Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis and limited therapeutic options. Research on the tumor microenvironment (TME) of PDAC has propelled the development of immunotherapeutic and targeted therapeutic strategies with a promising future. The emergence of single-cell sequencing and mass spectrometry technologies, coupled with spatial omics, has collectively revealed the heterogeneity of the TME from a multiomics perspective, outlined the development trajectories of cell lineages, and revealed important functions of previously underrated myeloid cells and tumor stroma cells. Concurrently, these findings necessitated more refined annotations of biological functions at the cell cluster or single-cell level. Precise identification of all cell clusters is urgently needed to determine whether they have been investigated adequately and to identify target cell clusters with antitumor potential, design compatible treatment strategies, and determine treatment resistance. Here, we summarize recent research on the PDAC TME at the single-cell multiomics level, with an unbiased focus on the functions and potential classification bases of every cellular component within the TME, and look forward to the prospects of integrating single-cell multiomics data and retrospectively reusing bulk sequencing data, hoping to provide new insights into the PDAC TME.

DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data.

Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional manual gating utilized to identify new cell populations has been inadequate, inefficient, unreliable, and difficult to use, and no algorithms to identify both calibration and new cell populations has been well established. A deep learning with graphic cluster (DGCyTOF) visualization is developed as a new integrated embedding visualization approach in identifying canonical and new cell types. The DGCyTOF combines deep-learning classification and hierarchical stable-clustering methods to sequentially build a tri-layer construct for known cell types and the identification of new cell types. First, deep classification learning is constructed to distinguish calibration cell populations from all cells by softmax classification assignment under a probability threshold, and graph embedding clustering is then used to identify new cell populations sequentially. In the middle of two-layer, cell labels are automatically adjusted between new and unknown cell populations via a feedback loop using an iteration calibration system to reduce the rate of error in the identification of cell types, and a 3-dimensional (3D) visualization platform is finally developed to display the cell clusters with all cell-population types annotated. Utilizing two benchmark CyTOF databases comprising up to 43 million cells, we compared accuracy and speed in the identification of cell types among DGCyTOF, DeepCyTOF, and other technologies including dimension reduction with clustering, including Principal Component Analysis (PCA), Factor Analysis (FA), Independent Component Analysis (ICA), Isometric Feature Mapping (Isomap), t-distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP) with k-means clustering and Gaussian mixture clustering. We observed the DGCyTOF represents a robust complete learning system with high accuracy, speed and visualization by eight measurement criteria. The DGCyTOF displayed F-scores of 0.9921 for CyTOF1 and 0.9992 for CyTOF2 datasets, whereas those scores were only 0.507 and 0.529 for the t-SNE+k-means; 0.565 and 0.59, for UMAP+ k-means. Comparison of DGCyTOF with t-SNE and UMAP visualization in accuracy demonstrated its approximately 35% superiority in predicting cell types. In addition, observation of cell-population distribution was more intuitive in the 3D visualization in DGCyTOF than t-SNE and UMAP visualization. The DGCyTOF model can automatically assign known labels to single cells with high accuracy using deep-learning classification assembling with traditional graph-clustering and dimension-reduction strategies. Guided by a calibration system, the model seeks optimal accuracy balance among calibration cell populations and unknown cell types, yielding a complete and robust learning system that is highly accurate in the identification of cell populations compared to results using other methods in the analysis of single-cell CyTOF data. Application of the DGCyTOF method to identify cell populations could be extended to the analysis of single-cell RNASeq data and other omics data.

Epidemiology of pancreatic cancer: New version, new vision.

Pancreatic cancer (PC) is a devastating malignancy with an extremely high mortality rate and poses significant challenges to healthcare systems worldwide. The prevalence of PC risk factors spiked over the years, leading to a global increase in PC incidence rates. The contribution of different risk factors, however, varied from region to region due to genetic predisposition, environmental, social, and political factors underlying disease prevalence in addition to public health strategies. This comprehensive review aims to provide a thorough analysis of the epidemiology of PC, discussing its incidence, risk factors, screening strategies and socioeconomic burden. We compiled a wide range of seminal studies as well as epidemiological investigations to serve this review as a comprehensive guide for researchers, healthcare professionals, and policymakers keen for a more profound understanding of PC epidemiology. This review highlights the essentiality of persistent research efforts, interdisciplinary collaboration, and public health initiatives to address the expanding burden of this malignancy.

