Screening for pancreatic cancer: why, how, and who?

The cross-talk between the macro and micro-environment in precursor lesions of pancreatic cancer leads to new and promising circulating biomarkers

Pancreatic cancer (PC) is a clinically challenging tumor to combat due to its advanced stage at diagnosis as well as its resistance to currently available therapies. The absence of early symptoms and known detectable biomarkers renders this disease incredibly difficult to detect/manage. Recent advances in the understanding of PC biology have highlighted the importance of cancer-immune cell interactions, not only in the tumor micro-environment but also in distant systemic sites, like the bone marrow, spleen and circulating immune cells, the so-called macro-environment. The response of the macro-environment is emerging as a determining factor in tumor development by contributing to the formation of an increasingly immunogenic micro-environment promoting tumor homeostasis and progression. We will summarize the key events associated with the feedback loop between the tumor immune micro-environment (TIME) and the tumor immune macroenvironment (TIMaE) in pancreatic precancerous lesions along with how it regulates disease development and progression. In addition, liquid biopsy biomarkers capable of diagnosing PC at an early stage of onset will also be discussed. A clearer understanding of the early crosstalk between micro-environment and macro-environment could contribute to identifying new molecular therapeutic targets and biomarkers, consequently improving early PC diagnosis and treatment.

Malpractice Claims Following Major Liver and Pancreatic Surgeries: What Can we Learn?

INTRODUCTION

General surgery is a highly litigious specialty. Lawsuits can be a source of emotional distress and burnout for surgeons. Major hepatic and pancreatic surgeries are technically challenging general surgical oncology procedures associated with an increased risk of complications and mortality. It is unclear whether these operations are associated with an increased risk of lawsuits. The objective of the present study was to summarize the medical malpractice claims surrounding pancreatic and hepatic surgeries from publicly available court records.

METHODS

The Westlaw legal database was searched and analyzed for relevant malpractice claims from the last two decades.

RESULTS

Of 165 search results, 30 (18.2%) cases were eligible for inclusion. Appellant cases comprised 53.3% of them. Half involved a patient death. Including co-defendants, a majority (n = 21, 70%) named surgeons as defendants, whereas several claims (n = 13, 43%) also named non-surgeons. The most common cause of alleged malpractice was a delay in diagnosis (n = 12, 40%). In eight of these, surgery could not be performed. The second most common were claims alleging the follow-up surgery was due to negligence (n = 6). Collectively, 20 claims were found in favor of the defendant. Seven verdicts (23.3%) returned in favor of the plaintiff, two of which resulted in monetary awards (totaling $1,608,325 and $424,933.85). Three cases went to trial or delayed motion for summary judgment. There were no settlements.

CONCLUSIONS

A defendant verdict was reached in two-thirds of malpractice cases involving major hepatic or pancreatic surgery. A delay in diagnosis was the most cited claim in hepatopancreaticobiliary lawsuits, and defendants may often practice in nonsurgical specialties. While rulings favoring plaintiffs are less frequent, the payouts may be substantial.

Predicting the risk of pancreatic cancer in women with new-onset diabetes mellitus

BACKGROUND AND AIM

People with new-onset diabetes mellitus (diabetes) could be a possible target population for pancreatic cancer surveillance. However, distinguishing diabetes caused by pancreatic cancer from type 2 diabetes remains challenging. We aimed to develop and validate a model to predict pancreatic cancer among women with new-onset diabetes.

METHODS

We conducted a retrospective cohort study among Australian women newly diagnosed with diabetes, using first prescription of anti-diabetic medications, sourced from administrative data, as a surrogate for the diagnosis of diabetes. The outcome was a diagnosis of pancreatic cancer within 3 years of diabetes diagnosis. We used prescription medications, severity of diabetes (i.e., change/addition of medication within 2 months after first medication), and age at diabetes diagnosis as potential predictors of pancreatic cancer.

RESULTS

Among 99 687 women aged ≥ 50 years with new-onset diabetes, 602 (0.6%) were diagnosed with pancreatic cancer within 3 years. The area under the receiver operating curve for the risk prediction model was 0.73. Age and diabetes severity were the two most influential predictors followed by beta-blockers, acid disorder drugs, and lipid-modifying agents. Using a risk threshold of 50%, sensitivity and specificity were 69% and the positive predictive value (PPV) was 1.3%.

CONCLUSIONS

Our model doubled the PPV of pancreatic cancer in women with new-onset diabetes from 0.6% to 1.3%. Age and rapid progression of diabetes were important risk factors, and pancreatic cancer occurred more commonly in women without typical risk factors for type 2 diabetes. This model could prove valuable as an initial screening tool, especially as new biomarkers emerge.

Pancreatic cancer: from early detection to personalized treatment approaches

Pancreatic cancer is notorious for its persistently poor prognosis and health outcomes, so some of the questions that may be begged are "Why is it mostly diagnosed at end stage?", "What could we possibly do with the advancing technology in today's world to detect early pancreatic cancer and intervene?", and "Are there any implementation of the existing novel imaging technologies?". Well, to start with, this is in part because the majority of patients presented would already have reached a locally advanced or metastatic stage at the time of diagnosis due to its highly aggressive characteristics and lack of symptoms. Due to this striking disparity in survival, advancements in early detection and intervention are likely to significantly increase patients' survival. Presently, screening is frequently used in high-risk individuals in order to obtain an early pancreatic cancer diagnosis. Having a thorough understanding of the pathogenesis and risk factors of pancreatic cancer may enable us to identify individuals at high risk, diagnose the disease early, and begin treatment promptly. In this review, the authors outline the clinical hurdles to early pancreatic cancer detection, describe high-risk populations, and discuss current screening initiatives for high-risk individuals. The ultimate goal of this current review is to study the roles of both traditional and novel imaging modalities for early pancreatic cancer detection. A lot of the novel imaging techniques mentioned seem promising, but they need to be put to the test on a large scale and may need to be combined with other non-invasive biomarkers before they can be widely used.

Pancreatic adenocarcinoma of the tail-Unveiling a rare presentation with venous thrombosis: A case report and literature review

Pancreatic cancer is a silent and lethal adversary that often conceals its presence until advanced stages. This report elucidates a distinctive case of a 46-year-old patient with pancreatic tail adenocarcinoma presenting with venous thrombosis, a rare manifestation. The patient's symptoms included severe left leg pain, swelling, and redness, accompanied by weight loss and decreased appetite. Laboratory findings indicated a prothrombotic state, whereas imaging revealed a substantial mass on the tail of the pancreas with hepatic metastasis. Elevated cancer antigen 19-9 and carcinoembryonic antigen supported the diagnosis which was confirmed by a liver biopsy. This case underscores the diagnostic challenges posed by pancreatic cancer, particularly in the tail, emphasizing the need for early detection. The intricate interplay between metastasis and thrombosis complicates the clinical landscape, requiring a comprehensive approach to management.

Identification of breath volatile organic compounds to distinguish pancreatic adenocarcinoma, pancreatic cystic neoplasm, and patients without pancreatic lesions

BACKGROUND

Volatile organic compounds (VOCs) are a promising potential biomarker that may be able to identify the presence of cancers.

AIM

To identify exhaled breath VOCs that distinguish pancreatic ductal adenocarcinoma (PDAC) from intraductal papillary mucinous neoplasm (IPMN) and healthy volunteers.

METHODS

We collected exhaled breath from histologically proven PDAC patients, radiological diagnosis IPMN, and healthy volunteers using the ReCIVA® device between 10/2021-11/2022. VOCs were identified by thermal desorption-gas chromatography/field-asymmetric ion mobility spectrometry and compared between groups.

RESULTS

A total of 156 participants (44% male, mean age 62.6 ± 10.6) were enrolled (54 PDAC, 42 IPMN, and 60 controls). Among the nine VOCs identified, two VOCs that showed differences between groups were dimethyl sulfide [0.73 vs 0.74 vs 0.94 arbitrary units (AU), respectively; P = 0.008] and acetone dimers (3.95 vs 4.49 vs 5.19 AU, respectively; P < 0.001). After adjusting for the imbalance parameters, PDAC showed higher dimethyl sulfide levels than the control and IPMN groups, with adjusted odds ratio (aOR) of 6.98 (95%CI: 1.15-42.17) and 4.56 (1.03-20.20), respectively (P < 0.05 both). Acetone dimer levels were also higher in PDAC compared to controls and IPMN (aOR: 5.12 (1.80-14.57) and aOR: 3.35 (1.47-7.63), respectively (P < 0.05 both). Acetone dimer, but not dimethyl sulfide, performed better than CA19-9 in PDAC diagnosis (AUROC 0.910 vs 0.796). The AUROC of acetone dimer increased to 0.936 when combined with CA19-9, which was better than CA19-9 alone (P < 0.05).

CONCLUSION

Dimethyl sulfide and acetone dimer are VOCs that potentially distinguish PDAC from IPMN and healthy participants. Additional prospective studies are required to validate these findings.

