Targeting neoadjuvant chemotherapy-induced metabolic reprogramming in pancreatic cancer promotes anti-tumor immunity and chemo-response

scRNA-seq reveals chemotherapy-induced tumor microenvironment changes in pancreatic ductal adenocarcinoma

Background

Challenges have arisen in finding an effective treatment for pancreatic ductal adenocarcinoma (PDAC). Poor outcomes have fueled ongoing efforts to exploit the tumor microenvironment (TME) in the treatment of PDAC; however, to date, treatment strategies have largely failed. Thus, a comprehensive and deep understanding of the PDAC TME is necessary. The purpose of the present study was to investigate chemotherapy-induced tumor microenvironment changes and to optimize the response to immunotherapy in PDAC.

Methods

We analyzed publicly available single-cell RNA sequencing (scRNA-seq) PDAC (with or without standard chemotherapy) data and performed systematic analyses to elucidate novel mechanisms and to determinate the marker expression alteration induced by the chemotherapy.

Results

Lysozyme (LYZ), which is usually used as a myeloid marker, was significantly increased in the tumor cells, including myeloid cells responding to chemotherapy. Additionally, chemotherapy altered the mechanism of antigen presentation and modulated the TME, which may lead to tumor drug resistance and recurrence. Chemotherapy also affected the receptor of polio virus receptor (PVR) signaling, which shifted from TIGIT in T cells to CD226 in myeloid cells. Thus, PVR (rather than TIGIT) should be the target for treatment.

Conclusions

We described the characteristics of widely expressed markers in different cell types in PDAC. Chemotherapy disrupted the TME balance, altered tumor antigen presentation, and changed PVR signaling. Combining the appropriate chemical and immune therapies could improve the immune therapy response in PDAC.

Crosstalk between the tumor immune microenvironment and metabolic reprogramming in pancreatic cancer: new frontiers in immunotherapy

In recent years, the incidence and mortality of pancreatic cancer (PC) are increasing year by year. The highly heterogeneous nature of PC, its strong immune escape ability and easy metastasis make it the most lethal malignant tumor in the world. With the rapid development of sequencing technology, the complex components in the tumor microenvironment (TME) of PC have been gradually revealed. Interactions between pancreatic stellate cells, tumor-associated fibroblasts, various types of immune cells, and cancer cells collectively promote metabolic reprogramming of all types of cells. This metabolic reprogramming further enhances the immune escape mechanism of tumor cells and ultimately induces tumor cells to become severely resistant to chemotherapy and immunotherapy. On the one hand, PC cells achieve re and rational utilization of glucose, amino acids and lipids through metabolic reprogramming, which in turn accomplishes biosynthesis and energy metabolism requirements. Under such conditions, tumorigenesis, proliferation and metastasis are ultimately promoted. On the other hand, various types of immune cells in the tumor immune microenvironment (TIME) also undergo metabolic reprogramming, which leads to tumor progression and suppression of anti-immune responses by inhibiting the function of normal anti-tumor immune cells and enhancing the function of immunosuppressive cells. The aim of this review is to explore the interaction between the immune microenvironment and metabolic reprogramming in PC. The focus is to summarize the specific mechanisms of action of metabolic reprogramming of PC cells and metabolic reprogramming of immune cells. In addition, this review will summarize the mechanisms of immunotherapy resistance in PC cells. In the future, targeting specific mechanisms of metabolic reprogramming will provide a solid theoretical basis for the development of combination therapies for PC.

Development of a Nomogram Integrating Modified Inflammation-Based Indexes for Predicting Overall Survival in Pancreatic Cancer: A Retrospective Study

Background

Pancreatic cancer (PCA) is a highly malignant tumor with a 5-year survival rate of <10%. It is characterized as a cold tumor with an immunosuppressive microenvironment. Liver dysfunction due to biliary obstruction can affect the inflammation index, an indicator of immune status. Adjusting inflammation indices for liver function may enhance their clinical utility for predicting overall survival (OS) in PCA patients.

