, liver, gastrointestinal tract, placenta, and brain. In humans, GDF15 protein expression is notably high in the placenta, moderate in the prostate and urinary bladder, and low in the gastrointestinal tract, pancreas, and kidney, according to data from the Human Protein Atlas [5, 10–12].

GDF15 is found in both the cytoplasm and extracellular matrix (ECM), as well as within the nucleus. It undergoes dynamic movement between these compartments: from the nucleus to the cytoplasm and then into the ECM. The protein chromosomal Maintenance 1 (CRM1) plays a crucial role in exporting GDF15 from the nucleus to the cytoplasm [13]. The human GDF15 promoter contains binding sites for several transcription factors, including p53, early growth response protein 1 (EGR1), cAMP-response element binding protein (CREB), C/EBP homologous protein (CHOP), transcription factor Sp1, and activating transcription factor 3 (ATF3) [10, 14].

Elevated levels of GDF15 are linked to pathological conditions, including tissue damage and inflammation, as well as to the development of cardiovascular diseases, endocrine diseases (diabetes and obesity) and cancer [5, 8, 15–18]. Additionally, this elevated expression is associated with the onset and progression of various cancers such as breast, colorectal, pancreatic, gastric, and prostate [19–24]. Furthermore, serum GDF15 levels as a biomarker are proposed for the early detection and diagnosis of various cancers [15].

Given its diverse range of functions in different tissues and cellular processes, it is critical to understand the process by which GDF15 acts, the receptors with which it interacts, and the resulting signaling events involved. Unfortunately, there is a significant gap in understanding which pathways are activated in specific cell types or conditions. While there are numerous reports describing GDF15-dependent effects in cancer cells, the depth of these effects is complex, diverse, and inconsistent, lacking any clear consensus. Owing to the biological importance of GDF15 in various cancers, we developed a GDF15 signaling pathway map using literature mining to gather the molecular interactions in various cancers. These experimentally reported interactions were systematically integrated by manually annotating research articles from the literature, enabling them to be depicted as a single pathway map. Previously, our group has published pathways such as RANKL/RANK, CCL19/CCL21-CCR7, Elabela, and several other signaling maps [25–27]. Similarly, we generated the GDF15-mediated signaling pathway map to enhance our understanding of its role and contribute to the existing knowledge in cancer contexts.

Functional enrichment analysis is a commonly used approach to examine transcriptomics and proteomics data. However, it is well-known that current annotation systems often exhibit biases, with only a small subset of genes being well-annotated while the majority remain sparsely covered [28]. To illustrate the relevance of our pathway in systems biology, we focused on proteins associated with colorectal cancer (CRC) and breast cancer (BC). The proteins implicated in CRC and BC progression from this pathway map were cross-referenced with widely used cancer pathway databases to confirm their documented roles in the disease and identify gaps in the existing annotations.

We also analyzed metabolomics data of ‘Kanchanara Guggulu,’ a traditional medicine previously reported for its anti-cancer properties [29, 30]. To further investigate its potential in regulating GDF15-induced signaling and anticancer activities, we conducted molecular docking simulations to assess whether its metabolites could effectively target the GDF15-GFRAL binding site and modulate its interaction.

Methodology

Pathway map development

We carried out a PubMed search for the research articles pertaining to GDF15-mediated signaling using the search terms ‘(“GDF15” OR “GDF-15”) AND (“signaling” OR “signalling” OR “pathway”) NOT review’ to develop a GDF15 pathway map. The literature was manually screened to select experimental studies that contain information on the downstream signaling events that occur when GDF15 is stimulated. We manually curated the signaling reactions from the studies using previously published PathBuilder, NetPath, and NetSlim annotation criteria [31–33]. The molecular events were grouped into five categories: protein/gene regulation, protein activation/inhibition, enzyme catalysis/post-translational modifications (PTMs), molecular associations, and protein translocation between cell organelles. Other information related to the curation was also included, such as cell lines used in the experiment, experiment type, and PTM sites and residues. Diverse types of molecular reactions reported under the influence of GDF15 thus gathered were manually curated into formatted Excel sheets. Each molecular event in the GDF15 signaling pathway is linked to the respective research article through PubMed identifier. Using known subcellular localizations, signaling contexts and molecular interactions of these proteins, a signaling pathway map was manually drawn using the PathVisio tool [34] that provides the gpml format of the pathway reactions. Different types of edges were employed to represent various reaction types, with dashed lines indicating phosphorylation and inhibition, while solid lines represent gene and protein regulation. Post-translational modifications (PTMs), along with their respective residues and interacting molecules, are highlighted using specific colors. A detailed legend was included to facilitate a clearer understanding of the pathway map. The pathway reactions and the pathway map were reviewed by internal reviewers (S.D., R.R., and T.S.K.P.), with expertise in developing pathway maps for numerous ligand-receptor systems [25, 26, 35–39].

Annotation of GDF15 as a biomarker in the pathway map

Following the construction of the GDF15 pathway map based on experimental data, we conducted a biocuration of published proteomic datasets to assess the role of GDF15 in cancer. In cases, where GDF15 was altered in cancers, we marked it with a star symbol (*) on the pathway map to visually highlight its relevance to cancer biology.

Comparison with pathway databases and TCGA mutation data

In addition, we compiled the proteins associated with the CRC pathway, including GDF15, VIM, CDH1, CDH2, AKT1, TGFBR2, SMAD2, MAPK1, MAPK3, MAPK14, among others. These proteins were analyzed using STRING database (https://string-db.org/) (Szklarczyk et al., 2023) to visualize their molecular interactions and their roles in CRC, leveraging widely available pathway databases like KEGG and WikiPathways. Additionally, we compared these findings by analyzing the colon adenocarcinoma TCGA data using SRplot’s MAF Oncoplot tool (https://www.bioinformatics.com.cn/plot_basic_maf_oncoplot_135_en). A similar analysis was performed for the proteins associated with the breast cancer pathway to provide deeper insights.

Identification of signature metabolites in Kanchanara Guggulu using a metabolomics approach

We analyzed the raw metabolomics data from ‘Kanchanara Guggulu,’ a formulation previously reported for its anticancer properties, to identify signature metabolites targeting GDF15. The data analysis process is detailed as follows. Mass spectrometry data, both in positive and negative ion modes, was processed separately using MZmine (Version 2.53) [40]. Initially, mzML files were generated from the.wiff files using MSConvert and uploaded into MZmine to extract retention time (RT), m/z values, and peak areas of the detected features. Mass detection was performed at MS1 and MS2 levels with predefined intensity thresholds. Precursor ions, along with their fragment details, were selected using the MS/MS peak list builder to generate the m/z feature list. Features within a 0.05 Da m/z tolerance were processed through chromatogram deconvolution using the Peak Extender algorithm. During deconvolution, the noise peak height was set to 1.5 × 102, and retention time and m/z tolerances for MS2 pairing were configured to 1 min and 0.1 Da, respectively.

