An Exosome-based Transcriptomic Signature for Noninvasive, Early Detection of Patients With Pancreatic Ductal Adenocarcinoma: A Multicenter Cohort Study

Circulating microRNAs in association with pancreatic cancer risk within 5 years

Early detection is critical for improving pancreatic cancer prognosis. Our study aims to identify circulating microRNAs (miRNAs) associated with pancreatic cancer risk. The two-stage study used plasma samples collected ≤5 years prior to cancer diagnosis, from case-control studies nested in five prospective cohort studies. The discovery stage included 185 case-control pairs from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Replication stage samples comprised 277 pairs from Shanghai Women's Health Study/Shanghai Men's Health Study, Southern Community Cohort Study, and Multiethnic Cohort Study. Seven hundred and ninety-eight miRNAs were measured using the NanoString nCounter Analysis System. Odds ratios (OR) and 95% confidence intervals (CI) for per 10% change in miRNAs in association with pancreatic cancer risk were derived from conditional logistic regression analysis in discovery and replication studies, separately, and then meta-analyzed. Stratified analysis was conducted by age at diagnosis (<65/≥65 years) and time interval between sample collection and diagnosis (≤2/>2 years). In the discovery stage, 120 risk associated miRNAs were identified at p < .05. Three were validated in the replication stage: hsa-miR-199a-3p/hsa-miR-199b-3p, hsa-miR-767-5p, and hsa-miR-191-5p, with respective ORs (95% CI) being 0.89 (0.84-0.95), 1.08 (1.02-1.13), and 0.90 (0.85-0.95). Five additional miRNAs, hsa-miR-640, hsa-miR-874-5p, hsa-miR-1299, hsa-miR-22-3p, and hsa-miR-449b-5p, were validated among patients diagnosed at ≥65 years, with OR (95% CI) of 1.23 (1.09-1.39), 1.33 (1.16-1.52), 1.25 (1.09-1.43), 1.28 (1.12-1.46), 0.76 (0.65-0.89), and 1.22 (1.07-1.39), respectively. The miRNA targets were enriched in pancreatic carcinogenesis/progression-related pathways. Our study suggests that circulating miRNAs may identify individuals at high risk for pancreatic cancer ≤5 years prior to diagnosis, indicating its potential utility in cancer screening and surveillance.

The role of biomarkers in the early detection of pancreatic cancer

Pancreatic surveillance can detect early-stage pancreatic cancer and achieve long-term survival, but currently involves annual endoscopic ultrasound and MRI/MRCP, and is recommended only for individuals who meet familial/genetic risk criteria. To improve upon current approaches to pancreatic cancer early detection and to expand access, more accurate, inexpensive, and safe biomarkers are needed, but finding them has remained elusive. Newer approaches to early detection, such as using gene tests to personalize biomarker interpretation, and the increasing application of artificial intelligence approaches to integrate complex biomarker data, offer promise that clinically useful biomarkers for early pancreatic cancer detection are on the horizon.

The systematic role of pancreatic cancer exosomes: distant communication, liquid biopsy and future therapy

Pancreatic cancer remains one of the most lethal diseases worldwide. Cancer-derived exosomes, benefiting from the protective role of the lipid membrane, exhibit remarkable stability in the circulatory system. These exosomes, released by tumor microenvironment, contain various biomolecules such as proteins, RNAs, and lipids that plays a pivotal role in mediating distant communication between the local pancreatic tumor and other organs or tissues. They facilitate the transfer of oncogenic factors to distant sites, contributing to the compromised body immune system, distant metastasis, diabetes, cachexia, and promoting a microenvironment conducive to tumor growth and metastasis in pancreatic cancer patients. Beyond their intrinsic roles, circulating exosomes in peripheral blood can be detected to facilitate accurate liquid biopsy. This approach offers a novel and promising method for the diagnosis and management of pancreatic cancer. Consequently, circulating exosomes are not only crucial mediators of systemic cell-cell communication during pancreatic cancer progression but also hold great potential as precise tools for pancreatic cancer management and treatment. Exosome-based liquid biopsy and therapy represent promising advancements in the diagnosis and treatment of pancreatic cancer. Exosomes can serve as drug delivery vehicles, enhancing the targeting and efficacy of anticancer treatments, modulating the immune system, and facilitating gene editing to suppress tumor growth. Ongoing research focuses on biomarker identification, drug delivery systems, and clinical trials to validate the safety and efficacy of exosome-based therapies, offering new possibilities for early diagnosis and precision treatment in pancreatic cancer. Leveraging the therapeutic potential of exosomes, including their ability to deliver targeted drugs and modulate immune responses, opens new avenues for innovative treatment strategies.

Blood-Derived Extracellular Vesicles as a Promising Liquid Biopsy Diagnostic Tool for Early Cancer Detection

Cancer poses a significant public health challenge worldwide, and timely screening has the potential to mitigate cancer progression and reduce mortality rates. Currently, early identification of most tumors relies on imaging techniques and tissue biopsies. However, the use of low-cost, highly sensitive, non-invasive detection methods for early cancer screening has become more attractive. Extracellular Vesicles (EVs) released by all living cells contain distinctive biological components, such as nucleic acids, proteins, and lipids. These vesicles play crucial roles in the tumor microenvironment and intercellular communication during tumor progression, rendering liquid biopsy a particularly suitable method for diagnosis. Nevertheless, challenges related to purification methods and validation of efficacy currently hinder its widespread clinical implementation. These limitations underscore the importance of refining isolation techniques and conducting comprehensive investigations on EVs. This study seeks to evaluate the potential of liquid biopsy utilizing blood-derived EVs as a practical, cost-effective, and secure approach for early cancer detection.