Characteristics of Early Pancreatic Cancer: Comparison between Stage 1A and Stage 1B Pancreatic Cancer in Multicenter Clinical Data Warehouse Study

BACKGROUND

Little is known about the characteristics of early pancreatic cancer. We aimed to identify the characteristics, clues for early detection, and prognostic factors for early pancreatic cancer by analyzing a large number of patients with stage 1 pancreatic cancer.

METHODS

A clinical data warehouse that includes databases of all the medical records of eight academic institutions was used to select and analyze patients with pancreatic cancer that had been diagnosed from January 2010 to May 2023.

RESULTS

In total, 257 stage 1 pancreatic cancer patients were included. There were 134 men (52%), and the average age was 67.2 ± 9.9 years. Compared to patients with stage 1B pancreatic cancer (2-4 cm), patients with stage 1A pancreatic cancer (≤2 cm) had more tumors in the body and tail than in the head (p = 0.028), more new-onset diabetes and less old diabetes (p = 0.010), less jaundice (p = 0.020), more follow-up of IPMN (intraductal papillary mucinous neoplasm, p = 0.029), and more histories of acute pancreatitis (p = 0.013). The pathological findings showed that stage 1A pancreatic cancer involved more IPMNs (p < 0.001) and lower pancreatic intraepithelial neoplasia (p = 0.004). IPMN was present in all 13 pancreatic tumors that were smaller than 1 cm. In multivariate analysis, positive resection margin (odds ratio [OR] 1.536, p = 0.040), venous invasion (OR 1.710, p = 0.010), and perineural invasion (OR 1.968, p = 0.002) were found to be risk factors affecting disease-free survival, while old diabetes (odds ratio [OS] 1.981, p = 0.003) and perineural invasion (OR 2.270, p = 0.003) were found to be risk factors affecting overall survival.

CONCLUSIONS

IPMN is closely associated with early pancreatic cancer and may provide an opportunity for early detection. The presence of perineural invasion was a crucial prognostic factor for both overall and disease-free survival in patients with stage 1 pancreatic cancer.

Endoscopic Ultrasound-Guided Fine-Needle Biopsy Versus Aspiration for Tissue Sampling Adequacy for Molecular Testing in Pancreatic Ductal Adenocarcinoma

BACKGROUND AND AIMS

There is limited literature on sample adequacy for molecular testing in pancreatic ductal adenocarcinoma obtained via endoscopic ultrasound (EUS) fine-needle aspiration (FNA) versus EUS fine-needle biopsy (FNB). We aimed to compare these two modalities regarding sample adequacy for molecular and genomic sequencing.

METHODS

We reviewed all patients with pancreatic ductal adenocarcinoma who underwent EUS at Saint Luke's Hospital from 2018 to 2021. The patients were categorized based on the method of EUS tissue acquisition, specifically FNA or FNB. A comprehensive evaluation was conducted for all cases by cytotechnologists.

RESULTS

Out of 132 patients who underwent EUS-guided biopsies, 76 opted for FNA, 48 opted for FNB, and 8 opted for a combination of both. The average number of passes required for FNB and FNA was 2.58 ± 1.06 and 2.49 ± 1.07, respectively (p = 0.704), indicating no significant difference. Interestingly, 71.4% (35) of FNB-obtained samples were deemed adequate for molecular testing, surpassing the 32.1% (26) adequacy observed with FNA (p < 0.001). Additionally, 46.4% (26) of FNB-obtained samples were considered adequate for genomic testing, a notable improvement over the 23.8% (20) adequacy observed with FNA (p = 0.005).

CONCLUSION

Although the number of passes required for cytologic diagnosis did not differ significantly between EUS-FNB and EUS-FNA, the former demonstrated superiority in obtaining samples adequate for molecular testing. Tumor surface area and cellularity were crucial parameters in determining sample adequacy for molecular testing, irrespective of the chosen tissue acquisition modality.

Resection of rectal metastasis after previous radical surgery for pancreatic cancer: Case report and literature review

RATIONALE

Pancreatic ductal adenocarcinoma (PDAC) is the main type of pancreatic cancer with a poor prognosis. Rectal metastasis after radical resection of PDAC is comparatively rare, and the understanding of such cases is currently not unified. This study presents the entire process of diagnosis and treatment of a patient with PDAC metastasized to the rectal. We propose the viewpoint of exploring potential biomarkers or establishing effective predictive models to assist in the clinical decision-making of such cases.

PATIENT CONCERNS

We present the case of a 71-year-old man with slight abdominal distension and dull pain. He underwent surgical treatment for a malignant tumor of the pancreatic body, which was discovered through computed tomography and magnetic resonance imaging examinations. Nine months after the pancreatectomy, a rectal mass was identified by digital rectal examination and diagnosed as a malignant lesion through a puncture biopsy. After a multidisciplinary joint consultation, the patient underwent radical surgery. It was later confirmed as rectal adenocarcinoma based on postoperative pathological results.

DIAGNOSIS

The pathological result after pancreatic surgery was PDAC, which had invaded the peripheral nerves and abdominal arteries. A diagnosis of rectal metastasis was determined ultimately by combining with the medical history and immunohistochemical staining results.

INTERVENTIONS AND OUTCOMES

Treatment of the PDAC included laparoscopic resection of the body and tail of the pancreas combined with splenectomy, and postoperative systemic chemotherapy. In addition, treatment of the rectal metastasis included laparoscopic radical resection and postoperative systemic chemotherapy. The patient's current living condition was good.

LESSONS

As a rare metastatic site of PDAC, rectal metastasis should be avoided because of misdiagnosis and missed diagnosis. Surgical resection is still an effective treatment strategy for localized pancreatic tumors and isolated metastases. Furthermore, the mining of potential biomarkers or the establishment of predictive models for pancreatic cancer and its metastases may contribute to better clinical decision-making in the future.

[Pancreatic cancer-screening or surveillance?]

BACKGROUND

Despite continuous improvement of diagnostic and therapeutic procedures, the number of new pancreatic ductal adenocarcinoma (PDAC) cases diagnosed annually almost equals the number of PDAC-related deaths. Prerequisite for curative treatment is a resectable tumor at the time of diagnosis. Individuals with genetic and/or familial risk profiles should therefore be screened and included in structured surveillance programs.

OBJECTIVES

Description of the status quo and usefulness of current PDAC screening and surveillance concepts.

METHODS

A selective literature search of current national and international guidelines including underlying literature was performed.

RESULTS

Nearly half of pancreatic cancer cases are missed by currently available surveillance programs, even in high-risk cohorts. Magnetic resonance imaging and endoscopic ultrasound supplemented by CA19‑9 (± HbA1c) are not accurate enough to ensure robust earlier pancreatic cancer detection. Complementary biomarker panels will take on a crucial diagnostic role in the future.

Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis

OBJECTIVES

To investigate the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with new-onset diabetes (NOD).

METHODS

The PRISMA statement standards were followed to conduct a systematic review. All studies investigating the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with NOD were included. Two-by-two tables, coupled forest plots and summary receiver operating characteristic plots were constructed using the number of true positives, false negatives, true negatives and false positives. Diagnostic random effects models were used to estimate summary sensitivity and specificity points.

RESULTS

A total of 26,752 individuals from four studies were included. The median follow-up was 3 years and the pooled risk of pancreatic cancer was 0.8% (95% CI 0.6-1.0%). END-PAC score ≥ 3, which classifies the patients as high risk, was associated with better predictive performance (sensitivity: 55.8% (43.9-67%); specificity: 82.0% (76.4-86.5%)) in comparison with END-PAC score 1-2 (sensitivity: 22.2% (16.6-29.2%); specificity: 69.9% (67.3-72.4%)) and END-PAC score < 1 (sensitivity: 18.0% (12.8-24.6%); specificity: 50.9% (48.6-53.2%)) which classify the patients as intermediate and low risk, respectively. The evidence quality was judged to be moderate to high.

CONCLUSIONS

END-PAC is a promising model for predicting pancreatic cancer risk in individuals with NOD. The score ≥3 should be considered as optimum cut-off value. More studies are needed to assess whether it could improve early pancreatic cancer detection rate, pancreatic cancer re-section rate, and pancreatic cancer treatment outcomes.

Identification and characterization of interferon-γ signaling-based personalized heterogeneity and therapeutic strategies in patients with pancreatic cancer

Background

Interferon-γ (IFN-γ) is a key cytokine with diverse biological functions, including antiviral defense, antitumor activity, immune regulation, and modulation of cellular processes. Nonetheless, its role in pancreatic cancer (PC) therapy remains debated. Therefore, it is worthwhile to explore the role of Interferon-γ related genes (IFN-γGs) in the progression of PC development.

Methodology

Transcriptomic data from 930 PC were sourced from TCGA, GEO, ICGC, and ArrayExpress, and 93 IFN-γGs were obtained from the MSigDB. We researched the characteristics of IFN-γGs in pan-cancer. Subsequently, the cohort of 930 PC was stratified into two distinct subgroups using the NMF algorithm. We then examined disparities in the activation of cancer-associated pathways within these subpopulations through GSVA analysis. We scrutinized immune infiltration in both subsets and probed classical molecular target drug sensitivity variations. Finally, we devised and validated a novel IFN-γ related prediction model using LASSO and Cox regression analyses. Furthermore, we conducted RT-qPCR and immunohistochemistry assays to validate the expression of seven target genes included in the prediction model.

