LPA released from dying cancer cells after chemotherapy inactivates Hippo signaling and promotes pancreatic cancer cell repopulation

doi:10.21203/rs.3.rs-5080105/v1

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LPA released from dying cancer cells after chemotherapy inactivates Hippo signaling and promotes pancreatic cancer cell repopulation

https://doi.org/10.21203/rs.3.rs-5080105/v1

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Gemcitabine-based chemotherapy remains the cornerstone of comprehensive treatment for pancreatic ductal adenocarcinoma (PDAC). A significant bottleneck in tumor therapeutic efficacy is tumor repopulation, which is also considered one of the key reasons for drug resistance and recurrence. Previous investigations have highlighted the crucial role of the Hippo pathway in the tumorigenesis and progression of PDAC, with lysophosphatidic acid (LPA) regulating the Hippo pathway to promote cancer. However, the effect of the Hippo signaling pathway on tumor repopulation in PDAC has not been reported. In this study, we constructed a model where dose-dependent gemcitabine-induced dying cells release LPA, which promotes the proliferation, clonal formation, and invasion of pancreatic cancer cells. Mechanistic studies show that gemcitabine and LPA inhibit the phosphorylation of Yes-associated protein 1 (YAP1) and induce the inactivation of the Hippo pathway. Overexpression of YAP1 significantly upregulates the mRNA and protein expression levels of autocrine motility factor (ATX), inducing pancreatic cancer cells to release LPA, forming a positive feedback loop of LPA-Hippo to promote the re-proliferation of residual tumor cells. At the same time, it was found that inhibiting LPA and YAP1 expression can also increase the sensitivity of pancreatic cancer to gemcitabine. Thus, this study suggests that targeting the LPA-YAP1 signaling pathway may represent an effective strategy to improve the comprehensive therapeutic efficacy of PDAC.

PDAC

Tumor repopulation

LPA

Hippo signaling

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide, the overall survival rate is less than 5%, and gemcitabine-based chemoradiotherapy is widely employed in the clinical treatment of locally advanced or unresectable PDAC ^{[1, 2]}. Due to the stealthy onset, rapid progression and the lower rate of early diagnosis of PDAC, it shows resistance to radiotherapy and chemotherapy in the short term, which is the main reason for the failure of pancreatic cancer treatment. Surviving tumor cells may repopulate during of chemoradiotherapy treatment intervals, and the accelerated repopulation of tumors is considered as a major reason for treatment failure^[3]. Previous studies indicate that dying cells can stimulate the repopulation of pancreatic cancer cells through the crosstalk between Hedgehog, Wnt pathway, microRNA-193a-TGF-β2/TGF-βRIII axis and so on^[4–6]. Caspase 3 regulates prostaglandin E2, which can potently stimulate growth of surviving tumor cells. The existence of a cell death-mediated tumor repopulation pathway in which caspase 3 also plays a major role^[7]. However, the underlying mechanisms remain not to be elucidated clearly.

The Hippo pathway, is associated with various human cancers including PDAC. YAP1/TAZ undergo dephosphorylation and translocate to the cell nucleus when the Hippo pathway is deactivated, plays critical roles in tumor survival, proliferation, and migration^{[8, 9]}. Lipid metabolism alternations that promote tumor progression, lysophosphatidic acid (LPA) receptor-mediated signaling in the regulation of cancer cell functions^[10]. Autotaxin (ATX) serves as a secreted enzyme which highly expressed in PDAC, catalyzes the formation of LPA from LPC^[11].LPA can inhibit LATS1/2 through G12/13-coupled receptors, thereby activating YAP1 and TAZ transcriptional co-activators^[12]. However, the role of ATX-LPA axis in the repopulation of pancreatic cancer has not been studied sufficiently.

In this study, we examined the hypothesis that dying pancreatic cancer cells may provide initial signals that promote tumor repopulation after chemotherapy. Specifically, we demonstrated that gemcitabine induces dying pancreatic cancer cells to release LPA, which mediates the inactivation of the Hippo pathway. Furthermore, there exist a positive feedback loop between LPA and YAP1. Targeting the LPA-YAP1 axis may be an effective strategy to overcome chemoresistance in PDAC.

1.Gemcitabine promotes the repopulation of residual tumor cells in vitro

In an attempt to identify repopulation of residual PDAC cells treated with gemcitabine. We first analyzed the IC50 value of gemcitabine was determined by CCK8 assay, which was about 1µM for PDAC cell lines (Fig. 1A). Subsequently, we investigated whether dying cells could promote the repopulation of residual pancreatic cancer cells using direct and indirect co-culture models (Fig. 1B). The results of direct and indirect co-culture model indicated that dying cells treated with gemcitabine significantly induced the stronger fluorescence activity of reporter cells and higher OD450nm value (Fig. 1C and D). Collectively, our results indicated that dying cells treated with gemcitabine can promote the repopulation of residual pancreatic cancer cells.

