Early 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.

Hidden in plain sight: commonly missed early signs of pancreatic cancer on CT.

Pancreatic ductal adenocarcinoma (PDAC) has poor prognosis mostly due to the advanced stage at which disease is diagnosed. Early detection of disease at a resectable stage is, therefore, critical for improving outcomes of patients. Prior studies have demonstrated that pancreatic abnormalities may be detected on CT in up to 38% of CT studies 5years before clinical diagnosis of PDAC. In this review, we highlight commonly missed signs of early PDAC on CT. Broadly, these commonly missed signs consist of small isoattenuating PDAC without contour deformity, isolated pancreatic duct dilatation and cutoff, focal pancreatic enhancement and focalparenchymal atrophy, pancreatitis with underlying PDAC, and vascular encasement. Through providing commentary on demonstrative examples of these signs, we demonstrate how to reduce the risk of missing or misinterpreting radiological features of early PDAC.

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.

Hepatic signal transducer and activator of transcription-3 signalling drives early-stage pancreatic cancer cachexia via suppressed ketogenesis.

Patients with pancreatic ductal adenocarcinoma (PDAC) often suffer from cachexia, a wasting syndrome that significantly reduces both quality of life and survival. Although advanced cachexia is associated with inflammatory signalling and elevated muscle catabolism, the early events driving wasting are poorly defined. During periods of nutritional scarcity, the body relies on hepatic ketogenesis to generate ketone bodies, and lipid metabolism via ketogenesis is thought to protect muscle from catabolizing during nutritional scarcity. We developed an orthotopic mouse model of early PDAC cachexia in 12-week-old C57BL/6J mice. Murine pancreatic cancer cells (KPC) were orthotopically implanted into the pancreas of wild-type, IL-6-/-, and hepatocyte STAT3-/- male and female mice. Mice were subject to fasting, 50% food restriction, ad libitum feeding or ketogenic diet interventions. We measured longitudinal body composition by EchoMRI, body mass and food intake. At the endpoint, we measured tissue mass, tissue gene expression by quantitative real-time polymerase chain reaction, whole-body calorimetry, circulating hormone levels, faecal protein and lipid content, hepatic lipid content and ketogenic response to medium-chain fatty acid bolus. We assessed muscle atrophy in vivo and C2C12 myotube atrophy in vitro. Pre-cachectic PDAC mice did not preserve gastrocnemius muscle mass during 3-day food restriction (-13.1±7.7% relative to food-restricted sham, P=0.0117) and displayed impaired fatty acid oxidation during fasting, resulting in a hypoketotic state (ketogenic response to octanoate bolus, -83.0±17.3%, P=0.0328; Hmgcs2 expression, -28.3±7.6%, P=0.0004). PDAC human patients display impaired fasting ketones (-46.9±7.1%, P<0.0001) and elevated circulating interleukin-6 (IL-6) (12.4±16.5-fold increase, P=0.0001). IL-6-/- PDAC mice had improved muscle mass (+35.0±3.9%, P=0.0031) and ketogenic response (+129.4±44.4%, P=0.0033) relative to wild-type PDAC mice. Hepatocyte-specific signal transducer and activator of transcription 3 (STAT3) deletion prevented muscle loss (+9.3±4.0%, P=0.009) and improved fasting ketone levels (+52.0±43.3%, P=0.018) in PDAC mice. Without affecting tumour growth, a carbohydrate-free diet improved tibialis anterior myofibre diameter (+16.5±3.5%, P=0.0089), circulating ketone bodies (+333.0±117.6%, P<0.0001) and Hmgcs2 expression (+106.5±36.1%, P<0.0001) in PDAC mice. Ketone supplementation protected muscle against PDAC-induced atrophy in vitro (+111.0±17.6%, P<0.0001 myofibre diameter). In early PDAC cachexia, muscle vulnerability to wasting is dependent on inflammation-driven metabolic reprogramming in the liver. PDAC suppresses lipid β-oxidation and impairs ketogenesis in the liver, which is reversed in genetically modified mouse models deficient in IL-6/STAT3 signalling or through ketogenic diet supplementation. This work establishes a direct link between skeletal muscle homeostasis and hepatic metabolism. Dietary and anti-inflammatory interventions that restore ketogenesis may be a viable preventative approach for pre-cachectic patients with pancreatic cancer.

Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma.

One of the primary reasons for the dismal survival rates in pancreatic ductal adenocarcinoma (PDAC) is that most patients are usually diagnosed at late stages. There is an urgent unmet clinical need to identify and develop diagnostic methods that could precisely detect PDAC at its earliest stages. To evaluate the potential value of radiomics analysis in the differentiation of early-stage PDAC from late-stage PDAC. A total of 71 patients with pathologically proved PDAC based on surgical resection who underwent contrast-enhanced computed tomography (CT) within 30 d prior to surgery were included in the study. Tumor staging was performed in accordance with the 8th edition of the American Joint Committee on Cancer staging system. Radiomics features were extracted from the region of interest (ROI) for each patient using Analysis Kit software. The most important and predictive radiomics features were selected using Mann-Whitney U test, univariate logistic regression analysis, and minimum redundancy maximum relevance (MRMR) method. Random forest (RF) method was used to construct the radiomics model, and 10-times leave group out cross-validation (LGOCV) method was used to validate the robustness and reproducibility of the model. A total of 792 radiomics features (396 from late arterial phase and 396 from portal venous phase) were extracted from the ROI for each patient using Analysis Kit software. Nine most important and predictive features were selected using Mann-Whitney U test, univariate logistic regression analysis, and MRMR method. RF method was used to construct the radiomics model with the nine most predictive radiomics features, which showed a high discriminative ability with 97.7% accuracy, 97.6% sensitivity, 97.8% specificity, 98.4% positive predictive value, and 96.8% negative predictive value. The radiomics model was proved to be robust and reproducible using 10-times LGOCV method with an average area under the curve of 0.75 by the average performance of the 10 newly built models. The radiomics model based on CT could serve as a promising non-invasive method in differential diagnosis between early and late stage PDAC.

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.

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.

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.

Abstract A014: Combinations of previously reported biomarkers achieve improved sensitivity and specificity of detection of early stage pancreatic ductal adenocarcinoma

Abstract A promising approach to the early detection of pancreatic ductal adenocarcinoma (PDAC) is surveillance among people at elevated risk for the disease using a blood test. Several groups have reported promising biomarkers, but no single biomarker delivers the rate of positively predicting cancers and of negatively predicting non-cancers needed for routine use. We hypothesized that combinations of previously reported PDAC biomarkers could contribute complementary detection across heterogeneous subgroups of patients and consequently improve biomarker performance. Blood plasma specimens from 427 individuals, grouped into a training set (n = 132) and a validation set (n = 295), were distributed to four different laboratories for analysis using their independently developed biomarker assays. We analyzed the training set to identify biomarker combinations that improved upon CA19-9 for identification of early stage PDAC relative to benign disease conditions, both for improved sensitivity while controlling for high specificity and improved specificity while controlling for high sensitivity. We then applied the biomarker combinations to the validation set to determine their performance. The combination of CA19-9 with the glycan biomarker CA199.STRA improved sensitivity from 0.44 sensitivity with 0.98 specificity for CA19-9 to 0.71 sensitivity with 0.94 specificity (p &amp;lt; 0.001, 1000-fold bootstrap), and CA19-9 combined with the protein biomarker LRG1 and CA199.STRA improved specificity from 0.16 specificity and 0.94 sensitivity for CA19-9 to 0.58 specificity and 0.89 sensitivity (p &amp;lt; 0.001, 1000-fold bootstrap). Notably, cross-laboratory biomarker combinations that did not include CA19-9 in the panel significantly improved upon CA19-9. The combination of CA199.STRA with the protein biomarker MUC5AC improved sensitivity over CA19-9 with 0.61 sensitivity and 0.94 specificity (p = 0.0002, 1000-fold bootstrap), and the combination of CA199.STRA and the protein biomarkers MUC5AC, THSP2, and ANG improved specificity over CA19-9 with 0.66 specificity and 0.88 sensitivity (p &amp;lt; 0.0001, 1000-fold bootstrap). By coordinating this biomarker study across independent laboratories, we have identified novel biomarker combinations that significantly increase the sensitivity and specificity of early stage PDAC detection and that demonstrate the future feasibility of surveillance for PDAC using combinations of serum assays. Citation Format: Brian Haab, Lu Qian, Ben Staal, Maneesh Jain, Johannes Fahrmann, Christine Worthington, Denise Prosser, Liudmila Velokokhatnaya, Camden Lopez, Runlong Tang, Mark Hurd, Gopalakrishnan Natarajan, Sushil Kumar, Lynette Smith, Samir Hanash, Surinder Batra, Anirban Maitra, Anna Lokshin, Ying Huang, Randall E. Brand, Liudmila Velokokhatnaya. Combinations of previously reported biomarkers achieve improved sensitivity and specificity of detection of early stage pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A014.

