Early Detection Of Pancreatic Ductal Adenocarcinoma Research Articles

Case Study on Analysing the Early Disease Detection of Pancreatic Ductal Adenocarcinoma in Korean Association for Clinical Oncology.

Pancreatic ductal adenocarcinoma (PDAC) is the most pervasive sort of pancreatic malignant growth. Due to the lack of early symptoms and effective methods for early detection and screening, the majority of patients (80% to 85%) are diagnosed with advanced metastatic or locally advanced disease, resulting in a low 5-year survival rate of 12%. The case study represents a comprehensive investigation into the intricate landscape of pancreatic cancer diagnosis within the Korean population. Grounded in epidemiological bits of knowledge, the review plans to disentangle the particular examples, commonness, and segment attributes of PDAC in Korea. By scrutinizing current diagnostic modalities, including conventional imaging techniques, molecular markers, and emerging technologies, the research seeks to evaluate the strengths and limitations of existing approaches within the Korean clinical context. Central to the study is an exploration of the collaborative initiatives spearheaded by the Association of Clinical Oncology in Korea in the domain of PDAC early detection. Analysing research projects, clinical trials, and interdisciplinary collaborations, the case study sheds light on the association's pivotal role in driving innovation and progress in oncology. The goal is to offer a detailed analysis of how the association helps in furthering knowledge and enhancing results in the management of PDAC. The case study delves into the implications of early PDAC detection for patient outcomes, emphasizing the significance of timely interventions and tailored treatment strategies. By outlining the potential benefits and challenges associated with early diagnosis, the study aims to inform health care policies, shape clinical guidelines, and guide future research priorities. Through a holistic approach, the case study endeavours to offer important experiences into the multifaceted landscape of PDAC early detection within the Korean health care system, contributing to the broader discourse on effective oncological practices and patient care.

Power-Doppler-based NH002 microbubble sonoporation with chemotherapy relieves hypoxia and enhances the efficacy of chemotherapy and immunotherapy for pancreatic tumors

Pancreatic ductal adenocarcinoma (PDAC) poses challenges due to late-stage diagnosis and limited treatment response, often attributed to the hypoxic tumor microenvironment (TME). Sonoporation, combining ultrasound and microbubbles, holds promise for enhancing therapy. However, additional preclinical research utilizing commercially available ultrasound equipment for PDAC treatment while delving into the TME's intricacies is necessary. This study investigated the potential of using a clinically available ultrasound system and phase 2-proven microbubbles to relieve tumor hypoxia and enhance the efficacy of chemotherapy and immunotherapy in a murine PDAC model. This approach enables early PDAC detection and blood-flow-sensitive Power-Doppler sonoporation in combination with chemotherapy. It significantly extended treated mice's median survival compared to chemotherapy alone. Mechanistically, this combination therapy enhanced tumor perfusion and substantially reduced tumor hypoxia (77% and 67%, 1- and 3-days post-treatment). Additionally, cluster of differentiation 8 (CD8) T-cell infiltration increased four-fold afterward. The combined treatment demonstrated a strengthening of the anti-programmed death-ligand 1(αPDL1) therapy against PDAC. Our study illustrates the feasibility of using a clinically available ultrasound system with NH-002 microbubbles for early tumor detection, alleviating hypoxic TME, and improving chemotherapy and immunotherapy. It suggests the development of an adjuvant theragnostic protocol incorporating Power-Doppler sonoporation for pancreatic tumor treatment.

Development of a multi-analyte blood test for the early detection of pancreatic ductal adenocarcinoma (PDAC) and performance compared to CA19-9.