HIF-1α-regulated stanniocalcin-1 mediates gemcitabine resistance in pancreatic ductal adenocarcinoma via PI3K/AKT signaling pathway.

Pancreatic ductal adenocarcinoma (PDAC) has a poor response to the first-line chemotherapy drug gemcitabine. We previously identified stanniocalcin-1 as a gemcitabine-resistant-related gene, but its specific role and function in pancreatic cancer remain unclear. RT-qPCR and Western blot were used to evaluate differential protein and mRNA expressions. The biological functions of genes were determined using proliferation and drug-resistance experiments. Subcutaneous tumorigenesis experiment was performed on nude mice. Prognostic analysis was performed using public databases and our clinical data. We found HIF-1α-regulated STC1 expression mediated chemoresistance in pancreatic cancer. Deeper, we explored the action mechanism of STC1 and identified PI3K/AKT as the downstream signaling pathway of STC1. Furthermore, we analyzed clinical data and found that STC1 expression was related to the prognosis of gemcitabine-treated patients after surgery. In general, we proved the HIF-1α/STC1/PI3K-AKT axis participated in PDAC progression and chemoresistance, and STC1 may serve as a potential prognostic factor and therapeutic target for PDAC treatment.

Expression, function and clinical application of stanniocalcin-1 in cancer.

The glycoprotein stanniocalcin-1 functions as a regulatory endocrine hormone that maintains the balance of calcium and phosphorus in bony fish and as a paracrine/autocrine factor involved in many physiological/pathological processes in humans, including carcinogenesis. In this review, we provide an overview of (a) the possible mechanisms through which STC1 affects the malignant properties of cancer, (b) transcriptional and post-transcriptional regulation pathways of STC1 and (c) the potential clinical relevance of STC1 as a cancer biomarker and even a therapeutic target in the future. Exploring the role of STC1 in cancer development may provide a better understanding of the tumorigenesis process in humans and may facilitate finding an effective therapeutic method against cancer.

Novel therapeutic strategies and perspectives for metastatic pancreatic cancer: vaccine therapy is more than just a theory.

Pancreatic cancer is an aggressive and malignant tumor with an exceedingly high mortality rate. The quality of life and survival rates of pancreatic cancer patients with metastasis are poor compared with those without metastasis. Thus far, no effective treatment strategy has been established for metastatic pancreatic cancer patients. Therefore, an appropriate therapeutic method based on the elimination of metastatic pancreatic cancer is critical to improve patient outcome. Tumor-targeted vaccines have been widely discussed in recent studies and enabled important breakthroughs in the treatment of pancreatic cancer by preventing the escape of tumor cells from immune surveillance and activating the immune system to eliminate cancer cells. T cells can be activated by the stimulation of tumor-targeted vaccines, but to mount an effective immune response, both immune checkpoint inhibitors and positive costimulatory molecules are required. In this review, we discuss potential tumor-targeted vaccines that can target pancreatic cancer, elaborate the probably appropriate combination of vaccines therapy and evaluate the underlying benefits as well as obstacles in the current therapy for metastatic pancreatic cancer.

Role of the microbiome in occurrence, development and treatment of pancreatic cancer.

Pancreatic cancer is one of the most lethal malignancies. Recent studies indicated that development of pancreatic cancer may be intimately connected with the microbiome. In this review, we discuss the mechanisms through which microbiomes affect the development of pancreatic cancer, including inflammation and immunomodulation. Potential therapeutic and diagnostic applications of microbiomes are also discussed. For example, microbiomes may serve as diagnostic markers for pancreatic cancer, and may also play an important role in determining the efficacies of treatments such as chemo- and immunotherapies. Future studies will provide additional insights into the various roles of microbiomes in pancreatic cancer.

FBXO32 Stimulates Protein Synthesis to Drive Pancreatic Cancer Progression and Metastasis.

