Study of SARS-CoV-2 in semen from asymptomatic donors with the presence of virus in nasopharyngeal swabs.

RESEARCH QUESTION: Is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) present in semen samples from asymptomatic donors who have positive virus results from nasopharyngeal swabs? DESIGN: Nasopharyngeal PCR was performed on 1943 sperm donors between January 2021 and March 2022. The result was positive for 140 donations, and the presence of SARS-CoV-2 could be studied in cryopreserved semen from 84 of these donors. This included 67 participants in whom the quality of fresh semen could be compared with the previous donation, the day of the PCR-positive nasopharyngeal sampling and the first subsequent donation. Semen donations were cryopreserved following total semen (n = 26) or ready-to-use (n = 58) protocols. The presence of SARS-CoV-2 in cryopreserved samples was determined by reverse transcription PCR. Semen quality (volume, concentration and progressive motility) was evaluated in accordance with World Health Organization 2010 recommendations. RESULTS: SARS-CoV-2 virus was not detected in any cryopreserved total semen or ready-to-use samples. No significant differences in semen volume, concentration or progressive motility were observed between the last previous donation, the day of the positive PCR nasopharyngeal sampling and the first subsequent donation. CONCLUSIONS: The lack of detection of SARS-CoV-2 in semen samples from asymptomatic individuals infected with SARS-CoV-2 supports the safety of assisted human reproduction treatments using this type of sample.

Serum nuclear magnetic resonance metabolomics analysis of human metastatic colorectal cancer: Biomarkers and pathway analysis.

We describe the use of nuclear magnetic resonance metabolomics to analyze blood serum samples from healthy individuals (n = 26) and those with metastatic colorectal cancer (CRC; n = 57). The assessment, employing both linear and nonlinear multivariate data analysis techniques, revealed specific metabolite changes associated with metastatic CRC, including increased levels of lactate, glutamate, and pyruvate, and decreased levels of certain amino acids and total fatty acids. Biomarker ratios such as glutamate-to-glutamine and pyruvate-to-alanine were also found to be related to CRC. The study also found that glutamate was linked to progression-free survival and that both glutamate and 3-hydroxybutyrate were risk factors for metastatic CRC. Additionally, gas chromatography coupled to flame-ionization detection was utilized to analyze the fatty acid profile and pathway analysis was performed on the profiled metabolites to understand the metabolic processes involved in CRC. A correlation was also found between the presence of certain metabolites in the blood of CRC patients and certain clinical features.

Serum biomarkers for the differentiation of autoimmune pancreatitis from pancreatic ductal adenocarcinoma.

Autoimmune pancreatitis (AIP), a chronic inflammation caused by the immune system attacking the pancreas, usually presents imaging and clinical features that overlap with those of pancreatic ductal adenocarcinoma (PDAC). Serum biomarkers, substances that quantitatively change in sera during disease development, are a promising non-invasive tool with high utility for differentiating between these diseases. In this way, the presence of AIP is currently suspected when serum concentrations of immunoglobulin G4 (IgG4) antibody are elevated. However, this approach has some drawbacks. Notably, IgG4 antibody concentrations are also elevated in sera from some patients with PDAC. This review focuses on the most recent and relevant serum biomarkers proposed to differentiate between AIP and PDAC, evaluating the usefulness of immunoglobulins, autoantibodies, chemokines, and cytokines. The proposed serum biomarkers have proven useful, although most studies had a small sample size, did not examine their presence in patients with PDAC, or did not test them in humans. In addition, current evidence suggests that a single serum biomarker is unlikely to accurately differentiate these diseases and that a set of biomarkers will be needed to achieve adequate specificity and sensitivity, either alone or in combination with clinical data and/or radiological images.

Pancreatitis crónica: análisis de factores de progresión de la enfermedad / Chronic pancreatitis: analysis of disease progression factors

BACKGROUND: Alcohol and tobacco are important risk factors for chronic pancreatitis (CP). AIM: To analyze the effect of etiological factors such as tobacco and alcohol and pancreatic enzyme replacement therapy (PERT) in the progression of CP. MATERIAL AND METHODS: Patients with a diagnosis of CP were recruited and grouped according to variables such as tobacco, alcohol and PERT. They were followed for 18 months. Subsequently, different variables and analytical parameters involved in the progression of the disease were analyzed. RESULTS: A total of 50 patients diagnosed with CP were included. Of these, 28 patients underwent PERT, 39 were smokers and 33 were alcohol users. Compared with patients without PERT, those with PERT had a higher proportion of diabetes (64 and 32%, respectively), had a higher need for endoscopic treatment (25 and 0%, respectively) and a normal body mass index (71 and 27.3%, respectively. The smokers had higher calcium levels and increased lymphocytosis and leukocytosis. The alcohol consumption group had a higher mean age (p = 0.04) CONCLUSIONS: PERT may improve the nutritional status but does not reduce the need for endoscopic or surgical treatment. Smoking and alcohol consumption favored the progression of CP. Also, smoking induced a pro-inflammatory state.

[Chronic pancreatitis: analysis of disease progression factors]. / Pancreatitis crónica: análisis de factores de progresión de la enfermedad.