Results

We demonstrated the CNV, SNV, methylation, expression levels, and prognostic characteristics of IFN-γGs in pan-cancers. Notably, Cluster 2 demonstrated superior prognostic outcomes and heightened immune cell infiltration compared to Clusters 1. We also assessed the IC50 values of classical molecular targeted drugs to establish links between IFN-γGs expression levels and drug responsiveness. Additionally, by applying our prediction model, we segregated PC patients into high-risk and low-risk groups, identifying potential benefits of cisplatin, docetaxel, pazopanib, midostaurin, epothilone.B, thapsigargin, bryostatin.1, and AICAR for high-risk PC patients, and metformin, roscovitine, salubrinal, and cyclopamine for those in the low-risk group. The expression levels of these model genes were further verified through HPA website data and qRT-PCR assays in PC cell lines and tissues.

Conclusion

This study unveils IFN-γGs related molecular subsets in pancreatic cancer for the first time, shedding light on the pivotal role of IFN-γGs in the progression of PC. Furthermore, we establish an IFN-γGs related prognostic model for predicting the survival of PC, offering a theoretical foundation for exploring the precise mechanisms of IFN-γGs in PC.

Listeria monocytogenes: a promising vector for tumor immunotherapy

Cancer receives enduring international attention due to its extremely high morbidity and mortality. Immunotherapy, which is generally expected to overcome the limits of traditional treatments, serves as a promising direction for patients with recurrent or metastatic malignancies. Bacteria-based vectors such as Listeria monocytogenes take advantage of their unique characteristics, including preferential infection of host antigen presenting cells, intracellular growth within immune cells, and intercellular dissemination, to further improve the efficacy and minimize off-target effects of tailed immune treatments. Listeria monocytogenes can reshape the tumor microenvironment to bolster the anti-tumor effects both through the enhancement of T cells activity and a decrease in the frequency and population of immunosuppressive cells. Modified Listeria monocytogenes has been employed as a tool to elicit immune responses against different tumor cells. Currently, Listeria monocytogenes vaccine alone is insufficient to treat all patients effectively, which can be addressed if combined with other treatments, such as immune checkpoint inhibitors, reactivated adoptive cell therapy, and radiotherapy. This review summarizes the recent advances in the molecular mechanisms underlying the involvement of Listeria monocytogenes vaccine in anti-tumor immunity, and discusses the most concerned issues for future research.

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Earlier Diagnosis of Pancreatic Cancer: Is It Possible?

Pancreatic ductal adenocarcinoma has a very high mortality rate which has been only minimally improved in the last 30 years. This high mortality is closely related to late diagnosis, which is usually made when the tumor is large and has extensively infiltrated neighboring tissues or distant metastases are already present. This is a paradoxical situation for a tumor that requires nearly 15 years to develop since the first founding mutation. Response to chemotherapy under such late circumstances is poor, resistance is frequent, and prolongation of survival is almost negligible. Early surgery has been, and still is, the only approach with a slightly better outcome. Unfortunately, the relapse percentage after surgery is still very high. In fact, early surgery clearly requires early diagnosis. Despite all the advances in diagnostic methods, the available tools for improving these results are scarce. Serum tumor markers permit a late diagnosis, but their contribution to an improved therapeutic result is very limited. On the other hand, effective screening methods for high-risk populations have not been fully developed as yet. This paper discusses the difficulties of early diagnosis, evaluates whether the available diagnostic tools are adequate, and proposes some simple and not-so-simple measures to improve it.

A review of deep learning and radiomics approaches for pancreatic cancer diagnosis from medical imaging

PURPOSE OF REVIEW

Early and accurate diagnosis of pancreatic cancer is crucial for improving patient outcomes, and artificial intelligence (AI) algorithms have the potential to play a vital role in computer-aided diagnosis of pancreatic cancer. In this review, we aim to provide the latest and relevant advances in AI, specifically deep learning (DL) and radiomics approaches, for pancreatic cancer diagnosis using cross-sectional imaging examinations such as computed tomography (CT) and magnetic resonance imaging (MRI).

RECENT FINDINGS

This review highlights the recent developments in DL techniques applied to medical imaging, including convolutional neural networks (CNNs), transformer-based models, and novel deep learning architectures that focus on multitype pancreatic lesions, multiorgan and multitumor segmentation, as well as incorporating auxiliary information. We also discuss advancements in radiomics, such as improved imaging feature extraction, optimized machine learning classifiers and integration with clinical data. Furthermore, we explore implementing AI-based clinical decision support systems for pancreatic cancer diagnosis using medical imaging in practical settings.

SUMMARY

Deep learning and radiomics with medical imaging have demonstrated strong potential to improve diagnostic accuracy of pancreatic cancer, facilitate personalized treatment planning, and identify prognostic and predictive biomarkers. However, challenges remain in translating research findings into clinical practice. More studies are required focusing on refining these methods, addressing significant limitations, and developing integrative approaches for data analysis to further advance the field of pancreatic cancer diagnosis.

Prognostic utility of TME-associated genes in pancreatic cancer

Background: Pancreatic cancer (PC) is a deadly disease. The tumor microenvironment (TME) participates in PC oncogenesis. This study focuses on the assessment of the prognostic and treatment utility of TME-associated genes in PC. Methods: After obtaining the differentially expressed TME-related genes, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) were performed to identify genes related to prognosis, and a risk model was established to evaluate risk scores, based on The Cancer Genome Atlas (TCGA) data set, and it was validated by external data sets from the Gene Expression Omnibus (GEO) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Multiomics analyses were adopted to explore the potential mechanisms, discover novel treatment targets, and assess the sensitivities of immunotherapy and chemotherapy. Results: Five TME-associated genes, namely, FERMT1, CARD9, IL20RB, MET, and MMP3, were identified and a risk score formula constructed. Next, their mRNA expressions were verified in cancer and normal pancreatic cells. Multiple algorithms confirmed that the risk model displayed a reliable ability of prognosis prediction and was an independent prognostic factor, indicating that high-risk patients had poor outcomes. Immunocyte infiltration, gene set enrichment analysis (GSEA), and single-cell analysis all showed a strong relationship between immune mechanism and low-risk samples. The risk score could predict the sensitivity of immunotherapy and some chemotherapy regimens, which included oxaliplatin and irinotecan. Various latent treatment targets (LAG3, TIGIT, and ARID1A) were addressed by mutation landscape based on the risk model. Conclusion: The risk model based on TME-related genes can reflect the prognosis of PC patients and functions as a novel set of biomarkers for PC therapy.

Pancreatic cancer detection with a non-contrast MR protocol: is it reliable?

PURPOSE

The pancreatic cancer (PC) is the 4th leading cancer-related death, becoming the second one by 2030, with a 5 year survival rate of 8%. Considering its increased incidence in high-risk categories compared to the general population, we aimed to validate a non-contrast MR protocol, to detect PC in its earliest phase, which could be suitable as a screening tool in high-risk patients.

MATERIALS AND METHODS

In this retrospective study, we selected 200 patients (> 40 years) from our radiological database, which performed upper abdominal MRI between 2012 and 2017. 100 were negative for pancreatic lesions and 100 positive for pancreatic lesion (< 30 mm). The latter group included: 40 PDAC (pancreatic adenocarcinoma), 42 BD-IPMN (Branch Duct- Intraductal Papillary Mucinous Neoplasm), 10 PNET(pancreatic neuroendocrine tumor), 4 SCN(serous cystic neoplasm), 3 IPS(intrapancreatic spleen), 1 MCN(mucinous cystic neoplasm). Three readers (R1, R2 and R3) with a high, medium and low experience, respectively, analysed, first, the non-contrast MR sequences (single-shot T2w breath-hold, GE T1w FS, DWI and 2D/3D MRCP), and then the standard MR protocol, independently, randomly and anonymously. Readers identified or excluded the presence of pancreatic lesion, in both reading sessions. These results were compared with the histopathological diagnosis, and then divided into 3 different classes of lesions: all lesions, pancreatic adenocarcinoma and solid lesion. Mcnemar's test was used to compare the results. The inter-observer agreement was determined according to the kappa statistic in both protocols, and then the inter-protocol agreement was calculated.

RESULTS

The non-contrast MR protocol has reached statistical parameters values ranging between 83% in SE (sensitivity) by R3 and 99% in NPV (negative predictive value) by R1. The standard MR protocol has reported slight increasing statistical parameters compared to those of the proposed one. However, there are not significant statistical differences between the both protocols. The proposed non-contrast MR protocol has reported the highest NPVs in the PDAC group detection (R1: 99%, R2: 99%, R3: 98%). In all groups of lesions, the agreement between the two protocols was excellent for each Reader ranging from 96 to 98%.

CONCLUSION

The proposed non-contrast MR protocol showed high PC detection values and a time execution ≤ 20 min. Therefore, it can be proposed as a screening tool in high-risk patients.

