Total pancreatectomy, splenectomy and remnant gastrectomy for invasive intraductal papillary mucinous neoplasm (IPMN) after prior Roux-en-Y gastric bypass.

A female patient in her 50s presented with abdominal pain, nausea and jaundice. She had a history of prior Roux-en-Y gastric bypass and her body mass index was 52.5 kg/m2 Biochemical testing revealed a total bilirubin level of 14.3 mg/dL (normal<1.2 mg/dL) and carbohydrate antigen 19-9 of 38.3 units/mL (normal<36.0 units/mL). CT demonstrated a 3.2 cm pancreatic head mass, biliary and pancreatic duct dilation and cystic replacement of the pancreas. The findings were consistent with a diagnosis of mixed-type intraductal papillary mucinous neoplasm (IPMN) with invasive malignancy. The patient's Roux-en-Y anatomy precluded endoscopic biopsy, and she underwent upfront resection with diagnostic laparoscopy, open total pancreatectomy, splenectomy and remnant gastrectomy with reconstruction. Pathology confirmed T2N1 pancreatic adenocarcinoma, 1/29 lymph nodes positive and diffuse IPMN. She completed adjuvant chemotherapy. IPMNs have malignant potential and upfront surgical resection should be considered without biopsy in the appropriate clinical setting.

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC. SIGNIFICANCE: PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.

Studying the impact of marital status on diagnosis and survival prediction in pancreatic ductal carcinoma using machine learning methods.

Pancreatic cancer is a commonly occurring malignant tumor, with pancreatic ductal carcinoma (PDAC) accounting for approximately 95% of cases. According of its poor prognosis, identifying prognostic factors of pancreatic ductal carcinoma can provide physicians with a reliable theoretical foundation when predicting patient survival. This study aimed to analyze the impact of marital status on survival outcomes of PDAC patients using propensity score matching and machine learning. The goal was to develop a prognosis prediction model specific to married patients with PDAC. We extracted a total of 206,968 patient records of pancreatic cancer from the SEER database. To ensure the baseline characteristics of married and unmarried individuals were balanced, we used a 1:1 propensity matching score. We then conducted Kaplan-Meier analysis and Cox proportional-hazards regression to examine the impact of marital status on PDAC survival before and after matching. Additionally, we developed machine learning models to predict 5-year CSS and OS for married patients with PDAC specifically. In total, 24,044 PDAC patients were included in this study. After 1:1 propensity matching, 8043 married patients and 8,043 unmarried patients were successfully enrolled. Multivariate analysis and the Kaplan-Meier curves demonstrated that unmarried individuals had a poorer survival rate than their married counterparts. Among the algorithms tested, the random forest performed the best, with 0.734 5-year CSS and 0.795 5-year OS AUC. This study found a significant association between marital status and survival in PDAC patients. Married patients had the best prognosis, while widowed patients had the worst. The random forest is a reliable model for predicting survival in married patients with PDAC.

A Current Synopsis of the Emerging Role of Extracellular Vesicles and Micro-RNAs in Pancreatic Cancer: A Forward-Looking Plan for Diagnosis and Treatment.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies worldwide, while it persists as the fourth most prevalent cause of cancer-related death in the United States of America. Although there are several novel therapeutic strategies for the approach of this intensely aggressive tumor, it remains a clinical challenge, as it is hard to identify in early stages, due to its asymptomatic course. A diagnosis is usually established when the disease is already in its late stages, while its chemoresistance constitutes an obstacle to the optimal management of this malignancy. The discovery of novel diagnostic and therapeutic tools is considered a necessity for this tumor, due to its low survival rates and treatment failures. One of the most extensively investigated potential diagnostic and therapeutic modalities is extracellular vesicles (EVs). These vesicles constitute nanosized double-lipid membraned particles that are characterized by a high heterogeneity that emerges from their distinct biogenesis route, their multi-variable sizes, and the particular cargoes that are embedded into these particles. Their pivotal role in cell-to-cell communication via their cargo and their implication in the pathophysiology of several diseases, including pancreatic cancer, opens new horizons in the management of this malignancy. Meanwhile, the interplay between pancreatic carcinogenesis and short non-coding RNA molecules (micro-RNAs or miRs) is in the spotlight of current studies, as they can have either a role as tumor suppressors or promoters. The deregulation of both of the aforementioned molecules leads to several aberrations in the function of pancreatic cells, leading to carcinogenesis. In this review, we will explore the role of extracellular vesicles and miRNAs in pancreatic cancer, as well as their potent utilization as diagnostic and therapeutic tools.

