Biomarker For Pancreatic Ductal Adenocarcinoma Research Articles

Evolution of Liquid Biopsies for Detecting Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy characterised by late diagnosis and poor prognosis. Despite advancements, current diagnostic and prognostic strategies remain limited. Liquid biopsy techniques, including circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), circulating tumour exosomes, and proteomics, offer potential solutions to improve PDAC diagnosis, prognostication, and management. A systematic search of Ovid MEDLINE identified studies published between 2019 and 2024, focusing on liquid biopsy biomarkers for PDAC. A total of 49 articles were included. ctDNA research shows some promise in diagnosing and prognosticating PDAC, especially through detecting mutant KRAS in minimal residual disease assays. CTC analyses had low sensitivity for early-stage PDAC and inconsistent prognostic results across subpopulations. Exosomal studies revealed diverse biomarkers with some diagnostic and prognostic potential. Proteomics, although relatively novel, has demonstrated superior accuracy in PDAC diagnosis, including early detection, and notable prognostic capacity. Proteomics combined with CA19-9 analysis has shown the most promising results to date. An update on multi-cancer early detection testing, given its significance for population screening, is also briefly discussed. Liquid biopsy techniques offer promising avenues for improving PDAC diagnosis, prognostication, and management. In particular, proteomics shows considerable potential, yet further research is needed to validate existing findings and comprehensively explore the proteome using an unbiased approach.

Prognosis prediction of PDAC via detection of O-glycan altered extracellular vesicles in perioperative sera.

Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignancy due to the difficulty in diagnosis and poor prognosis because of the high recurrence rate, necessitating reliable biomarkers to improve the diagnosis and prognosis. However, the existing markers have limitations. We previously identified extracellular vesicles (EVs) recognized by O-glycan-binding lectins (Amaranthus caudatus agglutinin [ACA]) as a novel diagnostic biomarker for PDAC using an EV-counting system (ExoCounter). This retrospective study analyzed changes in ACA-positive EVs in perioperative PDAC serum and its association with prognosis using ExoCounter. Absolute EV levels in the pre- and postoperative sera of 44 patients who underwent curative pancreatectomy for PDAC were quantified using ExoCounter. The carbohydrate antigen 19-9 levels declined in most samples postoperatively, and presented no correlation with poor prognosis. In contrast, ACA-positive EVs increased in serum at 7 days postoperatively in 27 of 44 patients (61.4%). We therefore divided participants with ACA-positive EVs before and after surgery into elevation and decline groups. The overall survival (OS) and recurrence-free survival (RFS) of patients with higher ACA-positive EVs were significantly shorter than those with lower ACA-positive EVs (26.1 months vs. not reached, P = 0.018; 11.9 vs. 38.6 months, P = 0.013). Multivariable analysis revealed that ACA-positive EV elevation in postoperative serum was an independent prognostic factor for poor OS (hazard ratio [HR] = 3.891, P = 0.023) and RFS (HR = 2.650, P = 0.024). The detection of ACA-positive EVs in perioperative serum may be used to predict the prognosis of PDAC in the early postoperative period.

A rigorous multi-laboratory study of known PDAC biomarkers identifies increased sensitivity and specificity over CA19-9 alone

A blood test that enables surveillance for early-stage pancreatic ductal adenocarcinoma (PDAC) is an urgent need. Independent laboratories have reported PDAC biomarkers that could improve biomarker performance over CA19-9 alone, but the performance of the previously reported biomarkers in combination is not known. Therefore, we conducted a coordinated case/control study across multiple laboratories using common sets of blinded training and validation samples (132 and 295 plasma samples, respectively) from PDAC patients and non-PDAC control subjects representing conditions under which surveillance occurs. We analyzed the training set to identify candidate biomarker combination panels using biomarkers across laboratories, and we applied the fixed panels to the validation set. The panels identified in the training set, CA19-9 with CA199.STRA, LRG1, TIMP-1, TGM2, THSP2, ANG, and MUC16.STRA, achieved consistent performance in the validation set. The panel of CA19-9 with the glycan biomarker CA199.STRA improved sensitivity from 0.44 with 0.98 specificity for CA19-9 alone to 0.71 with 0.98 specificity (p < 0.001, 1000-fold bootstrap). Similarly, CA19-9 combined with the protein biomarker LRG1 and CA199.STRA improved specificity from 0.16 with 0.94 sensitivity for CA19-9 to 0.65 with 0.89 sensitivity (p < 0.001, 1000-fold bootstrap). We further validated significantly improved performance using biomarker panels that did not include CA19-9. This study establishes the effectiveness of a coordinated study of previously discovered biomarkers and identified panels of those biomarkers that significantly increased the sensitivity and specificity of early-stage PDAC detection in a rigorous validation trial.

