Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer

Prostate cancer-derived extracellular vesicles metabolic biomarkers: Emerging roles for diagnosis and prognosis

Prostate cancer (PCa) is a global health concern, ranking as the most common cancer among men in Western countries. Traditional diagnostic methods are invasive with adverse effects on patients. Due to the heterogeneous nature of PCa and their multifocality, tissue biopsies often yield false-negative results. To address these challenges, researchers are exploring innovative approaches, particularly in the realms of proteomics and metabolomics, to identify more reliable biomarkers and improve PCa diagnosis. Liquid biopsy (LB) has emerged as a promising non-invasive strategy for PCa early detection, biopsy selection, active surveillance for low-risk cases, and post-treatment and progression monitoring. Extracellular vesicles (EVs) are lipid-bilayer nanovesicles released by all cell types and play an important role in intercellular communication. EVs have garnered attention as a valuable biomarker resource in LB for PCa-specific biomarkers, enhancing diagnosis, prognostication, and treatment guidance. Metabolomics provides insight into the body's metabolic response to both internal and external stimuli, offering quantitative measurements of biochemical alterations. It excels at detecting non-genetic influences, aiding in the discovery of more accurate cancer biomarkers for early detection and disease progression monitoring. This review delves into the potential of EVs as a resource for LB in PCa across various clinical applications. It also explores cancer-related metabolic biomarkers, both within and outside EVs in PCa, and summarises previous metabolomic findings in PCa diagnosis and risk assessment. Finally, the article addresses the challenges and future directions in the evolving field of EV-based metabolomic analysis, offering a comprehensive overview of its potential in advancing PCa management.

Transcriptomic analysis reveals molecular characterization and immune landscape of PANoptosis-related genes in atherosclerosis

BACKGROUND

Atherosclerosis is a chronic inflammatory disease characterized by abnormal lipid deposition in the arteries. Programmed cell death is involved in the inflammatory response of atherosclerosis, but PANoptosis, as a new form of programmed cell death, is still unclear in atherosclerosis. This study explored the key PANoptosis-related genes involved in atherosclerosis and their potential mechanisms through bioinformatics analysis.

METHODS

We evaluated differentially expressed genes (DEGs) and immune infiltration landscape in atherosclerosis using microarray datasets and bioinformatics analysis. By intersecting PANoptosis-related genes from the GeneCards database with DEGs, we obtained a set of PANoptosis-related genes in atherosclerosis (PANoDEGs). Functional enrichment analysis of PANoDEGs was performed and protein-protein interaction (PPI) network of PANoDEGs was established. The machine learning algorithms were used to identify the key PANoDEGs closely linked to atherosclerosis. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic potency of key PANoDEGs. CIBERSORT was used to analyze the immune infiltration patterns in atherosclerosis, and the Spearman method was used to study the relationship between key PANoDEGs and immune infiltration abundance. The single gene enrichment analysis of key PANoDEGs was investigated by GSEA. The transcription factors and target miRNAs of key PANoDEGs were predicted by Cytoscape and online database, respectively. The expression of key PANoDEGs was validated through animal and cell experiments.

RESULTS

PANoDEGs in atherosclerosis were significantly enriched in apoptotic process, pyroptosis, necroptosis, cytosolic DNA-sensing pathway, NOD-like receptor signaling pathway, lipid and atherosclerosis. Four key PANoDEGs (ZBP1, SNHG6, DNM1L, and AIM2) were found to be closely related to atherosclerosis. The ROC curve analysis demonstrated that the key PANoDEGs had a strong diagnostic potential in distinguishing atherosclerotic samples from control samples. Immune cell infiltration analysis revealed that the proportion of initial B cells, plasma cells, CD4 memory resting T cells, and M1 macrophages was significantly higher in atherosclerotic tissues compared to normal tissues. Spearman analysis showed that key PANoDEGs showed strong correlations with immune cells such as T cells, macrophages, plasma cells, and mast cells. The regulatory networks of the four key PANoDEGs were established. The expression of key PANoDEGs was verified in further cell and animal experiments.

CONCLUSIONS

This study evaluated the expression changes of PANoptosis-related genes in atherosclerosis, providing a reference direction for the study of PANoptosis in atherosclerosis and offering potential new avenues for further understanding the pathogenesis and treatment strategies of atherosclerosis.

ZFHX3 methylation in peripheral blood monocytes as a potential biomarker for pancreatic cancer detection

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is the digestive malignancy with poor prognosis, and there is still a lack of effective diagnostic biomarkers.

OBJECTIVE

We aimed to explore the diagnostic efficiency of DNA methylation in peripheral blood monocytes (PBMCs) in PDAC.

METHODS

850K BeadChips were used to detect genome-wide methylation of PBMCs. For the selected sites, MethylTarget assays was used for further verification. The support vector machine was used to establish the combined panel.

RESULTS

A total of 167 PDAC patients and 113 healthy controls were included in this study and were divided into three sets. In the discovery set, we found 4625 differentially methylated positions (DMPs) between cancer group and healthy controls. ZFHX3 (0.16 ± 0.04 vs. 0.18 ± 0.04, P = 0.001), cg01904886 (0.84 ± 0.05 vs. 0.81 ± 0.04, P = 0.02) and NUMBL (0.96 ± 0.005 vs. 0.957 ± 0.005, P = 0.04) were found to be significantly different in training set. The locus with more significant differences, namely ZFHX3, was used for further validation and to establish a combined diagnostic panel with CA19-9. In the validation set, the ROC curve indicated that the AUC value of ZFHX3 was 0.75. The AUC value of the combined model (AUC = 0.92) was higher than that of CA19-9 alone (AUC = 0.88). In patients with normal CA19-9 levels, the ZFHX3 methylation biomarker still maintained good diagnostic efficacy (AUC = 0.71).

CONCLUSION

Our study preliminarily suggests that ZFHX3 methylation combined with CA19-9 can improve the detection rate of PDAC. Especially in patients with normal CA19-9, ZFHX3 methylation can maintain stable diagnostic efficacy. The diagnostic value of ZFHX3 methylation still needs to be prospectively validated.

Liquid biomarkers in prostate cancer: recent advancements and future directions

PURPOSE OF REVIEW

Traditional diagnostic approaches of prostate cancer like PSA are limited by high false-positive rates and insufficient capture of tumour heterogeneity, necessitating the development of more precise tools. This review examines the latest advancements in liquid biomarkers for prostate cancer, focusing on their potential to refine diagnostic accuracy and monitor disease progression.

RECENT FINDINGS

Liquid biomarkers have gained prominence because of their minimally invasive nature and ability to reflect the molecular characteristics of prostate cancer. Circulating tumour cells provide insight into tumour cell dissemination and are indicative of aggressive disease phenotypes, with single-cell analyses revealing genomic instability and treatment resistance. Circulating tumour DNA offers real-time tumour genomic information, aiding in treatment decision-making in advanced prostate cancer, where it has been associated with clinical progression. MicroRNAs act as oncogenes or tumour suppressors and exhibit diagnostic and prognostic potential; however, their clinical utility is constrained by the lack of consistent validation. Extracellular vesicles contain tumour-derived biomolecules, with specific proteins demonstrating prognostic relevance. Applications of these markers to urinary testing have been demonstrated.

SUMMARY

Liquid biomarkers show potential in refining prostate cancer management. Future research should aim to integrate these biomarkers into a cohesive framework in line with precision medicine principles.