Unlocking the diagnostic power of plasma extracellular vesicle miR-200 family in pancreatic ductal adenocarcinoma

BACKGROUND

Distinguishing benign from malignant pancreaticobiliary disease is challenging because of the absence of reliable biomarkers. Circulating extracellular vesicles (EVs) have emerged as functional mediators between cells. Their cargos, including microRNAs (miRNAs), are increasingly acknowledged as an important source of potential biomarkers. This multicentric, prospective study aimed to establish a diagnostic plasma EV-derived miRNA signature to discriminate pancreatic ductal adenocarcinoma (PDAC) from benign pancreaticobiliary disease.

METHODS

Plasma EVs were isolated using size exclusion chromatography (SEC) and characterised using nanoparticle tracking analysis, electron microscopy and Western blotting. EV-RNAs underwent small RNA sequencing to discover differentially expressed markers for PDAC (n = 10 benign vs. 10 PDAC). Candidate EV-miRNAs were then validated in a cohort of 61 patients (n = 31 benign vs. 30 PDAC) by RT-qPCR. Logistic regression and optimal thresholds (Youden Index) were used to develop an EV-miR-200 family model to detect cancer. This model was tested in an independent cohort of 95 patients (n = 30 benign, 33 PDAC, and 32 cholangiocarcinoma).

RESULTS

Small RNA sequencing and RT-qPCR showed that EV-miR-200 family members were significantly overexpressed in PDAC vs. benign disease. Combined expression of the EV-miR-200 family showed an AUC of 0.823. In an independent validation cohort, application of this model showed a sensitivity, specificity and AUC of 100%, 88%, and 0.97, respectively, for diagnosing PDAC.

CONCLUSIONS

This is the first study to validate plasma EV-miR-200 members as a clinically-useful diagnostic biomarker for PDAC. Further validation in larger cohorts and clinical trials is essential. These findings also suggest the potential utility in monitoring response and/or recurrence.

MicroRNAs: circulating biomarkers for the early detection of imperceptible cancers via biosensor and machine-learning advances

This review explores the topic of microRNAs (miRNAs) for improved early detection of imperceptible cancers, with potential to advance precision medicine and improve patient outcomes. Historical research exploring miRNA's role in cancer detection collectively revealed initial hurdles in identifying specific miRNA signatures for early-stage and difficult-to-detect cancers. Early studies faced challenges in establishing robust biomarker panels and overcoming the heterogeneity of cancer types. Despite this, recent developments have supported the potential of miRNAs as sensitive and specific biomarkers for early cancer detection as well as having demonstrated remarkable potential as diagnostic tools for imperceptible cancers, such as those with elusive symptoms or challenging diagnostic criteria. This review discusses the advent of high-throughput technologies that have enabled comprehensive detection and profiling of unique miRNA signatures associated with early-stage cancers. Furthermore, advancements in bioinformatics and machine-learning techniques are considered, exploring the integration of multi-omics data which have potential to enhance both the accuracy and reliability of miRNA-based cancer detection assays. Finally, perspectives on the continuing development on technologies as well as discussion around challenges that remain, such as the need for standardised protocols and addressing the complex interplay of miRNAs in cancer biology are conferred.

Application of machine learning for high-throughput tumor marker screening

High-throughput sequencing and multiomics technologies have allowed increasing numbers of biomarkers to be mined and used for disease diagnosis, risk stratification, efficacy assessment, and prognosis prediction. However, the large number and complexity of tumor markers make screening them a substantial challenge. Machine learning (ML) offers new and effective ways to solve the screening problem. ML goes beyond mere data processing and is instrumental in recognizing intricate patterns within data. ML also has a crucial role in modeling dynamic changes associated with diseases. Used together, ML techniques have been included in automatic pipelines for tumor marker screening, thereby enhancing the efficiency and accuracy of the screening process. In this review, we discuss the general processes and common ML algorithms, and highlight recent applications of ML in tumor marker screening of genomic, transcriptomic, proteomic, and metabolomic data of patients with various types of cancers. Finally, the challenges and future prospects of the application of ML in tumor therapy are discussed.

The science of exosomes: Understanding their formation, capture, and role in cellular communication

Extracellular vesicles (EVs) serve as a crucial method for transferring information among cells, which is vital in multicellular organisms. Among these vesicles, exosomes are notable for their small size, ranging from 20 to 150 nm, and their role in cell-to-cell communication. They carry lipids, proteins, and nucleic acids between cells. The creation of exosomes begins with the inward budding of the cell membrane, which then encapsulates various macromolecules as cargo. Once filled, exosomes are released into the extracellular space and taken up by target cells via endocytosis and similar processes. The composition of exosomal cargo varies, encompassing diverse macromolecules with specific functions. Because of their significant roles, exosomes have been isolated from various cell types, including cancer cells, endothelial cells, macrophages, and mesenchymal cells, with the aim of harnessing them for therapeutic applications. Exosomes influence cellular metabolism, and regulate lipid, glucose, and glutamine pathways. Their role in pathogenesis is determined by their cargo, which can manipulate processes such as apoptosis, proliferation, inflammation, migration, and other molecular pathways in recipient cells. Non-coding RNA transcripts, a common type of cargo, play a pivotal role in regulating disease progression. Exosomes are implicated in numerous biological and pathological processes, including inflammation, cancer, cardiovascular diseases, diabetes, wound healing, and ischemic-reperfusion injury. As a result, they hold significant potential in the treatment of both cancerous and non-cancerous conditions.

