The Potential of Salivary Biomarkers in Early Detection of Pancreatic Ductal Adenocarcinoma: A Systematic Review.

Background:Increased expression of the homeobox (HOX) transcript antisense RNA (HOTAIR) has been reported in multiple types of malignancies and enhances the proliferation and migration of cancer cells. However, the association between HOTAIR expression and tumor progression and prognosis remains controversial. We performed a meta-analysis to clarify the association between the expression of HOTAIR and the clinicopathological features and prognosis in different cancers.Methods:A systematic search of the PubMed, Web of Science, EMBASE, and Ovid databases was conducted, up to September 2016, for eligible studies involving HOTAIR expression and malignancies. The odds ratios (ORs), hazard ratios (HRs), and corresponding 95% confidence intervals (CIs) were calculated using fixed- or random-effect models. Any publication bias was evaluated using Begg and Egger tests, and adjusted using the trim and fill method if a bias existed.Results:A total of 4116 patients from 44 studies were included in our meta-analysis. The results showed that high HOTAIR expression was associated with an advanced clinical tumor stage (OR = 3.90, 95% CI = 3.02–5.03, P < .001), lymph node metastasis (OR = 3.11, 95% CI = 2.15–4.49, P < .001), poor differentiation of the tumor (OR = 1.56, 95% CI = 1.01–2.41, P = .03), and worse prognosis (HR = 2.16, 95% CI = 1.73–2.69, P < .001) in different cancer types. HOTAIR expression was more predictive in monitoring the clinical tumor stage of patients and there was no significant heterogeneity or publication bias found in the analysis.Conclusion:Our meta-analysis suggests that HOTAIR is positively correlated with tumor development and negatively correlated with clinical outcome. Thus, an increase in HOTAIR expression may be a potential biomarker for tumor progression and evaluation of prognosis.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a poor prognosis. This poor prognosis is largely attributed to a late-stage diagnosis. Recent advancements in metabolomics have emerged as a promising avenue for biomarker discovery in PDAC. This systematic review evaluates the potential of metabolite biomarkers for early detection of PDAC. Four studies meeting the inclusion criteria were analyzed, encompassing experimental, case-control, and prospective cohort designs. Key findings include the identification of distinct metabolic subtypes in PDAC with varying sensitivities to metabolic inhibitors. A biomarker signature comprising nine metabolites plus CA19-9 showed high accuracy in distinguishing PDAC from chronic pancreatitis, outperforming CA19-9 alone. Another study identified a five-metabolite signature demonstrating high diagnostic accuracy for pancreatic cancer, differentiating it from type 2 diabetes mellitus. A two-metabolite model (isoleucine and adrenic acid) showed superior performance in detecting stage-I PDAC compared to CA19-9. These studies consistently demonstrate altered metabolic pathways in PDAC patients compared to healthy controls and those with benign pancreatic conditions. Integrating metabolomic data with other molecular profiling approaches has become a powerful strategy for improving diagnostic accuracy. However, challenges remain, including the influence of confounding factors, the need for large-scale validation studies, and the standardization of metabolomic methods. The potential of artificial intelligence in interpreting complex metabolomic data offers promising avenues for future research. This review highlights the significant potential of metabolite biomarkers in early PDAC detection while emphasizing the need for further validation and refinement of these approaches.

e14536 Background: Pancreatic ductal adenocarcinoma (PDAC) is highly aggressive with one- and five-year average net survival rates of approximately 28% and 8%, respectively (NHS Digital 2023). The majority of PDACs are diagnosed in late stages, when surgical resection and cure are not possible. Without better screening tools, by 2030, PDAC is expected to become the second leading cause of cancer death (Rahib et al. 2014). Undoubtedly, there is an exceedingly critical need for an early detection tool of PDAC. Our study utilizes multiplexed sensitive targeted proteomics, a unique biobank with longitudinal serum samples, and machine learning to measure and evaluate the change in abundance of select serum proteins over time. With this, we identified a novel panel of serum biomarkers for possible early detection of PDAC. Methods: Liquid chromatography coupled to selected reaction monitoring (LC-SRM) based targeted proteomics was used to measure the abundances of 140 candidate biomarker proteins in longitudinal serum samples of 82 subjects with PDAC and 82 healthy control subjects selected from the Department of Defense Serum Repository (DODSR) between 1988 to 2020. A random forest machine learning approach was used to develop two classification models using the SRM data. One model (termed the “cross-sectional” model) was trained on data from samples that were drawn during the “diagnosis window” (defined as 100 days before to 100 days after the date of each case subject’s diagnosis). The other “longitudinal” model was trained using data precomputed to measure change in relative abundance from 1-4 years before diagnosis to the “diagnosis window.” Results: The cross-sectional and longitudinal models yielded high classification performance, achieving area under the curve (AUC) values of 0.89 and 0.91, respectively. This of utilizing serum measurements from four years to one year prior to diagnosis as a reference point. The feature selection algorithm consistently selected fifteen proteins for each type of model. Among the ten proteins identified and overlapping between the two models, Gelsolin, Cartilage oligomeric matrix protein, Tetranectin, TIMP metallopeptidase inhibitor 1, and Apolipoprotein A4 have been linked to PDAC in previous studies measuring biomarker levels in sera, plasma, or tissue. Conclusions: Our study identified additional novel protein biomarkers which, after validation, may be utilized with the other proteins in the classifiers for earlier detection of pancreatic adenocarcinoma. Our findings highlight the promise of detecting PDAC earlier by determining longitudinal protein abundance change in serum and the potential substantial changes to PDAC outcomes if successful in identifying PDAC at earlier stages.