Methods

Resected PCA cases were selected using specific criteria. Liver function indicators identified by Spearman's analysis were integrated into a covariance analysis to refine inflammation indices, including modified neutrophil-to-lymphocyte ratio (mNLR), modified platelet-to-lymphocyte ratio (mPLR), modified lymphocyte-to-monocyte ratio (mLMR), modified systemic immune-inflammation index (mSII), and modified C-reactive protein (mCRP). These modified indices and clinicopathological factors were analyzed to identify independent OS predictors. A nomogram was developed and compared with a primary inflammation-based model using calibration curves, decision curve analysis (DCA), and the concordance index (C-index).

Results

Liver function indicators including direct bilirubin (DBIL), indirect bilirubin (IBIL), alanine aminotransferase (ALT), and aspartate aminotransferase (AST), lactate dehydrogenase (LDH), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), and albumin (ALB) were integrated to refine inflammation indices. In PCA patients, higher mNLR, mSII, CA19-9, T stage, and N stage were associated with worse OS, while higher mLMR or PNI levels correlated with better OS. Vascular invasion predicted poor OS, whereas chemotherapy improved OS. The nomogram model's clinical utility surpassed that of the primary inflammation-based model.

Conclusion

The nomogram incorporating modified inflammation indices demonstrated superior clinical utility. Adjusting inflammation indices for liver function is recommended for prognostic prediction, especially in PCA patients with biliary obstruction. For patients with advanced T and N staging or poorly differentiated tumors, intraoperative margin nanoknife ablation and timely postoperative adjuvant chemotherapy are recommended to enhance prognosis.

Enhanced integrated therapy for breast cancer employing Honokiol-loaded mesoporous polydopamine nanoparticles in conjunction with photothermal effects and low-dose metformin

Breast cancer remains a significant global health challenge, emphasizing the pressing need for innovative therapeutic approaches. Our thorough research investigates the potential of mesoporous polydopamine nanoparticles (MPDA) as a targeted treatment for breast cancer. Meticulously crafted, these nanoparticles were loaded with honokiol (HK), which is a natural product, and then coated with functionalized hyaluronic acid (HA) to boost their ability to target breast cancer cells that overexpress CD44 receptors. The deep penetrating and photothermal (PTT) composite nanosystem combined with low-dose metformin (Met) improves the efficacy of synergetic therapy against breast tumors. The designed nanosystem exhibited exceptional biocompatibility and stability, suggesting its suitability for therapeutic use. Our in vitro studies demonstrated that the nanosystem precisely targeted and penetrated breast cancer cells, resulting in significant cell death. Additionally, in vivo studies showed that the nanosystem markedly inhibited tumor growth compared to the control group. This tumor-inhibiting effect was due to the combined action of the encapsulated HK, free Met, and the photothermal effect induced by near-infrared laser irradiation. This combination potently stimulates the expression of cleaved caspase-3 and cleaved PARP proteins, ultimately triggering cell apoptosis and effectively curbing tumor proliferation. Our research not only underscores the promising potential of nanoparticles for targeted breast cancer therapy but also sets the stage for further exploration and development of novel nanomedicine-based therapeutic strategies.

CDCA7 enhances STAT3 transcriptional activity to regulate aerobic glycolysis and promote pancreatic cancer progression and gemcitabine resistance

Cell division cycle associated 7 (CDCA7) plays a role in various malignancies, especially pancreatic cancer (PC). However, its expression pattern and functional significance in PC require further research. Therefore, this study aimed to investigate CDCA7 expression levels and biological functions in PC using in vitro and in vivo experiments. Western blotting, immunohistochemistry, and real-time polymerase chain reaction were performed to detect CDCA7 expression in PC cells and tissues. Additionally, the biological functions of CDCA7 were assessed using cell proliferation, wound healing, and Transwell assays. CDCA7 overexpression promoted PC cell proliferation, migration, and invasion, and increased resistance to the chemotherapy drug gemcitabine, possibly through enhanced aerobic glycolysis. Additionally, immunoprecipitation assay showed that CDCA7 interacted with STAT3 protein and affected the transcriptional regulation of hexokinase 2. Conclusively, targeting CDCA7 might be a promising therapeutic strategy to increase gemcitabine sensitivity by inhibiting glycolysis in PC cells.

