Stromal biology and therapy in pancreatic cancer: ready for clinical translation?

Stromal fibrin shapes immune infiltration landscape of pancreatic ductal adenocarcinoma

In pancreatic ductal adenocarcinoma (PDAC), in-situ coagulation creates a thrombotic, crosslinked fibrin (x-fibrin)-rich tumor stroma (FibTS), whose impact on immune cell behavior remains unclear. We aimed to elucidate how FibTS in PDAC regulates immune cell infiltration, polarization, and crosstalk that favors immunosuppressive microenvironment and tumor growth. We assessed the spatial distribution of immune cells by multiplex immunostaining of human PDAC tissues, along with novel bioengineering and mouse tumor models. We investigated how FibTS influences the infiltration of tumor-associated macrophage (TAM) and T-cell subtypes and identified two distinct variants of PDAC, fibrin-high (Fibhi) and fibrin-low (Fiblow). Our findings reveal that PDAC cells secrete fibrinogen and thrombin to form FibTS, which acts as a physical barrier and biochemical niche that restricts CD8+ T-cell and TAM penetration into the tumor. The FibTS impeded immune cell penetration from the tumor stroma into the tumor parenchyma. Selective inhibition of FibTS formation by genetic and pharmacological tools altered the infiltration patterns of CD8+ T-cells and TAMs, decelerating PDAC growth. This study demonstrates that the barrier function of FibTS is crucial for immune evasion, particularly against macrophage and T-cell activity, presenting a potential therapeutic strategy to reshape the immune landscape within PDAC and slow tumor progression.

The function of microRNA related to cancer-associated fibroblasts in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignant tumor characterized by a poor prognosis. A prominent feature of PDAC is the rich and dense stroma present in the tumor microenvironment (TME), which significantly hinders drug penetration. Cancer-associated fibroblasts (CAFs), activated fibroblasts originating from various cell sources, including pancreatic stellate cells (PSCs) and mesenchymal stem cells (MSCs), play a critical role in PDAC progression and TME formation. MicroRNAs (miRNAs) are small, single-stranded non-coding RNA molecules that are frequently involved in tumorigenesis and progression, exhibiting either oncolytic or oncogenic activity. Increasing evidence suggests that aberrant expression of miRNAs can mediate interactions between cancer cells and CAFs, thereby providing novel therapeutic targets for PDAC treatment. In this review, we will focus on the potential roles of miRNAs that target CAFs or CAFs-derived exosomes in PDAC progression, highlighting the feasibility of therapeutic strategies aimed at restoring aberrantly expressed miRNAs associated with CAFs, offering new pathways for the clinical management of PDAC.

Real-time functional proteomics enhances therapeutic targeting in precision oncology molecular tumor boards

Collaborative review of molecular profiling data by multidisciplinary molecular tumor boards (MTB) is increasingly important for improving patient management and outcomes, though currently relies nearly exclusively on nucleic acid next-generation sequencing (NGS) and limited panels of immunohistochemistry-based protein abundance data. We examined the feasibility of incorporating real-time laser microdissection (LMD) enrichment of tumor epithelium and commercial CLIA-based reverse phase protein array (RPPA) protein drug target expression/activation profiling into our cancer center's MTB to complement standard clinical NGS-based profiling. The LMD-RPPA workflow was performed within a therapeutically permissive timeframe with a median dwell time of nine days, during which specimens were processed outside of standard clinical workflows. The RPPA-generated data supported additional and/or alternative therapeutic considerations for 54% of profiled patients following review by the MTB. These findings suggest that integrating proteomic/phosphoproteomic and NGS-based genomic data creates opportunities to further personalize clinical decision-making for precision oncology.

Spatial Profiling of Multiple Enzymatic Activities at Single Tissue Sections via Fenton-Promoted Electrochemiluminescence

Profiling multiple enzymatic activities in tissue is crucial for understanding complex metabolic and signaling networks, yet remains a challenge with existing optical microscopies. Here, we developed a Fenton-promoted luminol electrochemiluminescence (ECL) imaging method to achieve the spatial mapping of multiple enzymatic activities within a single tissue section. This method quantitatively visualizes individual enzymatic activity by combining the enzymatic conversion of substrates with the chemical confinement of the locally produced hydrogen peroxide. To achieve high-resolution spatial imaging by limiting the diffusion (∼500 μm) of hydrogen peroxide, iron oxide nanoparticles were coated on the tissue surface to initiate the Fenton process, locally converting hydrogen peroxide into short-lived hydroxyl radicals with a nanometer-scale diffusion range. The Fenton-promoted ECL emission is confined at the enzymatic conversion sites, offering unprecedented spatial visualization of four tumor-associated oxidases within a single tissue section. Colocalization revealed a synergistic effect between lysyl oxidase and quiescin sulfhydryl oxidase on post-translational modifications of tumor extracellular matrix proteins, along with a previously undiscovered interaction with amiloride-sensitive amine oxidase, which could not be distinguished based on expressions or single enzymatic activity alone. This approach offers a novel activity-based protein profiling tool at the tissue level, providing new data for future enzynomic research and multimodal imaging.

Overcoming cancer therapy resistance: From drug innovation to therapeutics

One of the major limitations of cancer therapy is the emergence of drug resistance. This review amis to provide a focused analysis of the multifactorial mechanisms underlying therapy resistance,with an emphasis on actionable insights for developing novel therapeutic strategies. It concisely outlines key factors contributing to therapy resistance, including drug delivery barriers, cancer stem cells (CSCs), epithelial-mesenchymal transition (EMT), cancer heterogeneity, tumor microenvironment (TME), genetic mutations, and alterlations in gene expression. Additionally, we explore how tumors evade targeted therapies through pathway-specific mechanisms that restore disrupted signaling pathways. The review critically evaluates innovative strategies designed to sensitize resistant tumor cells, such as targeted protein dedgradation, antibody-drug conjugates, structure-based drug design, allosteric drugs, multitarget drugs, nanomedicine and others We also highlight the importance of understanding the pharmacological actions of these agents and their integration into treatment regimens. By synthesizing current knowledge and identifying gaps in our understanding, this review aims to guide future research and improve patient outcomes in cancer therapy.

Quantitative characterization of the 3D self-organization of PDAC tumor spheroids reveals cell type and matrix dependence through advanced microscopy analysis

Pancreatic ductal adenocarcinoma (PDAC) is characterized by an abundant tumor-associated stroma composed from pancreatic stellate cells, which play a critical role in tumor progression. Developing accurate in vitro models requires understanding the complex interactions between tumor cells and their microenvironment. In this study, we present a quantitative imaging-based characterization of the three dimensional (3D) self-organization of PDAC tumour spheroids using a microfluidic platform that mimics key aspects of the tumor microenvironment. Our model incorporates collagen type I hydrogels to recreate the extracellular matrix, activated human pancreatic stellate cells (HPSCs), and various tumor cell types. Advanced imaging techniques, including Lattice Lightsheet Microscopy, allowed us to analyze the 3D growth and spatial organization of the spheroids, revealing intricate biomechanical interactions. Our results indicate that alterations in matrix properties-such as stiffness, pore size, and hydraulic permeability-due to variations in collagen concentration significantly influence the growth patterns and organization of PDAC spheroids, depending on tumor subtype and epithelial-mesenchymal phenotype. Higher collagen concentrations promoted larger spheroids in epithelial-like cell lines, while mesenchymal-type cells required increased collagen for self-organization into smaller spheroids. Furthermore, coculture with HPSCs affected spheroid formation distinctly based on each PDAC cell line's genetic and phenotypic traits. HPSCs had opposing effects on epithelial-like cell lines: one cell line exhibited enhanced spheroid growth, while another showed inhibited formation, whereas mesenchymal-like spheroids showed minimal impact. These results provide insights into tumor-stroma interactions, emphasizing the importance of the cell-specific and matrix-dependent factors for advancing our understanding of PDAC progression and informing future therapeutic strategies.

A machine learning model based on preoperative multiparametric quantitative DWI can effectively predict the survival and recurrence risk of pancreatic ductal adenocarcinoma

PURPOSE

To develop a machine learning (ML) model combining preoperative multiparametric diffusion-weighted imaging (DWI) and clinical features to better predict overall survival (OS) and recurrence-free survival (RFS) following radical surgery for pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

A retrospective analysis was conducted on 234 PDAC patients who underwent radical resection at two centers. Among 101 ML models tested for predicting postoperative OS and RFS, the best-performing model was identified based on comprehensive evaluation metrics, including C-index, Brier scores, AUC curves, clinical decision curves, and calibration curves. This model's risk stratification capability was further validated using Kaplan-Meier survival analysis.

RESULTS

The random survival forest model achieved the highest C-index (0.828/0.723 for OS and 0.781/0.747 for RFS in training/validation cohorts). Incorporating nine key factors-D value, T-stage, ADC-value, postoperative 7th day CA19-9 level, AJCC stage, tumor differentiation, type of operation, tumor location, and age-optimized the model's predictive accuracy. The model had integrated Brier score below 0.13 and C/D AUC values above 0.85 for both OS and RFS predictions. It also outperformed traditional models in predictive ability and clinical benefit, as shown by clinical decision curves. Calibration curves confirmed good predictive consistency. Using cut-off scores of 16.73/29.05 for OS/RFS, Kaplan-Meier analysis revealed significant prognostic differences between risk groups (p < 0.0001), highlighting the model's robust risk prediction and stratification capabilities.