Electrochemiluminescence biosensor for specific detection of pancreatic ductal carcinoma through dual targeting of MUC1 and miRNA-196a.

Pancreatic ductal adenocarcinoma (PDAC) poses significant diagnostic challenges due to its asymptomatic nature in its early stages, low specificity of conventional in vitro assays, and limited efficacy of surgical interventions. However, clinical specificity of the current serum biomarkers is suboptimal, leading to diagnostic inaccuracies and oversights. Therefore, this study introduced a novel dual-target electrochemiluminescence (ECL) biosensor to address these critical issues. The ECL biosensor synergistically employs the serum biomarker MUC1 and microRNA-196a to detect early-stage PDAC precisely. While MUC1 is a differential marker between normal and cancerous pancreatic cells, its standalone diagnostic performance is limited. However, integrating miRNA-196a as a complementary marker substantially enhances the specificity of the assay. This biosensor exhibits distinct ECL signal modulation-"on-off" in the presence of MUC1 and "off-on" upon concurrent detection of MUC1 and miRNA-196a. The biosensor achieves remarkably low limits of detection (LODs) at 0.63 fg mL-1 and 4.57 aM for MUC1 and miRNA-196a, respectively. Thus, it facilitates the real-time differentiation between human normal pancreatic (hTERT-HPNE) and pancreatic cancer (PANC-1) cells in authentic biological matrices. This innovative approach heralds a significant advancement in the early and specific detection of PDAC, offering promising prospects for clinical translation and the broader landscape of cancer diagnostics.

Intratumoral T-cell receptor repertoire composition predicts overall survival in patients with pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy that is refractory to immune checkpoint inhibitor therapy. However, intratumoral T-cell infiltration correlates with improved overall survival (OS). Herein, we characterized the diversity and antigen specificity of the PDAC T-cell receptor (TCR) repertoire to identify novel immune-relevant biomarkers. Demographic, clinical, and TCR-beta sequencing data were collated from 353 patients across three cohorts that underwent surgical resection for PDAC. TCR diversity was calculated using Shannon Wiener index, Inverse Simpson index, and "True entropy." Patients were clustered by shared repertoire specificity. TCRs predictive of OS were identified and their associated transcriptional states were characterized by single-cell RNAseq. In multivariate Cox regression models controlling for relevant covariates, high intratumoral TCR diversity predicted OS across multiple cohorts. Conversely, in peripheral blood, high abundance of T-cells, but not high diversity, predicted OS. Clustering patients based on TCR specificity revealed a subset of TCRs that predicts OS. Interestingly, these TCR sequences were more likely to encode CD8+ effector memory and CD4+ T-regulatory (Tregs) T-cells, all with the capacity to recognize beta islet-derived autoantigens. As opposed to T-cell abundance, intratumoral TCR diversity was predictive of OS in multiple PDAC cohorts, and a subset of TCRs enriched in high-diversity patients independently correlated with OS. These findings emphasize the importance of evaluating peripheral and intratumoral TCR repertoires as distinct and relevant biomarkers in PDAC.

Nomogram model for predicting early recurrence for resectable pancreatic cancer: A multicenter study.