2. Gemcitabine induced release of LPA and inactivation of the Hippo pathway in PDAC

Based on the UPLC-MS/MS detection platform, we conducted lipid metabolomics analysis. Compared with the control group, gemcitabine group significantly induced a variety of upregulations, including triglycerides (TG), phosphatidylinositol (PE) and LPA (Fig. 2A). Caspase3 can promote tumor cell repopulation by affecting iPLA2. The role and mechanism of iPLA2-AA-PGE2 signal axis in tumor repopulation were studied in detail. Another pathway downstream of iPLA2-LPC have not been reported in tumor repopulation. The effect of LPC on ATX decreases to LPA. Therefore, we selected LPA as the object of our study among a variety of upregulated lipids. Quantitative analysis results indicated that gemcitabine inhibits the overall lipid metabolism levels in pancreatic cancer but significantly promotes an increase in the concentration of LPA in the conditioned medium (Fig. 2B and C). To further examine the effect of gemcitabine on LPA, ELISA assays showed a dose-dependent increase in LPA concentration in conditioned media (Fig. 2D). Previous study demonstrated that LPA can inhibit the Hippo pathway kinase LATS1/2 in HEK293A cells via G12/13-coupled receptors^[12]. Therefore, we investigated whether similar mechanisms exist in PDAC.

To investigate the possible function between LPA and Hippo signaling pathway, we first examined mRNA and protein expression of YAP1 and pYAP1 under LPA intervention by Western blot and qRT-PCR. Results showed that LPA significantly suppresses YAP1 phosphorylation and promotes YAP1 nuclear translocation, and LPA inhibited ATX expression additionally (Fig. 2E and F). Subsequently, we assessed whether gemcitabine elicits similar effects to LPA. The results showed that gemcitabine can also significantly inhibit YAP1 phosphorylation, promote YAP1 overexpression and nuclear translocation, and suppress ATX protein expression (Fig. 2G and H). These findings indicate that gemcitabine induces dying cells to release LPA in a dose-dependent manner, inhibiting YAP1 phosphorylation and thereby inactivating the Hippo pathway.

We further investigated the impact of inhibiting LPA on the Hippo pathway. Western blot and qRT-PCR results indicated that HA130 (ATX inhibitor) significantly inhibits YAP1 expression and promotes ATX protein expression (Fig. 2I and J). Furthermore, ELISA assay results confirmed that HA130 significantly inhibits LPA concentration in CM of pancreatic cancer cells (Fig. 2K). These findings suggest that HA130 inhibits YAP1 expression and promotes ATX protein expression through negative feedback mechanisms.

Next, we investigated the role of LPA in dying cells induced repopulation of residual tumor cells. Colony formation and transwell assay reveled that LPA significantly promotes the clonogenic and migratory abilities of pancreatic cancer cells. In contrast, HA130 can significantly inhibits the clonogenic and migratory abilities of pancreatic cancer cells (Fig. 2L, M, and N). CCK8 assay indicated that compared to the control group, reporter cells in the gemcitabine-treated group exhibited significantly enhanced proliferation phenotype, whereas there was no statistical difference between the HA130-treated group and the control group (Fig. 2O). Furthermore, HA130 significantly reversed the pro-proliferative effect induced by dying cells after chemotherapy. These findings suggest that inhibiting LPA can significantly suppress the proliferative capacity of residual tumor cells.

In summary, these results demonstrate that gemcitabine induces the release of LPA from dying pancreatic cancer cells in a dose-dependent manner. LPA subsequently inhibits YAP1 phosphorylation, leading to inactivation of the Hippo pathway, thereby enhancing the clonogenicity, migration, and proliferative capacity of residual tumor cells.

3. LPA can promote the repopulation of residual tumor cells through YAP1

To explore the regulatory mechanism of LPA in PDAC, we used TCGA database for analysis firstly. In contrast to normal adjacent tissue, the mRNA levels of YAP1 showed notably higher in PDAC tissues (Fig. 3A). Based on the PDAC cohorts from TCGA and GEO, analysis of Kaplan-Meier plots for overall survival demonstrated that patients with higher YAP1 expression level had shorter overall survival (Fig. 3B). Meanwhile, the Pearson correlation analysis reveals a negative correlation between YAP1 and ENPP2 (ATX- encoding gene), consistent with previous findings (R = -0.15, P = 0.044) (Fig. 3C). Western blot and qRT-PCR results demonstrated that ATX was markedly decreased with YAP1 knockdown (Fig. 3D and E). Concordantly, overexpression of YAP1 by transiently transfecting YAP1 plasmid to AsPC-1 and PATU8988T cells significantly increased ATX expression (Fig. 3F and G).