The deconvoluted features were then processed using the isotopic peaks grouper algorithm, with m/z and retention time tolerances set at 0.25 Da and 0.2 min, respectively. These features were subsequently aligned using the Join Aligner algorithm. The features were then gap-filled using the Peak Finder algorithm, with an intensity tolerance of 30%, a retention time tolerance of 0.6 min, and an m/z tolerance of 0.05 Da. Duplicate peaks were removed using the New Average mode in the Duplicate Peaks Filter algorithm, applying m/z and retention time tolerances of 0.1 Da and 0.2 min, respectively. The results, including peak areas, RT, m/z values, and feature IDs, were exported as CSV files at the MS2 level. Additionally, precursor masses and their associated fragment details were exported for metabolite assignment. The files obtained after MZmine analysis were further analyzed to obtain MS2-level metabolites using the MS2Compound tool [41]. Metabolites were annotated and downloaded from PlantCyc and HMDB (Human Metabolome Database) [42, 43]. The identified MS2 metabolites were then further evaluated using MS2query [44], which compares library and query spectra through a random forest model. A prediction score greater than 0.7 was set as the cut-off for identifying the best-matching metabolites. The top-scoring metabolites from MS2query, along with rank one metabolites from MS2Compound, were selected for docking.

Molecular docking screens

The top metabolites of ‘Kanchanara Guggulu’ identified in the analysis were docked against GDF15 to assess whether these metabolites bind to the target protein. The 3D structure of GDF15 (PDB ID: 5VZ4) was obtained from the Protein Data Bank and prepared by removing water molecules and other heteroatoms using the “Prepare Protein” protocol in Discovery Studio 2022. The structures of the metabolites were downloaded from the PubChem compound database and underwent ligand preparation using the ligand preparation protocol in Discovery Studio 2022 before performing molecular docking. The key residues in GDF15 that showed interactions with its receptor were selected and defined as the active site of the protein. Protein–ligand docking was performed using the LibDock protocol in Discovery Studio 2020, with the LibDock score and intermolecular interactions between the ligands and GDF15 considered for selecting the best ligands from the library. Further, some standard chemotherapeutic drugs such as Doxorubicin (PubChem ID: 31703), Paclitaxel (PubChem ID: 36314), Cisplatin (PubChem ID: 441203), and 5-fluorouracil (PubChem ID: 3385) were also checked for their possible interactions with GDF15. The Online Resource 3 table provides the list of software, tools and databases used in each step of the study. The overall workflow of the study is depicted in Fig. 1.

Fig. 1.

Fig. 1

Open in a new tab

Schematic representation of the workflow adapted in this study. An overall workflow illustrating the key steps: 1. Literature screening and manual curation of signaling events, 2. Pathway map construction and cross-referencing with databases, 3. Metabolomics analysis and molecular docking

Results and discussion

The PubMed search with the specified search terms fetched 645 articles related to GDF15 signaling. Manual screening was performed to select the research articles with specific information about GDF15 signaling in cancer. The manual curation of these chosen articles had 149 molecules grouped into nine activation/inhibition events, six molecular associations, 34 enzyme catalysis, and two translocation events. A total of 52 genes and 46 proteins had differential mRNA and protein expression, respectively (Online Resource 1). These events were merged into a single pathway map. To the best of our knowledge, this resource offers a compilation of diverse molecular reactions facilitated by GDF15 in different cancer conditions, illustrated in Fig. 2.

Fig. 2.

Fig. 2

Open in a new tab

Illustrative depiction of the GDF15-induced signaling pathway in cancer. The signaling pathway diagram depicts the molecules involved in interactions between ligands and receptors, as well as downstream molecular processes triggered by GDF15. These processes encompass various events like molecular association, enzyme catalysis, translocation, and gene regulation. Additionally, details concerning posttranslational modification sites, residues and reporting as biomarker are provided within the pathway

A concise overview of the GDF15 signaling map in different cancers

GDF15 is involved in regulating body weight and food intake under physiological and pathophysiological conditions. In normal conditions, the expression of GDF15 remains low, whereas it increases in diseased conditions. GDF15 binds to GDNF family receptor-like (GFRAL) and Rearranged during Transfection (RET), which triggers various downstream signaling cascades. Its impact has been extensively documented across various human cancer types [7, 11, 45]. Stimulation by GDF15 alters the expression of multiple molecules within cells, consequently promoting cell proliferation in prostate cancer, oral cancer, cervical cancer, hepatoma, and bladder cancer cells [46–50]. The significant role of GDF15 signaling in different cancers is described below.

Head and neck cancer (HNC)

The elevated expression of GDF15 in head and neck cancer tumor tissues and cell lines is involved in tumor stage, lymphovascular invasion, and tumor grade [51]. Li et al. reported that GDF15 contributes to radioresistance and promotes cancer stemness through the inhibition of ROS, upregulation of SMAD1, SMAD5, SMAD3, NES, ALDH1 and CD44 via phosphorylation of SMAD1 (Ser190), SMAD5 (Ser463/465), SMAD3 (Ser423/425) in xenografted tumors in BALB/c nude mice. This demonstrated that overexpression of GDF15 induces significant resistance to radiation treatment [52]. Jin et al., reported that the ectopic expression of EGR1 significantly increased the expression of GDF15, which in turn decreased the expression of CDH1 and increased the expression of CDH2, VIM, and SNAI1 through the activation of AKT1 (Ser473) and MAPK3/1 pathways, which contributes to cancer progression in rhGDF15 treated HNC KB and FADU cells. This study suggested that the GDF15-EGR1 signaling axis may be a potential therapeutic target in HNC patients [51].