Pancreatic cancer is a highly aggressive malignancy that is characterized by early metastasis, high recurrence, and therapy resistance. Early recurrence after surgery is one of the important reasons affecting the prognosis of pancreatic cancer. This study aimed to establish an accurate preoperative nomogram model for predicting early recurrence (ER) for resectable pancreatic adenocarcinoma. We retrospectively analyzed patients who underwent pancreatectomy for pancreatic ductal adenocarcinoma between January 2011 and December 2020. The training set consisted of 604 patients, while the validation set included 222 patients. Survival was estimated using Kaplan-Meier curves. The factors influencing early recurrence of resectable pancreatic cancer after surgery were investigated, then the predictive model for early recurrence was established, and subsequently the predictive model was validated based on the data of the validation group. The preoperative risk factors for ER included a Charlson age-comorbidity index ≥ 4 (odds ratio [OR]: 0.628), tumor size > 3.0 cm on computed tomography (OR: 0.628), presence of clinical symptoms (OR: 0.515), carbohydrate antigen 19-9 > 181.3 U/mL (OR 0.396), and carcinoembryonic antigen > 6.01 (OR: 0.440). The area under the curve (AUC) of the predictive model in the training group was 0.711 (95% confidence interval: 0.669-0.752), while it reached 0.730 (95% CI: 0.663-0.797) in the validation group. The predictive model may enable the prediction of the risk of postoperative ER in patients with resectable pancreatic ductal adenocarcinoma, thereby optimizing preoperative decision-making for effective treatment.

Unraveling the potential of CD8, CD68, and VISTA as diagnostic and prognostic markers in patients with pancreatic ductal adenocarcinoma.

Introduction: Pancreatic cancer is a truculent disease with limited treatment options and a grim prognosis. Immunotherapy has shown promise in treating various types of cancer, but its effectiveness in pancreatic cancer has been lacking. As a result, it is crucial to identify markers associated with immunological pathways in order to improve the treatment outcomes for this deadly cancer. The purpose of this study was to investigate the diagnostic and prognostic significance of three markers, CD8, CD68, and VISTA, in pancreatic ductal adenocarcinoma (PDAC), the most common subtype of pancreatic cancer. Methods: We analyzed gene expression data from Gene Expression Omnibus (GEO) database using bioinformatics tools. We also utilized the STRING online tool and Funrich software to study the protein-protein interactions and transcription factors associated with CD8, CD68, and VISTA. In addition, tissue microarray (TMA) and immunohistochemistry (IHC) staining were performed on 228 samples of PDAC tissue and 10 samples of normal pancreatic tissue to assess the expression levels of the markers. We then correlated these expression levels with the clinicopathological characteristics of the patients and evaluated their survival rates. Results: The analysis of the GEO data revealed slightly elevated levels of VISTA in PDAC samples compared to normal tissues. However, there was a significant increase in CD68 expression and a notable reduction in CD8A expression in pancreatic cancer. Further investigation identified potential protein-protein interactions and transcription factors associated with these markers. The IHC staining of PDAC tissue samples showed an increased expression of VISTA, CD68, and CD8A in pancreatic cancer tissues. Moreover, we found correlations between the expression levels of these markers and certain clinicopathological features of the patients. Additionally, the survival analysis revealed that high expression of CD8 was associated with better disease-specific survival and progression-free survival in PDAC patients. Conclusion: These findings highlight the potential of CD8, CD68, and VISTA as diagnostic and prognostic indicators in PDAC.

