GDF15 propeptide promotes bone metastasis of castration-resistant prostate cancer by augmenting the bone microenvironment

GDF15 propeptide promotes bone metastasis of castration-resistant prostate cancer by augmenting the bone microenvironment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article GDF15 propeptide promotes bone metastasis of castration-resistant prostate cancer by augmenting the bone microenvironment Gaku Yamamichi, Taigo Kato, Noriaki Arakawa, Yoko Ino, Takeshi Ujike, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4834587/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Nov, 2024 Read the published version in Biomarker Research → Version 1 posted 13 You are reading this latest preprint version Abstract Background Bone metastasis (BM) is a common and fatal condition in patients with castration-resistant prostate cancer (CRPC). However, there are no useful blood biomarkers for CRPC with BM, and the mechanism underlying BM is unclear. In this study, we investigated precise blood biomarkers for evaluating BM that can improve the prognosis of patients with CRPC. Methods We comprehensively examined culture supernatants from four prostate cancer (PCa) cell lines using Orbitrap mass spectrometry to identify specific proteins secreted abundantly by PCa cells. The effects of this protein to PCa cells, osteoblasts, osteoclasts were examined, and BM mouse model. In addition, we measured the plasma concentration of this protein in CRPC patients for whom bone scan index (BSI) by bone scintigraphy was performed. Results A total of 2,787 proteins were identified by secretome analysis. We focused on GDF15 propeptide (GDPP), which is secreted by osteoblasts, osteoclasts, and PCa cells. GDPP promoted the proliferation, invasion, and migration of PC3 and DU145 CRPC cells, and GDPP aggravated BM in a mouse model. Importantly, GDPP accelerated bone formation and absorption in the bone microenvironment by enhancing the proliferation of osteoblasts and osteoclasts by upregulating individual transcription factors such as RUNX2 , OSX , ATF4 , NFATc1 , and DC-STAMP . In clinical settings, including a total of 386 patients, GDPP was more diagnostic of BM than prostate-specific antigen (PSA) (AUC = 0.92 and 0.78) and the seven other blood biomarkers (alkaline phosphatase, lactate dehydrogenase, bone alkaline phosphatase, tartrate-resistant acid phosphatase 5b, osteocalcin, procollagen I N-terminal propeptide and mature GDF15) in patients with CRPC. The changes in BSI over time with systemic treatment were correlated with that of GDPP (r = 0.63) but not with that of PSA (r = -0.16). Conclusions GDPP promotes a vicious cycle in the BM microenvironment and is a novel blood biomarker of BM in CRPC, which could lead to early treatment interventions in patients with CRPC. castration-resistant prostate cancer bone metastasis GDF15 biomarker Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Prostate cancer (PCa) is currently the most commonly diagnosed malignancy in the male population in more than half of the countries worldwide, with an incidence of approximately 1.4 million cases per year, and is the second leading cause of cancer-related deaths among men ( 1 , 2 ). Although first-line treatments, including androgen deprivation therapy for metastatic hormone-sensitive prostate cancer (mHSPC), are initially highly effective in decreasing the levels of the standard indicator of PCa progression, namely, prostate-specific antigen (PSA), and in shrinking tumors, therapeutic resistance is almost universal, and the disease often progresses to metastatic castration-resistant prostate cancer (mCRPC). Generally, PCa has the highest incidence of bone metastases (BM) among cancers, with 6–8% of new PCa patients having BM at first diagnosis ( 3 , 4 ) and more than 90% of patients with CRPC developing BM ( 5 ). However, to date, no useful blood biomarkers for diagnosing and monitoring the BM due to CRPC have been identified ( 6 – 8 ) because CRPC is highly heterogeneous and consists of a mixture of androgen-dependent and androgen-independent PCa. In addition, approximately 20% of PCa cases are accompanied by neuroendocrine alterations during the treatment course ( 9 ), which is associated with difficulty in assessing disease progression solely based on PSA levels ( 10 – 13 ), suggesting that the evaluation of PSA levels is not sufficient to accurately predict BM status ( 14 , 15 ). Bone scintigraphy is often used to evaluate BM volume in patients with CRPC in combination with laboratory parameters, including alkaline phosphatase (ALP) ( 16 ). However, bone scintigraphy has several disadvantages, such as high cost and radiation exposure, resulting in difficulty in frequent measurements ( 7 ). In this context, accurate and noninvasive biomarkers of BM are urgently required. Growth differentiation factor 15 (GDF15), also known as macrophage inhibitory cytokine 1 and NSAID-activated gene-1, is a member of the transforming growth factor β (TGF-β) superfamily ( 17 ). Among various types of cancers, PCa exhibits the highest GDF15 transcript expression ( 18 ). The GDF15 gene encodes a 308-aa peptide (pre-pro-GDF15) consisting of an N-terminal signal peptide, a mature domain (mGDF15), and a propeptide domain, which we named the GDF15-derived propeptide GDPP. The pro-GDF15 precursor is secreted as a homodimer from the endoplasmic reticulum. The active mature form, mGDF15, is released via the proteolytic cleavage of dimeric pro-GDF15 at a furin-like site (RXXR) ( 19 – 21 ). A recent study showed that mGDF15 binds to glial cell-derived neurotrophic factor family receptor alpha-like, is involved in PI3K/Akt/mTOR pathway activation, and participates in various physiological processes such as weight loss. In contrast, the GDPP domain is thought to be involved in the recognition and disposal of pre-pro-GDF15, depending on whether it is correctly folded, and processing of the precursor within the cell ( 22 ). However, no attention has been paid to the free GDPP domain released after its detachment from the mGDF15 domain, resulting in a lack of reports on the physiological functions and extracellular dynamics of free GDPP. In this study, we aimed to identify a convenient and accurate diagnostic biomarker that can enable the monitoring of BM in patients with CRPC and found that the newly identified protein “GDPP” promotes PCa progression and bone formation and resorption via the upregulation of transcription factor expression in the bone microenvironment, suggesting that plasma GDPP is a novel biomarker that reflects BM status more accurately than PSA in patients with CRPC and BM. Collectively, we believe that compared with traditional imaging tests, GDPP detection will reshape the diagnosis of BM. Materials and Methods Secretome analysis Proteomic analysis of culture medium from the PCa cell lines, described in Supplemental Materials “Cell culture and maintenance’’, was performed as previously described ( 23 ). In brief, the PCa cell lines were cultured under the recommended conditions until they reached 60% confluency. Then, the media were replaced with serum-free media, and cells were incubated for 48 h. The culture media were then collected and lyophilized. The lyophilized media were dissolved in 10 mM ammonium bicarbonate containing 4 M urea, and proteins were desalted by acetone precipitation. The precipitated protein was resuspended in 25 mM ammonium bicarbonate containing 4 M urea and 0.1% RapiGest detergent (Nihon Waters, Tokyo, Japan) and subsequently digested with trypsin for 16 h at 37°C after reduction, alkylation and dilution. The resulting peptides were desalted using C18 Stage Tips ( 24 ) and analyzed on an LTQ Orbitrap Velos (Thermo Fisher Scientific) equipped with a reverse-phase LC system. Peptides were detected sequentially in positive ion mode for MS/MS in data-dependent scanning mode and identified using Proteome Discoverer 2.5 software (Thermo Scientific) and the Swiss-Prot human database ( www.uniprot.org/proteomes/UP000005640 ) with the following parameters: enzyme, trypsin; peptide mass tolerance, ± 5 ppm; fragment mass tolerance, ± 0.5 Da; maximum missed cleavage sites, 2; variable modifications: oxidation of methionine, acetylation and/or loss of methionine at N-terminus; and static modification: carbamidomethylation of cysteine. Mass spectrometry proteomics data were deposited to the ProteomeXchange Consortium (PXD045369, http://www.proteomexchange.org/ ) via the jPOST partner repository (JPST002261, https://jpostdb.org/ ). Structure modeling with AlphaFold2 Structure predictions for pre-pro-GDF15, GDPP and mGDF15 were generated by the AlphaFold2 ( https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb , accessed on 4 June 2023) model using the relevant online resources with their default settings ( 25 , 26 ). Open source RNA-sequencing analysis RNA-seq transcriptome data of various cancer patients, including 493 PCa, 407 bladder cancer, 510 renal cell carcinoma, 1082 breast cancer, 484 lung cancer, 592 colon cancer, 443 melanoma, 412 gastric cancer, 366 liver cancer, 527 uterine cancer, 181 esophageal cancer, 515 head and neck carcinoma, 514 glioma and 177 pancreatic cancer patients, were downloaded from the TCGA database in 2018. Immunofluorescence staining LNCaP cells were seeded in 2-well chamber slides (5712-002, IWAKI) at a density of 3 × 10 5 cells/1.5 ml/well and incubated overnight at 37°C in a humidified atmosphere containing 5% CO 2 . The cells were then washed with PBS and fixed with 4% paraformaldehyde for 15 minutes on ice. After permeabilization with 0.1% Triton X-100 (87361, Muto Pure Chemicals Co., Ltd.) in PBS at room temperature for 15 minutes, the cells were incubated with primary antibodies diluted in PBS-T overnight at 4°C. The primary antibodies used were a rabbit anti-GDPP polyclonal antibody (HPA011191, Sigma‒Aldrich, 1:200) and a mouse anti-mGDF15 monoclonal antibody (sc-515675, Santa Cruz Biotechnology, 1:50). After PBS washes, the slides were incubated with the appropriate secondary antibodies, Alexa Fluor 488 goat anti-mouse secondary antibody (A-11001, Invitrogen) and Alexa Fluor 568 goat anti-rabbit secondary antibody (A-11011, Invitrogen), both diluted in PBS-T (1:500), for 1.5 hours at room temperature. The slides were then washed with PBS-T at 22°C and counterstained with ProLong Gold Antifade reagent with DAPI (P36931, Invitrogen). The stained LNCaP cells were examined using a fluorescence microscope (BZ-X710, KEYENCE). Rabbit polyclonal IgG (NBP2-24891, Novus) and mouse monoclonal IgG (ab18469, Abcam) were used as isotype controls for the respective antibodies. Human sample collection and data We collected human serum, plasma and tissue samples, such as PCa and bone samples, from healthy donors and PCa patients at Osaka University from December 2012 to December 2022. Total 386 patients (30 healthy donors, 60 localized PCa patients, 15 mCRPC patients without BM, 80 mCRPC patients with BM, 22 mCRPC patients with BM whose blood samples were collected over time and 179 PCa patients who underwent radical prostatectomy), we collected clinical information retrospectively. Whole blood (2.0–7.0 ml) was collected directly into Venoject Ⅱ EDTA-2Na tubes (TERUMO) for plasma samples, and whole blood (2.0–7.0 ml) was collected directly into Venoject Ⅱ tubes (TERUMO) for serum samples. Within three hours of collection, all plasma samples were centrifuged sequentially at 900 and 20,000 × g for 10 min each, and the supernatants were stored at − 80°C as plasma. All serum samples were centrifuged at 3000 rotations per minute (rpm) for 5 min, and the supernatants were stored at -80°C as serum. Serum PSA (Beckman Coulter), ALP (Shino-Test Corporation), BAP (IDS, Inc.), TRACP 5b (Nittobo Medical), LDH (FUJIFILM Wako Pure Chemical Corporation), OC (Tosoh), mGDF15 (R&D Systems) and PⅠNP (USCN) levels were measured in the same blood samples. Bone scan index (BSI) was assessed within two months of both blood collection time points. Bone scintigraphy All PCa patients were injected intravenously with 740 MBq of 99mTc MDP to evaluate the existence of BM. Three hours after injection, a whole-body bone scan was performed with a gamma camera equipped with a low-energy high-resolution parallel hole collimator in anterior and posterior views. The raw image data set was analyzed with the software package BONENAVI version 2, based on a personal database in Japan. This CAD system was used to calculate the BSI, which was calculated as a percentage of the sum of all spots classified as bone metastases in the patient's body. When the attending physician deemed it necessary especially for CRPC patients, it was taken about once every three month and their data was retrospectively analyzed. Establishment of an ELISA system to measure GDPP Anti-GDPP monoclonal antibodies targeting the GDF15 propeptide, namely, GD11-13 and GD01-62, were generated using a plasmid DNA immunization method, as we reported previously ( 27 ). These antibodies specifically recognize the central region of GDPP. To detect GDPP, a combination of GD11-13, immobilized on magnetic microparticles, and GD01-62, labeled with alkaline phosphatase, was employed. AIA-CL reagent (Tosoh) was developed based on the two-step sandwich enzyme immunoassay technique. Using the fully automated chemiluminescent enzyme immunoassay system (AIA-CL2400, Tosoh), sample dispensing, immunoreaction, B/F separation, substrate addition, and luminescence detection were performed automatically, and results were obtained in approximately 15 minutes. Cell culture and maintenance LNCaP and DU145 cells were purchased from RIKEN BRC CELL BANK, 22Rv1 and PC3 cells were purchased from the American Type Culture Collection (ATCC). All cell lines were maintained in basal culture medium (RPMI1640) (Nacalai Tesque) with 10% fetal bovine serum (FBS), 100 U/mL penicillin G, and 0.1 µg/mL streptomycin in a humidified incubator set to 37°C and 5% CO 2 . PC3-Luc2 cells were also purchased from the ATCC and maintained in basal culture medium [Ham’s F-12K Kaighn’s medium, Gibco™; 10% FBS; 8 µg/mL Blasticidin S (Invitrogen)] in a humidified incubator set to 37°C and 5% CO2. MC3T3-E1 cells (RIKEN BRC Cell Bank) were maintained in basal culture medium (αMEM, Nacalai Tesque) with 10% FBS, 100 U/mL penicillin G, and 0.1 µg/mL streptomycin, MLO-Y4 cells (Kerafast) were cultured on type I collagen-coated dishes (Corning) and maintained in basal culture medium (αMEM with 5% heat inactivated FBS, 5% calf serum, 100 U/mL penicillin G, and 0.1 µg/mL streptomycin), and OSC14C cells (Cosmo Bio) were suspended in osteoclast culture medium (OSCMW and OSCMM, Cosmo Bio). HOB (PromoCell, lot number #469Z022, from cancellous bone/femoral head tissue collected from a 78-year-old Caucasian man) was cultured in osteoblast growth medium (C-27001, PromoCell), and OSC15C (Cosmo Bio, lot number #VJ2-F-OSH) was cultured in osteoclast wash medium (OSCMW, Cosmo Bio) and growth medium including receptor activator of NF-κB ligand and macrophage-colony stimulating factor (OSCMW, Cosmo Bio). HOB was used for functional analysis with a maximum of five passages allowed for cell culture. OSC14C and OSC15C differentiation into mature osteoclasts was confirmed by TRAP staining. A cell scraper (99002, Techno Plastic Products) was used to scrape off the cells. Analysis of secreted proteins in cell culture media To analyze the secreted proteins in culture media, we seeded 5×10 5 cells in 2 ml of serum-free medium into a 6-well dish and collected the culture medium 24 hours after seeding. This medium was passed through a filter (Millex-GV, SLGVR33RS, Merck), and the filtrate was collected after centrifugation at 6000×g for 30 minutes using a centrifugal concentrator (Vivaspin, VS2091, SARTORIUS). The GDPP concentration in the culture medium for each sample was measured in triplicate. In total, 5 × 10 5 LNCaP cells were seeded in 6-well dishes, and the medium was changed 24 hours later. Then 25 µM furin inhibitor (#14965, Cayman Chemical) was added for 24 hours, and the whole-cell lysate and culture medium were collected. Sodium dodecyl sulfate‒polyacrylamide gel electrophoresis (SDS‒PAGE) and western blotting For SDS ‒ PAGE, sample buffer containing 10% 2-mercaptoethanol was added to whole-cell lysates, generated using RIPA Lysis Buffer (Santa Cruz Biotechnology), or culture media, and proteins were resolved on 10% polyacrylamide mini gels (TEFCO). Afterward, proteins were transferred onto a polyvinylidene difluoride membrane using a semidry transfer system (Thermo Fisher Scientific). The membrane was then probed with the indicated specific antibodies that were utilized for immunological analysis: GDPP (1:1000, HPA011191, Sigma‒Aldrich), mGDF15 (1:1000, LS-C383688, LSBio), and β-actin (1:5000, 4967S, Cell Signaling Technology). The membrane was incubated with a horseradish peroxidase-conjugated secondary antibody against rabbit immunoglobulin (1:5000, Cell Signaling Technology). Finally, the membrane was subjected to detection with enhanced chemiluminescence western blotting detection reagents (Nacalai Tesque) and visualized using the ChemiDoc XRS Plus system (Bio-Rad) as a chemiluminescence detector. Development of human recombinant GDPP The sequence of human GDPP with a Strep-tag at the N-terminus was cloned and inserted into an expression vector, and the resulting plasmid was amplified and utilized to transfect Expi293 mammalian cells for Strep-GDPP expression. The transfected cells were cultured, and the culture medium was collected. The recombinant GDPP protein was purified from the culture medium using a Strep-tag purification kit (IBA Lifesciences) according to the manufacturer’s instructions. Immunohistochemical studies Both human and mouse bone metastasis specimens were demineralized using Tris-ethylenediaminetetraacetic acid (EDTA) demineralization solution until tissue softening was observed, followed by