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.

Chemokine Receptor 2 Targeted PET/CT Imaging Distant Metastases in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and treatment-refractory malignancies. The lack of an effective screening tool results in the majority of patients being diagnosed at late stages, which underscores the urgent need to develop more sensitive and specific imaging modalities, particularly in detecting occult metastases, to aid clinical decision-making. The tumor microenvironment of PDAC is heavily infiltrated with myeloid-derived suppressor cells (MDSCs) that express C-C chemokine receptor type 2 (CCR2). These CCR2-expressing MDSCs accumulate at a very early stage of metastasis and greatly outnumber PDAC cells, making CCR2 a promising target for detecting early, small metastatic lesions that have scant PDAC cells. Herein, we evaluated a CCR2 targeting PET tracer (68Ga-DOTA-ECL1i) for PET imaging on PDAC metastasis in two mouse models. Positron emission tomography/computed tomography (PET/CT) imaging of 68Ga-DOTA-ECL1i was performed in a hemisplenic injection metastasis model (KI) and a genetically engineered orthotopic PDAC model (KPC), which were compared with 18F-FDG PET concurrently. Autoradiography, hematoxylin and eosin (H&E), and CCR2 immunohistochemical staining were performed to characterize the metastatic lesions. PET/CT images visualized the PDAC metastases in the liver/lung of KI mice and in the liver of KPC mice. Quantitative uptake analysis revealed increased metastasis uptake during disease progression in both models. In comparison, 18F-FDG PET failed to detect any metastases during the time course studies. H&E staining showed metastases in the liver and lung of KI mice, within which immunostaining clearly demonstrated the overexpression of CCR2 as well as CCR2+ cell infiltration into the normal liver. H&E staining, CCR2 staining, and autoradiography also confirmed the expression of CCR2 and the uptake of 68Ga-DOTA-ECL1i in the metastatic foci in KPC mice. Using our novel CCR2 targeted radiotracer 68Ga-DOTA-ECL1i and PET/CT, we demonstrated the sensitive and specific detection of CCR2 in the early PDAC metastases in two mouse models, indicating its potential in future clinical translation.