BackgroundEarly diagnosis of esophageal squamous cell carcinoma (ESCC) is an important issue to improve the prognosis. HOX transcript antisense RNA (HOTAIR), a long noncoding RNA (lncRNA) expressed from the HOXC locus, has been recently revealed as an oncogenic regulator in ESCC. This study aimed to investigate whether serum HOTAIR is involved in the diagnosis of ESCC.MethodsIn this study, we detected serum HOTAIR expression in 50 patients with ESCC (including 42 tumor resection and 8 without surgery) and 20 healthy volunteers to investigate the role of serum HOTAIR in ESCC using the quantitative real-time polymerase chain reaction (qRT-PCR) method.ResultsClinical data indicated that serum HOTAIR were correlated with TNM stage. The expression level of serum HOTAIR (0.189 ± 0.010) was significantly higher in ESCC patients compared with that of healthy controls (0.055 ± 0.008, P < 0.01). The ROC curve analysis yielded an area under the ROC curve (AUC) value of 0.793 (95% CI: 0.692 to 0.895, P < 0.01). Also, the serum HOTAIR expression level decreased obviously in postoperative samples (one month after the surgery) compared to preoperative specimens. Moreover, there was a significant correlation between serum HOTAIR expression and the expression of HOTAIR in ESCC tissue according to Pearson correlation analysis.ConclusionsOur study, for the first time, demonstrated that serum HOTAIR might serve as a potential biomarker for the diagnosis of ESCC.

There is urgent need for biomarkers that provide early detection of pancreatic ductal adenocarcinoma (PDAC) as well as discrimination of autoimmune pancreatitis, as current clinical approaches are not suitably accurate for precise diagnosis. We used mass spectrometry to analyze protein profiles of more than 300 plasma specimens obtained from PDAC, noncancerous pancreatic diseases including autoimmune pancreatitis patients and healthy subjects. We obtained 1063 proteomic signals from 160 plasma samples in the training cohort. A proteomic signature consisting of 7 mass spectrometry signals was used for construction of a proteomic model for detection of PDAC patients. Using the test cohort, we confirmed that this proteomic model had discrimination power equal to that observed with the training cohort. The overall sensitivity and specificity for detection of cancer patients were 82.6% and 90.9%, respectively. Notably, 62.5% of the stage I and II cases were detected by our proteomic model. We also found that 100% of autoimmune pancreatitis patients were correctly assigned as noncancerous individuals. In the present paper, we developed a proteomic model that was shown able to detect early-stage PDAC patients. In addition, our model appeared capable of discriminating patients with autoimmune pancreatitis from those with PDAC.

Since the introduction of endoscopic ultrasound guided fine-needle aspiration (EUS-FNA), EUS has assumed a growing role in the diagnosis and management of pancreatic ductal adenocarcinoma (PDAC). The objective of this review is to discuss the various applications of EUS and EUS-FNA in PDAC. Initially, its use for detection, diagnosis and staging will be described. EUS and EUS-FNA are highly accurate modalities for detection and diagnosis of PDAC, this high accuracy, however, is decreased in specific situations particularly in the presence of chronic pancreatitis. Novel techniques such as contrast-enhanced EUS, elastography and analysis of DNA markers such as k-ras mutation analysis in FNA samples are in progress and might improve the accuracy of EUS in the detection of PDAC in this setting and will be addressed. EUS and EUS-FNA have recently evolved from a diagnostic to a therapeutic technique in the management of PDAC. Significant developments in therapeutic EUS have occurred including advances in celiac plexus interventions with direct injection of ganglia and improved pain control, EUS-guided fiducial and brachytherapy seed placement, fine-needle injection of intra-tumoral agents and advances in EUS-guided biliary drainage. The future role of EUS and EUS in management of PDAC is still emerging.