paraffin fixation. Immunohistochemical staining was performed in 4 µm-thick paraffin-embedded tissue samples. The human sample sections were treated with EDTA buffer (pH 9.0) and activated by warming at 125°C for 30 seconds using a Pascal pressure chamber (S2800, Dako) for antigen activation treatment. Endogenous peroxidase activity was blocked by incubating the sections with 0.3% hydrogen peroxide for 5 min, followed by overnight incubation with primary antibodies against GDPP (1:200; HPA011191, Sigma‒Aldrich) at 4°C, and staining was performed using DAB substrate (MK210, TaKaRa). Finally, the sections were counterstained with hematoxylin. In the mouse tibial bone tissue specimens, antigen activation treatment was performed with 3-fold diluted Proteinase K Ready-to-use (S3020, Dako). The sections were incubated overnight at 4°C with a primary antibody against the osteoblast marker OC (M188, Takara, diluted 100 times), followed by incubation with secondary anti-rat antibody (714311, Nichirei Bioscience, Inc.). Staining was performed using DAB substrate (MK210, TaKaRa). Osteoclasts were stained using a commercially available TRAP Staining Kit (AK04F, Cosmo Bio). Osteoclasts were identified as TRAP-positive multinucleated (three or more nuclei) cells, and osteoblasts and osteoclasts were counted on the trabecular bone matrix surface in three randomly selected fields of view using light microscopy (BZ-X710, KEYENCE). RNA interference For knockdown of GDF15 using small interfering RNA (siRNA), cells were transfected with 10 nM of either targeting FlexiTube GeneSolution (GS9518, Qiagen) or negative control Stealth RNAi™ (12935112, Invitrogen) using Lipofectamine® RNAiMAX Reagent (13778075, Invitrogen) for 24 hours. Then, the medium containing siRNA and transfection reagent was replaced with fresh medium. Following validation of GDF15 knockdown confirmed by western blotting method, functional assays were performed. Cell proliferation assay PC3 cells and HOB transfected with either siRNA targeting GDF15 or negative control for 72 h were reseeded in medium supplemented with 10% FBS in 96-well plates at 1 × 10 3 cells/100 µL/well and 1.3× 10 3 cells/100 µL/well, respectively; DU145 cells were seeded in the same medium in 96-well plates at 1 × 10 3 cells/100 µL/well. The cells were incubated for 1 hour at 37°C in a humidified 5% CO 2 atmosphere, and then 0.1 µl MT Cell Viability Substrate (G9712, Promega) and 0.1 µl NanoLuc® Enzyme (G9712, Promega) were added to each well. Luminescence was measured with a GloMax® Explorer System (GM3510, Promega) according to the manufacturer’s instructions after 24, 48, and 72 hours in a humidified incubator set to 37°C and 5% CO 2 ; this timepoint was set as 0 hours, and GDPP was added at this point. The assay was repeated three times for each experimental group. Wound-healing assay PC3 cells transfected with either siRNA targeting GDF15 or negative control siRNA for 72 h were reseeded in 6-well plates at 6 × 10 5 cells/2 mL/well, and DU145 cells were seeded in 6-well plates at 6 × 10 5 cells/2 mL/well. Cells were grown to a monolayer, and a wound was created by scraping the cell layer using a sterile 200-µL yellow pipette tip when the cells reached approximately 90% confluence. Detached cells were removed by washing plates with PBS and adding fresh culture medium supplemented with 10% FBS to each plate. Cells were treated with or without GDPP at this point and then incubated at 37°C with 5% CO 2 . Cell migration was evaluated using a fluorescence microscope (BZ-X710, KEYENCE) at 0 h and 20 h after wound generation and quantified by measuring the size of the recovered area using ImageJ 1.53e. The assay for each experimental group was repeated three times. Cell invasion assay PC3 cells transfected with either siRNA targeting GDF15 or negative control siRNA for 72 h and DU145 cells were seeded into the upper chambers of Corning® BioCoat™ Matrigel Invasion Chambers (pore size—8 µm) (354480, Corning) (5 × 10 4 cells/well) in serum-free medium, with medium supplemented with 10% FBS present in the lower chamber. GDPP was added immediately after cell seeding. After 36 h of incubation at 37°C and 5% CO 2 , the cells that had penetrated into the Matrigel matrix were fixed and stained using a Diff-Quik stain kit (Sysmex, Kobe, Japan), and cell invasion was quantified using a fluorescence microscope (BZ-X710, KEYENCE). The analysis was repeated three times for each experimental group. Quantitative real-time PCR Total RNA was extracted from HOB (treated with or without GDPP for 3 days) and OSC15C cells (treated with or without GDPP for 12 days) using the ISOSPIN Cell & Tissue RNA Kit (NIPPON GENE). After verification of RNA quality by NanoDrop One (Thermo Fisher Scientific), the RNA was subjected to cDNA synthesis using the Prime Script RT reagent Kit (Perfect Real Time; TaKaRa Bio). Quantitative RT‒PCR was performed using the Thermal Cycler Dice Real Time System (TP800; Takara) and THUNDERBIRD™ Next SYBR® qPCR Mix (TOYOBO). Target gene expression was normalized to that of the housekeeping gene GAPDH using the delta-delta Ct method. The primers used for the PCRs are listed in Table S1 , and all PCRs were performed in triplicate for each sample. ALP staining and assessment of activity HOB was seeded in 24-well plates and cultured on type I collagen-coated dishes (Corning) at 1×10 5 cells/0.5 ml/well with or without GDPP. After 5 days of incubation, for ALP staining, the cells were washed with PBS and fixed for 20 min with 10% formalin at room temperature. After fixation, the cells were incubated with an Alkaline Phosphatase Staining kit (AK20, Cosmo Bio Co., Ltd.) for 20 minutes at 37°C according to the manufacturer’s instructions. The total percentage of ALP + cells was determined using a fluorescence microscope. To measure ALP activity, HOB was seeded to 24-well plates and incubated with or without GDPP for 5 days. Then, WCLs were obtained as stated in the Supplementary Materials section “Sodium dodecyl sulfate‒polyacrylamide gel electrophoresis (SDS‒PAGE) and western blotting’’, and ALP activity was measured using p-nitrophenylphosphate as the substrate for the alkaline phosphatase test (QFAP-100, BioAssay System) according to the manufacturer’s instructions. The optical density (OD) of WCLs was measured in a 96-well plate at 405 nm with a microplate reader (iMARK™, Bio-Rad). The assay was repeated three times for each experimental group. Alizarin Red S staining and bone mineralization quantification Human primary osteoblasts (HOB) was seeded in 24-well plates and cultured on type I collagen-coated dishes (354408, Corning) at 3×10 4 cells/0.5 ml/well using Osteoblast Mineralization Medium (C-27020, PromoCell) with or without GDPP for 21 days. The cells were subsequently washed with PBS, fixed, stained and digested with an Alizarin Red S staining kit (BMK-R009, BMK, Bio Mirai Kobo). The total area of staining was quantified using a fluorescence microscope, and after staining, the OD of the eluted Alizarin Red S solution was measured in a 96-well plate at 405 nm with a microplate reader (iMARK™, Bio-Rad). The assay was repeated three times for each experimental group. TRAP staining and resorption pit assay Human-derived primary osteoclast precursor cells (OSC15C) was seeded in 24-well plates at 2×10 5 cells/0.5 ml/well with or without GDPP for 12 days. TRAP staining was performed using a TRAP staining kit (AK04F, Cosmo Bio) according to the manufacturer’s instructions, and the total number of TRAP-positive cells with ≥ 3 nuclei was determined using a fluorescence microscope as the average of five randomly observed fields of view. The resorption pit assay was performed using the Bone Resorption Assay Kit (BRA-48KIT, PG Research). OSC15C cells were seeded in a 48-well Bone Resorption Assay Plate 48 (BRA-48P, PG Research) at 8×10 4 cells/0.5 ml/well with or without GDPP for 12 days. The bone resorption area was quantified using a fluorescence microscope as the average of five randomly observed fields of view. The assay was repeated three times for each experimental group. Animal experiments with bone metastasis of prostate cancer Male NOD.CB17-Prkdc SCID /J mice, 5–6 weeks of age, were purchased from Japan Charles River Laboratories, Inc. All mice were euthanized under anesthesia using isoflurane. For intratibial implantation, 1 × 10 6 PC3-Luc2 cells, purchased from ATCC, were suspended in 5 µl of VitroGel Hydrogel Matrix (VHM01S, TheWell Bioscience LLC) and 5 µl of phosphate-buffered saline (PBS). Mice were anesthetized with isoflurane, and the cell suspension was directly injected into the intramedullary cavity of the right tibia. The cavity was reached by drilling into the cortical bone of the tibial tuberosity using a 22 G needle (NN-2232R, TERUMO) with a 1 ml 29G syringe containing a needle (08299, NIPRO). Then, the skin was closed with a 6–0 suture. Mice in the treatment group were subcutaneously injected with recombinant GDPP (refer to the section “Development of human recombinant GDPP’’) dissolved in saline at a concentration of 0.1 mg/kg every other day. Control mice were injected with an equal amount, and subsequent tumor growth was evaluated weekly with bioluminescence analysis via an In Vivo Imaging System (IVIS® Lumina II, Caliper). The mice were randomized into two groups for experiments: the control (n = 10) and GDPP groups (n = 10). Micro-CT and IVIS imaging The mice were imaged to visualize luciferase activity immediately after injection and were monitored weekly using IVIS® imaging. Bioluminescence images of tumor-bearing mice were acquired with an IVIS Spectrum 10 minutes after intraperitoneal injection of D-luciferin (XLF-1, Summit Pharmaceutical International Corporation, 100 mg/kg), with an exposure time of 10 seconds. As a quality control measure, the photon flux was measured by quantifying the number of highlighted pixels within a circular region of interest (ROI) for each mouse in the supine position. These values were then normalized to the signal intensity obtained immediately after xenografting in the same area (day 0) of each mouse. Thus, all mice had an arbitrary starting normalized bioluminescence signal intensity of 1. This normalization was performed using Living Image® software version 4.2 (Caliper Life Sciences, Inc.) following the manufacturer's instructions. Bioluminescence imaging was employed to assess tumor burden and the localization of PC3-Luc2 cells. The bone-destructive phenotype caused by PC3-Luc2 cells was visually evaluated macroscopically. Additionally, three-dimensional images were constructed to confirm the presence of bone infiltration using R_mCT2 software (Rigaku) for micro-CT imaging. Statistics The statistical analyses were performed using JMP Pro (v.17.0.0; SAS Institute, NC, USA). Univariate analysis included two-tailed Student's t-test and the Mann‒Whitney U test. Multiple comparisons were assessed using the Tukey‒Kramer method to compare several treatments. Spearman's rank correlation coefficient was used as a measure of the strength of the correlation between the two variables. Statistical significance was defined as p < 0.05. The optimal cutoff value for diagnosis was determined from the receiver operating characteristic curve using the Youden index, and sensitivity and specificity for diagnosis were calculated based on each optimal cutoff value. The cutoff values for the parameters used in the prognostic analysis are the respective medians. Results GDF15 propeptide is a unique secreted peptide in PCa cells To identify candidate proteins secreted by PCa cells that may be useful as blood biomarkers, we first performed secretome analysis of the culture media from four PCa cell lines (LNCaP, 22Rv1, PC3, and DU145) and proteomic analysis of the peptides obtained. We identified 17,798 peptides from 2,787 proteins in all culture media from PCa cell lines. These proteins included two well-known PCa biomarkers: PSA and prostatic acid phosphatase (PAP) ( 28 ) (Table S2). Among these secreted proteins, we focused on GDF15, which was identified in three of the four cell lines (LNCaP, 22Rv1, and PC3) (Fig. 1 A) because in neuroendocrine prostate cancer (NEPC), GDF15 is highly expressed and PSA levels do not clearly reflect disease progression ( 29 , 30 ). Additionally, our secretome analysis revealed peptides annotated to the mGDF15 domain in the C-terminal region and multiple peptides located in the GDPP domain of the N-terminal propeptide in the culture media (Fig. 1 B). GDF15 secreted more unique peptides than PSA from the three different PCa cell lines (LNCaP, 22Rv1 and PC3) (Table S2), and considering that there are no reports regarding the function of GDF15 propeptide in human blood, we focused on GDPP. Three-dimensional (3D) structural predictions showed spatial connectivity between the signal peptides, mGDF15 and GDPP (Fig. 1 C) ( 25 , 26 ). In addition, analysis of bulk RNA-seq data from The Cancer Genome Atlas (TCGA) database showed that the expression levels of GDF15 were the highest, and those of Furin , which cleaves the junction between the GDPP domain and the remainder of the mGDF15 sequence, were relatively higher in PCa than in other cancer types (Fig. S1 A, S1B). To examine the subcellular localization of GDPP, we investigated the intracellular spatial relationship between GDPP and mGDF15. Immunofluorescence staining of LNCaP cell blocks revealed co-localization of GDPP and mGDF15 in the cytoplasm (Fig. 1 D). To verify whether GDPP was truly present as a secreted protein and to determine its levels in various PCa cell lines, we performed western blot analysis and confirmed the exogenous expression of GDPP and mGDF15 in the culture media of LNCaP, 22Rv1, PC3 and DU145 cells, whereas only pro-GDF15 expression was detected in the whole-cell lysate (WCL) of LNCaP, 22Rv1, and PC3 cells (Fig. 1 E). These findings suggest the secretion of GDPP into the culture supernatant. In cell lines with high pro-GDF15 expression, both GDPP and mGDF15 were highly expressed in the culture supernatant. When a furin inhibitor was added to the LNCaP cells, neither GDPP nor mGDF15 was secreted into the culture medium; instead, pro-GDF15 accumulated within the treated LNCaP cells (Fig. S1 C). Consistent with the findings of the secretome and western blot analyses, LNCaP, 22Rv1, and PC3 cells secreted GDPP into the culture medium, whereas DU145 cells secreted very little GDPP (Fig. 1 F). Taken together, these findings indicate that the GDPP peptide is secreted by PCa cells into the extracellular space. GDPP is more useful than other blood biomarkers in CRPC patients with bone metastasis To examine the clinical relevance of GDPP, we measured GDPP levels in patients with CRPC for whom PSA levels were not considered reliable. The clinical characteristics of the patients are summarized in Table 1 . The data showed that there were significant increases in the plasma levels of GDPP and serum levels of PSA, mGDF15, and bone turnover markers such as BAP and LDH in CRPC patients with BM compared with PCa patients without BM (Fig. 2 A). Notably, receiver operating characteristic (ROC) analysis revealed that GDPP had the strongest diagnostic ability for BM of CRPC among these blood markers in the two cohorts, with an area under the curve (AUC) of 0.92 (Fig. 2 B, Table S3). Table 1 Patient baseline characteristics and blood biomarker levels Healthy donors n = 30 Localized PCa n = 60 mCRPC (BM-) n = 15 mCRPC (BM+) n = 80 Age (years) 63 (37–74) 69 (52–79) 73 (59–86) 74 (51–88) Gleason Score < 8 ≥ 8 - 53 7 6 9 16 64 pT stage pT2 pT3 - 48 12 - - Metastasis site Bone Lymph node Lung Liver Bladder Ureter - - 0 12 0 2 0 1 80 44 8 2 1 0 PSA (ng/ml) 0.96 (0-8.5) 6.5 (2.6–45.5) 5.6 (0-110.8) 17.7 (0-4782) ALP (U/l) 183 (45–292) 196 (107–442) 186 (60–334) 187 (37-4987) LDH (U/l) 172 (118–340) 175 (120–312) 183 (151–280) 211 (115–853) OC (ng/ml) 15.2 (4.5–22.0) 14.7 (3.6–35.8) 14.4 (6.1-38.31) 7.8 (1.2-109.5) BAP (µg/l) 18.4 (13.9–30.7) 22.2 (10.5–49.4) 19.4 (3.7–45.3) 22.5 (0.8-364.9) PⅠNP (ng/ml) 11.9 (6.5–24.6) 36.4 (14.8–72.2) 95.6 (21.5-192.2) 37.0 (3.9-280.9) TRACP 5b (mIU/dl) 286.2 (141.8-532.9) 276.0 (117.1-582.6) 357.0 (159.9-953.4) 237.0 (17.9–2795) mGDF15 (pg/ml) 626.7 (272.3-1802.9) 1331.3 (632.9-5020.9) 1731.3 (860.7-7266.1) 3718.0 (760.0-21351.5) GDPP (ng/ml) 2.8 (1.6–11.2) 4.5 (1.9–7.9) 9.0 (2.7–21.0) 15.3 (4.4-247.9) Next, we evaluated the correlation between the bone scan index (BSI), an objective, quantitative score calculated using a computer-aided diagnostic system (BONENAVI) for bone scintigraphy, to determine the volume of BM and blood biomarkers. The correlation between GDPP and BSI was the strongest (r = 0.66, p < 0.01) among all the blood biomarkers examined, including mGDF15 (r = 0.43) (Fig. 2 C). Next, we investigated the changes in GDPP levels (ΔGDPP) in the same CRPC patients with BM over time to determine the clinical utility of GDPP for longitudinal monitoring of BM (Table S4). The value of ΔGDPP was significantly associated with ΔBSI (r = 0.63, p < 0.01), but the changes in PSA levels (ΔPSA) and in all bone turnover markers, except BAP, were not correlated with ΔBSI (Fig. 2 D). The representative case showed an increase in serum GDPP levels accompanied by an increase in the standard uptake value (SUV), as diagnosed by [ 18 F] PSMA-1007 PET, even though PSA levels remained low 2 years after surgical castration (Fig. 2 E). Overall, the changes in GDPP levels generally mirrored the dynamics of the BM burden throughout the clinical course of CRPC in patients with BM. We also allocated 80 CRPC patients with BM to either the high- or low-GDPP groups and found that the GDPP level was significantly correlated with cancer-specific survival (CSS) and overall survival (OS) (p < 0.01, Fig. 2 F Fig. S2A). Furthermore, multivariate analysis revealed that GDPP (≥ 15.3 ng/ml) as well as PSA (≥ 17.7 ng/ml) were independent predictors of CSS and OS