Ultrasensitive Detection and Separation of Pancreatic Cancer Biomarker CA 19-9 Using a Multiphoton Laser Wave-Mixing Detector Interfaced to Capillary Electrophoresis

The carbohydrate antigen 19-9 (CA 19-9) is the most commonly used biomarker in the clinical diagnosis of pancreatic cancer. Multiphoton nonlinear laser wave-mixing spectroscopy is presented as an ultrasensitive detection method for CA 19-9. Wave mixing is an optical absorption-based method, and hence, one can detect CA 19-9 without labels in their native form using compact ultraviolet (UV) lasers or labeled samples using a visible laser. The wave-mixing signal exhibits a quadratic dependence on the sample concentration, and hence, it is an ideal sensor to monitor small changes in the sample. Wave mixing has inherent advantages over other absorption-based detection methods, including short optical path length (micrometer-thin samples instead of 1 cm cuvette) and excellent spatial resolution (micrometer probe). Since the laser wave-mixing probe volume is small (picoliter), it is convenient to interface to microfluidics or capillary-based electrophoresis systems to enhance chemical specificity. Our wave-mixing detectors could be configured as portable battery-powered devices suitable for field use. Laser wave-mixing spectroscopy offers enhanced selectivity levels for protein detection when coupled with capillary electrophoresis (CE). We report a concentration detection limit of 0.16 U/mL, and a corresponding mass detection limit of 1.2 × 10-8 U, and these detection limits are better than those of chemiluminescence- or ELISA- based methods.

The Link between Diabetes, Pancreatic Tumors, and miRNAs-New Players for Diagnosis and Therapy?

Despite significant progress in medicine, pancreatic cancer is one of the most tardily diagnosed cancer and is consequently associated with a poor prognosis and a low survival rate. The asymptomatic clinical picture and the lack of relevant diagnostic markers for the early stages of pancreatic cancer are believed to be the major constraints behind an accurate diagnosis of this disease. Furthermore, underlying mechanisms of pancreatic cancer development are still poorly recognized. It is well accepted that diabetes increases the risk of pancreatic cancer development, however the precise mechanisms are weakly investigated. Recent studies are focused on microRNAs as a causative factor of pancreatic cancer. This review aims to provide an overview of the current knowledge of pancreatic cancer and diabetes-associated microRNAs, and their potential in diagnosis and therapy. miR-96, miR-124, miR-21, and miR-10a were identified as promising biomarkers for early pancreatic cancer prediction. miR-26a, miR-101, and miR-200b carry therapeutic potential, as they not only regulate significant biological pathways, including the TGF-β and PI3K/AKT, but their re-expression contributes to the improvement of the prognosis by reducing invasiveness or chemoresistance. In diabetes, there are also changes in the expression of microRNAs, such as in miR-145, miR-29c, and miR-143. These microRNAs are involved, among others, in insulin signaling, including IRS-1 and AKT (miR-145), glucose homeostasis (hsa-miR-21), and glucose reuptake and gluconeogenesis (miR-29c). Although, changes in the expression of the same microRNAs are observed in both pancreatic cancer and diabetes, they exert different molecular effects. For example, miR-181a is upregulated in both pancreatic cancer and diabetes mellitus, but in diabetes it contributes to insulin resistance, whereas in pancreatic cancer it promotes tumor cell migration, respectively. To conclude, dysregulated microRNAs in diabetes affect crucial cellular processes that are involved in pancreatic cancer development and progression.

Determination and characterization of molecular heterogeneity and precision medicine strategies of patients with pancreatic cancer and pancreatic neuroendocrine tumor based on oxidative stress and mitochondrial dysfunction-related genes

Background

Mitochondria are significant both for cellular energy production and reactive oxygen/nitrogen species formation. However, the significant functions of mitochondrial genes related to oxidative stress (MTGs-OS) in pancreatic cancer (PC) and pancreatic neuroendocrine tumor (PNET) are yet to be investigated integrally. Therefore, in pan-cancer, particularly PC and PNET, a thorough assessment of the MTGs-OS is required.

Methods

Expression patterns, prognostic significance, mutation data, methylation rates, and pathway-regulation interactions were studied to comprehensively elucidate the involvement of MTGs-OS in pan-cancer. Next, we separated the 930 PC and 226 PNET patients into 3 clusters according to MTGs-OS expression and MTGs-OS scores. LASSO regression analysis was utilized to construct a novel prognostic model for PC. qRT-PCR(Quantitative real-time PCR) experiments were performed to verify the expression levels of model genes.

Results

The subtype associated with the poorest prognosis and lowerest MTGs-OS scores was Cluster 3, which could demonstrate the vital function of MTGs-OS for the pathophysiological processes of PC. The three clusters displayed distinct variations in the expression of conventional cancer-associated genes and the infiltration of immune cells. Similar molecular heterogeneity was observed in patients with PNET. PNET patients with S1 and S2 subtypes also showed distinct MTGs-OS scores. Given the important function of MTGs-OS in PC, a novel and robust MTGs-related prognostic signature (MTGs-RPS) was established and identified for predicting clinical outcomes for PC accurately. Patients with PC were separated into the training, internal validation, and external validation datasets at random; the expression profile of MTGs-OS was used to classify patients into high-risk (poor prognosis) or low-risk (good prognosis) categories. The variations in the tumor immune microenvironment may account for the better prognoses observed in high-risk individuals relative to low-risk ones.

Conclusions

Overall, our study for the first time identified and validated eleven MTGs-OS remarkably linked to the progression of PC and PNET, and elaborated the biological function and prognostic value of MTGs-OS. Most importantly, we established a novel protocol for the prognostic evaluation and individualized treatment for patients with PC.

Potential of artificial intelligence in the risk stratification for and early detection of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is the third most lethal cancer in the United States, with a 5-year life expectancy of 11%. Most symptoms manifest at an advanced stage of the disease when surgery is no longer appropriate. The dire prognosis of PDAC warrants new strategies to improve the outcomes of patients, and early detection has garnered significant attention. However, early detection of PDAC is most often incidental, emphasizing the importance of developing new early detection screening strategies. Due to the low incidence of the disease in the general population, much of the focus for screening has turned to individuals at high risk of PDAC. This enriches the screening population and balances the risks associated with pancreas interventions. The cancers that are found in these high-risk individuals by MRI and/or EUS screening show favorable 73% 5-year overall survival. Even with the emphasis on screening in enriched high-risk populations, only a minority of incident cancers are detected this way. One strategy to improve early detection outcomes is to integrate artificial intelligence (AI) into biomarker discovery and risk models. This expert review summarizes recent publications that have developed AI algorithms for the applications of risk stratification of PDAC using radiomics and electronic health records. Furthermore, this review illustrates the current uses of radiomics and biomarkers in AI for early detection of PDAC. Finally, various challenges and potential solutions are highlighted regarding the use of AI in medicine for early detection purposes.

Recent Trends in Biosensing and Diagnostic Methods for Novel Cancer Biomarkers

Cancer is one of the major public health issues in the world. It has become the second leading cause of death, with approximately 75% of cancer deaths transpiring in low- or middle-income countries. It causes a heavy global economic cost estimated at more than a trillion dollars per year. The most common cancers are breast, colon, rectum, prostate, and lung cancers. Many of these cancers can be treated effectively and cured if detected at the primary stage. Nowadays, around 50% of cancers are detected at late stages, leading to serious health complications and death. Early diagnosis of cancer diseases substantially increases the efficient treatment and high chances of survival. Biosensors are one of the potential screening methodologies useful in the early screening of cancer biomarkers. This review summarizes the recent findings about novel cancer biomarkers and their advantages over traditional biomarkers, and novel biosensing and diagnostic methods for them; thus, this review may be helpful in the early recognition and monitoring of treatment response of various human cancers.

Multianalyte Serum Biomarker Panel for Early Detection of Pancreatic Adenocarcinoma

PURPOSE

We determined whether a large, multianalyte panel of circulating biomarkers can improve detection of early-stage pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

We defined a biologically relevant subspace of blood analytes on the basis of previous identification in premalignant lesions or early-stage PDAC and evaluated each in pilot studies. The 31 analytes that met minimum diagnostic accuracy were measured in serum of 837 subjects (461 healthy, 194 benign pancreatic disease, and 182 early-stage PDAC). We used machine learning to develop classification algorithms using the relationship between subjects on the basis of their changes across the predictors. Model performance was subsequently evaluated in an independent validation data set from 186 additional subjects.

RESULTS

A classification model was trained on 669 subjects (358 healthy, 159 benign, and 152 early-stage PDAC). Model evaluation on a hold-out test set of 168 subjects (103 healthy, 35 benign, and 30 early-stage PDAC) yielded an area under the receiver operating characteristic curve (AUC) of 0.920 for classification of PDAC from non-PDAC (benign and healthy controls) and an AUC of 0.944 for PDAC versus healthy controls. The algorithm was then validated in 146 subsequent cases presenting with pancreatic disease (73 benign pancreatic disease and 73 early- and late-stage PDAC cases) and 40 healthy control subjects. The validation set yielded an AUC of 0.919 for classification of PDAC from non-PDAC and an AUC of 0.925 for PDAC versus healthy controls.

CONCLUSION

Individually weak serum biomarkers can be combined into a strong classification algorithm to develop a blood test to identify patients who may benefit from further testing.