Liquid biopsy: An arsenal for tumour screening and early diagnosis

Cancer has become the second leading cause of death in the world, and more than 50% of cancer patients are diagnosed at an advanced stage. Early diagnosis of tumours is the key to improving patient quality of life and survival time and reducing the socioeconomic burden. However, there is still a lack of reliable early diagnosis methods in clinical practice. In recent years, liquid biopsy technology has developed rapidly. It has the advantages of noninvasiveness, easy access to sample sources, and reproducibility. It has become the main focus of research on the early diagnosis methods of tumours. This review summarises the research progress of existing liquid biopsy markers, such as circulating tumour DNA, circulating viral DNA, DNA methylation, circulating tumour cells, circulating RNA, exosomes, and tumour education platelets in early diagnosis of tumours, and analyses the current advantages and limitations of various markers, providing a direction for the application and transformation of liquid biopsy research in early diagnosis of clinical tumours.

miRNAs in pancreatic cancer progression and metastasis

Small non-coding RNA or microRNA (miRNA) are critical regulators of eukaryotic cells. Dysregulation of miRNA expression and function has been linked to a variety of diseases including cancer. They play a complex role in cancers, having both tumour suppressor and promoter properties. In addition, a single miRNA can be involved in regulating several mRNAs or many miRNAs can regulate a single mRNA, therefore assessing these roles is essential to a better understanding in cancer initiation and development. Pancreatic cancer is a leading cause of cancer death worldwide, in part due to the lack of diagnostic tools and limited treatment options. The most common form of pancreatic cancer, pancreatic ductal adenocarcinoma (PDAC), is characterised by major genetic mutations that drive cancer initiation and progression. The regulation or interaction of miRNAs with these cancer driving mutations suggests a strong link between the two. Understanding this link between miRNA and PDAC progression may give rise to novel treatments or diagnostic tools. This review summarises the role of miRNAs in PDAC, the downstream signalling pathways that they play a role in, how these are being used and studied as therapeutic targets as well as prognostic/diagnostic tools to improve the clinical outcome of PDAC.

Source Tracing of Kidney Injury via the Multispectral Fingerprint Identified by Machine Learning-Driven Surface-Enhanced Raman Spectroscopic Analysis

Early diagnosis of drug-induced kidney injury (DIKI) is essential for clinical treatment and intervention. However, developing a reliable method to trace kidney injury origins through retrospective studies remains a challenge. In this study, we designed ordered fried-bun-shaped Au nanocone arrays (FBS NCAs) to create microarray chips as a surface-enhanced Raman scattering (SERS) analysis platform. Subsequently, the principal component analysis (PCA)-two-layer nearest neighbor (TLNN) model was constructed to identify and analyze the SERS spectra of exosomes from renal injury induced by cisplatin and gentamycin. The established PCA-TLNN model successfully differentiated the SERS spectra of exosomes from renal injury at different stages and causes, capturing the most significant spectral features for distinguishing these variations. For the SERS spectra of exosomes from renal injury at different induction times, the accuracy of PCA-TLNN reached 97.8% (cisplatin) and 93.3% (gentamicin). For the SERS spectra of exosomes from renal injury caused by different agents, the accuracy of PCA-TLNN reached 100% (7 days) and 96.7% (14 days). This study demonstrates that the combination of label-free exosome SERS and machine learning could serve as an innovative strategy for medical diagnosis and therapeutic intervention.

A unique circulating microRNA pairs signature serves as a superior tool for early diagnosis of pan-cancer

Cancer remains a major burden globally and the critical role of early diagnosis is self-evident. Although various miRNA-based signatures have been developed in past decades, clinical utilization is limited due to a lack of precise cutoff value. Here, we innovatively developed a signature based on pairwise expression of miRNAs (miRPs) for pan-cancer diagnosis using machine learning approach. We analyzed miRNA spectrum of 15832 patients, who were divided into training, validation, test, and external test sets, with 13 different cancers from 10 cohorts. Five different machine-learning (ML) algorithms (XGBoost, SVM, RandomForest, LASSO, and Logistic) were adopted for signature construction. The best ML algorithm and the optimal number of miRPs included were identified using area under the curve (AUC) and youden index in validation set. The AUC of the best model was compared to previously published 25 signatures. Overall, Random Forest approach including 31 miRPs (31-miRP) was developed, proving highly efficient in cancer diagnosis across different datasets and cancer types (AUC range: 0.980-1.000). Regarding diagnosis of cancers at early stage, 31-miRP also exhibited high capacities, with AUC ranging from 0.961 to 0.998. Moreover, 31-miRP exhibited advantages in differentiating cancers from normal tissues (AUC range: 0.976-0.998) as well as differentiating cancers from corresponding benign lesions. Encouragingly, comparing to previously published 25 different signatures, 31-miRP also demonstrated clear advantages. In conclusion, 31-miRP acts as a powerful model for cancer diagnosis, characterized by high specificity and sensitivity as well as a clear cutoff value, thereby holding potential as a reliable tool for cancer diagnosis at early stage.