CONCLUSION

The random survival forest model, combining DWI and clinical features, accurately predicts survival and recurrence risk after radical resection of PDAC and effectively stratifies risk to guide clinical treatment.

CRITICAL RELEVANCE STATEMENT

The construction of 101 ML models based on multiparametric quantitative DWI combined with clinical variables has enhanced the prediction performance for survival and recurrence risks in patients undergoing radical resection for PDAC.

KEY POINTS

This study first develops DWI-based radiological-clinical ML models predicting PDAC prognosis. Among 101 models, RFS is the best and outperforms other traditional models. Multiparametric DWI is the key prognostic predictor, with model interpretations through SurvSHAP.

Multiphoton imaging-based quantifiable collagen signatures for predicting outcomes in patients with pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) presents a clinical challenge due to its poor prognosis and high mortality rate. Here, we aimed to enhance the prognostic prediction of patients with PDAC by studying collagen features in tumor microenvironment using multiphoton microscopy (MPM) combining with image processing technique. We identified eight distinct tumor-associated collagen signatures (TACS1-8) from multiphoton images of PDAC tissues and developed an optical biomarker, TACS-score, based on the TACS1-8 using ridge regression analysis. Additionally, we also extracted 142 microscopic TACS (M-TACS) from second-harmonic generation (SHG) images and constructed a new robust biomarker, M-TACS-score, using the least absolute shrinkage and selection operator (LASSO) regression analysis. Our statistical results demonstrate that as two new optical biomarkers, TACS- and M-TACS-score, are independent prognostic factors and have good discriminatory ability (high AUC) as well as risk stratification (high HR) comparing with traditional clinical model (combining seven clinical risk factors, age, sex, TNM stage, tumor location and differentiation, perineural and lymph-vascular invasion) in predicting overall survival (OS) of patients with PDAC, highlighting their potential prognostic and predictive value. A combination of label-free multiphoton imaging technique and computer-aided image processing method may offer a novel and promising approach for finding new biomarkers to improve prognosis prediction and thereby tailor treatment strategies more effectively.

Mechanical signatures in cancer metastasis

The cancer metastatic cascade includes a series of mechanical barrier-crossing events, involving the physical movement of cancer cells from their primary location to a distant organ. This review describes the physical changes that influence tumour proliferation, progression, and metastasis. We identify potential mechanical signatures at every step of the metastatic cascade and discuss some latest mechanobiology-based therapeutic interventions to highlight the importance of interdisciplinary approaches in cancer diagnosis and treatment.

A safe haven for cancer cells: tumor plus stroma control by DYRK1B

The development of resistance remains one of the biggest challenges in clinical cancer patient care and it comprises all treatment modalities from chemotherapy to targeted or immune therapy. In solid malignancies, drug resistance is the result of adaptive processes occurring in cancer cells or the surrounding tumor microenvironment (TME). Future therapy attempts will therefore benefit from targeting both, tumor and stroma compartments and drug targets which affect both sides will be highly appreciated. In this review, we describe a seemingly paradoxical oncogenic mediator with this potential: The dual-specificity tyrosine-phosphorylation regulated kinase 1B (DYRK1B). DYRK1B promotes proliferative quiescence and yet is overexpressed or amplified in many hyperproliferative malignancies including ovarian cancer and pancreatic cancer. In particular the latter disease is a paradigmatic example for a therapy-recalcitrant and highly stroma-rich cancer entity. Here, recent evidence suggests that DYRK1B exerts its oncogenic features by installing a protective niche for cancer cells by directly affecting cancer cells but also the TME. Specifically, DYRK1B not only fosters cell-intrinsic processes like cell survival, chemoresistance, and disease recurrence, but it also upregulates TME and cancer cell-protective innate immune checkpoints and down-modulates anti-tumoral macrophage functionality. In this article, we outline the well-established cell-autonomous roles of DYRK1B and extend its importance to the TME and the control of the tumor immune stroma. In summary, DYRK1B appears as a single novel key player creating a safe haven for cancer cells by acting cell-intrinsically and-extrinsically, leading to the promotion of cancer cell survival, chemoresistance, and relapse. Thus, DYRK1B appears as an attractive drug target for future therapeutic approaches.

A practical distribution pattern of α-SMA-positive carcinoma associated fibroblasts indicates poor prognosis of patients with pancreatic ductal adenocarcinoma

Purpose The present study aimed to clarify the distribution pattern of carcinoma associated fibroblasts (CAFs) across pancreatic ductal adenocarcinoma (PDAC) and its prognostic prediction value. Methods Data of two cohorts were retrospectively collected from consecutive patients who underwent primary pancreatic resection from January 2015 to December 2017. We used tumor specimens to screen out the most suitable markers for the spatial distribution analysis for CAFs subpopulations. We utilized a tissue microarray to assess the spatial intensity of α-SMA expression within the tumor microenvironment. Specifically, we classified CAFs into two types based on their α-SMA spatial expression. Type II CAFs were designated as those located in the juxtatumoural stroma with α-SMA expression that was moderate or higher, and those in the peripheral stroma with α-SMA expression that was less than moderate. All other cases, where the α-SMA expression did not meet these criteria, were categorized as Type I CAFs. Multivariable Cox proportional hazards regression was used to assess risk factors associated with patient outcomes. RNA sequencing data were obtained from bulk tumor samples and isolated CAFs from patients to reveal the distinct pattern and elucidated their fundamental characteristics. Results The α-SMA spatial intensity was the most suitable variable for representative of CAFs spatial characteristics. Patients with Type Ⅰ CAFs were more likely to be allocated into N1 or N2 of the N stage and Ⅱ and Ⅲ of the TNM stage. The spatial distribution pattern of CAFs (Type Ⅰ v.s. Type Ⅱ: HR, 1.568; 95 % CI, 1.053-2.334; P = 0.027) was an independent prognostic factor in the discovery cohort, so as in the validation (Type Ⅰ vs. Type Ⅱ: HR, 2.197; 95 % CI, 1.410-3.422; P = 0.001). RNA sequencing analysis revealed that the differentially expressed genes (DEGs) in Type I CAFs are closely associated with those in corresponding tumor tissues, highlighting the enhanced biological significance of immune-related and oncogenic invasive pathways. Conclusions Our findings that two types of α-SMA-positive CAFs with different spatial patterns present heterogeneously across tissues of PDACs and correlated with patients' outcomes. The spatial location of CAFs may facilitate patients' selection in precision medicine of PDACs.

Spatial profiling of endoplasmic reticulum stress markers in tumor associated cells predicts patient outcomes in pancreatic cancer

INTRODUCTION

The impact of endoplasmic reticulum (ER) stress in tumor-associated cells, such as cancer associated fibroblasts (CAFs), immune cells and endothelial cells, on patient outcomes in clinical specimens have not been examined. For the first time, we characterized the expression and spatial locations of ER stress markers, BiP and CHOP, in tumor-associated cells and assessed their prognostic significance in a panel of pancreatic ductal adenocarcinoma (PDAC) patient samples.

METHODS

Multiplex immunofluorescence was performed on tumor microarrays and images were analyzed using HALO AI software.

RESULTS

BiP and CHOP were upregulated in CAFs and endothelial cells in PDAC sections relative to non-neoplastic pancreas sections. High BiP expression in CAFs and endothelial cells was associated with greater vascular invasion and in immune cells was correlated with increased tumor size. High CHOP expression in immune cells correlated with poor patient survival. CAFs and immune cells were more likely to express BiP or CHOP when located close (< 20 μm) to tumor cells. High expression of CHOP in CAFs close to tumor cells correlated with improved patient survival.

CONCLUSION

For the first time, this study demonstrated that ER stress occurs in CAFs and immune cells predominantly in proximity to tumor cells in PDAC patient tissue. The correlation of high ER stress in immune cells with poor patient survival highlights the importance of the TME and the use of spatial analysis for the identification of novel biomarkers.