Early detection of pancreatic ductal adenocarcinoma (PDAC) is essential for survival. Preliminary research demonstrated significant associations between structural alternation of mycobiota and PDAC. In this study, we investigated the associations between oral mycobiota and PDAC. We further explored mycobiota biomarkers for PDAC detection. We enrolled 34 PDAC patients and 35 matched healthy controls from West China hospital in Southwest China. Demographic data, clinical information, and salivary samples were collected. Mycobiota characteristics were defined using Internal Transcribed Spacer (ITS) ribosomal RNA sequencing. We found that the PDAC patients had significant increase in fungal abundance (P < 0.001) and significant decrease in fungal diversity (P < 0.001) in comparison to the healthy controls. A higher abundance of Basidiomycota and Unclassifed_p_Ascomycota was associated with an increased risk of PDAC. With each increase of abundance of g__unclassified_k__Fungi and g__unclassified_p__Ascomycota in PDAC patients, the risk of pancreatic cancer increased by 1.359 odds and 1.260 odds, respectively. Aspergillus (AUC = 0.983, 95% CI 0.951–1.000) and Cladosporium (AUC = 0.969, 95% CI 0.921–1.000) achieved high classification powers to distinguish PDAC patients from the healthy controls. The rapid, inexpensive tests of ITS1 sequencing of mycobiota and PCR detection of potential fungal biomarkers make it promising for the clinical practice to use oral microbes for PDAC early detection and prevention. Results of our study provide evidence that salivary mycobiota may provide insights into cancer risk, prevention, and detection.

Markers are needed to facilitate early detection of pancreatic ductal adenocarcinoma (PDAC), which is often diagnosed too late for effective therapy. Starting with a PDAC cell reprogramming model that recapitulated the progression of human PDAC, we identified secreted proteins and tested a subset as potential markers of PDAC. We optimized an enzyme-linked immunosorbent assay (ELISA) using plasma samples from patients with various stages of PDAC, from individuals with benign pancreatic disease, and from healthy controls. A phase 1 discovery study (n = 20), a phase 2a validation study (n = 189), and a second phase 2b validation study (n = 537) revealed that concentrations of plasma thrombospondin-2 (THBS2) discriminated among all stages of PDAC consistently. The receiver operating characteristic (ROC) c-statistic was 0.76 in the phase 1 study, 0.84 in the phase 2a study, and 0.87 in the phase 2b study. The plasma concentration of THBS2 was able to discriminate resectable stage I cancer as readily as stage III/IV PDAC tumors. THBS2 plasma concentrations combined with those for CA19-9, a previously identified PDAC marker, yielded a c-statistic of 0.96 in the phase 2a study and 0.97 in the phase 2b study. THBS2 data improved the ability of CA19-9 to distinguish PDAC from pancreatitis. With a specificity of 98%, the combination of THBS2 and CA19-9 yielded a sensitivity of 87% for PDAC in the phase 2b study. A THBS2 and CA19-9 blood marker panel measured with a conventional ELISA may improve the detection of patients at high risk for PDAC.

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis and is a leading cause of cancer mortality. Early diagnosis is difficult due to the anatomical characteristics of the pancreas, which is a long and thin organ located dorsal to the stomach and large intestine. The aim of the present study was to search for protein biomarkers for PDAC in serum extracellular vesicles (EVs) using mass spectrometry, and to validate identified biomarkers using an enzyme-linked immunosorbent assay (ELISA) of sera from patients. Comprehensive and targeted proteomic analyses for biomarker discovery and verification were performed using EVs from serum of patients with PDAC, patients with chronic pancreatitis (PT) and healthy volunteers (HVs). For validation, the discriminatory power of candidate proteins was evaluated using an ELISA. Of the 3,043 proteins analyzed, 45 were identified as potential biomarkers, with receptor expression-enhancing protein 5 (REEP5) selected for further analysis. The serum level of fucosylated REEP5 was significantly higher in PDAC cases compared with in PT and HVs (P<0.001). The areas under the curve (AUC) of the receiver operator characteristic were 0.928 for fucosylated REEP5 and 0.805 for carbohydrate antigen 19-9 (CA19-9) in PDAC vs. non-cancer controls. The AUCs were 0.962 for fucosylated REEP5 and 0.810 for CA19-9 in stages I and II of PDAC. These results indicate that fucosylated REEP5 is a novel serum EV biomarker for detection of early stage PDAC. Further analysis in a larger cohort is warranted to evaluate the clinical utility of fucosylated REEP5 as a biomarker for PDAC.