MicroRNA Signatures for Pancreatic Cancer and Chronic Pancreatitis: Expression Profiling by NGS.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease due to the lack of early detection. Because chronic pancreatitis (CP) patients are a high-risk group for pancreatic cancer, this study aimed to assess the differential miRNA profile in pancreatic tissue of patients with CP and pancreatic cancer. METHODS: MiRNAs were isolated from formalin-fixed paraffin-embedded pancreatic tissue of 22 PDAC patients, 18 CP patients, and 10 normal pancreatic tissues from autopsy (C) cases and processed for next-generation sequencing. Known and novel miRNAs were identified and analyzed for differential miRNA expression, target prediction, and pathway enrichment between groups. RESULTS: Among the miRNAs identified, 166 known and 17 novel miRNAs were found exclusively in PDAC tissues, while 106 known and 10 novel miRNAs were found specifically in CP tissues. The pathways targeted by PDAC-specific miRNAs and differentially expressed miRNAs between PDAC versus CP tissues and PDAC versus control tissues were the proteoglycans pathway, Hippo signaling pathway, adherens junction, and transforming growth factor-ß signaling pathway. CONCLUSIONS: This study resulted in a set of exclusive and differentially expressed miRNAs in PDAC and CP can be assessed for their diagnostic value. In addition, studying the role of miRNA-target gene interactions in carcinogenesis may open new therapeutic avenues.

Inhibition of the Alternative Complement Pathway May Cause Secretion of Factor B, Enabling an Early Detection of Pancreatic Cancer.

This study aims to elucidate the cellular mechanisms behind the secretion of complement factor B (CFB), known for its dual roles as an early biomarker for pancreatic ductal adenocarcinoma (PDAC) and as the initial substrate for the alternative complement pathway (ACP). Using parallel reaction monitoring analysis, we confirmed a consistent ∼2-fold increase in CFB expression in PDAC patients compared with that in both healthy donors (HD) and chronic pancreatitis (CP) patients. Elevated ACP activity was observed in CP and other benign conditions compared with that in HD and PDAC patients, suggesting a functional link between ACP and PDAC. Protein-protein interaction analyses involving key complement proteins and their regulatory factors were conducted using blood samples from PDAC patients and cultured cell lines. Our findings revealed a complex control system governing the ACP and its regulatory factors, including Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation, adrenomedullin (AM), and complement factor H (CFH). Particularly, AM emerged as a crucial player in CFB secretion, activating CFH and promoting its predominant binding to C3b over CFB. Mechanistically, our data suggest that the KRAS mutation stimulates AM expression, enhancing CFH activity in the fluid phase through binding. This heightened AM-CFH interaction conferred greater affinity for C3b over CFB, potentially suppressing the ACP cascade. This sequence of events likely culminated in the preferential release of ductal CFB into plasma during the early stages of PDAC. (Data set ID PXD047043.).

Quantitative Metabolomics and Lipoprotein Analysis of PDAC Patients Suggests Serum Marker Categories for Pancreatic Function, Pancreatectomy, Cancer Metabolism, and Systemic Disturbances.

Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose in the early stages and lacks reliable biomarkers. The scope of this project was to establish quantitative nuclear magnetic resonance (NMR) spectroscopy to comprehensively study blood serum alterations in PDAC patients. Serum samples from 34 PDAC patients obtained before and after pancreatectomy as well as 83 age- and sex-matched control samples from healthy donors were analyzed with in vitro diagnostics research (IVDr) proton NMR spectroscopy at 600 MHz. Uni- and multivariate statistics were applied to identify significant biofluid alterations. We identified 29 significantly changed metabolites and 98 lipoproteins when comparing serum from healthy controls with those of PDAC patients. The most prominent features were assigned to (i) markers of pancreatic function (e.g., glucose and blood triglycerides), (ii) markers related to surgery (e.g., ketone bodies and blood cholesterols), (iii) PDAC-associated markers (e.g., amino acids and creatine), and (iv) markers for systemic disturbances in PDAC (e.g., gut metabolites DMG, TMAO, DMSO2, and liver lipoproteins). Quantitative serum NMR spectroscopy is suited as a diagnostic tool to investigate PDAC. Remarkably, 2-hydroxybutyrate (2-HB) as a previously suggested marker for insulin resistance was found in extraordinarily high levels only after pancreatectomy, suggesting this metabolite is the strongest marker for pancreatic loss of function.

A Randomized Trial of Two Remote Health Care Delivery Models on the Uptake of Genetic Testing and Impact on Patient-Reported Psychological Outcomes in Families With Pancreatic Cancer: The Genetic Education, Risk Assessment, and Testing (GENERATE) Study.