Brain cancer

GDF15 is involved in enhancing the proliferation, invasion and secondary tumor forming behavior through the phosphorylation of MAPK3/1 (Thr202 /Tyr 204), and JUN pathways in brain cancer cells such as H4 and A172[53]. In glioblastoma multiforme (GBM) cells, GDF15 induces phosphorylation of SMAD2 (Ser465, Ser467) and SMAD3 (Ser423, Ser425), thereby upregulating CD274, which regulates tissue development and cancer [54]. Zhu et al., reported that GDF15 induces the phosphorylation of STAT3 (Tyr705), MAPK3, and MAPK1 and the molecular association between FOS and LIF promoter. This leads to the upregulation of LIF, FOS, PROM1, and SOX2 in GSC (glioma stem cells)-like cells (GSCLCs) and U87 TS cells, which promotes glioma stem cell-like phenotype [55]. rhGDF15 induces the MAPK1 (Tyr204) phosphorylation, elevated expression of SP1 and its translocation to the nucleus, where it binds to the promoter region of VEGFA. This results in the upregulation of VEGFA, which in turn leads to the phosphorylation of KDR (Tyr1059) and induces angiogenesis in glioblastoma on endothelial cells [56]. Another study reported that GDF15 in glioblastoma cells induces the upregulation of cleaved CASP3, cleaved CASP9, BAX, CYCS and downregulation of BCL2 through the phosphorylation of PIK3R1 (Tyr458), AKT1 (Ser473), SMAD2 (Ser465, Ser467), and SMAD3 (Ser423, Ser425) pathways, which promotes apoptosis in glioblastoma cells [56].

Bladder cancer

The overexpression of GDF15 in bladder cancer cells leads to the increased level of NDRG1, NDRG2, NDRG3, SERPINB5, and CDH1 and attenuated CDH2, SNAI2, SNAI1 expression, which inhibit the cell proliferation, invasion, and tumorigenesis [50]. The study by Hou et al. reported that the rhGDF15 treatment in bladder carcinoma cells promotes cell proliferation and invasion by the upregulation of NDRG1 and SERPINB5 proteins [57].

Breast cancer

In breast cancer cells, GDF15 overexpression induces phosphorylation of IGF1R (Tyr1131) resulting in the downregulation of CDH1 and upregulation of CDH2, VIM, FOXM1, IGF1R, SNAI1, ZEB1, SNAI2, MMP2, MMP9, which mediates epithelial-mesenchymal transition (EMT) and invasion [58]. HER2-overexpressing breast cancer cells (BT474 cells) were stimulated with recombinant human GDF15, which induces phosphorylation of ERBB2 (Tyr1248), AKT1 (Ser473), MAPK3/1 (Thr202 /Tyr204), SMAD2, and SRC leads to trastuzumab resistance [59]. Sasahara et al. (2017) reported that GDF15 induces the phosphorylation of SMAD2 (Ser465/467), MAPK3/1 (Thr202 /Tyr 204). This phosphorylation upregulates POU5F1, SOX2, and NANOG in MCF7 (breast cancer) cells, which maintains cancer stem-like phenotype in breast cancer [60]. The overexpression of GDF15 in MCF7 (breast cancer) cells causes the activation of the MAPK3 pathway [61]. GDF15 in breast cancer cells induces the phosphorylation of AKT1 (Ser473 and Thr308), MAPK3/1 (Thr202 /Tyr204), Tyr phosphorylation of EGFR, ERBB2, ERBB3, MTOR (Ser2448), RPS6KB1 (Thr389), EIF4EBP1 (Thr37/46), and increased expression of VEGFA, HIF1A, which are involved in tumor progression and metastasis [62].

Cervical cancer

In cervical cancer HeLa and SiHa cells, GDF15 interacts with ERBB2 and phosphorylates AKT1 (Ser473), MAPK3/1 (Thr202 /Tyr204), ERBB2 (Tyr1221, Tyr1222). It further induces upregulation of CDK1, CDC25A, CDK2, CDK4, CCND1, CCNE1, MYC, PIK3CA, HRAS, KRAS, NRAS and downregulation of CDKN1A, CDKN1A, FOXO1, which promotes proliferation of cells [48].

Colorectal cancer

In colon cancer cells, GDF15 induces phosphorylation of MAPK14 (Thr180, Tyr182), MAPK3/1 (Thr202 /Tyr204), and AKT1 (Ser473), which promotes cell proliferation, migration, and invasion in colon adenoma and colorectal cancer cell lines. The increased GDF15 expression is observed in primary normal colon tissue from people at increased risk for CRC [63]. Zheng et al. (2019) reported that DDIT3 binds to the promoter of GDF15 in hypoxia-induced colorectal cancer cells. It induces downregulation of CDH1 and upregulation of CDH2, VIM and PPARGC1A, CPT1A, CPT1B, CPT2, ACSL1, CD36, genes which are involved in metastasis [64]. Another study reported that GDF15 induction in DLD1 (human colon cancer) cells leads to the upregulation of ACSL1, CPT1A, CPT1B, CPT2, CD36, and PPARGC1A, which stimulates tumor chemoresistance [65]. Lee et al. showed that GDF15 induces the phosphorylation of SMAD2 (Ser465/467) in recombinant GDF15 added TGFBR2 expressing HCT116 cells [66]. The recombinant rhGDF in HCT116 p53 wild-type cells induces phosphorylation of AKT1 (Ser473), which is involved in the inhibition of drug-induced cell death [67].

Esophageal cancer

In esophageal cancer cells, the high expression of GDF15 induces phosphorylation of AKT1 (Ser473, Thr308), and MAPK3/1 (Thr202 /Tyr204), which is involved in tumor progression [68]. Okamoto et al. (2020) reported that GDF15 stimulation in TE-8 and TE-11 (esophageal squamous cell carcinomas (ESCC)) cells induces the phosphorylation of AKT1 (Ser473), MAPK3/1 (Thr202 /Tyr204), TGFBR2 (Ser225) and promotes progression of cancer [69].

Prostate cancer

In prostate cancer cells, overexpression of GDF15 induces the upregulation of ST14, NDRG1, and IL6; and the downregulation of SERPINB5, which are involved in cell proliferation, invasion, and tumorigenesis [46]. Wang et al., reported that prostate cancer cells disseminate to bone, where they interact with osteocytes and release GDF15 into the bone microenvironment. GDF15 binds to its receptor GFRAL on prostate cancer cells, triggering the upregulation of EGR1, which contributes to cancer progression in the bone microenvironment and promotes bone metastasis [70]. In human prostate adenocarcinoma tissue, GDF15 induces the phosphorylation of SMAD2 (Ser433), SMAD3 (Ser435), MAPK3/1 (Thr202 /Tyr204), RPS6KA1 (Ser380), MAPK14 (Tyr182, Thr180), which are involved in cell growth and tumor progression [24, 71]. In agreement with this, Wang et al., reported that the overexpression of the wild-type GDF15 increases the phosphorylation of EGFR (Tyr1068), SRC, MAPK3/1 (Thr202 /Tyr204), and AKT1 (Ser473) level along with cell survival in castration-resistant prostate cancer (CRPC) cells, whereas the N70 glycosylation of GDF15 abolishes the inhibitory effect of GDF15 on EGFR [72].

