Molecular subtypes of pancreatic cancer

Functional and Clinical Proteomic Exploration of Pancreatic Cancer

Pancreatic cancer, most cases being pancreatic ductal adenocarcinoma (PDAC), is one of the most lethal cancers with a median survival time of less than 6 months. Therapeutic options are very limited for PDAC patients, and surgery is still the most effective treatment, making improvements in early diagnosis critical. One typical characteristic of PDAC is the desmoplastic reaction of its stroma microenvironment, which actively interacts with cancer cells to orchestrate key components in tumorigenesis, metastasis, and chemoresistance. Global exploration of cancer-stroma crosstalk is essential to decipher PDAC biology and design intervention strategies. Over the past decade, the dramatic improvement of proteomics technologies has enabled profiling of proteins, post-translational modifications (PTMs), and their protein complexes at unprecedented sensitivity and dimensionality. Here, starting with our current understanding of PDAC characteristics, including precursor lesions, progression models, tumor microenvironment, and therapeutic advancements, we describe how proteomics contributes to the functional and clinical exploration of PDAC, providing insights into PDAC carcinogenesis, progression, and chemoresistance. We summarize recent achievements enabled by proteomics to systematically investigate PTMs-mediated intracellular signaling in PDAC, cancer-stroma interactions, and potential therapeutic targets revealed by these functional studies. We also highlight proteomic profiling of clinical tissue and plasma samples to discover and verify useful biomarkers that can aid early detection and molecular classification of patients. In addition, we introduce spatial proteomic technology and its applications in PDAC for deconvolving tumor heterogeneity. Finally, we discuss future prospects of applying new proteomic technologies in comprehensively understanding PDAC heterogeneity and intercellular signaling networks. Importantly, we expect advances in clinical functional proteomics for exploring mechanisms of cancer biology directly by high-sensitivity functional proteomic approaches starting from clinical samples.

The expression characteristics of transmembrane protein genes in pancreatic ductal adenocarcinoma through comprehensive analysis of bulk and single-cell RNA sequence

Background

Transmembrane (TMEM) protein genes are a class of proteins that spans membranes and function to many physiological processes. However, there is very little known about TMEM gene expression, especially in cancer tissue. Using single-cell and bulk RNA sequence may facilitate the understanding of this poorly characterized protein genes in PDAC.

Methods

We selected the TMEM family genes through the Human Protein Atlas and characterized their expression by single-cell and bulk transcriptomic datasets. Identification of the key TMEM genes was performed through three machine learning algorithms: LASSO, SVM-RFE and RF-SRC. Then, we established TMEM gene riskscore and estimate its implication in predicting survival and response to systematic therapy. Additionally, we explored the difference and impact of TMEM gene expression in PDAC through immunohistochemistry and cell line research.

Results

5 key TMEM genes (ANO1, TMEM59, TMEM204, TMEM205, TMEM92) were selected based on the single-cell analysis and machine learning survival outcomes. Patients stratified into the high and low-risk groups based on TMEM riskscore, were observed with distinct overall survival in internal and external datasets. Moreover, through bulk RNA-sequence and immunohistochemical staining we verified the protein expression of TMEM genes in PDAC and revealed TMEM92 as an essential regulator of pancreatic cancer cell proliferation, migration, and invasion.

Conclusion

Our study on TMEM gene expression and behavior in PDAC has revealed unique characteristics, offering potential for precise therapeutic approaches. Insights into molecular mechanisms expand understanding of PDAC complexity and TMEM gene roles. Such knowledge may inform targeted therapy development, benefiting patients.

Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins

Background

Immune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC.

Methods

We comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients' clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell's concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms.

Results

Soluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes' expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16).

Conclusion

Five soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype.

Cell-selective proteomics segregates pancreatic cancer subtypes by extracellular proteins in tumors and circulation

Cell-selective proteomics is a powerful emerging concept to study heterocellular processes in tissues. However, its high potential to identify non-cell-autonomous disease mechanisms and biomarkers has been hindered by low proteome coverage. Here, we address this limitation and devise a comprehensive azidonorleucine labeling, click chemistry enrichment, and mass spectrometry-based proteomics and secretomics strategy to dissect aberrant signals in pancreatic ductal adenocarcinoma (PDAC). Our in-depth co-culture and in vivo analyses cover more than 10,000 cancer cell-derived proteins and reveal systematic differences between molecular PDAC subtypes. Secreted proteins, such as chemokines and EMT-promoting matrisome proteins, associated with distinct macrophage polarization and tumor stromal composition, differentiate classical and mesenchymal PDAC. Intriguingly, more than 1,600 cancer cell-derived proteins including cytokines and pre-metastatic niche formation-associated factors in mouse serum reflect tumor activity in circulation. Our findings highlight how cell-selective proteomics can accelerate the discovery of diagnostic markers and therapeutic targets in cancer.

The resurgence of the Adora2b receptor as an immunotherapeutic target in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense desmoplastic stroma that impedes drug delivery, reduces parenchymal blood flow, and suppresses the anti-tumor immune response. The extracellular matrix and abundance of stromal cells result in severe hypoxia within the tumor microenvironment (TME), and emerging publications evaluating PDAC tumorigenesis have shown the adenosine signaling pathway promotes an immunosuppressive TME and contributes to the overall low survival rate. Hypoxia increases many elements of the adenosine signaling pathway, resulting in higher adenosine levels in the TME, further contributing to immune suppression. Extracellular adenosine signals through 4 adenosine receptors (Adora1, Adora2a, Adora2b, Adora3). Of the 4 receptors, Adora2b has the lowest affinity for adenosine and thus, has important consequences when stimulated by adenosine binding in the hypoxic TME. We and others have shown that Adora2b is present in normal pancreas tissue, and in injured or diseased pancreatic tissue, Adora2b levels are significantly elevated. The Adora2b receptor is present on many immune cells, including macrophages, dendritic cells, natural killer cells, natural killer T cells, γδ T cells, B cells, T cells, CD4+ T cells, and CD8+ T cells. In these immune cell types, adenosine signaling through Adora2b can reduce the adaptive anti-tumor response, augmenting immune suppression, or may contribute to transformation and changes in fibrosis, perineural invasion, or the vasculature by binding the Adora2b receptor on neoplastic epithelial cells, cancer-associated fibroblasts, blood vessels, lymphatic vessels, and nerves. In this review, we discuss the mechanistic consequences of Adora2b activation on cell types in the tumor microenvironment. As the cell-autonomous role of adenosine signaling through Adora2b has not been comprehensively studied in pancreatic cancer cells, we will also discuss published data from other malignancies to infer emerging therapeutic considerations for targeting the Adora2b adenosine receptor to reduce the proliferative, invasive, and metastatic potential of PDAC cells.

Preoperative treatments in borderline resectable and locally advanced pancreatic cancer: current evidence and new perspectives

Surgery is the only curative treatment for non-metastatic pancreatic adenocarcinoma, but less than 20% of patients present a resectable disease at diagnosis. Treatment strategies and disease definition for borderline resectable pancreatic cancer (BRPC) and locally advanced pancreatic cancer (LAPC) vary in the different cancer centres. Preoperative chemotherapy (CT) is the standard of care for both BRPC and LAPC patients, however literature data are still controversial concerning the type, dose and duration of the different CT regimens, as well as regarding the integration of radiotherapy (RT) or chemoradiation (CRT) in the therapeutic algorithm. In this unsettled debate, we aimed at focusing on the therapeutic regimens currently in use and relative literature data, to report international trials comparing the available therapeutic options or explore the introduction of new pharmacological agents, and to analyse possible new scenarios in microenvironment evaluation before and after neoadjuvant therapies or in patients' selection at a molecular level.

Pancreatic cancer: Advances and challenges

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers. Significant efforts have largely defined major genetic factors driving PDAC pathogenesis and progression. Pancreatic tumors are characterized by a complex microenvironment that orchestrates metabolic alterations and supports a milieu of interactions among various cell types within this niche. In this review, we highlight the foundational studies that have driven our understanding of these processes. We further discuss the recent technological advances that continue to expand our understanding of PDAC complexity. We posit that the clinical translation of these research endeavors will enhance the currently dismal survival rate of this recalcitrant disease.