To confirm whether YAP1 directly regulates LPA expression, ELISA assay results showed that YAP1 knockdown significantly reduced the concentration of LPA in the pancreatic cancer CM, whereas overexpressing YAP1 exhibited higher concentrations of LPA (Fig. 3H and I). Taken together, these results demonstrated that YAP1 knockdown could inhibit ATX activity, thereby suppressing LPA production. Conversely, YAP1 overexpression promotes synthesis and release of LPA, and subsequently establish a negative feedback loop to suppress ATX protein expression. The above results confirm that post-chemotherapy induction of dying cells in pancreatic cancer releases LPA, promoting YAP1 nuclear translocation. Subsequent nuclear translocation of YAP1 further enhances LPA release, forming a LPA-YAP1 positive feedback loop.

To examine YAP1 oncogenic function, we performed transwell and colony formation assays using AsPC-1 and PATU8988T cells knockdown and overexpressing YAP1, and consistently, promotion of colony formation and cell migration by YAP1 overexpression (Fig. 3J, K, and L).

Further investigation about the indirect co-culture model revealed the impact of YAP1 on tumor repopulation. CCK-8 assays were employed to test cell growth in the reporter cells. The results indicated that there was no statistically significant difference between the gemcitabine treatment and control group (Fig. 3M). Therefore, these data above suggested that LPA could promote the repopulation of residual tumor cells through YAP1.

4. HA130 enhances gemcitabine-induced apoptosis

Since gemcitabine's mechanism of action primarily involves incorporating into DNA strands to prevent replication and induce cell death^[13], we further evaluated the effect of YAP1 on DNA replication using GSEA analysis. The results suggested that YAP1 plays an important role in regulating DNA repair, G2M checkpoint, DNA damage checkpoint, and Cell Cycle DNA replication (Fig. 4A). This makes the combination of gemcitabine with HA130 a potential option.

Based on data from the Synergyfinder database, we assessed whether there was synergy or antagonism between the two drug combinations. Using the CCK8 assay to measure absorbance per well, we calculated dose-response matrices for each drug concentration and cell viability, and subsequently submitted these matrices to the database to compute the HSA model synergy scores^[14]. A synergy score < 0 indicates drug antagonism, 0 ~ 10 indicates additive effects, and > 10 indicates synergy between the drug combinations. We found that the synergy scores for the combination of HA130 and gemcitabine in AsPC-1 (Fig. 4B and C) and PATU8988T (Fig. 4D and E) were 13.16 and 21.83, respectively, indicating a strong synergistic effect between the two drugs.

To ascertain whether combination therapy can synergistically induce apoptosis in pancreatic cancer cells, we further utilized flow cytometry to assess the effects of inhibiting LPA-YAP1 signal. Our study revealed that compared to monotherapy groups, the combination of gemcitabine with HA130/si-YAP1 significantly increased the proportion of apoptotic cells (Fig. 4F and G). As expected, the result of Western blot demonstrated that the combination administration significantly enhanced gemcitabine's ability to induce DNA damage (Fig. 4H). These findings imply that targeting the LPA-YAP1 signaling axis could be an effective strategy to enhance the efficacy of chemotherapy in pancreatic cancer.

5. Single-cell sequencing reveals YAP1 may regulate multiple chemokines

We further investigated the impact of YAP1 on the tumor microenvironment of pancreatic cancer using single-cell sequencing. The quality control process is as described in standard protocol outlined in the Materials and Methods section (Fig. S1A-J). Using the "SingleR" package, we identified 13 cell types, including fibroblasts, macrophages, endothelial cells, epithelial cells (tumor cells), NK cells, T cells, monocytes, smooth muscle cells, neurons, and others (Fig. 5A and B). The ssGSEA analysis results indicate that the Hippo signaling pathway activity varies significantly across different cell types (Fig. 5C). As expected, the median level of Hippo signaling in pancreatic cancer samples is lower than that in adjacent normal tissues (Fig. 5D). Furthermore, the expression level of YAP1 is significantly higher than that of ENPP2 in pancreatic cancer (Fig. 5E). And the UMAP distribution plot indicated that cell types with high YAP1 expression almost universally did not express ENPP2, and vice versa (Fig. 5F). We also showed the UMAP distribution of Hippo pathway genes and their differences in expression levels between adjacent tissues and pancreatic cancer (Fig. S2 and S3).