HPB P06 The clinical and molecular landscape of early onset pancreatic cancer

Abstract Background The incidence of Pancreatic ductal adenocarcinoma (PC) is rising in the western world. There is a particularly concerning trend in the rapid increase in incidence of early onset PC (EOPC). The reason for this, and the implications of EOPC is not well understood. The aim of this study was to investigate the clinical outcomes of patients with EOPC and the molecular heterogeneity between EOPC and late onset disease. Methods Clinical, pathological and survival outcome data was obtained from 2 large independent prospective cohorts curated by the Australian Pancreatic Genome Initiative (APGI) and the West of Scotland pancreatic unit (Glasgow Royal Infirmary). Patients were categorised into 2 age groups, &amp;lt; 50 and &amp;gt;50 years at time of diagnosis. Clinicopathological and outcome data were compared between groups. Molecular data was obtained from the APGI’s contribution to the International Cancer Genome Consortium, this included transcriptomic, genomic and immunohistochemical data. Molecular subtypes, gene expression signatures, mutational signatures, and tumour microenvironment data was compared between groups. Results N=851 patients were identified and n=71 (8%) were &amp;lt; 50 years old. EOPC was associated with earlier recurrence (10.9 vs 14.2 months, P=0.011) and higher incidence of liver recurrence (50% vs 37%, P=0.031). There were no differences in validated clinicopathological variables. Despite an increased proportion of patients with EOPC receiving adjuvant chemotherapy (P=0.020), recurrence was earlier in those that completed &amp;gt; 3 cycles (12.6 vs 16.0 months, P=0.022). There is enrichment of the poor prognostic squamous (basal) subtype (42% vs 28%) in EOPC. There were no differences in the incidence of germline mutations to account for the early onset of disease. Conclusions EOPC appears to be increasing in incidence and is associated with earlier recurrence and more aggressive disease pattern. This appears to be associated with resistance to adjuvant chemotherapy and more aggressive, adverse molecular pathology. The onset of early disease cannot be explained by inherited genomic aberrations. Ongoing mutation signature, gene expression and microenvironmental data analysis will be presented upon acceptance of this abstract.

Oncogenic KRAS, Mucin 4, and Activin A-Mediated Fibroblast Activation Cooperate for PanIN Initiation.

Over 90% of patients with pancreatic ductal adenocarcinoma (PDAC) have oncogenic KRAS mutations. Nevertheless, mutated KRAS alone is insufficient to initiate pancreatic intraepithelial neoplasia (PanIN), the precursor of PDAC. The identities of the other factors/events required to drive PanIN formation remain elusive. Here, optic-clear 3D histology is used to analyze entire pancreases of 2-week-old Pdx1-Cre; LSL-KrasG12D/+ (KC) mice to detect the earliest emergence of PanIN and observed that the occurrence is independent of physical location. Instead, it is found that the earliest PanINs overexpress Muc4 and associate with αSMA+ fibroblasts in both transgenic mice and human specimens. Mechanistically, KrasG12D/+ pancreatic cells upregulate Muc4 through genetic alterations to increase proliferation and fibroblast recruitments via Activin A secretion and consequently enhance cell transformation for PanIN formation. Inhibition of Activin A signaling using Follistatin (FST) diminishes early PanIN-associated fibroblast recruitment, effectively curtailing PanIN initiation and growth in KC mice. These findings emphasize the vital role of interactions between oncogenic KrasG12D/+ -driven genetic alterations and induced microenvironmental changes in PanIN initiation, suggesting potential avenues for early PDAC diagnostic and management approaches.

Blood-based Migration Signature Biomarker Panel Discriminates Early Stage New Onset Diabetes related Pancreatic Ductal Adenocarcinoma from Type 2 Diabetes

Background and aimsWhile type 2 diabetes is a well-known risk factor for pancreatic ductal adenocarcinoma (PDAC), PDAC-induced new-onset diabetes (PDAC-NOD) is a manifestation of underlying PDAC. In this study, we sought to identify potential blood-based biomarkers for distinguishing PDAC-NOD from type 2 diabetes (T2DM) without PDAC. Materials and methodsBy ELISA analysis, a migration signature biomarker panel comprising tissue factor pathway inhibitor (TFPI), tenascin C (TNC-FNIII-C) and CA 19–9 was analyzed in plasma samples from 50 PDAC-NOD and 50 T2DM controls. ResultsBoth TFPI (area under the curve (AUC) 0.71) and TNC-FNIII-C (AUC 0.69) outperformed CA 19–9 (AUC 0.60) in distinguishing all stages of PDAC-NOD from T2DM controls. The combined panel showed an AUC of 0.82 (95% CI = 0.73–0.90) (p = 0.002). In the PDAC-NOD early stage II samples, the three biomarkers had an AUC of 0.84 (95% CI = 0.73–0.93) vs CA 19-9, AUC = 0.60, (95% CI = 0.45–0.73), which also improved significance (p = 0.0123). ConclusionThe migration signature panel adds significantly to CA 19–9 to discriminate PDAC-NOD from T2DM controls and warrants further validation for high-risk group stratification.

