TAK1 Promotes an Immunosuppressive Tumor Microenvironment through Cancer-Associated Fibroblast Phenotypic Conversion in Pancreatic Ductal Adenocarcinoma

Pancreatic cancer is projected to rank as the third leading cause of cancer-related death by 2030 (1), with a 5-year survival rate of approximately 10% (2). Cancer cells have evolved various strategies to evade senescence and cell death, allowing them to evade immune attacks and proliferate in harsh environments during tumorigenesis. Despite advances in surgical techniques and therapies, most patients with pancreatic ductal adenocarcinoma (PDAC) succumb to the disease, which is linked to the complex immunosuppressive and inherently abundant tumor microenvironment (TME; ref. 3).

Cancer-associated fibroblasts (CAF) play a crucial role in the tumor microenvironment, influencing the spread of PDAC. They promote drug resistance by secreting cytokines, chemokines, and extracellular matrix, while also regulating immune cell activity (4), leading to desmoplastic, hypovascular tumors and poor response to treatment. PDAC contains numerous immunosuppressive elements, including FOXP3⁺ T regulatory cells (Tregs), M2 macrophages, and myeloid-derived suppressor cells (MDSC). Recent studies emphasize the pivotal role of CAFs in influencing the immunosuppressive and tumor growth-promoting characteristics of the TME by secreting immunosuppressive cytokines that modify immune checkpoint expression (5). Notably, recent studies revealed that CAFs are not a homogeneous cellular population but consist of functionally and originally heterogeneous subtypes, such as tumor-promoting CAFs (6) and tumor-decelerating CAFs (7).

Moreover, with the development of in-depth research on CAFs, Öhlund and colleagues classified CAFs into multiple subtypes based on different phenotypes: myofibroblastic CAFs (myCAF) and inflammatory CAFs (iCAF; ref. 8). myCAFs, characterized by myofibroblastic-like cells and high expressions of α-smooth muscle actin (α-SMA), are currently recognized as tumor suppressive (7). Conversely, iCAFs express inflammatory markers, such as IL6, which promote tumor progression and exhibit immunosuppressive effects (4, 9). Notably, CAFs can transition between different isoforms, indicating the significance of their plasticity.

TGFβ-activated kinase 1 (TAK1) protein is synthesized from the MAP3K7 gene and belongs to the mitogen-activated protein kinase (MAP3K) family and plays a role in mediating signaling by IL1β, TNFα, lipopolysaccharide, and Toll-like receptor (10). Moreover, it can influence inflammation, immune response, and several pathways, such as the NF-κB signaling pathway and MAPK/ERK pathway, by initiating a cascade of downstream signals, encompassing P38, ERK, and NF-κB (11). This results in the initiation of NF-κB and activator protein 1 transcription factors, which regulate the expression of various inflammatory cytokines (12). Oihana and colleagues reported that the TAK1 inhibitor 5Z-7-oxozeaenol (OXO) can inhibit triple-negative breast cancer lung metastasis in most animal models (13). Yu and colleagues demonstrated the effectiveness of TAK1 inhibitor OXO in inhibiting circulating tumor cells, providing a potential drug target for metastasis inhibition in pancreatic cancer (14). In colorectal cancer, the treatment of TAK1 inhibitor combined with a TGFBR1 inhibitor decreased tumor cell metastasis (15). These observations suggest that TAK1 holds potential in inhibiting tumor progression; however, its role in the CAFs of pancreatic cancer remains unknown.

Here, we hypothesize that TAK1⁺ CAFs in PDAC can convert myCAF differentiation by shaping the immunosuppressive TME. We also propose that interfering with TAK in CAFs could serve as a potential therapeutic approach for cancer immunotherapy.

Human primary active CAFs (CAF1, CAF2, and CAF3) were derived from fresh pancreatic cancer surgical specimens at Kyushu University, following the method described by Bachem and colleagues (16) and Ikenaga and colleagues (17) These isolated cells exhibited fibroblast-like morphology and tested negative for cytokeratin 19 (CK19), an epithelial cell marker (18).

Human PDAC cells used in this study included BxPC-3 (ATCC), MIA PaCa-2 (Japanese Cancer Resource Bank), SUIT-2 (Japan Health Science Research Resources Bank), and ASPC-1 (Riken BioResource Center), as well as SW1990 and SLMS that were established in our laboratory, as described previously (19). These cells were cultured in a cell incubator at 37°C with 10% CO₂, using DMEM (Sigma Chemical Co.) supplemented with 10% FBS (ref. 20).

The KPC (LSL-K-RasLSLG12D/+; LSL-p53R172H/+; Pdx1-Cre) genetically engineered mouse model was used (21). The procedures for isolating and culturing pancreatic cancer cells and CAFs from primary tumors in two Pdx1-Cre; LSL-Kras G12D; Trp53 R172H/+; KPC mouse strains (KPCF410-PC and KPCF453-PC) have been outlined (22). In the subcutaneous transplantation model, C57BL/6 mice were used for subcutaneous transplantation, and injections were conducted as previously described. Tumor cells obtained from KPC mice (5 × 10⁵) and CAFs (5 × 10⁵) derived from organoid cultures were suspended in a 45 μL mixture of 50% Matrigel in PBS and injected into C57BL/6 mice. The mice were categorized into four groups: two groups with only tumor cell implantation and two groups with tumor cells and CAFs with mixed implantation. One week after implantation, mice in the control group were treated with 100 µL PBS + 0.1 µL dimethyl sulfoxide (DMSO) and OXO (15 mg/kg). One week postimplantation, the mice received intraperitoneal injections as specified in the figure legends. On day 28, the mice were sacrificed, and all tumors were excised from the subcutaneous region and weighed. Tumor volume was computed using the formula π/6 × (L × W × W), in which L represents the largest tumor diameter and W denotes the smallest tumor diameter (23).