Heterogeneity of tertiary lymphoid structures predicts the response to neoadjuvant therapy and immune microenvironment characteristics in triple-negative breast cancer

BACKGROUND

Tertiary lymphoid structures (TLSs) impact cancer outcomes, including in triple-negative breast cancer (TNBC), where their role in immune modulation during neoadjuvant therapy (NAT) is underexplored.

METHODS

This study employed single-cell RNA sequencing (scRNA-seq), multiplex immunofluorescence (mIF) staining, and radiomic techniques to evaluate TLSs and the tumour microenvironment (TME) in TNBC patient samples before and after NAT.

RESULTS

The presence of TLSs in TNBC was associated with B-cell maturation and T-cell activation. Compared with TLS-low TNBC, TLS-high TNBC showed significantly greater expression of immunoglobulin family genes (IGHM and IGHG1) in B cells and greater cytotoxicity of neoantigen-specific CD8 + T cells (neoTCR8). Additionally, mIF revealed notable differences between TLSs and the TME in TNBC. Although CD8 + T-cell levels do not predict the NAT response effectively, TLS maturity strongly correlated with better NAT outcomes and prognosis (P < 0.05). An imaging biomarker scoring system was also developed to predict TLS status and NAT efficacy.

CONCLUSION

Our results demonstrated changes in TLSs and the TME in TNBC patients post-NAT. These findings confirm the predictive value of mature TLSs (mTLSs) and support the use of personalised immunotherapy based on post-NAT immune characteristics, thereby improving clinical outcomes.

Exploring the clinical significance of TPX2 in pancreatic cancer: from biomarker to immunotherapy

Pancreatic cancer (PC) is a highly aggressive malignancy characterized by a dismal prognosis. The present study is designed to elucidate the pivotal role of Xenopus kinesin-like protein 2 (TPX2) as a biomarker with substantial clinical prognostic significance in PC. By conducting a comprehensive analysis of RNA sequencing data and protein expression profiles obtained from multiple databases, we observed a pronounced upregulation of TPX2 expression in PC tissues compared to normal pancreatic tissues. Importantly, TPX2 emerged as an independent prognostic factor, demonstrating remarkable diagnostic accuracy. Notably, its expression levels were found to be significantly associated with the PC immune microenvironment and sensitivity to various therapeutic modalities. Functional assays revealed that the silencing of TPX2 markedly inhibited PC cell proliferation, metastasis, and the growth of subcutaneous tumors in PC mouse models. These effects were potentially mediated by the activation of CD8+ T cell immune responses and the inhibition of cell cycle progression and adhesion mechanisms. Taken together, our findings indicate that TPX2 may serve as a critical biomarker for the diagnosis and clinical management of patients with PC.

Targeting CA9 restricts pancreatic cancer progression through pH regulation and ROS production

PURPOSE

Lactate is a key metabolite produced by glycolytic metabolism, yet it also serves as an energy source for cancer cells. Lactate accumulation in the tumor microenvironment (TME) has been demonstrated to correlate with immunosuppressive TME and tumor progression. As a highly glycolytic tumor, it is crucial to decipher the underlying mechanism in pancreatic ductal adenocarcinoma (PDAC).

METHODS

Bioinformation analysis was used to identify lactate mediated carbonic anhydrase IX (CA9) upregulation. CCK-8, colony formation and mouse xenograft assay were utilized to study the effect of CA9 in PDAC. ECAR, OCR and pHi measurement confirmed the impacts of CA9 in Warburg phenotype. Using confocal microscopy, flow cytometry, qRT-PCR, co-IP, we validated the signaling pathways in PDAC to regulate reactive oxygen species (ROS) production.