e16360 Background: Early detection of PDAC can improve survival but is hampered by the lack of recognizable symptoms in early disease. Imaging has been the mainstay for surveillance of high-risk individuals but has proven to be cumbersome and may lack sensitivity to detect small tumors. CA19-9 is the only available blood biomarker for PDAC, but it is neither sensitive nor specific enough for it to be recommended for high-risk surveillance. A sensitive and specific blood biomarker for PDAC could positively impact this situation. Methods: Serum samples from patients across multiple centers with stage I and II PDAC (n = 75) and matched controls at high risk for PDAC (genetic and familial) (n = 83) were assessed for more than 2,900 protein analytes using O-link multiplex technology and conventional immunoassays for selected protein candidates. Machine learning was used to combine the biomarker candidates to create 4-plex signatures discriminating PDAC and controls. Results: ROC (receiver operating characteristic) curve analysis of these revealed signatures with performance superior to CA19-9 and a previously commercially available assay, IMMRay PanCan-d (AUC of 0.97 and 0.94 vs. 0.87 for CA19-9 and 0.88 for IMMRay). A subset of these candidate biomarkers has now been transitioned to standardized ELISA assays which are being used to construct a final signature for clinical validation in an independent set of PDAC and high-risk control samples. Conclusions: A novel multi-analyte blood test utilizing newly-discovered PDAC biomarkers has the potential to improve early detection of PDAC in high-risk individuals.

Early detection of pancreatic cancer in the era of precision medicine.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related mortality and it is often diagnosed at advanced stages due to non-specific clinical presentation. Disease detection at localized disease stage followed by surgical resection remains the only potentially curative treatment. In this era of precision medicine, a multifaceted approach to early detection of PDAC includes targeted screening in high-risk populations, serum biomarkers and "liquid biopsies", and artificial intelligence augmented tumor detection from radiologic examinations. In this review, we will review these emerging techniques in the early detection of PDAC.

The scRNA-sequencing landscape of pancreatic ductal adenocarcinoma revealed distinct cell populations associated with tumor initiation and progression

Pancreatic ductal adenocarcinoma (PDAC) stands as a formidable malignancy characterized by its profound lethality. The comprehensive analysis of the transcriptional landscape holds immense significance in understanding PDAC development and exploring novel treatment strategies. However, due to the firm consistency of pancreatic cancer samples, the dissociation of single cells and subsequent sequencing can be challenging. Here, we performed single-cell RNA sequencing (scRNA-seq) on 8 PDAC patients with different lymph node metastasis status. We first identified the crucial role of MMP1 in the transition from normal pancreatic cells to cancer cells. The knockdown of MMP1 in pancreatic cancer cell lines decreased the expression of ductal markers such as SOX9 while the overexpression of MMP1 in hTERT-HPNE increased the expression of ductal markers, suggesting its function of maintaining ductal identity. Secondly, we found a S100A2+ tumor subset which fueled lymph node metastasis in PDAC. The knockdown of S100A2 significantly reduced the motility of pancreatic cancer cell lines in both wound healing and transwell migration assays. While overexpression of S100A2 led to increased migratory capability. Moreover, overexpression of S100A2 in KPC1199, a mouse pancreatic cancer cell line, caused a larger tumor burden in a hemi-spleen injection model of liver metastasis. In addition, epithelial-mesenchymal transition-related genes were decreased by S100A2 knockdown revealed by bulk RNA sequencing. We also identified several pivotal contributors to the pro-tumor microenvironment, notably OMD+ fibroblast and CCL2+ macrophage. As a result, our study provides valuable insights for early detection of PDAC and promising therapeutic targets for combatting lymph node metastasis.

The Potential of Fecal and Urinary Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: A Systematic Review.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer often diagnosed at advanced stages, highlighting the urgent need for early detection strategies. This systematic review explores the potential of fecal and urinary biomarkers for early PDAC detection. A comprehensive search identified eight relevant studies investigating various biomarkers, including proteins, metabolites, microbial profiles, DNA mutations, and non-coding RNAs. Promising findings suggest that urinary biomarkers related to metabolic alterations, inflammatory processes, fecal microbiome profiles, and fecal miRNAs hold diagnostic potential even at early stages of PDAC. Combining biomarkers into panels may enhance diagnostic accuracy. Challenges such as validation in larger cohorts, standardization of protocols, and regulatory approval must be addressed for clinical translation. Despite these hurdles, non-invasive urinary and fecal biomarkers represent a promising avenue for improving PDAC outcomes through early detection.