We further examined the proportion of epithelial cells (tumor cells) expressing high and low levels of YAP1. The result showed that there exist a higher proportion of epithelial cells expressing high levels of YAP1 in the PDAC samples (Fig. 5G). Differential gene expression analysis was conducted on epithelial cells based on YAP1 expression levels, followed by KEGG and GO enrichment analysis. The results indicated that YAP1 primarily regulates pathways related to chemokine signaling, TNF signaling, extracellular matrix (Fig. 5H and I). Several pieces of literature have reported that in different cancers, IL6 and IL8 are regulated by various signal axes mediated by YAP1 to enhance their malignant capacity^{[15, 16]}. Based on the Pearson correlation analysis from TCGA cohort, YAP1 also shows positive correlations with IL8 and IL6, with correlation coefficients of 0.61 and 0.23, respectively (Fig. S1K and L). Therefore, we investigated the impact of YAP1 regulation on IL6 and IL8 expression. qRT-PCR results demonstrated that knocking down YAP1 expression significantly inhibited IL6 and IL8 expression, while YAP1 overexpression significantly promoted their upregulation (Fig. 5J and K). These pieces of evidence suggest that gemcitabine-induced nuclear translocation of YAP1 in pancreatic cancer may upregulate several critical chemokines, thereby inducing an inflammatory tumor microenvironment.

We used "irGSEA" package to conduct gene set enrichment analysis (GSEA) based on "AUCell" and "UCell" algorithms. The result indicated that YAP1 significantly enhanced cholesterol homeostasis (Fig. 5L). This finding was confirmed by GSEA analysis of RNA-seq data from TCGA-PDAC cohort (Fig. 5M). Multiple studies have highlighted the importance of YAP1 in cholesterol synthesis across different tumors^[17–19]. The accumulation of cholesterol and cholesterol-derived oxysterols inactivates the SREBP2 pathway by inducing the retention of the SREBP Cleavage-Activating Protein-SREBP2 complex in the endoplasmic reticulum, thereby downregulating cholesterol biosynthesis and uptake^[17]. qRT-PCR results demonstrated that YAP1 overexpression significantly promoted SREBP2 upregulation, and YAP1 knockdown reduced SREBP2 expression (Fig. 5N). Given cholesterol metabolism serves as a potential target for modulate processes in cancer^{[18, 19]}, these results imply that interventions in the Hippo signaling is one of the effective strategies to improve the tumor microenvironment following chemotherapy.

PDAC is a highly malignant tumor of the digestive system and is projected to become the second leading cause of cancer-related death in the United States by 2030^[20]. Pancreatic cancer patients are often diagnosed at an advanced stage, resulting in a very poor prognosis. Gemcitabine has been used as the first-line chemotherapy for PDAC^{[21, 22]}. Due to the response rate to gemcitabine is extremely low, most patients quickly develop resistance to the chemotherapy regimen. Lipid metabolism reprogramming has increasingly been recognized as a hallmark of malignancies. Previous studies have found that metabolic reprogramming is considered as a novel mechanism of chemotherapy resistance^[23]. Tumor-associated changes in lipid metabolism primarily include increased lipogenesis, enhanced lipid uptake in the extracellular microenvironment, and elevated lipid storage and mobilization within intracellular lipid droplets^[24]. Tumor repopulation refers to the accelerated growth of remaining tumor cells after chemoradiotherapy, resulting in resistance to chemoradiotherapy^[25]. Lipid metabolism and tumor repopulation are a major cause for chemotherapy failure and the underlying correlation and mechanism remains to be illustrated. Using direct and indirect co-culture models to simulate the in vivo environment, we demonstrated that dying pancreatic cancer cells treated with gemcitabine can significantly promote the repopulation of residual tumor cells.

Previous studies have reported that lipids not only play a crucial role in the formation of biological membranes and energy metabolism, but also function as second messengers regulating tumor progression^[26]. For instance, phospholipases can generate numerous pro-carcinogenic second messengers, such as LPA and arachidonic acid, which activate multiple carcinogenic signaling pathways ^{[27, 28]}. Accumulating evidence now supports a physiological role for LPA in regulating tumor progression, angiogenesis, and metastasis^[29]. LPA is a bioactive phospholipid that engages with at least six receptors, namely LPAR1-6, and each of these receptors is coupled to a specific G-protein^[30]. LPA also contributes to the progression, metastasis, and initiation of various cancers, including pancreatic cancer. LPA is found in various biological fluids, and its plasma levels are well-documented, particularly in relation to its role in blood coagulation. LPA is produced through the lysophospholipase D-mediated hydrolysis of LPC. ATX, also referred to as ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2), is a 125kDa secreted glycoprotein that was initially discovered as an autocrine cell motility factor produced by melanoma cells grown in conditioned medium^[31]. Initially believed to primarily function as a pyrophosphatase, further research has shown that ATX can hydrolyze LPC to produce LPA. Increased expression of ATX has been reported in PDAC and can be used for early detection^[32]. We further focused on the impact of gemcitabine on lipid metabolism, investigating whether abnormal lipid metabolism after chemotherapy contributes to the regulation of pancreatic cancer resistance. We indicated that gemcitabine generally inhibits lipid metabolism in pancreatic cancer cells but aberrantly induces a significant increase in LPA levels.