SSH3 promotes pancreatic cancer proliferation and migration by activating the notch signaling pathway

Recent studies have indicated that the dual-specificity phosphatases (DUSP) family may play a role in the advancement of pancreatic cancer. Exploring the role of the DUSP family in pancreatic cancer development and discovering novel therapeutic targets are crucial for pancreatic cancer therapy. A critical subset of 20 genes exhibiting differential expression was identified, with particular emphasis on four key genes: DUSP10, PTP4A2, SSH3, and CDKN3 by multivariate Cox proportional hazards analysis. These genes were integral to developing a novel risk model for PC, which has been independently validated as a prognostic factor for patients. To provide help for clinical treatment, we performed tumor immune analysis and predicted potential chemical drugs. Notably, our research unveiled elevated expression levels of SSH3 in human PC cells and tissues. Intriguingly, SSH3 expression correlates with the patient grade, staging, and T stage in PC. Additional studies reveal SSH3's role in enhancing PC cell proliferation and migration, intricately linked to the activation of the Notch signaling pathway. These insights provide a deeper understanding of PC pathophysiology and pave the way for novel therapeutic interventions.

Development of a Serum-Based MicroRNA Signature for Early Detection of Pancreatic Cancer: A Multicenter Cohort Study

BACKGROUND

A grim prognosis of pancreatic cancer (PCa) was attributed to the difficulty in early diagnosis of the disease.

AIMS

Identifying novel biomarkers for early detection of PCa is thus urgent to improve the overall survival rates of patients.

METHODS

The study was performed firstly by identification of candidate microRNAs (miRNAs) in formalin-fixed, paraffin-embedded tissues using microarray profiles, and followed by validation in a serum-based cohort study to assess clinical utility of the candidates. In the cohorts, a total of 1273 participants from four centers were retrospectively recruited as two cohorts including training and validation cohort. The collected serum specimens were analyzed by real-time polymerase chain reaction.

RESULTS

We identified 27 miRNAs expressed differentially in PCa tissues as compared to the benign. Of which, the top-four was selected as a panel whose diagnostic efficacy was fully assessed in the serum specimens. The panel exhibited superior to CA19-9, CA125, CEA and CA242 in discriminating patients with early stage PCa from healthy controls or non-PCa including chronic pancreatitis as well as pancreatic cystic neoplasms, with the area under the curves (AUC) of 0.971 (95% CI 0.956-0.987) and 0.924 (95% CI 0.899-0.949), respectively. Moreover, the panel eliminated interference from other digestive tumors with a specificity of 90.2%.

CONCLUSIONS

A panel of four serum miRNAs was developed showing remarkably discriminative ability of early stage PCa from either healthy controls or other pancreatic diseases, suggesting it may be developed as a novel, noninvasive approach for early screening of PCa in clinic.

Circulating small extracellular vesicle-based miRNA classifier for follicular thyroid carcinoma: a diagnostic study

BACKGROUND

The diagnosis of follicular thyroid carcinoma (FTC) prior to surgery remains a major challenge in the clinic.

METHODS

This multicentre diagnostic study involved 41 and 150 age- and sex-matched patients in the training cohort and validation cohort, respectively. The diagnostic properties of circulating small extracellular vesicle (sEV)-associated and cell-free RNAs were compared by RNA sequencing in the training cohort. Subsequently, using a quantitative real-time polymerase chain reaction (qRT‒PCR) assay, high-quality candidates were identified to construct an RNA classifier for FTC and verified in the validation cohort. The parallel expression, stability and influence of the RNA classifier on surgical strategy were also investigated.

RESULTS

The diagnostic properties of sEV long RNAs, cell-free long RNAs and sEV microRNAs (miRNAs) were comparable and superior to those of cell-free miRNAs in RNA sequencing. Given the clinical application, the circulating sEV miRNA (CirsEV-miR) classifier was developed from five miRNAs based on qRT‒PCR data, which could well identify FTC patients (area under curve [AUC] of 0.924 in the training cohort and 0.844 in the multicentre validation cohort). Further tests revealed that the CirsEV-miR score was significantly correlated with the tumour burden, and the levels of sEV miRNAs were also higher in sEVs from the FTC cell line, organoid and tissue. Additionally, circulating sEV miRNAs remained constant after different treatments, and the addition of the CirsEV-miR classifier as a biomarker improves the current surgical strategy.

CONCLUSIONS

The CirsEV-miR classifier could serve as a noninvasive, convenient, specific and stable auxiliary test to help diagnose FTC following ultrasonography.

[Early detection of sporadic pancreatic cancer]

The incidence of pancreatic cancer is rising. At present, pancreatic cancer is the third most common cancer-causing death in Germany, but it is expected to become the second in 2030 and finally the leading cause of cancer death in 2050. Pancreatic ductal adenocarcinoma (PC) is generally diagnosed at advanced stages, and 5-year-survival has remained poor. Early detection of sporadic PC at stage IA, however, can yield a 5-year-survival rate of about 80%. Early detection initiatives aim at identifying persons at high risk. People with new-onset diabetes at age 50 or older have attracted much interest. Novel strategies regarding how to detect sporadic PC at an early stage are being discussed.

Extracellular vesicles in cancer: challenges and opportunities for clinical laboratories

Extracellular vesicles (EVs) are nano-sized particles secreted by most cells. They transport different types of biomolecules (nucleic acids, proteins, and lipids) characteristic of their tissue or cellular origin that can mediate long-distance intercellular communication. In the case of cancer, EVs participate in tumor progression by modifying the tumor microenvironment, favoring immune tolerance and metastasis development. Consequently, EVs have great potential in liquid biopsy for cancer diagnosis, prognosis and follow-up. In addition, EVs could have a role in cancer treatment as a targeted drug delivery system. The intense research in the EV field has resulted in hundreds of patents and the creation of biomedical companies. However, methodological issues and heterogeneity in EV composition have hampered the advancement of EV validation trials and the development of EV-based diagnostic and therapeutic products. Consequently, only a few EV biomarkers have moved from research to clinical laboratories, such as the ExoDx Prostate IntelliScore (EPI) test, a CLIA/FDA-approved EV prostate cancer diagnostic test. In addition, the number of large-scale multicenter studies that would clearly define biomarker performance is limited. In this review, we will critically describe the different types of EVs, the methods for their enrichment and characterization, and their biological role in cancer. Then, we will specially focus on the parameters to be considered for the translation of EV biology to the clinic laboratory, the advances already made in the field of EVs related to cancer diagnosis and treatment, and the issues still pending to be solved before EVs could be used as a routine tool in oncology.