Induction of oxidative- and endoplasmic-reticulum-stress dependent apoptosis in pancreatic cancer cell lines by DDOST knockdown

The dolichyl-diphosphooligosaccharide-protein glycosyltransferase non-catalytic subunit (DDOST) is a key component of the oligosaccharyltransferase complex catalyzing N-linked glycosylation in the endoplasmic reticulum lumen. DDOST is associated with several cancers and congenital disorders of glycosylation. However, its role in pancreatic cancer remains elusive, despite its enriched pancreatic expression. Using quantitative mass spectrometry, we identify 30 differentially expressed proteins and phosphopeptides (DEPs) after DDOST knockdown in the pancreatic ductal adenocarcinoma (PDAC) cell line PA-TU-8988T. We evaluated DDOST / DEP protein–protein interaction networks using STRING database, correlation of mRNA levels in pancreatic cancer TCGA data, and biological processes annotated to DEPs in Gene Ontology database. The inferred DDOST regulated phenotypes were experimentally verified in two PDAC cell lines, PA-TU-8988T and BXPC-3. We found decreased proliferation and cell viability after DDOST knockdown, whereas ER-stress, ROS-formation and apoptosis were increased. In conclusion, our results support an oncogenic role of DDOST in PDAC by intercepting cell stress events and thereby reducing apoptosis. As such, DDOST might be a potential biomarker and therapeutic target for PDAC.

Multiplexed Glycan Immunofluorescence Identification of Pancreatic Cancer Cell Subpopulations in Both Tumor and Blood Samples.

Pancreatic ductal adenocarcinoma (PDAC) tumor heterogeneity impedes the development of biomarker assays suitable for early disease detection that would improve patient outcomes. The CA19-9 glycan is currently used as a standalone biomarker for PDAC. Furthermore, previous studies have shown that cancer cells may display aberrant membrane-associated glycans. We therefore hypothesized that PDAC cancer cell subpopulations could be distinguished by aberrant glycan signatures. We used multiplexed glycan immunofluorescence combined with pathologist annotation and automated image processing to distinguish between PDAC cancer cell subpopulations within tumor tissue. Using a training-set/test-set approach, we found that PDAC cancer cells may be identified by signatures comprising 4 aberrant glycans (VVL, CA19-9, sTRA, and GM2) and that there are three glycan-defined PDAC tumor types: sTRA type, CA19-9 type, and intermixed. To determine whether the aberrant glycan signatures could be detected in blood samples, we developed hybrid glycan sandwich assays for membrane-associated glycans. In both patient-matched tumor and blood samples, the proportion of aberrant glycans detected was consistent. Furthermore, our multiplexed glycan immunofluorescent approach proved to be more sensitive and more specific than CA19-9 alone. Our results provide proof of concept for a novel methodology to improve early PDAC detection and patient outcomes.

Pesticide-induced transgenerational alterations of genome-wide DNA methylation patterns in the pancreas of Xenopus tropicalis correlate with metabolic phenotypes

The unsustainable use of manmade chemicals poses significant threats to biodiversity and human health. Emerging evidence highlights the potential of certain chemicals to cause transgenerational impacts on metabolic health. Here, we investigate male transmitted epigenetic transgenerational effects of the anti-androgenic herbicide linuron in the pancreas of Xenopus tropicalis frogs, and their association with metabolic phenotypes. Reduced representation bisulfite sequencing (RRBS) was used to assess genome-wide DNA methylation patterns in the pancreas of adult male F2 generation ancestrally exposed to environmentally relevant linuron levels (44 ± 4.7 μg/L). We identified 1117 differentially methylated regions (DMRs) distributed across the X. tropicalis genome, revealing potential regulatory mechanisms underlying metabolic disturbances. DMRs were identified in genes crucial for pancreatic function, including calcium signalling (clstn2, cacna1d and cadps2), genes associated with type 2 diabetes (tcf7l2 and adcy5) and a biomarker for pancreatic ductal adenocarcinoma (plec). Correlation analysis revealed associations between DNA methylation levels in these genes and metabolic phenotypes, indicating epigenetic regulation of glucose metabolism. Moreover, differential methylation in genes related to histone modifications suggests alterations in the epigenetic machinery. These findings underscore the long-term consequences of environmental contamination on pancreatic function and raise concerns about the health risks associated with transgenerational effects of pesticides.