Hippo is a crucial anti-cancer pathway in vivo, where the STE20 family kinase MST1/2 is activated through various mechanisms^[33]. With the aid of adaptor proteins SAV1 and Mob1, MST1/2 further activates the NDR family kinase LATS1/2. By phosphorylating the transcription factor YAP/TAZ, LATS1/2 promotes the binding of YAP/TAZ to 14-3-3 proteins in the cytoplasm, thereby playing a cancer-inhibiting role. If LATS1/2 activity is decreased, YAP/TAZ will undergo nuclear translocation without phosphorylation, and once YAP/TAZ enters the nucleus, it can regulate the expression of a series of genes through transcription, promoting tumor cell proliferation, migration, invasion, and maintenance of dry characteristics^[34]. Our research group is the first to report that the Hippo pathway effector TAZ is highly expressed in pancreatic cancer and promotes metastasis by enhancing EMT^[35]. Subsequent studies have further revealed that the upstream regulatory factors MST1, Mob1, and Lats1 of the Hippo pathway play a crucial role in the occurrence and development of pancreatic cancer by regulating YAP/TAZ. However, the effect of the Hippo signaling pathway on tumor repopulation remains unexplored. Based on the results of mass spectrometry analysis and the aforementioned evidence, this study proposes a scientific hypothesis: gemcitabine induces the release of LPA from dying pancreatic cancer cells, subsequently regulating the overexpression and nuclear translocation of YAP1 in residual tumor cells, thereby promoting tumor repopulation. Furthermore, the results of the lipidomics analysis were confirmed by ELISA assay.

Mechanistic studies further revealed that both gemcitabine and LPA inhibit YAP1 phosphorylation in a dose-dependent manner, ultimately leading to the inactivation of the Hippo pathway. In the context of pancreatic cancer, a negative correlation between ATX and YAP1 was observed. Both gemcitabine and LPA significantly reduced ATX protein expression through a negative feedback mechanism. Additionally, we found that HA130 notably inhibited YAP1 expression and decreased LPA concentration in the conditioned medium. While several studies have reported that various factors can activate YAP1 to enhance the malignancy of solid tumors^{[16, 36]}, the connection between YAP1 and post-chemotherapy regrowth in pancreatic cancer remains unclear. These findings suggest the presence of an LPA-YAP1 positive feedback loop in the tumor microenvironment after chemotherapy (Fig. 6). The results of the indirect co-culture model further confirmed that inhibiting YAP1 expression in reporter cells abrogated the pro-proliferative effect of chemotherapy-treated dying cells. Classical molecular biology experiments suggest that targeting the LPA-YAP1 signaling axis maybe an effective strategy to enhance chemotherapy efficacy.

Upregulation of the ATX-LPA signal in tumor cells can also effectively induce lymphocyte entry into secondary lymphoid organs^[37]. Therefore, the potential impact of the ATX-LPA signal on lymphocytes in tumor immune environments warrants further exploration. To further investigate, we utilized single-cell sequencing analysis to explore the impact of YAP1 on the pancreatic cancer tumor microenvironment. The results revealed that YAP1 might regulate the expression of various chemokines and cholesterol, suggesting a significant role of YAP1 in reprogramming the tumor environment. Specifically, YAP1 knockdown significantly inhibited IL6 and IL8 expression. Furthermore, GO analysis in this study suggests that YAP1 may be involved in T cell activation, integrin binding, and immune receptor activity, implying the potential of targeting the ATX-LPA-YAP1 signaling axis to improve the prognosis of PADC patients.

We humbly acknowledge the limitations of our study. Primarily, this research focused on in vitro mechanistic studies and lacks validation in in vivo models. Currently, a stable chemotherapeutic-induced repopulation mouse model has not been developed, unlike the well-established radiation-induced repopulation mouse model. Controlling the dosage and interval of gemcitabine administration in a chemotherapeutic-induced regrowth mouse model requires further exploration.