BACKGROUND: Alcohol and tobacco are important risk factors for chronic pancreatitis (CP). AIM: To analyze the effect of etiological factors such as tobacco and alcohol and pancreatic enzyme replacement therapy (PERT) in the progression of CP. MATERIAL AND METHODS: Patients with a diagnosis of CP were recruited and grouped according to variables such as tobacco, alcohol and PERT. They were followed for 18 months. Subsequently, different variables and analytical parameters involved in the progression of the disease were analyzed. RESULTS: A total of 50 patients diagnosed with CP were included. Of these, 28 patients underwent PERT, 39 were smokers and 33 were alcohol users. Compared with patients without PERT, those with PERT had a higher proportion of diabetes (64 and 32%, respectively), had a higher need for endoscopic treatment (25 and 0%, respectively) and a normal body mass index (71 and 27.3%, respectively. The smokers had higher calcium levels and increased lymphocytosis and leukocytosis. The alcohol consumption group had a higher mean age (p = 0.04) Conclusions: PERT may improve the nutritional status but does not reduce the need for endoscopic or surgical treatment. Smoking and alcohol consumption favored the progression of CP. Also, smoking induced a pro-inflammatory state.

Liquid biopsy approach to pancreatic cancer.

Pancreatic cancer (PC) continues to pose a major clinical challenge. There has been little improvement in patient survival over the past few decades, and it is projected to become the second leading cause of cancer mortality by 2030. The dismal 5-year survival rate of less than 10% after the diagnosis is attributable to the lack of early symptoms, the absence of specific biomarkers for an early diagnosis, and the inadequacy of available chemotherapies. Most patients are diagnosed when the disease has already metastasized and cannot be treated. Cancer interception is vital, actively intervening in the malignization process before the development of a full-blown advanced tumor. An early diagnosis of PC has a dramatic impact on the survival of patients, and improved techniques are urgently needed to detect and evaluate this disease at an early stage. It is difficult to obtain tissue biopsies from the pancreas due to its anatomical position; however, liquid biopsies are readily available and can provide useful information for the diagnosis, prognosis, stratification, and follow-up of patients with PC and for the design of individually tailored treatments. The aim of this review was to provide an update of the latest advances in knowledge on the application of carbohydrates, proteins, cell-free nucleic acids, circulating tumor cells, metabolome compounds, exosomes, and platelets in blood as potential biomarkers for PC, focusing on their clinical relevance and potential for improving patient outcomes.

Importance of BRCA mutation for the current treatment of pancreatic cancer beyond maintenance.

In this editorial, we comment on pancreatic cancer (PC), one of the most aggressive and lethal cancers. Only minimal improvements in survival rates have been achieved over recent years. Available chemotherapeutic regimens have little impact, and surgical resection remains the only reliable curative approach. We address current treatment options for these patients, focusing on the usefulness of breast cancer (BRCA) gene mutation as a prognostic biomarker and predictor of response to chemotherapy. Superior survival outcomes have been reported in patients with PC and mutant BRCA gene treated with first-line platinum-based chemotherapy. Therefore, it appears appropriate to include BRCA gene status among clinical criteria used to select the chemotherapy regimen. In addition, maintenance treatment with poly(ADP-ribose) polymerase inhibitors has been found to improve progression-free survival in patients with PC and mutated BRCA whose disease does not progress after first-line platinum-based chemotherapy. This combination has therefore been proposed as the optimal treatment regimen for these patients.

Untargeted Metabolomics for the Diagnosis of Exocrine Pancreatic Insufficiency in Chronic Pancreatitis.

Background and Objectives: The clinical manifestations and course of chronic pancreatitis (CP) are often nonspecific and variable, hampering diagnosis of the risk of exocrine pancreatic insufficiency (EPI). Development of new, reproducible, and non-invasive methods to diagnose EPI is therefore a major priority. The objective of this metabolomic study was to identify novel biomarkers associated with EPI. Materials and Methods: We analyzed 53 samples from patients with CP, 32 with and 21 without EPI, using an untargeted metabolomics workflow based on hydrophilic interaction chromatography coupled to high-resolution mass spectrometry. Principal component and partial least squares-discriminant analyses showed significant between-group differentiation, and univariate and multivariate analyses identified potential candidate metabolites that significantly differed between samples from CP patients with EPI and those without EPI. Results: Excellent results were obtained using a six-metabolic panel to diagnose the presence of EPI in CP patients (area under the ROC curve = 0.785). Conclusions: This study confirms the usefulness of metabolomics in this disease setting, allowing the identification of novel biomarkers to differentiate between the presence and absence of EPI in CP patients.

Circulating PTGS2, JAG1, GUCY2C and PGF mRNA in Peripheral Blood and Serum as Potential Biomarkers for Patients with Metastatic Colon Cancer.