Excavation of gene markers associated with pancreatic ductal adenocarcinoma based on interrelationships of gene expression.

Pancreatic ductal adenocarcinoma (PDAC) accounts for 95% of all pancreatic cancer cases, posing grave challenges to its diagnosis and treatment. Timely diagnosis is pivotal for improving patient survival, necessitating the discovery of precise biomarkers. An innovative approach was introduced to identify gene markers for precision PDAC detection. The core idea of our method is to discover gene pairs that display consistent opposite relative expression and differential co-expression patterns between PDAC and normal samples. Reversal gene pair analysis and differential partial correlation analysis were performed to determine reversal differential partial correlation (RDC) gene pairs. Using incremental feature selection, the authors refined the selected gene set and constructed a machine-learning model for PDAC recognition. As a result, the approach identified 10 RDC gene pairs. And the model could achieve a remarkable accuracy of 96.1% during cross-validation, surpassing gene expression-based models. The experiment on independent validation data confirmed the model's performance. Enrichment analysis revealed the involvement of these genes in essential biological processes and shed light on their potential roles in PDAC pathogenesis. Overall, the findings highlight the potential of these 10 RDC gene pairs as effective diagnostic markers for early PDAC detection, bringing hope for improving patient prognosis and survival.

Abstract 1021: Defining total protease activity profiles in pancreatic cancer using a FRET substrate array

Abstract Proteases are an important component of many biological processes in the human body, and as such makes them a well-known subject to explore when investigating a variety of disease states from cancer to cardiovascular disease. In all stages of cancer, including early development, proteases play critical roles in almost every aspect for processes such as invasion, promotion of tumor growth, and metastasis. This makes screening of circulating proteases a potentially powerful tool for early detection and prognosis for a variety of cancers. The human proteome, however, is very complex, with around 600 proteases in total, and at least 234 of them found in circulation. Additionally, proteases often act on more than one substrate, cross reactively cleaving several substrates at different rates, further adding to the complexity of cleavage patterns of the human proteome. Previous liquid biopsies for cancer detection based on protease cleavage patterns focused mainly on detecting the activities of specific proteases, using single substrates to examine the effects of well-studied cancer-related proteases such as MMPs and cathepsins. In this study, we developed a method for screening cleavage patterns of proteases active in plasma samples that deviated from this norm. Due to the complexity of the human proteome, rather than developing a specific substrate for a specific protease, we utilized a large array of substrates to screen for cleavage patterns in plasma samples of cancer patients aimed at not one specific protease, but a wide range that may be present. In this proof of concept study, we used a commercially available internally quenched set of 360 substrates composed of 8 amino acids and a FRET pair. Initially, we optimized this assay to measure protease activity in the complex plasma environment. Next, we screened several plasma samples collected from patients with pancreatic ductal adenocarcinoma (PDAC) or pancreatitis, and screen negative samples using the 360 substrate set assay and identified 5 top substrates that were proficient in identifying PDAC from other conditions. Finally, we performed a validation study with a larger cohort (45 screen negative, 26 PDAC, 19 pancreatitis) using the selected substrates to determine the diagnostic performance of the assay. All five of the selected substrates showed 1.3-1.8-fold increase in fluorescence signal in PDAC compared to screen negative and pancreatitis. Amongst the cancer samples, the substrates showed no significant difference between stage, supporting possible applications for early detection. Additionally, area under the curve analysis of the five substrates gave a score of 0.8. In summary, in this study, we reported a novel approach for the detection of cancer exploiting the protease cleavage patterns in plasma samples. We believe that this approach holds great potential for detecting substrates and proteases for early detection of PDAC and other cancers. Citation Format: Morgan Stewart, Arnaud Quentel, Jose Montoya Mira, Elise Manalo-Hall, Srivathsan Ranganathan, Bruce Branchaud, Fehmi Civitci, Eugene Tu, Jared Fischer, Yu-Jui Chiu, Adem Yildirim. Defining total protease activity profiles in pancreatic cancer using a FRET substrate array [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1021.