In this study, we demonstrated that gemcitabine induces the release of LPA from dying pancreatic cancer cells, which inhibits YAP1 phosphorylation and promotes YAP1 nuclear translocation. On one hand, YAP1 promotes the upregulation of various chemokines and cholesterol, creating a tumor microenvironment that supports pancreatic cancer survival. On the other hand, YAP1 overexpression facilitates the activation of ATX, inducing pancreatic cancer cells to release more LPA, thereby forming a positive feedback loop between LPA and YAP1. These mechanisms suggest the potential of targeting the LPA-YAP1 signaling axis to overcome chemoresistance, recurrence, and metastasis in pancreatic cancer (Fig. 7H).

Materials and reagents

The components and reagents used in the study were sourced from the following companies: Roswell Park Memorial Institute (RPMI, Gbico, USA) 1640 culture medium, Penicillin-Streptomycin solution (100×) from Hangzhou Jino Company, 10×PBS from Biyuntian Company, DMSO and Polybrene from Sigma, fetal bovine serum (FBS, Hyclone, USA), 0.25% trypsin-EDTA, Lipofectamine 2000, and puromycin from Gibco, and D-luciferin substrate from Promega.

Cell Cultures and Cultivation

Human pancreatic carcinoma cell lines, PATU8988T and AsPc-1, were procured from the American Type Culture Collection (ATCC, Manassas, VA, USA). These cells were cultured at 37°C in a humidified incubator (5% CO₂) using RPMI 1640 medium supplemented with 10% FBS. Short tandem repeat (STR) analysis was conducted to verify cell identities. All cell lines were confirmed to be free of mycoplasma contamination

Flow Cytometry for Apoptosis Detection

AsPC-1and PATU8988T cells (1 × 10⁵ cells/mL) were allowed to grow for 24 hours in a 6-well plate containing 10% FBS-supplemented 1640 medium. Subsequently, the cells were treated with different concentrations of gemcitabine (0, 5, and 10 µM/mL). After 48h, the cells were harvested and washed with cold PBS buffer. The cells were resuspended in a binding buffer and stained in the dark with 5µL of Annexin V-FITC and 5µL of propidium iodide precursor (Beyotime, Shanghai, China) at 4°C for 30 minutes. Stained cells were washed three times with the binding buffer to remove excess dye and then resuspended in 500µL of binding buffer. untreated cells served as negative controls. The percentage of apoptotic cells was analyzed within 1 hour using flow cytometry (BD, FACSCalibur, USA).

Tumor Repopulation Cell Model:

Pancreatic cancer cells treated with 1µM gemcitabine (IC50 concentration) for 48 to 72 hours were washed twice with 1 × PBS after discarding the supernatant, followed by replacing the medium with 2% serum and incubating for 24 hours. The adherent dying cells were collected and referred to as feeder cells.

In the direct co-culture model, 1×10⁵ dying cells were evenly seeded in 24-well plates. After attachment, 1000 GFP-labeled pancreatic cancer cells (Reporter cells) were uniformly seeded on top. The medium containing 2% serum was replaced every 48 hours, and images were captured every 24 to 48 hours under a fluorescence microscope to observe the proliferation activity of the reporter cells.

In the indirect co-culture model, 1×10⁵ normal pancreatic cancer cells were uniformly seeded in 24-well plates. Once the cells adhered, transwell inserts containing 3×10⁵ dying cells with 0.4µm pore size were placed above each well, ensuring the lower part of the transwell inserts was submerged in medium containing 2% serum. After 48 hours, the adherent pancreatic cells (Reporter cells) were collected, and their cell proliferation activity was assessed using a CCK-8 assay.

Cell Counting Kit-8 assay for the detection of proliferation

According to the manufacturer's instructions, cell viability was assessed using the Cell Counting Kit-8 (CCK8, Beyotime, Shanghai, China). Cells were seeded in a 96-well microplate (Corning, USA) at a density of 3 × 10³ cells per well in 100 µL of culture medium. Every 24 hours, 10 µL of CCK8 reagent was added to each well, followed by a 1hour incubation. The absorbance was analyzed at 450 nm using a microplate reader (Bio-Rad, Hercules, CA, USA).

Transwell Migration Assay

We added 1ml complete medium to the lower chamber of the Transwell invasion system. Subsequently, PATU8988T and AsPC-1 cells were resuspended in serum-free medium and seeded into the upper chamber at a density of 5 × 10⁴ cells per well. After 24 hours of incubation, we quantitatively assessed the number of cancer cells that traversed the membrane and compared it with the cancer cells cultured alone (NC).