Progress on diagnostic and prognostic markers of pancreatic cancer

Pancreatic cancer is a malignant disease characterized by low survival and high recurrence rate, whose patients are mostly at the stage of locally advanced or metastatic disease when first diagnosed. Early diagnosis is particularly important because prognostic/predictive markers help guide optimal individualized treatment regimens. So far, CA19-9 is the only biomarker for pancreatic cancer approved by the FDA, but its effectiveness is limited by low sensitivity and specificity. With recent advances in genomics, proteomics, metabolomics, and other analytical and sequencing technologies, the rapid acquisition and screening of biomarkers is now possible. Liquid biopsy also occupies a significant place due to its unique advantages. In this review, we systematically describe and evaluate the available biomarkers that have the greatest potential as vital tools in diagnosing and treating pancreatic cancer.

A novel immune checkpoint score system for prognostic evaluation in pancreatic adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) remains a lethal malignancy making the detection of novel prognostic biomarkers urgent. Limited studies have investigated the predictive capability of immune checkpoints in PAAD.

METHOD

Gene expression data and correlative clinical information of PAAD cohort were obtained from public databases, including TCGA, ICGC, GTEX and GEO databases. Risk factors were screened and used to establish a risk score model through LASSO and Cox regression analyses. The prognostic ability of the risk score model was demonstrated. The association between risk score with immune cells infiltration, immune checkpoint genes expression, immunogenic cell death, somatic mutations and signaling pathways enrichment were analysed. scRNA-seq data were collected to confirmed the immune checkpoints expression in PAAD samples. The prognosis prediction ability of OX40/TNFRSF4 was identified. The mRNA and protein expression of OX40 in our clinical specimens were examined by RT-PCR and IHC method and its prognosis ability was verified.

RESULTS

First of all, the difference of immune microenvironment between pancreatic cancer and adjacent tissues was shown. A risk score system based on three immune checkpoints (OX40, TNFSF14 and KIR3DL1) was established. The risk score model was an independent prognostic factor and performed well regarding overall survival (OS) predictions among PAAD patients. A nomogram was established to facilitate the risk model application in clinical prognosis. Immune cells including naive B cells, CD8⁺ T cells and Tregs were negatively correlated with the risk score. The risk score was associated with expression of immune checkpoint genes, immunogenic cell death related genes and somatic mutations. Glycolysis processes, IL-2-STAT5, IL-6-STAT3, and mTORC1 signaling pathways were enriched in the high-risk score group. Furthermore, scRNA-seq data confirmed that TNFRSF4, TNFSF14 and KIR3DL1 were expressed on immune cells in PAAD samples. We then identified OX40 as an independent prognosis-related gene, and a higher OX40 expression was associated with increased survival rate and immune environment change. In 84 PAAD clinical specimens collected from our center, we confirmed that higher OX40 mRNA expression levels were related to a good prognosis. The protein expression of OX40 on tumor-infiltrating immune cells (TIICs), endothelial cells and tumor cells was verified in PAAD tissues by immunohistochemistry (IHC) method.

CONCLUSIONS

Overall, our findings strongly suggested that the three-immune checkpoints score system might be useful in the prognosis and design of personalized treatments for PAAD patients. Finally, we identified OX40 as an independent potential biomarker for PAAD prognosis prediction.

Development of an artificial intelligence-derived histologic signature associated with adjuvant gemcitabine treatment outcomes in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) has been left behind in the evolution of personalized medicine. Predictive markers of response to therapy are lacking in PDAC despite various histological and transcriptional classification schemes. We report an artificial intelligence (AI) approach to histologic feature examination that extracts a signature predictive of disease-specific survival (DSS) in patients with PDAC receiving adjuvant gemcitabine. We demonstrate that this AI-generated histologic signature is associated with outcomes following adjuvant gemcitabine, while three previously developed transcriptomic classification systems are not (n = 47). We externally validate this signature in an independent cohort of patients treated with adjuvant gemcitabine (n = 46). Finally, we demonstrate that the signature does not stratify survival outcomes in a third cohort of untreated patients (n = 161), suggesting that the signature is specifically predictive of treatment-related outcomes but is not generally prognostic. This imaging analysis pipeline has promise in the development of actionable markers in other clinical settings where few biomarkers currently exist.

Molecular Subtyping and Survival Analysis of Osteosarcoma Reveals Prognostic Biomarkers and Key Canonical Pathways

Osteosarcoma (OS) is a common bone malignancy in children and adolescents. Although histological subtyping followed by improved OS treatment regimens have helped achieve favorable outcomes, a lack of understanding of the molecular subtypes remains a challenge to characterize its genetic heterogeneity and subsequently to identify diagnostic and prognostic biomarkers for developing effective treatments. In the present study, global analysis of DNA methylation, and mRNA and miRNA gene expression in OS patient samples were correlated with their clinical characteristics. The mucin family of genes, MUC6, MUC12, and MUC4, were found to be highly mutated in the OS patients. Results revealed the enrichment of molecular pathways including Wnt signaling, Calcium signaling, and PI3K-Akt signaling in the OS tumors. Survival analyses showed that the expression levels of several genes such as RAMP1, CRIP1, CORT, CHST13, and DDX60L, miRNAs and lncRNAs were associated with survival of OS patients. Molecular subtyping using Cluster-Of-Clusters Analysis (COCA) for mRNA, lncRNA, and miRNA expression; DNA methylation; and mutation data from the TARGET dataset revealed two distinct molecular subtypes, each with a distinctive gene expression profile. Between the two subtypes, three upregulated genes, POP4, HEY1, CERKL, and seven downregulated genes, CEACAM1, ABLIM1, LTBP2, ISLR, LRRC32, PTPRF, and GPX3, associated with OS metastasis were found to be differentially regulated. Thus, the molecular subtyping results provide a strong basis for classification of OS patients that could be used to develop better prognostic treatment strategies.

Mechanisms of obesity- and diabetes mellitus-related pancreatic carcinogenesis: a comprehensive and systematic review

Research on obesity- and diabetes mellitus (DM)-related carcinogenesis has expanded exponentially since these two diseases were recognized as important risk factors for cancers. The growing interest in this area is prominently actuated by the increasing obesity and DM prevalence, which is partially responsible for the slight but constant increase in pancreatic cancer (PC) occurrence. PC is a highly lethal malignancy characterized by its insidious symptoms, delayed diagnosis, and devastating prognosis. The intricate process of obesity and DM promoting pancreatic carcinogenesis involves their local impact on the pancreas and concurrent whole-body systemic changes that are suitable for cancer initiation. The main mechanisms involved in this process include the excessive accumulation of various nutrients and metabolites promoting carcinogenesis directly while also aggravating mutagenic and carcinogenic metabolic disorders by affecting multiple pathways. Detrimental alterations in gastrointestinal and sex hormone levels and microbiome dysfunction further compromise immunometabolic regulation and contribute to the establishment of an immunosuppressive tumor microenvironment (TME) for carcinogenesis, which can be exacerbated by several crucial pathophysiological processes and TME components, such as autophagy, endoplasmic reticulum stress, oxidative stress, epithelial-mesenchymal transition, and exosome secretion. This review provides a comprehensive and critical analysis of the immunometabolic mechanisms of obesity- and DM-related pancreatic carcinogenesis and dissects how metabolic disorders impair anticancer immunity and influence pathophysiological processes to favor cancer initiation.

Ferroptosis in gastrointestinal cancer: From mechanisms to implications

Ferroptosis is a form of regulated cell death that is initiated by excessive lipid peroxidation that results in plasma membrane damage and the release of damage-associated molecular patterns. In recent years, ferroptosis has gained significant attention in cancer research due to its unique mechanism compared to other forms of regulated cell death, especially caspase-dependent apoptotic cell death. Gastrointestinal (GI) cancer encompasses malignancies that arise in the digestive tract, including the stomach, intestines, pancreas, colon, liver, rectum, anus, and biliary system. These cancers are a global health concern, with high incidence and mortality rates. Despite advances in medical treatments, drug resistance caused by defects in apoptotic pathways remains a persistent challenge in the management of GI cancer. Hence, exploring the role of ferroptosis in GI cancers may lead to more efficacious treatment strategies. In this review, we provide a comprehensive overview of the core mechanism of ferroptosis and discuss its function, regulation, and implications in the context of GI cancers.