Tumor tissues were preserved in formaldehyde, encased in paraffin, and sectioned into 4-μm-thick slices. Experimental procedures involving mice were approved by the Ethics Committee of Kyushu University (approval number: A21-383).

The tissue samples used in this study were obtained from patients who underwent surgery for pancreatic cancer at Kyushu University Hospital. The use of pancreatic cancer surgical specimens was approved by the Ethics Committee of Kyushu University (approval number: 22002-00 and 2020-7882020-503). This study was conducted in accordance with the Ethical Guidelines for Human Genome/Gene Research established by the Japanese government and the principles outlined in the Helsinki Declaration.

For in vitro studies, the TAK1 inhibitor OXO (Cat. No. 3604; Tocris Co.) was dissolved in DMSO to 25 mmol/L and frozen at −20°C until use. Subsequently, OXO was appropriately diluted to the culture medium. The resulting DMSO concentration in the medium did not exceed 0.1% (v/v).

As previously described, all PDAC organoids [patient-derived organoids (PDO)] were derived from human PDAC, whereas mouse PDAC organoids were sourced from KPC mouse pancreatic tumors. Organoids embedded in growth factor–reduced Matrigel (Cat. # 356231; BD Biosciences) were finally cultured in a complete medium at 37°C from 1 to 2 weeks as described previously (24). For the purpose of distinguishing and visualizing in fluorescence microscopy, organoids were tagged by a GFP, and CAFs were labeled with a red fluorescent protein. The medium was changed every 2 or 3 days. For passaging, the established PDOs were collected, rinsed with 0.5 mmol/L EDTA–PBS, and dissociated using trypsinization and mechanical shearing.

The process involved deparaffinizing 4-µm-thick sections of tissues of patients with PDAC or mouse pancreas tissues with xylene and subsequent rehydration through an ethanol gradient. Antigen revitalization was performed according to the manufacturer’s protocol. After blocking with 3% BSA in PBS, sections were incubated overnight at 4°C with primary antibodies (Supplementary Table S1) diluted in 1% BSA. Subsequently, cells were treated with antirabbit and antimouse antibodies (Supplementary Table S1). Counterstaining was performed using hematoxylin. Sirius red staining was performed using a Picrosirius Red Staining Kit (24901, Polysciences, Inc.), following the manufacturer’s guidelines (17). Comprehensive tissue slide imaging was conducted using a BZ-X800 fluorescence microscope (KEYENCE), covering a minimum of three distinct regions at 40× and 100× magnifications. Quantification was performed in a blinded manner using ImageJ software (NIH).

For immunofluorescence (IF) staining, sections were incubated with the primary antibodies (Supplementary Table S1) overnight at 4°C. Subsequently, the cells were exposed to Alexa 546–conjugated anti–mouse IgG, Alexa 488–conjugated anti–rabbit IgG, Alexa 488–conjugated anti–mouse IgG, and Alexa 546–conjugated anti–rabbit IgG (Supplementary Table S1) for 1 hour. Nuclear DNA was counterstained with 4′,6-diamidino-2-phenylindole, and fluorescent images were captured using a fluorescence microscope. TAK1 positivity, as determined by IF in CAFs that are positive or negative for the indicated α-SMA markers. Ten fields were randomly selected for each section, and a semiquantitative evaluation of the positivity rate of α-SMA⁺TAK1⁻ CAFs and α-SMA⁻TAK1⁺ CAFs was performed under a 400× magnification in five PDAC sections.

The levels of cytokines in the CAF culture media were assessed using human SDF-1 (CXCL12) from Invitrogen and the Human Cytokine Array C1000 (RayBiotech) and Human Cytokine Array C4 (RayBiotech). The procedure was performed according to the manufacturer’s instructions.

The mouse tumors were initially sliced into sections of 0.5 to 1.0 mm, and processed into single-cell suspensions using the Tumor Dissociation Kit (Miltenyi Biotec, 130-096-730) at 37°C for 40 minutes. Subsequently, the suspensions were filtered through a 70-μm cell strainer. To prepare for staining, the single-cell suspensions were treated with an anti-CD16/32 Fc receptor blocker (BioLegend, 101319) for 10 minutes at 4°C. After a PBS wash, surface proteins were stained for 30 minutes at 4°C. Following this, the cells were washed, resuspended in PBS, and analyzed using a flow cytometer (BD FACSAria Fusion). Fluorescent conjugate–labeled antibodies are listed in Supplementary Table S2.

The transwell coculture model was established as previously described (25) using transwell membranes (82051-572; VWR, pore size 3 µm). Organoids were positioned on top of of the compartment in Matrigel (356231; Corning) in 24-well plates, whereas 5 × 10⁴ CAFs were seeded in the lower compartment, either directly cultured in the plates or embedded in Matrigel. The cells were incubated in DMEM with 5% FBS for 3 days. For drug testing, OXO (300 nmol/L) was added to the CAFs 24 hours after seeding. Each cell line was assessed at least once after isolation and underwent retesting before qRT-PCR analysis.