RESULTS

We confirmed that CA9 is highly expressed in PDAC and positively regulated by lactate levels. CA9 can enhance the proliferative and migratory capabilities of PDAC cells. Pharmacologic inhibition or knockdown of CA9 significantly reduce pHi, increase the intracellular lactate and reverse the Warburg phenotype. The intracellular lactate accumulation caused by CA9 knockdown upregulates ROS and mitochondrial dysfunction. Furthermore, it was discovered that the competitive binding of CA9 with FUS inhibits the facilitation of FUS on NOX4 pre-mRNA splicing.

CONCLUSION

Collectively, our data illustrate that CA9 has a direct regulatory role in pHi homeostasis and ROS production, providing a potential therapeutic target for PDAC treatment.

Current hotspots and trends in cancer metabolic reprogramming: a scientometric analysis

Background

Metabolic reprogramming (MR) in cancer (CA) has been a focus of intense research in the recent two decades. This phenomenon has attracted great interest because it offers potential targets for cancer therapy. To capture the intellectual landscape of this field, we conducted a bibliometric analysis to assess the scientific output, major contributors, and trends in the MR/CA research.

Methods

We performed a systematic search using the Web of Science to retrieve articles published on MR of cancer from 2006 until 2023. The bibliometric tools such as Biblioshiny, VOSviewer, and Microsoft Excel were used to identify the most prolific authors, institutions, citation patterns, and keywords. We also used co-citation analysis to map the conceptual structure of the field and identify influential publications. Furthermore, we examined the literature by analyzing publication years, citations, and research impact factors.

Results

A total of 4,465 publications about MR/CA were retrieved. Publications on MR/CA increased rapidly from 2006 to 2023. Frontiers in Oncology published the most papers, while Cell Metabolism had the most citations. Highly cited papers were mainly published in Cancer Cell, Nature, Cell, Science and Cell Metabolism. China and the United States led the way in publications and contributed the most to MR/CA research. The University of Texas System, Chinese Academy of Sciences, and Fudan University were the most productive institutions. The profitable authors were Deberardinis Ralph J and Chiarugi Paola. The current topics included MR in tumorigenesis and progression of CA, MR of tumor cells and tumor microenvironment, the effect of MR on the CA treatment, the underlying mechanisms of MR (such as gene regulation, epigenetics, extracellular vesicles, and gut microbiota), and the modulation of MR. Some topics such as tumor microenvironment, lipid MR, circular RNA, long noncoding RNA, exosome, prognostic model, and immunotherapy may be the focus of MR/CA research in the next few years.

Conclusion

This study evaluated the global scientific output in the field of MR/CA research, analyzing its quantitative characteristics. It identified some significant and distinguished papers and compiled information regarding the current status and evolving trends of MR/CA research.

Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era

As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

Spatiotemporal metabolomic approaches to the cancer-immunity panorama: a methodological perspective

Metabolic reprogramming drives the development of an immunosuppressive tumor microenvironment (TME) through various pathways, contributing to cancer progression and reducing the effectiveness of anticancer immunotherapy. However, our understanding of the metabolic landscape within the tumor-immune context has been limited by conventional metabolic measurements, which have not provided comprehensive insights into the spatiotemporal heterogeneity of metabolism within TME. The emergence of single-cell, spatial, and in vivo metabolomic technologies has now enabled detailed and unbiased analysis, revealing unprecedented spatiotemporal heterogeneity that is particularly valuable in the field of cancer immunology. This review summarizes the methodologies of metabolomics and metabolic regulomics that can be applied to the study of cancer-immunity across single-cell, spatial, and in vivo dimensions, and systematically assesses their benefits and limitations.

Cancer cell metabolism and antitumour immunity

Accumulating evidence suggests that metabolic rewiring in malignant cells supports tumour progression not only by providing cancer cells with increased proliferative potential and an improved ability to adapt to adverse microenvironmental conditions but also by favouring the evasion of natural and therapy-driven antitumour immune responses. Here, we review cancer cell-intrinsic and cancer cell-extrinsic mechanisms through which alterations of metabolism in malignant cells interfere with innate and adaptive immune functions in support of accelerated disease progression. Further, we discuss the potential of targeting such alterations to enhance anticancer immunity for therapeutic purposes.

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.