BACKGROUND & AIMS: Genetic testing uptake for cancer susceptibility in family members of patients with cancer is suboptimal. Among relatives of patients with pancreatic ductal adenocarcinoma (PDAC), The GENetic Education, Risk Assessment, and TEsting (GENERATE) study evaluated 2 online genetic education/testing delivery models and their impact on patient-reported psychological outcomes. METHODS: Eligible participants had ≥1 first-degree relative with PDAC, or ≥1 first-/second-degree relative with PDAC with a known pathogenic germline variant in 1 of 13 PDAC predisposition genes. Participants were randomized by family, between May 8, 2019, and June 1, 2021. Arm 1 participants underwent a remote interactive telemedicine session and online genetic education. Arm 2 participants were offered online genetic education only. All participants were offered germline testing. The primary outcome was genetic testing uptake, compared by permutation tests and mixed-effects logistic regression models. We hypothesized that Arm 1 participants would have a higher genetic testing uptake than Arm 2. Validated surveys were administered to assess patient-reported anxiety, depression, and cancer worry at baseline and 3 months postintervention. RESULTS: A total of 424 families were randomized, including 601 participants (n = 296 Arm 1; n = 305 Arm 2), 90% of whom completed genetic testing (Arm 1 [87%]; Arm 2 [93%], P = .014). Arm 1 participants were significantly less likely to complete genetic testing compared with Arm 2 participants (adjusted ratio [Arm1/Arm2] 0.90, 95% confidence interval 0.78-0.98). Among participants who completed patient-reported psychological outcomes questionnaires (Arm 1 [n = 194]; Arm 2 [n = 206]), the intervention did not affect mean anxiety, depression, or cancer worry scores. CONCLUSIONS: Remote genetic education and testing can be a successful and complementary option for delivering genetics care. (Clinicaltrials.gov, number NCT03762590).

A liquid biomarker signature of inflammatory proteins accurately predicts early pancreatic cancer progression during FOLFIRINOX chemotherapy.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is often treated with FOLFIRINOX, a chemotherapy associated with high toxicity rates and variable efficacy. Therefore, it is crucial to identify patients at risk of early progression during treatment. This study aims to explore the potential of a multi-omics biomarker for predicting early PDAC progression by employing an in-depth mathematical modeling approach. METHODS: Blood samples were collected from 58 PDAC patients undergoing FOLFIRINOX before and after the first cycle. These samples underwent gene (GEP) and inflammatory protein expression profiling (IPEP). We explored the predictive potential of exclusively IPEP through Stepwise (Backward) Multivariate Logistic Regression modeling. Additionally, we integrated GEP and IPEP using Bayesian Kernel Regression modeling, aiming to enhance predictive performance. Ultimately, the FOLFIRINOX IPEP (FFX-IPEP) signature was developed. RESULTS: Our findings revealed that proteins exhibited superior predictive accuracy than genes. Consequently, the FFX-IPEP signature consisted of six proteins: AMN, BANK1, IL1RL2, ITGB6, MYO9B, and PRSS8. The signature effectively identified patients transitioning from disease control to progression early during FOLFIRINOX, achieving remarkable predictive accuracy with an AUC of 0.89 in an independent test set. Importantly, the FFX-IPEP signature outperformed the conventional CA19-9 tumor marker. CONCLUSIONS: Our six-protein FFX-IPEP signature holds solid potential as a liquid biomarker for the early prediction of PDAC progression during toxic FOLFIRINOX chemotherapy. Further validation in an external cohort is crucial to confirm the utility of the FFX-IPEP signature. Future studies should expand to predict progression under different chemotherapies to enhance the guidance of personalized treatment selection in PDAC.

Extracellular Vesicular Analysis of Glypican 1 mRNA and Protein for Pancreatic Cancer Diagnosis and Prognosis.