Abstract 2445: Peripheral blood immune phenotypes in pancreatic ductal adenocarcinoma

Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a major cancer killer with a low 5-year survival rate of 12%. Diagnosing PDAC at an early stage is one of the strongest predictors of long-term survival. Therefore, novel methods for early detection of PDAC must be explored. In this pilot study we aimed to compare the peripheral blood immune cell phenotypes in PDAC cases and cancer-free controls. Method: CyTOF (cytometry by time-of-flight) was used to evaluate peripheral blood mononuclear cells (PBMC) from newly diagnosed treatment naïve patients with PDAC and sex and age matched cancer-free controls using a 29-marker immune phenotyping panel. Multiple analysis approaches including dimensionality reduction using tSNE and clustering using Phenograph were used to evaluate the results. Immune subsets having differential abundance differences were verified by manual gating. Results: Twenty patients were included in this pilot study (15 PDAC cases; 5 Cancer-free controls). Among the 15 PDAC cases, 5 were early stage (Stage 1-2). Thirty-two unique immune cell clusters were identified using the Phenograph algorithm: 10 unique clusters with properties consistent with monocytes/macrophages, 9 CD4 T cell clusters, 6 CD8 T cell clusters and 4 NK cells clusters. When comparing the case and control groups we noted lower percentages of CD8+CD27+ T-cells in cases. This was further verified by manual gating that confirmed the distribution of CD8+CD27+ T-cells relative to all T-cells were decreased in PDAC patients. In addition, a 57% increase in naïve CD4 T cells was found in case samples compared to controls. A principal component analysis of the clustering results identified two unique clusters of immune profiles that emerged providing a potential peripheral blood immune cell signature that could stratify and differentiate PDAC cases from controls. A CD14+CD16+CD4LoCD38+CD45RO+ population of monocytes was the primary cell population driving this difference. Conclusion: This study provides early evidence to indicate that a distinct PBMC immune phenotype may differentiate PDAC patients from control subjects. Further analysis in larger sample sets is warranted for in-depth characterization and identification of unique immune based biomarkers for PDAC detection. Citation Format: Kevin D. Pavelko, Jose C. Villasboas, William R. Taylor, Karen A. Doering, John B. Kisiel, Shounak Majumder. Peripheral blood immune phenotypes in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2445.

Abstract 1074: Plasma EV profiling facilitates low abundance biomarker discovery in pancreatic cancer

Abstract The lack of reliable biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) results in poor prognosis due to advanced disease at diagnosis. Biopsies for pancreatic cancer are known to be particularly difficult to perform because of the location of the pancreas and low volume of primary tumors that metastasize aggressively. Currently, there is no blood test or other screening modality in use, for stratification of individuals with higher-than-average risk (5-8-fold) of developing PDAC in their lifetime. Given this existing void in the US and worldwide, an FDA-compliant, minimally invasive, quantitative biomarker test for the early detection of PDAC would be critical for screening subpopulations with, a) inherent genetic or familial predisposition; history of chronic pancreatitis; c) precursor lesions of pancreas; and d) older patients (>50 years) with new onset diabetes or sudden weight loss. Extracellular vesicles (EVs) are shed by normal and cancer cells and carry a rich molecular cargo that can be leveraged for biomarker discovery. Whereas molecular profiling of bio-fluids poses intrinsic limitations for detection of low abundant, disease-specific biomarkers due to matrix effects; EVs, on the other hand, offer promise as a robust and minimally invasive biomarker resource. Mass spectrometry data were developed in our laboratory, based on multi-omics (proteomics, lipidomics and metabolomics) analyses of plasma EVs derived from patients diagnosed with early-stage PC (N=60), pancreatitis (N=39), precursor lesions of pancreas (N=45) as well as normal controls (N=50). These clinically annotated samples were made available by the Georgetown University Medical Center (GUMC) repository. Feature selection using a training-validation design allowed the development of a multiplexed biomarker panel comprising of 12-analytes (5-lipids, 2-metabolites and 5-proteins) that can robustly stratify early-stage PC from normal controls with high accuracy (AUC>95%). Availability of a FDA compliant, multi-analyte-based classification algorithm that can stratify patients with precursor lesions of the pancreas that are at potential risk of progression to PC with > 90% specificity and sensitivity is a critical clinical need. Refinement of panel to improve positive predictive value as well as identification of markers predictive of progression of precursor lesions to malignant transformation is ongoing. Citation Format: Shivani Bansal, Shu Wang, Yaoxiang Li, Sunil Bansal, Jill Smith, John B. Tyburski, Keith Unger, Amrita Cheema. Plasma EV profiling facilitates low abundance biomarker discovery in pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1074.