In-depth immune profiling of peripheral blood mononuclear cells in patients with pancreatic ductal adenocarcinoma reveals discriminative immune subpopulations

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis with a 5-year survival of less than 10%. More knowledge of the immune response developed in patients with PDAC is pivotal to develop better combination immune therapies to improve clinical outcome. In this study, we used mass cytometry time-of-flight to undertake an in-depth characterization of PBMCs from patients with PDAC and examine the differences with healthy controls and patients with benign diseases of the biliary system or pancreas. Peripheral blood mononuclear cells from patients with PDAC or benign disease are characterized by the increase of pro-inflammatory cells, as CD86+ classical monocytes and memory T cells expressing CCR6+ and CXCR3+, associated with T helper 1 (Th1) and Th17 immune responses, respectively. However, PBMCs from patients with PDAC present also an increase of CD39+ regulatory T cells and CCR4+CCR6-CXCR3- memory T cells, suggesting Th2 and regulatory responses. Concluding, our results show PDAC develops a multifaceted immunity, where a proinflammatory component is accompanied by regulatory responses, which could inhibit potential antitumor mechanisms.

Innate and adaptive immune-directed tumour microenvironment in pancreatic ductal adenocarcinoma

One of the most deadly and aggressive cancers in the world, pancreatic ductal adenocarcinoma (PDAC), typically manifests at an advanced stage. PDAC is becoming more common, and by the year 2030, it is expected to overtake lung cancer as the second greatest cause of cancer-related death. The poor prognosis can be attributed to a number of factors, including difficulties in early identification, a poor probability of curative radical resection, limited response to chemotherapy and radiotherapy, and its immunotherapy resistance. Furthermore, an extensive desmoplastic stroma that surrounds PDAC forms a mechanical barrier that prevents vascularization and promotes poor immune cell penetration. Phenotypic heterogeneity, drug resistance, and immunosuppressive tumor microenvironment are the main causes of PDAC aggressiveness. There is a complex and dynamic interaction between tumor cells in PDAC with stromal cells within the tumour immune microenvironment. The immune suppressive microenvironment that promotes PDAC aggressiveness is contributed by a range of cellular and humoral factors, which itself are modulated by the cancer. In this review, we describe the role of innate and adaptive immune cells, complex tumor microenvironment in PDAC, humoral factors, innate immune-mediated therapeutic advances, and recent clinical trials in PDAC.

A Comprehensive Review of the Potential Role of Liquid Biopsy as a Diagnostic, Prognostic, and Predictive Biomarker in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the most lethal malignant diseases, with a mortality rate being close to incidence. Due to its heterogeneity and plasticity, as well as the lack of distinct symptoms in the early phases, it is very often diagnosed at an advanced stage, resulting in poor prognosis. Traditional tissue biopsies remain the gold standard for making a diagnosis, but have an obvious disadvantage in their inapplicability for frequent sampling. Blood-based biopsies represent a non-invasive method which potentially offers easy and repeated sampling, leading to the early detection and real-time monitoring of the disease and hopefully an accurate prognosis. Given the urgent need for a reliable biomarker that can estimate a patient's condition and response to an assigned treatment, blood-based biopsies are emerging as a potential new tool for improving patients' survival and surveillance. In this article, we discuss the current advances and challenges in using liquid biopsies for pancreatic cancer, focusing on circulating tumour DNA (ctDNA), extracellular vesicles (EVs), and circulating tumour cells (CTCs), and compare the performance and reliability of different biomarkers and combinations of biomarkers.

Prostate cancer-derived small extracellular vesicle proteins: the hope in diagnosis, prognosis, and therapeutics

Current diagnostic tools for prostate cancer (PCa) diagnosis and risk stratification are insufficient. The hidden onset and poor efficacy of traditional therapies against metastatic PCa make this disease a heavy burden in global men's health. Prostate cancer-derived extracellular vesicles (PCDEVs) have garnered attention in recent years due to their important role in communications in tumor microenvironment. Recent advancements have demonstrated PCDEVs proteins play an important role in PCa invasion, progression, metastasis, therapeutic resistance, and immune escape. In this review, we briefly discuss the applications of sEV proteins in PCa diagnosis and prognosis in liquid biopsy, focus on the roles of the PCa-derived small EVs (sEVs) proteins in tumor microenvironment associated with cancer progression, and explore the therapeutic potential of sEV proteins applied for future metastatic PCa therapy.

A novel pyroptosis-associated lncRNA LINC01133 promotes pancreatic adenocarcinoma development via miR-30b-5p/SIRT1 axis

PURPOSE

Pancreatic adenocarcinoma (PAAD) remains a highly aggressive gastrointestinal malignancy with a dismal prognosis. Pyroptosis has a key role in tumor development. Long noncoding RNAs (lncRNAs) are involved in tumorigenesis and pyroptosis regulation. However, the prognostic potential and function of pyroptosis-related lncRNAs (PRLs) in PAAD remain unclear. We aimed to identify PRLs with promising predictive value for PAAD prognosis and investigate the mechanism by which PRLs affect pyroptosis and PAAD development.

METHODS

Key genes that regulate pyroptosis were determined from previous studies, and PRLs were identified from lncRNAs shown to be co-expressed in The Cancer Genome Atlas. Cox analysis and the least absolute shrinkage and selection operator (LASSO) regression model was used to establish a prognostic PRL signature. The clinical significance and functional mechanisms of LINC01133 were explored in vitro and in vivo.

RESULTS

A seven-lncRNA signature was established and the high-risk subgroup exhibited a shorter survival time. With lower immune infiltration abundance, poor immune function, and higher tumor mutational burden (TMB), the high-risk subgroup reflected a more immunosuppressive status with a greater scope for benefiting from immunotherapy. After LINC01133 knockdown, PAAD cells showed lower viability and higher pyroptosis-related gene expression. LINC01133 functioned as a competing endogenous RNA to sequester miR-30b-5p from sponging SIRT1 mRNA to inhibit PAAD pyroptosis.

CONCLUSION

With significant prognostic value, our PRL signature are involved in the biological processes of PAAD cells and associated with the immune environment. LINC01133 suppresses pyroptosis to promote PAAD development and could serve as a potential target for PAAD treatment.

The multifunction of HSP70 in cancer: Guardian or traitor to the survival of tumor cells and the next potential therapeutic target

Heat shock protein 70 (HSP70) is a highly conserved protein composed of nucleotide-binding domains (NBD) and C-terminal substrate binding domain (SBD) that can function as a "molecular chaperone". HSP70 was discovered to directly or indirectly play a regulatory role in both internal and external apoptosis pathways. Studies have shown that HSP70 can not only promote tumor progression, enhance tumor cell resistance and inhibit anticancer effects but also induce an anticancer response by activating immune cells. In addition, chemotherapy, radiotherapy and immunotherapy for cancer may be affected by HSP70, which has shown promising potential as an anticancer drug. In this review, we summarized the molecular structure and mechanism of HSP70 and discussed the dual effects of HSP70 on tumor cells and the possibility and potential methods of using HSP70 as a target to treat cancer.

Blood-Based Biomarkers in the Diagnosis and Risk Stratification of Pancreatic Cysts

The use of blood-based biomarkers for the assessment of pancreatic cystic lesions is a rapidly growing field with incredible potential. CA 19-9 remains the only blood-based marker in common use, while many novel biomarkers are in early stages of development and validation. We highlight current work in the fields of proteomics, metabolomics, cell-free DNA/circulating tumor DNA, extracellular vesicles, and microRNA among others, as well as barriers to development and future directions in the work of blood-based biomarkers for pancreatic cystic lesions.

Intratumour microbiome of pancreatic cancer

Pancreatic cancer is a high mortality malignancy with almost equal mortality and morbidity rates. Both normal and tumour tissues of the pancreas were previously considered sterile. In recent years, with the development of technologies for high-throughput sequencing, a variety of studies have revealed that pancreatic cancer tissues contain small amounts of bacteria and fungi. The intratumour microbiome is being revealed as an influential contributor to carcinogenesis. The intratumour microbiome has been identified as a crucial factor for pancreatic cancer progression, diagnosis, and treatment, chemotherapy resistance, and immune response. A better understanding of the biology of the intratumour microbiome of pancreatic cancer contributes to the establishment of better early cancer screening and treatment strategies. This review focuses on the possible origins of the intratumour microbiome in pancreatic cancer, the intratumour localization, the interaction with the tumour microenvironment, and strategies for improving the outcome of pancreatic cancer treatment. Thus, this review offers new perspectives for improving the prognosis of pancreatic cancer.