In the direct 3D coculture, GFP-tagged PDOs were dissociated into individual cells and seeded at a 1:1 ratio (1 × 10⁵ PDO cells and 1 × 10⁵ CAFs per well) in 96-well plates with Matrigel and serum medium, following a previously described method (26). Fluorescence and images of the PDOs with and without CAFs were recorded on day 10 using BZ-X800. Completely focused and covered images were produced using a BZ-X analyzer. The overall area per PDO was measured using ImageJ software.

The migration and invasion capacities of cancer cells were assessed using transwell chambers (8 μm pore size; Becton Dickinson), following established procedures. Migration was assessed 24 hours after cell seeding, with or without OXO treatment, whereas the invasion was evaluated 48 hours after cell seeding, with or without OXO treatment. Subsequently, hematoxylin and eosin staining was used to visualize migrated or invaded PDAC cells and CAFs. The three-dimensional (3D) collagen I matrix invasion assay was conducted following established methods (27).

Cells were seeded in 96-well flat bottom plates at a density of 5,000 cells (PDAC1 and PDAC2) or 3,000 cells (CAF1 and CAF2) per well and incubated with 100 µL fresh DMEM containing 10% FBS medium for 24 hours. After 24 hours, the cells were treated with OXO. Control cells were exposed to DMSO at an equivalent concentration. Cell viability was assessed using Luminescent Cell Viability Assay Kit (CellTiter-Glo Kit, G7571; Promega) following the manufacturer’s instructions and checked using CellTiter-Glo.

RNA was extracted from CAFs cultured under different conditions [two-dimensional (2D) and 3D with control medium] and in indirect coculture with PDO498 and PDO501 in control medium for 10 days. Following this, the medium was replaced with either the control medium or subjected to OXO treatment for 24 hours. A High Pure RNA Isolation Kit (11828665001; Roche) was used for RNA extraction from both CAFs and PDO. Subsequently, iTaq Universal SYBR Green One-Step Kit (172–5150; Bio-Rad) and CFX96 Touch Real-Time PCR Detection System (Bio-Rad) were used to detect the data. The primers used are listed in Supplementary Table S3. Transcript quantities were assessed using the ΔΔCt method. All data were normalized to GAPDH mRNA levels.

Total cellular proteins from CAFs and tumor cells were extracted using PRO-PREP Protein Extraction Solution (iNtRON Biotechnology) following the previously described method (28). For cell lysate analysis, 20 μg of protein samples underwent separation on 10% SDS-PAGE using Mini-PROTEAN TGX precast gels from Bio-Rad Laboratories. The membrane was then transferred to a Trans-Blot Turbo Mini PVDF Transfer Pack. Primary antibodies (1:1,000; Supplementary Table S4) were separately incubated with the membrane overnight at 4°C, followed by probing with secondary antibodies (1:2,000; Supplementary Table S4). Enhanced chemiluminescence Western blotting (WB) detection reagent from Bio-Rad was used to visualize the immunoblot data, which were subsequently analyzed using the ChemiDoc XRS System (Bio-Rad Laboratories). Protein bands were surrounded by a volume box on a WB image using the box intensity to quantify the protein expression.

TAK1 (MAP3K7) expression was reduced by transfecting cells with a predesigned Silencer Select small interfering RNA (siRNA) targeting TAK1 (GS6885, Cat. #1027416, Qiagen), whereas a nontargeting siRNA (Cat. #1027310, Qiagen) served as a negative control. After 24 to 48 hours, the CAFs were detected using a Nucleofector Device (Nucleofector AAD-1001).

Figure 1A, Supplementary Figure 3F, and Supplementary Table S5 were created using publicly available databases The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression through GEPIA2 (http://gepia2.cancer-pku.cn). The public single-cell RNA sequencing datasets utilized in this study were obtained from the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/). Supplementary Figure S1F and S1G were created using The Human Protein Atlas (https://www.proteinatlas.org/). Coagulation pathways were gathered from the Kyoto Encyclopedia of Genes and Genomes database (https://www.genome.jp/kegg/).

We conducted statistical analyses utilizing Prism 9 software (GraphPad Software). Unless otherwise stated, data are presented as mean values accompanied by the SEM. We used the unpaired two-tailed Student t test, with statistical significance defined as P value < 0.05 to assess the differences between the two groups. Survival analysis was performed using the Kaplan–Meier method, comparing survival curves using the log-rank and Gehan–Breslow–Wilcoxon test. We conducted a simple linear regression analysis to investigate the association between TAK1 and α-SMA expression. The χ² test or Fisher exact test was used to evaluate the correlations between clinicopathologic characters and TAK1 expression (Supplementary Table S5).

All data generated or analyzed during this study are included in this published article (and its Supplementary Materials). The datasets analyzed in this study can be found in the online repositories: Genome Sequence Archive database (CRA001160, https://bigd.big.ac.cn/gsa), TCGA (https://www.cancer.gov/ccg/research/genome-sequencing/tcga), and Gene Expression Omnibus (GSE114417, https://www.ncbi.nlm.nih.gov/geo/). The data shown in the figures will be made available upon reasonable request to the corresponding author.