Temporal progression of pancreatic cancer computed tomography findings until diagnosis: A large-scale multicenter study.

Focal parenchymal atrophy and main pancreatic duct (MPD) dilatation have been identified as early signs of pancreatic ductal adenocarcinoma. However, limited evidence exists regarding their temporal progression due to previous study limitations with restricted case numbers. To ascertain a more precise frequency assessment of suspicious pancreatic ductal adenocarcinoma findings as well as delineate the temporal progression of them. A multicenter retrospective study was conducted on patients diagnosed with pancreatic ductal adenocarcinoma between 2015 and 2021. We included patients who had undergone at least one computed tomography (CT) scan ≥6months before diagnosing pancreatic ductal adenocarcinoma. The temporal progression of suspicious pancreatic ductal adenocarcinoma findings on CT was investigated. Out of 1832 patients diagnosed with pancreatic ductal adenocarcinoma, 320 had a previous CT before their diagnosis. Suspicious pancreatic ductal adenocarcinoma findings were detected in 153 cases (47.8%), with focal parenchymal atrophy (26.6%) being the most common followed by MPD dilatation (11.3%). Focal parenchymal atrophy was the earliest detectable sign among all suspicious findings and became visible on average 2.7years before diagnosis, and the next most common, MPD dilatation, 1.1years before diagnosis. Other findings, such as retention cysts, were less frequent and appeared around 1year before diagnosis. Focal parenchymal atrophy followed by MPD dilatation was observed in 10 patients but not in reverse order. Focal parenchymal atrophy was more frequently detected in the pancreatic body/tail. No significant relationship was found between the pathological pancreatic ductal adenocarcinoma differentiation or tumor stage and the time course of the CT findings. All cases of focal parenchymal atrophy progressed just prior to diagnosis, and the atrophic area was occupied by tumor at diagnosis. Main pancreatic duct dilatation continued to progress until diagnosis. This large-scale study revealed that the temporal progression of focal parenchymal atrophy is the earliest detectable sign indicating pancreatic ductal adenocarcinoma. These results provide crucial insights for early pancreatic ductal adenocarcinoma detection.

MicroRNA-20a in extracellular vesicles derived from duodenal fluid is a possible biomarker for pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) has a high mortality rate owing to its late diagnosis and aggression. In addition, there are relatively few minimally invasive screening methods for the early detection of PDAC, making the identification of biomarkers for this disease a critical priority. Recent studies have reported that microRNAs in extracellular vesicles (EV-miRs) from bodily fluids can be useful for the diagnosis of PDACs. Given this, we designed this study to evaluate the utility of cancer EVs extracted from duodenal fluid (DF) and their resident EV-miRs as potential biomarkers for the detection of PDAC. EV-miRs were evaluated and identified in the supernatants of various pancreatic cancer cell lines (Panc-1, SUIT2, and MIAPaca2), human pancreatic duct epithelial cells, and the DF from patients with PDAC and healthy controls. EVs were extracted using ultracentrifugation and the relative expression of EV-miR-20a was quantified. We collected a total of 34 DF samples (27 PDAC patients and seven controls) for evaluation and our data suggest that the relative expression levels of EV-miR-20a were significantly higher in patients with PDAC than in controls (p = 0.0025). In addition, EV-miR-20a expression could discriminate PDAC from control patients regardless of the location of the tumor with an area under the curve values of 0.88 and 0.88, respectively. We confirmed the presence of EVs in the DF and suggest that the expression of EV-miR-20a in these samples may act as a potential diagnostic biomarker for PDAC.