Colony Formation Assay

The reporter cells were resuspended in 1640 medium containing 10% FBS and incubated at 37°C in a 5% CO₂ environment for 15 days to allow colony formation. The plates were then washed with cold PBS, and the colonies were fixed with 4% paraformaldehyde at room temperature. Subsequently, the colonies were stained with 1% crystal violet at room temperature for 30 minutes. Colonies were counted using a microscope (Leica Microsystems, Germany) after exceeding 100 cells per colony.

Lentivirus Infection:

Pancreatic cancer cells and drug screening were conducted by seeding 1 × 10⁶ PATU8988T and AsPC-1 cells, respectively, into six-well plates. After 24 hours, when the cells reached approximately 80% confluence, the culture medium was discarded. Then, 1 mL of viral culture medium was added to 1 mL of fresh culture medium with Polybrene (final concentration 1:1000) and added to the cells for continued cultivation. After 24 hours of infection, the expression of GFP in tumor cells was observed under a fluorescence microscope. If the brightness was uniform, the cells were collected and continued to be cultured in 10 cm culture dishes.

To obtain stable cells expressing the exogenous gene GFP-Luc, 24 hours after continuing cultivation, puromycin (1 µg/mL) was added to the cells for selection. The culture medium was changed every 3 days, and fresh puromycin was added for selection for a continuous period of 2 weeks. This yielded double-labeled cells, namely AsPC-1/GFP-Luc and PATU8988T/GFP-Luc. The expression of GFP in cells was observed under a fluorescence microscope and photographed. The labeled cells were expanded, and corresponding cells were stored.

Western blotting

The cells were collected by centrifugation and washed twice with cold PBS. Cell pellets were suspended in 100µl of ice-cold RIPA lysis buffer, incubated on ice for 30 minutes with vortexing every 10 minutes, and then centrifuged at 15,000g for 30 minutes. Immunoblot analysis was performed with 10µg of sample proteins on a 12% SDS-PAGE gel. Electrophoresis was conducted at 120V for 60 minutes, separating the proteins on the SDS-PAGE gel, and then transferring them to a PVDF membrane in cold transfer buffer using a wet transfer system at 300mA for 90 minutes. The PVDF membrane was blocked for 1 hours and then incubated with primary antibodies (diluted 1:1000) overnight at 4°C. Subsequently, the membrane was washed and incubated with secondary antibodies (diluted 1:4000) at room temperature for 1.5 hours. Protein bands were visualized using an ECL protein blot detection system (Tanon 4200), and band intensities were analyzed using Quantity One software. Antibodies against caspase-3 and YAP1 were obtained from Cell Signaling Technology, Inc. (Boston, USA). The antibody against GAPDH was sourced from Abcam, Inc. (Cambridge, USA). Secondary antibodies against rabbit or mouse were purchased from Boster Biotechnology company (Wuhan, China).

Total RNA and quantitative real-time polymerase chain reaction

According to the manufacturer's instructions, cDNA was generated using the RevertAid First Strand cDNA Synthesis Kit (Thermo Scientific). Real-time polymerase chain reaction (RT-PCR) was performed using PowerUp SYBR Green Master Mix (Thermo Fisher). β-actin was used as the internal control. The primer sequences are listed in Supplementary Table 1.

ELISA

According to the manufacturer's instructions, LPA levels were assessed using an ELISA kit (Bioo Scientific) in conditioned medium (CM) from cultured cells and patient serum samples.

Clinical analysis

Samples of cancer tissue and serum were collected from xx pancreatic cancer patients who underwent gemcitabine chemotherapy at the inpatient department of Shanghai East Hospital. The survival time of pancreatic cancer patients was evaluated from the date of diagnosis to the date of their last follow-up or death.

Single cell sequencing analysis and RNA-sequencing analysis

The pancreatic cancer single-cell RNA sequencing (scRNA-seq) data, GSE212966, was downloaded from the GEO platform (https://www.ncbi.nlm.nih.gov/geo/). A total of 44 Hippo pathway-related genes were collected from the MSigDB database (https://www.gsea-msigdb.org/gsea/msigdb/human/search.jsp). The detailed processing of the scRNA-seq data was as follows: 1) The scRNA-seq data was preprocessed using the "Seurat" package. The "PercentageFeatureSet" function was employed to determine the proportion of mitochondrial genes, and correlation analysis was performed to investigate the relationship between sequencing depth and the proportion of mitochondrial genes/total intracellular sequences. 2) Each gene was required to be expressed in at least 3 cells. 3) The expression level of genes in each cell was set to be greater than 300 and less than 5000, with mitochondrial content less than 10%, and the UMI count in each cell exceeding 1000. 4) After filtering the data, the "LogNormalize" method was used to normalize the scRNA-seq data.