Identification of PRTN3 as a novel biomarker for the diagnosis of early gastric cance

Gastric cancer (GC) remains one of the most common types of cancer worldwide and has a high mortality rate. However, tools for the early detection of gastric cancer are still lacking. Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic assays were conducted to identify and quantify the differentially expressed proteins (DEPs) in the gastric mucosal tissues of GC patients at different stages. Bioinformatics analysis was used to identify the pathways enriched among the DEPs and candidate marker proteins. The expression levels and distribution of candidate proteins were confirmed by parallel reaction monitoring (PRM) analysis. In this study, by using the iTRAQ quantitative proteomic strategy, we identified 727 and 502 DEPs that were upregulated in EGC vs. PGC and EGC vs. NGC, respectively. These DEPs were mainly involved in the innate immune response and RNA binding. PRTN3 was identified as a marker of early gastric cancer by Gene Ontology enrichment analysis. Furthermore, the PRM assay confirmed the significant overexpression of PRTN3 in EGC gastric mucosa compared to PGC and NGC mucosa. Our data demonstrated that PRTN3 in the gastric mucosa could be used as a novel biomarker to identify patients with early gastric cancer via endoscopy. SIGNIFICANCE: Gastric cancer remains one of the most common types of cancer worldwide and has a high mortality rate. Patients with progressive gastric cancer and gastroesophageal junction cancer have a poor prognosis, with a 5-year relative survival rate of 6%. Therefore, early detection and diagnosis of gastric cancer is a key step toward improving the survival rate. The present study identified PRTN3 as a marker of early gastric cancer by an iTRAQ quantitative proteomic strategy. The PRM assay confirmed the significant overexpression of PRTN3 in EGC gastric mucosa compared to PGC and NGC mucosa. This study discovered that PRTN3 in the gastric mucosa could be used as a novel biomarker to identify patients with early gastric cancer via endoscopy.

Recent advances in the use of liquid biopsy to fight central nervous system tumors

Brain tumors are considered one of the deadliest types of cancer, being challenging to treat, especially due to the blood-brain barrier, which has been linked to treatment resistance. The genomic classification of brain tumors has been helping in the diagnostic precision, however tumor heterogeneity in addition to the difficulties to obtain tissue biopsies, represent a challenge. The biopsies are usually obtained either via neurosurgical removal or stereotactic tissue biopsy, which can be risky procedures for the patient. To overcome these challenges, liquid biopsy has become an interesting option by constituting a safer procedure than conventional biopsy, which may offer valuable cellular and molecular information representative of the whole organism. Besides, it is relatively easy to obtain such as in the case of blood (venipuncture) and urine sample collection. In the present comprehensive review, we discuss the newest information regarding liquid biopsy in the brain tumors' field, methods employed, the different sources of bio-fluids and their potential circulating targets.

Multiplexed analysis of EV reveals specific biomarker composition with diagnostic impact

Exosomes and extracellular vesicles (EV) are increasingly being explored as circulating biomarkers, but their heterogenous composition will likely mandate the development of multiplexed EV technologies. Iteratively multiplexed analyses of near single EVs have been challenging to implement beyond a few colors during spectral sensing. Here we developed a multiplexed analysis of EV technique (MASEV) to interrogate thousands of individual EVs during 5 cycles of multi-channel fluorescence staining for 15 EV biomarkers. Contrary to the common belief, we show that: several markers proposed to be ubiquitous are less prevalent than believed; multiple biomarkers concur in single vesicles but only in small fractions; affinity purification can lead to loss of rare EV subtypes; and deep profiling allows detailed analysis of EV, potentially improving the diagnostic content. These findings establish the potential of MASEV for uncovering fundamental EV biology and heterogeneity and increasing diagnostic specificity.

Recent progress in aptamer-based microfluidics for the detection of circulating tumor cells and extracellular vesicles

Liquid biopsy is a technology that exhibits potential to detect cancer early, monitor therapies, and predict cancer prognosis due to its unique characteristics, including noninvasive sampling and real-time analysis. Circulating tumor cells (CTCs) and extracellular vesicles (EVs) are two important components of circulating targets, carrying substantial disease-related molecular information and playing a key role in liquid biopsy. Aptamers are single-stranded oligonucleotides with superior affinity and specificity, and they can bind to targets by folding into unique tertiary structures. Aptamer-based microfluidic platforms offer new ways to enhance the purity and capture efficiency of CTCs and EVs by combining the advantages of microfluidic chips as isolation platforms and aptamers as recognition tools. In this review, we first briefly introduce some new strategies for aptamer discovery based on traditional and aptamer-based microfluidic approaches. Then, we subsequently summarize the progress of aptamer-based microfluidics for CTC and EV detection. Finally, we offer an outlook on the future directional challenges of aptamer-based microfluidics for circulating targets in clinical applications.

Tumor-Derived Biomarkers in Liquid Biopsy of Glioblastoma

There is a pressing clinical need for minimally invasive liquid biopsies to supplement imaging in the treatment of glioblastoma. Diagnostic imaging is often difficult to interpret and the medical community is divided on distinguishing among complete response, partial response, stable disease, and progressive disease. A minimally invasive liquid biopsy would supplement imaging and clinical findings and has the capacity to be helpful in several ways: 1) diagnosis, 2) selection of patients for specific treatments, 3) tracking of treatment response, and 4) prognostic value. The liquid biome is the combination of biological fluids including blood, urine, and cerebrospinal fluid that contain small amounts of tumor cells, DNA/RNA coding material, peptides, and metabolites. Within the liquid biome, 2 broad categories of biomarkers can exist: tumor-derived, which can be directly traced to the tumor, and tumor-associated, which can be traced back to the response of the body to disease. Although tumor-associated biomarkers are promising liquid biopsy candidates, recent advances in biomarker enrichment and detection have allowed concentration on a new class of biomarker: tumor-derived biomarkers. This review focuses on making the distinction between the 2 biomarker categories and highlights promising new direction.

Serum biomarker-based early detection of pancreatic ductal adenocarcinomas with ensemble learning

BACKGROUND

Earlier detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes, as it is mostly detected at advanced stages which are associated with poor survival. Developing non-invasive blood tests for early detection would be an important breakthrough.

METHODS

The primary objective of the work presented here is to use a dataset that is prospectively collected, to quantify a set of cancer-associated proteins and construct multi-marker models with the capacity to predict PDAC years before diagnosis. The data used is part of a nested case-control study within the UK Collaborative Trial of Ovarian Cancer Screening and is comprised of 218 samples, collected from a total of 143 post-menopausal women who were diagnosed with pancreatic cancer within 70 months after sample collection, and 249 matched non-cancer controls. We develop a stacked ensemble modelling technique to achieve robustness in predictions and, therefore, improve performance in newly collected datasets.

RESULTS

Here we show that with ensemble learning we can predict PDAC status with an AUC of 0.91 (95% CI 0.75-1.0), sensitivity of 92% (95% CI 0.54-1.0) at 90% specificity, up to 1 year prior to diagnosis, and at an AUC of 0.85 (95% CI 0.74-0.93) up to 2 years prior to diagnosis (sensitivity of 61%, 95% CI 0.17-0.83, at 90% specificity).

CONCLUSIONS

The ensemble modelling strategy explored here outperforms considerably biomarker combinations cited in the literature. Further developments in the selection of classifiers balancing performance and heterogeneity should further enhance the predictive capacity of the method.