In vivo models of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with high mortality rate. Within the next decade, PDAC is projected to become the second leading cause of cancer-associated death in the United States. Understanding the pathophysiology of PDAC tumorigenesis and metastases is crucial toward developing new therapeutics. One of the challenges in cancer research is generating in vivo models that closely recapitulate the genomic, histological, and clinical characteristics of human tumors. An ideal model for PDAC not only captures the tumor and stromal environment of human disease, but also allows for mutational control and is easy to reproduce in terms of time and cost. In this review, we highlight evolution of in vivo models for PDAC including spontaneous tumors models (i.e., chemical induction, genetic modification, viral delivery), implantation models including patient derived xenografts (PDX), and humanized PDX. We discuss the implementation of each system and evaluate the benefits and shortcomings of these models. Overall, this review provides a broad overview of prior and current techniques of in vivo PDAC modeling and their associated challenges.

Single-cell profiling to explore pancreatic cancer heterogeneity, plasticity and response to therapy

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer entity characterized by a heterogeneous genetic landscape and an immunosuppressive tumor microenvironment. Recent advances in high-resolution single-cell sequencing and spatial transcriptomics technologies have enabled an in-depth characterization of both malignant and host cell types and increased our understanding of the heterogeneity and plasticity of PDAC in the steady state and under therapeutic perturbation. In this Review we outline single-cell analyses in PDAC, discuss their implications on our understanding of the disease and present future perspectives of multimodal approaches to elucidate its biology and response to therapy at the single-cell level.

Multi-omics profiling of papillary thyroid microcarcinoma reveals different somatic mutations and a unique transcriptomic signature

BACKGROUND

Papillary thyroid microcarcinoma (PTMC) incidence has significantly increased, and some cases still exhibit invasive traits. The entire molecular landscape of PTMC, which can offer hints for the etiology of cancer, is currently absent.

METHODS

We compared our findings with those for PTMC in the TCGA by analyzing the largest study at the current stage of whole exome sequencing and RNA-sequencing data from 64 patients with PTMC. Then, we systematically demonstrated the differences between the two PTMC subtypes based on multi-omics analyses. Additionally, we created a molecular prediction model for the PTMC subtypes and validated them among TCGA patients for individualized integrative assessment.

RESULTS

In addition to the presence of BRAF mutations and RET fusions in the TCGA cohort, we also discovered a new molecular signature named PTMC-inflammatory that implies a potential response to immune intervention, which is enriched with AFP mutations, IGH@-ext fusions, elevated immune-related genes, positive peroxidase antibody, and positive thyroglobulin antibody. Additionally, a molecular prediction model for the PTMC-inflammatory patients was created and validated among TCGA patients, while the prognosis for these patients is poor.

CONCLUSIONS

Our findings comprehensively define the clinical and molecular features of PTMC and may inspire new therapeutic hypotheses.

Neoadjuvant therapy for pancreatic cancer

Patients with localized pancreatic ductal adenocarcinoma (PDAC) are best treated with surgical resection of the primary tumour and systemic chemotherapy, which provides considerably longer overall survival (OS) durations than either modality alone. Regardless, most patients will have disease relapse owing to micrometastatic disease. Although currently a matter of some debate, considerable research interest has been focused on the role of neoadjuvant therapy for all forms of resectable PDAC. Whilst adjuvant combination chemotherapy remains the standard of care for patients with resectable PDAC, neoadjuvant chemotherapy seems to improve OS without necessarily increasing the resection rate in those with borderline-resectable disease. Furthermore, around 20% of patients with unresectable non-metastatic PDAC might undergo resection following 4-6 months of induction combination chemotherapy with or without radiotherapy, even in the absence of a clear radiological response, leading to improved OS outcomes in this group. Distinct molecular and biological responses to different types of therapies need to be better understood in order to enable the optimal sequencing of specific treatment modalities to further improve OS. In this Review, we describe current treatment strategies for the various clinical stages of PDAC and discuss developments that are likely to determine the optimal sequence of multimodality therapies by integrating the fundamental clinical and molecular features of the cancer.

HMGA1 induces FGF19 to drive pancreatic carcinogenesis and stroma formation

High mobility group A1 (HMGA1) chromatin regulators are upregulated in diverse tumors where they portend adverse outcomes, although how they function in cancer remains unclear. Pancreatic ductal adenocarcinomas (PDACs) are highly lethal tumors characterized by dense desmoplastic stroma composed predominantly of cancer-associated fibroblasts and fibrotic tissue. Here, we uncover an epigenetic program whereby HMGA1 upregulates FGF19 during tumor progression and stroma formation. HMGA1 deficiency disrupts oncogenic properties in vitro while impairing tumor inception and progression in KPC mice and subcutaneous or orthotopic models of PDAC. RNA sequencing revealed HMGA1 transcriptional networks governing proliferation and tumor-stroma interactions, including the FGF19 gene. HMGA1 directly induces FGF19 expression and increases its protein secretion by recruiting active histone marks (H3K4me3, H3K27Ac). Surprisingly, disrupting FGF19 via gene silencing or the FGFR4 inhibitor BLU9931 recapitulates most phenotypes observed with HMGA1 deficiency, decreasing tumor growth and formation of a desmoplastic stroma in mouse models of PDAC. In human PDAC, overexpression of HMGA1 and FGF19 defines a subset of tumors with extremely poor outcomes. Our results reveal what we believe is a new paradigm whereby HMGA1 and FGF19 drive tumor progression and stroma formation, thus illuminating FGF19 as a rational therapeutic target for a molecularly defined PDAC subtype.

Clinical Value of Circulating miRNA in Diagnosis, Prognosis, Screening and Monitoring Therapy of Pancreatic Ductal Adenocarcinoma-A Review of the Literature

Pancreatic cancer (PC) is considered to be the seventh most common cause of cancer-related deaths. The number of deaths caused by PC is estimated to increase in the future. An early diagnosis of PC is crucial for improving treatment outcomes. The most common histopathological subtype of PC is pancreatic ductal adenocarcinoma (PDAC). MicroRNAs (miRNAs)-which are endogenous non-coding RNAs involved in the posttranscriptional regulation of multiple gene expression-constitute useful diagnostic and prognostic biomarkers in various neoplasms, including PDAC. Circulating miRNAs detected in a patient's serum or plasma are drawing more and more attention. Hence, this review aims at evaluating the clinical value of circulating miRNA in the screening, diagnosis, prognosis and monitoring of pancreatic ductal adenocarcinoma therapy.

A Paradigm Shifts: Neoadjuvant Therapy for Clearly Resectable Pancreatic Cancer

Over the past decade, neoadjuvant therapy has become the standard of care for patients with borderline resectable and locally advanced pancreatic cancer. The surgical community remains divided regarding the value of neoadjuvant therapy for patients who present with clearly resectable disease. Thus far, randomized controlled trials comparing neoadjuvant therapy with conventional upfront surgical strategies for patients with clearly resectable pancreatic cancer have been plagued by poor accrual, and are often underpowered. Nonetheless, meta-analyses of the results of these trials suggest that neoadjuvant therapy can be offered as an acceptable standard of care for patients with clearly resectable pancreatic cancer. Previous trials used neoadjuvant gemcitabine, but more recent studies have demonstrated superior survival for patients who were able to tolerate neoadjuvant FOLFIRINOX (leucovorin, 5-fluorouracil, irinotecan hydrochloride, and oxaliplatin). The increased utilization of FOLFIRINOX may be shifting the treatment paradigm in favor of neoadjuvant therapy among patients with clearly resectable disease. Randomized controlled trials assessing the value of neoadjuvant FOLFIRINOX in clearly resectable pancreatic cancer, which are expected to provide more conclusive recommendations, are still ongoing. This review outlines the rationale, considerations, and current level of evidence for the use of neoadjuvant therapy in patients with clearly resectable pancreatic cancer.