We totally collected 38,981 cells from 6 scRNA-seq samples. 34,208 cells were reserved after quality control (Table s1). As shown in Fig.s1A and B, there is a strong correlation between UMI count and mRNA (r = 0.85), but no correlation exists between mRNA count and mitochondrial or ribosomal gene content (Fig. S1A and B). The top 2000 highly variable genes were identified for subsequent dimensionality reduction analysis (Fig. S1C). We used the principal component analysis (PCA) to estimate available dimensions and depicted the raw distribution of different samples. The result showed no substantial differences among all cells (Fig. S1D and E). The top 30 most unique principal components were selected for further investigation (Fig. S1F). After removing batch effects, the combined distribution of the CO (adjacent tissues) and PC (pancreatic cancer) samples is as depicted in Fig. S1G and H. We also presented the gene expression patterns of the top 15 PCs (Fig. S1I). Based on the clustering tree, a resolution of 1 was chosen, identifying a total of 26 clusters (Fig. S1J).

The RNA-sequencing expression profiles in the GSE57495 dataset were also retrieved from the GEO database. The detailed processing of the microarray data was as follows: 1) Gene symbols were obtained by converting probe IDs. 2) Probes that corresponded to multiple genes were removed. 3) When multiple probes corresponded to a single gene, the average value of these probes was considered as the gene expression level.

Statistical analysis

Statistical analysis was conducted using R (version 4.2.3) and GraphPad Prism 7. Results are presented as the mean ± SEM from three or more experimental replicates. Survival analysis was performed using the log-rank test and Kaplan-Meier analysis. Mean values between two groups were compared using the t-test. P < 0.05 was considered statistically significant.

PDAC

pancreatic ductal adenocarcinoma

LPE

lysopFFhosphatidylcholine

LPA

lysophosphatidic acid༛ATX:autotaxin

YAP1

yes-associated protein1

TEAD

Transcriptional enhanced associate domain

RPMI

Roswell Park Memorial Institute

FBS

Foetal Bovine Serum

MST1/2

The serine/threonine protein kinases3/4༛LATS1/2༚Large tumor suppressor1/2༛MRM:multiple reaction monitoring

TIC

total ion chromatogram

EMT༚Epithelial-mesenchymal transition༛PGE2༚Prostaglandin E2༛IL6༚Interleukin-6༛IL8༚Interleukin-8

SREBP-2

Sterol Regulatory Element-Binding Protein-2

GSEA

Gene set enrichment analysis.

Data availability statement

Raw data for all bioinformatics analyses can be found in TCGA (https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/).

Conflict of interest

The authors declare that they have no competing interests.

Funding

This study was supported by Public Institutions Livelihood Research Project of Science and Technology Development Foundation of Pudong (grant number PKJ2023-Y37, to Zhiqin Chen); National Natural Science Foundation of China (grant number 81972280, to Ming Quan);; Natural Science Foundation of Shanghai Municipality (grant number 23ZR1452300, to Ming Quan); Academic Leaders Training Program of Pudong Health Bureau of Shanghai (grant number PWRd2022-02, to Ming Quan).

Author Contribution

LY, DJ and LS contributed equally to this work. LY: design of the work and the implementation of the experiment. DJ: implementation of the experiment and write the manuscript. LS: design of the work and interpretation of data. JA: contributed materials /reagents /analysis tools. CZ and QM: design and revise the manuscript. All authors read and approved the final manuscript.

Acknowledgments

We are grateful for the support of lipidomics analysis provided by Wuhan Metware Biotechnology Company.

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LPA released from dying cancer cells after chemotherapy inactivates Hippo signaling and promotes pancreatic cancer cell repopulation

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Version 1

Abstract

Figures

Introduction

Results

2. Gemcitabine induced release of LPA and inactivation of the Hippo pathway in PDAC

3. LPA can promote the repopulation of residual tumor cells through YAP1

4. HA130 enhances gemcitabine-induced apoptosis

5. Single-cell sequencing reveals YAP1 may regulate multiple chemokines

Discussion

Methods

Materials and reagents

Cell Cultures and Cultivation

Flow Cytometry for Apoptosis Detection

Tumor Repopulation Cell Model:

Cell Counting Kit-8 assay for the detection of proliferation

Transwell Migration Assay

Colony Formation Assay

Lentivirus Infection:

Western blotting

Total RNA and quantitative real-time polymerase chain reaction

ELISA

Clinical analysis

Single cell sequencing analysis and RNA-sequencing analysis

Statistical analysis

Abbreviations

Declarations

Data availability statement

Conflict of interest

Funding

Author Contribution

Acknowledgments

References

Additional Declarations

Supplementary Files

Status:

Version 1