Integrative multi-omics analysis reveals the role of toll-like receptor signaling in pancreatic cancer

As one of the most destructive and invasive cancers, pancreatic cancer exhibits complex tumor heterogeneity, which has been a major challenge for clinicians in terms of patient treatment and prognosis. The toll-like receptor (TLR) pathway is closely related to the immune microenvironment within various cancer tissues. To explore the development pattern of pancreatic cancer and find an ideal biomarker, our research has explored the mechanism of the TLR pathway in pancreatic cancer. We collected single-cell expression data from 57,024 cells and transcriptomic data from 945 pancreatic cancer patients, and conducted a series of analyses at both the single-cell and transcriptomic levels. By calculating the TLR pathway score, we clustered pancreatic cancer patients and conducted a series of analyses including metabolic pathways, immune microenvironment, drug sensitivity and so on. In the process of building prognostic models, we screened 33 core genes related to the prognosis of pancreatic cancer, and combined a series of machine learning algorithms to build the prognosis model of pancreatic cancer. We used single cell sequencing to clarify the complex intrinsic relationship between TLR pathway and pancreatic cancer. The strongest TLR signals were observed in macrophages and endothelial cells. With the occurrence of pancreatic cancer, the TLR signal of various cell types gradually increased, but with the increase of the malignant degree of ductal epithelial cells, the TLR signal gradually weakened. Cluster analysis showed that patients with the most active TLR pathway had severe dysregulation of immune microenvironment and the worst prognosis. Finally, we combined a series of machine learning algorithms to build a pancreatic cancer prognosis model that includes four genes (NT5E, TGFBI, ANLN, and FAM83A). The model showed strong performance in predicting the survival state of pancreatic cancer samples. We explored the important role of TLR pathway in pancreatic cancer and established and validated a new prognosis model for pancreatic cancer based on TLR-related genes.

Performance of fibroblast activating protein inhibitor PET imaging for pancreatic neoplasms assessment: a systematic review and meta-analysis

BACKGROUND

Recent studies have shown the potential of fibroblast activating protein inhibitor (FAPI) PET imaging for pancreatic cancer assessment.

PURPOSE

This article is dedicated to comparing the diagnostic efficacy of FAPI PET and [18F]fluorodeoxyglucose (FDG) PET in the evaluation of primary tumors, lymph nodes, and distant metastases in pancreatic cancer.

METHODS

In this review, we conducted a systematic search of studies published in PubMed and Web of Science databases up to September 18, 2023. All included studies used radionuclide labeled FAPI and FDG as PET diagnostic tracers to evaluate their applicability in patients with pancreatic cancer.

RESULTS

The FAPI PET imaging group showed significantly higher sensitivity in the detection of primary lesions (1.000, [95% CI: 0.999-1.000]), lymph node metastases (0.624 [95% CI: 0.391-0.834]) and distant metastatic (0.965 [95% CI: 0.804-1.000]) in pancreatic cancer compared to the FDG PET imaging group (0.889 [95% CI: 0.788-0.966], 0.373 [95% CI: 0.163-0.606] and 0.889 [95% CI: 0.689-0.999], respectively). Furthermore, the maximum standardized uptake value (SUVmax) in FAPI PET imaging is significantly higher than that in FDG imaging for primary lesions (mean difference (MD) = 7.51, 95% CI: 5.34-9.67).

CONCLUSION

Compared with [18F]FDG PET/CT, FAPI PET imaging showed higher sensitivity, SUVmax. This method can be effectively utilized for the evaluation of pancreatic cancer.

CLINICAL RELEVANCE STATEMENT

Fibroblast activating protein inhibitor PET may be a better alternative to [18F]FDG in evaluating primary pancreatic cancer, lymph node metastases, and distant metastases.

KEY POINTS

Fibroblast activating protein inhibitor (FAPI) PET is compared with FDG PET for evaluating pancreatic cancer. Multiple radiolabeled FAPI variants have shown promising results in the diagnosis of pancreatic cancer. FAPI PET imaging effectively helps clinicians diagnose and stage pancreatic cancer.

Pancreatic cancer cell-derived migrasomes promote cancer progression by fostering an immunosuppressive tumor microenvironment

Pancreatic cancer is distinguished by an immunosuppressive tumor microenvironment (TME) that facilitates cancer progression. The assembly of the TME involves numerous contributing factors. Migrasomes, recently identified as cellular organelles in migrating cells, play a pivotal role in intercellular signaling. However, research into their involvement in cancers remains nascent. Thus far, whether pancreatic cancer cells generate migrasomes and their potential role in TME formation remains unexplored. In this study, it was found that both murine and human pancreatic cancer cells could indeed generate migrasomes, termed pancreatic cancer cell-derived migrasomes (PCDMs), which actively promote cancer progression. Moreover, utilizing chemokine antibody arrays and quantitative mass spectrometry analysis, we observed significant differences between the chemokines, cytokines, and proteins present in PCDMs compared to their originating cell bodies. Notably, PCDMs exhibited an enrichment of immunosuppression-inducing factors. Furthermore, macrophages could directly uptake PCDMs, leading to the expression of high levels of M2-like markers and secretion of tumor-promoting factors. PCDM-induced macrophages played a pivotal role in inhibiting T cell proliferation and activation partially through ARG-1. In summary, this study provides compelling evidence that pancreatic cancer cells generate migrasomes, which play a crucial role in promoting tumor progression by contributing to an immunosuppressive TME. The exploration of migrasomes as a therapeutic target could pave the way for the development of tailored immunotherapies for pancreatic cancer.

Cancer-associated fibroblasts barrier breaking via TGF-β blockade paved way for docetaxel micelles delivery to treat pancreatic cancer

TGF-β is a crucial regulator in tumor microenvironment (TME), especially for myofibroblastic cancer-associated fibroblasts (myCAFs). The myCAFs can be motivated by TGF-β signaling to erect pro-tumor TME, meanwhile, myCAFs overexpress TGF-β to mediate the crosstalk between tumor and stromal cells. The blockade of TGF-β can break cancer-associated fibroblasts barrier, consequently opening the access for drugs into tumor. The TGF-β is a promising target in anti-tumor therapy. Herein, we introduced a two-stage combination therapy (TC-Therapy), including TGF-β receptor I inhibitor SB525334 (SB) and cytotoxicity agent docetaxel micelle (DTX-M). We found that SB and DTX-M synergistically inhibited myCAFs proliferation and elevated p53 protein expression in BxPC-3/3T3 mixed cells. Gene and protein tests demonstrated that SB cut off TGF-β signaling via receptor blockade and it did not arouse TGF-β legend compensated internal autocrine. On the contrary, two agents combined decreased TGF-β secretion and inhibited myCAFs viability marked by α-SMA and FAPα. TC-Therapy was applied in BxPc-3/3T3 mixed tumor-bearing mice model. After TC-Therapy, the α-SMA+/ FAPα+ myCAFs faded increasingly and collagenous fibers mainly secreted by myCAFs decreased dramatically as well. More than that, the myCAFs barrier breaking helped to normalize micro-vessels and paved way for micelle penetration. The TGF-β protein level of TC-Therapy in TME was much lower than that of simplex DTX-M, which might account for TME restoration. In conclusion, TGF-β inhibitor acted as the pioneer before nano chemotherapeutic agents. The TC-Therapy of TGF-β signaling inhibition and anti-tumor agent DTX-M is a promising regimen without arising metastasis risk to treat pancreatic cancer. The therapeutic regimen focused on TGF-β related myCAFs reminds clinicians to have a comprehensive understanding of pancreatic cancer.

Increased needle passes for comparable diagnostic yield in endoscopic ultrasound-guided tissue acquisition for pancreatic stiff lesions measured by elastography

BACKGROUND/OBJECTIVES

Pancreatic cancer is characterized by tissue stiffness due to the high concentration of cancer-associated fibroblasts and extracellular matrix. Endoscopic ultrasound-guided tissue acquisition (EUS-TA) is performed to diagnose pancreatic cancer but yields false-negative results attributed to inadequate specimens. EUS-elastography is a real-time assessment method to pancreatic tissue stiffness. This study aims to investigate the correlation between diagnostic yield and the number of needle passes based on the stiffness measured by elastography.

METHODS

Patients who underwent EUS-TA for pancreatic solid mass were retrospectively reviewed and included in this study. The number of needle passes during EUS-TA was determined based on macroscopic on-site evaluation. Tissue stiffness measurements were taken using EUS-elastography. The primary study outcome was the diagnostic yield. The secondary outcome included the number of needle passes required for a diagnosis.

RESULTS

A total of 652 patients were included. The average stiffness differed depending on the location of the tumor, and high-stiffness group had more malignant lesions. Although the diagnostic yield was not significantly different between groups, the number of needle passes was significantly higher in the high-stiffness group (3.6 ± 1.0 vs. 3.2 ± 0.9, p < 0.001).

CONCLUSIONS

The higher the stiffness of the pancreatic mass in EUS-elastography, the more needle passes are required to achieve a comparable diagnostic yield.

Signal enhancement ratio of multi-phase contrast-enhanced MRI: an imaging biomarker for survival in pancreatic adenocarcinoma

OBJECTIVES

To evaluate signal enhancement ratio (SER) for tissue characterization and prognosis stratification in pancreatic adenocarcinoma (PDAC), with quantitative histopathological analysis (QHA) as the reference standard.

METHODS

This retrospective study included 277 PDAC patients who underwent multi-phase contrast-enhanced (CE) MRI and whole-slide imaging (WSI) from three centers (2015-2021). SER is defined as (SIlt - SIpre)/(SIea - SIpre), where SIpre, SIea, and SIlt represent the signal intensity of the tumor in pre-contrast, early-, and late post-contrast images, respectively. Deep-learning algorithms were implemented to quantify the stroma, epithelium, and lumen of PDAC on WSIs. Correlation, regression, and Bland-Altman analyses were utilized to investigate the associations between SER and QHA. The prognostic significance of SER on overall survival (OS) was evaluated using Cox regression analysis and Kaplan-Meier curves.