Genetics, Genomics and Emerging Molecular Therapies of Pancreatic Cancer

The number of cases of pancreatic cancers in 2019 in Poland was 3852 (approx. 2% of all cancers). The course of the disease is very fast, and the average survival time from the diagnosis is 6 months. Only <2% of patients live for 5 years from the diagnosis, 8% live for 2 years, and almost half live for only about 3 months. A family predisposition to pancreatic cancer occurs in about 10% of cases. Several oncogenes in which somatic changes lead to the development of tumours, including genes BRCA1/2 and PALB2, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1, are involved in pancreatic cancer. Between 4% and 10% of individuals with pancreatic cancer will have a mutation in one of these genes. Six percent of patients with pancreatic cancer have NTRK pathogenic fusion. The pathogenesis of pancreatic cancer can in many cases be characterised by homologous recombination deficiency (HRD)-cell inability to effectively repair DNA. It is estimated that from 24% to as many as 44% of pancreatic cancers show HRD. The most common cause of HRD are inactivating mutations in the genes regulating this DNA repair system, mainly BRCA1 and BRCA2, but also PALB2, RAD51C and several dozen others.

Biological and Clinical Impacts of Glucose Metabolism in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer type as it is prone to metastases and is difficult to diagnose at an early stage. Despite advances in molecular detection, its clinical prognosis remains poor and it is expected to become the second leading cause of cancer-related deaths. Approximately 85% of patients develop glucose metabolism disorders, most commonly diabetes mellitus, within three years prior to their pancreatic cancer diagnosis. Diabetes, or glucose metabolism disorders related to PDAC, are typically associated with insulin resistance, and beta cell damage, among other factors. From the perspective of molecular regulatory mechanisms, glucose metabolism disorders are closely related to PDAC initiation and development and to late invasion and metastasis. In particular, abnormal glucose metabolism impacts the nutritional status and prognosis of patients with PDAC. Meanwhile, preliminary research has shown that metformin and statins are effective for the prevention or treatment of malignancies; however, no such effect has been shown in clinical trials. Hence, the causes underlying these conflicting results require further exploration. This review focuses on the clinical significance of glucose metabolism disorders in PDAC and the mechanisms behind this relationship, while also summarizing therapeutic approaches that target glycolysis.

Clinical Prediction Models for Pancreatic Cancer in General and At-Risk Populations: A Systematic Review

INTRODUCTION

Identifying high-risk individuals using a risk prediction model could be a crucial first stage of screening pathways to improve the early detection of pancreatic cancer. A systematic review was conducted to critically evaluate the published primary literature on the development or validation of clinical risk prediction models for pancreatic cancer risk.

METHODS

MEDLINE, Embase, and Web of Science were searched for relevant articles from the inception of each database up to November 2021. Study selection and data extraction were conducted by 2 independent reviewers. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was applied to assess risk of bias.

RESULTS

In total, 33 studies were included, describing 38 risk prediction models. Excluding studies with an overlapping population, this study consist of 15,848,100 participants, of which 58,313 were diagnosed with pancreatic cancer. Eight studies externally validated their model, and 13 performed internal validation. The studies described risk prediction models for pancreatic cancer in the general population (n = 14), patients with diabetes (n = 8), and individuals with gastrointestinal (and other) symptoms (symptoms included abdominal pain, unexplained weight loss, jaundice, and change in bowel habits and indigestion; n = 11). The commonly used clinical risk factors in the model were cigarette smoking (n = 27), age (n = 25), diabetes history (n = 22), chronic pancreatitis (n = 18), and body mass index (n = 14). In the 25 studies that assessed model performance, C-statistics ranged from 0.61 to 0.98. Of the 33 studies included, 6 were rated as being at a low risk of bias based on PROBAST.

DISCUSSION

Many clinical risk prediction models for pancreatic cancer had been developed for different target populations. Although low risk-of-bias studies were identified, these require external validation and implementation studies to ensure that these will benefit clinical decision making.

Association between type 2 diabetes and 5-year overall survival in early-stage pancreatic cancer: a retrospective cohort study

Background

This study examined the association between type 2 diabetes mellitus (T2DM) and 5-year overall survival (OS) in patients with pancreatic cancer (PC).

Methods

This retrospective cohort study included patients diagnosed with stage I/II PC at Shengjing Hospital of China Medical University from January 2012 to December 2017. All patients had pancreatic ductal adenocarcinoma or its subtypes. The outcome was the 5-year OS rate based on data from the patient charts. Data analysis was performed using SPSS 22.0.

Results

A total of 238 patients were included: 72 with T2DM and 166 without T2DM. There were significant differences in blood glucose levels and OS between the two groups (all P < 0.05). The median OS was 11.4 (95% confidence interval CI [8.49-14.31]) months in the T2DM group and 16.3 (95% CI [12.44-20.16], P = 0.023) months in the non-T2DM group. After adjustment for confounders, T2DM was an independent factor affecting 5-year OS (P = 0.010). Compared with non-T2DM patients, T2DM patients had a higher risk of death (HR = 1.475, 95% CI [1.096-1.985]).

Conclusions

T2DM is associated with 5-year OS in patients with PC.

Accelerated Pancreatobiliary MRI for Pancreatic Cancer Surveillance in Patients With Pancreatic Cystic Neoplasms

BACKGROUND

Pancreatobiliary MRI is often recommended for patients at risk of developing pancreas cancer. But the surveillance MRI protocol has not yet been widely accepted.

PURPOSE

To establish an accelerated MRI protocol targeting the table time of 15 minutes for pancreatic cancer surveillance and test its performance in lesion characterization.

STUDY TYPE

Prospective.

POPULATION

A total of 30 participants were enrolled, who were undergoing follow-up care for intraductal papillary mucinous neoplasms or newly diagnosed pancreatic cysts (≥10 mm) and were scheduled for or had recently undergone contrast-enhanced CT (CECT).

FIELD STRENGTH/SEQUENCE

A 3 T; heavily T2WI, 3D MRCP, DWI, dynamic T1WI, two-point Dixon.

ASSESSMENT

In-room time and table time were measured. Seven radiologists independently reviewed image quality of MRI and then the presence of high-risk stigmata and worrisome features in addition to diagnostic confidence for accelerated MRI, CECT, and the noncontrast part of accelerated MRI (NC-MRI).

STATISTICAL ANALYSIS

Fisher's exact test was used for categorical variables and either the Student's t-test or Mann-Whitney test was performed for continuous variables. The generalized estimated equation was used to compare the diagnostic performance of examinations on a per-patient basis. Interobserver agreement was evaluated via Fleiss kappa. A P value of <0.05 was considered to be statistically significant.

RESULTS

The in-room time was 18.5 ± 2.6 minutes (range: 13.7-24.9) and the table time was 13.9 ± 1.9 minutes (range: 10.7-17.5). There was no significant difference between the diagnostic performances of the three examinations (pooled sensitivity: 75% for accelerated MRI and CECT, 68% for NC-MRI, P = 0.95), with the highest significant diagnostic confidence for accelerated MRI (4.2 ± 0.1). With accelerated MRI, the interobserver agreement was fair to excellent for high-risk stigmata (κ = 0.34-0.98).

DATA CONCLUSION

Accelerated MRI protocol affords a table time of 15 minutes, making it potentially suitable for cancer surveillance in patients at risk of developing pancreatic cancer.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY STAGE: 2.

Model-based screening for pancreatic cancer in Sweden

BACKGROUND

Detecting pancreatic cancer at an earlier stage may contribute to an increased survival. Patients with stage I pancreatic cancer have a 5-year survival rate of 36%, while stage IV patients have a 5-year survival rate of 1% in Sweden. Research into novel blood-based biomarkers for pancreatic cancer is highly intensive and innovative, but has yet to result in any routine screening test. The aim of this study was to evaluate the specificity and sensitivity of a hypothetical blood test for pancreatic cancer used for screening purposes and the economic aspects of testing.

METHOD

A model of a screening test was created, with varying specificity and sensitivity both set at 80%, 85%, 90%, 95% or 99% and applied to selected risk groups. Excessive costs of false positive screening outcomes, QALYs, ICERs and total costs were calculated.

RESULTS

Individuals with family history and genetic mutations associated with pancreatic cancer, new-onset diabetes ≥50 years of age and early symptoms had the highest positive predictive values and ICERs beneath the willingness-to-pay-level of EUR 100,000/QALY. Screening of the general population and smokers resulted in a high rate of false positive cases and extensive extra costs.

CONCLUSIONS

General screening for pancreatic cancer is not cost-effective, while screening of certain high-risk groups may be economically justified given the availability of a high-performing blood-based test.

Role of circulating exosomal biomarkers and their diagnostic accuracy in pancreatic cancer

Background and Aim

New biomarkers have the potential to facilitate early diagnosis of pancreatic cancer (PC). Circulating exosomes are cell-derived protein complexes containing RNA that can be used as indicators of cancer development. The aim of this review is to evaluate the current literature involving PC patient groups for highly accurate exosomal biomarkers.