Other types of cancers including gastric, hepatoma, lung, bone and oral

In gastric cancer cells, GDF15 induces the FAO (Fatty acid oxidation) associated upregulation of CD36, ACSL1, PPARGC1A, CPT1A, CPT1B, and CPT2, which promotes chemoresistance [73]. The higher expression of GDF15 in HCV-infected hepatoma cells (Huh7.5.1 cells) causes the phosphorylation of AKT1 (Ser473), RAF1 (Ser259), and GSK3B (Ser9). It results in the upregulation of PCNA, CCNA2, IGFBP3, CCNB1, CDK2, CDH1, CTNNB1, MYC, CCND1, SOCS2, TGFA, AFP, CDK4 and downregulation of EGF, FOXO1, IFNAR1, CDKN2A, which are involved in increased DNA synthesis, promoted cell proliferation, and importantly enhanced invasiveness of the cells [49]. The expression of GDF15 in A549 (lung adenocarcinoma) cells inhibits phosphorylation of SMAD2 which in turn is involved in the inhibition of bone metastasis [74]. In human bone osteosarcoma epithelial cells (U20S), GDF15 controls the transcriptional regulation of Smad pathway by the upregulation of HMGA1 and downregulation of COL1A1, TIMP3, TGM2, TGFB1, LTBP1, LTBP2, SERPINE1, PMEPA1, IGFBP5 in human bone osteosarcoma epithelial cells (U20S) [13]. Zhao et al., reported that GDF15 overexpression in oral squamous cell carcinoma (OSCC) cells and xenograft mice model increases the phosphorylation of ERBB2 (Tyr1139), AKT1 (Ser473), MAPK1 (Tyr204), MAPK3 (Thr204), PDK1, GSK3B, RAF1 (Ser331), MAP2K1, RPS6KA1, RPS6KA5, which promotes cellular proliferation [47].

Common downstream pathways of GDF15 in various cancers

Across different cancers, GDF15 predominantly activates pathways that promote cell proliferation, survival, and metastasis. One of the central themes is the activation of the PI3K/AKT pathway, which is frequently upregulated in cancers including head and neck, prostate, oral, cervical, esophagus, and colorectal. For instance, GDF15 stimulation leads to the phosphorylation of AKT1 (Ser473) and MAPK3/1 (Thr202/Tyr204) in prostate, cervical, and colorectal cancers, facilitating tumor growth and resistance to treatment. Similarly, in breast cancer, GDF15-induced phosphorylation of IGF1R (Tyr1131) and MAPK3/1 (Thr202/Tyr204) supports EMT and invasion. GDF15 also affects the SMAD signaling pathways, which are crucial for cellular responses to TGF-beta superfamily members. In various cancers, such as head and neck cancer and glioblastoma, GDF15-induced phosphorylation of SMAD2 and SMAD3 contributes to cancer stem cell maintenance and resistance to radiation therapy (Fig. 3).

Fig. 3.

Fig. 3

Open in a new tab

Common downstream pathways of GDF15 in cancer. The schematic representation illustrates the key molecular pathways activated by GDF15 and their role across various cancers

Overall, the diverse roles of GDF15 across different cancers reflect its potential as both a biomarker and a therapeutic target. The activation of common pathways such as PI3K/AKT and SMAD, coupled with cancer-specific effects, underscores the complexity of GDF15 signaling. Understanding these mechanisms can provide insights into developing targeted therapies and improving treatment outcomes for cancer patients.

Emphasizing the significance of the GDF15 pathway

To highlight the significance of the GDF15 signaling pathway, we selected the proteins involved in the CRC and BC pathways. While some key proteins like TGFBR2, AKT1, SMAD2, MAPK3, and MAPK1 were identified in the KEGG pathway database for CRC, additional proteins related to EMT in CRC were found in WikiPathways (Fig. 4a). Despite this, proteins such as PPARGC1A, CPT1A, CPT1B, ACSL1, VIM, CPT2, CD36, and DDIT3 did not show hits in any pathway databases for CRC. Similarly, for BC, proteins such as MTOR, ERBB2, MAPK1, RPS6KB1, MAPK3, EGFR, IGF1R, and AKT1 were identified in both KEGG and WikiPathways (Figure S1a). In contrast, proteins like MMP9, CDH1, CDH2, and SMAD2 did not align with any pathway database. This comparison revealed that many proteins curated in this GDF15 pathway map are absent in existing databases, suggesting a gap in existing pathway annotations.

Fig. 4.

Fig. 4

Open in a new tab

Comparison of GDF15 pathway proteins associated to colorectal cancer with existing pathway databases and TCGA mutational data. a The protein interaction network of proteins from the GDF15 pathway map with those found in the colorectal cancer (CRC) pathway. Proteins marked with circles represent hits in KEGG (red) and WikiPathways (blue). b The MAF Oncoplot illustrates mutation frequencies of CRC proteins in TCGA data for colon adenocarcinoma

Moreover, we examined the presence of mutations in these proteins related to colon adenocarcinoma and breast invasive carcinoma in TCGA data. Notably, proteins like PPARGC1A and CPT1A were found to be mutated in CRC according to TCGA data, as depicted through an MAF oncoplot (Fig. 4b). Based on TCGA data, proteins such as CDH1 and ERBB3 were found to harbor mutations in BC (Figure S1b). This indicates that while these proteins are absent from pathway databases, they are represented in mutation datasets, further validating their importance in CRC and BC, as reflected in our pathway map. These pathway databases lead to the under-representation of clinically significant genes. The inclusion of poorly annotated but relevant proteins in our pathway map not only enhances our understanding of the targets but also underscores the need for more comprehensive pathway databases.