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death worldwide, primarily due to its rapid progression. The current treatment options for PDAC are limited, and a better understanding of the underlying mechanisms responsible for PDAC progression is required to identify improved therapeutic strategies. In this study, we identified FBXO32 as an oncogenic driver in PDAC. FBXO32 was aberrantly upregulated in PDAC, and high FBXO32 expression was significantly associated with an unfavorable prognosis in patients with PDAC. FRG1 deficiency promoted FBXO32 upregulation in PDAC. FBXO32 promoted cell migration and invasion in vitro and tumor growth and metastasis in vivo. Mechanistically, FBXO32 directly interacted with eEF1A1 and promoted its polyubiquitination at the K273 site, leading to enhanced activity of eEF1A1 and increased protein synthesis in PDAC cells. Moreover, FBXO32-catalyzed eEF1A1 ubiquitination boosted the translation of ITGB5 mRNA and activated focal adhesion kinase (FAK) signaling, thereby facilitating focal adhesion assembly and driving PDAC progression. Importantly, interfering with the FBXO32-eEF1A1 axis or pharmaceutical inhibition of FAK by defactinib, an FDA-approved FAK inhibitor, substantially inhibited PDAC growth and metastasis driven by aberrantly activated FBXO32-eEF1A1 signaling. Overall, this study uncovers a mechanism by which PDAC cells rely on FBXO32-mediated eEF1A1 activation to drive progression and metastasis. FBXO32 may serve as a promising biomarker for selecting eligible patients with PDAC for treatment with defactinib. Significance: FBXO32 upregulation in pancreatic cancer induced by FRG1 deficiency increases eEF1A1 activity to promote ITGB5 translation and stimulate FAK signaling, driving cancer progression and sensitizing tumors to the FAK inhibitor defactinib.

Human Equilibrative Nucleoside Transporter 1: Novel Biomarker and Prognostic Indicator for Patients with Gemcitabine-Treated Pancreatic Cancer.

Aim: This article aimed to find appropriate pancreatic cancer (PC) patients to treat with Gemcitabine with better survival outcomes by detecting hENT1 levels. Methods: We collected surgical pathological tissues from PC patients who received radical surgery in our hospital from September 2004 to December 2014. A total of 375 PC tissues and paired adjacent nontumor tissues were employed for the construction of 4 tissue microarrays (TMAs). The quality of the 4 TMAs was examined by HE staining. We performed immunohistochemistry analysis to evaluate hENT1 expression in the TMAs. Moreover, we detected hENT1 expression level and proved the role of hENT1 in cell proliferation, drug resistance, migration and invasion in vivo and vitro. Results: The results indicated that low hENT1 expression indicated a significantly poor outcome in PC patients, including shortened DFS (21.6±2.8 months versus 36.9±4.0 months, p<0.001) and OS (33.6±3.9 versus 39.6±3.9, p=0.004). Meanwhile, patients in stage I/II of TNM stage had a longer OS (40.2±3.4 versus 15.4±1.7, p=0.002) and DFS (31.0±3.1 versus 12.4±1.9, p=0.016) than patients in stage III/IV. Patients in M0 stage had a longer OS (39.7±3.4 versus 16.2±1.9, p=0.026) and DFS(30.7±3.0 versus 11.8±2.2, p=0.031) than patients in M1 stage, and patients with tumors not invading the capsule had a better DFS than those with tumor invasion into the capsule (30.8±3.0 versus 12.6±2.3, p=0.053). Patients with preoperative CA19-9 values ≤467 U/mL have longer DFS than that of patients who had preoperative CA19-9 values >467 U/mL (37.9±4.1 versus 22.9±4.0, p=0.04). In the subgroup analysis, a high hENT1 expression level was related to a longer OS(39.4±4.0 versus 31.5±3.9, p=0.001) and DFS(35.7±4.0 versus 20.6±2.7; p<0.0001) in the Gemcitabine subgroup. Conclusion: PC patients with high hENT1 expression have a better survival outcomes when receiving Gemcitabine. hENT1 expression can be a great prognostic indicator for PC patients to receive Gemcitabine treatment.

E3 ubiquitin ligase RBCK1 confers ferroptosis resistance in pancreatic cancer by facilitating MFN2 degradation.