RESULTS

The internal dataset comprised 159 patients, which was further divided into training, validation, and internal test datasets (n = 60, 41, and 58, respectively). Sixty-five and 53 patients were included in two external test datasets. Excluding lumen, SER demonstrated significant correlations with stroma (r = 0.29-0.74, all p < 0.001) and epithelium (r = -0.23 to -0.71, all p < 0.001) across a wide post-injection time window (range, 25-300 s). Bland-Altman analysis revealed a small bias between SER and QHA for quantifying stroma/epithelium in individual training, validation (all within ± 2%), and three test datasets (all within ± 4%). Moreover, SER-predicted low stromal proportion was independently associated with worse OS (HR = 1.84 (1.17-2.91), p = 0.009) in training and validation datasets, which remained significant across three combined test datasets (HR = 1.73 (1.25-2.41), p = 0.001).

CONCLUSION

SER of multi-phase CE-MRI allows for tissue characterization and prognosis stratification in PDAC.

CLINICAL RELEVANCE STATEMENT

The signal enhancement ratio of multi-phase CE-MRI can serve as a novel imaging biomarker for characterizing tissue composition and holds the potential for improving patient stratification and therapy in PDAC.

KEY POINTS

Imaging biomarkers are needed to better characterize tumor tissue in pancreatic adenocarcinoma. Signal enhancement ratio (SER)-predicted stromal/epithelial proportion showed good agreement with histopathology measurements across three distinct centers. Signal enhancement ratio (SER)-predicted stromal proportion was demonstrated to be an independent prognostic factor for OS in PDAC.

Pancreatic ductal adenocarcinoma cells reshape the immune microenvironment: Molecular mechanisms and therapeutic targets

Pancreatic ductal adenocarcinoma (PDAC) is a digestive system malignancy characterized by challenging early detection, limited treatment alternatives, and generally poor prognosis. Although there have been significant advancements in immunotherapy for hematological malignancies and various solid tumors in recent decades, with impressive outcomes in recent preclinical and clinical trials, the effectiveness of these therapies in treating PDAC continues to be modest. The unique immunological microenvironment of PDAC, especially the abnormal distribution, complex composition, and variable activation states of tumor-infiltrating immune cells, greatly restricts the effectiveness of immunotherapy. Undoubtedly, integrating data from both preclinical models and human studies helps accelerate the identification of reliable molecules and pathways responsive to targeted biological therapies and immunotherapies, thereby continuously optimizing therapeutic combinations. In this review, we delve deeply into how PDAC cells regulate the immune microenvironment through complex signaling networks, affecting the quantity and functional status of immune cells to promote immune escape and tumor progression. Furthermore, we explore the multi-modal immunotherapeutic strategies currently under development, emphasizing the transformation of the immunosuppressive environment into an anti-tumor milieu by targeting specific molecular and cellular pathways, providing insights for the development of novel treatment strategies.

Overcoming therapy resistance in pancreatic cancer: New insights and future directions

Pancreatic adenocarcinoma (PDAC) is predicted to become the second leading cause of cancer deaths by 2030 and this is mostly due to therapy failure. Limited treatment options and resistance to standard-of-care (SoC) therapies makes PDAC one of the cancer types with poorest prognosis and survival rates [1,2]. Pancreatic tumors are renowned for their poor response to therapeutic interventions including targeted therapies, chemotherapy and radiotherapy. Herein, we review hallmarks of therapy resistance in PDAC and current strategies aiming to tackle escape mechanisms and to re-sensitize cancer cells to therapy. We will further provide insights on recent advances in the field of drug discovery, nanomedicine, and disease models that are setting the ground for future research.

Targeting extracellular matrix interaction in gastrointestinal cancer: Immune modulation, metabolic reprogramming, and therapeutic strategies

The extracellular matrix (ECM) is a major constituent of the tumor microenvironment, acting as a mediator that supports the progression of gastrointestinal (GI) cancers, particularly in mesenchymal subtypes. Beyond providing structural support, the ECM actively shapes the tumor microenvironment (TME) through complex biochemical and biomechanical remodeling. Dysregulation of ECM composition and signaling is closely linked to increased cancer aggressiveness, poor prognosis, and resistance to therapy. ECM components, such as collagen, fibronectin, laminin, and periostin, influence tumor growth, metastasis, immune modulation, and metabolic reprogramming by interacting with tumor cells, immune cells, and cancer-associated fibroblasts. In this review, we highlight the heterogeneous nature of the ECM and the dualistic roles of its components across GI cancers, with a focus on their contributions to immune evasion and metabolic remodeling via intercellular interactions. Additionally, we explore therapeutic strategies targeting ECM remodeling and ECM-centered interactions, emphasizing their potential in enhancing existing anti-tumor therapies.

Partial regression of conventional renal cell carcinoma displays markers of wound repair

AIMS

During detailed analysis of H&E-stained histological slides of 710 unbiased conventional renal cell carcinomas (cRCCs), 141 tumours displayed partial regressive changes showing strong similarity to that of wound healing. We aimed to analyse the molecular processes occurring in regressive tumours.

METHODS

Immunohistochemistry was applied to analyse the signalling molecules in 12 selected tumours, and statistical analysis was used to estimate the correlation between regression and the outcome of the disease.

RESULTS

The regressive areas displayed inflammatory granulation tissue expressing transforming growth factor beta-1 (TGFB1), interleukin-1 beta and interleukin-6 (IL1B and IL6), proliferation of alpha smooth muscle actin (αSMA) positive naïve activated fibroblasts and a diffuse fibronectin 1 (FN1) network. In the central areas of regressive tissues, parallel-running myofibroblasts showed FN1, collagen type I alpha 1 (COL1A1) and collagen type III alpha 1 (COL3A1) positive immunoreaction. Partial tumour regression is associated with a better postoperative course of the disease.

CONCLUSIONS

Partial regression is a frequent event in cRCCs. Recognising complex molecular processes involved in tumour regression might help to find a way towards 'healing' cRCC.

The Prognostic Significance of Collagen VI in Pancreatic Ductal Adenocarcinoma

OBJECTIVES

Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognosis and lack of biomarkers. A rich desmoplastic tumor stroma is considered a hallmark of PDAC and previous studies have indicated upregulated expression of collagen VI (COL6) in PDAC. COL6 is shown to associate with prognosis in many cancers but has been less extensively studied in PDAC.

MATERIALS AND METHODS

The expression of COL6 was analyzed by immunohistochemistry in tissue microarrays containing resected tumor tissue samples from PDAC patients (n = 164). Significance of COL6 was estimated with Kaplan-Meier survival estimates and multivariable Cox regression analysis. COL6 protein and mRNA expression patterns were further investigated in publicly available datasets.

RESULTS

There were no statistically significant ( P < 0.05) differences in survival when comparing high and low protein expression of any of the analyzed COL6 α-chains (α1(VI): hazard ratio [HR] 0.90, 95% confidence interval [CI] 0.64-1.28; α2(VI): HR 1.28, 95% CI 0.86-1.89; α3(VI): HR 0.91, 95% CI 0.64-1.29). Similar results were obtained when assessing public data from the Cancer Proteome Atlas, Clinical Proteomic Tumor Analysis Consortium, and The Cancer Genome Atlas.

CONCLUSIONS

In contrast with previous studies and some other cancers, we did not find any association of COL6 tissue expression and PDAC survival.

Pre-metastatic niche: formation, characteristics and therapeutic implication

Distant metastasis is a primary cause of mortality and contributes to poor surgical outcomes in cancer patients. Before the development of organ-specific metastasis, the formation of a pre-metastatic niche is pivotal in promoting the spread of cancer cells. This review delves into the intricate landscape of the pre-metastatic niche, focusing on the roles of tumor-derived secreted factors, extracellular vesicles, and circulating tumor cells in shaping the metastatic niche. The discussion encompasses cellular elements such as macrophages, neutrophils, bone marrow-derived suppressive cells, and T/B cells, in addition to molecular factors like secreted substances from tumors and extracellular vesicles, within the framework of pre-metastatic niche formation. Insights into the temporal mechanisms of pre-metastatic niche formation such as epithelial-mesenchymal transition, immunosuppression, extracellular matrix remodeling, metabolic reprogramming, vascular permeability and angiogenesis are provided. Furthermore, the landscape of pre-metastatic niche in different metastatic organs like lymph nodes, lungs, liver, brain, and bones is elucidated. Therapeutic approaches targeting the cellular and molecular components of pre-metastatic niche, as well as interventions targeting signaling pathways such as the TGF-β, VEGF, and MET pathways, are highlighted. This review aims to enhance our understanding of pre-metastatic niche dynamics and provide insights for developing effective therapeutic strategies to combat tumor metastasis.