An analysis of classical multidimensional scaling with applications to clustering

Classical multidimensional scaling is a widely used dimension reduction technique. Yet few theoretical results characterizing its statistical performance exist. This paper provides a theoretical framework for analyzing the quality of embedded samples produced by classical multidimensional scaling. This lays a foundation for various downstream statistical analyses, and we focus on clustering noisy data. Our results provide scaling conditions on the signal-to-noise ratio under which classical multidimensional scaling followed by a distance-based clustering algorithm can recover the cluster labels of all samples. Simulation studies confirm these scaling conditions are sharp. Applications to the cancer gene-expression data, the single-cell RNA sequencing data and the natural language data lend strong support to the methodology and theory.

Construction of a radiogenomic association map of pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PDAC) persists as a malignancy with high morbidity and mortality that can benefit from new means to characterize and detect these tumors, such as radiogenomics. In order to address this gap in the literature, constructed a transcriptomic-CT radiogenomic (RG) map for PDAC.

METHODS

In this Institutional Review Board approved study, a cohort of subjects (n = 50) with gene expression profile data paired with histopathologically confirmed resectable or borderline resectable PDAC were identified. Studies with pre-operative contrast-enhanced CT images were independently assessed for a set of 88 predefined imaging features. Microarray gene expression profiling was then carried out on the histopathologically confirmed pancreatic adenocarcinomas and gene networks were constructed using Weighted Gene Correlation Network Analysis (WCGNA) (n = 37). Data were analyzed with bioinformatics analyses, multivariate regression-based methods, and Kaplan-Meier survival analyses.

RESULTS

Survival analyses identified multiple features of interest that were significantly associated with overall survival, including Tumor Height (P = 0.014), Tumor Contour (P = 0.033), Tumor-stroma Interface (P = 0.014), and the Tumor Enhancement Ratio (P = 0.047). Gene networks for these imaging features were then constructed using WCGNA and further annotated according to the Gene Ontology (GO) annotation framework for a biologically coherent interpretation of the imaging trait-associated gene networks, ultimately resulting in a PDAC RG CT-transcriptome map composed of 3 stage-independent imaging traits enriched in metabolic processes, telomerase activity, and podosome assembly (P < 0.05).

CONCLUSIONS

A CT-transcriptomic RG map for PDAC composed of semantic and quantitative traits with associated biology processes predictive of overall survival, was constructed, that serves as a reference for further mechanistic studies for non-invasive phenotyping of pancreatic tumors.

Leveraging Tumor Microenvironment Infiltration in Pancreatic Cancer to Identify Gene Signatures Related to Prognosis and Immunotherapy Response

The hallmark of pancreatic ductal adenocarcinoma (PDAC) is an exuberant tumor microenvironment (TME) comprised of diverse cell types that play key roles in carcinogenesis, chemo-resistance, and immune evasion. Here, we propose a gene signature score through the characterization of cell components in TME for promoting personalized treatments and further identifying effective therapeutic targets. We identified three TME subtypes based on cell components quantified by single sample gene set enrichment analysis. A prognostic risk score model (TMEscore) was established based on TME-associated genes using a random forest algorithm and unsupervised clustering, followed by validation in immunotherapy cohorts from the GEO dataset for its performance in predicting prognosis. Importantly, TMEscore positively correlated with the expression of immunosuppressive checkpoints and negatively with the gene signature of T cells' responses to IL2, IL15, and IL21. Subsequently, we further screened and verified F2R-like Trypsin Receptor1 (F2RL1) among the core genes related to TME, which promoted the malignant progression of PDAC and has been confirmed as a good biomarker with therapeutic potential in vitro and in vivo experiments. Taken together, we proposed a novel TMEscore for risk stratification and selection of PDAC patients in immunotherapy trials and validated effective pharmacological targets.

Extrahepatic Distal Cholangiocarcinoma vs. Pancreatic Ductal Adenocarcinoma: Histology and Molecular Profiling for Differential Diagnosis and Treatment

Pancreatic ductal adenocarcinoma (PDAC) and distal cholangiocarcinoma (dCCA) are very aggressive tumors with a high mortality rate. Pancreas and distal bile ducts share a common embryonic development. Hence, PDAC and dCCA exhibit similar histological features that make a differential diagnosis during routine diagnostic practice challenging. However, there are also significant differences, with potential clinical implications. Even if PDAC and dCCA are generally associated with poor survival, patients with dCCA seem to present a better prognosis. Moreover, although precision oncology-based approaches are still limited in both entities, their most important targets are different and include alterations affecting BRCA1/2 and related genes in PDAC, as well as HER2 amplification in dCCA. Along this line, microsatellite instability represents a potential contact point in terms of tailored treatments, but its prevalence is very low in both tumor types. This review aims at defining the most important similarities and differences in terms of clinicopathological and molecular features between these two entities, also discussing the main theranostic implications derived from this challenging differential diagnosis.

Single-cell RNA sequencing reveals the effects of chemotherapy on human pancreatic adenocarcinoma and its tumor microenvironment

The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. Here, we perform single-cell RNA sequencing on freshly collected human PDAC samples either before or after chemotherapy. Overall, we find a heterogeneous mixture of basal and classical cancer cell subtypes, along with distinct cancer-associated fibroblast and macrophage subpopulations. Strikingly, classical and basal-like cancer cells exhibit similar transcriptional responses to chemotherapy and do not demonstrate a shift towards a basal-like transcriptional program among treated samples. We observe decreased ligand-receptor interactions in treated samples, particularly between TIGIT on CD8 + T cells and its receptor on cancer cells, and identify TIGIT as the major inhibitory checkpoint molecule of CD8 + T cells. Our results suggest that chemotherapy profoundly impacts the PDAC TME and may promote resistance to immunotherapy.

Open-source curation of a pancreatic ductal adenocarcinoma gene expression analysis platform (pdacR) supports a two-subtype model

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease for which potent therapies have limited efficacy. Several studies have described the transcriptomic landscape of PDAC tumors to provide insight into potentially actionable gene expression signatures to improve patient outcomes. Despite centralization efforts from multiple organizations and increased transparency requirements from funding agencies and publishers, analysis of public PDAC data remains difficult. Bioinformatic pitfalls litter public transcriptomic data, such as subtle inclusion of low-purity and non-adenocarcinoma cases. These pitfalls can introduce non-specificity to gene signatures without appropriate data curation, which can negatively impact findings. To reduce barriers to analysis, we have created pdacR ( http://pdacR.bmi.stonybrook.edu , github.com/rmoffitt/pdacR), an open-source software package and web-tool with annotated datasets from landmark studies and an interface for user-friendly analysis in clustering, differential expression, survival, and dimensionality reduction. Using this tool, we present a multi-dataset analysis of PDAC transcriptomics that confirms the basal-like/classical model over alternatives.

Context-Specific Determinants of the Immunosuppressive Tumor Microenvironment in Pancreatic Cancer

Immunotherapies have shown benefits across a range of human cancers, but not pancreatic ductal adenocarcinoma (PDAC). Recent evidence suggests that the immunosuppressive tumor microenvironment (TME) constitutes an important roadblock to their efficacy. The landscape of the TME differs substantially across PDAC subtypes, indicating context-specific principles of immunosuppression. In this review, we discuss how PDAC cells, the local TME, and systemic host and environmental factors drive immunosuppression in context. We argue that unraveling the mechanistic drivers of the context-specific modes of immunosuppression will open new possibilities to target PDAC more efficiently by using multimodal (immuno)therapeutic interventions.

SIGNIFICANCE

Immunosuppression is an almost universal hallmark of pancreatic cancer, although this tumor entity is highly heterogeneous across its different subtypes and phenotypes. Here, we provide evidence that the diverse TME of pancreatic cancer is a central executor of various different context-dependent modes of immunosuppression, and discuss key challenges and novel opportunities to uncover, functionalize, and target the central drivers and functional nodes of immunosuppression for therapeutic exploitation.