Molecular docking of GDF15 with metabolites of Kanchanara Guggulu

Mass spectrometry-based untargeted metabolomics of ‘Kanchanara Guggulu’ enabled the identification of 497 nonredundant metabolites at the MS1 level corresponding to 253 in positive and 244 in negative modes. There were 95 nonredundant metabolites at the MS2 level corresponding to 54 in positive and 41 in negative modes. The top-scoring metabolites from MS2query search with > 0.7 prediction score and rank 1 metabolites from MS2Compound were selected for docking with GDF15. The high-confidence metabolites in this study include Quercetin 3-O-[2''-O-b-d-glucopyranosyl]-a-l-rhamnopyranoside, 4-Hydroxyquinoline, Gallic acid 4-O-(6-galloylglucoside), Phosphatidylcholine among others. The metabolites identified from the search in MS2Compound are provided in Online Resource 2.

Molecular docking was carried out to identify potential metabolites of ‘Kanchanara Guggulu’ that could bind to the active site of GDF15 to its receptor GFRAL, potentially contributing to its anticancer properties. The docking analysis revealed the successful docking of four compounds, with Vitisifuran B achieving the highest LibDock score (70.86) followed by Phosphatidylinositol lyso 18:1 (69.79), 5-(10-Nonadecenyl)resorcinol (65.57) and 3'-N-Acetyl-4'-O-(14-methylpentadecanoyl)fusarochromanone (33. 76). The ligand Vitisifuran B formed hydrogen bonds with Tyr279 and Asp299, along with additional interactions involving Asp299, Leu300, and Leu223. The docking results are summarized in Table 1, and the docked complex structure of Vitisifuran B with GDF15 is illustrated in Fig. 5.

Table 1.

Molecular docking results of GDF15 with top 4 compounds

PubChem ID IUPAC Name Libdock score Amino acids forming hydrogen bonds Amino acids forming other interactions
131751783 Vitisifuran B 70.86 Tyr279, Asp299 Asp299, Leu300, Leu223
134756595 Phosphatidylinositol lyso 18:1 69.79 Cys240 Val235, Val237, Pro276, Ala302, Leu300, Val229, Pro232, Met282, Leu284, Trp225, Tyr279
131752736 5-(10-Nonadecenyl)-1,3-benzenediol 65.57 Gly224 Val229, Val235, Val237, Leu284, Leu223, Met282, Leu300, Leu220, Pro232, Trp225, Tyr297
101420967 3'-N-Acetyl-4'-O-(14-methylpentadecanoyl)fusarochromanone 33.76 Tyr279, Asp299 Asp299, Val235, Val237, Leu223, Leu300, Leu220, Val229, Pro232, Leu284, Trp225
Open in a new tab

Fig. 5.

Fig. 5

Open in a new tab

Visualization of 3D docked complex structure of Vitisifuran B with GDF15. The molecular docking model depicts the interaction between Vitisifuran B and GDF15. Vitisifuran B is shown to bind to the active site of GDF15, suggesting its potential as an inhibitor

The Highest LibDock score of Vitisifuran B suggests a favorable binding affinity, indicating that this metabolite may influence the GDF15-GFRAL interaction, potentially playing a role in its anticancer effects. Vitisifuran B is a member of the 2-arylbenzofuran flavonoid class of organic compounds, with unknown biological effects (https://doi.org/10.1016/S0040-4020(99)00039-3). Our study has demonstrated its potential in targeting GDF15, making this a key highlight of the research. Further experimental validations are required to confirm these findings. Docking studies were performed with four chemotherapeutic drugs against the same active site of GDF15. The results revealed that only doxorubicin successfully bound to the defined pocket, with a LibDock score of 68.29 and formed hydrogen bonds with Tyr279 and Asp299.

Limitations of the study

Signaling pathway information is provided as a supplementary file. The curators and reviewers follow the established protocols for pathway curation, however, there is always room for confusion because of common alternate names for different proteins used by different laboratories. Each molecular reaction is sourced from different types of experiments from multiple laboratories. Model systems, experimental conditions, quality controls, and contexts of investigations may vary depending on the investigators and laboratories. The curators cannot have control over the quality of the way publicly available data is generated. We urge the biomedical community to participate in improving the pathway annotations by reporting any errors of omission/commission, which will help revise these signaling pathways.

Conclusions

The depiction of molecular reactions induced by GDF15, which are reported from multiple laboratories under diverse experimental conditions into a single larger network of GDF15 as a signaling pathway resource, along with indications on its implications in different cancers, will provide a critical platform for designing further research investigations in this area. The accessibility of the GDF-15-mediated signaling pathway will assist researchers in biomedicine to comprehend the functions of various molecules controlled by GDF15 in the progression of cancers. We also demonstrated the pathway’s potential in functional enrichment studies and identified a compound of ‘Kanchanara Guggulu’ through molecular docking that could target the binding of GDF15 to GFRAL, filling a critical gap in available inhibitors. This work provides a foundation for further investigation into GDF15 signaling and its therapeutic targeting.

Supplementary Information

Additional file1 (XLSX 428 KB) (427.8KB, xlsx)
Additional file2 (XLSX 1498 KB) (1.5MB, xlsx)
Additional file3 (DOC 37 KB) (36.5KB, doc)
Additional file4 (JPG 1418 KB) (1.4MB, jpg)
Additional file5 (DOC 286 KB) (286KB, doc)
Additional file6 (DOCX 14 KB) (14.2KB, docx)

Acknowledgements

We thank Karnataka Biotechnology and Information Technology Services (KBITS), Government of Karnataka, for the support to the Center for Systems Biology and Molecular Medicine (CSBMM) at Yenepoya (Deemed to be University) under the Biotechnology Skill Enhancement Programme in Multiomics Technology (BiSEP GO ITD 02 MDA 2017). We also acknowledge and thank the Department of Biotechnology (DBT) National Facility grant for supporting the CSBMM at Yenepoya (Deemed to be University), particularly through the project "Skill Development in Mass Spectrometry-based Metabolomics Technology BIC" (BT/PR40202/BTIS/137/53/2023). We also thank the Indian Council of Medical Research (ICMR), Government of India, for designating our Center as ICMR- Collaborating Centre of Excellence 2024 (ICMR-CCoE) in recognition of the commendable achievements in biomedical research.