Using TCGA and Genotype-Tissue Expression databases, we observed high expression of TAK1 (MAP3K7 gene) in PDAC samples (n = 178) compared with that in normal pancreas samples (n = 171; P < 0.05; Fig. 1A). Our IF examination of human tumor tissues via the surgical resection of patients with PDAC revealed widespread TAK1 expression not only restricted to the cancer cell area (CK19 positive) but also highly extended to the cancer stroma (Fig. 1B). IHC was performed on our surgical specimen with TAK1, which revealed that TAK1 is primarily localized in the stroma (Fig. 1C). Additionally, through serial section IHC staining for CK19, fibroblast activation protein, and podoplanin, we found the same conclusion (Supplementary Fig. S1A). Analyzing previously published single-cell RNA sequencing datasets of KPC mouse TAK1 (MAP3K7; ref. 29), TAK1 was expressed in the stromal CAFs (Supplementary Fig. S1B–S1D). To confirm this, we found that the CAF markers podoplanin and fibroblast activation protein were coexpressed with TAK1 in the tumor stroma (Fig. 1D). Furthermore, we cultured CAFs extracted from human tissues in vitro, defined by collagen I and fibronectin in IF staining (Supplementary Fig. S1E). Upon comparison with several tumor cells, we found that TAK1 was also highly expressed in various CAFs (Fig. 1E). These data suggested that TAK1⁺ CAFs were mainly localized in the tumor stroma.

Previous studies had shown that inhibiting TAK1 increased the antitumor immune effect of T cells, in mice with non–small cell lung cancer (ref. 30). We examined the expression signatures of genes representing T-cell status to detect the effect of TAK1 in CAFs on T cells in PDAC, as described by Tirosh and colleagues (31). Utilizing these signatures, we observed a positive correlation between MAP3K7 expression and T-cell exhaustion signatures (LAG3, PDCD1, CTLA4, HAVCR2, and TIGHT) in PDAC in TCGA database (Fig. 1F). These findings suggest that TAK1⁺ CAFs contribute to the formation of immunosuppressive TME.

Furthermore, in The Human Protein Atlas database, they classified TAK1 protein expression into TAK1-high and TAK1-low groups based on their IHC intensity. We observed a correlation between TAK1 expression and prognostic probability in early-stage tumors (P < 0.05). However, although the P value was unfortunately not significant in the survival rate of all-staged patients, the images indicated a trend of poorer prognosis with high TAK1 expression (Supplementary Fig. S1F and S1G).

Previous studies have highlighted the significance of α-SMA expressions in myofibroblasts as an important component of TME of PDAC (32). Dual-color IF showed that a minor subset of cells expressing α-SMA also exhibited TAK1 protein expression (Fig. 1G). Specifically, IF detection revealed that about 15% of CAFs expressing α-SMA protein were TAK1 positive in human PDAC, whereas approximately 25% of α-SMA-negative CAFs expressed TAK1 protein (Fig. 1H). Furthermore, quantification by counting the dots per cell for each human PDAC revealed that there was a negative correlation between TAK1 and α-SMA expression (Supplementary Fig. S1H). Our observations were further supported by IF staining of CAFs, which demonstrated a partial inverse relationship between TAK1 and α-SMA expression (Supplementary Fig. S1I). These data suggested that CAFs with high TAK1 expression showed low levels of α-SMA expression.

Previous studies identified two subtypes of CAFs: iCAFs expressing inflammatory markers such as IL6 were located farther within the dense stroma, and myCAFs that expressed markers such as α-SMA found adjacent to tumor cells. This suggests that the observed distinct phenotypes may be linked to their spatial distribution (8). First, according to the previous study (33), we established that MAP3K7 (TAK1) is primarily expressed in the iCAF population through single-cell expression data (Supplementary Fig. S1J and S1K). To investigate the spatial distribution, we conducted IF costaining of TAK1, α-SMA, and CK19 in human PDAC. Our results revealed low levels of TAK1 in α-SMA⁺ myCAFs present near tumor cells. Conversely, we identified several TAK1-positive cells in the stroma distant from tumor cells, lacking α-SMA expression (Fig. 1I). Quantitative analysis indicated significantly greater distance from tumor cells for TAK1⁺ CAFs compared with α-SMA⁺ CAFs (Fig. 1J). Consistently, IF staining results showed that most TAK1-expressing CAFs also expressed IL6 (Supplementary Fig. S1L). These findings revealed that the CAF population, which was highly positive for TAK1, is distinct from populations enriched for α-SMA (myCAF marker) and TAK1-positive CAFs were highly coexpressed with IL6.

The functional inhibition experiment was performed to explore the role of TAK1 in CAFs. In CAFs treated in the medium with OXO, we observed a reduction in proliferation that was dose-dependent. We confirmed this effect using two distinct CAF types to validate the IC₅₀ for each CAF type (P < 0.01; Supplementary Fig. S2A). Upon administering varying doses of OXO (100, 200, and 300 nmol/L), we observed a dose-dependent reduction in protein levels of TAK1 concurrent with reduced IL6 and increased α-SMA expression in different CAFs (Fig. 2A and B; Supplementary Fig. S2B). We used OXO treatment at 300 nmol/L for subsequent experiments. Consistent with the WB result, IF staining of CAFs indicated decreased IL6 intensity and increased α-SMA expression (Supplementary Fig. S2C). Similarly, the downregulation of IL6 and TAK1, coupled with the upregulation of α-SMA, was also confirmed via siTAK1 (siRNA–induced suppression; Supplementary Fig. S2D). Moreover, we found similar results with IF staining (Fig. 2C) of α-SMA and IL6.