Development of a Fit-For-Purpose Multi-Marker Panel for Early Diagnosis of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) suffers from a lack of an effective diagnostic method, which hampers improvement in patient survival. Carbohydrate antigen 19-9 (CA19-9) is the only FDA-approved blood biomarker for PDAC, yet its clinical utility is limited due to suboptimal performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics for the discovery, verification, and validation of novel biomarkers. A plethora of protein biomarker candidates for PDAC have been identified using LC-MS, yet few has successfully transitioned into clinical practice. This translational standstill is owed partly to insufficient considerations of practical needs and perspectives of clinical implementation during biomarker development pipelines, such as demonstrating the analytical robustness of proposed biomarkers which is critical for transitioning from research-grade to clinical-grade assays. Moreover, the throughput and cost-effectiveness of proposed assays ought to be considered concomitantly from the early phases of the biomarker pipelines for enhancing widespread adoption in clinical settings. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS protocol. In the discovery phase, we comprehensively surveyed putative PDAC biomarkers from both in-house data and prior studies. In the verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation tests. We adopted a high-throughput protocol including a short gradient (<10min) and simple sample preparation (no depletion or enrichment steps). Additionally, we developed our assay using serum samples, which are usually the preferred biospecimen in clinical settings. We developed predictive models based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone in discriminating PDAC from non-PDAC controls including healthy individuals and patients with benign pancreatic diseases. A large-scale clinical validation is underway to demonstrate the clinical validity of our novel panel.

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

BackgroundDistinguishing benign from malignant pancreaticobiliary disease is challenging because of the absence of reliable biomarkers. Circulating extracellular vesicles (EVs) have emerged as functional mediators between cells. Their cargos, including microRNAs (miRNAs), are increasingly acknowledged as an important source of potential biomarkers. This multicentric, prospective study aimed to establish a diagnostic plasma EV-derived miRNA signature to discriminate pancreatic ductal adenocarcinoma (PDAC) from benign pancreaticobiliary disease.MethodsPlasma EVs were isolated using size exclusion chromatography (SEC) and characterised using nanoparticle tracking analysis, electron microscopy and Western blotting. EV-RNAs underwent small RNA sequencing to discover differentially expressed markers for PDAC (n = 10 benign vs. 10 PDAC). Candidate EV-miRNAs were then validated in a cohort of 61 patients (n = 31 benign vs. 30 PDAC) by RT-qPCR. Logistic regression and optimal thresholds (Youden Index) were used to develop an EV-miR-200 family model to detect cancer. This model was tested in an independent cohort of 95 patients (n = 30 benign, 33 PDAC, and 32 cholangiocarcinoma).ResultsSmall RNA sequencing and RT-qPCR showed that EV-miR-200 family members were significantly overexpressed in PDAC vs. benign disease. Combined expression of the EV-miR-200 family showed an AUC of 0.823. In an independent validation cohort, application of this model showed a sensitivity, specificity and AUC of 100%, 88%, and 0.97, respectively, for diagnosing PDAC.ConclusionsThis is the first study to validate plasma EV-miR-200 members as a clinically-useful diagnostic biomarker for PDAC. Further validation in larger cohorts and clinical trials is essential. These findings also suggest the potential utility in monitoring response and/or recurrence.Graphical