Nucleic acid and nanomaterial-assisted signal-amplified strategies in fluorescent analysis of circulating tumor cells and small extracellular vesicles

As two main types of liquid biopsy markers, both circulating tumor cells (CTCs) and small extracellular vesicles (sEVs) play important roles in the diagnosis and prognosis of cancers. CTCs are malignant cells that detach from the original tumor tissue and enter the circulation of body fluids. sEVs are nanoscale vesicles secreted by normal cells or pathological cells. However, CTCs and sEVs in body fluids are scarce, leading to great difficulties in the accurate analysis of related diseases. For the sensitive detection of CTCs and sEVs in body fluids, various types of nucleic acid and nanomaterial-assisted signal amplification strategies have been developed. In this review, we summarize the recent advances in fluorescent detection of CTCs and sEVs in liquid biopsy based on nucleic acid and nanomaterial-assisted signal amplification strategies. We also discuss their advantages, challenges, and future prospects.

Preclinical models derived from endoscopic ultrasound-guided tissue acquisition for individualized treatment of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with poor outcomes. Although the management strategies have evolved in recent years, the PDAC 5-year survival rate remains at only 9%; it may become the second leading cause of cancer death in the USA by 2030. Only 15-20% of PDAC patients are eligible to undergo surgery; diagnostic biopsies and individualized treatment present a more significant challenge for the remaining group. Endoscopic ultrasound-guided tissue acquisition (EUS-TA) has been widely used in the diagnosis of pancreatic masses. With the advancement of this sampling technique, adequate specimens can be obtained from all patients with PDAC in both early and late clinical stages. Recent data suggest that the specimens obtained from EUS-TA might be used to establish viable preclinical models, which conserve the genetic mutation and preserve the heterogeneity of the original tumors. Additionally, any drug sensitivity evident in the EUS-TA-derived preclinical models might predict the clinical response, thus guiding the prospective therapeutic selection. As we move toward the era of precision medicine, this review provides an update on the role of EUS-TA as a method for obtaining genetic material used in preclinical models that can assess and stratify individuals according to their individual cancer biology.

Multi-biomarker panel prediction model for diagnosis of pancreatic cancer

BACKGROUND/PURPOSE

The current study aimed to develop a prediction model using a multi-marker panel as a diagnostic screening tool for pancreatic ductal adenocarcinoma.

METHODS

Multi-center cohort of 1991 blood samples were collected from January 2011 to September 2019, of which 609 were normal, 145 were other cancer (colorectal, thyroid, and breast cancer), 314 were pancreatic benign disease, and 923 were pancreatic ductal adenocarcinoma. The automated multi-biomarker Enzyme-Linked Immunosorbent Assay kit was developed using three potential biomarkers: LRG1, TTR, and CA 19-9. Using a logistic regression model on a training data set, the predicted values for pancreatic ductal adenocarcinoma were obtained, and the result was classification into one of the three risk groups: low, intermediate, and high. The five covariates used to create the model were sex, age, and three biomarkers.

RESULTS

Participants were categorized into four groups as normal (n = 609), other cancer (n = 145), pancreatic benign disease (n = 314), and pancreatic ductal adenocarcinoma (n = 923). The normal, other cancer, and pancreatic benign disease groups were clubbed into the non-pancreatic ductal adenocarcinoma group (n = 1068). The positive and negative predictive value, sensitivity, and specificity were 94.12, 90.40, 93.81, and 90.86, respectively.

CONCLUSIONS

This study demonstrates a significant diagnostic performance of the multi-marker panel in distinguishing pancreatic ductal adenocarcinoma from normal and benign pancreatic disease states, as well as patients with other cancers.

Epithelial to Mesenchymal Transition as Mechanism of Progression of Pancreatic Cancer: From Mice to Men

Owed to its aggressive yet subtle nature, pancreatic cancer remains unnoticed till an advanced stage so that in most cases the diagnosis is made when the cancer has already spread to other organs with deadly efficiency. The progression from primary tumor to metastasis involves an intricate cascade of events comprising the pleiotropic process of epithelial to mesenchymal transition (EMT) facilitating cancer spread. The elucidation of this pivotal phenotypic change in cancer cell morphology, initially heretic, moved from basic studies dissecting the progression of pancreatic cancer in animal models to move towards human disease, although no clinical translation of the concept emerged yet. Despite this transition, a full-blown mesenchymal phenotype may not be accomplished; rather, the plasticity of the program and its dependency on heterotopic signals implies a series of fluctuating modifications of cancer cells encompassing mesenchymal and epithelial features. Despite the evidence supporting the activation of EMT and MET during cancer progression, our understanding of the relationship between tumor microenvironment and EMT is not yet mature for a clinical application. In this review, we attempt to resume the knowledge on EMT and pancreatic cancer, aiming to include the EMT among the hallmarks of cancer that could potentially modify our clinical thinking with the purpose of filling the gap between the results pursued in basic research by animal models and those achieved in translational research by surrogate biomarkers, as well as their application for prognostic and predictive purposes.

Insulin receptor tyrosine kinase substrate (IRTKS) promotes the tumorigenesis of pancreatic cancer via PI3K/AKT signaling

Pancreatic cancer (PC) is a common type of tumor, which ranks for the seventh leading cause of cancer death worldwide. Insulin receptor tyrosine kinase substrate (IRTKS) plays an important regulatory role in cell proliferation, motility and survival. In this study, we explore the effect of IRTKS on the occurrence and development of PC. The expression and clinical features of IRTKS were predicted in database, PC cell lines and samples. IRTKS overexpressed and knocked down PC cell lines were established by lentivirus. CCK-8 assay, scratch migration assay and Transwell assay were used to analyze IRTKS oncogenic functions in cell lines. Bioinformatic enrichment analysis were conducted to explore the biological functions IRTKS involved in PC and Western Bolt assay was performed to reveal the downstream signaling molecules. It is detected that IRTKS is highly expressed in PC (P < 0.05), and overexpression of IRTKS predicted worse overall survival (OS, P = 0.018). The proliferation, migration and invasion ability were significantly enhanced in IRTKS overexpressed cells and inhibited in IRTKS knocked down cells (P < 0.05). Bioinformatic enrichment analysis based on GSE46583 dataset showed that IRTKS was significantly involved in PI3K/AKT pathway. Further investigation revealed that overexpression of IRTKS upregulated the ratio of p-PI3K/PI3K and p-AKT/AKT in vitro, while silencing of IRTKS presented opposite results, and PI3K inhibitor LY294002 treatment induced the phenotypic alteration of cell lines (P < 0.05). In conclusion, IRTKS plays an important role in PC tumorigenesis via PI3K/AKT pathway phosphorylated activation, and has a potential clinical application value in prognosis for PC.

A Cross-Sectional and Longitudinal Analysis of Pre-Diagnostic Blood Plasma Biomarkers for Early Detection of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a major cause of cancer death that typically presents at an advanced stage. No reliable markers for early detection presently exist. The prominent tumor stroma represents a source of circulating biomarkers for use together with cancer cell-derived biomarkers for earlier PDAC diagnosis. CA19-9 and CEA (cancer cell-derived biomarkers), together with endostatin and collagen IV (stroma-derived) were examined alone, or together, by multivariable modelling, using pre-diagnostic plasma samples (n = 259 samples) from the Northern Sweden Health and Disease Study biobank. Serial samples were available for a subgroup of future patients. Marker efficacy for future PDAC case prediction (n = 154 future cases) was examined by both cross-sectional (ROC analysis) and longitudinal analyses. CA19-9 performed well at, and within, six months to diagnosis and multivariable modelling was not superior to CA19-9 alone in cross-sectional analysis. Within six months to diagnosis, CA19-9 (AUC = 0.92) outperformed the multivariable model (AUC = 0.81) at a cross-sectional level. At diagnosis, CA19-9 (AUC = 0.995) and the model (AUC = 0.977) performed similarly. Longitudinal analysis revealed increases in CA19-9 up to two years to diagnosis which indicates a window of opportunity for early detection of PDAC.