Detecting pancreatic duct adenocarcinoma (PDAC) in its early stages and predicting late-stage patient prognosis undergoing chemotherapy is challenging. This work shows that the activation of specific oncogenes leads to elevated expression of mRNAs and their corresponding proteins in extracellular vesicles (EVs) circulating in blood. Utilizing an immune lipoplex nanoparticle (ILN) biochip assay, these findings demonstrate that glypican 1 (GPC1) mRNA expression in the exosomes-rich (Exo) EV subpopulation and GPC1 membrane protein (mProtein) expression in the microvesicles-rich (MV) EV subpopulation, particularly the tumor associated microvesicles (tMV), served as a viable biomarker for PDAC. A combined analysis effectively discriminated early-stage PDAC patients from benign pancreatic diseases and healthy donors in sizable clinical from multiple hospitals. Furthermore, among late-stage PDAC patients undergoing chemotherapy, lower GPC1 tMV-mProtein and Exo-mRNA expression before treatment correlated significantly with prolonged overall survival. These findings underscore the potential of vesicular GPC1 expression for early PDAC screenings and chemotherapy prognosis.

Optimal Surveillance Interval of Branch Duct Intraductal Papillary Mucinous Neoplasm of the Pancreas.

Importance: Despite the increasing prevalence of intraductal papillary mucinous neoplasm (IPMN), data on the growth and malignant conversion rates based on long-term surveillance cohorts are limited. Many international guidelines recommend surveillance for benign lesions, but the optimal interval and duration are unclear. Objective: To determine the optimal surveillance protocol for IPMN and propose which patients may be exempted from surveillance. Design, Setting, and Participants: This large-scale, international cohort study examined data of 3825 patients with IPMN treated at 5 tertiary pancreatic centers. Included were patients with branch duct (BD) IPMN who underwent surveillance or surgery between January 1, 1988, and December 31, 2020. After a thorough review, 3656 patients were included in the analytic sample. Changes in cyst size, worrisome features or high-risk stigmata, and malignant conversion rates were assessed. Patients who underwent surveillance over 5 years were compared to suggest discontinuation of surveillance protocol. Clinical data collection began in January 1, 2021, and the mean (SD) follow-up duration was 84 (47.7) months. The data analysis was performed from May 2, 2022, through September 14, 2022. Exposure: The patients with BD-IPMN were followed up based on International Association of Pancreatology guidelines. Patients with suspicious malignant neoplasms during surveillance underwent surgical resection. Main Outcome and Measures: The main outcome of this study was the optimal follow-up interval and duration of BD-IPMN surveillance. The association among cyst size, growth rate, and progression was examined using descriptive statistics. Results: Of the 3656 patients with BD-IPMN in the analytic sample (1973 [54.0%] female; mean [SD] age, 63.7 [10.2] years), 172 (4.7%) were confirmed to have malignant lesions through surgery. Considering cyst growth, the time to develop worrisome features, and malignant conversion, a 1.5-, 1-, and 0.5-year surveillance interval could be optimal for cysts smaller than 20 mm, 20 to 30 mm, and 30 mm, respectively, after initial short-term (6-month) follow-up. Patients with cysts smaller than 20 mm, no worrisome features, and no growth during 5-year surveillance did not show malignant conversion after 5 years of follow-up and had time to progression of greater than 10 years. Conclusions: These findings suggest that BD-IPMN surveillance may depend on the size of the cyst and morphologic changes at the initial 6-month follow-up. For patients with small cysts (ie, <20 mm) with no morphologic changes during the initial 5-year surveillance period, surveillance may be discontinued for those unfit for surgery or who have a limited life expectancy of 10 years or less.

A novel method for detection of pancreatic Ductal Adenocarcinoma using explainable machine learning.