Novel diagnostic biomarkers for pancreatic cancer: assessing methylation status with epigenetic-specific peptide nucleic acid and KRAS mutation in cell-free DNA.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive tumor with a poor prognosis that poses challenges for diagnosis using traditional tissue-based techniques. DNA methylation alterations have emerged as potential and promising biomarkers for PDAC. In this study, we aimed to assess the diagnostic potential of a novel DNA methylation assay based on epigenetic-specific peptide nucleic acid (Epi-sPNA) in both tissue and plasma samples for detecting PDAC. The study involved 46 patients with PDAC who underwent surgical resection. Epi-TOP pancreatic assay was used to detect PDAC-specific epigenetic biomarkers. The Epi-sPNA allowed accurate and rapid methylation analysis without bisulfite sample processing. Genomic DNA extracted from paired normal pancreatic and PDAC tissues was used to assess the diagnostic efficacy of epigenetic biomarkers for PDAC. Subsequent validation was conducted on cell-free DNA (cfDNA) extracted from plasma samples, with 10 individuals represented in each group: PDAC, benign pancreatic cystic neoplasm, and healthy control. The combination of seven epigenetic biomarkers (HOXA9, TWIST, WT1, RPRM, BMP3, NPTX2, and BNC1) achieved 93.5% sensitivity and 96.7% specificity in discerning normal pancreatic from PDAC tissues. Plasma cfDNA, analyzed using these markers and KRAS mutations, exhibited a substantial 90.0% sensitivity, 95.0% specificity, and an overall 93.3% accuracy for discriminating PDAC. Notably, cancer antigen 19-9 and carcinoembryonic antigen both had an accuracy of 90.0%. Our study suggests that analyzing seven differentially methylated genes with KRAS mutations in cfDNA using the novel Epi-TOP pancreatic assay is a potential blood-based biomarker for the diagnosis of PDAC.

Circulating tumor DNA for recurrence monitoring following resection for pancreas adenocarcinoma.

e16365 Background: Detecting early recurrence among patients with resected pancreatic cancer may facilitate earlier treatment and better outcomes for patients with resected pancreatic ductal adenocarcinoma (PDAC). Circulating tumor DNA (ctDNA) has shown promise as a tumor-specific biomarker for PDAC but has not yet entered routine clinical use. This study aims to conduct analytical and clinical validation of Signatera ctDNA profiling to predict recurrence in patients with PDAC. Methods: A retrospective IRB-approved protocol evaluating the use of Signatera ctDNA testing among patients who underwent resection at Northwell Health during 2019-2023. The utility of ctDNA status to predict PDAC recurrence during follow-up was assessed using cox regression. Results: There were 91 ctDNA tests among 24 patients. With a median follow-up of 15 months, recurrence was observed in 38% (9/24) of patients and 8 patients died. Among patients with recurrence, most of them had positive ctDNA before showing signs of recurrence on the imaging (6/9, 66.7%) with mean lead time of 116 days, while 2 of them had positive ctDNA after recurrence and one patient never had positive ctDNA. At the time of recurrence, eight patients had elevated CA19-9, while two patients with normal CA19-9 had positive ctDNA. The median recurrence-free survival (RFS) was 23 months (95% CI, 11-not reached). Patients with detectable preoperative ctDNA had significantly decreased median RFS (14 months; 7 of 10 (70%) recurred) when compared with patients negative for ctDNA [not reached; 2/14 (14.3%) recurred; P= 0.005). In multivariable Cox model after adjusting for potential risk factors, detection of ctDNA was associated with RFS. (table). Conclusions: Signatera ctDNA profiling identified relapse earlier than imaging for most patients. These results suggest the potential for a prospective trial evaluating early treatment interventions in this deadly disease to improve survival rates. [Table: see text]

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.

Comprehensive analysis of KLF family reveals KLF6 as a promising prognostic and immune biomarker in pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the deadliest tumors worldwide, with extremely aggressive and complicated biology. Krüppel-like factors (KLFs) encode a series of transcriptional regulatory proteins and play crucial roles in a variety of processes, including tumor cell differentiation and proliferation. However, the potential biological functions and possible pathways of KLFs in the progression of PDAC remain elusive.MethodsWe systematically evaluated the transcriptional variations and expression patterns of KLFs in pancreatic cancer from the UCSC Xena. Based on difference analysis, the non-negative matrix factorization (NMF) algorithm was utilized to identify the immune characteristics and clinical significance of two different subtypes. The multivariate Cox regression was used to construct the risk model and then explore the differences in tumor immune microenvironment (TIME) and drug sensitivity between high and low groups. Through single-cell RNA sequencing (scRNA-seq) analysis, we screened KLF6 and further investigated its biological functions in pancreatic cancer and pan-cancer.ResultsThe KLFs exhibited differential expression and mutations in the transcriptomic profile of PDAC. According to the expression of KLFs, patients were classified into two distinct subtypes, each exhibiting significant differences in prognosis and TIME. Moreover, the KLF signature was developed using univariate Cox and Lasso regression, which proved to be a reliable and effective prognostic model. Furthermore, the KLF_Score was closely associated with immune infiltration, response to immunotherapy, and drug sensitivity and we screened small molecule compounds targeting prognostic genes separately. Through scRNA-seq analysis, KLF6 was selected to further demonstrate its role in the malignance of PC in vitro. Finally, pan-cancer analysis emphasized the biological significance of KLF6 in multiple types of tumors and its clinical utility in assessing cancer prognosis.ConclusionThis study elucidated the pivotal role of KLF family genes in the malignant development of PC through comprehensive analysis and revealed that KLF6 would be a novel diagnostic biomolecule marker and potential therapeutic target for PDAC.