Plasma metabolites as mediators in immune cell-pancreatic cancer risk: insights from Mendelian randomization

Background

Immune cells play a crucial role in the development and progression of pancreatic cancer, yet the causal relationship remains uncertain due to complex immune microenvironments and conflicting research findings. Mendelian randomization (MR), this study aims to delineate the causal relationships between immune cells and pancreatic cancer while identifying intermediary factors.

Methods

The genome-wide association study (GWAS) data on immune cells, pancreatic cancer, and plasma metabolites are derived from public databases. In this investigation, inverse variance weighting (IVW) as the primary analytical approach to investigate the causal relationship between exposure and outcome. Furthermore, this study incorporates MR-Egger, simple mode, weighted median, and weighted mode as supplementary analytical approaches. To ensure the reliability of our findings, we further assessed horizontal pleiotropy and heterogeneity and evaluated the stability of MR results using the Leave-one-out method. In conclusion, this study employed mediation analysis to elucidate the potential mediating effects of plasma metabolites.

Results

Our investigation revealed a causal relationship between immune cells and pancreatic cancer, highlighting the pivotal roles of CD11c+ monocytes (odds ratio, ORIVW=1.105; 95% confidence interval, 95%CI: 1.002-1.218; P=0.045), HLA DR+ CD4+ antigen-presenting cells (ORIVW=0.920; 95%CI: 0.873-0.968; P=0.001), and HLA DR+ CD8br T cells (ORIVW=1.058; 95%CI: 1.002-1.117; P=0.041) in pancreatic cancer progression. Further mediation analysis indicated that oxalate (proportion of mediation effect in total effect: -11.6%, 95% CI: -89.7%, 66.6%) and the mannose to trans-4-hydroxyproline ratio (-19.4, 95% CI: -136%, 96.8%) partially mediate the relationship between HLA DR+ CD8br T cells and pancreatic cancer in nature. In addition, our analysis indicates that adrenate (-8.39%, 95% CI: -18.3%, 1.54%) plays a partial mediating role in the association between CD11c+ monocyte and pancreatic cancer, while cortisone (-26.6%, 95% CI: 138%, -84.8%) acts as a partial mediator between HLA DR+ CD4+ AC and pancreatic cancer.

Conclusion

This MR investigation provides evidence supporting the causal relationship between immune cell and pancreatic cancer, with plasma metabolites serving as mediators. Identifying immune cell phenotypes with potential causal effects on pancreatic cancer sheds light on its underlying mechanisms and suggests novel therapeutic targets.

Construction of S100 family members prognosis prediction model and analysis of immune microenvironment landscape at single-cell level in pancreatic adenocarcinoma: a tumor marker prognostic study

Pancreatic adenocarcinoma characterized by a mere 10% 5-year survival rate, poses a formidable challenge due to its specific anatomical location, making tumor tissue acquisition difficult. This limitation underscores the critical need for novel biomarkers to stratify this patient population. Accordingly, this study aimed to construct a prognosis prediction model centered on S100 family members. Leveraging six S100 genes and their corresponding coefficients, an S100 score was calculated to predict survival outcomes. The present study provided comprehensive internal and external validation along with power evaluation results, substantiating the efficacy of the proposed model. Additionally, the study explored the S100-driven potential mechanisms underlying malignant progression. By comparing immune cell infiltration proportions in distinct patient groups with varying prognoses, the research identified differences driven by S100 expression. Furthermore, the analysis explored significant ligand-receptor pairs between malignant cells and immune cells influenced by S100 genes, uncovering crucial insights. Notably, the study identified a novel biomarker capable of predicting the sensitivity of neoadjuvant chemotherapy, offering promising avenues for further research and clinical application.

Genetically predicted blood metabolites mediate the association between circulating immune cells and pancreatic cancer: A Mendelian randomization study

BACKGROUND

Pancreatic cancer is characterized by metabolic dysregulation and unique immunological profiles. Nevertheless, the comprehensive understanding of immune and metabolic dysregulation of pancreatic cancer remains unclear. In the present study, we aimed to investigate the causal relationship of circulating immune cells and pancreatic cancer and identify the blood metabolites as potential mediators.