Prevención y detección precoz del cáncer de páncreas

In western countries, pancreatic ductal adenocarcinoma (PDAC) has shown a rising incidence and is currently one of the leading causes of cancer related mortality. Due to its aggressive biology, most patients diagnosed with PDAC present with advanced disease not suitable for curative treatment. An early detection strategy could potentially improve results by detecting more PDAC patients within the initial stages of the disease.Currently, diagnosis of PDAC is mostly based in cross sectional imaging, including computed tomography and magnetic resonance imaging (MRI) as well as biomarkers such as CA 19-9. Selected cases might be further studied using endoscopic ultrasound (EUS) with the option of EUS guided biopsy if histology is needed to confirm diagnosis.Due to its low incidence, screening general population for PDAC has been shown to be an ineffective and expensive approach. For this reason, efforts have shifted towards surveillance of specific groups of patients known to be at risk for development of PDAC. In these groups, screening has shown to have a higher yield for early cases and improved results in terms of resection rates and survival. These groups include carriers of certain oncogenic germline mutations, patients with strong family history for PDAC, and patients diagnosed with mucinous cystic neoplasms of the pancreas. Patients over 50 years old diagnosed with new-onset diabetes and patients living with chronic pancreatitis are also considered to be at risk for PDAC development. Patients selected for surveillance should be included in screening protocols including periodic imaging with MRI or EUS.Development of biomarkers is an area of active research in the field of pancreatic cancer. New genetic or molecular biomarkers, to be measured in an isolated or combined manner, are an interesting approach looking to improve current diagnostic capabilities and to provide new tools for effective screening in wider groups of patients.The aim of this article is to describe strategies currently available for early detection of PDAC, including promising research areas for the near future.

Emerging Horizons in the Diagnosis of Pancreatic Cancer: The Role of Circulating microRNAs as Early Detection Biomarkers for Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with a poor prognosis, primarily due to a late diagnosis. Recent studies have focused on identifying non-invasive biomarkers for early detection, with microRNAs (miRNAs) emerging as promising candidates. This systematic review aims to evaluate the potential of circulating miRNAs as biomarkers for the early detection of PDAC, analyzing their diagnostic accuracy, specificity, and sensitivity. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search across PubMed, Embase, and the Cochrane Library was conducted. Studies published from January 2013 to October 2023 focusing on miRNA biomarkers for early PDAC detection were included. Data synthesis was performed through a narrative approach due to the heterogeneity of the studies. Nine studies met the inclusion criteria. Key findings include the elevated levels of specific miRNAs, such as miR-18a, miR-106a, and miR-25, in early-stage PDAC patients compared to controls. The integration of miRNA profiles with traditional biomarkers like CA19-9 showed improved diagnostic performance. However, challenges in the standardization of miRNA evaluation methodologies were noted. Circulating miRNAs demonstrate significant potential as non-invasive biomarkers for early PDAC detection. Despite promising results, further research and standardization are necessary for clinical application.

Identifying Symptoms Prior to Pancreatic Ductal Adenocarcinoma Diagnosis in Real-World Care Settings: Natural Language Processing Approach.

Pancreatic cancer is the third leading cause of cancer deaths in the United States. Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, accounting for up to 90% of all cases. Patient-reported symptoms are often the triggers of cancer diagnosis and therefore, understanding the PDAC-associated symptoms and the timing of symptom onset could facilitate early detection of PDAC. This paper aims to develop a natural language processing (NLP) algorithm to capture symptoms associated with PDAC from clinical notes within a large integrated health care system. We used unstructured data within 2 years prior to PDAC diagnosis between 2010 and 2019 and among matched patients without PDAC to identify 17 PDAC-related symptoms. Related terms and phrases were first compiled from publicly available resources and then recursively reviewed and enriched with input from clinicians and chart review. A computerized NLP algorithm was iteratively developed and fine-trained via multiple rounds of chart review followed by adjudication. Finally, the developed algorithm was applied to the validation data set to assess performance and to the study implementation notes. A total of 408,147 and 709,789 notes were retrieved from 2611 patients with PDAC and 10,085 matched patients without PDAC, respectively. In descending order, the symptom distribution of the study implementation notes ranged from 4.98% for abdominal or epigastric pain to 0.05% for upper extremity deep vein thrombosis in the PDAC group, and from 1.75% for back pain to 0.01% for pale stool in the non-PDAC group. Validation of the NLP algorithm against adjudicated chart review results of 1000 notes showed that precision ranged from 98.9% (jaundice) to 84% (upper extremity deep vein thrombosis), recall ranged from 98.1% (weight loss) to 82.8% (epigastric bloating), and F1-scores ranged from 0.97 (jaundice) to 0.86 (depression). The developed and validated NLP algorithm could be used for the early detection of PDAC.