An oncolytic HSV-1 armed with Visfatin enhances antitumor effects by remodeling tumor microenvironment against murine pancreatic cancer

Oncolytic viruses (OVs) have shown potential in converting a "cold" tumor into a "hot" one and exhibit effectiveness in various cancer types. However, only a subset of patients respond to oncolytic virotherapy. It is important to understand the resistance mechanisms to OV treatment in pancreatic ductal adenocarcinoma (PDAC) to engineer oncolytic viruses. In this study, we used transcriptome RNA sequencing (RNA-seq) to identify Visfatin, which was highly expressed in the responsive tumors following OV treatment. To explore the antitumor efficacy, we modified OV-mVisfatin, which effectively inhibited tumor growth. For the first time, we revealed that Visfatin promoted the antitumor efficacy of OV by remodeling the tumor microenvironment, which involved enhancing CD8+ T cell and DC cell infiltration and activation, repolarizing macrophages towards the M1-like phenotype, and decreasing Treg cells using single-cell RNA sequencing (scRNA-seq) and flow cytometry. Furthermore, PD-1 blockade significantly enhanced OV-mVisfatin antitumor efficacy, offering a promising new therapeutic strategy for PDAC.

Effect of Bioactive Black Phosphorus Nanomaterials on Cancer-Associated Fibroblast Heterogeneity in Pancreatic Cancer

Tumor-stromal interactions and stromal heterogeneity in the tumor microenvironment are critical factors that influence the progression, metastasis, and chemoresistance of pancreatic ductal adenocarcinoma (PDAC). Here, we used spatial transcriptome technology to profile the gene expression landscape of primary PDAC and liver metastatic PDAC after bioactive black phosphorus nanomaterial (bioactive BP) treatment using a murine model of PDAC (LSL-KrasG12D/+; LSL-Trp53R172H/+; and Pdx-1-Cre mice). Bioinformatic and biochemical analyses showed that bioactive BP contributes to the tumor-stromal interplay by suppressing cancer-associated fibroblast (CAF) activation. Our results showed that bioactive BP contributes to CAF heterogeneity by decreasing the amount of inflammatory CAFs and myofibroblastic CAFs, two CAF subpopulations. Our study demonstrates the influence of bioactive BP on tumor-stromal interactions and CAF heterogeneity and suggests bioactive BP as a potential PDAC treatment.

Thickness-Resolved Electrochemiluminescence Microscopy of Extracellular Matrix at Tumor Tissues for Rapid Cancer Diagnosis

The traditional recognition of extracellular matrix (ECM) at tissue sections relies on the time-consuming immunofluorescence that could not meet the demand of rapid diagnosis. Herein, we introduce a thickness-resolved electrochemiluminescence (ECL) microscopy to image thin-layer ECM at tissue sections for fast histopathological analysis. The unique surface-confined ECL mechanism enables to unveil the diversity and complexity of multiple tissue structures with varying thicknesses. Notably, the short lifetimes and the limited diffusion of electrogenerated coreactant radicals combined with their chemical reactivity result in a 2-fold increase in ECL intensity on ECM structures compared to the remaining tissue, enabling ECM visualization without specific labeling. The further quantitation of the ECM localization within tissue sections furnishes crucial insights into tumor progression and, more importantly, differentiates carcinoma and paracancerous tissues from patients in less than 30 min. Moreover, the reported electrochemistry-based microscopy is a dynamic approach allowing to investigate the transport, tortuosity, and trafficking properties through the tissues. This thickness-resolved recognition strategy not only opens new avenues for imaging complex samples but also holds promise for expediting tissue pathologic diagnosis, offering a more automated protocol with enhanced quantitative data compared to current intraoperative pathology methods.

Single-Cell RNA Sequencing Analysis Reveals Metabolic Changes in Epithelial Glycosphingolipids and Establishes a Prognostic Risk Model for Pancreatic Cancer

OBJECTIVE

Metabolic reprogramming serves as a distinctive feature of cancer, impacting proliferation and metastasis, with aberrant glycosphingolipid expression playing a crucial role in malignancy. Nevertheless, limited research has investigated the connection between glycosphingolipid metabolism and pancreatic cancer.

METHODS

This study utilized a single-cell sequencing dataset to analyze the cell composition in pancreatic cancer tissues and quantified single-cell metabolism using a newly developed computational pipeline called scMetabolism. A gene signature developed from the differential expressed genes (DEGs), related to epithelial cell glycosphingolipid metabolism, was established to forecast patient survival, immune response, mutation status, and reaction to chemotherapy with pancreatic adenocarcinoma (PAAD).

RESULTS

The single-cell sequencing analysis revealed a significant increase in epithelial cell proportions in PAAD, with high glycosphingolipid metabolism occurring in the cancerous tissue. A six-gene signature prognostic model based on abnormal epithelial glycosphingolipid metabolism was created and confirmed using publicly available databases. Patients with PAAD were divided into high- and low-risk categories according to the median risk score, with those in the high-risk group demonstrating a more unfavorable survival outcome in all three cohorts, with higher rates of gene mutations (e.g., KRAS, CDKN2A), increased levels of immunosuppressive cells (macrophages, Th2 cells, regulatory T cells), and heightened sensitivity to Acetalax and Selumetinlb.

CONCLUSIONS

Abnormal metabolism of glycosphingolipids in epithelial cells may promote the development of PAAD. A model utilizing a gene signature associated with epithelial glycosphingolipids metabolism has been established, serving as a valuable indicator for the prognostic stratification of patients with PAAD.

Tumor Stroma as a Therapeutic Target for Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis owing to its desmoplastic stroma. Therefore, therapeutic strategies targeting this tumor stroma should be developed. In this study, we describe the heterogeneity of cancer-associated fibroblasts (CAFs) and their diverse roles in the progression, immune evasion, and resistance to treatment of PDAC. We subclassified the spatial distribution and functional activity of CAFs to highlight their effects on prognosis and drug delivery. Extracellular matrix components such as collagen and hyaluronan are described for their roles in tumor behavior and treatment outcomes, implying their potential as therapeutic targets. We also discussed the roles of extracellular matrix (ECM) including matrix metalloproteinases and tissue inhibitors in PDAC progression. Finally, we explored the role of the adaptive and innate immune systems in shaping the PDAC microenvironment and potential therapeutic strategies, with a focus on immune cell subsets, cytokines, and immunosuppressive mechanisms. These insights provide a comprehensive understanding of PDAC and pave the way for the development of prognostic markers and therapeutic interventions.

Quantitative proteomic analysis of HER2 protein expression in PDAC tumors

Metastatic pancreatic adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States, with a 5-year survival rate of only 11%, necessitating identification of novel treatment paradigms. Tumor tissue specimens from patients with PDAC, breast cancer, and other solid tumor malignancies were collected and tumor cells were enriched using laser microdissection (LMD). Reverse phase protein array (RPPA) analysis was performed on enriched tumor cell lysates to quantify a 32-protein/phosphoprotein biomarker panel comprising known anticancer drug targets and/or cancer-related total and phosphorylated proteins, including HER2Total, HER2Y1248, and HER3Y1289. RPPA analysis revealed significant levels of HER2Total in PDAC patients at abundances comparable to HER2-positive (IHC 3+) and HER2-low (IHC 1+ /2+ , FISH-) breast cancer tissues, for which HER2 screening is routinely performed. These data support a critical unmet need for routine clinical evaluation of HER2 expression in PDAC patients and examination of the utility of HER2-directed antibody-drug conjugates in these patients.

Activated hedgehog gene pattern correlates with dismal clinical outcome and tumor microenvironment heterogeneity in hepatocellular carcinoma

Background

Activation of the Hedgehog signaling pathway is linked to the initiation and development of human hepatocellular carcinoma (HCC). However, its impact on clinical outcomes and the HCC microenvironment remains unclear.

Methods

We performed comprehensive analyses of Hedgehog pathway genes in a large cohort of HCC patients. Specifically, we utilized univariate Cox regression analysis to identify Hedgehog genes linked to overall survival, and the LASSO algorithm was used to construct a Hedgehog-related gene pattern. We subsequently examined the correlation between the Hedgehog pattern and the HCC microenvironment employing the CIBERSORT and ssGSEA algorithms. Furthermore, Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and the anti-PD-L1 treatment dataset (IMvigor210) are used to evaluate the clinical response of the Hedgehog pattern in predicting immune checkpoint inhibitors.

Results

We found that the Hedgehog activation score (HHAS), a prognostic score based on 11 Hedgehog genes, was significantly associated with HCC patient survival. Patients exhibiting high HHAS experienced markedly reduced survival rates compared to those with low HHAS, and HHAS emerged as an independent prognostic factor for HCC. Functional enrichment analysis unveiled the association of the HHAS phenotype with functions related to the immune system, and further investigation demonstrated that HCC patients exhibiting low HHAS displayed elevated levels of anti-tumor immune activation in CD8+ T cells, while high HHAS were linked to immune escape phenotypes and increased infiltration of immune suppressive cells. In addition, in the Immune Checkpoint Inhibitor (ICI) cohort of IMvigor210, patients with higher HHAS had worse ICI treatment outcomes and shortened survival time, indicating that the HHAS is a useful indicator for predicting patient response to immunotherapy.