Abbreviations

ACSL1

Acyl-CoA synthetase long chain family member 1

AKT1

AKT serine/threonine Kinase 1

BC

Breast cancer

CDH1

Cadherin 1

CDH2

Cadherin 2

CDKN1A

Cyclin dependent kinase inhibitor 1A

CPT1A

Carnitine palmitoyltransferase 1A

CPT1B

Carnitine palmitoyltransferase 1B

CPT2

Carnitine palmitoyltransferase 2

CRC

Colorectal cancer

EGFR

Epidermal growth factor receptor

EMT

Epithelial-mesenchymal transition

ERBB2

Erb-B2 receptor tyrosine kinase 2

GDF15

Growth differentiation factor 15

GFRAL

GDNF family receptor alpha like

HNC

Head and neck cancer

IGF1R

Insulin like growth factor 1 receptor

MAPK1

Mitogen-activated protein kinase 1

MAPK14

Mitogen-activated protein kinase 14

MAPK3

Mitogen-activated protein kinase 3

NDRG1

N-Myc Downstream Regulated 1

PPARGC1A

PPARG coactivator 1 alpha

PTM

Post-translational modification

rhGDF15

Recombinant human GDF15

Ser

Serine

SERPINB5

Serpin family B member 5

SMAD2

SMAD family member 2

SMAD3

SMAD family member 3

SNAI1

Snail family transcriptional repressor 1

SOX2

SRY-Box transcription factor 2

TGFBR2

Transforming growth

Author contributions

T.S.K.P., S.D., and R.R. conceived the idea and designed the work. A.B.R. performed the data curation, data analysis, drafted the manuscript, and prepared figures. S.G.P. performed the data curation. J.A.K.C. and R.R. participated in the manuscript review. K.N.H. performed metabolomic data analysis. C.S.A. performed molecular docking. T.S.K.P. and S.D. critically reviewed and edited the pathway map and manuscript. All authors read and approved the final version of the manuscript.

Funding

No funding was received for conducting this study.

Data availability

The manually-assembled signaling pathway data is provided in the ‘.xlsx’ format (Online Resource 1). The pathway visualized using the PathVisio tool is provided as supplementary material in the file GDF15_pathway.doc. The corresponding '.gpml' format is available upon request and can be converted to international data exchange formats such as BioPAX, PSI-MI, and SBML. The analyzed metabolomics data is provided in ‘.xlsx’ format (Online Resource 2).

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Jalaluddin Akbar Kandel Codi, Email: akbar21.Ja@gmail.com.

Shobha Dagamajalu, Email: shobha_d@yenepoya.edu.in.

Thottethodi Subrahmanya Keshava Prasad, Email: keshav@yenepoya.edu.in, Email: tskprasad@gmail.com.