Ferroptosis, a novel form of iron-dependent non-apoptotic cell death, plays an active role in the pathogenesis of diverse diseases, including cancer. However, the mechanism through which ferroptosis is regulated in pancreatic ductal adenocarcinoma (PDAC) remains unclear. Here, our study, via combining bioinformatic analysis with experimental validation, showed that ferroptosis is inhibited in PDAC. Genome-wide sequencing further revealed that the ferroptosis activator imidazole ketone erastin (IKE) induced upregulation of the E3 ubiquitin ligase RBCK1 in PDAC cells at the transcriptional or translational level. RBCK1 depletion or knockdown rendered PDAC cells more vulnerable to IKE-induced ferroptotic death in vitro. In a mouse xenograft model, genetic depletion of RBCK1 increased the killing effects of ferroptosis inducer on PDAC cells. Mechanistically, RBCK1 interacts with and polyubiquitylates mitofusin 2 (MFN2), a key regulator of mitochondrial dynamics, to facilitate its proteasomal degradation under ferroptotic stress, leading to decreased mitochondrial reactive oxygen species (ROS) production and lipid peroxidation. These findings not only provide new insights into the defense mechanisms of PDAC cells against ferroptotic death but also indicate that targeting the RBCK1-MFN2 axis may be a promising option for treating patients with PDAC.

The NF-κB/NUAK2 signaling axis regulates pancreatic cancer progression by targeting SMAD2/3.

Nuclear factor kappa B (NF-κB) plays a pivotal role in the development of pancreatic cancer, and its phosphorylation has previously been linked to the regulation of NUAK2. However, the regulatory connection between NF-κB and NUAK2, as well as NUAK2's role in pancreatic cancer, remains unclear. In this study, we observed that inhibiting NUAK2 impeded the proliferation, migration, and invasion of pancreatic cancer cells while triggering apoptosis. NUAK2 overexpression partially resisted apoptosis and reversed the inhibitory effects of the NF-κB inhibitor. NF-κB transcriptionally regulated NUAK2 transcription by binding to the promoter region of NUAK2. Mechanistically, NUAK2 knockdown remarkably reduced the expression levels of p-SMAD2/3 and SMAD2/3, resulting in decreased nuclear translocation of SMAD4. In SMAD4-negative cells, NUAK2 knockdown impacted FAK signaling by downregulating SMAD2/3. Moreover, NUAK2 knockdown heightened the sensitivity of pancreatic cancer cells to gemcitabine, suggesting that NUAK2 inhibitors could be a promising strategy for pancreatic cancer treatment.

Multiomics integration reveals NETosis heterogeneity and TLR2 as a prognostic biomarker in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant neoplasm characterized by a poor prognosis and limited therapeutic strategy. The PDAC tumor microenvironment presents a complex heterogeneity, where neutrophils emerge as the predominant constituents of the innate immune cell population. Leveraging the power of single-cell RNA-seq, spatial RNA-seq, and multi-omics approaches, we included both published datasets and our in-house patient cohorts, elucidating the inherent heterogeneity in the formation of neutrophil extracellular traps (NETs) and revealed the correlation between NETs and immune suppression. Meanwhile, we constructed a multi-omics prognostic model that suggested the patients exhibiting downregulated expression of NETs may have an unfavorable outcome. We also confirmed TLR2 as a potent prognosis factor and patients with low TLR2 expression had more effective T cells and an overall survival extension for 6 months. Targeting TLR2 might be a promising strategy to reverse immunosuppression and control tumor progression for an improved prognosis.

Ribosome profiling: a powerful tool in oncological research.

Neoplastic cells need to adapt their gene expression pattern to survive in an ever-changing or unfavorable tumor microenvironment. Protein synthesis (or mRNA translation), an essential part of gene expression, is dysregulated in cancer. The emergence of distinct translatomic technologies has revolutionized oncological studies to elucidate translational regulatory mechanisms. Ribosome profiling can provide adequate information on diverse aspects of translation by aiding in quantitatively analyzing the intensity of translating ribosome-protected fragments. Here, we review the primary currently used translatomics techniques and highlight their advantages and disadvantages as tools for translatomics studies. Subsequently, we clarified the areas in which ribosome profiling could be applied to better understand translational control. Finally, we summarized the latest advances in cancer studies using ribosome profiling to highlight the extensive application of this powerful and promising translatomic tool.

Single-cell RNA-seq reveals heterogeneity in metastatic renal cell carcinoma and effect of anti-angiogenesis therapy in the pancreas metastatic lesion.