Methods

The literature search followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eight-hundred and seventy-five studies were identified across various databases (Ovid MEDLINE, Embase, and Cochrane) published between 2009 and 2020. Nine studies fulfilled the inclusion criteria: human PC patients, diagnosis as outcome of interest, serum biomarker of exosomal content, reporting of diagnostic values, and disease progress. Area under the curve (AUC) of the exosomal biomarker was compared against that of CA19-9.

Results

Nine papers were reviewed for relevant outcomes based on the inclusion criteria. These studies involved 565 participants (331 PC, 234 controls; male/female ratio 1.21; mean age 64.1). Tumor staging was reported in all studies, with 45.6% of PC patients diagnosed with early-stage PC (T1-2). The mRNA panel (ARG1, CD63, CK18, Erbb3, GAPDH, H3F3A, KRAS, ODC1) and GPC 1 reported the highest performing sensitivity and specificity at 100% each. The microRNA panel (miR-10b, miR-21, miR-30c, miR-181a, and miR-let7a), mRNA panel (ARG1, CD63, CK18, Erbb3, GAPDH, H3F3A, KRAS, ODC1), and GPC 1 showed a perfect AUC of 1.0. Five studies compared the AUC of the exosomal biomarker against CA19-9, each being superior to that of CA19-9.

Conclusion

The potential of exosomal biomarkers remains promising in PC diagnosis. Standardization of future studies will allow for larger comparative analyses and overcoming contrasting findings.

Pancreatic Tumorigenesis: Precursors, Genetic Risk Factors and Screening

Pancreatic cancer (PC) is a highly malignant and aggressive tumor. Despite medical advancement, the silent nature of PC results in only 20% of all cases considered resectable at the time of diagnosis. It is projected to become the second leading cause in 2030. Most pancreatic cancer cases are diagnosed in the advanced stages. Such cases are typically unresectable and are associated with a 5-year survival of less than 10%. Although there is no guideline consensus regarding recommendations for screening for pancreatic cancer, early detection has been associated with better outcomes. In addition to continued utilization of imaging and conventional tumor markers, clinicians should be aware of novel testing modalities that may be effective for early detection of pancreatic cancer in individuals with high-risk factors. The pathogenesis of PC is not well understood; however, various modifiable and non-modifiable factors have been implicated in pancreatic oncogenesis. PC detection in the earlier stages is associated with better outcomes; nevertheless, most oncological societies do not recommend universal screening as it may result in a high false-positive rate. Therefore, targeted screening for high-risk individuals represents a reasonable option. In this review, we aimed to summarize the pathogenesis, genetic risk factors, high-risk population, and screening modalities for PC.

The molecular landscape of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is predicted to become the second leading cause of cancer-related mortality within the next decade, with limited effective treatment options and a dismal long-term prognosis for patients. Surgical resection of early, localised disease provides the only chance for potentially curative treatment; however, most patients with PDAC present with advanced disease and are not suitable for surgery. Genomic analyses of PDAC tumour lesions have identified a small number of recurrent alterations that are detected across most tumours, and beyond that a large number that either occur at a low (<5%) prevalence or are patient-specific in nature. This molecular heterogeneity has presented a significant challenge for the characterisation of tumour subtypes and effective molecular biomarkers, which have not yet manifested clinical benefits for diagnosis, treatment or prognosis in PDAC. These challenges are compounded by the overall lack of tumour biopsies for sequencing, the invasive nature of tissue sampling and the confounding effects of low tumour cellularity in many PDAC biopsy specimens, which have limited the applications of molecular profiling in unresectable patients and for longitudinal tumour monitoring. Further investigation into alternative sources of tumour analytes that can be sampled using minimally invasive methods and used to complement molecular analyses from tissue sequencing are required.

Rate of pancreatic cancer following a negative endoscopic ultrasound and associated factors

BACKGROUND : Data are limited regarding pancreatic cancer diagnosed following a pancreaticobiliary endoscopic ultrasound (EUS) that does not diagnose pancreatic cancer. We have studied the frequency of, and factors associated with, post-EUS pancreatic cancer (PEPC) and 1-year mortality. METHODS : Between 2010 and 2017, patients with pancreatic cancer and a preceding pancreaticobiliary EUS were identified in a national cohort using Hospital Episode Statistics. Patients with a pancreaticobiliary EUS 6-18 months before a later pancreatic cancer diagnosis were the PEPC cases; controls were those with pancreatic cancer diagnosed within 6 months of pancreaticobiliary EUS. Multivariable logistic regression models examined the factors associated with PEPC and a Cox regression model examined factors associated with 1-year cumulative mortality. RESULTS : 9363 pancreatic cancer patients were studied; 93.5 % identified as controls (men 53.2 %; median age 68 [interquartile range (IQR) 61-75]); 6.5 % as PEPC cases (men 58.2 %; median age 69 [IQR 61-77]). PEPC was associated with older age (≥ 75 years compared with < 65 years, odds ratio [OR] 1.42, 95 %CI 1.15-1.76), increasing co-morbidity (Charlson co-morbidity score > 5, OR 1.90, 95 %CI 1.49-2.43), chronic pancreatitis (OR 3.13, 95 %CI 2.50-3.92), and diabetes mellitus (OR 1.58, 95 %CI 1.31-1.90). Metal biliary stents (OR 0.57, 95 %CI 0.38-0.86) and EUS-FNA (OR 0.49, 95 %CI 0.41-0.58) were inversely associated with PEPC. PEPC was associated with a higher cumulative mortality at 1 year (hazard ratio 1.12, 95 %CI 1.02-1.24), with only 14 % of PEPC patients (95 %CI 12 %-17 %) having a surgical resection, compared with 21 % (95 %CI 20 %-22 %) of controls. CONCLUSIONS : PEPC occurred in 6.5 % of patients and was associated with chronic pancreatitis, older age, more co-morbidities, and specifically diabetes mellitus. PEPC was associated with a worse prognosis and lower surgical resection rates.

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

BACKGROUND & AIMS

Pancreatic ductal adenocarcinoma (PDAC) incidence is rising worldwide, and most patients present with an unresectable disease at initial diagnosis. Measurement of carbohydrate antigen 19-9 (CA19-9) levels lacks adequate sensitivity and specificity for early detection; hence, there is an unmet need to develop alternate molecular diagnostic biomarkers for PDAC. Emerging evidence suggests that tumor-derived exosomal cargo, particularly micro RNAs (miRNAs), offer an attractive platform for the development of cancer-specific biomarkers. Herein, genomewide profiling in blood specimens was performed to develop an exosome-based transcriptomic signature for noninvasive and early detection of PDAC.

METHODS

Small RNA sequencing was undertaken in a cohort of 44 patients with an early-stage PDAC and 57 nondisease controls. Using machine-learning algorithms, a panel of cell-free (cf) and exosomal (exo) miRNAs were prioritized that discriminated patients with PDAC from control subjects. Subsequently, the performance of the biomarkers was trained and validated in independent cohorts (n = 191) using quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays.

RESULTS

The sequencing analysis initially identified a panel of 30 overexpressed miRNAs in PDAC. Subsequently using qRT-PCR assays, the panel was reduced to 13 markers (5 cf- and 8 exo-miRNAs), which successfully identified patients with all stages of PDAC (area under the curve [AUC] = 0.98 training cohort; AUC = 0.93 validation cohort); but more importantly, was equally robust for the identification of early-stage PDAC (stages I and II; AUC = 0.93). Furthermore, this transcriptomic signature successfully identified CA19-9 negative cases (<37 U/mL; AUC = 0.96), when analyzed in combination with CA19-9 levels, significantly improved the overall diagnostic accuracy (AUC = 0.99 vs AUC = 0.86 for CA19-9 alone).

CONCLUSIONS

In this study, an exosome-based liquid biopsy signature for the noninvasive and robust detection of patients with PDAC was developed.

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.

Improved survival of non-small cell lung cancer patients after introducing patient navigation: A retrospective cohort study with propensity score weighted historic control

OnkoNetwork is a patient navigation program established in the Moritz Kaposi General Hospital to improve the timeliness and completeness of cancer investigations and treatment. The H2020 SELFIE consortium selected OnkoNetwork as a promising integrated care initiative in Hungary and conducted a multicriteria decision analysis based on health, patient experience, and cost outcomes. In this paper, a more detailed analysis of clinical impacts is provided in the largest subgroup, non-small cell lung cancer (NSCLC) patients. A retrospective cohort study was conducted, enrolling new cancer suspect patients with subsequently confirmed NSCLC in two annual periods, before and after OnkoNetwork implementation (control and intervention cohorts, respectively). To control for selection bias and confounding, baseline balance was improved via propensity score weighting. Overall survival was analyzed in univariate and multivariate weighted Cox regression models and the effect was further characterized in a counterfactual analysis. Our analysis included 123 intervention and 173 control NSCLC patients from early to advanced stage, with significant between-cohort baseline differences. The propensity score-based weighting resulted in good baseline balance. A large survival benefit was observed in the intervention cohort, and intervention was an independent predictor of longer survival in a multivariate analysis when all baseline characteristics were included (HR = 0.63, p = 0.039). When post-baseline variables were included in the model, belonging to the intervention cohort was not an independent predictor of survival, but the survival benefit was explained by slightly better stage distribution and ECOG status at treatment initiation, together with trends for broader use of PET-CT and higher resectability rate. In conclusion, patient navigation is a valuable tool to improve cancer outcomes by facilitating more timely and complete cancer diagnostics. Contradictory evidence in the literature may be explained by common sources of bias, including the wait-time paradox and adjustment to intermediate outcomes.