Identification of potential biomarkers for pancreatic ductal adenocarcinoma: a bioinformatics analysis.

PDA is an aggressive cancer with a 5-year survival rate, which is very low. There is no effective prognosis or therapy for PDA because of the lack of target biomarkers. The objective of this article is to identify the target biomarkers for PDA using a bioinformatics approach. In this work, we have analysed the three microarray datasets from the NCBI GEO database. We used the Geo2R tool to analyse the microarray data with the Benjamini and Hochberg false discovery rate method, and the significance level cut-off was set to 0.05. We have identified 659 DEGs from the datasets. There are a total of 15 hub genes that were selected from the PPI network constructed using the STRING application. Furthermore, these 15 genes were evaluated on PDA patients using TCGA and GTEx databases in (GEPIA). The online tool DAVID was used to analyse the functional annotation information for the DEGs. The functional pathway enrichment was performed on the GO and KEGG. The hub genes were mainly enriched for cell division, chromosome segregation, protein binding and microtubule binding. Further, the gene alteration study was performed using the cBioportal tool and screened out six hub genes (ASPM, CENPF, BIRC5, TTK, DLGAP5, and TOP2A) with a high alteration rate in PDA samples. Furthermore, Kaplan-Meier survival analysis was performed on the six hub genes and identified poor-survival outcomes that may be involved in tumorigenesis and PDA development. So, this study concludes that, these six hub genes may be potential prognostic biomarkers for PDA.

Keratin 17 is a prognostic and predictive biomarker in pancreatic ductal adenocarcinoma.

To determine the role of keratin 17 (K17) as a predictive biomarker for response to chemotherapy by defining thresholds of K17 expression based on immunohistochemical tests that could be used to optimize therapeutic intervention for patients with pancreatic ductal adenocarcinoma (PDAC). We profiled K17 expression, a hallmark of the basal molecular subtype of PDAC, by immunohistochemistry in 2 cohorts of formalin-fixed, paraffin-embedded PDACs (n = 305). We determined a K17 threshold of expression to optimize prognostic stratification according to the lowest Akaike information criterion and explored the potential relationship between K17 and chemoresistance by multivariate predictive analyses. Patients with advanced-stage, low K17 PDACs treated using 5-fluorouracil (5-FU)-based chemotherapeutic regimens had 3-fold longer survival than corresponding cases treated with gemcitabine-based chemotherapy. By contrast, PDACs with high K17 did not respond to either regimen. The predictive value of K17 was independent of tumor mutation status and other clinicopathologic variables. The detection of K17 in 10% or greater of PDAC cells identified patients with shortest survival. Among patients with low K17 PDACs, 5-FU-based treatment was more likely than gemcitabine-based therapies to extend survival.

Integration of single-nucleus and exosome RNA sequencing dissected inter-cellular communication and biomarkers in pancreatic ductal adenocarcinoma

BackgroundMounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication. MethodWe analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network. ResultsWe established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes. ConclusionOur study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

Abstract 3514: A deep learning model for detection and characterization of tertiary lymphoid structures in H&amp;E-stained images from pancreatic ductal adenocarcinoma