Metastatic clear cell renal cell carcinoma has heterogenous tumor microenvironment (TME). Among the metastatic lesions, pancreas metastasis is rare and controversy in treatment approaches. Here, extensive primary and metastatic lesion samples were included by single-cell RNA-seq to decipher the distinct metastasis TME. The hypoxic and inflammatory TME of pancreas metastasis was decoded in this study, and the activation of PAX8-myc signaling, and metabolic reprogramming were observed. The active components including endothelial cells, fibroblasts and T cells were profiled. Meanwhile, we also evaluated the effect of anti-angiogenesis treatment in the pancreas metastasis patient. The potential mechanisms of pancreatic tropism, instability of genome, and the response of immunotherapy were also discussed in this work. Taken together, our findings suggest a clue to the heterogeneity in metastasis TME and provide evidence for the treatment of pancreas metastasis in renal cell carcinoma patients.

CALB2 drives pancreatic cancer metastasis through inflammatory reprogramming of the tumor microenvironment.

BACKGROUND: Early dissemination to distant organs accounts for the dismal prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). Chronic, dysregulated, persistent and unresolved inflammation provides a preferred tumor microenvironment (TME) for tumorigenesis, development, and metastasis. A better understanding of the key regulators that maintain inflammatory TME and the development of predictive biomarkers to identify patients who are most likely to benefit from specific inflammatory-targeted therapies is crucial for advancing personalized cancer treatment. METHODS: This study identified cell-specific expression of CALB2 in human PDAC through single-cell RNA sequencing analysis and assessed its clinicopathological correlations in tissue microarray using multi-color immunofluorescence. Co-culture systems containing cancer-associated fibroblasts (CAFs) and patient-derived organoids (PDOs) in vitro and in vivo were employed to elucidate the effects of CALB2-activated CAFs on PDAC malignancy. Furthermore, CUT&RUN assays, luciferase reporter assays, RNA sequencing, and gain- or loss-of-function assays were used to unravel the molecular mechanisms of CALB2-mediated inflammatory reprogramming and metastasis. Additionally, immunocompetent KPC organoid allograft models were constructed to evaluate CALB2-induced immunosuppression and PDAC metastasis, as well as the efficacy of inflammation-targeted therapy. RESULTS: CALB2 was highly expressed both in CAFs and cancer cells and correlated with an unfavorable prognosis and immunosuppressive TME in PDAC patients. CALB2 collaborated with hypoxia to activate an inflammatory fibroblast phenotype, which promoted PDAC cell migration and PDO growth in vitro and in vivo. In turn, CALB2-activated CAFs upregulated CALB2 expression in cancer cells through IL6-STAT3 signaling-mediated direct transcription. In cancer cells, CALB2 further activated Ca2+-CXCL14 inflammatory axis to facilitate PDAC metastatic outgrowth and immunosuppression. Genetic or pharmaceutical inhibition of CXCL14 significantly suppressed CALB2-mediated metastatic colonization of PDAC cells in vivo and extended mouse survival. CONCLUSIONS: These findings identify CALB2 as a key regulator of inflammatory reprogramming to promote PDAC metastatic progression. Combination therapy with αCXCL14 monoclonal antibody and gemcitabine emerges as a promising strategy to suppress distant metastasis and improve survival outcomes in PDAC with CALB2 overexpression.

New animal models of Alzheimer's disease that display insulin desensitization in the brain.

Alzheimer's disease (AD) is a complex neurodegenerative disorder, which involves many underlying pathological processes. Recently, it has been demonstrated that AD also includes impairments of insulin signaling in the brain. Type 2 diabetes is a risk factor for AD, and AD and diabetes share a number of pathologies. The classical hallmarks of AD are senile plaques and neurofibrillary tangles, which consist of amyloid-ß and hyperphosphorylated tau. Based on the two hallmarks, transgenic animal models of AD have been developed, which express mutant human genes of amyloid precursor protein, presenilin-1/2, and tau. It is likely that these mouse models are too limited in their pathology. In this work, we describe mouse models that model diabetes and show insulin signaling impairment as well as neurodegenerative pathologies that are similar to those seen in the brains of AD patients. The combination of traditional AD mouse models with induced insulin impairments in the brain may be a more complete model of AD. Interestingly, AD mouse models treated with drugs that have been developed to cure type 2 diabetes have shown impressive outcomes. Based on these findings, several ongoing clinical trials are testing long lasting insulin analogues or GLP-1 mimetics in patients with AD.