Emerging Therapeutic Options in Pancreatic Cancer Management

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a 5-year survival rate of <8% [...].

Extracellular vesicles associated microRNAs: Their biology and clinical significance as biomarkers in gastrointestinal cancers

Gastrointestinal (GI) cancers, including colorectal, gastric, esophageal, pancreatic, and liver, are associated with high mortality and morbidity rates worldwide. One of the underlying reasons for the poor survival outcomes in patients with these malignancies is late disease detection, typically when the tumor has already advanced and potentially spread to distant organs. Increasing evidence indicates that earlier detection of these cancers is associated with improved survival outcomes and, in some cases, allows curative treatments. Consequently, there is a growing interest in the development of molecular biomarkers that offer promise for screening, diagnosis, treatment selection, response assessment, and predicting the prognosis of these cancers. Extracellular vesicles (EVs) are membranous vesicles released from cells containing a repertoire of biological molecules, including nucleic acids, proteins, lipids, and carbohydrates. MicroRNAs (miRNAs) are the most extensively studied non-coding RNAs, and the deregulation of miRNA levels is a feature of cancer cells. EVs miRNAs can serve as messengers for facilitating interactions between tumor cells and the cellular milieu, including immune cells, endothelial cells, and other tumor cells. Furthermore, recent years have witnessed considerable technological advances that have permitted in-depth sequence profiling of these small non-coding RNAs within EVs for their development as promising cancer biomarkers -particularly non-invasive, liquid biopsy markers in various cancers, including GI cancers. Herein, we summarize and discuss the roles of EV-associated miRNAs as they play a seminal role in GI cancer progression, as well as their promising translational and clinical potential as cancer biomarkers as we usher into the area of precision oncology.

Thinking small to win big? A critical review on the potential application of extracellular vesicles for biomarker discovery and new therapeutic approaches in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is an extremely deadly form of cancer, with limited progress in 5-year survival rates despite significant research efforts. The main challenges in treating PDAC include difficulties in early detection, and resistance to current therapeutic approaches due to aggressive molecular and microenvironment features. These challenges emphasize the importance of identifying clinically validated biomarkers for early detection and clinical management. Extracellular vesicles (EVs), particularly exosomes, have emerged as crucial mediators of intercellular communication by transporting molecular cargo. Recent research has unveiled their role in initiation, metastasis, and chemoresistance of PDAC. Consequently, utilizing EVs in liquid biopsies holds promise for the identification of biomarkers for early detection, prognosis, and monitoring of drug efficacy. However, numerous limitations, including challenges in isolation and characterization of homogeneous EVs populations, as well as the absence of standardized protocols, can affect the reliability of studies involving EVs as biomarkers, underscoring the necessity for a prudent approach. EVs have also garnered considerable attention as a promising drug delivery system and novel therapy for tumors. The loading of biomolecules or chemical drugs into exosomes and their subsequent delivery to target cells can effectively impede tumor progression. Nevertheless, there are obstacles that must be overcome to ensure the accuracy and efficacy of therapies relying on EVs for the treatment of tumors. In this review, we examine both recent advancements and remaining obstacles, exploring the potential of utilizing EVs in biomarker discovery as well as for the development of drug delivery vehicles.

Diagnosis and prognosis of pancreatic cancer with immunoglobulin heavy constant delta blood marker

BACKGROUND

Pancreatic cancer (PC) is highly malignant and difficult to detect, while few blood markers are currently available for diagnosing PC.

METHODS

We obtained differential expression genes (DEGs) from GEO (gene expression omnibus) database and assessed by quantitative real-time polymerase chain reaction (qRT-PCR), receiver operating characteristic (ROC), univariate and multifactorial regression analysis, and survival analysis in our clinic center. Through the TCGA (the cancer genome atlas) database, we analyzed functional enrichment, different risk groups with survival analysis, immunological features, and the risk score established by the Cox regression model and constructed a nomogram.

RESULT

Immunoglobulin heavy constant delta (IGHD) was remarkably upregulated in peripheral blood from PC patients, and IGHD was a potential independent biomarker for PC diagnosis (ROC sensitivity, 76.0%; specificity, 74.2%; area under the curve (AUC) = 0.817; univariate logistic regression analysis: odds ratio (OR) 1.488; 95% confidence interval (CI) 1.182-1.872; P < 0.001; multiple logistic: OR 2.097; 95% CI 1.276-3.389, P = 0.003). In addition, the IGHD expression was remarkably reduced after resectioning the primary tumor. High IGHD expression indicated higher lymphocyte infiltration and increased activities of immunological pathways in PC patients. KRAS and SMAD were observed with a prominent difference among top mutated genes between the two groups. The risk score predicted reliable clinical prognosis and drug responses. Furthermore, a nomogram with the risk score and clinical characteristics was constructed, showing a better predictive performance.

CONCLUSION

IGHD is a valuable PC diagnosis, prognosis, and therapeutic response marker.