To further determine the TAK1-related pathways uniquely expressed in CAFs, we initially examined single-cell expression data obtained from human and KPC tissues (29, 34). Subsequently, we selected the top 140 differentially expressed pathways upregulated in CAFs from each group (TAK1⁻ CAFs vs. TAK1⁺ CAFs) for Kyoto Encyclopedia of Genes and Genomes analysis. Our analysis identified 75 pathways specifically expressed in CAFs (Supplementary Fig. S3A and S3B). We focused on two identified pathways: MAPK and the NF-κB signaling pathways (Supplementary Fig. S3C) based on previous reports related to TAK1 (35–37). According to single-cell analysis, we extracted high-expressing TAK1⁺ CAFs to analyze the MAPK pathway. We found that the membrane receptor proteins regulating TAK1—IL1r1, TNFRSF1A, and eGFR—as well as key molecules in the MAPK pathway, including ERK (MAPK1), JNK (MAPK9), and P38 (MAPK14), are all positively correlated with TAK1 (MAP3K7; P < 0.05; Supplementary Fig. S3D and S3E). Simultaneously, we observed in TCGA data of PDAC samples that high NF-κB scores correlated with significantly elevated T-cell exhaustion signatures (Supplementary Fig. S3F).

To validate these pathways, we performed WB on CAFs using siTAK1. siTAK1 downregulated the protein of TAK1 phosphorylation, with strongly downregulated phosphorylated P38, and faintly downregulated phosphorylated NF-κB (Fig. 2D). This highlights the significant impact of TAK1 inhibition on the MAPK signaling pathway while eliciting a slight reduction in the NF-κB signaling pathway via siRNA.

Previous studies identified TAK1 as a key regulator of multiple oncogenic proteins (38). Therefore, we aimed to explore the functional role of TAK1 in CAFs within human PDAC tumors. We isolated primary CAFs from two distinct patients with PDAC and used a targeted approach using siRNA to inhibit the activity of TAK1 in CAFs. As shown in Fig. 2E, siTAK1 inhibited substrate oncoproteins, such as p-ERK1/2 and p-STAT3, in CAFs. Subsequently, we examined the effects of TAK1 inhibitors on CAF ability to secrete a wide range of cytokines. We observed downregulation of IL6, OPG, and CXCL1 secretion by CAFs in response to TAK1 inhibition (Fig. 2F). Additionally, ELISA showed that CAFs secreted significantly higher levels of the proinflammatory cytokine SDF-1 (CXCL12), which significantly reduced upon OXO addition (Supplementary Fig. S4A). These factors facilitate the cancer cell progression (39–41) while hindering T-cell recruitment to the TME (42, 43) and inducing the formation of a desmoplastic and immunosuppressive TME. We found upregulation of CCL7 and angiogenin secretion by CAFs in response to TAK1 inhibition (Fig. 2F). CCL7 can act as a chemoattractant, drawing immune cells to the tumor site, which can either promote or inhibit tumor progression (44). These findings underscore the role of TAK1 in CAFs, suggesting its involvement in promoting the protumorigenic TME through several pathways.

Transwell coculture experiments of CAFs with PDAC cancer cells (the scheme in Fig. 3A) were conducted to assess the impact of soluble factors produced through heterotypic cross-talk. First, we detected the proliferation of pancreatic cancer cells following OXO treatment and confirmed the IC₅₀ of each. This indicated that low concentrations of OXO did not affect PDAC cell proliferation (Fig. 3B). Additionally, the concentration level of 300 nmol/L of TAK1 inhibited the migration and invasion of CAFs (Supplementary Fig. S4B). The ability to migrate and invade upper pancreatic cancer cells was achieved when cocultured with CAFs. However, introducing OXO to the coculture significantly reduced this migration and invasion, indicating that CAFs are crucial in restricting these processes. Notably, PDAC cells treated with OXO alone did not affect migration and invasion, indicating that TAK1 in cancer cells lacks the ability to independently regulate their migration and invasion (Fig. 3C and D). Moreover, in PDAC, the transwell system cocultured with CAFs exhibited a reduction in N-cadherin and vimentin expression upon adding OXO, whereas E-cadherin expression was increased. These results confirmed that IL6-upregulated CAFs promote a general tumor metastasis phenotype, whereas the TAK1 inhibitor (OXO) can control CAF subtype identity, thereby reducing epithelial–mesenchymal transition (EMT) in PDAC (Fig. 3E).

To establish an in vitro model reflecting the dynamic plasticity of CAFs in PDAC (Fig. 3F), we modified the coculture protocols recently documented (25).

CAFs exhibit dynamic equilibrium processes. CAFs planted in Matrigel reverted to a quiescent state (45) and were reactivated by coculturing with organoids (Fig. 3G).

First, we identified the induction of myCAFs and iCAFs in the CAF model, consistent with previous reports (29). CAFs incorporated into Matrigel displayed a quiescent state when cultured in control media (5% FBS/DMEM). However, encapsulating CAFs in Matrigel and exposing them to a transwell system alongside tumor organoids or conditioned media by tumor organoids, they undergo a phenotypic transformation into an iCAF phenotype. Finally, CAFs cultured in monolayers acquired myofibroblastic features typical of myCAFs. The myCAF marker ACTA2 was induced in fibroblasts cultured on 2D support. Coculturing tumor organoids (PDOs) with CAFs through a transwell system in 2D resulted in further elevation of ACTA2 expression. Additionally, the induction of iCAF markers (IL6) was pronounced during coculture when CAFs were seeded in 3D Matrigel, consistent with previous reports (29).

In 3D coculture, treatment with OXO significantly reduced IL6 in CAFs, as shown by qRT-PCR analysis, and this reduction was even greater than that observed in 2D coculture. Conversely, OXO treatment significantly increased ACTA2 expression in 2D coculture, significantly higher than that observed in 3D coculture (Fig. 3H). This suggests that myCAF signatures were more prevalent in 2D models, whereas iCAFs decreased in the 3D models after OXO treatment, indicating that TAK1 regulated this phenotypic switch.