METHODS

The exposure and outcome genome-wide association studies (GWAS) data used in the present study were obtained from the GWAS open-access database (https://gwas.mrcieu.ac.uk). The study used 731 circulating immune cell features, 1400 types of blood metabolites and pancreatic cancer from GWAS. We then performed bidirectional Mendelian randomization (MR) analyses to explore the causal relationships between the circulating immune cells and pancreatic cancer, and two-step MR to discover potential mediating blood metabolites in this process. All statistical analyses were performed in R software. The STROBE-MR (i.e. Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization) checklist for the reporting of MR studies was also used.

RESULTS

MR analysis identified seven types of circulating immune cells causally associated with pancreatic cancer. Furthermore, there was no strong evidence that genetically predicted pancreatic cancer had an effect on these seven types of circulating immune cells. Further two-step MR analysis found 10 types of blood metabolites were causally associated with pancreatic cancer and the associations between circulating CD39+CD8+ T cells and pancreatic cancer were mediated by blood orotates with proportions of 5.18% (p = 0.016).

CONCLUSIONS

The present study provides evidence supporting the causal relationships between various circulating immune cells, especially CD39+CD8+ T cells, and pancreatic cancer, with a potential effect mediated by blood orotates. Further research is needed on additional risk factors as potential mediators and establish a comprehensive immunity-metabolism network in pancreatic cancer.

EPYC functions as a novel prognostic biomarker for pancreatic cancer

Pancreatic cancer (PC) has become a worldwide challenge attributed to its difficult early diagnosis and rapid progression. Treatments continue to be limited besides surgical resection. Hence, we aimed to discover novel biological signatures as clinically effective therapeutic targets for PC via the mining of public tumor databases. We found that epiphycan (EPYC) could function as an independent risk factor to predict the poor prognosis in PC based on integrated bioinformatics analysis. We downloaded associated PC data profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) online websites, then applied the software Rstudio to filter out genes under the strict criteria. After the batch survival analysis using Log-rank test and univariate cox regression, we obtained 39 candidate genes. Subsequently, we narrowed the scope to 8 genes by establishing a Lasso regression model. Eventually, we focused on 2 genes (EPYC and MET) by further building a multivariate cox regression model. Given that the role of EPYC in PC remains obscure, we then performed a series of molecular functional experiments, including RT-qPCR, CCK8, EdU, colony formation, Transwell, western blot, cell live-dead staining, subcutaneous tumor formation, to enhance our insight into its underlying molecular mechanisms. The above results demonstrated that EPYC was highly expressed in PC cell lines and could promote the proliferation of PCs via PI3K-AKT signaling pathway in vivo and in vitro. We arrived at a conclusion that EPYC was expected to be a biological neo-biomarker for PC followed by being a potential therapeutic target.

Tumor immune microenvironment-based therapies in pancreatic ductal adenocarcinoma: time to update the concept

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid tumors. The tumor immune microenvironment (TIME) formed by interactions among cancer cells, immune cells, cancer-associated fibroblasts (CAF), and extracellular matrix (ECM) components drives PDAC in a more immunosuppressive direction: this is a major cause of therapy resistance and poor prognosis. In recent years, research has advanced our understanding of the signaling mechanism by which TIME components interact with the tumor and the evolution of immunophenotyping. Through revolutionary technologies such as single-cell sequencing, we have gone from simply classifying PDACs as "cold" and "hot" to a more comprehensive approach of immunophenotyping that considers all the cells and matrix components. This is key to improving the clinical efficacy of PDAC treatments. In this review, we elaborate on various TIME components in PDAC, the signaling mechanisms underlying their interactions, and the latest research into PDAC immunophenotyping. A deep understanding of these network interactions will contribute to the effective combination of TIME-based therapeutic approaches, such as immune checkpoint inhibitors (ICI), adoptive cell therapy, therapies targeting myeloid cells, CAF reprogramming, and stromal normalization. By selecting the appropriate integrated therapies based on precise immunophenotyping, significant advances in the future treatment of PDAC are possible.