Cancer-derived small extracellular vesicles: emerging biomarkers and therapies for pancreatic ductal adenocarcinoma diagnosis/prognosis and treatment

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal cancers worldwide with high mortality, which is mainly due to the lack of reliable biomarkers for PDAC diagnosis/prognosis in the early stages and effective therapeutic strategies for the treatment. Cancer-derived small extracellular vesicles (sEVs), which carry various messages and signal biomolecules (e.g. RNAs, DNAs, proteins, lipids, and glycans) to constitute the key features (e.g. genetic and phenotypic status) of cancer cells, are regarded as highly competitive non-invasive biomarkers for PDAC diagnosis/prognosis. Additionally, new insights on the biogenesis and molecular functions of cancer-derived sEVs pave the way for novel therapeutic strategies based on cancer-derived sEVs for PDAC treatment such as inhibition of the formation or secretion of cancer-derived sEVs, using cancer-derived sEVs as drug carriers and for immunotherapy. This review provides a comprehensive overview of the most recent scientific and clinical research on the discovery and involvement of key molecules in cancer-derived sEVs for PDAC diagnosis/prognosis and strategies using cancer-derived sEVs for PDAC treatment. The current limitations and emerging trends toward clinical application of cancer-derived sEVs in PDAC diagnosis/prognosis and treatment have also been discussed.

Serum Carboxypeptidase Activity and Genotype-Stratified CA19-9 to Detect Early-Stage Pancreatic Cancer

BACKGROUND AND AIMS

Serum diagnostic markers of early-stage pancreatic ductal adenocarcinoma (PDAC) are needed, especially for stage I disease. As tumors grow and cause pancreatic atrophy, markers derived from pancreatic parenchyma such as serum carboxypeptidase A (CPA) activity lose diagnostic performance. We evaluated, with CA19-9, serum CPA as a marker of early pancreatic cancer.

METHODS

Serum CPA activity levels were measured in 345 controls undergoing pancreatic surveillance, divided into 2 sets, set 1 being used to establish a reference range. Variants within the CPA1 locus were sought for their association with pancreatic CPA1 expression to determine if such variants associated with serum CPA levels. A total of 190 patients with resectable PDAC were evaluated.

RESULTS

Among controls, those having 1 or more minor alleles of CPA1 variants rs6955723 or rs2284682 had significantly higher serum CPA levels than did those without (P = .001). None of the PDAC cases with pancreatic atrophy had an elevated CPA. Among 122 PDAC cases without atrophy, defining serum CPA diagnostic cutoffs by a subject's CPA1 variants yielded a diagnostic sensitivity of 18% at 99% specificity (95% confidence interval [CI], 11.7-26) (vs 11.1% sensitivity using a uniform diagnostic cutoff); combining CPA with variant-stratified CA19-9 yielded a sensitivity of 68.0% (95% CI, 59.0-76.2) vs 63.1% (95% CI, 53.9- 71.7) for CA19-9 alone; and among stage I PDAC cases, diagnostic sensitivity was 51.9% (95% CI, 31.9-71.3) vs 37.0% (95% CI, 19.4-57.6) for CA19-9 alone. In the validation control set, the variant-stratified diagnostic cutoff yielded a specificity of 98.2%.

CONCLUSION

Serum CPA activity has diagnostic utility before the emergence of pancreatic atrophy as a marker of localized PDAC, including stage I disease.

Identification of novel early pancreatic cancer biomarkers KIF5B and SFRP2 from “first contact” interactions in the tumor microenvironment

Background

Pancreatic cancer is one of the most difficult cancers to detect early and most patients die from complications arising due to distant organ metastases. The lack of bona fide early biomarkers is one of the primary reasons for late diagnosis of pancreatic cancer. It is a multifactorial disease and warrants a novel approach to identify early biomarkers.

Methods

In order to characterize the proteome, Extracellular vesicles (EVs) isolated from different in vitro conditions mimicking tumor-microenvironment interactions between pancreatic cancer epithelial and stromal cells were analyzed using high throughput mass spectrometry. The biological activity of the secreted EVome was analyzed by investigating changes in distant organ metastases and associated early changes in the microbiome. Candidate biomarkers (KIF5B, SFRP2, LOXL2, and MMP3) were selected and validated on a mouse-human hybrid Tissue Microarray (TMA) that was specifically generated for this study. Additionally, a human TMA was used to analyze the expression of KIF5B and SFRP2 in progressive stages of pancreatic cancer.

Results

The EVome of co-cultured epithelial and stromal cells is different from individual cells with distinct protein compositions. EVs secreted from stromal and cancer cells cultures could not induce significant changes in Pre-Metastatic Niche (PMN) modulation, which was assessed by changes in the distant organ metastases. However, they did induce significant changes in the early microbiome, as indicated by differences in α and β-diversities. KIF5B and SFRP2 show promise for early detection and investigation in progressive pancreatic cancer. These markers are expressed in all stages of pancreatic cancer such as low grade PanINs, advanced cancer, and in liver and soft tissue metastases.

Conclusions

Proteomic characterization of EVs derived from mimicking conditions of epithelial and stromal cells in the tumor-microenvironment resulted in the identification of several proteins, some for the first time in EVs. These secreted EVs cannot induce changes in distant organ metastases in in vivo models of EV education, but modulate changes in the early murine microbiome. Among all the proteins that were analyzed (MMP3, KIF5B, SFRP2, and LOXL2), KIF5B and SFRP2 show promise as bona fide early pancreatic cancer biomarkers expressed in progressive stages of pancreatic cancer.

Pancreatic Cancer: Pathogenesis, Screening, Diagnosis, and Treatment

Pancreatic ductal adenocarcinoma (PDAC) is a clinically challenging cancer, due to both its late stage at diagnosis and its resistance to chemotherapy. However, recent advances in our understanding of the biology of PDAC have revealed new opportunities for early detection and targeted therapy of PDAC. In this review, we discuss the pathogenesis of PDAC, including molecular alterations in tumor cells, cellular alterations in the tumor microenvironment, and population-level risk factors. We review the current status of surveillance and early detection of PDAC, including populations at high risk and screening approaches. We outline the diagnostic approach to PDAC and highlight key treatment considerations, including how therapeutic approaches change with disease stage and targetable subtypes of PDAC. Recent years have seen significant improvements in our approaches to detect and treat PDAC, but large-scale, coordinated efforts will be needed to maximize the clinical impact for patients and improve overall survival.

Defective Fe Metal-Organic Frameworks Enhance Metabolic Profiling for High-Accuracy Diagnosis of Human Cancers

Cancers heavily threaten human life; therefore, a high-accuracy diagnosis is vital to protect human beings from the suffering of cancers. While biopsies and imaging methods are widely used as current technologies for cancer diagnosis, a new detection platform by metabolic analysis is expected due to the significant advantages of fast, simple, and cost-effectiveness with high body tolerance. However, the signal of molecule biomarkers is too weak to acquire high-accuracy diagnosis. Herein, precisely engineered metal-organic frameworks for laser desorption/ionization mass spectrometry, allowing favorable charge transfer within the molecule-substrate interface and mitigated thermal dissipation by adjusting the phonon scattering with metal nodes, are developed. Consequently, a surprising signal enhancement of ≈10 000-fold is achieved, resulting in diagnosis of three major cancers (liver/lung/kidney cancer) with area-under-the-curve of 0.908-0.964 and accuracy of 83.2%-90.6%, which promises a universal detection tool for large-scale clinical diagnosis of human cancers.

Is There a Benefit to Adjuvant Chemotherapy in Resected, Early Stage Pancreatic Ductal Adenocarcinoma?

BACKGROUND

The role of systemic therapy for Stage IA pancreatic ductal adenocarcinoma (PDAC) is unclear. The aim of our study was to evaluate the impact of adjuvant chemotherapy (AC) on survival in patients with early stage disease.