in patients with CRPC (Table 2 , Table S5). Table 2 Univariate and multivariate logistic regression analysis of OS in CRPC patients with BM (n = 80) Univariate analysis Multivariate analysis HR 95% CI P value HR 95% CI P value Age (< 75 vs. ≥75 y) 0.95 0.45–1.99 0.89 - - - Gleason Score (< 8 vs. ≥8) 0.67 0.28–1.60 0.37 - - - PSA (ng/ml) (< 17.7 vs. ≥17.7) 8.30 3.16–21.8 < 0.01 4.68 1.53–14.3 < 0.01 ALP (U/l) (< 186.5 vs. ≥186.5) 1.39 0.65-3.00 0.39 - - - LDH (U/l) (< 210.5 vs. ≥210.5) 1.96 0.92–4.19 0.08 - - - OC (ng/ml) (< 7.8 vs. ≥7.8) 0.67 0.32–1.41 0.29 - - - BAP (µg/l) (< 22.5 vs. ≥22.5) 3.21 1.44–7.18 0.044 1.97 0.81–4.76 0.13 PⅠNP (ng/ml) (< 37.0 vs. ≥37.0) 0.95 0.45-2.00 0.90 - - - TRACP 5b (mIU/dl) (< 237 vs. ≥237) 1.69 0.79–3.62 0.18 - - - GDPP (ng/ml) (< 15.3 vs. ≥15.3) 11.3 4.13-31.0 < 0.01 7.26 2.40–21.9 < 0.01 GDPP promotes prostate cancer cell progression To determine why GDPP was more sensitive than PSA as a blood biomarker in patients with CRPC and BM, we sought to elucidate the underlying mechanisms. We explored the function of GDPP in the BM microenvironment through molecular and cellular studies involving RNA silencing. To investigate the biological role of GDPP in various PCa cell processes, we used siRNA to knockdown GDF15 expression in PC3, which was originally derived from the BM site of a CRPC patient in which GDF15 is moderately expressed, and DU145, which was derived from the brain metastasis site of a CRPC patient in which GDF15 exhibited low expression. Transfection of PC3 cells with siGDF15 resulted in a decrease in GDF15 transcript levels and in the amount of target pro-GDF15 protein (Fig. 3 A). These cell lines were then used to evaluate the role of GDPP in various cellular processes associated with cancer progression. To examine the effect of GDPP on PC3 cell proliferation, we treated GDF15 knockdown cells with recombinant GDPP (rGDPP) (Fig. S3A and S3B) and compared their proliferation levels with those of control cells. The results showed that GDF15 knockdown significantly decreased cell viability compared to control cells (Fig. 3 B). Interestingly, treatment with rGDPP counteracted the effect of GDF15 knockdown by markedly increasing cell viability in a dose-dependent manner in GDF15 knockdown cells, suggesting that GDPP promoted the proliferation of PCa cells. Similarly, rGDPP treatment of DU145 cells significantly enhanced their proliferation (Fig. 3 B). Furthermore, rGDPP treatment significantly increased the migration and invasion of PC3 and DU145 cells (Fig. 3 C and D). Collectively, these results indicated that GDPP independently promoted PCa cellular processes associated with tumor progression and metastasis, including cell proliferation, migration, and invasion. Bone-associated cells secrete GDPP in the bone microenvironment Next, because of its higher accuracy in reflecting the extent of BM in CRPC patients than PSA, GDPP was hypothesized to be secreted from osteoblasts or osteoclasts. We also tested whether GDPP is expressed by cells involved in BM. First, we examined the expression levels of pro-GDF15 in HOB and OSC15C cells. Western blotting revealed that pro-GDF15 was expressed in mouse osteoblasts (MC3T3-E1), HOB, mouse osteoclasts (OSC14C), and OSC15C. This result was also observed in mouse osteocytes (MLO-Y4) (Fig. 4 A). However, we could not confirm this in human osteocytes because these cells are not commercially available. The results of our ELISA showed that GDPP was secreted by HOB and OSC15C cells into the culture medium (Fig. 4 B). Additionally, immunohistochemical analysis of pro-GDF15 in human PCa tissues and the BM of CRPC patients confirmed that pro-GDF15 was expressed not only in PCa tissues but also in bone-related cells, including human osteocytes (Fig. 4 C), suggesting that all relevant cell types associated with BM can secrete GDPP in the bone microenvironment. GDPP promotes bone metabolism by increasing the proliferation and differentiation of human osteoblasts and osteoclasts To investigate the biological function of GDPP in the bone microenvironment, we evaluated whether GDPP influenced the proliferation and viability of osteoblasts. First, we confirmed that siRNA successfully reduced the amount of GDPP expressed in HOB cells (Fig. 5 A), which significantly decreased their proliferation (Fig. 5 B). Notably, the addition of rGDPP increased the viability of HOB treated with siGDF15 in a dose-dependent manner (Fig. 5 B). We examined the transcriptional regulation in HOB cells treated with rGDPP. Gene expression analysis showed that rGDPP treatment increased the transcript levels of osteoblast-related genes essential for bone formation, including RUNX2 , OSX , ATF4 , and ALP (Fig. 5 C, Fig. S4A). In addition, rGDPP treatment increased ALP activity, which is an indicator of osteoblastic differentiation and bone mineralization (Fig. 5 D, 5 E). These findings suggest that GDPP may enhance the osteogenic potential by increasing the expression of transcription factors in human osteoblasts and promoting their differentiation. To investigate whether GDPP influences osteoclast proliferation and viability, we evaluated the effect of GDPP on OSC15C cells, which are related to bone absorption in the bone microenvironment. The addition of rGDPP to OSC15C cells resulted in increased expression levels of differentiation-related genes such as NFATc1 , DC-STAMP , CTSK , and TRAP (Fig. 5 F, Fig. S4B). We also found that the addition of rGDPP to OSC15C cells led to a significant increase in mature osteoclasts (Fig. 5 G) and bone resorption potential (Fig. 5 H). Collectively, these findings suggested that GDPP enhanced bone metabolism by upregulating the expression of osteogenic and osteoclastic factors in the bone microenvironment. GDPP promotes bone metastasis of CRPC in vivo These results prompted us to investigate whether GDPP administration promotes BM development in preclinical models (Fig. 6 A). In our established models, we first confirmed bone invasion by cancer cells into the bone substrate (Fig. 6 B-D, Fig. S5). Consistent with the in vitro results, rGDPP administration increased the CRPC tumor volume in the BM compared to that in control mice (Fig. 6 E). We also confirmed that the number of osteoblasts and osteoclasts was significantly higher in the tumors of the rGDPP treatment group than in those of the control group, suggesting that GDPP enhances the proliferation of osteoblasts and osteoclasts in the bone microenvironment and may develop a vicious cycle of BM (Fig. 6 F, G). Discussion BM can occur in various types of cancers and significantly reduces the quality of life of patients by causing skeleton-related events leading to serious immobility ( 31 ). CRPC is an advanced form of PCa that develops due to disease progression following surgical or chemical castration, and approximately 80–90% of patients with CRPC develop BM, which significantly affects clinical prognosis ( 32 ). In general, for the diagnosis of PCa, whole-body CT and bone scintigraphy are performed to assess metastasis in organs, particularly the bone. However, bone scintigraphy does not lead to a definitive diagnosis because of some limitations, including limited availability of facilities, exposure to radiation, and a high false-positivity rate ( 7 ). Guidelines for BM diagnosis currently do not provide information on effective imaging examinations or blood biomarkers, making early diagnosis challenging ( 6 , 33 ). Therefore, we aimed to identify a convenient and accurate diagnostic biomarker for BM monitoring. NEPC is a histological variant of PCa characterized by aggressiveness and poor clinical outcomes and occurs in approximately 20% of patients with mCRPC. In general, PSA levels do not reflect disease status in NEPC because NEPC-derived cancer cells scarcely produce PSA, leading to a difficult challenge in understanding the disease ( 9 ). Hence, in this study, we focused on GDF15, which has been reported to be expressed in NEPC ( 29 , 30 ), with the aim of investigating its potential as a useful biomarker not only in CRPC patients but also in NEPC patients with BM. In this study, we demonstrated several novel findings that identified GDPP as a novel biomarker for the diagnosis and monitoring of BM in patients with CRPC. First, we found that a unique propeptide, GDPP, was secreted by PCa cells, which is also secreted by bone-associated cells: osteoblasts and osteoclasts (Fig. 1 E, 1 F, Fig. 4 A, 4 B). GDPP is normally expressed intracellularly as pre-pro-GDF15, which is then cleaved into mGDF15 and GDPP by furin. So far, previous studies have shown that mGDF15 is secreted extracellularly and may promote cancer progression ( 19 , 34 ). In contrast, similar to the C-peptide, which is a precursor of proinsulin, the propeptide domain of a protein is sometimes considered functional, which prompted us to investigate the detailed functions of GDPP ( 35 , 36 ). As expected, our study revealed that secreted GDPP promotes PCa carcinogenesis and the proliferation of bone-associated cells, leading to the development of a vicious cycle in the BM (Fig. 3 B-D, Fig. 5 B-H, Fig. 6 E-G). The high incidence of BM in PCa is believed to involve the development of a bone microenvironment that supports the growth of PCa cells, as indicated by the seed and soil theory ( 37 ). For instance, growth factors such as the TGF-β family are released and activated in response to bone tissue degradation and various changes in the bone microenvironment. In this context, CXCR4 has been reported to be a therapeutic target because TGF-β signaling induces acetylation of the transcription factor KLF5 in PCa with BM, which activates CXCR4, leading to osteoclastogenesis and BM ( 38 , 39 ). Our results also highlighted the pivotal role of GDPP in the vicious cycle of osteoblastic and osteolytic BM, which may be a candidate therapeutic target for patients with CRPC. We also found a significant increase in GDPP levels in CRPC patients with BM compared to those in CRPC patients with visceral metastases or locally advanced disease (Table 1 , Fig. 2 A- 2 C). GDPP is considered a superior biomarker compared to tumor and bone turnover markers, all of which are conventionally used for the diagnosis of BM, because GDPP has synergistic effects on PCa cells, osteoblasts, and osteoclasts during the progression of BM. Indeed, there was no significant difference in the GDPP levels between patients with localized PCa and healthy donors (Fig. 2 A). Given that there was no influence on GDPP levels after radical prostatectomy (Table S6, Fig. S2B), we speculated that the GDPP value would drastically increase once BM began. Indeed, GDPP levels were significantly correlated with BM volume in patients receiving systemic therapy (Fig. 2 C, D). These findings suggest that GDPP, which is not a traditional osteogenic marker, may perceptively diagnose BM and reduce radiological imaging tests, leading to an early diagnosis of oligometastases and thereby earlier intervention in CRPC patients (Fig. 2 E). Furthermore, we found that the change in GDPP levels reflected the clinical course of BM volume, as evidenced by the change in BSI or SUV in imaging tests (Fig. 2 E, Fig. S2C). In addition, multivariate analysis revealed that GDPP was an independent poor prognostic factor for CSS and OS in patients with CRPC and BM (Table 2 , Table S5). Considering that PSA levels often do not serve as an indicator of disease status in patients with CRPC and NEPC, we believe that GDPP measurements may be useful for disease monitoring in daily practice (Fig. 7 ). Future studies are required to validate our results for diagnosing BM at earlier stages using GDPP measurements before imaging tests. This study has several limitations. First, the GDPP receptor was not identified and the detailed pathway underlying the effects of GDPP has not yet been elucidated. Second, PSMA-PET is not covered by insurance in Japan, making it difficult to assess tumor volume using PSMA-PET in routine clinical practice. To investigate the clinical utility of GDPP more effectively, our future work will aim to prospectively examine patients with CRPC using GDPP, BSI, and PSMA PET by conducting clinical trials to determine whether GDPP is prognostically elevated at the time of CRPC diagnosis and whether it is useful for the diagnosis of bone oligometastases, contributing to early therapeutic intervention and improved prognosis. In conclusion, we demonstrated that the GDF15 propeptide, GDPP, is secreted from PCa cells, osteoblasts, and osteoclasts into the blood circulation of patients and has autocrine effects that promote the BM of PCa by augmenting the vicious cycle of osteoblastic and osteolytic BM in PCa and altering the bone microenvironment. Therefore, we believe that GDPP is a novel clinically useful blood biomarker that reduces the need for imaging studies and is a new therapeutic target in patients with CRPC and BM. Abbreviations BM Bone metastasis CRPC castration-resistant prostate cancer PCa prostate cancer GDF15 Growth differentiation factor 15 GDPP Growth differentiation factor 15 propeptide AUC Area under the curve PSA prostate-specific antigen mHSPC metastatic hormone-sensitive prostate cancer ALP alkaline phosphatase TGF-β transforming growth factorβ mGDF15 Mature growth differentiation factor 15 BAP Bone alkaline phosphatase TRACP 5b Tartrate-resistant acid phosphatase 5b LDH Lactate dehydrogenase OC Osteocalcin PⅠNP Procollagen I N-terminal propeptide BSI Bone scan index EDTA Tris-ethylenediaminetetraacetic acid PBS phosphate-buffered saline IVIS In vivo imaging system PAP prostatic acid phosphatase NEPC neuroendocrine prostate cancer 3D Three-dimensional TCGA The cancer genome atlas WCL Whole-cell lysate ROC Receiver operating characteristic SUV Standard uptake value CSS Cancer-specific survival OS Overall survival rGDPP recombinant growth differentiation factor 15 propeptide ATCC American type culture collection FBS Fetal bovine serum. Declarations Acknowledgments : We thank all members of the Department of Urology, Pathology, and Orthopedic Surgery of Osaka University for their constructive comments and the use of their facilities and services. Author contributions: G.Y., T.K., and M.U. conceived the study and designed the experiments; G.Y. and S.M. performed the experiments and statistical analyses; N.A. and Y.I. performed secretome data acquisition and analysis; G.Y., T.U., and S.M. analyzed the patient samples; G.Y., N.A., and T.K. prepared the manuscript; and T.K. and M.U. supervised the project. All authors contributed to the critical revision of the manuscript. Funding: This study was supported by grants from the Japan Society for the Promotion of Science, KAKENHI (21K09396, 20K23002 and 24K12436 to G.Y.). Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate All animal procedures were approved by the Osaka University Animal Research Committee (J008014-002) and adhered to the 'Regulations for Animal Experimentation' of the University, which are in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and other relevant regulatory standards. Before the collection of human blood from patients, written informed consent was obtained from each patient, and all experiments were carried out following institutional ethical regulations and guidelines under protocols approved by the Institutional Review Board of Osaka University Hospital (# 13397-19). Consent for publication Not applicable. Competing interests The all authors declare that they have no competing interests. References Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73(1):17–48. 