Abstract Tertiary lymphoid structures (TLSs) are ectopic aggregates of a number of immune cells in nonlymphoid tissues under chronically inflamed environments and cancer. Emergence evidence suggested that TLSs were found in diverse cancers and TLSs have been referred as an independently predictive biomarker for immunotherapy response, especially immune checkpoint inhibitors. Moreover, the density and mature status of TLSs often positively associated with the favorable outcomes in cancers. Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related mortality with low survival rate in the whole world. Here, we developed a multi-resolution machine learning model for detection of TLSs from hema-toxylin and eosin (H&amp;E) stained digital pathology slides as a potential clinical biomarker in PDAC. We selected 120 H&amp;E slides (patients) with a total of 1,896 TLSs manually annotated as immature or mature TLSs by two pathologists. We also used immunohistochemistry (IHC) for CD20 and CD23 markers as a reference standard for H&amp;E-based manual annotations. Our model mainly included detection and segmentation of individual TLSs. First, we used a transformer convolutional neural network to build a classification task to detect the presence of immature or mature TLSs. Then the instance segmentation model was applied to quantify the number of lymphocytes per unit square to validate the presence and maturation of TLSs. F1-score, calculated by the harmonic mean of precision (positive predictive value) and recall (sensitivity), was finally used to quantitatively evaluate the performance of model for each H&amp;E slide. In validation dataset with 250 H&amp;E slides (patients), we selected 50 slides to calculate F1-score, suggesting that our machine learning model achieved high F1-scores for detection and classification of immature TLSs (mean = 0.87, range from 0.79 to 0.95), and mature TLSs (mean = 0.92, range from 0.86 to 0.97). We further stratified 370 PDAC patients into three groups with mature TLSs (23%), immature TLSs (16%), and no TLSs (61%), respectively. Combined the clinical information, survival analysis revealed that patients with mature TLS had better survival outcomes than those without TLS (HR = 0.63; 95% CI, 0.44 - 0.90; P = 0.010). We developed a machine learning model that can accurately detect and classify TLSs in PDAC, and also demonstrated the prognosis value of predictive TLSs in H&amp;E slides by automatedly machine learning model. These data highlight the promise of machine learning model for automated identification and quantification of the TLS on H&amp;E slides in PDAC pathology. Citation Format: Chaoxian Zhao, Jidong Jia, Mingxi Lv, Jiayi Feng, Yijun Wang, Yingbin Liu. A deep learning model for detection and characterization of tertiary lymphoid structures in H&amp;E-stained images from 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 3514.

Abstract 4153: PET/CT imaging of pancreatic ductal adenocarcinoma with a claudin-4 binding peptide in preclinical mouse model

Abstract There is a critical need to develop new imaging and therapeutic strategies for pancreatic cancer. Current positron emission tomography (PET) imaging assessments of pancreatic ductal adenocarcinoma (PDAC) rely on 18F-FDG as a radiopharmaceutical. To increase the sensitivity of PDAC detection, we identified Claudin-4 (CLDN4), a tight junction transmembrane protein, as a PDAC biomarker through spatial transcriptomic and proteomic analyses. CLDN4 expression has previously been reported to be enhanced in 99% of primary and 100% of metastatic pancreatic cancer tissue samples and in 10 of 11 precancerous pancreatic intraepithelial neoplasia (PanIN) specimens. A small fragment of naturally occurring Clostridium perfringens enterotoxin (CPE) was previously reported to bind to the extracellular loop domain of CLDN4 protein (PDB:7kp4) with nanomolar (nM) affinity (Kd). A CLDN4 binding peptide (C4BP) was developed as a radioligand by modifying the n-terminus of C4BP which does not impact receptor binding. Here, we designed and synthesized a DOTA-PEG1-C4BP ligand on a rink amide resin using a microwave-assisted peptide synthesizer. Radiolabeling of DOTA-PEG1-C4BP (2 nmol) with 64CuCl2 (70 MBq) conferred 64Cu-C4BP (28 MBq/nmol) with 80% non-decay corrected yield and &amp;gt;99% radiochemical purity. PET/CT imaging of 64Cu-C4BP (~0.1 μg/mouse) performed in an inducible PDAC (KrasLSL-G12D/+;Rosa26LSL-tdTomato/LSL-tdTomato(KT);Ptf1aCreER;Trp53fl/fl) model at 84 day after tamoxifen injection resulted in ~25% injected activity per cubic centimeter (IA/cc) accumulation in metastases and at ~18% IA/cc retention in pancreatic tumors within 30 minutes of tail vein injection with minimal background accumulation. Ex vivo PET imaging confirmed the localized accumulation of 64Cu-C4BP in transgenic mice within the colon, pancreas, and liver. Blocking of 64Cu-C4BP accumulation with the cold compound in a xenograft model (NOD/SCID) bearing Capan-1 PDAC tumors demonstrated the specificity of 64Cu-C4BP binding. Here we report that CLDN4 is a promising target and 64Cu-C4BP is a promising ligand for the detection of pancreatic cancer. Citation Format: Jai Woong Seo, James Wang, Aris J. Kare, Spencer K. Tumbale, Bo Wu, Marina N. Raie, Mallesh Pandrala, Katherine W. Ferrara. PET/CT imaging of pancreatic ductal adenocarcinoma with a claudin-4 binding peptide in preclinical mouse model [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 4153.