Circulating microRNA Panels for Detection of Liver Cancers and Liver-Metastasizing Primary Cancers

Malignant liver tumors, including primary malignant liver tumors and liver metastases, are among the most frequent malignancies worldwide. The disease carries a poor prognosis and poor overall survival, particularly in cases involving liver metastases. Consequently, the early detection and precise differentiation of malignant liver tumors are of paramount importance for making informed decisions regarding patient treatment. Significant research efforts are currently directed towards the development of diagnostic tools for different types of cancer using minimally invasive techniques. A prominent area of focus within this research is the evaluation of circulating microRNA, for which dysregulated expression is well documented in different cancers. Combining microRNAs in panels using serum or plasma samples derived from blood holds great promise for better sensitivity and specificity for detection of certain types of cancer.

Pancreatic Cancer Health Disparity: Pharmacologic Anthropology

Pancreatic cancer (PCa) remains a formidable global health challenge, with high mortality rates and limited treatment options. While advancements in pharmacology have led to improved outcomes for various cancers, PCa continues to exhibit significant health disparities, disproportionately affecting certain populations. This paper explores the intersection of pharmacology and anthropology in understanding the health disparities associated with PCa. By considering the socio-cultural, economic, and behavioral factors that influence the development, diagnosis, treatment, and outcomes of PCa, pharmacologic anthropology provides a comprehensive framework to address these disparities and improve patient care.

Development of a blood-based extracellular vesicle classifier for detection of early-stage pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has an overall 5-year survival rate of just 12.5% and thus is among the leading causes of cancer deaths. When detected at early stages, PDAC survival rates improve substantially. Testing high-risk patients can increase early-stage cancer detection; however, currently available liquid biopsy approaches lack high sensitivity and may not be easily accessible.

METHODS

Extracellular vesicles (EVs) were isolated from blood plasma that was collected from a training set of 650 patients (105 PDAC stages I and II, 545 controls). EV proteins were analyzed using a machine learning approach to determine which were the most informative to develop a classifier for early-stage PDAC. The classifier was tested on a validation cohort of 113 patients (30 PDAC stages I and II, 83 controls).

RESULTS

The training set demonstrates an AUC of 0.971 (95% CI = 0.953-0.986) with 93.3% sensitivity (95% CI: 86.9-96.7) at 91.0% specificity (95% CI: 88.3-93.1). The trained classifier is validated using an independent cohort (30 stage I and II cases, 83 controls) and achieves a sensitivity of 90.0% and a specificity of 92.8%.

CONCLUSIONS

Liquid biopsy using EVs may provide unique or complementary information that improves early PDAC and other cancer detection. EV protein determinations herein demonstrate that the AC Electrokinetics (ACE) method of EV enrichment provides early-stage detection of cancer distinct from normal or pancreatitis controls.

Salivary Extracellular MicroRNAs for Early Detection and Prognostication of Esophageal Cancer: A Clinical Study

BACKGROUND & AIMS

Early detection of esophageal squamous cell carcinoma (ESCC) will facilitate curative treatment. We aimed to establish a microRNA (miRNA) signature derived from salivary extracellular vesicles and particles (EVPs) for early ESCC detection and prognostication.

METHODS

Salivary EVP miRNA expression was profiled in a pilot cohort (n = 54) using microarray. Area under the receiver operator characteristic curve (AUROC) and least absolute shrinkage and selector operation regression analyses were used to prioritize miRNAs that discriminated patients with ESCC from controls. Using quantitative reverse transcription polymerase chain reaction, the candidates were measured in a discovery cohort (n = 72) and cell lines. The prediction models for the biomarkers were derived from a training cohort (n = 342) and validated in an internal cohort (n = 207) and an external cohort (n = 226).

RESULTS

The microarray analysis identified 7 miRNAs for distinguishing patients with ESCC from control subjects. Because 1 was not always detectable in the discovery cohort and cell lines, the other 6 miRNAs formed a panel. A signature of this panel accurately identified patients with all-stage ESCC in the training cohort (AUROC = 0.968) and was successfully validated in 2 independent cohorts. Importantly, this signature could distinguish patients with early-stage (stage Ⅰ/Ⅱ) ESCC from control subjects in the training cohort (AUROC = 0.969, sensitivity = 92.00%, specificity = 89.17%) and internal (sensitivity = 90.32%, specificity = 91.04%) and external (sensitivity = 91.07%, specificity = 88.06%) validation cohorts. Moreover, a prognostic signature based on the panel was established and efficiently predicted the high-risk cases with poor progression-free survival and overall survival.

CONCLUSIONS

The salivary EVP-based 6-miRNA signature can serve as noninvasive biomarkers for early detection and risk stratification of ESCC. Chinese Clinical Trial Registry, ChiCTR2000031507.

Identification of stromal cell-derived factor 4 as a liquid biopsy-based diagnostic marker in solid cancers

There is a need for serum diagnostic biomarkers to improve the prognosis of solid malignant tumors. Here, we conducted a single-institutional study to evaluate the diagnostic performance of serum stromal cell-derived factor 4 (SDF4) levels in cancer patients. Serum samples were collected from a total of 582 patients with solid cancers including gastric cancer (GC) and 80 healthy volunteers. SDF4 protein levels in sera, and conditioned media or lysates of human GC cell lines were measured by enzyme-linked immunosorbent assay, and those in GC tissue by immunohistochemistry. Serum SDF4 levels were higher in patients with cancer than the healthy control in all cancer type. Regarding GC, serum SDF4 levels distinguished healthy controls from GC patients with the area under the curve value of 0.973, sensitivity of 89%, and specificity of 99%. Serum SDF4 levels were significantly elevated in patient with early stage GC. In immunohistochemistry, the frequency of SDF4-positive GC tumors did not vary significantly between GC stages. The ability of human GC cell lines to both produce and secrete SDF4 was confirmed in vitro. In conclusion, serum SDF4 levels could be a promising candidate for a novel diagnostic biomarker for GC and other malignancies.