Introduction: EUS has been recommended when computer tomography (CT) is inconclusive for PDAC. CA19 – 9 has been suggested as a potential marker in the detection of PDAC. Aims: The aim of our study was to assess the utility of CA19 – 9 and EUS in PDAC detection after a negative abdominal CT in a selected population of pancreatic EUS referrals. Methods: A retrospective study of patients who underwent radial EUS between 2012 and 2015 in our institution, with the aim to confirm the presence or absence of PDAC subsequent to no tumor detection by abdominal CT compared normal with elevated Ca 19 – 9 level. Results: 46 patients (20 male, 26 female, mean age 63.54 ± 18 years) were recruited in the study. 24 patient had abdominal pain, 3 fever, 9 weight lost and 18 patients were asymptomatic. EUS revealed 18 PDAC and 28 EUS were negative. The CA 19 – 9 level was normal in 8 and elevated in 10 patients with PDAC, and it was normal in 23 and elevated in 5 patients with negative EUS. Sensitivity, specificity and positive and negative predictive value of CA19 – 9 were 55.5%, 82.1%, 66.6% and 74.1%, respectively. Conclusions: EUS is recommended to be performed, when PDAC is suspected, but CT is negative. Ca 19 – 9 is not a reliable diagnostic tool for PDAC.

DNA markers for pancreatic ductal adenocarcinoma (PDAC) are urgently needed for detection of minimally invasive disease. The epigenetic relevance of the cysteine dioxygenase 1 gene (CDO1) has been never investigated in PDAC. Three studies, including cellular experiments, tissue validation, and pilot testing for pancreatic cytology, were carried out. Promoter DNA methylation value (MV) of CDO1 was quantified by quantitative methylation‐specific PCR. CDO1 expression was consistent with its promoter DNA methylation in 7 PDAC cell lines. In 160 retrospectively collected primary PDAC tumor tissues, MV was significantly higher compared to the corresponding noncancerous pancreas (area under the receiver operating characteristic curve [AUC] = 0.97, P < .0001), and CDO1 hypermethylation was highly specific to PDAC tumor tissues. CDO1 hypermethylation group (MV over 19) was significantly associated with diverse prognostic factors in PDAC. Surprisingly, it was significantly higher in prospectively collected PDAC cytology samples (n = 37), including both pancreatic juice (n = 12) and endoscopic ultrasound‐fine needle aspiration (EUS‐FNA) cytology (n = 25) compared to pancreatic benign diseases (AUC = 0.96, P < .0001). Detection of PDAC was confirmed by DNA testing in 35 of 37 patients (95% sensitivity); thus, it was more sensitive than cytology (33%) or EUS‐FNA cytology (88%). Promoter DNA methylation of CDO1 is extremely specific for PDAC tumors, and accumulates with PDAC tumor progression. It could be a definitive diagnostic marker of PDAC in pancreatic juice or EUS‐FNA cytology.

The purpose of this study was to evaluate whether intravoxel incoherent motion (IVIM) parameters can enhance the diagnostic performance of MRI in differentiating normal pancreatic parenchyma from solid pancreatic adenocarcinomas. This study included 113 participants: 66 patients diagnosed with pancreatic adenocarcinoma and 47 healthy volunteers. An MRI was conducted at 1.5 T MR unit, using nine b-values. Postprocessing involved analyzing both conventional monoexponential apparent diffusion coefficient (ADC) and IVIM parameters (diffusion coefficient D-pure molecular diffusion coefficient, perfusion-dependent diffusion coefficient D*-pseudodiffusion coeffitient, and perfusion fraction coefficient (f)) across four different b-value selections. Significantly higher parameters were found in the control group when using high b-values for the pure diffusion analysis and all b-values for the monoexponential analysis. Conversely, in the study group, the parameters were affected by low b-values. Most parameters could differentiate between normal and cancerous tissue, with D* showing the highest diagnostic performance (AUC 98-100%). A marked decrease in perfusion in the patients with pancreatic cancer, indicated by the significant differences in the D* medians between groups, was found. In conclusion, standard ADC maps alone may not suffice for a definitive pancreatic cancer diagnosis, and incorporating IVIM into MRI protocols is recommended, as the reduced tissue perfusion detected by the IVIM parameters is a promising marker for pancreatic adenocarcinoma.