Conclusions

In summary, our study offers valuable insights for advancing research on Hedgehog and its impact on tumor immunity, which provides an opportunity to optimize prognosis and immune therapy for HCC.

Hyperbaric Oxygen Boosts Antitumor Efficacy of Copper-Diethyldithiocarbamate Nanoparticles against Pancreatic Ductal Adenocarcinoma by Regulating Cancer Stem Cell Metabolism

Cuproptosis-based cancer nanomedicine has received widespread attention recently. However, cuproptosis nanomedicine against pancreatic ductal adenocarcinoma (PDAC) is severely limited by cancer stem cells (CSCs), which reside in the hypoxic stroma and adopt glycolysis metabolism accordingly to resist cuproptosis-induced mitochondria damage. Here, we leverage hyperbaric oxygen (HBO) to regulate CSC metabolism by overcoming tumor hypoxia and to augment CSC elimination efficacy of polydopamine and hydroxyethyl starch stabilized copper-diethyldithiocarbamate nanoparticles (CuET@PH NPs). Mechanistically, while HBO and CuET@PH NPs inhibit glycolysis and oxidative phosphorylation, respectively, the combination of HBO and CuET@PH NPs potently suppresses energy metabolism of CSCs, thereby achieving robust tumor inhibition of PDAC and elongating mice survival importantly. This study reveals novel insights into the effects of cuproptosis nanomedicine on PDAC CSC metabolism and suggests that the combination of HBO with cuproptosis nanomedicine holds significant clinical translation potential for PDAC patients.

Characterization and verification of CAF-relevant prognostic gene signature to aid therapy in bladder cancer

Cancer-associated fibroblasts (CAFs) are significantly involved in determining the patient's prognosis and response to bladder cancer (BLCA) therapy. CAFs can induce epithelial-mesenchymal transformation (EMT) as well as complex interaction with immune cells. Hence, it is imperative to identify potential markers for enhancing our understanding of CAFs in BLCA progression and immune regulation. A variety of algorithms and analyses were employed in the study, leading to the development of a novel prognostic feature for CAFs-Stromal-EMT (CSE)-prognostic feature. This feature was constructed based on the genes MFAP5, PCOLCE2, and JUN. Furthermore, we revealed that patients with higher CSE risk scores responded to immunotherapy better compared to those with lower. Finally, we verified two CSE-related genes using in vitro experiments. Our results suggested that the CSE-prognostic feature could predict the prognosis and evaluate the response of patients to immune and chemotherapies. This would aid clinicians in designing treatment strategies for patients with BLCA.

Epithelial and Mesenchymal-like Pancreatic Cancer Cells Exhibit Different Stem Cell Phenotypes Associated with Different Metastatic Propensities

Pancreatic ductal adenocarcinoma (PDAC) is mostly diagnosed at advanced or even metastasized stages, limiting the prognoses of patients. Metastasis requires high tumor cell plasticity, implying phenotypic switching in response to changing environments. Here, epithelial-mesenchymal transition (EMT), being associated with an increase in cancer stem cell (CSC) properties, and its reversion are important. Since it is poorly understood whether different CSC phenotypes exist along the EMT axis and how these impact malignancy-associated properties, we aimed to characterize CSC populations of epithelial and mesenchymal-like PDAC cells. Single-cell cloning revealed CSC (Holoclone) and non-CSC (Paraclone) clones from the PDAC cell lines Panc1 and Panc89. The Panc1 Holoclone cells showed a mesenchymal-like phenotype, dominated by a high expression of the stemness marker Nestin, while the Panc89 Holoclone cells exhibited a SOX2-dominated epithelial phenotype. The Panc89 Holoclone cells showed enhanced cell growth and a self-renewal capacity but slow cluster-like invasion. Contrarily, the Panc1 Holoclone cells showed slower cell growth and self-renewal ability but were highly invasive. Moreover, cell variants differentially responded to chemotherapy. In vivo, the Panc1 and Panc89 cell variants significantly differed regarding the number and size of metastases, as well as organ manifestation, leading to different survival outcomes. Overall, these data support the existence of different CSC phenotypes along the EMT axis in PDAC, manifesting different metastatic propensities.

Glycogen synthase kinase 3β: the nexus of chemoresistance, invasive capacity, and cancer stemness in pancreatic cancer

The treatment of pancreatic cancer remains a significant clinical challenge due to the limited number of patients eligible for curative (R0) surgery, failures in the clinical development of targeted and immune therapies, and the pervasive acquisition of chemotherapeutic resistance. Refractory pancreatic cancer is typified by high invasiveness and resistance to therapy, with both attributes related to tumor cell stemness. These malignant characteristics mutually enhance each other, leading to rapid cancer progression. Over the past two decades, numerous studies have produced evidence of the pivotal role of glycogen synthase kinase (GSK)3β in the progression of over 25 different cancer types, including pancreatic cancer. In this review, we synthesize the current knowledge on the pathological roles of aberrant GSK3β in supporting tumor cell proliferation and invasion, as well as its contribution to gemcitabine resistance in pancreatic cancer. Importantly, we discuss the central role of GSK3β as a molecular hub that mechanistically connects chemoresistance, tumor cell invasion, and stemness in pancreatic cancer. We also discuss the involvement of GSK3β in the formation of desmoplastic tumor stroma and in promoting anti-cancer immune evasion, both of which constitute major obstacles to successful cancer treatment. Overall, GSK3β has characteristics of a promising therapeutic target to overcome chemoresistance in pancreatic cancer.

Epigenetic therapeutic strategies in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid malignancies, characterized by its aggressiveness and metastatic potential, with a 5-year survival rate of only 8-11%. Despite significant improvements in PDAC treatment and management, therapeutic alternatives are still limited. One of the main reasons is its high degree of intra- and inter-individual tumor heterogeneity which is established and maintained through a complex network of transcription factors and epigenetic regulators. Epigenetic drugs, have shown promising preclinical results in PDAC and are currently being evaluated in clinical trials both for their ability to sensitize cancer cells to cytotoxic drugs and to counteract the immunosuppressive characteristic of PDAC tumor microenvironment. In this review, we discuss the current status of epigenetic treatment strategies to overcome molecular and cellular PDAC heterogeneity in order to improve response to therapy.

Mapping three-dimensional intratumor proteomic heterogeneity in uterine serous carcinoma by multiregion microsampling

BACKGROUND

Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics.

METHODS

Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor.

RESULTS

LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ).

CONCLUSIONS

Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.

Fibroblast Activation Protein-Targeted PET/CT with 18F-Fibroblast Activation Protein Inhibitor-74 for Evaluation of Gastrointestinal Cancer: Comparison with 18F-FDG PET/CT

Fibroblast activation protein is overexpressed in the stroma of several cancer types. 18F-fibroblast activation protein inhibitor (FAPI)-74 is a PET tracer with high selectivity for fibroblast activation protein and has shown high accumulation in human tumors in clinical studies. However, the use of 18F-FAPI-74 for PET imaging of gastrointestinal cancer has not been systematically investigated. Herein, we investigated the diagnostic accuracy of 18F-FAPI-74 (18F-LNC1005) PET/CT in gastric, liver, and pancreatic cancers and compared the results with those of 18F-FDG PET/CT. Methods: This prospective study analyzed patients with confirmed gastric, liver, or pancreatic malignancies who underwent concurrent 18F-FDG and 18F-FAPI-74 PET/CT between June 2022 and December 2022. PET/CT findings were confirmed by histopathology or radiographic follow-up. 18F-FDG and 18F-FAPI-74 uptake and tumor-to-background ratios were compared using the Wilcoxon signed-rank test. The McNemar test was used to compare the diagnostic accuracy of the 2 scans. Results: Our cohort consisted of 112 patients: 49 with gastric cancer, 39 with liver cancer, and 24 with pancreatic cancer. Among them, 69 patients underwent PET/CT for initial staging and 43 for recurrence detection. Regarding lesion-based diagnostic accuracy, 18F-FAPI-74 PET/CT showed higher sensitivity than did 18F-FDG in the detection of primary tumors (gastric cancer, 88% [22/25] vs. 60% [15/25], P = 0.016; liver cancer, 100% [22/22] vs. 82% [18/22], P = 0.125; pancreatic cancer, 100% [22/22] vs. 86% [19/22], P = 0.250), local recurrence (92% [23/25] vs. 56% [14/25]; P = 0.021), involved lymph nodes (71% [41/58] vs. 40% [23/58]; P < 0.001), and bone and visceral metastases (98% [350/358] vs. 47% [168/358]; P < 0.001). Compared with 18F-FDG, 18F-FAPI-74 PET/CT upstaged 17 patients' TNM staging among all treatment-naïve patients (17/69, 25%) and changed the clinical management of 4 patients (4/43, 9%) in whom recurrence or metastases were detected. Conclusion: 18F-FAPI-74 PET/CT is superior to 18F-FDG PET/CT in detecting primary tumors, local recurrence, lymph node involvement, and bone and visceral metastases in gastric, pancreatic, and liver cancers, with higher uptake in most primary and metastatic lesions.