Emerging role of exosome-shuttled noncoding RNAs in gastrointestinal cancers: From intercellular crosstalk to clinical utility

Gastrointestinal cancer remains a significant global health burden. The pursuit of advancing the comprehension of tumorigenesis, along with the identification of reliable biomarkers and the development of precise therapeutic strategies, represents imperative objectives in this field. Exosomes, small membranous vesicles released by most cells, commonly carry functional biomolecules, including noncoding RNAs (ncRNAs), which are specifically sorted and encapsulated by exosomes. Exosome-mediated communication involves the release of exosomes from tumor or stromal cells and the uptake by nearby or remote recipient cells. The bioactive cargoes contained within these exosomes exert profound effects on the recipient cells, resulting in significant modifications in the tumor microenvironment (TME) and distinct alterations in gastrointestinal tumor behaviors. Due to the feasibility of isolating exosomes from various bodily fluids, exosomal ncRNAs have shown great potential as liquid biopsy-based indicators for different gastrointestinal cancers, using blood, ascites, saliva, or bile samples. Moreover, exosomes are increasingly recognized as natural delivery vehicles for ncRNA-based therapeutic interventions. In this review, we elucidate the processes of ncRNA-enriched exosome biogenesis and uptake, examine the regulatory and functional roles of exosomal ncRNA-mediated intercellular crosstalk in gastrointestinal TME and tumor behaviors, and explore their potential clinical utility in diagnostics, prognostics, and therapeutics.

Exosomal circRNAs in cancer: Implications for therapy resistance and biomarkers

Despite the advances in cancer treatment in recent years, the development of resistance to cancer therapy remains the biggest hurdle towards curative cancer treatments. Therefore, investigating the molecular mechanisms underlying cancer therapy resistance is of paramount clinical importance. Circular RNAs (circRNAs), novel members of the noncoding RNA family, are endogenous biomolecules in eukaryotes characterized by a covalently closed loop structure with multiple biological functions. Significantly, circRNAs are abundant and stable in exosomes and can be packaged, secreted and transferred to targeted tumour cells, thereby modulating diverse hallmarks of cancer behaviours, such as proliferation, migration, and immune escape. Notably, a great number of exosomal circRNAs are abnormally expressed during cancer treatment and can mediate cancer therapy resistance through complex mechanisms; therefore, targeting exosomal circRNAs is a promising therapeutic method to reverse therapy resistance. This review aimed to elucidate the mechanisms underlying exosomal circRNAs controlling the resistance of cancer to common therapies, such as chemotherapy, targeted therapy, immunotherapy and radiotherapy, and we also discussed the therapeutic potential of exosomal circRNAs as clinical biomarkers and novel targets in cancer clinical management. We also discussed the prospects and challenges of targeting exosomal circRNAs as a novel therapeutic strategy for reversing cancer therapy resistance.

Evolving utility of exosomes in pancreatic cancer management

Despite the development of newer oncological treatment, the survival of patients with pancreatic cancer (PC) remains poor. Recent studies have identified exosomes as essential mediators of intercellular communications and play a vital role in tumor initiation, metastasis and chemoresistance. Thus, the utility of liquid biopsies using exosomes in PC management can be used for early detection, diagnosis, monitoring as well as drug delivery vehicles for cancer therapy. This review summarizes the function, and clinical applications of exosomes in cancers as minimally invasive liquid biomarker in diagnostic, prognostic and therapeutic roles.

Can the molecules carried by extracellular vesicles help to diagnose pancreatic cancer early?

BACKGROUND

Pancreatic cancer is a deadly malignancy mainly because of its asymptomatic onset which prevents the implementation of the primary tumour's resection surgery, leading to metastatic spread resistant to chemotherapy. Early-detection of this cancer in its initial stage would represent a game changer in the fight against this disease. The few currently available biomarkers detectable in patients' body fluids lack sensitivity and specificity.

SCOPE OF REVIEW

The recent discovery of extracellular vesicles and their role in promoting cancer's advancement, has boosted interest in researching their cargo, to find reliable early detection biological markers. This review examines the most recent discoveries in the analysis of potential extra vesicle-carried biological markers for the early detection of pancreatic cancer.

MAJOR CONCLUSIONS

Despite the advantages of using extracellular vesicles for early diagnosis, and the promising findings of extracellular vesicle-carried molecules possibly functional as biomarkers, until now there are no validated markers derived from extracellular vesicles available to be used in the clinic.

GENERAL SIGNIFICANCE

Further studies in this direction are urgently required to provide what would be a major asset for defeating pancreatic cancer.