METHODS

The National Cancer Database was queried from 2006 to 2017 for resected pT1N0M0 (Stage 1A) PDAC. Exclusion criteria included neoadjuvant therapy, radiation, or those who suffered a 90-day mortality.

RESULTS

Of the 1526 patients included in the study, 42.2% received AC and 57.8% underwent surgery alone. Patients who received AC were younger, had fewer comorbidities, and were more likely to have private insurance, compared with those treated with surgery alone. Patients who received AC had longer median overall survival (OS) compared with those who underwent surgery alone (105.7 months vs 72.0 months, p < 0.01). Subset analyses based on individual "good" prognostic features (size ≤ 1.0 cm, lymphovascular invasion negative, well/moderately differentiated, margin negative resection) demonstrated improved OS with AC. Following propensity score matching based on key clinicopathologic features, AC remained associated with improved median OS (83.7 months vs 59.8 months, p < 0.01). However, in the cohort with body/tail tumors (101.2 months vs 95.0 months, p = 0.19) and those with all "good" prognostic features (95.9 months vs 90.6 months, p = 0.15), AC was not associated with improved survival.

CONCLUSIONS

In resected, Stage IA PDAC, AC is associated with improved overall survival in the vast majority of patients; however, in select cohorts the role of AC is unclear. Further study is needed to tailor treatment to individual patients with PDAC.

Detection of Early-Stage Pancreatic Ductal Adenocarcinoma From Blood Samples: Results of a Multiplex Biomarker Signature Validation Study

INTRODUCTION

The IMMray PanCan-d test combines an 8-plex biomarker signature with CA19-9 in a proprietary algorithm to detect pancreatic ductal adenocarcinoma (PDAC) in serum samples. This study aimed to validate the clinical performance of the IMMray PanCan-d test and to better understand test performance in Lewis-null (le/le) individuals who cannot express CA19-9.

METHODS

Serum samples from 586 individuals were analyzed with the IMMray PanCan-d biomarker signature and CA19-9 assay, including 167 PDAC samples, 203 individuals at high risk of familial/hereditary PDAC, and 216 healthy controls. Samples were collected at 11 sites in the United States and Europe. The study was performed by Immunovia, Inc (Marlborough, MA), and sample identity was blinded throughout the study. Test results were automatically generated using validated custom software with a locked algorithm and predefined decision value cutoffs for sample classification.

RESULTS

The IMMray PanCan-d test distinguished PDAC stages I and II (n = 56) vs high-risk individuals with 98% specificity and 85% sensitivity and distinguished PDAC stages I-IV vs high-risk individuals with 98% specificity and 87% sensitivity. We identified samples with a CA19-9 value of 2.5 U/mL or less as probable Lewis-null (le/le) individuals. Excluding these 55 samples from the analysis increased the IMMray PanCan-d test sensitivity to 92% for PDAC stages I-IV (n = 157) vs controls (n = 379) while maintaining specificity at 99%; test sensitivity for PDAC stages I and II increased from 85% to 89%.

DISCUSSION

These results demonstrate the IMMray PanCan-d blood test can detect PDAC with high specificity (99%) and sensitivity (92%).

High-performance Collective Biomarker from Liquid Biopsy for Diagnosis of Pancreatic Cancer Based on Mass Spectrometry and Machine Learning

Background: Most pancreatic cancers are found at progressive stages when they cannot be surgically removed. Therefore, a highly accurate early detection method is urgently needed.

Methods: This study analyzed serum from Japanese patients who suffered from pancreatic ductal adenocarcinoma (PDAC) and aimed to establish a PDAC-diagnostic system with metabolites in serum. Two groups of metabolites, primary metabolites (PM) and phospholipids (PL), were analyzed using liquid chromatography/electrospray ionization mass spectrometry. A support vector machine was employed to establish a machine learning-based diagnostic algorithm.

Results: Integrating PM and PL databases improved cancer diagnostic accuracy and the area under the receiver operating characteristic curve. It was more effective than the algorithm based on either PM or PL database, or single metabolites as a biomarker. Subsequently, 36 statistically significant metabolites were fed into the algorithm as a collective biomarker, which improved results by accomplishing 97.4% and was further validated by additional serum. Interestingly, specific clusters of metabolites from patients with preoperative neoadjuvant chemotherapy (NAC) showed different patterns from those without NAC and were somewhat comparable to those of the control.

Conclusion: We propose an efficient screening system for PDAC with high accuracy by liquid biopsy and potential biomarkers useful for assessing NAC performance.

Pancreatic Cancer Surveillance and Novel Strategies for Screening

Individuals with a genetic susceptibility to pancreatic ductal adenocarcinoma (PDAC) may benefit from surveillance to increase the likelihood of early detection. Currently, candidates for surveillance are identified based on genetic test results and family history of PDAC, and surveillance is accomplished through imaging of the pancreas (endoscopic ultrasound or MRI). Novel methods that incorporate personalized risk, biomarkers, and radiomics are being investigated in an attempt to improve identification of at-risk individuals and to increase detection of precursor and early-stage lesions.

Diagnostic biomarkers for pancreatic cancer: An update

Pancreatic ductal adenocarcinoma accounts for the primary type of pancreatic cancer (PC) with a 5-year survival rate of only about 10% in the United States. Early diagnosis will improve chances for curative treatment. To date, a broadly used serum marker for PC diagnosis is carbohydrate antigen 19-9, which is the only approved biomarker currently by the United States Food and Drug Administration. However, it has low specificity; therefore, development of novel biomarkers is urgently needed. Clinical trials are ongoing to evaluate candidate biomarkers for PC diagnosis, and the use of a multi-biomarker panel with current PC diagnostic biomarkers appears promising.

Circulating EVs long RNA-based subtyping and deconvolution enable prediction of immunogenic signatures and clinical outcome for PDAC

Identification of clinically applicable molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) is crucial to improving patient outcomes. However, the traditional tissue-dependent transcriptional subtyping strategies are invasive and not amenable to routine clinical evaluation. In this study, we developed a circulating extracellular vesicle (cEV) long RNA (exLR)-based PDAC subtyping method and provided exLR-derived signatures for predicting immunogenic features and clinical outcomes in PDAC. We enrolled 426 individuals, among which 227 PDACs served as an internal cohort, 118 PDACs from two other medical centers served as an independent validation cohort, and 81 healthy individuals served as the control. ExLR sequencing was performed on all plasma samples. We found that PDAC could be categorized into three subtypes based on plasma exLR profiles. Each subpopulation showed its own molecular features and was associated with patient clinical prognosis. The immunocyte-derived cEV fractions were altered among PDAC subtypes and interconnected with tumor-infiltrating lymphocytes in cancerous tissue. Additionally, we found a significant concordance of immunoregulators between tissue and blood EVs, and we harvested potential PDAC therapeutic targets. Most importantly, we constructed a nine exLR-derived, tissue-applicable signature for prognostic assessment of PDAC. The circulating exLR-based features may offer an attractive platform for personalized treatment and predicting patient outcomes in multiple types of cancer.

Successively triggered Rod-shaped protocells for enhanced tumor Chemo-Photothermal therapy

Abundant existence of extracellular matrix biological hydrogels in solid tumors precludes most therapeutics to arrive at intracellular target sites, which is probably one of the threatened reasons of pancreatic ductal adenocarcinoma (PDAC) for public health. In this study, we designed a rod-shaped protocell nanoparticle loading with doxorubicin hydrochloride (Dox) and indocyanine green (ICG), denoted as Dox/ICG-RsPNs, for enhanced chemo-photothermal PDAC treatment. The enhanced therapeutic efficacy was achieved by successively enhancing penetration across matrix hydrogels, endocytosis, increasing local temperature under laser irradiation and hyperthermia-triggered Dox release to nucleus. We found that RsPNs with rod shape could easily penetrate across matrix hydrogel, exerting excellent tumor accumulation. Then RsPNs was internalized effectively by BxPC-3 cells via a caveolin-mediated endocytosis pathway. In addition, ICG endowed the Dox/ICG-RsPNs with photothermal effect and the photothermal conversion efficiency was calculated for 16.2%. Under irradiation, a great number of Dox transported to the nucleus via hyperthermia-induced release. Furthermore, we found that the relative tumor volume of Dox/ICG-RsPNs was merely 1.37 under irradiation at the end of pharmacodynamic studies, which was significantly lower than that of other groups. These findings will provide a promise on the rational design of drug delivery system for effective chemo-photothermal combination therapy to treat PDAC.