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Supplementary Files supplementaryinformation.docx Cite Share Download PDF Status: Published Journal Publication published 25 Nov, 2024 Read the published version in Biomarker Research → Version 1 posted Editorial decision: Revision requested 18 Sep, 2024 Reviews received at journal 17 Sep, 2024 Reviews received at journal 17 Sep, 2024 Reviews received at journal 01 Sep, 2024 Reviewers agreed at journal 27 Aug, 2024 Reviewers agreed at journal 22 Aug, 2024 Reviewers agreed at journal 21 Aug, 2024 Reviewers agreed at journal 21 Aug, 2024 Reviewers agreed at journal 21 Aug, 2024 Reviewers invited by journal 21 Aug, 2024 Editor assigned by journal 01 Aug, 2024 Submission checks completed at journal 01 Aug, 2024 First submitted to journal 31 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4834587","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":345675341,"identity":"e785512a-9bcd-45ac-a1a2-4c88565cd8df","order_by":0,"name":"Gaku Yamamichi","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Gaku","middleName":"","lastName":"Yamamichi","suffix":""},{"id":345675342,"identity":"c880efb5-bdb0-4c27-a990-205025a48bfa","order_by":1,"name":"Taigo Kato","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYBACCRDxAZkjAZNibMClhZmBcQbJWph5sGrBBSTbzx98bNt2T45B7PDBGwwVdfKS7QfYJBhq7BiYZ2O3Rponmdk4t63YmEE6LdmC4cxhw9k8CUAtx5IZGOccwKpFjiGZTTq3LSGxQTrHTIKx7QDjPIb8bxIMbAeAXkzAroX/MZu0JVgLUCVjW539PP4HQFv+4dYiLQG0hRFiCxtQC3PibIkEEAO3FskZj40Ne84lGLNJpxlbJJw5nDxzxgNmi8S+ZB5cfpE4n/jwwY+yBDl+6eSHNz5U1NnOOJ/AeOPDNzs5QxwhBgdsIALuEiCDx3AGLrU4gTzBSB0Fo2AUjIIRAgDIBFBS4VuAogAAAABJRU5ErkJggg==","orcid":"","institution":"Osaka University","correspondingAuthor":true,"prefix":"","firstName":"Taigo","middleName":"","lastName":"Kato","suffix":""},{"id":345675343,"identity":"7ac1fcbf-b301-444b-9e54-0c18764d91a6","order_by":2,"name":"Noriaki Arakawa","email":"","orcid":"","institution":"National Institute of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Noriaki","middleName":"","lastName":"Arakawa","suffix":""},{"id":345675344,"identity":"c2c3397c-9efb-403b-9886-0dcc0fe70f43","order_by":3,"name":"Yoko Ino","email":"","orcid":"","institution":"Yokohama City University","correspondingAuthor":false,"prefix":"","firstName":"Yoko","middleName":"","lastName":"Ino","suffix":""},{"id":345675345,"identity":"bc22aaa0-55c2-47d4-8a41-7d396cbac29c","order_by":4,"name":"Takeshi Ujike","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Takeshi","middleName":"","lastName":"Ujike","suffix":""},{"id":345675346,"identity":"73626655-25e5-46f4-ab83-6126fcd61741","order_by":5,"name":"Kosuke Nakano","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Kosuke","middleName":"","lastName":"Nakano","suffix":""},{"id":345675347,"identity":"437751fa-22a0-4f87-b42e-29b3f4aed112","order_by":6,"name":"Yoko Koh","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Yoko","middleName":"","lastName":"Koh","suffix":""},{"id":345675348,"identity":"5e1d6eb4-3682-48b0-be29-3a399c67a5eb","order_by":7,"name":"Yuichi Motoyama","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Yuichi","middleName":"","lastName":"Motoyama","suffix":""},{"id":345675349,"identity":"c2b94ebd-9209-440e-bff3-b1382d253fa5","order_by":8,"name":"Hidetatsu Outani","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Hidetatsu","middleName":"","lastName":"Outani","suffix":""},{"id":345675350,"identity":"77374426-7f50-44c0-83f7-de311d2132bf","order_by":9,"name":"Shohei Myoba","email":"","orcid":"","institution":"Tosoh (Japan)","correspondingAuthor":false,"prefix":"","firstName":"Shohei","middleName":"","lastName":"Myoba","suffix":""},{"id":345675351,"identity":"8e7c3bb4-c0dc-41b8-9817-178491f8b834","order_by":10,"name":"Yu Ishizuya","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Ishizuya","suffix":""},{"id":345675352,"identity":"b169aa38-d18a-42c0-a1c9-0a6eba8ba084","order_by":11,"name":"Yoshiyuki Yamamoto","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Yoshiyuki","middleName":"","lastName":"Yamamoto","suffix":""},{"id":345675353,"identity":"9f3b7e3f-996a-40f4-afcc-7e8a2a2ec5ad","order_by":12,"name":"Koji Hatano","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Koji","middleName":"","lastName":"Hatano","suffix":""},{"id":345675354,"identity":"7584b05d-fe77-435c-8c7e-63db1324929a","order_by":13,"name":"Atsunari Kawashima","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Atsunari","middleName":"","lastName":"Kawashima","suffix":""},{"id":345675355,"identity":"c2a3a6a6-269a-47e0-b94b-3ebe0298e317","order_by":14,"name":"Shinichiro Fukuhara","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Shinichiro","middleName":"","lastName":"Fukuhara","suffix":""},{"id":345675356,"identity":"1eb721a6-7092-428d-889f-130cb5d6535a","order_by":15,"name":"Hiroji Uemura","email":"","orcid":"","institution":"Yokohama City University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Hiroji","middleName":"","lastName":"Uemura","suffix":""},{"id":345675357,"identity":"4895c3b6-0de1-43c4-ab80-5516ae61a3df","order_by":16,"name":"Seiji Okada","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Seiji","middleName":"","lastName":"Okada","suffix":""},{"id":345675358,"identity":"46dac3f1-82ed-4681-b172-78199c81e2be","order_by":17,"name":"Eiichi Morii","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Eiichi","middleName":"","lastName":"Morii","suffix":""},{"id":345675359,"identity":"295f2981-9cc1-40db-8304-343dd103fe1e","order_by":18,"name":"Norio Nonomura","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Norio","middleName":"","lastName":"Nonomura","suffix":""},{"id":345675360,"identity":"e91f7f37-8a7d-4c2a-bcc3-911baad5ead6","order_by":19,"name":"Motohide Uemura","email":"","orcid":"","institution":"Fukushima Medical University","correspondingAuthor":false,"prefix":"","firstName":"Motohide","middleName":"","lastName":"Uemura","suffix":""}],"badges":[],"createdAt":"2024-07-31 10:16:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4834587/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4834587/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40364-024-00695-6","type":"published","date":"2024-11-25T15:57:37+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64143630,"identity":"9a08c3d5-bb22-4f8d-bf29-68f30044d7bc","added_by":"auto","created_at":"2024-09-08 19:33:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":112621,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGDPP is cleaved from pro-GDF15 and secreted from PCa\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Of the culture medium from LNCaP, 22Rv1, PC3, and DU145 cell lines, a total of 2,787 proteins were identified through secretome analysis. (\u003cstrong\u003eB\u003c/strong\u003e) Peptides from the pro-GDF15 precursor annotated in the secretome analysis of PCa cell lines. Solid red lines indicate detection in three PCa cell lines (LNCaP, 22Rv1 and PC3). Solid blue lines indicate detection in two PCa cell lines (LNCaP and 22Rv1). Solid black lines indicate detection in one PCa cell line (LNCaP). Dotted black lines indicate detection in one PCa cell line (22Rv1). *: N-glycan binding site, □: furin protease consensus sequence (RXXR). The amino acid sequence before the black box is GDPP, and the amino acid sequence after the black box is the amino acid sequence of mGDF15. (\u003cstrong\u003eC\u003c/strong\u003e) The AlphaFold2 program was used to predict the 3D structure of mGDF15. The signal peptide, GDPP, and mGDF15 are connected to form pre-pro-GDF15. (\u003cstrong\u003eD\u003c/strong\u003e) Immunofluorescence staining showed the colocalization of GDPP and mGDF15 within LNCaP cells. Nuclei are indicated in blue (DAPI); GDPP is indicated in green (GFP), mGDF15 is indicated in red (TRITC). GFP: Green fluorescent protein, TRITC: Tetramethylrhodamine, DAPI: 4',6-diamidino-2-phenylindole. Scale bar, 50 μm.(\u003cstrong\u003eE\u003c/strong\u003e) Analysis of GDPP and mGDF15 in PCa cell lines by western blot revealed that GDPP and mGDF15 exist intracellularly as bound pro-GDF15 and extracellularly as separate entities, GDPP and mGDF15, respectively. (\u003cstrong\u003eF\u003c/strong\u003e) The concentration of GDPP in the culture medium in each of the four PCa cell lines was quantified using ELISA.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/5b661687f6874165070f7d9e.png"},{"id":64144591,"identity":"7526a90f-afba-4a05-abf1-4a341a19e52f","added_by":"auto","created_at":"2024-09-08 19:41:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153123,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReal-world data on GDPP in CRPC patients with BM\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) A comparison of GDPP, PSA, TRACP 5b, BAP, mGDF15, PINP, OC, ALP, and LDH levels in healthy donors (n=30) versus CRPC patients with and without BM (n=80 and 75,respectively). The data show significantly elevated levels of GDPP, PSA, BAP, mGDF15 and LDH in patients with BM. GDPP: Growth differentiation factor 15 propeptide, Data are expressed as the mean ± standard deviation (SD), and statistical analyses were performed using theTukey‒Kramer method (* p \u0026lt; 0.05, ** p \u0026lt; 0.01; n.s., not significant). (\u003cstrong\u003eB\u003c/strong\u003e) GDPP had the best AUC when comparing the diagnostic performance of each blood biomarker for BM in CRPC patients in each of the two randomized cohorts. (\u003cstrong\u003eC\u003c/strong\u003e) The analysis of the relationship between the BSI and GDPP, PSA, TRACP 5b, BAP, mGDF15, PINP, OC, ALP, or LDH in CRPC patients with BM is shown, together with the comparison of the strength of the correlation between each biomarker and the BSI (n=80). Statistical analyses were performed using Spearman's rank correlation coefficient.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eD\u003c/strong\u003e) The relationships between the change in BSI (ΔBSI) and the changes in many blood biomarkers during systemic treatment in CRPC patients with BM showed that the change in GDPP (ΔGDPP) correlated best with the change in the BSI (n=22). Statistical analyses were performed using Spearman's rank correlation coefficient. (\u003cstrong\u003eE\u003c/strong\u003e) This panel shows data from a representative patient who underwent longitudinal monitoring. During the clinical course of the patients, the plasma GDPP levels, rather than PSA levels, reflected the volume of BM revealed by PSMA PET. Red arrow indicates the solitary BM location from PCa. (\u003cstrong\u003eF\u003c/strong\u003e) Kaplan‒Meier analysis of the OS of CRPC patients with BM stratified by GDPP value;statistical analyses were performed using the log-rank test (** p \u0026lt; 0.01).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/7dd8668fb85e1879be816e75.png"},{"id":64145206,"identity":"d4ba445a-e496-435c-a901-b8af2de619ef","added_by":"auto","created_at":"2024-09-08 19:49:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":135240,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional analysis of GDPP in PCa cell lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Western blot analysis of GDPP expression in PC3 transfected with negative control siRNA or siGDF15. (\u003cstrong\u003eB\u003c/strong\u003e) PC3 transfected with siGDF15 or control siRNA and DU145 seeded with or without rGDPP treatment were incubated and proliferation was examined by MTS cell proliferation assay. (\u003cstrong\u003eC\u003c/strong\u003e) Scratch wound-healing assays of PC3 transfected with siGDF15 or negative control siRNA and of DU145 treated with or without rGDPP. Scale bar, 500 μm. (\u003cstrong\u003eD\u003c/strong\u003e) Invasion assays of PC3 transfected with siGDF15 or negative control siRNA and DU145 with or without rGDPP. Data are expressed as the mean ± SD, and statistical analyses were performed using theTukey‒Kramer method (* p \u0026lt; 0.05, ** p \u0026lt; 0.01; n.s., not significant).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/5e6b11e0c269128bab53cfc3.png"},{"id":64143631,"identity":"0c9fb53f-058e-44cb-afa8-b2ab792c404d","added_by":"auto","created_at":"2024-09-08 19:33:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":219101,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntracellular and extracellular molecular dynamics of GDPP in HOB and OSC15C\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Western blot analysis of cell lysatesrevealed the expression of pro-GDF15 in osteoblasts (MC3T3-E1 and HOB), osteoclasts (OSC14C and OSC15C), and osteocytes (MLO-Y4). Furthermore, the images depict the differentiation of OSC15C cells into mature osteoclasts. Scale bar, 500 μm. (\u003cstrong\u003eB\u003c/strong\u003e) ELISA-based evaluation of the concentration of GDPP in the culture medium of HOB and OSC15C. (\u003cstrong\u003eC\u003c/strong\u003e) Immunohistochemical staining of pro-GDF15 in human PCa cells, as well as in osteoblasts, osteoclasts, and osteocytes within the BM of PCa patients. Black arrows indicate osteocytes. Scale bar, 250 μm.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/853030c79305f7dcc18fbb6e.png"},{"id":64143635,"identity":"63cfa637-4fb8-49d9-bc34-1c05ecea82a3","added_by":"auto","created_at":"2024-09-08 19:33:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":183607,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional analysis of GDPP in HOB and OSC15C\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Western blot analysis of the expression of GDPP in HOB. HOB was transfected with negative control siRNA or siGDF15. (\u003cstrong\u003eB\u003c/strong\u003e) Cell growth curve of HOB lines transfected with siGDF15 or negative control siRNA that were seeded with or without rGDPP, and proliferation was examined by MTS assays. (\u003cstrong\u003eC\u003c/strong\u003e) Expression analysis of genes related to differentiation of HOB. Total RNA was isolated from HOB treated with or without rGDPP. mRNA expression of \u003cem\u003eRUNX2\u003c/em\u003e, \u003cem\u003eOSX\u003c/em\u003e, \u003cem\u003eATF4\u003c/em\u003e and \u003cem\u003eALP\u003c/em\u003e was evaluated using quantitative real-time PCR analysis. The expression of each gene was normalized to \u003cem\u003eGAPDH\u003c/em\u003e expression. (\u003cstrong\u003eD\u003c/strong\u003e) Analysis of ALP activity in HOB. Representative images of ALP staining, OD values and ALP\u003csup\u003e+\u003c/sup\u003e area percentages of HOB with or without rGDPP are shown. (\u003cstrong\u003eE\u003c/strong\u003e) Bone mineralization analysis of HOB. Representative images of HOB mineralization detected by Alizarin Red S staining, with OD values and area percentages with or without GDPP are shown. (\u003cstrong\u003eF\u003c/strong\u003e) Expression analysis of genes related to differentiation of OSC15C. Total RNA was isolated from OSC15C treated with or without rGDPP after differentiation into mature osteoclasts. mRNA expression of \u003cem\u003eNFATc1\u003c/em\u003e, \u003cem\u003eDC-STAMP\u003c/em\u003e, \u003cem\u003eCTSK\u003c/em\u003e and \u003cem\u003eTRAP\u003c/em\u003e was evaluated using quantitative real-time PCR analysis. The expression of each gene was normalized to \u003cem\u003eGAPDH\u003c/em\u003e expression. (\u003cstrong\u003eG\u003c/strong\u003e) TRAP staining analysis of OSC15C. OSC15C was treated with or without rGDPP and stained for TRAP. Scale bar, 500 μm. (\u003cstrong\u003eH\u003c/strong\u003e) Pit formation analysis of OSC15C. OSC15C was seeded into bone resorption assay plates and treated with or without rGDPP. Representative images of resorption pit formation and the percentage of resorbed area (bright area) were quantified. Data are expressed as the mean ± SD, and statistical analyses were performed using the Tukey‒Kramer method (* p \u0026lt; 0.05, ** p \u0026lt; 0.01; n.s., not significant). Scale bar, 500 μm.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/1242795b5e375e3962370bd5.png"},{"id":64144593,"identity":"89b40069-a7be-458f-8d12-aa55eb8b0750","added_by":"auto","created_at":"2024-09-08 19:41:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":343636,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional analysis of GDPP in a xenograft model of human PCa cells within the bone microenvironment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Schema of the experimental procedure. PC3-Luc2 cells were directly injected into the tibia of male NOD/SCID mice. The mice were subsequently subcutaneously administered rGDPP (n = 10), while the control group received saline injections (n = 10). Weekly imaging using an IVIS was performed. (\u003cstrong\u003eB\u003c/strong\u003e) Macroscopic image of a tibial bone tumor 50 days following the injection of PC3-Luc2 cells. (\u003cstrong\u003eC\u003c/strong\u003e) µCT and 3D modeling images demonstrated that the tumor cells had invaded the tibial bone. Scale bar, 500 μm. (\u003cstrong\u003eD\u003c/strong\u003e) Histological staining using hematoxylin and eosin revealed the infiltration of tumor cells into the tibial bone. Scale bar, 500 μm. (\u003cstrong\u003eE\u003c/strong\u003e) Weekly bioluminescence imaging captured changes in the tumor growth pattern of PC3-Luc2 cells within the tibia over time. (\u003cstrong\u003eF\u003c/strong\u003e) The number of OC-positive cells was quantified per unit trabecular bone surface. Black arrows indicate osteoblasts. Scale bar, 500 μm. (\u003cstrong\u003eG\u003c/strong\u003e) The number of TRAP-positive cells was quantified per unit trabecular bone surface. Black arrows indicate osteoclasts. Scale bar, 500 μm. Data are expressed as the mean ± SD, and statistical analyses were performed using a Mann–Whitney U test (* p \u0026lt; 0.05, ** p \u0026lt; 0.01).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/226ecac59011dedbfffc07c0.png"},{"id":64143637,"identity":"f3f3eadc-a513-48a3-a0b7-9cef8e9db8f0","added_by":"auto","created_at":"2024-09-08 19:33:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":112070,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical abstract showing the role of GDPP in promoting bone metastasis in CRPC patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn CRPC patients, GDPP augments the vicious cycle of BM in the bone microenvironment and is an accurate biomarker for BM. The illustration on the left shows a vicious cycle in which PCa cells, osteoblasts, and osteoclasts secret GDPP, PCa progresses, and osteoblasts and osteoclasts also proliferate, each of which, coupled with autocrine actions, exacerbates BM. The illustration on the right shows that blood GDPP levels in CRPC patients with BM reflect BSI accurately and are a very useful biomarker.\u003c/p\u003e","description":"","filename":"floatimage72.png","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/71cb52b7215ad9d4039170c5.png"},{"id":70388855,"identity":"c6f95ed8-0795-4561-bdf0-7c119799d890","added_by":"auto","created_at":"2024-12-02 17:27:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2321287,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/6427a3b9-3706-4e62-8430-682bda5a07d2.pdf"},{"id":64143634,"identity":"28828f01-ae60-41fd-9347-9fea078164d5","added_by":"auto","created_at":"2024-09-08 19:33:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":417966,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-4834587/v1/08982f91e884a17effeaecb5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"GDF15 propeptide promotes bone metastasis of castration-resistant prostate cancer by augmenting the bone microenvironment","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProstate cancer (PCa) is currently the most commonly diagnosed malignancy in the male population in more than half of the countries worldwide, with an incidence of approximately 1.4\u0026nbsp;million cases per year, and is the second leading cause of cancer-related deaths among men (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Although first-line treatments, including androgen deprivation therapy for metastatic hormone-sensitive prostate cancer (mHSPC), are initially highly effective in decreasing the levels of the standard indicator of PCa progression, namely, prostate-specific antigen (PSA), and in shrinking tumors, therapeutic resistance is almost universal, and the disease often progresses to metastatic castration-resistant prostate cancer (mCRPC).