Levels of retinol and retinoic acid in pancreatic cancer, type-2 diabetes and chronic pancreatitis.

Retinoids participate in multiple key processes in the human body e.g., vision, cell differentiation and embryonic development. There is growing evidence of the relationship between retinol, its active metabolite- all-trans retinoic acid (ATRA) - and several pancreatic disorders. Although low levels of ATRA in pancreatic ductal adenocarcinoma (PDAC) tissue have been reported, data on serum levels of ATRA in PDAC is still limited. The aim of our work was to determine serum concentrations of retinol and ATRA in patients with PDAC, type-2 diabetes mellitus (T2DM), chronic pancreatitis (CHP) and healthy controls. High performance liquid chromatography with UV detection (HPLC) was used to measure serum levels of retinol and ATRA in 246 patients with different stages of PDAC, T2DM, CHP and healthy controls. We found a significant decrease in the retinol concentration in PDAC (0.44+/-0.18 mg/L) compared to T2DM (0.65+/-0.19 mg/L, P<0.001), CHP (0.60+/-0.18 mg/L, P< 0.001) and healthy controls (0.61+/-0.15 mg/L, P<0.001), significant decrease of ATRA levels in PDAC (1.14+/-0.49 ug/L) compared to T2DM (1.37+/-0.56 ug/L, P<0.001) and healthy controls(1.43+/-0.55 ug/L, P<0.001). Differences between early stages (I+II) of PDAC and non-carcinoma groups were not significant. We describe correlations between retinol, prealbumin and transferrin, and correlation of ATRA and IGFBP-2. Significant decrease in retinol and ATRA levels in PDAC compared to T2DM, healthy individuals and/or CHP supports existing evidence of the role of retinoids in PDAC. However, neither ATRA nor retinol are suitable for detection of early PDAC. Correlation of ATRA levels and IGFBP-2 provides new information about a possible IGF and retinol relationship.

Detection of Pancreatic Ductal Adenocarcinoma-Associated Proteins in Serum

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer types, partly because it is frequently identified at an advanced stage, when surgery is no longer feasible. Therefore, early detection using minimally invasive methods such as blood tests may improve outcomes. However, studies to discover molecular signatures for the early detection of PDAC using blood tests have only been marginally successful. In the current study, a quantitative glycoproteomic approach via data-independent acquisition mass spectrometry was utilized to detect glycoproteins in 29 patient-matched PDAC tissues and sera. A total of 892 N-linked glycopeptides originating from 141 glycoproteins had PDAC-associated changes beyond normal variation. We further evaluated the specificity of these serum-detectable glycoproteins by comparing their abundance in 53 independent PDAC patient sera and 65 cancer-free controls. The PDAC tissue-associated glycoproteins we have identified represent an inventory of serum-detectable PDAC-associated glycoproteins as candidate biomarkers that can be potentially used for the detection of PDAC using blood tests.