BACKGROUND AND OBJECTIVE: Pancreatic Ductal Adenocarcinoma (PDAC) is a form of pancreatic cancer that is one of the primary causes of cancer-related deaths globally, with less than 10 % of the five years survival rate. The prognosis of pancreatic cancer has remained poor in the last four decades, mainly due to the lack of early diagnostic mechanisms. This study proposes a novel method for detecting PDAC using explainable and supervised machine learning from Raman spectroscopic signals. METHODS: An insightful feature set consisting of statistical, peak, and extended empirical mode decomposition features is selected using the support vector machine recursive feature elimination method integrated with a correlation bias reduction. Explicable features successfully identified mutations in Kirsten rat sarcoma viral oncogene homolog (KRAS) and tumor suppressor protein53 (TP53) in the fingerprint region for the first time in the literature. PDAC and normal pancreas are classified using K-nearest neighbor, linear discriminant analysis, and support vector machine classifiers. RESULTS: This study achieved a classification accuracy of 98.5% using a nonlinear support vector machine. Our proposed method reduced test time by 28.5 % and saved 85.6 % memory utilization, which reduces complexity significantly and is more accurate than the state-of-the-art method. The generalization of the proposed method is assessed by fifteen-fold cross-validation, and its performance is evaluated using accuracy, specificity, sensitivity, and receiver operating characteristic curves. CONCLUSIONS: In this study, we proposed a method to detect and define the fingerprint region for PDAC using explainable machine learning. This simple, accurate, and efficient method for PDAC detection in mice could be generalized to examine human pancreatic cancer and provide a basis for precise chemotherapy for early cancer treatment.

Contributions of the Microbiome-Derived Metabolome for Risk Assessment and Prognostication of Pancreatic Cancer.

BACKGROUND: Increasing evidence implicates microbiome involvement in the development and progression of pancreatic ductal adenocarcinoma (PDAC). Studies suggest that reflux of gut or oral microbiota can lead to colonization in the pancreas, resulting in dysbiosis that culminates in release of microbial toxins and metabolites that potentiate an inflammatory response and increase susceptibility to PDAC. Moreover, microbe-derived metabolites can exert direct effector functions on precursors and cancer cells, as well as other cell types, to either promote or attenuate tumor development and modulate treatment response. CONTENT: The occurrence of microbial metabolites in biofluids thereby enables risk assessment and prognostication of PDAC, as well as having potential for design of interception strategies. In this review, we first highlight the relevance of the microbiome for progression of precancerous lesions in the pancreas and, using liquid chromatography-mass spectrometry, provide supporting evidence that microbe-derived metabolites manifest in pancreatic cystic fluid and are associated with malignant progression of intraductal papillary mucinous neoplasm(s). We secondly summarize the biomarker potential of microbe-derived metabolite signatures for (a) identifying individuals at high risk of developing or harboring PDAC and (b) predicting response to treatment and disease outcomes. SUMMARY: The microbiome-derived metabolome holds considerable promise for risk assessment and prognostication of PDAC.

Cyfra 21.1: A Useful Tumour Marker in Pancreatic Ductal Adenocarcinoma: Cross-Sectional Study.

BACKGROUND: Pancreatic cancer is a challenging disease, often requiring invasive procedures for diagnosis. Reliable tumour markers are essential for ensuring early detection and better patient outcomes. Although Carbohydrate Antigen 19-9 is the most commonly used marker, it is marred by low predictive accuracy and high false positivity. Carcino Embryonic Antigen also has limited practical use. A novel antigen, Cytokeratin fragment 21-1, is gaining significance for its diagnostic value in various tumours. MATERIALS AND METHODS: This prospective study aimed to evaluate the potential of Cytokeratin fragment 21-1 in comparison with Carbohydrate Antigen 19-9 and Carcino Embryonic Antigen in diagnosing pancreatic cancer. From January 2016 to December 2019, 45 patients with confirmed pancreatic ductal adenocarcinoma were included in this cross-sectional study. RESULTS: Carbohydrate Antigen 19-9 was raised in 22 patients, Carcino Embryonic Antigen was elevated in 17, and Cytokeratin fragment 21-1 was elevated in 30 cases. Carbohydrate Antigen 19-9 was found to be elevated in the presence of jaundice. Both Carbohydrate Antigen 19-9 and Cytokeratin fragment 21-1 had good correlation with stage of cancer, while Carcino Embryonic Antigen had very minimal correlation. CONCLUSION: In this study, Cytokeratin fragment 21-1 was elevated in a higher number of cases than Carbohydrate Antigen 19-9 and Carcino Embryonic Antigen. Both Cytokeratin fragment 21-1 and Carbohydrate Antigen 19-9 correlated well with cancer stage. Also Cytokeratin fragment 21-1 was not affected by jaundice, unlike Carbohydrate Antigen 19-9. Therefore, Cytokeratin fragment 21-1 has the potential to be an effective individual tumour marker in pancreatic cancer.