Exosomal DNAJB11 promotes the development of pancreatic cancer by modulating the EGFR/MAPK pathway

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with invasive and metastatic characteristics and poor prognosis. Intracellular protein homeostasis is associated with invasion and metastasis of pancreatic cancer, but the specific molecular mechanism remains unclear. Our previous studies have revealed that DNAJB11, a key protein in protein homeostasis, is secreted by exosomes in the supernatant of dissociated pancreatic cancer cells with high metastasis. The results from transcriptome sequencing and co-immunoprecipitation (Co-IP)-based liquid chromatography with tandem mass spectrometry (LC–MS/MS) showed that depletion of DNAJB11 levels could increase HSPA5 expression and induce endoplasmic reticulum stress through the PRKR-like endoplasmic reticulum kinase signaling pathway in pancreatic cancer cells. Furthermore, exosomal DNAJB11 promoted cell development of PC cells in vitro and in vivo. In addition, exosomal DNAJB11 could regulate the expression of EGFR and activate the downstream MAPK signaling pathway. Clinical blood samples were collected to evaluate the potential of exosome DNAJB11 as a diagnostic biomarker and therapeutic target for the treatment of pancreatic cancer. This study could provide a new theoretical basis and potential molecular targets for the treatment of pancreatic cancer.

Diagnostic value of serum carbohydrate antigen 19-9 in pancreatic cancer: a systematic review and meta-analysis

Carbohydrate antigen 19-9 (CA19-9) is the most widely used serum biomarker for detecting pancreatic cancer (PC). Since early diagnosis is important for improving PC prognosis, a comprehensive understanding of the diagnostic performance of CA19-9 is critical. This study focused on comprehensive evaluation of the efficacy of CA19-9 in PC diagnosis. Literature research was based on the seven databases. Studies released from January 2002 to January 2022 focused on the efficacy of CA19-9 in the detection of PC were included. Summarized sensitivity, specificity, and sROC/accuracy of discrimination (AUC) were estimated. Potential publication bias was measured with Funnel plot and Egger's test. Meta-regression was performed to detect possible causes of heterogeneity. Subgroup analysis was used to assess the diagnostic efficacy of CA19-9 under different conditions. The study is registered on PROSPERO (CRD42021253861). Seventy-nine studies containing 20 991 participants who met the criteria were included. The pooled sensitivity, specificity, and AUC of CA19-9 in diagnose PC were 72% (95% CI, 71-73%), 86% (95% CI, 85-86%), and 0.8474 (95% CI, 0.8272-0.8676). Subgroup analysis suggested that the diagnostic efficiency of CA19-9 in studies with healthy controls was the highest, followed by intraductal papillary mucinous neoplasm, in pancreatitis and diabetes were consistent with the overall result. Our analysis showed that serum CA19-9 had high and stable diagnostic efficacy for PC (not affected by diabetes). Subgroup analysis showed that serum CA19-9 yielded highest effectiveness in the diagnosis of pancreatic precancerous lesions, which indicated an irreplaceable clinical value in the early detection and warning value for PC.

METTL3 promotes the growth and metastasis of pancreatic cancer by regulating the m6A modification and stability of E2F5

BACKGROUND

Pancreatic cancer belongs to lethal cancer with limited efficient treatment currently, and its main cause of death is rapid tumor growth and early metastasis. N6-methyladenosine (m6A) modification is a new method of epigenetic gene regulation involved in tumor progression, in which methyltransferase-like 3(METTL3) is the sole catalytic subunit. However, the role of METTL3 in pancreatic cancer remains to be explored.

METHODS

m6A level was measured using MeRIP assay, and RT-qPCR and western blot were applied to determine mRNA and protein expression, respectively. Cellular behaviors were detected using CCK-8, EdU, wound healing and transwell assays. Xenograft assays were conducted to further verify the roles of METTL3 in pancreatic cancer.

RESULTS

METTL3 was highly expressed in pancreatic cancer. However, downregulation of METTL3 restrained the viability, migration and invasion of pancreatic cancer cells. Moreover, E2F5 was found to be positively regulated by METTL3. Intriguingly, the anti-tumor functions of METTL3 knockdown in the phenotype of pancreatic cancer cells were overturned by overexpression of E2F5. Silencing METTL3 resulted in the decreased stability of E2F5 by methylating E2F5.

CONCLUSIONS

In conclusion, METTL3 can promote the malignant progression of pancreatic cancer by modifying E2F5 through m6A methylation to promote its stability.

Circulating cancer-associated extracellular vesicles as early detection and recurrence biomarkers for pancreatic cancer

Early detection of pancreatic ductal adenocarcinoma (PDAC) is essential for improving patient survival rates, and non-invasive biomarkers are urgently required to identify patients who are eligible for curative surgery. Here, we examined extracellular vesicles (EVs) from the serum of PDAC patients to determine their ability to detect early-stage disease. EV-associated proteins purified by ultracentrifugation and affinity columns underwent proteomic analysis to identify novel PDAC markers G protein-coupled receptor class C group 5 member C (GPRC5C) and epidermal growth factor receptor pathway substrate 8 (EPS8). To verify the potency of GPRC5C- or EPS8-positive EVs as PDAC biomarkers, we analyzed EVs from PDAC patient blood samples using ultracentrifugation in two different cohorts (a total of 54 PDAC patients, 32 healthy donors, and 22 pancreatitis patients) by immunoblotting. The combination of EV-associated GPRC5C and EPS8 had high accuracy, with area under the curve (AUC) values of 0.922 and 0.946 for distinguishing early-stage PDAC patients from healthy controls in the two cohorts, respectively, and could detect PDAC patients who were negative for CA19-9. Moreover, we analyzed 30 samples taken at three time points from 10 PDAC patients who underwent surgery: before surgery, after surgery, and recurrence as an early-stage model. These proteins were detected in EVs derived from preoperative and recurrence samples. These results indicated that GPRC5C- or EPS8-positive EVs were biomarkers that have the potential to detect stage I early pancreatic cancer and small recurrent tumors detected by computed tomography.

Extracellular vesicle-derived microRNAs in pancreatic juice as biomarkers for detection of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is usually diagnosed in an advanced stage, with minimal likelihood of long-term survival. Only a small subset of patients are diagnosed with early (T1) disease. Early detection is challenging due to the late onset of symptoms and limited visibility of sub-centimeter cancers on imaging. A novel approach is to support the clinical diagnosis with molecular markers. MicroRNA derived from extracellular vehicles (EVs) in blood has shown promise as a potential biomarker for pancreatic neoplasia, but microRNA derived from pancreatic juice (PJ) may be a more sensitive biomarker, given that is in close contact with ductal cells from which PDAC arises. This study aims to evaluate and compare the performance of PJ- and serum-derived EV-miRNA for the detection of PDAC.

METHODS

PJ was collected from the duodenum during EUS after secretin stimulation from 54 patients with PDAC and 118 non-malignant controls. Serum was available for a subset of these individuals. MiR-16, miR-21, miR-25, miR-155 and miR-210 derived from EVs isolated from PJ and serum were analyzed by qPCR, and serum CA19-9 levels were determined by electrochemiluminescence immunoassay. For statistical analysis, either a Mann-Whitney U test or a Wilcoxon Signed Rank test was performed. ROC curves and AUC were used to assess the sensitivity and specificity of miR expression for PDAC detection.

RESULTS

Expression of EV-miR-21, EV-miR-25 and EV-miR-16 were increased in cases vs controls in PJ, while only EV-miR-210 was increased in serum. The potential to detect PC was good for a combination of PJ EV-miR-21, EV-miR-25, EV-miR-16 and serum miR-210, CA-19-9, with an area under the curve of 0.91, a specificity of 84.2% and a sensitivity of 81.5%.

CONCLUSION

Detection of miRNA from EVs in PJ is feasible. A combined panel of PJ EV-miR-21, EV-miR-25, EV-miR-16, and serum EV-miR-210 and CA19-9 distinguishes cases with PDAC from controls undergoing surveillance with a specificity of 81.5% and sensitivity of 84.2%.

Nanomedicine for overcoming therapeutic and diagnostic challenges associated with pancreatic cancer

Pancreatic cancer is the second leading cause of cancer-related death in the USA. The 5-year survival rate for pancreatic cancer is as low as 10%, making it one of the most deadly cancers. This dismal prognosis is caused, in part, by the lack of early detection and screening options, leading to late-stage detection of the disease, at a point at which chemotherapy is no longer effective. However, nanoparticle (NP) drug delivery systems have increased the efficacy of chemotherapeutics by improving the targeting ability of drugs to the tumor site, while also decreasing the risk of local and systemic toxicity. Such efforts can contribute to the development of early diagnosis and routine screening tests, which will drastically improve the survival rates and prognosis of patients with pancreatic cancer.