\u003c/p\u003e \u003cp\u003eGenerally, PCa has the highest incidence of bone metastases (BM) among cancers, with 6\u0026ndash;8% of new PCa patients having BM at first diagnosis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) and more than 90% of patients with CRPC developing BM (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). However, to date, no useful blood biomarkers for diagnosing and monitoring the BM due to CRPC have been identified (\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) because CRPC is highly heterogeneous and consists of a mixture of androgen-dependent and androgen-independent PCa. In addition, approximately 20% of PCa cases are accompanied by neuroendocrine alterations during the treatment course (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), which is associated with difficulty in assessing disease progression solely based on PSA levels (\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), suggesting that the evaluation of PSA levels is not sufficient to accurately predict BM status (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Bone scintigraphy is often used to evaluate BM volume in patients with CRPC in combination with laboratory parameters, including alkaline phosphatase (ALP) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, bone scintigraphy has several disadvantages, such as high cost and radiation exposure, resulting in difficulty in frequent measurements (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In this context, accurate and noninvasive biomarkers of BM are urgently required.\u003c/p\u003e \u003cp\u003eGrowth differentiation factor 15 (GDF15), also known as macrophage inhibitory cytokine 1 and NSAID-activated gene-1, is a member of the transforming growth factor β (TGF-β) superfamily (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Among various types of cancers, PCa exhibits the highest \u003cem\u003eGDF15\u003c/em\u003e transcript expression (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The \u003cem\u003eGDF15\u003c/em\u003e gene encodes a 308-aa peptide (pre-pro-GDF15) consisting of an N-terminal signal peptide, a mature domain (mGDF15), and a propeptide domain, which we named the GDF15-derived propeptide GDPP. The pro-GDF15 precursor is secreted as a homodimer from the endoplasmic reticulum. The active mature form, mGDF15, is released via the proteolytic cleavage of dimeric pro-GDF15 at a furin-like site (RXXR) (\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). A recent study showed that mGDF15 binds to glial cell-derived neurotrophic factor family receptor alpha-like, is involved in PI3K/Akt/mTOR pathway activation, and participates in various physiological processes such as weight loss. In contrast, the GDPP domain is thought to be involved in the recognition and disposal of pre-pro-GDF15, depending on whether it is correctly folded, and processing of the precursor within the cell (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). However, no attention has been paid to the free GDPP domain released after its detachment from the mGDF15 domain, resulting in a lack of reports on the physiological functions and extracellular dynamics of free GDPP.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to identify a convenient and accurate diagnostic biomarker that can enable the monitoring of BM in patients with CRPC and found that the newly identified protein \u0026ldquo;GDPP\u0026rdquo; promotes PCa progression and bone formation and resorption via the upregulation of transcription factor expression in the bone microenvironment, suggesting that plasma GDPP is a novel biomarker that reflects BM status more accurately than PSA in patients with CRPC and BM. Collectively, we believe that compared with traditional imaging tests, GDPP detection will reshape the diagnosis of BM.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSecretome analysis\u003c/h2\u003e \u003cp\u003eProteomic analysis of culture medium from the PCa cell lines, described in Supplemental Materials \u0026ldquo;Cell culture and maintenance\u0026rsquo;\u0026rsquo;, was performed as previously described (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In brief, the PCa cell lines were cultured under the recommended conditions until they reached 60% confluency. Then, the media were replaced with serum-free media, and cells were incubated for 48 h. The culture media were then collected and lyophilized. The lyophilized media were dissolved in 10 mM ammonium bicarbonate containing 4 M urea, and proteins were desalted by acetone precipitation. The precipitated protein was resuspended in 25 mM ammonium bicarbonate containing 4 M urea and 0.1% RapiGest detergent (Nihon Waters, Tokyo, Japan) and subsequently digested with trypsin for 16 h at 37\u0026deg;C after reduction, alkylation and dilution. The resulting peptides were desalted using C18 Stage Tips (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and analyzed on an LTQ Orbitrap Velos (Thermo Fisher Scientific) equipped with a reverse-phase LC system. Peptides were detected sequentially in positive ion mode for MS/MS in data-dependent scanning mode and identified using Proteome Discoverer 2.5 software (Thermo Scientific) and the Swiss-Prot human database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.uniprot.org/proteomes/UP000005640\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.uniprot.org/proteomes/UP000005640\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) with the following parameters: enzyme, trypsin; peptide mass tolerance, \u0026plusmn; 5 ppm; fragment mass tolerance, \u0026plusmn; 0.5 Da; maximum missed cleavage sites, 2; variable modifications: oxidation of methionine, acetylation and/or loss of methionine at N-terminus; and static modification: carbamidomethylation of cysteine. Mass spectrometry proteomics data were deposited to the ProteomeXchange Consortium (PXD045369, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.proteomexchange.org/\u003c/span\u003e\u003cspan address=\"http://www.proteomexchange.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) via the jPOST partner repository (JPST002261, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://jpostdb.org/\u003c/span\u003e\u003cspan address=\"https://jpostdb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStructure modeling with AlphaFold2\u003c/h2\u003e \u003cp\u003eStructure predictions for pre-pro-GDF15, GDPP and mGDF15 were generated by the AlphaFold2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb\u003c/span\u003e\u003cspan address=\"https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, accessed on 4 June 2023) model using the relevant online resources with their default settings (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOpen source RNA-sequencing analysis\u003c/h2\u003e \u003cp\u003eRNA-seq transcriptome data of various cancer patients, including 493 PCa, 407 bladder cancer, 510 renal cell carcinoma, 1082 breast cancer, 484 lung cancer, 592 colon cancer, 443 melanoma, 412 gastric cancer, 366 liver cancer, 527 uterine cancer, 181 esophageal cancer, 515 head and neck carcinoma, 514 glioma and 177 pancreatic cancer patients, were downloaded from the TCGA database in 2018.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence staining\u003c/h2\u003e \u003cp\u003eLNCaP cells were seeded in 2-well chamber slides (5712-002, IWAKI) at a density of 3 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/1.5 ml/well and incubated overnight at 37\u0026deg;C in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e. The cells were then washed with PBS and fixed with 4% paraformaldehyde for 15 minutes on ice. After permeabilization with 0.1% Triton X-100 (87361, Muto Pure Chemicals Co., Ltd.) in PBS at room temperature for 15 minutes, the cells were incubated with primary antibodies diluted in PBS-T overnight at 4\u0026deg;C. The primary antibodies used were a rabbit anti-GDPP polyclonal antibody (HPA011191, Sigma‒Aldrich, 1:200) and a mouse anti-mGDF15 monoclonal antibody (sc-515675, Santa Cruz Biotechnology, 1:50). After PBS washes, the slides were incubated with the appropriate secondary antibodies, Alexa Fluor 488 goat anti-mouse secondary antibody (A-11001, Invitrogen) and Alexa Fluor 568 goat anti-rabbit secondary antibody (A-11011, Invitrogen), both diluted in PBS-T (1:500), for 1.5 hours at room temperature. The slides were then washed with PBS-T at 22\u0026deg;C and counterstained with ProLong Gold Antifade reagent with DAPI (P36931, Invitrogen). The stained LNCaP cells were examined using a fluorescence microscope (BZ-X710, KEYENCE). Rabbit polyclonal IgG (NBP2-24891, Novus) and mouse monoclonal IgG (ab18469, Abcam) were used as isotype controls for the respective antibodies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eHuman sample collection and data\u003c/h2\u003e \u003cp\u003eWe collected human serum, plasma and tissue samples, such as PCa and bone samples, from healthy donors and PCa patients at Osaka University from December 2012 to December 2022. Total 386 patients (30 healthy donors, 60 localized PCa patients, 15 mCRPC patients without BM, 80 mCRPC patients with BM, 22 mCRPC patients with BM whose blood samples were collected over time and 179 PCa patients who underwent radical prostatectomy), we collected clinical information retrospectively. Whole blood (2.0\u0026ndash;7.0 ml) was collected directly into Venoject Ⅱ EDTA-2Na tubes (TERUMO) for plasma samples, and whole blood (2.0\u0026ndash;7.0 ml) was collected directly into Venoject Ⅱ tubes (TERUMO) for serum samples. Within three hours of collection, all plasma samples were centrifuged sequentially at 900 and 20,000 \u0026times; g for 10 min each, and the supernatants were stored at \u0026minus;\u0026thinsp;80\u0026deg;C as plasma. All serum samples were centrifuged at 3000 rotations per minute (rpm) for 5 min, and the supernatants were stored at -80\u0026deg;C as serum. Serum PSA (Beckman Coulter), ALP (Shino-Test Corporation), BAP (IDS, Inc.), TRACP 5b (Nittobo Medical), LDH (FUJIFILM Wako Pure Chemical Corporation), OC (Tosoh), mGDF15 (R\u0026amp;D Systems) and PⅠNP (USCN) levels were measured in the same blood samples. Bone scan index (BSI) was assessed within two months of both blood collection time points.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBone scintigraphy\u003c/h2\u003e \u003cp\u003eAll PCa patients were injected intravenously with 740 MBq of 99mTc MDP to evaluate the existence of BM. Three hours after injection, a whole-body bone scan was performed with a gamma camera equipped with a low-energy high-resolution parallel hole collimator in anterior and posterior views. The raw image data set was analyzed with the software package BONENAVI version 2, based on a personal database in Japan. This CAD system was used to calculate the BSI, which was calculated as a percentage of the sum of all spots classified as bone metastases in the patient's body. When the attending physician deemed it necessary especially for CRPC patients, it was taken about once every three month and their data was retrospectively analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEstablishment of an ELISA system to measure GDPP\u003c/h2\u003e \u003cp\u003eAnti-GDPP monoclonal antibodies targeting the GDF15 propeptide, namely, GD11-13 and GD01-62, were generated using a plasmid DNA immunization method, as we reported previously (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). These antibodies specifically recognize the central region of GDPP. To detect GDPP, a combination of GD11-13, immobilized on magnetic microparticles, and GD01-62, labeled with alkaline phosphatase, was employed. AIA-CL reagent (Tosoh) was developed based on the two-step sandwich enzyme immunoassay technique. Using the fully automated chemiluminescent enzyme immunoassay system (AIA-CL2400, Tosoh), sample dispensing, immunoreaction, B/F separation, substrate addition, and luminescence detection were performed automatically, and results were obtained in approximately 15 minutes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCell culture and maintenance\u003c/h2\u003e \u003cp\u003eLNCaP and DU145 cells were purchased from RIKEN BRC CELL BANK, 22Rv1 and PC3 cells were purchased from the American Type Culture Collection (ATCC). All cell lines were maintained in basal culture medium (RPMI1640) (Nacalai Tesque) with 10% fetal bovine serum (FBS), 100 U/mL penicillin G, and 0.1 \u0026micro;g/mL streptomycin in a humidified incubator set to 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e. PC3-Luc2 cells were also purchased from the ATCC and maintained in basal culture medium [Ham\u0026rsquo;s F-12K Kaighn\u0026rsquo;s medium, Gibco\u0026trade;; 10% FBS; 8 \u0026micro;g/mL Blasticidin S (Invitrogen)] in a humidified incubator set to 37\u0026deg;C and 5% CO2. MC3T3-E1 cells (RIKEN BRC Cell Bank) were maintained in basal culture medium (αMEM, Nacalai Tesque) with 10% FBS, 100 U/mL penicillin G, and 0.1 \u0026micro;g/mL streptomycin, MLO-Y4 cells (Kerafast) were cultured on type I collagen-coated dishes (Corning) and maintained in basal culture medium (αMEM with 5% heat inactivated FBS, 5% calf serum, 100 U/mL penicillin G, and 0.1 \u0026micro;g/mL streptomycin), and OSC14C cells (Cosmo Bio) were suspended in osteoclast culture medium (OSCMW and OSCMM, Cosmo Bio). HOB (PromoCell, lot number #469Z022, from cancellous bone/femoral head tissue collected from a 78-year-old Caucasian man) was cultured in osteoblast growth medium (C-27001, PromoCell), and OSC15C (Cosmo Bio, lot number #VJ2-F-OSH) was cultured in osteoclast wash medium (OSCMW, Cosmo Bio) and growth medium including receptor activator of NF-κB ligand and macrophage-colony stimulating factor (OSCMW, Cosmo Bio). HOB was used for functional analysis with a maximum of five passages allowed for cell culture. OSC14C and OSC15C differentiation into mature osteoclasts was confirmed by TRAP staining. A cell scraper (99002, Techno Plastic Products) was used to scrape off the cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of secreted proteins in cell culture media\u003c/h2\u003e \u003cp\u003eTo analyze the secreted proteins in culture media, we seeded 5\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells in 2 ml of serum-free medium into a 6-well dish and collected the culture medium 24 hours after seeding. This medium was passed through a filter (Millex-GV, SLGVR33RS, Merck), and the filtrate was collected after centrifugation at 6000\u0026times;g for 30 minutes using a centrifugal concentrator (Vivaspin, VS2091, SARTORIUS). The GDPP concentration in the culture medium for each sample was measured in triplicate. In total, 5 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e LNCaP cells were seeded in 6-well dishes, and the medium was changed 24 hours later. Then 25 \u0026micro;M furin inhibitor (#14965, Cayman Chemical) was added for 24 hours, and the whole-cell lysate and culture medium were collected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSodium dodecyl sulfate‒polyacrylamide gel electrophoresis (SDS‒PAGE) and western blotting\u003c/h2\u003e \u003cp\u003eFor SDS\u003cb\u003e‒\u003c/b\u003ePAGE, sample buffer containing 10% 2-mercaptoethanol was added to whole-cell lysates, generated using RIPA Lysis Buffer (Santa Cruz Biotechnology), or culture media, and proteins were resolved on 10% polyacrylamide mini gels (TEFCO). Afterward, proteins were transferred onto a polyvinylidene difluoride membrane using a semidry transfer system (Thermo Fisher Scientific). The membrane was then probed with the indicated specific antibodies that were utilized for immunological analysis: GDPP (1:1000, HPA011191, Sigma‒Aldrich), mGDF15 (1:1000, LS-C383688, LSBio), and β-actin (1:5000, 4967S, Cell Signaling Technology). The membrane was incubated with a horseradish peroxidase-conjugated secondary antibody against rabbit immunoglobulin (1:5000, Cell Signaling Technology). Finally, the membrane was subjected to detection with enhanced chemiluminescence western blotting detection reagents (Nacalai Tesque) and visualized using the ChemiDoc XRS Plus system (Bio-Rad) as a chemiluminescence detector.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDevelopment of human recombinant GDPP\u003c/h2\u003e \u003cp\u003eThe sequence of human GDPP with a Strep-tag at the N-terminus was cloned and inserted into an expression vector, and the resulting plasmid was amplified and utilized to transfect Expi293 mammalian cells for Strep-GDPP expression. The transfected cells were cultured, and the culture medium was collected. The recombinant GDPP protein was purified from the culture medium using a Strep-tag purification kit (IBA Lifesciences) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemical studies\u003c/h2\u003e \u003cp\u003eBoth human and mouse bone metastasis specimens were demineralized using Tris-ethylenediaminetetraacetic acid (EDTA) demineralization solution until tissue softening was observed, followed by paraffin fixation. Immunohistochemical staining was performed in 4 \u0026micro;m-thick paraffin-embedded tissue samples. The human sample sections were treated with EDTA buffer (pH 9.0) and activated by warming at 125\u0026deg;C for 30 seconds using a Pascal pressure chamber (S2800, Dako) for antigen activation treatment. Endogenous peroxidase activity was blocked by incubating the sections with 0.3% hydrogen peroxide for 5 min, followed by overnight incubation with primary antibodies against GDPP (1:200; HPA011191, Sigma‒Aldrich) at 4\u0026deg;C, and staining was performed using DAB substrate (MK210, TaKaRa). Finally, the sections were counterstained with hematoxylin. In the mouse tibial bone tissue specimens, antigen activation treatment was performed with 3-fold diluted Proteinase K Ready-to-use (S3020, Dako). The sections were incubated overnight at 4\u0026deg;C with a primary antibody against the osteoblast marker OC (M188, Takara, diluted 100 times), followed by incubation with secondary anti-rat antibody (714311, Nichirei Bioscience, Inc.). Staining was performed using DAB substrate (MK210, TaKaRa). Osteoclasts were stained using a commercially available TRAP Staining Kit (AK04F, Cosmo Bio). Osteoclasts were identified as TRAP-positive multinucleated (three or more nuclei) cells, and osteoblasts and osteoclasts were counted on the trabecular bone matrix surface in three randomly selected fields of view using light microscopy (BZ-X710, KEYENCE).