References

  • 1.Emmerson PJ, Duffin KL, Chintharlapalli S, et al. GDF15 and growth control. Front Physiol. 2018;9:1712. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Spanopoulou A, Gkretsi V. Growth differentiation factor 15 (GDF15) in cancer cell metastasis: from the cells to the patients. Clin Exp Metastasis. 2020;37(4):451–64. [DOI] [PubMed] [Google Scholar]
  • 3.Breit SN, Brown DA, Tsai VW. The GDF15-GFRAL pathway in health and metabolic disease: friend or foe? Annu Rev Physiol. 2021;83:127–51. [DOI] [PubMed] [Google Scholar]
  • 4.Rochette L, Zeller M, Cottin Y, et al. Insights into mechanisms of GDF15 and receptor GFRAL: therapeutic targets. Trends Endocrinol Metab. 2020;31(12):939–51. [DOI] [PubMed] [Google Scholar]
  • 5.Wischhusen J, Melero I, Fridman WH. Growth/differentiation factor-15 (GDF-15): from biomarker to novel targetable immune checkpoint. Front Immunol. 2020;11:951. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Wang D, Day EA, Townsend LK, et al. GDF15: emerging biology and therapeutic applications for obesity and cardiometabolic disease. Nat Rev Endocrinol. 2021;17(10):592–607. [DOI] [PubMed] [Google Scholar]
  • 7.Yang L, Chang CC, Sun Z, et al. GFRAL is the receptor for GDF15 and is required for the anti-obesity effects of the ligand. Nat Med. 2017;23(10):1158–66. [DOI] [PubMed] [Google Scholar]
  • 8.Hohensinner PJ, Niessner A, Huber K, et al. Inflammation and cardiac outcome. Curr Opin Infect Dis. 2011;24(3):259–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Silva-Bermudez LS, Kluter H, Kzhyshkowska JG. Macrophages as a Source and Target of GDF-15. Int J Mol Sci. 2024;25(13):7313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Johann K, Kleinert M, Klaus S. The role of GDF15 as a myomitokine. Cells. 2021;10(11):2990. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Assadi A, Zahabi A, Hart RA. GDF15, an update of the physiological and pathological roles it plays: a review. Pflugers Arch. 2020;472(11):1535–46. [DOI] [PubMed] [Google Scholar]
  • 12.Xue Y, Zhang Y, Su Y, et al. The implicated role of GDF15 in gastrointestinal cancer. Eur J Clin Invest. 2024;54(11): e14290. [DOI] [PubMed] [Google Scholar]
  • 13.Min KW, Liggett JL, Silva G, et al. NAG-1/GDF15 accumulates in the nucleus and modulates transcriptional regulation of the Smad pathway. Oncogene. 2016;35(3):377–88. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Baek SJ, Eling T. Growth differentiation factor 15 (GDF15): a survival protein with therapeutic potential in metabolic diseases. Pharmacol Ther. 2019;198:46–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Adela R, Banerjee SK. GDF-15 as a target and biomarker for diabetes and cardiovascular diseases: a translational prospective. J Diabetes Res. 2015;2015: 490842. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Larsson K, Hoglund M, Larsson A, et al. Increased levels of the cardiovascular disease risk biomarkers GDF15 and myostatin in patients with chronic lymphocytic leukemia. Growth Factors. 2020;38(3–4):189–96. [DOI] [PubMed] [Google Scholar]
  • 17.Ouyang J, Isnard S, Lin J, et al. GDF-15 as a weight watcher for diabetic and non-diabetic people treated with metformin. Front Endocrinol (Lausanne). 2020;11: 581839. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Zhu X, Olson B, Keith D, et al. GDF15 and LCN2 for early detection and prognosis of pancreatic cancer. Transl Oncol. 2024;50: 102129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.He Y, Zhang X, Zhang Y, et al. Growth differentiation factor 15 is required for triple-negative breast cancer cell growth and chemoresistance. Anticancer Drugs. 2023;34(3):351–60. [DOI] [PubMed] [Google Scholar]
  • 20.Lu L, Ma GQ, Liu XD, et al. Correlation between GDF15, MMP7 and gastric cancer and its prognosis. Eur Rev Med Pharmacol Sci. 2017;21(3):535–41. [PubMed] [Google Scholar]
  • 21.Suzuki H, Mitsunaga S, Ikeda M, et al. Clinical and tumor characteristics of patients with high serum levels of growth differentiation factor 15 in advanced pancreatic cancer. Cancers (Basel). 2021;13(19):4842. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Li C, Wang J, Kong J, et al. GDF15 promotes EMT and metastasis in colorectal cancer. Oncotarget. 2016;7(1):860–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Mimeault M, Johansson SL, Batra SK. Pathobiological implications of the expression of EGFR, pAkt, NF-kappaB and MIC-1 in prostate cancer stem cells and their progenies. PLoS One. 2012;7(2): e31919. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Chen SJ, Karan D, Johansson SL, et al. Prostate-derived factor as a paracrine and autocrine factor for the proliferation of androgen receptor-positive human prostate cancer cells. Prostate. 2007;67(5):557–71. [DOI] [PubMed] [Google Scholar]
  • 25.Raju R, Balakrishnan L, Nanjappa V, et al. A comprehensive manually curated reaction map of RANKL/RANK-signaling pathway. Database (Oxf). 2011;2011:bar21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Raju R, Gadakh S, Gopal P, et al. Differential ligand-signaling network of CCL19/CCL21-CCR7 system. Database (Oxf). 2015;2015:bar106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Dagamajalu S, Rex DAB, Suchitha GP, et al. The network map of Elabela signaling pathway in physiological and pathological conditions. J Cell Commun Signal. 2022;16(1):145–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Gable AL, Szklarczyk D, Lyon D, et al. Systematic assessment of pathway databases, based on a diverse collection of user-submitted experiments. Brief Bioinform. 2022. 10.1093/bib/bbac355. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Behera SK, Modi PK, Karthikkeyan G, et al. From LC-MS/MS metabolomics profiling of Kanchanara Guggulu to molecular docking and dynamics simulation of quercetin pentaacetate with aldose reductase. Bioinformation. 2021;17(11):911–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Tomar P, Dey YN, Sharma D, et al. Cytotoxic and antiproliferative activity of kanchnar guggulu, an Ayurvedic formulation. J Integr Med. 2018;16(6):411–7. [DOI] [PubMed] [Google Scholar]
  • 31.Kandasamy K, Mohan SS, Raju R, et al. NetPath: a public resource of curated signal transduction pathways. Genome Biol. 2010;11(1):R3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Kandasamy K, Keerthikumar S, Raju R, et al. PathBuilder–open source software for annotating and developing pathway resources. Bioinformatics. 2009;25(21):2860–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Raju R, Nanjappa V, Balakrishnan L, et al. NetSlim: high-confidence curated signaling maps. Database (Oxf). 2011;2011:bar032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Kutmon M, van Iersel MP, Bohler A, et al. PathVisio 3: an extendable pathway analysis toolbox. PLoS Comput Biol. 2015;11(2): e1004085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Rex DAB, Deepak K, Vaid N, et al. A modular map of Bradykinin-mediated inflammatory signaling network. J Cell Commun Signal. 2022;16(2):301–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Sahu A, Gopalakrishnan L, Gaur N, et al. The 5-hydroxytryptamine signaling map: an overview of serotonin-serotonin receptor mediated signaling network. J Cell Commun Signal. 2018;12(4):731–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Sandhya VK, Raju R, Verma R, et al. A network map of BDNF/TRKB and BDNF/p75NTR signaling system. J Cell Commun Signal. 2013;7(4):301–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Pinto SM, Subbannayya Y, Rex DAB, et al. A network map of IL-33 signaling pathway. J Cell Commun Signal. 2018;12(3):615–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Yelamanchi SD, Jayaram S, Thomas JK, et al. A pathway map of glutamate metabolism. J Cell Commun Signal. 2016;10(1):69–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Du X, Smirnov A, Pluskal T, et al. Metabolomics data preprocessing using ADAP and MZmine 2. Methods Mol Biol. 2020;2104:25–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Behera SK, Kasaragod S, Karthikkeyan G, et al. MS2Compound: a user-friendly compound identification tool for LC-MS/MS-based metabolomics data. OMICS. 2021;25(6):389–99. [DOI] [PubMed] [Google Scholar]
  • 42.Hawkins C, Ginzburg D, Zhao K, et al. Plant metabolic network 15: a resource of genome-wide metabolism databases for 126 plants and algae. J Integr Plant Biol. 2021;63(11):1888–905. [DOI] [PubMed] [Google Scholar]