Next, we cultured CAFs in Matrigel and stimulated them with the control medium from the organoids. The relative markers of myCAFs and iCAFs in CAFs were measured using qRT-PCR. These results revealed that iCAF-related genes (IL6, CXCL12, CXCL1, and PDGFA) were downregulated, and some myCAF markers (Thy1, Tnc, and ACTA2) were significantly increased. This suggests that the TAK1 inhibitor can induce the transformation of the iCAF-like phenotype into the myCAF phenotype (Fig. 3I).

We embedded CAFs in Matrigel to investigate TAK1-driven CAF plasticity. It has been reported that the introduction of TGFβ induces a myofibroblastic phenotype in fibroblasts and stimulates an active state (46).

Notably, our findings revealed that OXO-treated CAFs cultured in Matrigel no longer maintained a quiescent phenotype because these CAFs retained their activated and morphologic phenotypes (Fig. 3J). Furthermore, qRT-PCR analysis of ACTA2 in Matrigel demonstrated that OXO-treated CAFs significantly increased ACTA2 expression, with or without TGFβ, indicating that TAK1 inhibition promotes sustained activation of CAFs in the TME (Fig. 3K). These findings highlight the critical role of TAK1 in mediating CAF plasticity.

Our previous detection of secretory factors of CAFs suggests that CAFs provide essential elements for PDAC growth (47). Subsequently, we investigated the effect of interfering with TAK1 expression in CAFs on the behavior of tumor cells in the microenvironment.

We established a 3D direct coculture model involving PDOs of pancreatic cancer and CAFs (Fig. 4A) to examine the impact of CAFs on organoid proliferation and growth. We used established PDOs following a previous method from resected specimens of patients with PDAC (24). Here, we utilized two different PDOs for validation, namely, PDO497 and PDO501 (Fig. 4B; Supplementary Fig. S5A). PDOs were collected and embedded in a mixture of CAFs at a 1:1 ratio in a 3D matrix in low-attachment 96-well plates.

Suppression of TAK1 through siRNA inhibited the invasive ability of CAFs when cocultured with PDOs in Matrigel. Although green constitutes a component of PDOs, after 3 days of observation, a notable decrease in the green component was observed, suggesting that siTAK1 from CAFs significantly decreased the growth of PDOs in the matrix. Interestingly, TAK1⁺ CAFs showed a substantial increase in PDO growth (Fig. 4C), whereas the sphere area of CAFs was partially reduced or unchanged with siTAK1 treatment. However, the sphere area of PDOs was significantly reduced (Fig. 4D), consistent with observations in other PDOs (Supplementary Fig. S5A–S5C). Moreover, the total sphere area was significantly reduced by siTAK1 CAFs over time (Supplementary Fig. S5D and S5E). These results indicate that TAK1 plays a crucial role in the ability of CAFs to promote tumor growth and invasion.

We examined the impact of PDO outgrowth in Matrigel to investigate the role of TAK1 in CAF-driven tumor invasion by monitoring the invasion of cells from the central region of the spheroid into the surrounding matrix using light microscopy. Our findings revealed that after 7 days, the tumor outgrowth from the surface of spheroids into the matrix significantly decreased, whereas the main body areas of spheroids were not suppressed (Fig. 4E and F), confirming the central role of TAK1 as a key mechanosensory factor in promoting invasion.

Our findings indicate that TAK1 plays a crucial role in the invasive capacity of CAFs, which in turn could influence the progression of malignant tumor growth by regulating the extracellular matrix.

Subsequently, we investigated whether OXO could produce corresponding results in KPC (LSL-K-RasG12D/+; LSL-p53R172H/+; Pdx1-Cre) CAFs. Our result revealed that OXO inhibited TAK1 expression in CAFs from KPC, namely, MF1 and MF401 (Supplementary Fig. S6A). To examine the effects of OXO (15 mg/kg, once every 3 days), we subcutaneously cotransplanted KPC mice–derived tumor cell (5 × 10⁵) organoids with or without KPC CAFs (5 × 10⁵ + 5 × 10⁵) into C57BL/6 mice (Fig. 5A; Supplementary Fig. S6B).

One week after implantation, mice were administered intraperitoneal injections of OXO or PBS (control) for 3 weeks. Tumor growth inhibition was the most pronounced in the OXO coimplantation group (Fig. 5B).

Compared with vehicle controls, OXO markedly reduced tumor growth, encompassing both tumor weight and tumor volume in the coimplanted group (Fig. 5C), without influencing mouse weights. However, no substantial difference was observed between the control and the OXO groups in terms of tumor weight and volume.

Treatment with OXO reduced the number of collagen fiber areas in tumors cocultured with CAFs compared with that in the control group (Fig. 5D and E). Additionally, the proliferating cell nuclear antigen plays a crucial role in DNA replication and repair, suggesting cancer development in mice. OXO treatment significantly decreased the proliferating cell nuclear antigen index of the tumors (Fig. 5F) while increasing the percentage of CD31-positive area, indicating a decrease in tumor proliferation and an increase in angiogenesis (Fig. 5G).

Upon IF staining and semiquantitative analysis, we observed a significant reduction of IL6 expression and an increase of α-SMA expression by TAK1 inhibition. These findings suggest that TAK1 inhibition is associated with the suppression of iCAF phenotypes and induces myCAF phenotypes in vivo (Fig. 5H and I).