Abstract 4156: Monitoring early chemotherapy response in murine pancreatic ductal adenocarcinoma using non-invasive hyperpolarized magnetic resonance spectroscopic imaging with 13C-pyruvate

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is a rarely operable cancer with a very poor prognosis. Nearly 100% of affected patients receive one of two alternative first-line chemotherapies during the course of their disease: 1.) Gemcitabine-Abraxane (G/A) or 2.) FOLFIRINOX. Treatment success varies widely between the patients due to individual molecular, structural tumor and metabolic heterogeneity. In this project, we use hyperpolarized 13C-pyruvate magnetic resonance spectroscopic imaging (HP-MRSI) to non-invasively characterize early metabolic changes in murine endogenous PDAC in response to the mentioned chemotherapies. Methods: 18 KPC (Ptf1awt/cre(C)Kraswt/G12D(K)Trp53fl/fl(P)) mice with 74 distinct tumour nodules, visually identified based on T2-weighted anatomical imaging, were used in this study. The conversion of pyruvate to lactate was detected by HP-MRSI, performed on 7 T preclinical system using modified 3D balanced steady-state free precession (bSSFP) sequence on day 0 pre-therapy and on day 3 post-therapy. 100μg/g G (intraperitoneally) and 30μg/g A (intravenously) were applied twice on day 0 post-scan and day 2 (n=6). FOLFIRINOX (60μg/g 5-Fluoruracil, 27μg/g Irinotecan, 12.8μg/g Oxaliplatin, 60μg/g Leucovorin) was injected intravenously once on day 0 post-scan (n=6). Vehicle mice (n=6) were left untreated. Area under the curves (AUC) of lactate to pyruvate time-courses (AUCl/AUCp) were calculated. Primary murine PDAC cell lines were established from biopsies of 58 imaging region, sequenced using 3’RNA-Seq (Poly-ASeq) method and analysed using Dseq2 R package. Results: G/A and FOLFIRINOX-treated tumors exhibited heterogeneous metabolic responses in distinct nodules, while non-treated group tumors remained stable. A significant difference in metabolic changes (p = 0.01, ANOVA) from day 0 to day 3 was observed between FOLFIRINOX, G/A, and non-treated groups. Low glycolytic tumors showed a positive trend, more pronounced with FOLFIRINOX than G/A treatment. Metabolically active nodules with high AUCl/AUCp on day 0 reduced lactate turnover under therapy. These findings suggest that metabolic HP-MRSI can detect treatment-induced changes in tumor composition and subtype-specific epithelial/mesenchymal plasticity, correlating with the metabolic phenotype. Further investigation will include histology, subtype-specific biomarkers, transcriptional signatures, and regional transcriptome analysis to explain molecular changes in metabolism. Conclusions: We have applied a non-invasive approach for detection of metabolic changes under chemotherapy in murine PDAC. These findings will contribute in the long term to the establishment of predictive imaging biomarkers for PDAC. Citation Format: Irina Heid, Anna-Maria Schmidmüller, Simon Baller, Jason G. Skinner, Geoffrey J. Topping, Wolfgang Gottwald, Hussein Trabulssi, Rupert Öllinger, Katja Steiger, Roland Rad, Franz Schilling, Rickmer F. Braren. Monitoring early chemotherapy response in murine pancreatic ductal adenocarcinoma using non-invasive hyperpolarized magnetic resonance spectroscopic imaging with 13C-pyruvate [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 4156.

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

ABSTRACT 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.

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.