Low dosage combination treatment with metformin and simvastatin inhibits obesity-promoted pancreatic cancer development in male KrasG12D mice

Pancreatic ductal adenocarcinoma (PDAC), a highly lethal disease with limited therapeutic options, may benefit from repurposing of FDA-approved drugs in preventive or interceptive strategies in high-risk populations. Previous animal studies demonstrated that the use of metformin and statins as single agents at relatively high doses restrained PDAC development. Here, four-week-old mice expressing KrasG12D in all pancreatic lineages (KC mice) and fed an obesogenic high fat, high calorie diet that promotes early PDAC development were randomized onto low dosage metformin, simvastatin, or both drugs in combination administered orally. Dual treatment attenuated weight gain, fibro-inflammation, and development of advanced PDAC precursor lesions (pancreatic intraepithelial neoplasia [PanIN]-3) in male KC mice, without significant effect in females or when administered individually. Dual-treated KC mice had reduced proliferation of PanIN cells and decreased transcriptional activity of the Hippo effectors, YAP and TAZ, which are important regulators of PDAC development. Metformin and simvastatin also synergistically inhibited colony formation of pancreatic cancer cells in vitro. Together, our data demonstrated that a combination of low doses of metformin and simvastatin inhibits PDAC development and imply that both drugs are promising agents for being tested in clinical trials for preventing pancreatic cancer progression.

Early vs conventional onset pancreatic ductal adenocarcinoma: analysis of surgical and oncologic outcomes in patients undergoing curative intent resection

BackgroundPancreatic ductal adenocarcinoma (PDAC) impacts patients in their 60s, but its incidence in younger patients is increasing. We hypothesize that younger patients may have worse oncologic outcomes. MethodsPatients who underwent curative pancreatic resection for PDAC between January 2011 and December 2021 at a single institution were analyzed. Early-onset pancreatic cancer (EOPC) was defined as pancreatic cancer diagnosed in patients ≤50 years. Clinical and survival outcomes were compared between EOPC and Conventional Onset Pancreas Cancer (COPC). ResultsA total of 1133 patients were identified, 65 (5.7%) were EOPC. Preoperative patient characteristics including sex, smoking status, alcohol habitus, diabetes mellitus, CA 19-9, and neoadjuvant therapy were similar between EOPC and COPC (p > 0.05). EOPC patients were more likely non-white (p = 0.03), had lower ASA scores (p = 0.02) and larger median tumor size (33 vs 28 mm, p = 0.04), but had similar pathological stages and rate of R0 resections (p > 0.05). Postoperative outcomes were similar (p > 0.05). There was no statistically significant difference in overall (HR 0.93, CI 0.64, 1.33; p = 0.68) or recurrence free (HR 1.05, CI 0.75, 1.48; p = 0.77) survival between the EOPC and COPC after adjusting for significant factors. ConclusionPatients with EOPC who underwent surgical resection had similar oncological outcomes compared to patients with COPC.

Cancer-associated fibroblasts drive early pancreatic cancer cell invasion via the SOX4/MMP11 signalling axis

Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant cancer-associated fibroblasts (CAFs), early perineural invasion (PNI) and microvascular invasion (MVI). However, the differentiation trajectories and underlying molecular mechanisms of CAFs in PDAC early invasion have not been fully elucidated. In this study, we integrated and reanalysed single-cell data from the National Geoscience Data Centre (NGDC) database and confirmed that myofibroblast-like CAFs (myCAFs) mediated epithelial-mesenchymal transformation (EMT) and enhanced the invasion abilities of PDAC cells by secreting regulators of angiogenesis and metastasis. Furthermore, we constructed a differentiation trajectory of CAFs and revealed that reprogramming from iCAFs to myCAFs was associated with poor prognosis. Mechanistically, SOX4 was aberrantly activated in myCAFs, which promoted the secretion of MMP11 and eventually induced early cancer cell invasion. Together, our results provide a comprehensive transcriptomic overview of PDAC patients with early invasion and reveal the intercellular crosstalk between myCAFs and cancer cells, which suggests potential targets for early invasion PDAC therapy.