The aim of this study was to establish a minimally invasive and simple screening test for detection of pancreatic ductal adenocarcinoma (PDAC) using duodenal juice (DJ). Duodenal juice was collected prospectively before endoscopic retrograde cholangiopancreatography in 46 patients. A protease inhibitor was not added to the samples collected during the initial 2.5 minutes but was added in the latter 2.5 minutes. Thereafter, secretin was administered intravenously, and DJ was subsequently collected for additional 10 minutes. The sensitivities of carcinoembryonic antigen (CEA), S100 calcium-binding protein P (S100P), and interleukin 8 in DJ and pancreatic juice were assessed. There were 30 patients with PDAC and 16 with benign lesions. It was possible to collect an adequate amount of DJ without secretin administration. In the PDAC group, CEA concentrations in DJ were significantly higher than those in the benign group, even without the use of a protease inhibitor. S100P levels in DJ in the PDAC group were significantly higher than those in the benign group in the presence of the protease inhibitor. Duodenal juice collection during routine upper endoscopy and assessments of CEA and S100P in DJ might become a useful screening test for detection of PDAC.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal neoplasm because of difficulties in early detection. Several studies have recently suggested that exosomes may have potential as novel biomarkers. This study aimed to isolate exosomes from pancreatic juice and to investigate whether exosomal microRNAs (ex-miRs) could be used as biomarkers for PDAC. Pancreatic juice was collected from patients with PDAC and chronic pancreatitis (CP) by endoscopic retrograde pancreatography. Exosomes were extracted by ultracentrifugation. The presence of exosomes was confirmed by electron microscopy and Western blotting using anti-CD63, -CD81, and -TSG101 antibodies. Relative levels of ex-miR-21 and ex-miR-155 were quantified and compared between PDAC and CP patients. A total of 35 pancreatic juice samples (27 PDAC and 8 CP) were collected. Relative levels of both ex-miR-21 and ex-miR-155 were significantly higher in PDAC patients compared with CP patients (p < 0.001 and p = 0.008, respectively). By contrast, no significant difference was apparent in relative levels of miR-21 and miR-155 in whole pancreatic juice from PDAC patients compared with CP patients (p = 0.08 and p = 0.61, respectively). Ex-miR-21 and ex-miR-155 levels discriminated PDAC patients from CP patients with area under the curve values of 0.90 and 0.89, respectively. The accuracies of ex-miR-21 levels, ex-miR-155 levels, and pancreatic juice cytology were 83%, 89%, and 74%, respectively. When combining the results of ex-miR profiling with pancreatic juice cytology, the accuracy was improved to 91%. We successfully extracted exosomes from pancreatic juice. Ex-miRs, including ex-miR-21 and ex-miR-155, in pancreatic juice may be developed as biomarkers for PDAC.

The lack of tools for early detection of pancreatic ductal adenocarcinoma (PDAC) is directly correlated to the abysmal survival rate in patients. In addition to several potential detection tools under active investigation, we present the gut microbiome and its metabolic complement as one of the earliest detection tools that could be useful in patients at high risk for PDAC. A combination of 16s pyrosequencing and whole-genome sequencing of gut microbiota in a spontaneous genetically engineered PDAC murine model (KRASG12DTP53R172HPdxCre or KPC) showed a progressive Proteobacterial and Firmicutes dominance in gut microbiota in early stages of PDAC development. Upon in silico reconstruction of active metabolic pathways within the altered microbial flora, polyamine and nucleotide biosynthetic pathways were found to be significantly elevated. These metabolic products are known to be actively assimilated by the host and eventually utilized by rapidly dividing cells for proliferation, validating their importance in the context of tumorigenesis. In KPC mice, as well as PDAC patients, we show significantly elevated serum polyamine concentration. Therefore, at the early stages of tumorigenesis, the gut microbial composition changes in a way to promote inflammation and release metabolites that foster host tumorigenesis, thereby fulfilling the “vicious cycle hypothesis” of the role of the microbiome in health and disease states. Our results provide a potential, precise, noninvasive tool for early detection of PDAC, which will result in improved outcomes. Citation Format: Roberto Mendez, Kousik Kesh, Nivedita Arora, Leá Di Martino, Florencia McAllister, Nipun Merchant, Sulagna Banerjee, Santanu Banerjee. Microbial polyamines and early detection of pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr A67.