A Serum Marker for Early Pancreatic Cancer with a Possible Link to Diabetes

BACKGROUND

Pancreatic cancer (PC) has a grim prognosis, and an early diagnostic biomarker has been highly desired. The molecular link between diabetes and PC has not been well-established.

METHODS

Bioinformatics screening was performed for a serum PC marker. Experiments in cell lines (5 PC and 1 normal cell lines), mouse models, and human tissue staining (37 PC and 10 normal cases) were performed to test asprosin production from PC. Asprosin's diagnostic performance was tested with serums from multi-center cohorts (347 PC, 209 normal, and 55 additional diabetic subjects) and evaluated according to PC status, stages, and diabetic status, which was compared with that of CA19-9.

RESULTS

Asprosin, a diabetes-related hormone, was found from the bioinformatics screening, and its production from PC was confirmed. Serum asprosin levels from multi-center cohorts yielded an age-adjusted diagnostic AUC of 0.987 (95% confidence interval [CI] = 0.961 to 0.997), superior to that of CA19-9 (AUC = 0.876, 95% CI = 0.847 to 0.905), and a cut-off of 7.18 ng/mL, at which the validation set exhibited a sensitivity of 0.957 and a specificity of 0.924. Importantly, the performance was maintained in early-stage and non-metastatic PC, consistent with the tissue staining. A slightly lower performance against additional diabetic patients (n = 55) was restored by combining asprosin and CA19-9 (AUC = 0.985, 95% CI = 0.975 to 0.995).

CONCLUSION

Asprosin is presented as an early-stage PC serum marker that may provide clues for PC-induced diabetes. Larger prospective clinical studies are warranted to solidify its utility.

Methylation-based Cell-free DNA Signature for Early Detection of Pancreatic Cancer

OBJECTIVES

The potential of DNA methylation alterations in early pancreatic cancer (PC) detection among pancreatic tissue cell-free DNA seems promising. This study investigates the diagnostic capacity of the 4-gene methylation biomarker panel, which included ADAMTS1, BNC1, LRFN5, and PXDN genes, in a case-control study.

METHODS

A genome-wide pharmacoepigenetic approach identified ADAMTS1, BNC1, LRFN5, and PXDN genes as putative targets. Tissue samples including stage I-IV PC (n = 44), pancreatic intraepithelial neoplasia (n = 15), intraductal papillary mucinous neoplasms (n = 24), and normal pancreas (n = 8), and cell-free DNA, which was acquired through methylation on beads technology from PC (n = 22) and control patients (n = 10), were included. The 2-∆ct was the outcome of interest and underwent receiver operating characteristic analysis to determine the diagnostic accuracy of the panel.

RESULTS

Receiver operating characteristic analysis revealed an area under the curve of 0.93 among ADAMTS1, 0.76 among BNC1, 0.75 among PXDN, and 0.69 among LRFN5 gene. The combination gene methylation panel (ADAMTS1, BNC1, LRFN5, and PXDN) had an area under the curve of 0.94, with a sensitivity of 100% and specificity of 90%.

CONCLUSIONS

This methylation-based biomarker panel had promising accuracy for PC detection and warranted further validation in prospective PC surveillance trials.

Metastatic pancreatic cancer: Mechanisms and detection (Review)

Pancreatic cancer (PC) is a lethal malignancy. Its prevalence rate remains low but continues to grow each year. Among all stages of PC, metastatic PC is defined as late-stage (stage IV) PC and has an even higher fatality rate. Patients with PC do not have any specific clinical manifestations. Most cases are inoperable at the time-point of diagnosis. Prognosis is also poor even with curative-intent surgery. Complications during surgery, postoperative pancreatic fistula and recurrence with metastatic foci make the management of metastatic PC difficult. While extensive efforts were made to improve survival outcomes, further elucidation of the molecular mechanisms of metastasis poses a formidable challenge. The present review provided an overview of the mechanisms of metastatic PC, summarizing currently known signaling pathways (e.g. epithelial-mesenchymal transition, NF-κB and KRAS), imaging that may be utilized for early detection and biomarkers (e.g. carbohydrate antigen 19-9, prostate cancer-associated transcript-1, F-box/LRR-repeat protein 7 and tumor stroma), giving insight into promising therapeutic targets.

Blood small extracellular vesicles derived miRNAs to differentiate pancreatic ductal adenocarcinoma from chronic pancreatitis

BACKGROUND

The differential diagnosis of pancreatic ductal adenocarcinoma (PDAC) from chronic pancreatitis (CP) is clinically challenging due to a lack of minimally invasive diagnosis methods. MicroRNAs (miRNAs) derived from small extracellular vesicles (EVs) in the blood have been reported as a promising diagnosis biomarker for various types of cancer. However, blood small EV miRNA signatures and their diagnostic value to differentiate between PDAC and CP remain to be determined.

METHODS

In this study, 107 patients with PDAC or CP were recruited, and 90 patients were finally enrolled for a training cohort (n = 48) and test cohort (n = 42). Small RNA sequencing was used to assess the expression of blood small EV miRNAs in these patients.

RESULTS

The linear model from the differentially expressed blood small EV miR-95-3p divided by miR-26b-5p showed an average sensitivity of 84.1% and an average specificity of 96.6% to identify PDAC from CP in the training cohort and the test cohort, respectively. When the model was combined with serum carbohydrate antigen 19-9 (CA19-9), the average sensitivity increased to 96.5%, and the average specificity remained at 96.4% of both cohorts, which demonstrated the best performance of all the published biomarkers for distinguishing between PDAC and CP. The causal analysis performed using the Bayesian network demonstrated that miR-95-3p was associated with a "consequence" of "cancer" and miR-26b-5p as a "cause" of "pancreatitis." A subgroup analysis revealed that blood small EV miR-335-5p/miR-340-5p could predict metastases in both cohorts and was associated with an overall survival (p = 0.020).

CONCLUSIONS

This study indicated that blood small EV miR-95-3p/miR-26b-5p and its combination with serum levels of CA19-9 could separate PDAC from CP, and miR-335-5p/miR-340-5p was identified to associate with PDAC metastasis and poor prognosis. These results suggested the potentiality of blood small EV miRNAs as differential diagnosis and metastases biomarkers of PDAC.

Distinguishing diabetes secondary to pancreatic diseases from type 2 diabetes mellitus

PURPOSE OF REVIEW

Diabetes secondary to pancreatic diseases (i.e., acute pancreatitis, chronic pancreatitis, and pancreatic cancer) is increasingly studied, but remains challenging to distinguish from type 2 diabetes (T2DM). We review the clinical significance and potential biomarkers that may help differentiate these types of diabetes.

RECENT FINDINGS

Recent studies have identified several complications (including nonvascular) that occur more frequently in patients with diabetes secondary to acute and chronic pancreatitis than T2DM, and biomarkers to differentiate these types of diabetes. There have been advances that may enable the enrichment of a population of adults with new onset diabetes to potentially screen for occult pancreatic cancer, but efforts are needed to identify and validate promising diagnostic biomarkers.

SUMMARY

High-quality studies are needed to more precisely understand the risk factors and natural course of diabetes secondary to pancreatic diseases. Mechanistic and interventional studies are awaited to provide insights that will distinguish diabetes secondary to pancreatic diseases and refine the management of hyperglycemia in this patient population.