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRNA interference\u003c/h2\u003e \u003cp\u003eFor knockdown of \u003cem\u003eGDF15\u003c/em\u003e using small interfering RNA (siRNA), cells were transfected with 10 nM of either targeting FlexiTube GeneSolution (GS9518, Qiagen) or negative control Stealth RNAi\u0026trade; (12935112, Invitrogen) using Lipofectamine\u0026reg; RNAiMAX Reagent (13778075, Invitrogen) for 24 hours. Then, the medium containing siRNA and transfection reagent was replaced with fresh medium. Following validation of \u003cem\u003eGDF15\u003c/em\u003e knockdown confirmed by western blotting method, functional assays were performed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCell proliferation assay\u003c/h2\u003e \u003cp\u003ePC3 cells and HOB transfected with either siRNA targeting \u003cem\u003eGDF15\u003c/em\u003e or negative control for 72 h were reseeded in medium supplemented with 10% FBS in 96-well plates at 1 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells/100 \u0026micro;L/well and 1.3\u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells/100 \u0026micro;L/well, respectively; DU145 cells were seeded in the same medium in 96-well plates at 1 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells/100 \u0026micro;L/well. The cells were incubated for 1 hour at 37\u0026deg;C in a humidified 5% CO\u003csub\u003e2\u003c/sub\u003e atmosphere, and then 0.1 \u0026micro;l MT Cell Viability Substrate (G9712, Promega) and 0.1 \u0026micro;l NanoLuc\u0026reg; Enzyme (G9712, Promega) were added to each well. Luminescence was measured with a GloMax\u0026reg; Explorer System (GM3510, Promega) according to the manufacturer\u0026rsquo;s instructions after 24, 48, and 72 hours in a humidified incubator set to 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e; this timepoint was set as 0 hours, and GDPP was added at this point. The assay was repeated three times for each experimental group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eWound-healing assay\u003c/h2\u003e \u003cp\u003ePC3 cells transfected with either siRNA targeting \u003cem\u003eGDF15\u003c/em\u003e or negative control siRNA for 72 h were reseeded in 6-well plates at 6 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/2 mL/well, and DU145 cells were seeded in 6-well plates at 6 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/2 mL/well. Cells were grown to a monolayer, and a wound was created by scraping the cell layer using a sterile 200-\u0026micro;L yellow pipette tip when the cells reached approximately 90% confluence. Detached cells were removed by washing plates with PBS and adding fresh culture medium supplemented with 10% FBS to each plate. Cells were treated with or without GDPP at this point and then incubated at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e. Cell migration was evaluated using a fluorescence microscope (BZ-X710, KEYENCE) at 0 h and 20 h after wound generation and quantified by measuring the size of the recovered area using ImageJ 1.53e. The assay for each experimental group was repeated three times.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eCell invasion assay\u003c/h2\u003e \u003cp\u003ePC3 cells transfected with either siRNA targeting \u003cem\u003eGDF15\u003c/em\u003e or negative control siRNA for 72 h and DU145 cells were seeded into the upper chambers of Corning\u0026reg; BioCoat\u0026trade; Matrigel Invasion Chambers (pore size\u0026mdash;8 \u0026micro;m) (354480, Corning) (5 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cells/well) in serum-free medium, with medium supplemented with 10% FBS present in the lower chamber. GDPP was added immediately after cell seeding. After 36 h of incubation at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e, the cells that had penetrated into the Matrigel matrix were fixed and stained using a Diff-Quik stain kit (Sysmex, Kobe, Japan), and cell invasion was quantified using a fluorescence microscope (BZ-X710, KEYENCE). The analysis was repeated three times for each experimental group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative real-time PCR\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from HOB (treated with or without GDPP for 3 days) and OSC15C cells (treated with or without GDPP for 12 days) using the ISOSPIN Cell \u0026amp; Tissue RNA Kit (NIPPON GENE). After verification of RNA quality by NanoDrop One (Thermo Fisher Scientific), the RNA was subjected to cDNA synthesis using the Prime Script RT reagent Kit (Perfect Real Time; TaKaRa Bio). Quantitative RT‒PCR was performed using the Thermal Cycler Dice Real Time System (TP800; Takara) and THUNDERBIRD\u0026trade; Next SYBR\u0026reg; qPCR Mix (TOYOBO). Target gene expression was normalized to that of the housekeeping gene \u003cem\u003eGAPDH\u003c/em\u003e using the delta-delta Ct method. The primers used for the PCRs are listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, and all PCRs were performed in triplicate for each sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eALP staining and assessment of activity\u003c/h2\u003e \u003cp\u003eHOB was seeded in 24-well plates and cultured on type I collagen-coated dishes (Corning) at 1\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/0.5 ml/well with or without GDPP. After 5 days of incubation, for ALP staining, the cells were washed with PBS and fixed for 20 min with 10% formalin at room temperature. After fixation, the cells were incubated with an Alkaline Phosphatase Staining kit (AK20, Cosmo Bio Co., Ltd.) for 20 minutes at 37\u0026deg;C according to the manufacturer\u0026rsquo;s instructions. The total percentage of ALP\u003csup\u003e+\u003c/sup\u003e cells was determined using a fluorescence microscope. To measure ALP activity, HOB was seeded to 24-well plates and incubated with or without GDPP for 5 days. Then, WCLs were obtained as stated in the Supplementary Materials section \u0026ldquo;Sodium dodecyl sulfate‒polyacrylamide gel electrophoresis (SDS‒PAGE) and western blotting\u0026rsquo;\u0026rsquo;, and ALP activity was measured using p-nitrophenylphosphate as the substrate for the alkaline phosphatase test (QFAP-100, BioAssay System) according to the manufacturer\u0026rsquo;s instructions. The optical density (OD) of WCLs was measured in a 96-well plate at 405 nm with a microplate reader (iMARK\u0026trade;, Bio-Rad). The assay was repeated three times for each experimental group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eAlizarin Red S staining and bone mineralization quantification\u003c/h2\u003e \u003cp\u003eHuman primary osteoblasts (HOB) was seeded in 24-well plates and cultured on type I collagen-coated dishes (354408, Corning) at 3\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells/0.5 ml/well using Osteoblast Mineralization Medium (C-27020, PromoCell) with or without GDPP for 21 days. The cells were subsequently washed with PBS, fixed, stained and digested with an Alizarin Red S staining kit (BMK-R009, BMK, Bio Mirai Kobo). The total area of staining was quantified using a fluorescence microscope, and after staining, the OD of the eluted Alizarin Red S solution was measured in a 96-well plate at 405 nm with a microplate reader (iMARK\u0026trade;, Bio-Rad). The assay was repeated three times for each experimental group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eTRAP staining and resorption pit assay\u003c/h2\u003e \u003cp\u003eHuman-derived primary osteoclast precursor cells (OSC15C) was seeded in 24-well plates at 2\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/0.5 ml/well with or without GDPP for 12 days. TRAP staining was performed using a TRAP staining kit (AK04F, Cosmo Bio) according to the manufacturer\u0026rsquo;s instructions, and the total number of TRAP-positive cells with \u0026ge;\u0026thinsp;3 nuclei was determined using a fluorescence microscope as the average of five randomly observed fields of view. The resorption pit assay was performed using the Bone Resorption Assay Kit (BRA-48KIT, PG Research). OSC15C cells were seeded in a 48-well Bone Resorption Assay Plate 48 (BRA-48P, PG Research) at 8\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells/0.5 ml/well with or without GDPP for 12 days. The bone resorption area was quantified using a fluorescence microscope as the average of five randomly observed fields of view. The assay was repeated three times for each experimental group.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eAnimal experiments with bone metastasis of prostate cancer\u003c/h2\u003e \u003cp\u003eMale NOD.CB17-Prkdc\u003csup\u003eSCID\u003c/sup\u003e/J mice, 5\u0026ndash;6 weeks of age, were purchased from Japan Charles River Laboratories, Inc. All mice were euthanized under anesthesia using isoflurane. For intratibial implantation, 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e PC3-Luc2 cells, purchased from ATCC, were suspended in 5 \u0026micro;l of VitroGel Hydrogel Matrix (VHM01S, TheWell Bioscience LLC) and 5 \u0026micro;l of phosphate-buffered saline (PBS). Mice were anesthetized with isoflurane, and the cell suspension was directly injected into the intramedullary cavity of the right tibia. The cavity was reached by drilling into the cortical bone of the tibial tuberosity using a 22 G needle (NN-2232R, TERUMO) with a 1 ml 29G syringe containing a needle (08299, NIPRO). Then, the skin was closed with a 6\u0026ndash;0 suture. Mice in the treatment group were subcutaneously injected with recombinant GDPP (refer to the section \u0026ldquo;Development of human recombinant GDPP\u0026rsquo;\u0026rsquo;) dissolved in saline at a concentration of 0.1 mg/kg every other day. Control mice were injected with an equal amount, and subsequent tumor growth was evaluated weekly with bioluminescence analysis via an In Vivo Imaging System (IVIS\u0026reg; Lumina II, Caliper). The mice were randomized into two groups for experiments: the control (n\u0026thinsp;=\u0026thinsp;10) and GDPP groups (n\u0026thinsp;=\u0026thinsp;10).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eMicro-CT and IVIS imaging\u003c/h2\u003e \u003cp\u003eThe mice were imaged to visualize luciferase activity immediately after injection and were monitored weekly using IVIS\u0026reg; imaging. Bioluminescence images of tumor-bearing mice were acquired with an IVIS Spectrum 10 minutes after intraperitoneal injection of D-luciferin (XLF-1, Summit Pharmaceutical International Corporation, 100 mg/kg), with an exposure time of 10 seconds. As a quality control measure, the photon flux was measured by quantifying the number of highlighted pixels within a circular region of interest (ROI) for each mouse in the supine position. These values were then normalized to the signal intensity obtained immediately after xenografting in the same area (day 0) of each mouse. Thus, all mice had an arbitrary starting normalized bioluminescence signal intensity of 1. This normalization was performed using Living Image\u0026reg; software version 4.2 (Caliper Life Sciences, Inc.) following the manufacturer's instructions. Bioluminescence imaging was employed to assess tumor burden and the localization of PC3-Luc2 cells. The bone-destructive phenotype caused by PC3-Luc2 cells was visually evaluated macroscopically. Additionally, three-dimensional images were constructed to confirm the presence of bone infiltration using R_mCT2 software (Rigaku) for micro-CT imaging.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eThe statistical analyses were performed using JMP Pro (v.17.0.0; SAS Institute, NC, USA). Univariate analysis included two-tailed Student's t-test and the Mann‒Whitney U test. Multiple comparisons were assessed using the Tukey‒Kramer method to compare several treatments. Spearman's rank correlation coefficient was used as a measure of the strength of the correlation between the two variables. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The optimal cutoff value for diagnosis was determined from the receiver operating characteristic curve using the Youden index, and sensitivity and specificity for diagnosis were calculated based on each optimal cutoff value. The cutoff values for the parameters used in the prognostic analysis are the respective medians.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003eGDF15 propeptide is a unique secreted peptide in PCa cells\u003c/h2\u003e \u003cp\u003eTo identify candidate proteins secreted by PCa cells that may be useful as blood biomarkers, we first performed secretome analysis of the culture media from four PCa cell lines (LNCaP, 22Rv1, PC3, and DU145) and proteomic analysis of the peptides obtained. We identified 17,798 peptides from 2,787 proteins in all culture media from PCa cell lines. These proteins included two well-known PCa biomarkers: PSA and prostatic acid phosphatase (PAP) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) (Table S2). Among these secreted proteins, we focused on GDF15, which was identified in three of the four cell lines (LNCaP, 22Rv1, and PC3) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) because in neuroendocrine prostate cancer (NEPC), GDF15 is highly expressed and PSA levels do not clearly reflect disease progression (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdditionally, our secretome analysis revealed peptides annotated to the mGDF15 domain in the C-terminal region and multiple peptides located in the GDPP domain of the N-terminal propeptide in the culture media (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). GDF15 secreted more unique peptides than PSA from the three different PCa cell lines (LNCaP, 22Rv1 and PC3) (Table S2), and considering that there are no reports regarding the function of GDF15 propeptide in human blood, we focused on GDPP. Three-dimensional (3D) structural predictions showed spatial connectivity between the signal peptides, mGDF15 and GDPP (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In addition, analysis of bulk RNA-seq data from The Cancer Genome Atlas (TCGA) database showed that the expression levels of \u003cem\u003eGDF15\u003c/em\u003e were the highest, and those of \u003cem\u003eFurin\u003c/em\u003e, which cleaves the junction between the GDPP domain and the remainder of the mGDF15 sequence, were relatively higher in PCa than in other cancer types (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA, S1B).\u003c/p\u003e \u003cp\u003eTo examine the subcellular localization of GDPP, we investigated the intracellular spatial relationship between GDPP and mGDF15. Immunofluorescence staining of LNCaP cell blocks revealed co-localization of GDPP and mGDF15 in the cytoplasm (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). To verify whether GDPP was truly present as a secreted protein and to determine its levels in various PCa cell lines, we performed western blot analysis and confirmed the exogenous expression of GDPP and mGDF15 in the culture media of LNCaP, 22Rv1, PC3 and DU145 cells, whereas only pro-GDF15 expression was detected in the whole-cell lysate (WCL) of LNCaP, 22Rv1, and PC3 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). These findings suggest the secretion of GDPP into the culture supernatant. In cell lines with high pro-GDF15 expression, both GDPP and mGDF15 were highly expressed in the culture supernatant. When a furin inhibitor was added to the LNCaP cells, neither GDPP nor mGDF15 was secreted into the culture medium; instead, pro-GDF15 accumulated within the treated LNCaP cells (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC). Consistent with the findings of the secretome and western blot analyses, LNCaP, 22Rv1, and PC3 cells secreted GDPP into the culture medium, whereas DU145 cells secreted very little GDPP (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Taken together, these findings indicate that the GDPP peptide is secreted by PCa cells into the extracellular space.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eGDPP is more useful than other blood biomarkers in CRPC patients with bone metastasis\u003c/h2\u003e \u003cp\u003eTo examine the clinical relevance of GDPP, we measured GDPP levels in patients with CRPC for whom PSA levels were not considered reliable. The clinical characteristics of the patients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The data showed that there were significant increases in the plasma levels of GDPP and serum levels of PSA, mGDF15, and bone turnover markers such as BAP and LDH in CRPC patients with BM compared with PCa patients without BM (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Notably, receiver operating characteristic (ROC) analysis revealed that GDPP had the strongest diagnostic ability for BM of CRPC among these blood markers in the two cohorts, with an area under the curve (AUC) of 0.92 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, Table S3).