Exosomal miRNAs in the microenvironment of pancreatic cancer

Pancreatic cancer (PC) is highly aggressive having an extremely poor prognosis. The tumor microenvironment (TME) of PC is complex and heterogeneous. Various cellular components in the microenvironment are capable of secreting different active substances that are involved in promoting tumor development. Their release may occur via exosomes, the most abundant extracellular vesicles (EVs), that can carry numerous factors as well as act as a mean of intercellular communication. Emerging evidence suggests that miRNAs are involved in the regulation and control of many pathological and physiological processes. They can also be transported by exosomes from donor cells to recipient cells, thereby regulating the TME. Exosomal miRNAs show promise for use as future targets for PC diagnosis and prognosis, which may reveal new treatment strategies for PC. In this paper, we review the important role of exosomal miRNAs in mediating cellular communication in the TME of PC as well as their potential use in clinical applications.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. “Classical” tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

Liquid biopsy in pancreatic cancer - Current perspective and future outlook

Pancreatic cancer is a lethal condition with a rising incidence and often presents at an advanced stage, contributing to abysmal five-year survival rates. Unspecific symptoms and the current lack of biomarkers and screening tools hamper early diagnosis. New technologies for liquid biopsies and their respective evaluation in pancreatic cancer patients have emerged over recent years. The term liquid biopsy summarizes the sampling and analysis of circulating tumor cells (CTCs), small extracellular vesicles (sEVs), and tumor DNA (ctDNA) from body fluids. The major advantages of liquid biopsies rely on their minimal invasiveness and repeatability, allowing serial sampling for dynamic insights to aid diagnosis, particularly early detection, risk stratification, and precision medicine in pancreatic cancer. However, liquid biopsies have not yet developed into a new pillar for clinicians' routine armamentarium. Here, we summarize recent findings on the use of liquid biopsy in pancreatic cancer patients. We discuss current challenges and future perspectives of this potentially powerful alternative to conventional tissue biopsies.

An exosome-based liquid biopsy signature for pre-operative identification of lymph node metastasis in patients with pathological high-risk T1 colorectal cancer

BACKGROUND

According to current guidelines, more than 70% of patients with invasive submucosal colorectal cancer (T1 CRC) undergo a radical operation with lymph node dissection, even though only ~ 10% have lymph node metastasis (LNM). Hence, there is imperative to develop biomarkers that can help robustly identify LNM-positive patients to prevent such overtreatments. Given the emerging interest in exosomal cargo as a source for biomarker development in cancer, we examined the potential of exosomal miRNAs as LNM prediction biomarkers in T1 CRC.

METHODS

We analyzed 200 patients with high-risk T1 CRC from two independent cohorts, including a training (n = 58) and a validation cohort (n = 142). Cell-free and exosomal RNAs from pre-operative serum were extracted, followed by quantitative reverse-transcription polymerase chain reactions for a panel of miRNAs.

RESULTS

A panel of four miRNAs (miR-181b, miR-193b, miR-195, and miR-411) exhibited robust ability for detecting LNM in the exosomal vs. cell-free component. We subsequently established a cell-free and exosomal combination signature, successfully validated in two independent clinical cohorts (AUC, 0.84; 95% CI 0.70-0.98). Finally, we developed a risk-stratification model by including key pathological features, which reduced the false positive rates for LNM by 76% without missing any true LNM-positive patients.

CONCLUSIONS

Our novel exosomal miRNA-based liquid biopsy signature robustly identifies T1 CRC patients at risk of LNM in a preoperative setting. This could be clinically transformative in reducing the significant overtreatment burden of this malignancy.

Screening for pancreatic cancer has the potential to save lives, but is it practical?

INTRODUCTION

Most patients with pancreatic cancer present with advanced stage, incurable disease. However, patients with high-grade precancerous lesions and many patients with low-stage disease can be cured with surgery, suggesting that early detection has the potential to improve survival. While serum CA19.9 has been a long-standing biomarker used for pancreatic cancer disease monitoring, its low sensitivity and poor specificity have driven investigators to hunt for better diagnostic markers.

AREAS COVERED

This review will cover recent advances in genetics, proteomics, imaging, and artificial intelligence, which offer opportunities for the early detection of curable pancreatic neoplasms.

EXPERT OPINION

From exosomes, to circulating tumor DNA, to subtle changes on imaging, we know much more now about the biology and clinical manifestations of early pancreatic neoplasia than we did just five years ago. The overriding challenge, however, remains the development of a practical approach to screen for a relatively rare, but deadly, disease that is often treated with complex surgery. It is our hope that future advances will bring us closer to an effective and financially sound approach for the early detection of pancreatic cancer and its precursors.

Early Diagnosis of Pancreatic Cancer: Clinical Premonitions, Timely Precursor Detection and Increased Curative-Intent Surgery

BACKGROUND

The overall poor prognosis in pancreatic cancer is related to late clinical detection. Early diagnosis remains a considerable challenge in pancreatic cancer. Unfortunately, the onset of clinical symptoms in patients usually indicate advanced disease or presence of metastasis.

ANALYSIS AND RESULTS

Currently, there are no designated diagnostic or screening tests for pancreatic cancer in clinical use. Thus, identifying risk groups, preclinical risk factors or surveillance strategies to facilitate early detection is a target for ongoing research. Hereditary genetic syndromes are a obvious, but small group at risk, and warrants close surveillance as suggested by society guidelines. Screening for pancreatic cancer in asymptomatic individuals is currently associated with the risk of false positive tests and, thus, risk of harms that outweigh benefits. The promise of cancer biomarkers and use of 'omics' technology (genomic, transcriptomics, metabolomics etc.) has yet to see a clinical breakthrough. Several proposed biomarker studies for early cancer detection lack external validation or, when externally validated, have shown considerably lower accuracy than in the original data. Biopsies or tissues are often taken at the time of diagnosis in research studies, hence invalidating the value of a time-dependent lag of the biomarker to detect a pre-clinical, asymptomatic yet operable cancer. New technologies will be essential for early diagnosis, with emerging data from image-based radiomics approaches, artificial intelligence and machine learning suggesting avenues for improved detection.

CONCLUSIONS

Early detection may come from analytics of various body fluids (eg 'liquid biopsies' from blood or urine). In this review we present some the technological platforms that are explored for their ability to detect pancreatic cancer, some of which may eventually change the prospects and outcomes of patients with pancreatic cancer.