UEG position paper on pancreatic cancer. Bringing pancreatic cancer to the 21st century: Prevent, detect, and treat the disease earlier and better

BACKGROUND

Pancreatic ductal adenocarcinoma is the deadliest cancer worldwide with a 98% loss-of-life expectancy and a 30% increase in the disability-adjusted life years during the last decade in Europe. The disease cannot be effectively prevented nor being early detected. When diagnosed, 80% of patients have tumors that are in incurable stages, while for those who undergo surgery, 80% of patients will present with local or distant metastasis. Importantly, chemotherapies are far from being effective.

OBJECTIVE

Pancreatic cancer represents a great challenge and, at the same time, a huge opportunity for advancing our understanding on the basis of the disease, the molecular profiles, that would lead to develop tools for early detection and effective treatments, thus, boosting patient survival.

RESULTS

Research on pancreatic cancer has being receiving little or minimal funds from European funding bodies. UEG is calling for public-private partnerships that would effectively fund research on pancreatic cancer.

CONCLUSION

This would increase our understanding of this disease and better treatment, through pan-European efforts that take advantage of the strong academic European research landscape on pancreatic cancer, and the contribution by the industry of all sizes.

Plastin-3 is a diagnostic and prognostic marker for pancreatic adenocarcinoma and distinguishes from diffuse large B-cell lymphoma

Background

Altered Plastin-3 (PLS3; an actin-binding protein) expression was associated with human carcinogenesis, including pancreatic ductal adenocarcinoma (PDA). This study first assessed differentially expressed genes (DEGs) and then bioinformatically and experimentally confirmed PLS3 to be able to predict PDA prognosis and distinguish PDA from diffuse large B-cell lymphoma.

Methods

This study screened multiple online databases and revealed DEGs among PDA, normal pancreas, diffuse large B-cell lymphoma (DLBCL), and normal lymph node tissues and then focused on PLS3. These DEGs were analyzed for Gene Ontology (GO) terms, Kaplan–Meier curves, and the log-rank test to characterize their association with PDA prognosis. The receiver operating characteristic curve (ROC) was plotted, and Spearman’s tests were performed. Differential PLS3 expression in different tissue specimens (n = 30) was evaluated by reverse transcription quantitative polymerase chain reaction (RT-qPCR).

Results

There were a great number of DEGs between PDA and lymph node, between PDA and DLBCL, and between PDA and normal pancreatic tissues. Five DEGs (NET1, KCNK1, MAL2, PLS1, and PLS3) were associated with poor overall survival of PDA patients, but only PLS3 was further verified by the R2 and ICGC datasets. The ROC analysis showed a high PLS3 AUC (area under the curve) value for PDA diagnosis, while PLS3 was able to distinguish PDA from DLBCL. The results of Spearman's analysis showed that PLS3 expression was associated with levels of KRT7, SPP1, and SPARC. Differential PLS3 expression in different tissue specimens was further validated by RT-qPCR.

Conclusions

Altered PLS3 expression was useful in diagnosis and prognosis of PDA as well as to distinguish PDA from DLBCL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02117-1.

Biomarkers for early detection of pancreatic cancer - miRNAs as a potential diagnostic and therapeutic tool?

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies, with poor prognosis resulting mostly from late diagnosis. Surgery remains the most effective treatment and early detection significantly increases the overall survival. Biomarkers used for diagnosis and to monitor the response to treatment, such as carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA), are not adequate as early detection markers of PDAC, partly due to low sensitivity/specificity. Therefore, new biomarkers for PDAC are critically needed. This review aims at recent advancements in the identification and characterization of new biomarkers, microRNAs, which might prove useful in the early detection of PDAC.

Advances in the epidemiology of pancreatic cancer: Trends, risk factors, screening, and prognosis

Pancreatic cancer is a malignancy with poor prognosis and high mortality. The recent increase in pancreatic cancer incidence and mortality has resulted in an increased number of studies on its epidemiology. This comprehensive and systematic literature review summarizes the advances in the epidemiology of pancreatic cancer, including its epidemiological trends, risk factors, risk prediction models, screening modalities, and prognosis. The risk factors for pancreatic cancers can be categorized as those related to individual characteristics, lifestyle and environment, and disease status. Several prediction models for pancreatic cancer have been developed in populations with new-onset diabetes or a family history of pancreatic cancer; however, these models require further validation. Despite recent progress in pancreatic cancer screening, the quantity and quality of related studies are also unsatisfactory, especially with respect to the identification of high-risk populations and development of effective screening modality. Apart from the populations with familial genetic risk and those at a high risk of sporadic pancreatic cancer, risk factors such as new-onset diabetes may be a new direction for timely intervention. We hope this work will provide new ideas for further prevention and treatment of pancreatic cancer.

Non-Invasive Biomarkers for Earlier Detection of Pancreatic Cancer-A Comprehensive Review

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 90% of all pancreatic cancers, is an extremely aggressive and lethal disease. It is considered a silent killer due to a largely asymptomatic course and late clinical presentation. Earlier detection of the disease would likely have a great impact on changing the currently poor survival figures for this malignancy. In this comprehensive review, we assessed over 4000 reports on non-invasive PDAC biomarkers in the last decade. Applying the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool, we selected and reviewed in more detail 49 relevant studies reporting on the most promising candidate biomarkers. In addition, we also highlight the present challenges and complexities of translating novel biomarkers into clinical use.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) carries a deadly diagnosis, due in large part to delayed presentation when the disease is already at an advanced stage. CA19-9 is currently the most commonly utilized biomarker for PDAC; however, it lacks the necessary accuracy to detect precursor lesions or stage I PDAC. Novel biomarkers that could detect this malignancy with improved sensitivity (SN) and specificity (SP) would likely result in more curative resections and more effective therapeutic interventions, changing thus the present dismal survival figures. The aim of this study was to systematically and comprehensively review the scientific literature on non-invasive biomarkers in biofluids such as blood, urine and saliva that were attempting earlier PDAC detection. The search performed covered a period of 10 years (January 2010—August 2020). Data were extracted using keywords search in the three databases: MEDLINE, Web of Science and Embase. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied for study selection based on establishing the risk of bias and applicability concerns in Patient Selection, Index test (biomarker assay) and Reference Standard (standard-of-care diagnostic test). Out of initially over 4000 published reports, 49 relevant studies were selected and reviewed in more detail. In addition, we discuss the present challenges and complexities in the path of translating the discovered biomarkers into the clinical setting. Our systematic review highlighted several promising biomarkers that could, either alone or in combination with CA19-9, potentially improve earlier detection of PDAC. Overall, reviewed biomarker studies should aim to improve methodological and reporting quality, and novel candidate biomarkers should be investigated further in order to demonstrate their clinical usefulness. However, challenges and complexities in the path of translating the discovered biomarkers from the research laboratory to the clinical setting remain and would have to be addressed before a more realistic breakthrough in earlier detection of PDAC is achieved.

Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants

For optimal pancreatic cancer treatment, early and accurate diagnosis is vital. Blood-derived biomarkers and genetic predispositions can contribute to early diagnosis, but they often have limited accuracy or applicability. Here, we seek to exploit the synergy between them by combining the biomarker CA19-9 with RNA-based variants. We use deep sequencing and deep learning to improve differentiating pancreatic cancer and chronic pancreatitis. We obtained samples of nucleated cells found in peripheral blood from 268 patients suffering from resectable, non-resectable pancreatic cancer, and chronic pancreatitis. We sequenced RNA with high coverage and obtained millions of variants. The high-quality variants served as input together with CA19-9 values to deep learning models. Our model achieved an area under the curve (AUC) of 96% in differentiating resectable cancer from pancreatitis using a test cohort. Moreover, we identified variants to estimate survival in resectable cancer. We show that the blood transcriptome harbours variants, which can substantially improve noninvasive clinical diagnosis.