Automated classification of urine biomarkers to diagnose pancreatic cancer using 1-D convolutional neural networks

BackgroundEarly diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC) is the main key to surviving cancer patients. Urine proteomic biomarkers which are creatinine, LYVE1, REG1B, and TFF1 present a promising non-invasive and inexpensive diagnostic method of the PDAC. Recent utilization of both microfluidics technology and artificial intelligence techniques enables accurate detection and analysis of these biomarkers. This paper proposes a new deep-learning model to identify urine biomarkers for the automated diagnosis of pancreatic cancers. The proposed model is composed of one-dimensional convolutional neural networks (1D-CNNs) and long short-term memory (LSTM). It can categorize patients into healthy pancreas, benign hepatobiliary disease, and PDAC cases automatically.ResultsExperiments and evaluations have been successfully done on a public dataset of 590 urine samples of three classes, which are 183 healthy pancreas samples, 208 benign hepatobiliary disease samples, and 199 PDAC samples. The results demonstrated that our proposed 1-D CNN + LSTM model achieved the best accuracy score of 97% and the area under curve (AUC) of 98% versus the state-of-the-art models to diagnose pancreatic cancers using urine biomarkers.ConclusionA new efficient 1D CNN-LSTM model has been successfully developed for early PDAC diagnosis using four proteomic urine biomarkers of creatinine, LYVE1, REG1B, and TFF1. This developed model showed superior performance on other machine learning classifiers in previous studies. The main prospect of this study is the laboratory realization of our proposed deep classifier on urinary biomarker panels for assisting diagnostic procedures of pancreatic cancer patients.

Abstract 6515: Pancreatic ductal adenocarcinoma (PDAC) early detection

Abstract Introduction Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer and is one of the deadliest cancer in the U.S., with a 5-year survival rate of just 11%. It is expected that ~62,000 new cases will be diagnosed in the US in 2023 and &amp;gt;70% of those will be at the regional or distant state, when curative resection is no longer an option. It is imperative that tools enabling early disease detection (stages I and II) are developed to improve patient survival outcomes. Here, we report the results of a study on the utility of extracellular vesicles (EVs) for early PDAC detection. Methods Our case-control training set was comprised of 75 pathologically confirmed PDAC cases (Stage I = 31, Stage II = 44) and 640 controls (including 11 subjects with pancreatitis) for EV biomarker and algorithm selection via machine learning. EVs from plasma were isolated using a proprietary technology, then EV-bound proteins of interest were analyzed via an immunoassay. A second independently collected cohort of 20 confirmed PDAC cases (Stage I = 10, Stage II = 10) and 27 controls (including 9 patients newly diagnosed with diabetes) was used for validation. Results The machine learning analysis using EV-isolated proteins generated a signature that utilized 8 different biomarkers, with an AUC of 0.989 (95% CI: 0.980 - 0.998) in the training set and an AUC of 0.987 (CI: 0.964 - 1.000) in the validation set. For the validation set, the sensitivity was 95% (CI: 76.4% - 99.1%) and the specificity was 92.6% (CI: 76.6% - 97.9%), with 10 out of 10 stage I cases and 9 out of 10 stage II cases correctly classified. Conclusions The ability to alter the future outcomes of PDAC patients will be predicated on development of a new generation of early-detection biomarkers and technologies. The use of EV protein signatures, a new class of cell-free biomarker, permits detection at high sensitivity and specificity, as demonstrated for the independently collected validation cohort. Studies aimed to assess this test for high-risk patients (family history of PDAC, known germline mutations, precursor lesions, hereditary pancreatitis, new onset diabetes will continue towards the establishment of real-world evidence. Citation Format: Juan P. Hinestrosa, Harmeet Dhani, Gregor Schroeder, Jean M. Lewis, Heath I. Balcer, Razelle Kurzrock, Dove Keith, Rosalie Sears, Paul Billings. Pancreatic ductal adenocarcinoma (PDAC) early detection. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6515.