Meflin is a marker of pancreatic stellate cells involved in fibrosis and epithelial regeneration in the pancreas

Pancreatic stellate cells (PSCs) are stromal cells in the pancreas that play an important role in pancreatic pathology. In chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC), PSCs are known to get activated to form myofibroblasts or cancer-associated fibroblasts (CAFs) that promote stromal fibroinflammatory reactions. However, previous studies on PSCs were mainly based on the findings obtained using ex vivo expanded PSCs, with few studies that addressed the significance of in situ tissue-resident PSCs using animal models. Their contributions to fibrotic reactions in CP and PDAC are also lesser-known. These limitations in our understanding of PSC biology have been attributed to the lack of specific molecular markers of PSCs. Herein, we established Meflin (Islr), a glycosylphosphatidylinositol-anchored membrane protein, as a PSC-specific marker in both mouse and human by using human pancreatic tissue samples and Meflin reporter mice. Meflin-positive (Meflin+ ) cells contain lipid droplets and express the conventional PSC marker Desmin in normal mouse pancreas, with some cells also positive for Gli1, the marker of pancreatic tissue-resident fibroblasts. Three-dimensional analysis of the cleared pancreas of Meflin reporter mice showed that Meflin+ PSCs have long and thin cytoplasmic protrusions, and are localised on the abluminal side of vessels in the normal pancreas. Lineage tracing experiments revealed that Meflin+ PSCs constitute one of the origins of fibroblasts and CAFs in CP and PDAC, respectively. In these diseases, Meflin+ PSC-derived fibroblasts showed a distinctive morphology and distribution from Meflin+ PSCs in the normal pancreas. Furthermore, we showed that the genetic depletion of Meflin+ PSCs accelerated fibrosis and attenuated epithelial regeneration and stromal R-spondin 3 expression, thereby implying that Meflin+ PSCs and their lineage cells may support tissue recovery and Wnt/R-spondin signalling after pancreatic injury and PDAC development. Together, these data indicate that Meflin may be a marker specific to tissue-resident PSCs and useful for studying their biology in both health and disease. © 2023 The Pathological Society of Great Britain and Ireland.

An Update on Gemcitabine-Based Chemosensitization Strategies in Pancreatic Ductal Adenocarcinoma

Pancreatic cancer is the seventh leading cause of cancer-related deaths, and chemotherapy is one of the most important treatments for pancreatic cancer. Unfortunately, pancreatic cancer cells can block chemotherapy drugs from entering the tumor. This is owing to interactions between the tumor's environment and the cancer cells. Here, we review the latest research on the mechanisms by which pancreatic cancer cells block the chemotherapy drug, gemcitabine. The results of our review can help identify potential therapeutic targets for the blocking of gemcitabine by pancreatic cancer cells and may provide new strategies to help chemotherapy drugs penetrate tumors.

Inhibiting stromal Class I HDACs curbs pancreatic cancer progression

Oncogenic lesions in pancreatic ductal adenocarcinoma (PDAC) hijack the epigenetic machinery in stromal components to establish a desmoplastic and therapeutic resistant tumor microenvironment (TME). Here we identify Class I histone deacetylases (HDACs) as key epigenetic factors facilitating the induction of pro-desmoplastic and pro-tumorigenic transcriptional programs in pancreatic stromal fibroblasts. Mechanistically, HDAC-mediated changes in chromatin architecture enable the activation of pro-desmoplastic programs directed by serum response factor (SRF) and forkhead box M1 (FOXM1). HDACs also coordinate fibroblast pro-inflammatory programs inducing leukemia inhibitory factor (LIF) expression, supporting paracrine pro-tumorigenic crosstalk. HDAC depletion in cancer-associated fibroblasts (CAFs) and treatment with the HDAC inhibitor entinostat (Ent) in PDAC mouse models reduce stromal activation and curb tumor progression. Notably, HDAC inhibition (HDACi) enriches a lipogenic fibroblast subpopulation, a potential precursor for myofibroblasts in the PDAC stroma. Overall, our study reveals the stromal targeting potential of HDACi, highlighting the utility of this epigenetic modulating approach in PDAC therapeutics.

Genomic analysis and filtration of novel prognostic biomarkers based on metabolic and immune subtypes in pancreatic cancer

PURPOSE

Patients with pancreatic cancer (PC) can be classified into various molecular subtypes and benefit from some precise therapy. Nevertheless, the interaction between metabolic and immune subtypes in the tumor microenvironment (TME) remains unknown. We hope to identify molecular subtypes related to metabolism and immunity in pancreatic cancer METHODS: Unsupervised consensus clustering and ssGSEA analysis were utilized to construct molecular subtypes related to metabolism and immunity. Diverse metabolic and immune subtypes were characterized by distinct prognoses and TME. Afterward, we filtrated the overlapped genes based on the differentially expressed genes (DEGs) between the metabolic and immune subtypes by lasso regression and Cox regression, and used them to build risk score signature which led to PC patients was categorized into high- and low-risk groups. Nomogram were built to predict the survival rates of each PC patient. RT-PCR, in vitro cell proliferation assay, PC organoid, immunohistochemistry staining were used to identify key oncogenes related to PC RESULTS: High-risk patients have a better response for various chemotherapeutic drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) database. We built a nomogram with the risk group, age, and the number of positive lymph nodes to predict the survival rates of each PC patient with average 1-year, 2-year, and 3-year areas under the curve (AUCs) equal to 0.792, 0.752, and 0.751. FAM83A, KLF5, LIPH, MYEOV were up-regulated in the PC cell line and PC tissues. Knockdown of FAM83A, KLF5, LIPH, MYEOV could reduce the proliferation in the PC cell line and PC organoids CONCLUSION: The risk score signature based on the metabolism and immune molecular subtypes can accurately predict the prognosis and guide treatments of PC, meanwhile, the metabolism-immune biomarkers may provide novel target therapy for PC.

Gallium-68-labeled fibroblast activation protein inhibitor-46 PET in patients with resectable or borderline resectable pancreatic ductal adenocarcinoma: A phase 2, multicenter, single arm, open label non-randomized study protocol

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease prone to widespread metastatic dissemination and characterized by a desmoplastic stroma that contributes to poor outcomes. Fibroblast activation protein (FAP)-expressing Cancer-Associated Fibroblasts (CAFs) are crucial components of the tumor stroma, influencing carcinogenesis, fibrosis, tumor growth, metastases, and treatment resistance. Non-invasive tools to profile CAF identity and function are essential for overcoming CAF-mediated therapy resistance, developing innovative targeted therapies, and improved patient outcomes. We present the design of a multicenter phase 2 study (clinicaltrials.gov identifier NCT05262855) of [68Ga]FAPI-46 PET to image FAP-expressing CAFs in resectable or borderline resectable PDAC.

METHODS

We will enroll up to 60 adult treatment-naïve patients with confirmed PDAC. These patients will be eligible for curative surgical resection, either without prior treatment (Cohort 1) or after neoadjuvant therapy (NAT) (Cohort 2). A baseline PET scan will be conducted from the vertex to mid-thighs approximately 15 minutes after administering 5 mCi (±2) of [68Ga]FAPI-46 intravenously. Cohort 2 patients will undergo an additional PET after completing NAT but before surgery. Histopathology and FAP immunohistochemistry (IHC) of initial diagnostic biopsy and resected tumor samples will serve as the truth standards. Primary objective is to assess the sensitivity, specificity, and accuracy of [68Ga]FAPI-46 PET for detecting FAP-expressing CAFs. Secondary objectives will assess predictive values and safety profile validation. Exploratory objectives are comparison of diagnostic performance of [68Ga]FAPI-46 PET to standard-of-care imaging, and comparison of pre- versus post-NAT [68Ga]FAPI-46 PET in Cohort 2.

CONCLUSION

To facilitate the clinical translation of [68Ga]FAPI-46 in PDAC, the current study seeks to implement a coherent strategy to mitigate risks and increase the probability of meeting FDA requirements and stakeholder expectations. The findings from this study could potentially serve as a foundation for a New Drug Application to the FDA.

TRIAL REGISTRATION

@ClinicalTrials.gov identifier NCT05262855.

Arachidonate 15-lipoxygenase-mediated production of Resolvin D5n-3 DPA abrogates pancreatic stellate cell-induced cancer cell invasion

Activation of pancreatic stellate cells (PSCs) to cancer-associated fibroblasts (CAFs) is responsible for the extensive desmoplastic reaction observed in PDAC stroma: a key driver of pancreatic ductal adenocarcinoma (PDAC) chemoresistance leading to poor prognosis. Specialized pro-resolving mediators (SPMs) are prime modulators of inflammation and its resolution, traditionally thought to be produced by immune cells. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based lipid mediator profiling PSCs as well as primary human CAFs express enzymes and receptors to produce and respond to SPMs. Human PSC/CAF SPM secretion profile can be modulated by rendering these cells activated [transforming growth factor beta (TGF-β)] or quiescent [all-trans retinoic acid (ATRA)]. ATRA-induced nuclear translocation of arachidonate-15-lipoxygenase (ALOX15) was linked to increased production of n-3 docosapentaenoic acid-derived Resolvin D5 (RvD5n-3 DPA), among other SPMs. Inhibition of RvD5n-3 DPA formation increases cancer cell invasion, whereas addback of this molecule reduced activated PSC-mediated cancer cell invasion. We also observed that circulating concentrations of RvD5n-3 DPA levels were decreased in peripheral blood of metastatic PDAC patients when compared with those measured in plasma of non-metastatic PDAC patients. Together, these findings indicate that RvD5n-3 DPA may regulate cancer-stroma cross-talk and invasion.