Recent Advances in Well-Designed Therapeutic Nanosystems for the Pancreatic Ductal Adenocarcinoma Treatment Dilemma

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with an extremely poor prognosis and low survival rate. Due to its inconspicuous symptoms, PDAC is difficult to diagnose early. Most patients are diagnosed in the middle and late stages, losing the opportunity for surgery. Chemotherapy is the main treatment in clinical practice and improves the survival of patients to some extent. However, the improved prognosis is associated with higher side effects, and the overall prognosis is far from satisfactory. In addition to resistance to chemotherapy, PDAC is significantly resistant to targeted therapy and immunotherapy. The failure of multiple treatment modalities indicates great dilemmas in treating PDAC, including high molecular heterogeneity, high drug resistance, an immunosuppressive microenvironment, and a dense matrix. Nanomedicine shows great potential to overcome the therapeutic barriers of PDAC. Through the careful design and rational modification of nanomaterials, multifunctional intelligent nanosystems can be obtained. These nanosystems can adapt to the environment's needs and compensate for conventional treatments' shortcomings. This review is focused on recent advances in the use of well-designed nanosystems in different therapeutic modalities to overcome the PDAC treatment dilemma, including a variety of novel therapeutic modalities. Finally, these nanosystems' bottlenecks in treating PDAC and the prospect of future clinical translation are briefly discussed.

Utility of Comprehensive Genomic Profiling Tests for Patients with Incurable Pancreatic Cancer in Clinical Practice

Although comprehensive genomic profiling (CGP) tests have been covered under the Japanese national health insurance program since 2018, the utility and issues of CGP tests have not been clarified. We retrospectively reviewed 115 patients with incurable pancreatic cancer (IPC) who underwent CGP tests in a Japanese cancer referral center from November 2019 to August 2021. We evaluated the results of CGP tests, treatments based on CGP tests, and survival time. Eight cases (6.9%) were diagnosed as tumor mutation burden-high (TMB-H) and/or microsatellite instability-high (MSI-H). The gene mutation rates of KRAS/TP53/CDKN2A/SMAD4 were 93.0/83.0/53.0/25.2%, respectively. Twenty-five patients (21.7%) had homologous recombination deficiency (HRD)-related genetic mutations. Four patients (3.5%) having TMB-H and/or MSI-H were treated with pembrolizumab, and only two patients (1.7%) participated in the clinical trials. Patient characteristics were not significantly different between patients with and without HRD-related gene mutations. The median OS was significantly longer in the HRD (+) group than in the HRD (-) group (749 days vs. 519 days, p = 0.047). In multivariate analysis, HRD-related gene mutation was an independent prognostic factor associated with favorable OS. CGP tests for patients with IPC have the potential utility of detecting HRD-related gene mutations as prognostic factors as well as a therapeutic search.

Targeting ubiquitin-specific protease 8 sensitizes anti-programmed death-ligand 1 immunotherapy of pancreatic cancer

Programmed death-1 (PD-1) and its ligand programmed death-ligand 1 (PD-L1) help tumor cells evade immune surveillance, and are regarded as important targets of anti-tumor immunotherapy. Post-translational modification of PD-L1 has potential value in immunosuppression. Here, we identified that ubiquitin-specific protease 8 (USP8) deubiquitinates PD-L1. Pancreatic cancer tissues exhibited significantly increased USP8 levels compared with those in normal tissues. Clinically, the expression of USP8 showed a significant association with the tumor-node-metastasis stage in multiple patient-derived cohorts of pancreatic cancer. Meanwhile, USP8 deficiency could reduce tumor invasion and migration and tumor size in an immunity-dependent manner, and improve anti-tumor immunogenicity. USP8 inhibitor pretreatment led to reduced tumorigenesis and immunocompetent mice with Usp8 knockdown tumors exhibited extended survival. Moreover, USP8 interacted positively with PD-L1 and upregulated its expression by inhibiting the ubiquitination-regulated proteasome degradation pathway in pancreatic cancer. Combination therapy with a USP8 inhibitor and anti-PD-L1 effectively suppressed pancreatic tumor growth by activation of cytotoxic T-cells and the anti-tumor immunity was mainly dependent on the PD-L1 pathway and CD8 + T cells. Our findings highlight the importance of targeting USP8, which can sensitize PD-L1-targeted pancreatic cancer to immunotherapy and might represent a novel therapeutic strategy to treat patients with pancreatic tumors in the future.

The Impact of Molecular Subtyping on Pathological Staging of Pancreatic Cancer

BACKGROUND

The long-term outcomes following surgical resection for pancreatic ductal adenocarcinoma (PDAC) remains poor, with only 20% of patients surviving 5 years after pancreatectomy. Patient selection for surgery remains suboptimal largely due to the absence of consideration of aggressive tumor biology.

OBJECTIVE

The aim of this study was to evaluate traditional staging criteria for PDAC in the setting of molecular subtypes.

METHODS

Clinicopathological data were obtained for 5 independent cohorts of consecutive unselected patients, totaling n = 1298, including n = 442 that underwent molecular subtyping. The main outcome measure was disease-specific survival following surgical resection for PDAC stratified according to the American Joint Commission for Cancer (TNM) staging criteria, margin status, and molecular subtype.

RESULTS

TNM staging criteria and margin status confers prognostic value only in tumors with classical pancreatic subtype. Patients with tumors that are of squamous subtype, have a poor outcome irrespective of favorable traditional pathological staging [hazard ratio (HR) 1.54, 95% confidence interval (CI) 1.04-2.28, P = 0.032]. Margin status has no impact on survival in the squamous subtype (16.0 vs 12.1 months, P = 0.374). There were no differences in molecular subtype or gene expression of tumors with positive resection margin status.

CONCLUSIONS

Aggressive tumor biology as measured by molecular subtype predicts poor outcome following pancreatectomy for PDAC and should be utilized to inform patient selection for surgery.

Macrophages direct cancer cells through a LOXL2-mediated metastatic cascade in pancreatic ductal adenocarcinoma

OBJECTIVE

The lysyl oxidase-like protein 2 (LOXL2) contributes to tumour progression and metastasis in different tumour entities, but its role in pancreatic ductal adenocarcinoma (PDAC) has not been evaluated in immunocompetent in vivo PDAC models.

DESIGN

Towards this end, we used PDAC patient data sets, patient-derived xenograft in vivo and in vitro models, and four conditional genetically-engineered mouse models (GEMMS) to dissect the role of LOXL2 in PDAC. For GEMM-based studies, K-Ras +/LSL-G12D;Trp53 LSL-R172H;Pdx1-Cre mice (KPC) and the K-Ras +/LSL-G12D;Pdx1-Cre mice (KC) were crossed with Loxl2 allele floxed mice (Loxl2Exon2 fl/fl) or conditional Loxl2 overexpressing mice (R26Loxl2 KI/KI) to generate KPCL2KO or KCL2KO and KPCL2KI or KCL2KI mice, which were used to study overall survival; tumour incidence, burden and differentiation; metastases; epithelial to mesenchymal transition (EMT); stemness and extracellular collagen matrix (ECM) organisation.

RESULTS

Using these PDAC mouse models, we show that while Loxl2 ablation had little effect on primary tumour development and growth, its loss significantly decreased metastasis and increased overall survival. We attribute this effect to non-cell autonomous factors, primarily ECM remodelling. Loxl2 overexpression, on the other hand, promoted primary and metastatic tumour growth and decreased overall survival, which could be linked to increased EMT and stemness. We also identified tumour-associated macrophage-secreted oncostatin M (OSM) as an inducer of LOXL2 expression, and show that targeting macrophages in vivo affects Osm and Loxl2 expression and collagen fibre alignment.

CONCLUSION

Taken together, our findings establish novel pathophysiological roles and functions for LOXL2 in PDAC, which could be potentially exploited to treat metastatic disease.

Proteogenomic landscape of human pancreatic ductal adenocarcinoma in an Asian population reveals tumor cell-enriched and immune-rich subtypes

We report a proteogenomic analysis of pancreatic ductal adenocarcinoma (PDAC). Mutation-phosphorylation correlations identified signaling pathways associated with somatic mutations in significantly mutated genes. Messenger RNA-protein abundance correlations revealed potential prognostic biomarkers correlated with patient survival. Integrated clustering of mRNA, protein and phosphorylation data identified six PDAC subtypes. Cellular pathways represented by mRNA and protein signatures, defining the subtypes and compositions of cell types in the subtypes, characterized them as classical progenitor (TS1), squamous (TS2-4), immunogenic progenitor (IS1) and exocrine-like (IS2) subtypes. Compared with the mRNA data, protein and phosphorylation data further classified the squamous subtypes into activated stroma-enriched (TS2), invasive (TS3) and invasive-proliferative (TS4) squamous subtypes. Orthotopic mouse PDAC models revealed a higher number of pro-tumorigenic immune cells in TS4, inhibiting T cell proliferation. Our proteogenomic analysis provides significantly mutated genes/biomarkers, cellular pathways and cell types as potential therapeutic targets to improve stratification of patients with PDAC.