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient baseline characteristics and blood biomarker levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy donors\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;30\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLocalized PCa\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003emCRPC (BM-)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;15\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003emCRPC (BM+)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;80\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003cp\u003e(37\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003cp\u003e(52\u0026ndash;79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73\u003c/p\u003e \u003cp\u003e(59\u0026ndash;86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74\u003c/p\u003e \u003cp\u003e(51\u0026ndash;88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGleason Score\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;8\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epT stage pT2\u003c/p\u003e \u003cp\u003epT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastasis site\u003c/p\u003e \u003cp\u003eBone\u003c/p\u003e \u003cp\u003eLymph node\u003c/p\u003e \u003cp\u003eLung\u003c/p\u003e \u003cp\u003eLiver\u003c/p\u003e \u003cp\u003eBladder\u003c/p\u003e \u003cp\u003eUreter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003cp\u003e44\u003c/p\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSA (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003cp\u003e(0-8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003cp\u003e(2.6\u0026ndash;45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003cp\u003e(0-110.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003cp\u003e(0-4782)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP (U/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183\u003c/p\u003e \u003cp\u003e(45\u0026ndash;292)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196\u003c/p\u003e \u003cp\u003e(107\u0026ndash;442)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003cp\u003e(60\u0026ndash;334)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e187\u003c/p\u003e \u003cp\u003e(37-4987)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH (U/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e172\u003c/p\u003e \u003cp\u003e(118\u0026ndash;340)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003cp\u003e(120\u0026ndash;312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e183\u003c/p\u003e \u003cp\u003e(151\u0026ndash;280)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e211\u003c/p\u003e \u003cp\u003e(115\u0026ndash;853)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOC (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.2\u003c/p\u003e \u003cp\u003e(4.5\u0026ndash;22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003cp\u003e(3.6\u0026ndash;35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003cp\u003e(6.1-38.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003cp\u003e(1.2-109.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAP (\u0026micro;g/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003cp\u003e(13.9\u0026ndash;30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003cp\u003e(10.5\u0026ndash;49.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003cp\u003e(3.7\u0026ndash;45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003cp\u003e(0.8-364.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePⅠNP (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003cp\u003e(6.5\u0026ndash;24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.4\u003c/p\u003e \u003cp\u003e(14.8\u0026ndash;72.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95.6\u003c/p\u003e \u003cp\u003e(21.5-192.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.0\u003c/p\u003e \u003cp\u003e(3.9-280.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRACP 5b (mIU/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e286.2\u003c/p\u003e \u003cp\u003e(141.8-532.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276.0\u003c/p\u003e \u003cp\u003e(117.1-582.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e357.0\u003c/p\u003e \u003cp\u003e(159.9-953.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e237.0\u003c/p\u003e \u003cp\u003e(17.9\u0026ndash;2795)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emGDF15 (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e626.7\u003c/p\u003e \u003cp\u003e(272.3-1802.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1331.3\u003c/p\u003e \u003cp\u003e(632.9-5020.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1731.3\u003c/p\u003e \u003cp\u003e(860.7-7266.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3718.0\u003c/p\u003e \u003cp\u003e(760.0-21351.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDPP (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003cp\u003e(1.6\u0026ndash;11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003cp\u003e(1.9\u0026ndash;7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003cp\u003e(2.7\u0026ndash;21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003cp\u003e(4.4-247.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNext, we evaluated the correlation between the bone scan index (BSI), an objective, quantitative score calculated using a computer-aided diagnostic system (BONENAVI) for bone scintigraphy, to determine the volume of BM and blood biomarkers. The correlation between GDPP and BSI was the strongest (r\u0026thinsp;=\u0026thinsp;0.66, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) among all the blood biomarkers examined, including mGDF15 (r\u0026thinsp;=\u0026thinsp;0.43) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Next, we investigated the changes in GDPP levels (ΔGDPP) in the same CRPC patients with BM over time to determine the clinical utility of GDPP for longitudinal monitoring of BM (Table S4). The value of ΔGDPP was significantly associated with ΔBSI (r\u0026thinsp;=\u0026thinsp;0.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), but the changes in PSA levels (ΔPSA) and in all bone turnover markers, except BAP, were not correlated with ΔBSI (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The representative case showed an increase in serum GDPP levels accompanied by an increase in the standard uptake value (SUV), as diagnosed by [\u003csup\u003e18\u003c/sup\u003eF] PSMA-1007 PET, even though PSA levels remained low 2 years after surgical castration (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Overall, the changes in GDPP levels generally mirrored the dynamics of the BM burden throughout the clinical course of CRPC in patients with BM.\u003c/p\u003e \u003cp\u003eWe also allocated 80 CRPC patients with BM to either the high- or low-GDPP groups and found that the GDPP level was significantly correlated with cancer-specific survival (CSS) and overall survival (OS) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF Fig. S2A). Furthermore, multivariate analysis revealed that GDPP (\u0026ge;\u0026thinsp;15.3 ng/ml) as well as PSA (\u0026ge;\u0026thinsp;17.7 ng/ml) were independent predictors of CSS and OS in patients with CRPC (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table S5).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate logistic regression analysis of OS in CRPC patients with BM (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;75 vs. \u0026ge;75 y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u0026ndash;1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGleason Score\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;8 vs. \u0026ge;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.28\u0026ndash;1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSA (ng/ml)\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;17.7 vs. \u0026ge;17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.16\u0026ndash;21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.53\u0026ndash;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP (U/l)\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;186.5 vs. \u0026ge;186.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.65-3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH (U/l)\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;210.5 vs. \u0026ge;210.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.92\u0026ndash;4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOC (ng/ml)\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;7.8 vs. \u0026ge;7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.32\u0026ndash;1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAP (\u0026micro;g/l)\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;22.5 vs. \u0026ge;22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.44\u0026ndash;7.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.81\u0026ndash;4.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePⅠNP (ng/ml)\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;37.0 vs. \u0026ge;37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45-2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRACP 5b (mIU/dl)\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;237 vs. \u0026ge;237)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.79\u0026ndash;3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDPP (ng/ml)\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;15.3 vs. \u0026ge;15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.13-31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.40\u0026ndash;21.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eGDPP promotes prostate cancer cell progression\u003c/h2\u003e \u003cp\u003eTo determine why GDPP was more sensitive than PSA as a blood biomarker in patients with CRPC and BM, we sought to elucidate the underlying mechanisms. We explored the function of GDPP in the BM microenvironment through molecular and cellular studies involving RNA silencing. To investigate the biological role of GDPP in various PCa cell processes, we used siRNA to knockdown \u003cem\u003eGDF15\u003c/em\u003e expression in PC3, which was originally derived from the BM site of a CRPC patient in which \u003cem\u003eGDF15\u003c/em\u003e is moderately expressed, and DU145, which was derived from the brain metastasis site of a CRPC patient in which \u003cem\u003eGDF15\u003c/em\u003e exhibited low expression. Transfection of PC3 cells with siGDF15 resulted in a decrease in \u003cem\u003eGDF15\u003c/em\u003e transcript levels and in the amount of target pro-GDF15 protein (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). These cell lines were then used to evaluate the role of GDPP in various cellular processes associated with cancer progression. To examine the effect of GDPP on PC3 cell proliferation, we treated \u003cem\u003eGDF15\u003c/em\u003e knockdown cells with recombinant GDPP (rGDPP) (Fig. S3A and S3B) and compared their proliferation levels with those of control cells. The results showed that \u003cem\u003eGDF15\u003c/em\u003e knockdown significantly decreased cell viability compared to control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Interestingly, treatment with rGDPP counteracted the effect of \u003cem\u003eGDF15\u003c/em\u003e knockdown by markedly increasing cell viability in a dose-dependent manner in \u003cem\u003eGDF15\u003c/em\u003e knockdown cells, suggesting that GDPP promoted the proliferation of PCa cells. Similarly, rGDPP treatment of DU145 cells significantly enhanced their proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Furthermore, rGDPP treatment significantly increased the migration and invasion of PC3 and DU145 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and D). Collectively, these results indicated that GDPP independently promoted PCa cellular processes associated with tumor progression and metastasis, including cell proliferation, migration, and invasion.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBone-associated cells secrete GDPP in the bone microenvironment\u003c/h3\u003e\n\u003cp\u003eNext, because of its higher accuracy in reflecting the extent of BM in CRPC patients than PSA, GDPP was hypothesized to be secreted from osteoblasts or osteoclasts. We also tested whether GDPP is expressed by cells involved in BM. First, we examined the expression levels of pro-GDF15 in HOB and OSC15C cells. Western blotting revealed that pro-GDF15 was expressed in mouse osteoblasts (MC3T3-E1), HOB, mouse osteoclasts (OSC14C), and OSC15C. This result was also observed in mouse osteocytes (MLO-Y4) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). However, we could not confirm this in human osteocytes because these cells are not commercially available. The results of our ELISA showed that GDPP was secreted by HOB and OSC15C cells into the culture medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Additionally, immunohistochemical analysis of pro-GDF15 in human PCa tissues and the BM of CRPC patients confirmed that pro-GDF15 was expressed not only in PCa tissues but also in bone-related cells, including human osteocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), suggesting that all relevant cell types associated with BM can secrete GDPP in the bone microenvironment.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eGDPP promotes bone metabolism by increasing the proliferation and differentiation of human osteoblasts and osteoclasts\u003c/h2\u003e \u003cp\u003eTo investigate the biological function of GDPP in the bone microenvironment, we evaluated whether GDPP influenced the proliferation and viability of osteoblasts. First, we confirmed that siRNA successfully reduced the amount of GDPP expressed in HOB cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), which significantly decreased their proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Notably, the addition of rGDPP increased the viability of HOB treated with siGDF15 in a dose-dependent manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). We examined the transcriptional regulation in HOB cells treated with rGDPP. Gene expression analysis showed that rGDPP treatment increased the transcript levels of osteoblast-related genes essential for bone formation, including \u003cem\u003eRUNX2\u003c/em\u003e, \u003cem\u003eOSX\u003c/em\u003e, \u003cem\u003eATF4\u003c/em\u003e, and \u003cem\u003eALP\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, Fig. S4A). In addition, rGDPP treatment increased ALP activity, which is an indicator of osteoblastic differentiation and bone mineralization (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). These findings suggest that GDPP may enhance the osteogenic potential by increasing the expression of transcription factors in human osteoblasts and promoting their differentiation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo investigate whether GDPP influences osteoclast proliferation and viability, we evaluated the effect of GDPP on OSC15C cells, which are related to bone absorption in the bone microenvironment. The addition of rGDPP to OSC15C cells resulted in increased expression levels of differentiation-related genes such as \u003cem\u003eNFATc1\u003c/em\u003e, \u003cem\u003eDC-STAMP\u003c/em\u003e, \u003cem\u003eCTSK\u003c/em\u003e, and \u003cem\u003eTRAP\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF, Fig. S4B). We also found that the addition of rGDPP to OSC15C cells led to a significant increase in mature osteoclasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG) and bone resorption potential (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH). Collectively, these findings suggested that GDPP enhanced bone metabolism by upregulating the expression of osteogenic and osteoclastic factors in the bone microenvironment.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGDPP promotes bone metastasis of CRPC\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThese results prompted us to investigate whether GDPP administration promotes BM development in preclinical models (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). In our established models, we first confirmed bone invasion by cancer cells into the bone substrate (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-D, Fig. S5). Consistent with the \u003cem\u003ein vitro\u003c/em\u003e results, rGDPP administration increased the CRPC tumor volume in the BM compared to that in control mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). We also confirmed that the number of osteoblasts and osteoclasts was significantly higher in the tumors of the rGDPP treatment group than in those of the control group, suggesting that GDPP enhances the proliferation of osteoblasts and osteoclasts in the bone microenvironment and may develop a vicious cycle of BM (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF, G).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eBM can occur in various types of cancers and significantly reduces the quality of life of patients by causing skeleton-related events leading to serious immobility (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). CRPC is an advanced form of PCa that develops due to disease progression following surgical or chemical castration, and approximately 80\u0026ndash;90% of patients with CRPC develop BM, which significantly affects clinical prognosis (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). In general, for the diagnosis of PCa, whole-body CT and bone scintigraphy are performed to assess metastasis in organs, particularly the bone. However, bone scintigraphy does not lead to a definitive diagnosis because of some limitations, including limited availability of facilities, exposure to radiation, and a high false-positivity rate (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Guidelines for BM diagnosis currently do not provide information on effective imaging examinations or blood biomarkers, making early diagnosis challenging (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Therefore, we aimed to identify a convenient and accurate diagnostic biomarker for BM monitoring.