Increased Levels of miR-15b-5p and miR-20b-5p in Pancreatic Ductal Adenocarcinoma with Hepatic Metastases.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal forms of cancer. The symptoms appear in advanced stages, and diagnostic and prognostic tests for the early detection of PDAC and disease evolution are not available. The dysregulation of microRNAs (miRNAs) has been associated with cancer development and progression, and some miRNAs have been reported to promote specific metastasis. In this study we aimed to identify the miRNAs dysregulated in PDAC tumoral tissues and a subset of miRNAs associated with tumoral characteristics, mainly metastasis presence and site. For this, the expression of 84 miRNAs was evaluated by qPCR in 30 tumoral tissues and 16 samples of non-tumoral pancreatic tissues. The comparison revealed 32 dysregulated miRNAs (19 upregulated and 13 downregulated) in the PDAC group. Reactome pathway over-representation analysis revealed that these miRNAs are involved in several biological pathways, including "ESR-mediated signaling", "PIP3 activates AKT signaling", and "Regulation of PTEN", among others. Moreover, our study identified an upregulation of miR-15b-5p and miR-20b-5p in the tumoral tissues of patients with hepatic metastasis, outlining these miRNAs as potential markers for hepatic metastasis. No significant difference in miRNA expression was observed in relation to anatomic location, lymphovascular invasion, lung metastasis, and the presence of diabetes.

ExoLuminate: An observational registry study for detection of pancreatic adenocarcinoma (PDAC) in high-risk or clinically suspicious patients.

TPS4203 Background: The detection of pancreatic ductal adenocarcinoma (PDAC) at early-stages is critical to improving patient survival. However, the lack of a clinically useful biomarker assay poses a challenge for earlier detection. A liquid biopsy test (ExoVita Pancreas) which uses extracellular vesicles (EV) protein biomarkers has been developed for detection of PDAC. In a previous case-control study of n=715 (75 cases of PDAC Stage I and II, 640 controls), the EV-protein biomarker assay yielded a sensitivity of 96.0% and specificity of 91.1%. By optimizing the assay for high sensitivity, we aim to generate evidence for earlier detection of PDAC in high-risk and clinically suspicious patients in the hope of impacting PDAC patient diagnostic journeys. Methods: ExoLuminate is a prospective, multi-center, observational registry study to demonstrate that early detection of PDAC using ExoVita is non-inferior to current standard of care methods of surveillance. The study duration will be 36 months (24-month accrual, 12-month follow-up), with a minimum of 1000 subjects to be enrolled between two cohorts as described below. The first cohort enriches for “high-risk” individuals without a cancer suspicion or diagnosis including those with intraductal papillary mucinous neoplasms (IPMNs), personal or family history of pancreatitis, family member(s) who have at least one first-degree relative affected by pancreatic cancer, patients over 50 years of age with new-onset diabetes (NOD), and germline mutations known to be associated with PDAC. The second cohort includes patients with clinical findings suspicious for early-stage PDAC or those with biopsy-proven PDAC. Patients enrolled in the study will have their blood obtained at six-month intervals. The performance of ExoVita liquid biopsy will be compared to standard-of-care imaging and biomarkers such as CA19-9. Through this registry, which began enrollment in December 2022 and is open for accrual (NCT0562552), we aim to demonstrate the clinical utility of a novel liquid biopsy based on detection of EV-derived biomarkers for early diagnosis of PDAC which can provide credence to a new paradigm in early detection to improve patient outcomes. Clinical trial information: NCT0562552 .

Stratifying Risk for Pancreatic Cancer by Multiplexed Blood Test.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease, for which mortality closely parallels incidence. So far, the available techniques for PDAC detection are either too invasive or not sensitive enough. To overcome this limitation, here we present a multiplexed point-of-care test that provides a "risk score" for each subject under investigation, by combining systemic inflammatory response biomarkers, standard laboratory tests, and the most recent nanoparticle-enabled blood (NEB) tests. The former parameters are routinely evaluated in clinical practice, whereas NEB tests have been recently proven as promising tools to assist in PDAC diagnosis. Our results revealed that PDAC patients and healthy subjects can be distinguished accurately (i.e., 88.9% specificity, 93.6% sensitivity) by the presented multiplexed point-of-care test, in a quick, non-invasive, and highly cost-efficient way. Furthermore, the test allows for the definition of a "risk threshold", which can help clinicians to trace the optimal diagnostic and therapeutic care pathway for each patient. For these reasons, we envision that this work may accelerate progress in the early detection of PDAC and contribute to the design of screening programs for high-risk populations.