An ultra-small bispecific protein augments tumor penetration and treatment for pancreatic cancer

PURPOSE

The once highly anticipated antibody-based pathway-targeted therapies have not achieved promising outcomes for deadly pancreatic ductal adenocarcinoma (PDAC), mainly due to drugs' low intrinsic anticancer activity and poor penetration across the dense physiological barrier. This study aims to develop an ultra-small-sized, EGFR/VEGF bispecific therapeutic protein to largely penetrate deep tumor tissue and effectively inhibit PDAC tumor growth in vivo.

METHODS

The bispecific protein, Bi-fp50, was constructed by a typical synthetic biology method and labeled with fluorescent dyes for in vitro and in vivo imaging. Physicochemical properties, protein dual-binding affinity, and specificity of the Bi-fp50 were evaluated in several PDAC cell lines. In vitro quantitatively and qualitatively anticancer activity of Bi-fp50 was assessed by live/dead staining, MTT assay, and flow cytometry. In vivo pharmacokinetic and biodistribution were evaluated using blood biopsy samples and near-infrared fluorescence imaging. In vivo real-time tracking of Bi-fp50 in the local tumor was conducted by fibered confocal fluorescence microscopy. The subcutaneous PDAC tumor model was used to assess the in vivo antitumor effect of Bi-fp50.

RESULTS

Bi-fp50 with an ultra-small size of 50 kDa (5 ~ 6 nm) showed an excellent binding ability to VEGF and EGFR simultaneously and had enhanced, accumulated binding capability for Bxpc3 PDAC cells compared with anti-VEGF scFv and anti-EGFR scFv alone. Additionally, bi-fp50 significantly inhibited the proliferation and growth of Bxpc3 and Aspc1 PDAC cells even under a relatively low concentration (0.3 µM). It showed synergistically enhanced therapeutic effects relative to two individual scFv and Bi-fp50x control in vitro. The half-life of blood clearance of Bi-fp50 was 4.33 ± 0.23 h. After intravenous injection, Bi-fp50 gradually penetrated the deep tumor, widely distributed throughout the whole tissue, and primarily enriched in the tumor with nearly twice the accumulation than scFv2 in the orthotopic PDAC tumor model. Furthermore, the Bi-fp50 protein could induce broad apoptosis in the whole tumor and significantly inhibited tumor growth 3 weeks after injection in vivo without other noticeable side effects.

CONCLUSION

The proof-of-concept study demonstrated that the ultra-small-sized, bispecific protein Bi-fp50 could be a potential tumor suppressor and an efficient, safe theranostic tool for treating PDAC tumors.

Compressed phenotypic screens for complex multicellular models and high-content assays

High-throughput phenotypic screens leveraging biochemical perturbations, high-content readouts, and complex multicellular models could advance therapeutic discovery yet remain constrained by limitations of scale. To address this, we establish a method for compressing screens by pooling perturbations followed by computational deconvolution. Conducting controlled benchmarks with a highly bioactive small molecule library and a high-content imaging readout, we demonstrate increased efficiency for compressed experimental designs compared to conventional approaches. To prove generalizability, we apply compressed screening to examine transcriptional responses of patient-derived pancreatic cancer organoids to a library of tumor-microenvironment (TME)-nominated recombinant protein ligands. Using single-cell RNA-seq as a readout, we uncover reproducible phenotypic shifts induced by ligands that correlate with clinical features in larger datasets and are distinct from reference signatures available in public databases. In sum, our approach enables phenotypic screens that interrogate complex multicellular models with rich phenotypic readouts to advance translatable drug discovery as well as basic biology.

EPS8L3 promotes pancreatic cancer proliferation and metastasis by activating GSK3B

Background

We intended to investigate the role and regulatory mechanism of EPS8L3 in increase the development of pancreatic cancer (PC).

Methods

In order to analyze the relationship between EPS8L3 level and clinicopathological indicators of PC patients, qRT-PCR was used to detect the expression of EPS8L3 in tumor specimens of 40 PC patients. EPS8L3 knockdown models were then constructed in PC cell lines. Furthermore, the effect of EPS8L3 on PC cell function was analyzed by CCK-8 and Transwell assay. Dual luciferase reporter gene assay and recovery assay were used to further investigate the underlying mechanism.

Results

qRT-PCR results indicated that EPS8L3 was highly expressed in PC tissues compared with adjacent ones. At the same time, the incidence of distant metastasis was higher in PC patients with high EPS8L3 level. In vitro analysis such as CCK-8 and Transwell experimentations indicated that knockdown of EPS8L3 markedly inhibited the proliferative and metastatic ability. Bio-informatics together with luciferase report assay proposing that EPS8L3 can target GSK3B. Western Blot results revealed that knockdown of EPS8L3 markedly reduced the GSK3B expression in PC cells, and there was a positively associated between the two in PC cells. In addition, the recovery experimentation proved that EPS8L3 and GSK3B have a mutual regulation effect. Overexpression of GSK3B can reversal the prohibitive effect of EPS8L3 knockdown on the malignant development of PC cells, thereby jointly regulating the occurrence and development of PC.

Conclusions

EPS8L3 promotes the development of PC by regulating GSK3B, suggesting that EPS8L3 can be used as a biomarker for early diagnosis and treatment of PC.

The Relationship between the Expression of GATA4 and GATA6 with the Clinical Characteristics and Prognosis of Resectable Pancreatic Adenocarcinoma

GATA4 and GATA6 are transcription factors involved in the differentiation and development of PDAC. GATA6 expression is related to the classic molecular subtype, while its absence is related to the basal-like molecular subtype. The aim was to determine the clinical utility of IHC determination of GATA4 and GATA6 in a series of patients with resected PDAC. GATA4 and GATA6 expression was studied by IHC in TMA samples of normal tissue, PanIN, tumor tissue and lymph node metastases from a series of 89 patients with resected PDAC. Its relationship with clinicopathologic variables and the outcome was investigated. Seventy-two (81%) tumors were GATA6+ and 37 (42%) were GATA4+. While GATA4 expression was reduced during tumor progression, GATA6 expression remained highly conserved, except in lymph node metastases. All patients with early stages and well-differentiated tumors were GATA6+. The absence of GATA4 expression was related to smoking. Patients with GATA4+ or GATA6+ tumors had significantly lower Ca 19.9 levels. The expression of GATA4 and GATA6 was related to DFS, being more favorable in the GATA4+/GATA6+ group. The determination of the expression of GATA4 and GATA6 by IHC is feasible and provides complementary clinical and prognostic information that can help improve the stratification of patients with PDAC.

Role of epigenetics in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, associated with poor survival outcomes. Lack of early diagnosis, resistance to conventional therapeutic treatments (including immunotherapy) and recurrence are some of the major hurdles in PDAC and contribute to its poor survival rate. While the risk of genetic predisposition to cancers is widely acknowledged and understood, recent advances in whole-genome and next-generation sequencing techniques have led to the acknowledgment of the role played by epigenetics, especially in PDAC. Epigenetic changes are heritable genetic modifications that influence gene expression without altering the DNA sequence. Epigenetic mechanisms (e.g., DNA methylation, post-translational modification of histone complexes and ncRNA) that result in reversible changes in gene expression are increasingly understood to be responsible for tumor initiation, development and even escape from immune surveillance. Our review seeks to highlight the various components of the epigenetic machinery that are known to be implicated in PDAC initiation and development and the feasibility of targeting these components to identify novel pharmacological strategies that could potentially lead to breakthroughs in PDAC treatment.