Effect of body fat mass loss on prognosis of radical resection for pancreatic ductal adenocarcinoma based on bioelectrical impedance analysis.

BACKGROUND: Few reports have performed a prognostic analysis based on bioelectrical impedance analysis in patients with radical resection of pancreatic ductal adenocarcinoma (PDAC), and its usefulness in prognostic analysis remains unclear. This study aimed to evaluate body composition changes in patients undergoing radical resection for PDAC and analyze its impact on prognosis. METHODS: The medical records of radical resection for patients with PDAC were retrospectively reviewed, and the parameters of body composition, including body weight, skeletal muscle mass, body fat mass (BFM), and extracellular water-total body water ratio, from preoperatively to 12 months postoperatively, for each surgical procedure were measured based on direct segmental multifrequency bioelectrical impedance analysis with an InBody 770 (InBody Inc., Tokyo, Japan) device. The clinicopathological and prognostic factors were analyzed. RESULTS: Among 79 patients who underwent radical resection for PDAC, 36 (46%), 7 (8%), and 36 (46%) underwent pancreatoduodenectomy, total pancreatectomy, and distal pancreatectomy, respectively. The multivariate overall survival analysis demonstrated that BFM loss percentage at 1 month postoperatively ≧14% (p = 0.021), lymph node metastasis (p = 0.014), and non-adjuvant chemotherapy (p <  0.001) were independent poor prognostic factors. Multivariate analysis revealed that preoperative BFM < 12 kg and preoperative albumin < 3.5 g/dL were independently associated with BFM loss percentage at 1 month postoperatively ≧14% (p = 0.021 and p = 0.047, respectively). CONCLUSIONS: Loss of BFM in the early postoperative period may have a poor prognosis in radical resection of PDAC.

[Histopathologic diagnosis of solid and cystic pancreatic lesions with a focus on ductal adenocarcinoma : A vademecum for daily practice]. / Histopathologische Diagnostik von soliden und zystischen Pankreasläsionen mit Hauptaugenmerk auf dem duktalen Adenokarzinom : Ein Vademecum für den Alltag.

Pancreas pathology is constantly evolving and can present various challenges for pathologists. This paper is focused on providing helpful hints for daily routine diagnostics. During histopathological analysis of pancreas biopsies, pancreatic ductal adenocarcinoma must be distinguished not only from other solid neoplasms, but especially from its mimicker, autoimmune pancreatitis. This can be achieved by a systematic workup following clear diagnostic criteria. When analyzing samples from cystic pancreatic lesions, mucin-producing neoplasms must be detected due to their role as pancreatic cancer precursors; molecular analyses can help considerably with their detection and distinction. During frozen section examination, evaluation of the pancreatic neck margin and analysis of unclear lesions of the liver are two important tasks, which are explained further in this article. A special challenge is the evaluation of neoadjuvant treated pancreatic cancer, which requires a detailed macroscopic and microscopic workup. Finally, current advances in precision oncology and emerging approaches for pancreatic cancer within this field are discussed. With the advancement of technical possibilities and their increasingly broad implementation, the classification systems in pancreatic pathology will continue to gain in complexity, but also in accuracy.