We assessed tumor-infiltrating immune cell populations to explore the relevance of TAK1 in the immunosuppressive TME in vivo. Overt tumor-bearing C57BL/6 mice were treated with OXO, following the model presented in Fig. 5A. Using IHC antibody staining, we observed increased infiltration of CD3, CD8, and CD4 in the treatment group compared with that in the control group (P < 0.05; Fig. 6A). Dissociated infiltrating CD45⁺ leukocytes in tumors were analyzed using flow cytometry and evaluated for multiple immunizations. Notably, OXO-treated tumors exhibited a significant increase in infiltrating CD8⁺ T cells (% CD45⁺ cells; P < 0.05), whereas CD4⁺ T cells (% CD45⁺ cells) showed minimal change (Fig. 6B). Additionally, IF results revealed an increase in merged orange-color cells after OXO treatment, indicating an increase in tumor-infiltrating CD8⁺Granzyme B⁺ cytotoxic T lymphocytes (Fig. 6C). In contrast to T cells, the OXO group showed no impact on the infiltration of F4/80 macrophages (Supplementary Fig. S6C–S6E). Interestingly, the marker associated with M2 macrophages (CD206) decreased in the OXO group (P < 0.05; Fig. 6D). Along with the reduced expression of M2 macrophages, CD11b and Ly6G (MDSCs/neutrophils), as immunosuppressive markers, were decreased significantly by IHC staining and FACS (P < 0.05; Fig. 6E; Supplementary Fig. S6F and S6G). Subsequently, we examined the expression of FOXP3⁺ Tregs in PDAC tissues. We assessed the infiltration of FOXP3⁺ T cells in the margin and center (>300 mm from the tissue edge) of the tumor. In both the center and periphery of the tumor, no notable reduction was observed in the number of immunosuppressive FOXP3⁺ cells (P < 0.05; Fig. 6F and G). These findings suggest that the TAK1 inhibitor enhanced T-cell dysfunction and improved the immunosuppressive TME.

Moreover, our findings revealed that OXO enhanced MHC-1 expression by IHC staining (Supplementary Fig. S6H), potentially improving the tendency of tumors to evade immune system recognition and clearance. In mice, OXO treatment resulted in elevated PDL1 expression, indicating a potential trend toward an improved response to anti-PD1 treatment. This suggests that cancer cells with high surface expression of PDL1 are more likely to be recognized, as previously reported (Supplementary Fig. S6H; ref. 48). In human cells, siTAK1 or OXO treatment of CAFs and coculture with tumors increased the protein levels of MHC and PDL1 in tumors (Supplementary Fig. S6I). This suggests that TAK1 might alter MHC-1 and PDL1 levels in tumors through CAFs.

Collectively, these findings suggest that TAK1 may be an attractive transition hub for conversion to myCAFs in PDAC. Interference with TAK1 inhibits CAF migration, blocks certain inflammatory factors, disrupts the immunosuppressive TME, and restricts tumor growth via several pathways (Fig. 7). TAK1 promotes immunosuppression in the TME and may be a potential therapeutic target for PDAC.

We demonstrated through single-cell data that TAK1 is primarily expressed in iCAFs of PDAC and positively correlated with the expression of IL1r1, TNFRSF1A and eGFR receptors. Biffi and colleagues reported that IL1 induces downstream IL6–STAT activation and NF-κB signaling to generate iCAFs (29). Additionally, a previous report highlighted that TAK1 knockout modulates NF-κB and MAPK signaling (49). However, in our findings on the role of TAK1 regulating CAFs, NF-κB activation by phosphorylation is rendered insignificant through TAK1 knockdown in CAFs. p-NFκB is usually activated not only by TAK1 but also by other signaling pathways such as IκB kinase (ref. 50). Consequently, TAK1 knockdown could prompt activation of other pathways in CAFs, maintaining or increasing NF-κB activities, leading to an insignificant reduction of p-NFκB. Additionally, we found that inhibition of TAK1 suppressed STAT3 phosphorylation, a significant pathway regulating IL6 and iCAFs, and that the phosphorylation of P38, an important link in the inhibition of the MAPK pathway, was also completely inhibited, as reported previously. Therefore, we propose that TAK1 inhibition may affect the conversion of iCAFs to myCAFs by changing P38, NF-κB, and STAT3. Undeniably, our study has limitations, and in this examination, we have not yet elucidated the specific mechanism of TAK1 in the transformation of myCAF except for the pathway analysis.

Our in vitro findings further validated the crucial role of TAK1 in the tumor–stroma cross-talk in PDAC. It was previously identified that IL6, produced by iCAFs, played a pivotal role in the initiation of tumorigenesis, tumor growth, metastasis, angiogenesis, and immunosuppression within the TME through signaling pathways such as JAK/STAT, MEK, and AKT (39). Notably, our in vitro results revealed that CAFs were more sensitive than cancer cells to the TAK1 inhibitor OXO. Therefore, the present research focused TAK1 functions in the CAFs, rather than pancreatic cancer cells (PCC). In the migration and invasion coculture system experiment, we speculated that the change in IL6 in CAFs influenced the metastatic infiltration of PDAC under OXO influence.

In the previous study, antigen-presenting CAFs (apCAF) are another subtype of CAFs, believed to exert immunosuppressive effects in pancreatic cancer by inducing the formation of Tregs. Therefore, we further discussed the status of apCAFs in KPC mice by single-cell analysis. However, based on single-cell analysis results, the correlation between TAK1 and apCAFs was very low, so we reduced the consideration of apCAFs (Supplementary Fig. S6J).