Current Status of the Diagnosis of Early-Stage Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) can be treated with surgery, chemotherapy, and radiotherapy. Despite medical progress in each field in recent years, it is still insufficient for managing PDAC, and at present, the only curative treatment is surgery. A typical pancreatic cancer is relatively easy to diagnose with imaging. However, it is often not recommended for surgical treatment at the time of diagnosis due to metastatic spread beyond the pancreas. Even if it is operable, it often recurs during postoperative follow-up. In the case of PDAC with a diameter of 10 mm or less, the 5-year survival rate is as good as 80% or more, and the best index for curative treatment is tumor size. The early detection of pancreatic cancer with a diameter of less than 10 mm or carcinoma in situ is critical. Here, we provide an overview of the current status of diagnostic imaging features and genetic tests for the accurate diagnosis of early-stage PDAC.

Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma

Objective

To develop and validate an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma (PDAC).

Background

"Radiomics" enables the investigation of huge amounts of radiological features in parallel by extracting high-throughput imaging data. MRI provides better tissue contrast with no ionizing radiation for PDAC.

Methods

There were 78 PDAC patients enrolled in this study. In total, there were 386 radiomics features extracted from MRI scan, which were screened by the least absolute shrinkage and selection operator algorithm to develop a risk score. Cox multivariate regression analysis was applied to develop the radiomics-based nomogram. The performance was assessed by discrimination and calibration.

Results

The radiomics-based risk-score was significantly associated with PDAC overall survival (OS) (P < 0.05). With respect to survival prediction, integrating the risk score, clinical data and TNM information into the nomogram exhibited better performance than the TNM staging system, radiomics model and clinical model. In addition, the nomogram showed fine discrimination and calibration.

Conclusions

The radiomics nomogram incorporating the radiomics data, clinical data and TNM information exhibited precise survival prediction for PDAC, which may help accelerate personalized precision treatment.

Clinical trial registration

clinicaltrials.gov, identifier NCT05313854.

Anti‑silencing function 1B promotes the progression of pancreatic cancer by activating c‑Myc

The present study aimed to explore the role of histone chaperone anti‑silencing function 1B (ASF1B) in pancreatic cancer and the underlying mechanism. The biological function of ASF1B was investigated in pancreatic cancer cell lines (PANC‑1 and SW1990) and a mouse xenograft model. Chromatin immunoprecipitation was used to detect the effect of ASF1B on the transcriptional activity of c‑Myc. ASF1B was highly expressed in pancreatic adenocarcinoma (PAAD) samples from The Cancer Genome Atlas. ASF1B expression was positively associated with poor survival rates in patients with PAAD. Silencing of ASF1B in PANC‑1 and SW1990 cells inhibited cell proliferation, migration and invasion, and induced apoptosis. Mechanistically, ASF1B increased H3K56 acetylation (H3K56ac) in a CREB‑binding protein (CBP)‑dependent manner. ASF1B promoted H3K56ac at the c‑Myc promoter and increased c‑Myc expression. In PANC‑1 and SW1990 cells, the CBP inhibitor curcumin and the c‑Myc inhibitor 10058‑F4 reversed the promoting effects of ASF1B on cell proliferation, migration and invasion. In the mouse xenograft model, ASF1B silencing inhibited tumor growth, and was associated with low H3K56ac and c‑Myc expression. ASF1B promoted pancreatic cancer progression by activating c‑Myc via CBP‑mediated H3K56ac.

Replication stress identifies novel molecular classification associated with treatment outcomes in pancreatic cancer

BACKGROUND

Replication stress is a prominent hallmark of tumor cells, which is crucial for maintaining genomic integrity. However, it remains poorly understood whether replication stress can serve as a surrogate biomarker to indicate prognosis and treatment response of pancreatic cancer.

METHODS

Transcriptomic and clinical data were obtained from The Cancer Genome Atlas and literature. An integrated signature of 18 replication-stress associated genes (termed as REST18) was established using the cox proportional hazards regression analysis. Tumors were sorted into REST18-low and REST18-high groups. Survival analysis, gene set enrichment analysis and composition of immune cells were compared between these tumors.

RESULTS

Patients with REST18-high tumors showed worse prognoses than those with REST18-low tumors in the TCGA database and the finding is validated in an independent cohort of pancreatic cancer. Comparison of REST18 model and other molecular classifications showed that REST18-high tumors are positively correlated to basal-like or squamous phenotypes, which have higher metastasis potential. DNA repair pathway is enriched in the REST18-high tumors. Analysis of tumor immune microenvironment found that REST18-high tumors are characterized with "immune-cold" features. Univariate and multivariate analysis show that REST18 is an independent risk factor for overall survival and predicts outcomes of chemotherapy in pancreatic cancer.

CONCLUSION

REST18 is a novel biomarker to indicate prognosis and treatment response of chemotherapy in pancreatic cancer.

hTERT Gene Modification Using CRISPR-dCas9-dnmt3a System as a Therapeutic Approach Against Glioma

Background

Abnormal DNA methylation patterns have been reported in various diseases, including different cancers. CRISPR/Cas9 is a low-cost and highly effective gene editing tool that has lately revolutionized biotechnology. Studies have shown that the CRISPR/Cas9 system can effectively target and correct methylation.

Objectives

Telomerase plays a survival role for cancer cells. It is encoded by the hTERT gene. The effectiveness of CRISPR/Cas9 in targeting hTERT to treat glioma cancer cells was assessed in this study.

Methods

EF1a-hsaCas9-U6-gRNA vector carrying sgRNA and Cas9 hybrids were used to transfect U87 glioma cells. Four and eight μg/mL polybrene concentrations were investigated to improve transfection efficiency. The expression level of hTERT that has undergone metabisulfite modification was assessed using real-time PCR. Flow cytometry and Western blotting were also used to determine whether telomerase was present in the cells. High-resolution melting analysis (HRM) was used to examine the hTERT promoter's methylation. Finally, flow cytometry was used to measure the apoptotic rate of transfected U87 cells.

Results

The findings demonstrated that gRNA significantly boosted transfection effectiveness. Significant variations were seen in the expression of hTERT in U87 cells at 4 μg/mL polybrene and 80 μg/mL transfection compared to transfection without gRNA and basal cells. Flow cytometry showed a decrease in hTERT levels in transfected cells. Furthermore, transfection with gRNA increased U87 cell apoptosis compared to transfection without gRNA.

Conclusions

It appears that the designed CRISPR/Cas9 system can reduce hTERT expression and telomerase activity and thus inhibit glioma cell growth.

Clustering analysis and prognostic model based on PI3K/AKT-related genes in pancreatic cancer

Background

Pancreatic cancer is one of most aggressive malignancies with a dismal prognosis. Activation of PI3K/AKT signaling is instrumental in pancreatic cancer tumorigenesis. The aims of this study were to identify the molecular clustering, prognostic value, relationship with tumor immunity and targeting of PI3K/AKT-related genes (PARGs) in pancreatic cancer using bioinformatics.

Methods

The GSEA website was searched for PARGs, and pancreatic cancer-related mRNA data and clinical profiles were obtained through TCGA downloads. Prognosis-related genes were identified by univariate Cox regression analysis, and samples were further clustered by unsupervised methods to identify significant differences in survival, clinical information and immune infiltration between categories. Next, a prognostic model was constructed using Lasso regression analysis. The model was well validated by univariate and multivariate Cox regression analyses, Kaplan-Meier survival analysis and ROC curves, and correlations between risk scores and patient pathological characteristics were identified. Finally, GSEA, drug prediction and immune checkpoint protein analyses were performed.

Results

Pancreatic cancers were divided into Cluster 1 (C1) and Cluster 2 (C1) according to PARG mRNA expression. C1 exhibited longer overall survival (OS) and higher immune scores and CTLA4 expression, whereas C2 exhibited more abundant PD-L1. A 6-PARG-based prognostic model was constructed to divide pancreatic cancer patients into a high-risk score (HRS) group and a low-risk score (LRS) group, where the HRS group exhibited worse OS. The risk score was defined as an independent predictor of OS. The HRS group was significantly associated with pancreatic cancer metastasis, aggregation and immune score. Furthermore, the HRS group exhibited immunosuppression and was sensitive to radiotherapy and guitarbine chemotherapy. Multidrug sensitivity prediction analysis indicated that the HRS group may be sensitive to PI3K/AKT signaling inhibitors (PIK-93, GSK2126458, CAL-101 and rapamycin) and ATP concentration regulators (Thapsigargin). In addition, we confirmed the oncogenic effect of protein phosphatase 2 regulatory subunit B'' subunit alpha (PPP2R3A) in pancreatic cancer in vitro and in vivo.