\u003c/p\u003e \u003cp\u003eNEPC is a histological variant of PCa characterized by aggressiveness and poor clinical outcomes and occurs in approximately 20% of patients with mCRPC. In general, PSA levels do not reflect disease status in NEPC because NEPC-derived cancer cells scarcely produce PSA, leading to a difficult challenge in understanding the disease (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Hence, in this study, we focused on GDF15, which has been reported to be expressed in NEPC (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), with the aim of investigating its potential as a useful biomarker not only in CRPC patients but also in NEPC patients with BM. In this study, we demonstrated several novel findings that identified GDPP as a novel biomarker for the diagnosis and monitoring of BM in patients with CRPC.\u003c/p\u003e \u003cp\u003eFirst, we found that a unique propeptide, GDPP, was secreted by PCa cells, which is also secreted by bone-associated cells: osteoblasts and osteoclasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). GDPP is normally expressed intracellularly as pre-pro-GDF15, which is then cleaved into mGDF15 and GDPP by furin. So far, previous studies have shown that mGDF15 is secreted extracellularly and may promote cancer progression (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In contrast, similar to the C-peptide, which is a precursor of proinsulin, the propeptide domain of a protein is sometimes considered functional, which prompted us to investigate the detailed functions of GDPP (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). As expected, our study revealed that secreted GDPP promotes PCa carcinogenesis and the proliferation of bone-associated cells, leading to the development of a vicious cycle in the BM (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-D, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-H, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE-G).\u003c/p\u003e \u003cp\u003eThe high incidence of BM in PCa is believed to involve the development of a bone microenvironment that supports the growth of PCa cells, as indicated by the seed and soil theory (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). For instance, growth factors such as the TGF-β family are released and activated in response to bone tissue degradation and various changes in the bone microenvironment. In this context, CXCR4 has been reported to be a therapeutic target because TGF-β signaling induces acetylation of the transcription factor KLF5 in PCa with BM, which activates CXCR4, leading to osteoclastogenesis and BM (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Our results also highlighted the pivotal role of GDPP in the vicious cycle of osteoblastic and osteolytic BM, which may be a candidate therapeutic target for patients with CRPC.\u003c/p\u003e \u003cp\u003eWe also found a significant increase in GDPP levels in CRPC patients with BM compared to those in CRPC patients with visceral metastases or locally advanced disease (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). GDPP is considered a superior biomarker compared to tumor and bone turnover markers, all of which are conventionally used for the diagnosis of BM, because GDPP has synergistic effects on PCa cells, osteoblasts, and osteoclasts during the progression of BM. Indeed, there was no significant difference in the GDPP levels between patients with localized PCa and healthy donors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Given that there was no influence on GDPP levels after radical prostatectomy (Table S6, Fig. S2B), we speculated that the GDPP value would drastically increase once BM began. Indeed, GDPP levels were significantly correlated with BM volume in patients receiving systemic therapy (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, D). These findings suggest that GDPP, which is not a traditional osteogenic marker, may perceptively diagnose BM and reduce radiological imaging tests, leading to an early diagnosis of oligometastases and thereby earlier intervention in CRPC patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003eFurthermore, we found that the change in GDPP levels reflected the clinical course of BM volume, as evidenced by the change in BSI or SUV in imaging tests (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, Fig. S2C). In addition, multivariate analysis revealed that GDPP was an independent poor prognostic factor for CSS and OS in patients with CRPC and BM (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table S5). Considering that PSA levels often do not serve as an indicator of disease status in patients with CRPC and NEPC, we believe that GDPP measurements may be useful for disease monitoring in daily practice (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Future studies are required to validate our results for diagnosing BM at earlier stages using GDPP measurements before imaging tests.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the GDPP receptor was not identified and the detailed pathway underlying the effects of GDPP has not yet been elucidated. Second, PSMA-PET is not covered by insurance in Japan, making it difficult to assess tumor volume using PSMA-PET in routine clinical practice. To investigate the clinical utility of GDPP more effectively, our future work will aim to prospectively examine patients with CRPC using GDPP, BSI, and PSMA PET by conducting clinical trials to determine whether GDPP is prognostically elevated at the time of CRPC diagnosis and whether it is useful for the diagnosis of bone oligometastases, contributing to early therapeutic intervention and improved prognosis.\u003c/p\u003e \u003cp\u003eIn conclusion, we demonstrated that the GDF15 propeptide, GDPP, is secreted from PCa cells, osteoblasts, and osteoclasts into the blood circulation of patients and has autocrine effects that promote the BM of PCa by augmenting the vicious cycle of osteoblastic and osteolytic BM in PCa and altering the bone microenvironment. Therefore, we believe that GDPP is a novel clinically useful blood biomarker that reduces the need for imaging studies and is a new therapeutic target in patients with CRPC and BM.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBone metastasis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecastration-resistant prostate cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCa\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprostate cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGDF15\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGrowth differentiation factor 15\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGDPP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGrowth differentiation factor 15 propeptide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprostate-specific antigen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emHSPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emetastatic hormone-sensitive prostate cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ealkaline phosphatase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTGF-β\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etransforming growth factorβ\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emGDF15\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMature growth differentiation factor 15\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBone alkaline phosphatase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTRACP 5b\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTartrate-resistant acid phosphatase 5b\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLDH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLactate dehydrogenase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOsteocalcin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePⅠNP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProcollagen I N-terminal propeptide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBone scan index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDTA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTris-ethylenediaminetetraacetic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ephosphate-buffered saline\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIVIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIn vivo imaging system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprostatic acid phosphatase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNEPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eneuroendocrine prostate cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e3D\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThree-dimensional\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTCGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe cancer genome atlas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWCL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWhole-cell lysate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSUV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard uptake value\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCancer-specific survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003erGDPP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erecombinant growth differentiation factor 15 propeptide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eATCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican type culture collection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFetal bovine serum.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eWe thank all members of the Department of Urology, Pathology, and Orthopedic Surgery of Osaka University for their constructive comments and the use of their facilities and services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eG.Y., T.K., and M.U. conceived the study and designed the experiments; G.Y. and S.M. performed the experiments and statistical analyses; N.A. and Y.I. performed secretome data acquisition and analysis; G.Y., T.U., and S.M. analyzed the patient samples; G.Y., N.A., and T.K. prepared the manuscript; and T.K. and M.U. supervised the project. All authors contributed to the critical revision of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis study was supported by grants from the Japan Society for the Promotion of Science, KAKENHI (21K09396, 20K23002 and 24K12436 to G.Y.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal procedures were approved by the Osaka University Animal Research Committee (J008014-002) and adhered to the \u0026apos;Regulations for Animal Experimentation\u0026apos; of the University, which are in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and other relevant regulatory standards. Before the collection of human blood from patients, written informed consent was obtained from each patient, and all experiments were carried out following institutional ethical regulations and guidelines under protocols approved by the Institutional Review Board of Osaka University Hospital (# 13397-19).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe all authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSiegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. 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Eur Urol. 2020;77(4):508\u0026ndash;547.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBootcov MR, Bauskin AR, Valenzuela SM, Moore AG, Bansal M, He XY, et al. MIC-1, a novel macrophage inhibitory cytokine, is a divergent member of the TGF-beta superfamily. Proc Natl Sci U S A. 1997;94(21):11514\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLim YC, Bhatt MP, Kwon MH, Park D, Lee S, Choe J, et al. Prevention of VEGF-mediated microvascular permeability by C-peptide in diabetic mice. Cardiovasc Res. 2014;101(1):155\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWalcher D, Babiak C, Poletek P, Rosenkranz S, Bach H, Betz S, et al. C-Peptide induces vascular smooth muscle cell proliferation: involvement of SRC-kinase, phosphatidylinositol 3-kinase, and extracellular signal-regulated kinase 1/2. Circ Res. 2006;99(11):1181\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePaget S. The distribution of secondary growth in cancer of the breast.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e. Lancet 1889;1:571\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo P, Zhao KW, Dong XY, Sun X, Dong JT. Acetylation of KLF5 alters the assembly of p15 transcription factors in transforming growth factor-beta-mediated induction in epithelial cells. J Biol Chem. 2009;284(27):18184\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang B, Li Y, Wu Q, Xie L, Barwick B, Fu C, et al. Acetylation of KLF5 maintains EMT and tumorigenicity to cause chemoresistant bone metastasis in prostate cancer. Nat Commun. 2021;12(1):1714.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biomarker-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmre","sideBox":"Learn more about [Biomarker Research](http://biomarkerres.biomedcentral.com)","snPcode":"40364","submissionUrl":"https://submission.nature.com/new-submission/40364/3","title":"Biomarker Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"castration-resistant prostate cancer, bone metastasis, GDF15, biomarker","lastPublishedDoi":"10.21203/rs.3.rs-4834587/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4834587/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBone metastasis (BM) is a common and fatal condition in patients with castration-resistant prostate cancer (CRPC). However, there are no useful blood biomarkers for CRPC with BM, and the mechanism underlying BM is unclear. In this study, we investigated precise blood biomarkers for evaluating BM that can improve the prognosis of patients with CRPC.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe comprehensively examined culture supernatants from four prostate cancer (PCa) cell lines using Orbitrap mass spectrometry to identify specific proteins secreted abundantly by PCa cells. The effects of this protein to PCa cells, osteoblasts, osteoclasts were examined, and BM mouse model. In addition, we measured the plasma concentration of this protein in CRPC patients for whom bone scan index (BSI) by bone scintigraphy was performed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 2,787 proteins were identified by secretome analysis. We focused on GDF15 propeptide (GDPP), which is secreted by osteoblasts, osteoclasts, and PCa cells. GDPP promoted the proliferation, invasion, and migration of PC3 and DU145 CRPC cells, and GDPP aggravated BM in a mouse model. Importantly, GDPP accelerated bone formation and absorption in the bone microenvironment by enhancing the proliferation of osteoblasts and osteoclasts by upregulating individual transcription factors such as \u003cem\u003eRUNX2\u003c/em\u003e, \u003cem\u003eOSX\u003c/em\u003e, \u003cem\u003eATF4\u003c/em\u003e, \u003cem\u003eNFATc1\u003c/em\u003e, and \u003cem\u003eDC-STAMP\u003c/em\u003e. In clinical settings, including a total of 386 patients, GDPP was more diagnostic of BM than prostate-specific antigen (PSA) (AUC\u0026thinsp;=\u0026thinsp;0.92 and 0.78) and the seven other blood biomarkers (alkaline phosphatase, lactate dehydrogenase, bone alkaline phosphatase, tartrate-resistant acid phosphatase 5b, osteocalcin, procollagen I N-terminal propeptide and mature GDF15) in patients with CRPC. The changes in BSI over time with systemic treatment were correlated with that of GDPP (r\u0026thinsp;=\u0026thinsp;0.63) but not with that of PSA (r = -0.16).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eGDPP promotes a vicious cycle in the BM microenvironment and is a novel blood biomarker of BM in CRPC, which could lead to early treatment interventions in patients with CRPC.\u003c/p\u003e","manuscriptTitle":"GDF15 propeptide promotes bone metastasis of castration-resistant prostate cancer by augmenting the bone microenvironment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-08 19:32:58","doi":"10.21203/rs.3.rs-4834587/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-18T16:01:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-17T19:11:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-17T16:46:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-01T14:11:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88509200675276109116101881098425924874","date":"2024-08-27T10:12:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"312641914938658729726686673414925966741","date":"2024-08-23T03:06:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42765102504785937738431525245658836396","date":"2024-08-21T13:14:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292271869643397749269107899566700579348","date":"2024-08-21T12:08:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294326093520397585643322078669964189150","date":"2024-08-21T10:57:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-21T10:52:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-01T10:47:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-01T07:26:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biomarker Research","date":"2024-07-31T10:15:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biomarker-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmre","sideBox":"Learn more about [Biomarker Research](http://biomarkerres.biomedcentral.com)","snPcode":"40364","submissionUrl":"https://submission.nature.com/new-submission/40364/3","title":"Biomarker Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eeda1661-6e43-436c-af63-1aeea25adfc8","owner":[],"postedDate":"September 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T17:22:54+00:00","versionOfRecord":{"articleIdentity":"rs-4834587","link":"https://doi.org/10.1186/s40364-024-00695-6","journal":{"identity":"biomarker-research","isVorOnly":false,"title":"Biomarker Research"},"publishedOn":"2024-11-25 15:57:37","publishedOnDateReadable":"November 25th, 2024"},"versionCreatedAt":"2024-09-08 19:32:58","video":"","vorDoi":"10.1186/s40364-024-00695-6","vorDoiUrl":"https://doi.org/10.1186/s40364-024-00695-6","workflowStages":[]},"version":"v1","identity":"rs-4834587","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4834587","identity":"rs-4834587","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}