Furthermore, previous findings indicated a fibroblast-abundant stroma as a predictor of unfavorable prognosis in PDAC; in particular, iCAF differentiation can promote tumor progression (51). However, α-SMA⁺ CAFs generally present an inhibitory function on tumor progression (19). Our analysis suggests that CXCL1 and IL6, which inhibit CAF secretion through TAK1, may contribute to the phenotypic transformation of myCAFs, supporting reduced EMT in organoids in coculture models. In our previous study, we established that grade 3 PDOs did not undergo differentiation even in the presence of CAFs (24). Therefore, two grade 3 PDOs were selected for direct coculture with CAFs, with or without TAK1. Interestingly, we found that TAK1 in CAFs played an important role in promoting CAFs’ plasticity and its role in restricting tumor cell proliferation in coculture with organoids.

Our examination of intratumoral immune cells revealed an increase in lymphocyte infiltration, especially of cytotoxic T cells, and a decrease in MDSCs in vivo, likely due to CAF–immune cell cross-talk. CXCL1, which seems to be produced exclusively by iCAFs (8), promoted polymorphonuclear MDSC infiltration into the TME (52), driving tumor progression (53), whereas IL6 from CAFs promoted the differentiation of myeloid cells into MDSCs within the TME, leading to an immunosuppressive tumor microenvironment (54). Costa and colleagues found that high CXCL12 secretion most effectively attracts CD4⁺CD25⁺ T cells (55). In pancreatic cancer mouse models, CXCL12–CXCR4 inhibitors synergized with anti-PDL1 therapy (56). These findings suggest that inhibiting CXCL1, IL6, and CXCL12 from CAFs could remodel the immune environment. However, further investigation into the specific mechanisms of immune environment regulation was needed. Interestingly, in vivo and in vitro data revealed that interference with TAK1 in CAFs enhanced the expression of immune checkpoint proteins in PCCs and KPC-derived tumor cells, such as increased expression of PDL1 and MHC-I. These results may be caused by TAK1 involvement in regulating signaling pathways, such as NF-κB and STAT3, known to regulate the expression of PDL1 and MHC-I (57). In subsequent research, we aim to explore the impact of antiPD1 (aPD1) targeting with or without TAK1 in the KPC mouse model because immune cells may not be exhausted by aPD1 treatment and may be reactivated to treat cancer cells with high surface expression of PDL1.

Furthermore, in our current study, we found no evidence indicating a direct correlation between TAK1 and tumor prognosis. On the contrary, analysis of TCGA data revealed a close association between TAK1 and tumor metastasis among 176 patients, suggesting promising clinical applications of TAK1 (P < 0.0001; Supplementary Table S5). Moreover, our investigation into immune checkpoint blockade in PDAC revealed that interfering with TAK1 in CAFs promotes MHC-1 expression. These findings aligned with recent reports indicating that targeting CAFs sensitized pancreatic cancer to PD1 therapy by influencing immune checkpoint inhibitors (refs. 58, 59). Considering multiple research analyses, TAK1 inhibitors seemed to promote the transformation of procancerous CAFs into anticancerous CAFs, enhanced immune checkpoint blockade, mitigated tumor-suppressing inflammatory factors, and ultimately inhibited tumor progression. Hence, there is a strong rationale for further research into TAK1 inhibitors as part of combination therapies with immunotherapy.

A limitation of the current study lies in the lack of elucidation whether immune infiltration arises solely from TAK1 deletion in CAFs or in conjunction with the tumor. Moreover, at present, OXO resistance has not been fully elucidated. Nevertheless, our findings highlight that in vitro blockade of TAK1 in CAFs can convert myCAF differentiation and inhibit CAF migration, block certain inflammatory factors through several pathways, limit tumor metastasis invasion, and reduce EMT ability. In poorly differentiated organoids cocultured with CAFs, interference with TAK1 enhanced tumor growth. Additionally, the in vivo TAK1 inhibitor disrupts the immunosuppressive TME and enhances the recruitment of T cells, thereby impairing tumor growth. Therefore, TAK1 might be a potential therapeutic target for PDAC.

No disclosures were reported.

N. Sheng: Conceptualization, data curation, formal analysis, validation, investigation, methodology, writing–original draft. K. Shindo: Conceptualization, supervision, writing–review and editing. K. Ohuchida: Conceptualization, supervision, writing–review and editing. T. Shinkawa: Conceptualization, resources. B. Zhang: Data curation, software, writing–review and editing. H. Feng: Conceptualization, methodology. T. Yamamoto: Resources, validation, methodology. T. Moriyama: Writing–review and editing. N. Ikenaga: Writing–review and editing. K. Nakata: Writing–review and editing. Y. Oda: Resources, supervision, writing–review and editing. M. Nakamura: Resources, investigation, project administration, writing–review and editing.

The study was approved by the Ethics Committee of Kyushu University (approval number: 22002-00 and 2020-7882020-503).

Animal Studies: All mouse experiments were conducted in accordance with the guidelines of the Institutional Animal Committee of Kyushu University (approval number: A21-383).

We appreciate S. Sadatomi and E. Manabe (Department of Surgery and Oncology, Kyushu University Hospital) and the members of the Research Support Center, Graduate School of Medical Sciences, Kyushu University, for their technical assistance. This work was supported by the Japan Society for the Promotion of Science KAKENHI (Grant Numbers: JP21K19531, JP22H00480, JP21K9530, JP23H02770, JP21K08800, and JP23K08175) and grants from JST SPRING and assisted by The Shin-Nihon Foundation of Advanced Medical Treatment Research (Grant Number: JPMJSP2136).