Sensitization of Guinea Pig Skin to Imported Fire Ant Alkaloids and Establishment of an Inflammatory Model.

Imported fire ants (IFAs), Solenopsis invicta, release their venom through multiple stings that induce inflammation, allergies, shock, and even death. Although IFA venom protein sensitization and related subcutaneous immunotherapy have been studied, few studies have examined the potential toxicity or pathogenicity of alkaloids, the main substances in IFA venom. Here, IFA alkaloids were identified and analyzed by gas chromatography-mass spectrometry; we further determined an appropriate extraction method and its effectiveness for extracting high-purity alkaloids through comparative analysis and guinea pig skin sensitivity tests. The alkaloids released from the IFA abdomen included those present in the head and thorax, and the alkaloids in the abdomen accounted for the highest proportion of the total extract. The abdominal extirpation method yielded alkaloids with a purity above 97%, and the skin irritation response score and histopathological diagnosis suggest that intradermal injection of the extracted alkaloids produced symptoms effectively simulating those of IFA stings. The successful establishment of an inflammatory model in guinea pigs stung by IFAs provides a basis for further research on the mechanism of inflammatory diseases caused by IFAs.

Organoid: Bridging the gap between basic research and clinical practice.

Nowadays, the diagnosis and treatment system of malignant tumors has increasingly tended to be more precise and personalized while the existing tumor models are still unable to fully meet the needs of clinical practice. Notably, the emerging organoid platform has been proven to have huge potential in the field of basic-translational medicine, which is expected to promote a paradigm shift in personalized medicine. Here, given the unique advantages of organoid platform, we mainly explore the prominent role of organoid models in basic research and clinical practice from perspectives of tumor biology, tumorigenic microbes-host interaction, clinical decision-making, and regenerative strategy. In addition, we also put forward some practical suggestions on how to construct a new generation of organoid platform, which is destined to vigorously promote the reform of basic-translational medicine.

mTOR inhibitor, gemcitabine and PD-L1 antibody blockade combination therapy suppresses pancreatic cancer progression via metabolic reprogramming and immune microenvironment remodeling in Trp53flox/+LSL-KrasG12D/+Pdx-1-Cre murine models.

OBJECTIVE: Resistance to immunotherapy and chemotherapy hinders the prognosis of pancreatic cancer(PC). We hypothesized that the combination of mTOR inhibitor sirolimus and gemcitabine would change the metabolic landscape of PC and enhance the anti-PD-L1 therapy. METHODS: In KPC mice, the following regimens were administered and tumor growth inhibition rates(TGI%) were calculated: sirolimus(S), PD-L1 antibody(P), gemcitabine(G), sirolimus + PD-L1 antibody(SP), sirolimus + gemcitabine(SG), PD-L1 + gemcitabine(PG) and sirolimus + PD-L1 antibody + gemcitabine(SPG). The metabolic changes of tumors were identified by LC-MS and subpopulations of immune cells were measured by flow cytometry. Sirolimus treated macrophages were co-cultured with PC cells in vitro, and the metabolic changes of macrophages and tumor cells as well as tumor cells' viability were detected. RESULTS: The monotherapy of S, P and G didn't inhibit tumor growth significantly. The combination of SP, PG and SG didn't improve the TGI% significantly compared with monotherapy. However, the TGI% of SPG combination was higher than other groups. The proportion of CD68+ macrophages increased in the peripheral blood and CD8+ T cells decreased in the tumor tissues after SPG treatment. LC-MS identified 42 differential metabolites caused by sirolimus in SPG group, among which 10 metabolites had potential effects on macrophages. Sirolimus treated M1 and M2 macrophages inhibited the proliferation of tumor cells and decreased tumor cells' glycolysis. The glycolysis of M2 macrophages was increased by sirolimus. CONCLUSIONS: mTOR inhibitor can change the immune microenvironment of PC via metabolic reprogramming, thus promoting the efficacy of PD-L1 blockade when combined with gemcitabine.