Eukaryotic translation initiation factor 2α kinase 2 in pancreatic cancer: An approach towards managing clinical prognosis and molecular immunological characterization

Most patients with pancreatic cancer are already in the late stages of the disease when they are diagnosed, and pancreatic cancer is a deadly disease with a poor prognosis. With the advancement of research, immunotherapy has become a new focus in the treatment of tumors. To the best of our knowledge, there is currently no reliable diagnostic or prognostic marker for pancreatic cancer; therefore, the present study investigated the potential of eukaryotic translation initiation factor 2α kinase 2 (EIF2AK2) as a predictive and diagnostic marker for pancreatic cancer. Immunohistochemical staining of clinical samples independently verified that EIF2AK2 expression was significantly higher in clinically operated pancreatic cancer tissues than in adjacent pancreatic tissues., and EIF2AK2 expression and differentially expressed genes (DEGs) were identified using downloadable RNA sequencing data from The Cancer Genome Atlas and Genomic Tumor Expression Atlas. In addition, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes analyses and immune cell infiltration were used for functional enrichment analysis of EIF2AK2-associated DEGs. The clinical importance of EIF2AK2 was also determined using Kaplan-Meier survival, Cox regression and time-dependent survival receiver operating characteristic curve analyses, and a predictive nomogram model was generated. Finally, the functional role of EIF2AK2 was assessed in PANC-1 cells using a short hairpin RNA-EIF2AK2 knockdown approach, including CCK-8, wound healing assay, cell cycle and apoptosis assays. The findings suggested that EIF2AK2 may have potential as a diagnostic and prognostic biomarker for patients with pancreatic cancer. Furthermore, EIF2AK2 may provide a new therapeutic target for patients with pancreatic cancer.

Deoxyribonucleic acid methylation driven aberrations in pancreatic cancer-related pathways

Pancreatic cancer (PanCa) presents a catastrophic disease with poor overall survival at advanced stages, with immediate requirement of new and effective treatment options. Besides genetic mutations, epigenetic dysregulation of signaling pathway-associated enriched genes are considered as novel therapeutic target. Mechanisms beneath the deoxyribonucleic acid methylation and its utility in developing of epi-drugs in PanCa are under trails. Combinations of epigenetic medicines with conventional cytotoxic treatments or targeted therapy are promising options to improving the dismal response and survival rate of PanCa patients. Recent studies have identified potentially valid pathways that support the prediction that future PanCa clinical trials will include vigorous testing of epigenomic therapies. Epigenetics thus promises to generate a significant amount of new knowledge of biological and medical importance. Our review could identify various components of epigenetic mechanisms known to be involved in the initiation and development of pancreatic ductal adenocarcinoma and related precancerous lesions, and novel pharmacological strategies that target these components could potentially lead to breakthroughs. We aim to highlight the possibilities that exist and the potential therapeutic interventions.

Inhibiting Stromal Class I HDACs Curbs Pancreatic Cancer Progression

Oncogenic lesions in pancreatic ductal adenocarcinoma (PDAC) hijack the epigenetic machinery in stromal components to establish a desmoplastic and therapeutic resistant tumor microenvironment (TME). Here we identify Class I histone deacetylases (HDACs) as key epigenetic factors facilitating the induction of pro-desmoplastic and pro-tumorigenic transcriptional programs in pancreatic stromal fibroblasts. Mechanistically, HDAC-mediated changes in chromatin architecture enable the activation of pro-desmoplastic programs directed by serum response factor (SRF) and forkhead box M1 (FOXM1). HDACs also coordinate fibroblast pro-inflammatory programs inducing leukemia inhibitory factor (LIF) expression, supporting paracrine pro-tumorigenic crosstalk. HDAC depletion in cancer-associated fibroblasts (CAFs) and treatment with the HDAC inhibitor entinostat (Ent) in PDAC mouse models reduce stromal activation and curb tumor progression. Notably, HDAC inhibition (HDACi) enriches a lipogenic fibroblast subpopulation, a potential precursor for myofibroblasts in the PDAC stroma. Overall, our study reveals the stromal targeting potential of HDACi, highlighting the utility of this epigenetic modulating approach in PDAC therapeutics.

A first-in-class pan-lysyl oxidase inhibitor impairs stromal remodeling and enhances gemcitabine response and survival in pancreatic cancer

The lysyl oxidase family represents a promising target in stromal targeting of solid tumors due to the importance of this family in crosslinking and stabilizing fibrillar collagens and its known role in tumor desmoplasia. Using small-molecule drug-design approaches, we generated and validated PXS-5505, a first-in-class highly selective and potent pan-lysyl oxidase inhibitor. We demonstrate in vitro and in vivo that pan-lysyl oxidase inhibition decreases chemotherapy-induced pancreatic tumor desmoplasia and stiffness, reduces cancer cell invasion and metastasis, improves tumor perfusion and enhances the efficacy of chemotherapy in the autochthonous genetically engineered KPC model, while also demonstrating antifibrotic effects in human patient-derived xenograft models of pancreatic cancer. PXS-5505 is orally bioavailable, safe and effective at inhibiting lysyl oxidase activity in tissues. Our findings present the rationale for progression of a pan-lysyl oxidase inhibitor aimed at eliciting a reduction in stromal matrix to potentiate chemotherapy in pancreatic ductal adenocarcinoma.

Heterogeneous tumor microenvironment in pancreatic ductal adenocarcinoma: An emerging role of single-cell analysis

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies in the world, for which the mortality is almost as high as the disease incidence and is predicted to be the second-highest cause of cancer-related deaths by 2030. These cancerous tumors consist of diversified gene expressions within the different cellular subpopulations that include neoplastic ductal cells, cancer-associated fibroblasts, and immune cells, all of which collectively facilitate cellular heterogeneity in the PDAC tumor microenvironment (TME). Active intratumoral interaction within the cell populations in TME induces the proliferation of cancerous cells, accounting for tumorigenesis and rapid metastasis.

METHODS

This review will focus on novel findings uncovering PDAC heterogeneity in different cellular subpopulations using single-cell RNA-sequencing (scRNA-seq) and other single-cell analysis technologies. It will further explore the emerging role of single-cell technologies in assessing the role of different subpopulations of neoplastic ductal cells, cancer-associated fibroblasts, and immune cells in PDAC progression.

RESULTS AND CONCLUSION

The application of scRNA-seq in PDAC has started to unveil associations between disease progression and heterogeneity in pancreatic TME and could influence future PDAC treatment. Recent advances in scRNA-seq have uncovered comprehensive analyses of heterogeneous ecosystems present within the TME. These emerging findings underpins further need for a more in-depth understanding of intratumoral heterogeneity in the PDAC microenvironment.

Identifying a baicalein-related prognostic signature contributes to prognosis prediction and tumor microenvironment of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant and lethal human cancers in the world due to its high metastatic potential, and patients with PDAC have a poor prognosis, yet quite little is understood regarding the underlying biological mechanisms of its high metastatic capacity. Baicalein has a dramatic anti-tumor function in the treatment of different types of cancer. However, the therapeutic effects of baicalein on human PDAC and its mechanisms of action have not been extensively understood. In order to explore the biological characteristic, molecular mechanisms, and potential clinical value of baicalein in inhibiting the metastatic capacity of PDAC. We performed several in vitro, in vivo, and in silico studies. We first examined the potential regulation of baicalein in the metastatic capacity of PDAC cells. We showed that baicalein could dramatically suppress liver metastasis of PDAC cells with highly metastatic potential in mice model. The high-throughput sequencing analysis was employed to explore the biological roles of baicalein in PDAC cells. We found that baicalein might be involved in the infiltration of Cancer-Associated Fibroblasts (CAF) in PDAC. Moreover, a baicalein-related risk model and a lncRNA-related model were built by Cox analysis according to the data set of PDAC from TCGA database which suggested a clinical value of baicalein. Finally, we revealed a potential downstream target of baicalein in PDAC, we proposed that baicalein might contribute to the infiltration of CAF via FGFBP1. Thus, we uncovered a novel role for baicalein in regulation of PDAC liver metastasis that may contribute to its anti-cancer effect. We proposed that baicalein might suppress PDAC liver metastasis via regulation of FGFBP1-mediated CAF infiltration. Our results provide a new perspective on clinical utility of baicalein and open new avenues for the inhibition of liver-metastasis of PDAC.