Conclusions

PARGs predict prognosis, tumor immune profile, radiotherapy and chemotherapy drug sensitivity and are potential predictive markers for pancreatic cancer treatment that can help clinicians make decisions and personalize treatment.

AP1/Fra1 confers resistance to MAPK cascade inhibition in pancreatic cancer

Targeting KRAS downstream signaling remains an important therapeutic approach in pancreatic cancer. We used primary pancreatic ductal epithelial cells and mouse models allowing the conditional expression of oncogenic Kras^G12D, to investigate KRAS signaling integrators. We observed that the AP1 family member FRA1 is tightly linked to the KRAS signal and expressed in pre-malignant lesions and the basal-like subtype of pancreatic cancer. However, genetic-loss-of-function experiments revealed that FRA1 is dispensable for Kras^G12D-induced pancreatic cancer development in mice. Using FRA1 gain- and loss-of-function models in an unbiased drug screen, we observed that FRA1 is a modulator of the responsiveness of pancreatic cancer to inhibitors of the RAF-MEK-ERK cascade. Mechanistically, context-dependent FRA1-associated adaptive rewiring of oncogenic ERK signaling was observed and correlated with sensitivity to inhibitors of canonical KRAS signaling. Furthermore, pharmacological-induced degradation of FRA1 synergizes with MEK inhibitors. Our studies establish FRA1 as a part of the molecular machinery controlling sensitivity to MAPK cascade inhibition allowing the development of mechanism-based therapies.

A Novel Molecular Signature of Cancer-Associated Fibroblasts Predicts Prognosis and Immunotherapy Response in Pancreatic Cancer

Cancer-associated fibroblasts (CAFs), a prominent population of stromal cells, play a crucial role in tumor progression, prognosis, and treatment response. However, the relationship among CAF-based molecular signatures, clinical outcomes, and tumor microenvironment infiltration remains largely elusive in pancreatic cancer (PC). Here, we collected multicenter PC data and performed integrated analysis to investigate the role of CAF-related genes (CRGs) in PC. Firstly, we demonstrated that α-SMA⁺ CAFs were the most prominent stromal components and correlated with the poor survival rates of PC patients in our tissue microarrays. Then, we discriminated two diverse molecular subtypes (CAF clusters A and B) and revealed the significant differences in the tumor immune microenvironment (TME), four reported CAF subpopulations, clinical characteristics, and prognosis in PC samples. Furthermore, we analyzed their association with the immunotherapy response of PC patients. Lastly, a CRG score was constructed to predict prognosis, immunotherapy responses, and chemosensitivity in pancreatic cancer patients. In summary, these findings provide insights into further research targeting CAFs and their TME, and they pave a new road for the prognosis evaluation and individualized treatment of PC patients.

Interplay of four types of RNA modification writers revealed distinct tumor microenvironment and biological characteristics in pancreatic cancer

Background

Pancreatic cancer (PC) is one of the most lethal malignancies and carries a dismal mortality and morbidity. Four types of RNA modification (namely m6A, m1A, APA and A-to-I) could be catalyzed by distinct enzymatic compounds ("writers"), mediating numerous epigenetic events in carcinogenesis and immunomodulation. We aim to investigate the interplay mechanism of these writers in immunogenomic features and molecular biological characteristics in PC.

Methods

We first accessed the specific expression pattern and transcriptional variation of 26 RNA modification writers in The Cancer Genome Atlas (TCGA) dataset. Unsupervised consensus clustering was performed to divide patients into two RNA modification clusters. Then, based on the differentially expressed genes (DEGs) among two clusters, RNA modification score (WM_Score) model was established to determine RNA modification-based subtypes and was validated in International Cancer Genome Consortium (ICGC) dataset. What's more, we manifested the unique status of WM_Score in transcriptional and post-transcriptional regulation, molecular biological characteristics, targeted therapies and immunogenomic patterns.

Results

We documented the tight-knit correlations between transcriptional expression and variation of RNA modification writers. We classified patients into two distinct RNA modification patterns (WM_Score_high and _low), The WM_Score_high subgroup was correlated with worse prognosis, Th2/Th17 cell polarization and oncogenic pathways (e.g. EMT, TGF-β, and mTORC1 signaling pathways), whereas the WM_Score_low subgroup associated with favorable survival rate and Th1 cell trend. WM_Score model also proved robust predictive power in interpreting transcriptional and post-transcriptional events. Additionally, the potential targeted compounds with related pathways for the WM_Score model were further identified.

Conclusions

Our research unfolds a novel horizon on the interplay network of four RNA modifications in PC. This WM_Score model demonstrated powerful predictive capacity in epigenetic, immunological and biological landscape, providing a theoretical basis for future clinical judgments of PC.

HDAC5 Loss Enhances Phospholipid-Derived Arachidonic Acid Generation and Confers Sensitivity to cPLA2 Inhibition in Pancreatic Cancer

HDAC5 is a class IIa histone deacetylase member that is downregulated in multiple solid tumors, including pancreatic cancer, and loss of HDAC5 is associated with unfavorable prognosis. In this study, assessment of The Cancer Genome Atlas pancreatic adenocarcinoma dataset revealed that expression of HDAC5 correlates negatively with arachidonic acid (AA) metabolism, which has been implicated in inflammatory responses and cancer progression. Nontargeted metabolomics analysis revealed that HDAC5 knockdown resulted in a significant increase in AA and its downstream metabolites, such as eicosanoids and prostaglandins. HDAC5 negatively regulated the expression of the gene encoding calcium-dependent phospholipase A2 (cPLA2), the key enzyme in the production of AA from phospholipids. Mechanistically, HDAC5 repressed cPLA2 expression via deacetylation of GATA1. HDAC5 knockdown in cancer cells enhanced sensitivity to genetic or pharmacologic inhibition of cPLA2 in vitro and in vivo. Fatty acid supplementation in the diet reversed the sensitivity of HDAC5-deficient tumors to cPLA2 inhibition. These data indicate that HDAC5 loss in pancreatic cancer results in the hyperacetylation of GATA1, enabling the upregulation of cPLA2, which contributes to overproduction of AA. Dietary management plus cPLA2-targeted therapy could serve as a viable strategy for treating HDAC5-deficient pancreatic cancer patients.

SIGNIFICANCE

The HDAC5-GATA1-cPLA2-AA signaling axis regulates sensitivity to fat restriction plus cPLA2 inhibition in pancreatic ductal adenocarcinoma, proposing dietary management as a feasible strategy for treating a subset of patients with pancreatic cancer.

The novel subclusters based on cancer-associated fibroblast for pancreatic adenocarcinoma

Introduction

Pancreatic adenocarcinoma (PAAD) is a fatal disease characterized by promoting connective tissue proliferation in the stroma. Activated cancer-associated fibroblasts (CAFs) play a key role in fibrogenesis in PAAD. CAF-based tumor typing of PAAD has not been explored.

Methods

We extracted single-cell sequence transcriptomic data from GSE154778 and CRA001160 datasets from Gene Expression Omnibus or Tumor Immune Single-cell Hub to collect CAFs in PAAD. On the basis of Seurat packages and new algorithms in machine learning, CAF-related subtypes and their top genes for PAAD were analyzed and visualized. We used CellChat package to perform cell-cell communication analysis. In addition, we carried out functional enrichment analysis based on clusterProfiler package. Finally, we explored the prognostic and immunotherapeutic value of these CAF-related subtypes for PAAD.

Results

CAFs were divided into five new subclusters (CAF-C0, CAF-C1, CAF-C2, CAF-C3, and CAF-C4) based on their marker genes. The five CAF subclusters exhibited distinct signaling patterns, immune status, metabolism features, and enrichment pathways and validated in the pan-cancer datasets. In addition, we found that both CAF-C2 and CAF-C4 subgroups were negatively correlated with prognosis. With their top genes of each subclusters, the sub-CAF2 had significantly relations to immunotherapy response in the patients with pan-cancer and immunotherapy.

Discussion

We explored the heterogeneity of five subclusters based on CAF in signaling patterns, immune status, metabolism features, enrichment pathways, and prognosis for PAAD.