Healthcare use in the year preceding a diagnosis of pancreatic cancer: a register-based cohort study in Denmark

OBJECTIVE

To describe the use of healthcare prior to a diagnosis of pancreatic cancer in Denmark.

DESIGN

A population-based cohort study using prospectively recorded data from Danish National Health Registries.

SETTING

Danish general practice and hospitals.

SUBJECTS

A total of 5926 patients diagnosed with pancreatic cancer in 2012-2018 and 59,260 matched references without pancreatic cancer from the Danish general population.

MAIN OUTCOME MEASURES

The monthly frequency of healthcare use (contacts and tests in general practice and contacts and diagnostic investigations in hospitals) during the 12 months preceding the pancreatic cancer diagnosis and a corresponding index date assigned to the references.

RESULTS

Compared to the references, the patients had increased contacts and diagnostic tests, especially blood glucose testing, in general practice from 7 to 12 months before diagnosis. Hospital contacts and diagnostic imaging increased from 5 months before the diagnosis.

CONCLUSIONS

The pattern of increasing healthcare contacts before a diagnosis of pancreatic cancer may represent a window of opportunity to diagnose pancreatic cancer earlier. The increased use of blood glucose test in general practice may represent an important sign of an underlying disease. Key pointsPancreatic cancer is a rapidly progressing and highly lethal disease. Focus on early diagnosis is essential to improve the prognosis.Patients with pancreatic cancer had increased number of healthcare contacts from 7 months before the diagnosis.Patients with pancreatic cancer had increased number of blood glucose tests taken throughout almost the entire year before the diagnosis.The results may indicate that a window of opportunity exists to diagnose pancreatic cancer earlier.

Designing optimal allocations for cancer screening using queuing network models

Cancer is one of the leading causes of death, but mortality can be reduced by detecting tumors earlier so that treatment is initiated at a less aggressive stage. The tradeoff between costs associated with screening and its benefit makes the decision of whom to screen and when a challenge. To enable comparisons across screening strategies for any cancer type, we demonstrate a mathematical modeling platform based on the theory of queuing networks designed for quantifying the benefits of screening strategies. Our methodology can be used to design optimal screening protocols and to estimate their benefits for specific patient populations. Our method is amenable to exact analysis, thus circumventing the need for simulations, and is capable of exactly quantifying outcomes given variability in the age of diagnosis, rate of progression, and screening sensitivity and intervention outcomes. We demonstrate the power of this methodology by applying it to data from the Surveillance, Epidemiology and End Results (SEER) program. Our approach estimates the benefits that various novel screening programs would confer to different patient populations, thus enabling us to formulate an optimal screening allocation and quantify its potential effects for any cancer type and intervention.

We describe a mathematical modeling methodology that offers quantitative insights into the potential benefits of screening and other interventions on cancer mortality. Our queuing-theoretic approach represents a potentially useful alternative to more traditional modeling approaches, in that it can provide more detailed results and entirely circumvents the need for simulations. Our methodology can be widely applied to estimate costs and benefits of screening strategies. By providing a detailed example of our method applied to epidemiological data, we hope to encourage greater uptake of this methodology in the community.

Preoperative Serum Carbohydrate Antigen 19-9 Levels Cannot Predict the Surgical Resectability of Pancreatic Cancer: A Meta-Analysis

Background and Aims: Pancreatic ductal adenocarcinoma has one of the worst prognosis of all malignancies. This investigated the relationship between the preoperative serum carbohydrate antigen 19-9 and surgical resectability. Methods: A systematic search was performed in three databases (MEDLINE, EMBASE, and Web of Science) to compare the surgical resectability of pancreatic ductal adenocarcinoma in patients with high and low preoperative serum carbohydrate antigen 19-9 values. The receiving operating characteristic curves were constructed and the weighted mean differences for preoperative serum carbohydrate antigen 19-9 levels of resectable and unresectable groups of patients were calculated. The PROSPERO registration number is CRD42019132522. Results: Results showed that there was a significant difference in resectability between the low and high carbohydrate antigen 19-9 groups. Six out of the eight studies utilised receiver operating characteristic curves in order to find the cut-off preoperative carbohydrate antigen 19-9 levels marking unresectability. The overall result from the pooled area under curve values from the receiver operating characteristic curves was 0.794 (CI: 0.694-0.893), showing that the preoperative carbohydrate antigen 19-9 level is a "fair" marker of resectability. The result of the pooled weighted mean differences was 964 U/ml (p < 0.001) showing that there is a significant carbohydrate antigen 19-9 difference between the resectable and unresectable groups. Based on the results of the I-squared test, the result was 87.4%, accounting for "considerable" heterogeneity within the population. Conclusion: Carbohydrate antigen 19-9 is not a reliable marker of unresectability, it should not be used on its own in surgical decision-making.

A Computational Approach to Justifying Stratifin as a Candidate Diagnostic and Prognostic Biomarker for Pancreatic Cancer

Pancreatic cancer (PC) is considered a silent killer because it does not show specific symptoms at an early stage. Thus, identifying suitable biomarkers is important to avoid the burden of PC. Stratifin (SFN) encodes the 14-3-3σ protein, which is expressed in a tissue-dependent manner and plays a vital role in cell cycle regulation. Thus, SFN could be a promising therapeutic target for several types of cancer. This study was aimed at investigating, using online bioinformatics tools, whether SFN could be used as a diagnostic and prognostic biomarker in PC. SFN expression was explored by utilizing the ONCOMINE, UALCAN, GEPIA2, and GENT2 tools, which revealed that SFN expression is higher in PC than in normal tissues. The clinicopathological analysis using the ULCAN tool showed that the intensity of SFN expression is commensurate with cancer progression. GEPIA2, R2, and OncoLnc revealed a negative correlation between SFN expression and survival probability in PC patients. The ONCOMINE, UCSC Xena, and GEPIA2 tools showed that cofilin 1 is strongly coexpressed with SFN. Moreover, enrichment and network analyses of SFN were performed using the Enrichr and NetworkAnalyst platforms, respectively. Receiver operating characteristic (ROC) curves revealed that tissue-dependent expression of the SFN gene could serve as a diagnostic and prognostic biomarker. However, further wet laboratory studies are necessary to determine the relevance of SFN expression as a biomarker.

Considerations for Germline Testing in Melanoma: Updates in Behavioral Change and Pancreatic Surveillance for Carriers of CDKN2A Pathogenic Variants

The largest proportion of hereditary melanoma cases are due to pathogenic variants (PVs) in the CDKN2A/p16 gene, which account for 20%-40% of familial melanomas and confer up to a 30%-70% lifetime risk for melanoma in individuals with these variants. In addition, PVs in the CDKN2A gene also increase risk for pancreatic cancer (~5-24% lifetime risk). Individuals with PVs in the CDKN2A gene also tend to have an earlier onset of cancer. Despite these known risks, uptake of germline testing has been limited in the past, largely due to perceptions of limited benefit for patients. Prevention recommendations have been developed for individuals with CDKN2A PVs as well the providers who care for them. On the patient level, behavioral modifications regarding melanoma prevention such as wearing sunscreen, limiting prolonged sun exposure and practicing general sun safety can help reduce risks. Germline testing can provide motivation for some individuals to adhere to these lifestyle changes. On the provider level, pancreatic cancer surveillance for individuals with CDKN2A PVs has been increasingly endorsed by expert consensus, although the efficacy of these surveillance methods remains under study. This review summarizes the updated surveillance guidelines for individuals with CDKN2A PVs and explores the impact of genetic counseling and testing in influencing behavioral changes in these individuals.

Diagnosing Pancreatic Adenocarcinoma With Contrast-Enhanced Ultrasonography: A Literature Review of Research in Europe and Asia

The National Cancer Institute names pancreatic cancer the 11^th most common type of cancer in the United States. However, even with a somewhat low prevalence, in 2017, the American Cancer Society reported pancreatic cancer as the fourth leading cause of cancer-related death. With a lack of symptomology and a broad range of risk factors, pancreatic cancer is frequently diagnosed in a later phase than many other types of cancers, thus resulting in higher metastasis along with a poorer prognosis. This highlights the need for early detection and diagnosis. Currently, abdominal ultrasound or contrast-enhanced CT imaging of the abdomen are standard of care. A new technology: contrast-enhanced ultrasound (CEUS), which employs contrast agents to act as acoustic enhancers for ultrasound, has FDA approval for use in hepatic and renal lesions, but not pancreatic. By examining seven individual studies from Europe and Asia, this review aims to examine the diagnostic value of CEUS to initially diagnose pancreatic adenocarcinomas, potentially followed by a biopsy to confirm, when compared against modalities currently used such as conventional ultrasound and CT imaging. CEUS would potentially be more accurate when compared to conventional ultrasound due to the addition of contrast, and when compared against CT and MRI, CEUS would be advantageous in its low cost, similar sensitivities, and specificities, limited renal toxicity, lack of ionizing radiation, short half-life, and its safe use in both adult and pediatric patients. Due to this, additional research is warranted for further FDA approval and future clinical implementation.