  • 43.Wishart DS, Tzur D, Knox C, et al. HMDB: the Human Metabolome Database. Nucleic Acids Res. 2007;35(Database issue):D521-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.de Jonge NF, Louwen JJR, Chekmeneva E, et al. MS2Query: reliable and scalable MS(2) mass spectra-based analogue search. Nat Commun. 2023;14(1):1752. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Dong XC, Xu DY. Research progress on the role and mechanism of GDF15 in body weight regulation. Obes Facts. 2024;17(1):1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Tsui KH, Chang YL, Feng TH, et al. Growth differentiation factor-15 upregulates interleukin-6 to promote tumorigenesis of prostate carcinoma PC-3 cells. J Mol Endocrinol. 2012;49(2):153–63. [DOI] [PubMed] [Google Scholar]
  • 47.Zhao TC, Zhou ZH, Ju WT, et al. Mechanism of sensitivity to cisplatin, docetaxel, and 5-fluorouracil chemoagents and potential erbB2 alternatives in oral cancer with growth differentiation factor 15 overexpression. Cancer Sci. 2022;113(2):478–88. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Li S, Ma YM, Zheng PS, et al. GDF15 promotes the proliferation of cervical cancer cells by phosphorylating AKT1 and Erk1/2 through the receptor ErbB2. J Exp Clin Cancer Res. 2018;37(1):80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Si Y, Liu X, Cheng M, et al. Growth differentiation factor 15 is induced by hepatitis C virus infection and regulates hepatocellular carcinoma-related genes. PLoS One. 2011;6(5): e19967. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Tsui KH, Hsu SY, Chung LC, et al. Growth differentiation factor-15: a p53- and demethylation-upregulating gene represses cell proliferation, invasion, and tumorigenesis in bladder carcinoma cells. Sci Rep. 2015;5:12870. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Jin Y, Jung SN, Lim MA, et al. Transcriptional regulation of GDF15 by EGR1 promotes head and neck cancer progression through a positive feedback loop. Int J Mol Sci. 2021;22(20):11151. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Li YL, Chang JT, Lee LY, et al. GDF15 contributes to radioresistance and cancer stemness of head and neck cancer by regulating cellular reactive oxygen species via a SMAD-associated signaling pathway. Oncotarget. 2017;8(1):1508–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Kalli M, Voutouri C, Minia A, et al. Mechanical compression regulates brain cancer cell migration through MEK1/Erk1 pathway activation and GDF15 expression. Front Oncol. 2019;9:992. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Peng H, Li Z, Fu J, et al. Growth and differentiation factor 15 regulates PD-L1 expression in glioblastoma. Cancer Manag Res. 2019;11:2653–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Zhu S, Yang N, Guan Y, et al. GDF15 promotes glioma stem cell-like phenotype via regulation of ERK1/2-c-Fos-LIF signaling. Cell Death Discov. 2021;7(1):3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Park H, Nam KS, Lee HJ, et al. Ionizing radiation-induced GDF15 promotes angiogenesis in human glioblastoma models by promoting VEGFA expression through p-MAPK1/SP1 signaling. Front Oncol. 2022;12: 801230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Hou CP, Tsui KH, Chen ST, et al. The upregulation of caffeic acid phenethyl ester on growth differentiation factor 15 inhibits transforming growth factor beta/smad signaling in bladder carcinoma cells. Biomedicines. 2022;10(7):1625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Peake BF, Eze SM, Yang L, et al. Growth differentiation factor 15 mediates epithelial mesenchymal transition and invasion of breast cancers through IGF-1R-FoxM1 signaling. Oncotarget. 2017;8(55):94393–406. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Joshi JP, Brown NE, Griner SE, et al. Growth differentiation factor 15 (GDF15)-mediated HER2 phosphorylation reduces trastuzumab sensitivity of HER2-overexpressing breast cancer cells. Biochem Pharmacol. 2011;82(9):1090–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Sasahara A, Tominaga K, Nishimura T, et al. An autocrine/paracrine circuit of growth differentiation factor (GDF) 15 has a role for maintenance of breast cancer stem-like cells. Oncotarget. 2017;8(15):24869–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Wollmann W, Goodman ML, Bhat-Nakshatri P, et al. The macrophage inhibitory cytokine integrates AKT/PKB and MAP kinase signaling pathways in breast cancer cells. Carcinogenesis. 2005;26(5):900–7. [DOI] [PubMed] [Google Scholar]
  • 62.Kim KK, Lee JJ, Yang Y, et al. Macrophage inhibitory cytokine-1 activates AKT and ERK-1/2 via the transactivation of ErbB2 in human breast and gastric cancer cells. Carcinogenesis. 2008;29(4):704–12. [DOI] [PubMed] [Google Scholar]
  • 63.Guo Y, Ayers JL, Carter KT, et al. Senescence-associated tissue microenvironment promotes colon cancer formation through the secretory factor GDF15. Aging Cell. 2019;18(6): e13013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Zheng H, Wu Y, Guo T, et al. Hypoxia induces growth differentiation factor 15 to promote the metastasis of colorectal cancer via PERK-eIF2alpha signaling. Biomed Res Int. 2020;2020:5958272. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Zheng H, Yu S, Zhu C, et al. HIF1alpha promotes tumor chemoresistance via recruiting GDF15-producing TAMs in colorectal cancer. Exp Cell Res. 2021;398(2): 112394. [DOI] [PubMed] [Google Scholar]
  • 66.Lee J, Fricke F, Warnken U, et al. Reconstitution of TGFBR2-mediated signaling causes upregulation of GDF-15 in HCT116 colorectal cancer cells. PLoS One. 2015;10(6): e0131506. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Proutski I, Stevenson L, Allen WL, et al. Prostate-derived factor–a novel inhibitor of drug-induced cell death in colon cancer cells. Mol Cancer Ther. 2009;8(9):2566–74. [DOI] [PubMed] [Google Scholar]
  • 68.Urakawa N, Utsunomiya S, Nishio M, et al. GDF15 derived from both tumor-associated macrophages and esophageal squamous cell carcinomas contributes to tumor progression via Akt and Erk pathways. Lab Invest. 2015;95(5):491–503. [DOI] [PubMed] [Google Scholar]
  • 69.Okamoto M, Koma YI, Kodama T, et al. Growth Differentiation factor 15 promotes progression of esophageal squamous cell carcinoma via TGF-beta type II receptor activation. Pathobiology. 2020;87(2):100–13. [DOI] [PubMed] [Google Scholar]
  • 70.Wang W, Yang X, Dai J, et al. Prostate cancer promotes a vicious cycle of bone metastasis progression through inducing osteocytes to secrete GDF15 that stimulates prostate cancer growth and invasion. Oncogene. 2019;38(23):4540–59. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Nazarova N, Qiao S, Golovko O, et al. Calcitriol-induced prostate-derived factor: autocrine control of prostate cancer cell growth. Int J Cancer. 2004;112(6):951–8. [DOI] [PubMed] [Google Scholar]
  • 72.Wang R, Wen P, Yang G, et al. N-glycosylation of GDF15 abolishes its inhibitory effect on EGFR in AR inhibitor-resistant prostate cancer cells. Cell Death Dis. 2022;13(7):626. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.Yu S, Li Q, Yu Y, et al. Activated HIF1alpha of tumor cells promotes chemoresistance development via recruiting GDF15-producing tumor-associated macrophages in gastric cancer. Cancer Immunol Immunother. 2020;69(10):1973–87. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74.Duan L, Pang HL, Chen WJ, et al. The role of GDF15 in bone metastasis of lung adenocarcinoma cells. Oncol Rep. 2019;41(4):2379–88. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Additional file1 (XLSX 428 KB) (427.8KB, xlsx)
Additional file2 (XLSX 1498 KB) (1.5MB, xlsx)
Additional file3 (DOC 37 KB) (36.5KB, doc)
Additional file4 (JPG 1418 KB) (1.4MB, jpg)
Additional file5 (DOC 286 KB) (286KB, doc)
Additional file6 (DOCX 14 KB) (14.2KB, docx)

Data Availability Statement

The manually-assembled signaling pathway data is provided in the ‘.xlsx’ format (Online Resource 1). The pathway visualized using the PathVisio tool is provided as supplementary material in the file GDF15_pathway.doc. The corresponding '.gpml' format is available upon request and can be converted to international data exchange formats such as BioPAX, PSI-MI, and SBML. The analyzed metabolomics data is provided in ‘.xlsx’ format (Online Resource 2).

Articles from Discover Oncology are provided here courtesy of Springer

RESOURCES