Genes involved in the angiogenic process have been proposed for the diagnosis and therapeutic response of metastatic colorectal cancer (CRC). This study aimed to investigate the value of PTGS2, JAG1, GUCY2C and PGF-circulating RNA as biomarkers in metastatic CRC. Blood cells and serum mRNA from 59 patients with metastatic CRC and 47 healthy controls were analyzed by digital PCR. The area under the receiver operating characteristic curve (AUC) was used to estimate the diagnostic value of each mRNA alone or mRNA combinations. A significant upregulation of the JAG1, PTGS2 and GUCY2C genes in blood cells and serum samples from metastatic CRC patients was detected. Circulating mRNA levels in the serum of all genes were significantly more abundant than in blood. The highest discrimination ability between metastatic CRC patients and healthy donors was obtained with PTGS2 (AUC of 0.984) and GUCY2C (AUC of 0.896) in serum samples. Biomarker combinations did not improve the discriminatory capacity of biomarkers separately. Analyzed biomarkers showed no correlation with overall survival or progression-free survival, but GUCY2C and GUCY2C/PTGS2 expression in serum correlated significantly with the response to antiangiogenic agents. These findings demonstrate that assessment of genes involved in the angiogenic process may be a potential non-invasive diagnostic tool for metastatic CRC and its response to antiangiogenic therapy.

Novel Biomarkers to Distinguish between Type 3c and Type 2 Diabetes Mellitus by Untargeted Metabolomics.

Pancreatogenic diabetes mellitus (T3cDM) is a highly frequent complication of pancreatic disease, especially chronic pancreatitis, and it is often misdiagnosed as type 2 diabetes mellitus (T2DM). A correct diagnosis allows the appropriate treatment of these patients, improving their quality of life, and various technologies have been employed over recent years to search for specific biomarkers of each disease. The main aim of this metabolomic project was to find differential metabolites between T3cDM and T2DM. Reverse-phase liquid chromatography coupled to high-resolution mass spectrometry was performed in serum samples from patients with T3cDM and T2DM. Multivariate Principal Component and Partial Least Squares-Discriminant analyses were employed to evaluate between-group variations. Univariate and multivariate analyses were used to identify potential candidates and the area under the receiver-operating characteristic (ROC) curve was calculated to evaluate their diagnostic value. A panel of five differential metabolites obtained an area under the ROC curve of 0.946. In this study, we demonstrate the usefulness of untargeted metabolomics for the differential diagnosis between T3cDM and T2DM and propose a panel of five metabolites that appear altered in the comparison between patients with these diseases.

MMR-proficient and MMR-deficient colorectal cancer cells: 5-Fluorouracil treatment response and correlation to CD133 and MGMT expression.

Cancer stem cells (CSCs) from colorectal cancer (CRC), characterized by CD133 expression, have been associated with 5-fluorouracile (5-FU) chemoresistance. DNA repair mechanisms, such as O6-alkylguanine DNA alkyltransferase (MGMT) and mismatch repair (MMR) systems, have also been correlated to 5-FU resistance in CRC. The aim of this study was to evaluate the modulation of CD133 and MGMT in MMRproficient and MMR-deficient CRC cells under 5-FU treatment and the effect of this drug in CSCs. CD133 and MGMT methylation status were determined in MMR-proficient (SW480 and HT29) and MMR-deficient (RKO and HCT116) cell lines by methylation-specific PCRs. SW480 and RKO were selected to determine modulation of CD133, MGMT and MMR expression after 5-FU treatment by qPCR. In addition, CD133, MGMT and MMR were analyze in SW480 and RKO CSCs. No association between promoter methylation and MGMT and CD133 expression was found. 5-FU treatment increased CD133 expression independently to MMR status in SW480 and RKO and was able to increase hMLH1 expression in RKO, a MMR-deficient cell line. RKO/ CSCs overexpressed CD133 and MMR (hMSH2 and hMSH6) while SW480/CSCs showed a significant increase in CD133, MMR (hMLH1, hMSH2 and hMSH6) and MGMT, moreover 5-FU resistance than parental cell lines. Thus, although CSCs 5-FU chemoresistance appears to be independently to MMR status, hMLH1 might play a key role in CSC response to 5-FU. New drugs exploding these differences could benefit the prognostic of patients with CRC.

State of the Art in Exocrine Pancreatic Insufficiency.

Exocrine pancreatic insufficiency (EPI) is defined as the maldigestion of foods due to inadequate pancreatic secretion, which can be caused by alterations in its stimulation, production, transport, or interaction with nutrients at duodenal level. The most frequent causes are chronic pancreatitis in adults and cystic fibrosis in children. The prevalence of EPI is high, varying according to its etiology, but it is considered to be underdiagnosed and undertreated. Its importance lies in the quality of life impairment that results from the malabsorption and malnutrition and in the increased morbidity and mortality, being associated with osteoporosis and cardiovascular events. The diagnosis is based on a set of symptoms, indicators of malnutrition, and an indirect non-invasive test in at-risk patients. The treatment of choice combines non-restrictive dietary measures with pancreatic enzyme replacement therapy to correct the associated symptoms and improve the nutritional status of patients. Non-responders require the adjustment of pancreatic enzyme therapy, the association of proton pump inhibitors, and/or the evaluation of alternative diagnoses such as bacterial overgrowth. This review offers an in-depth overview of EPI in order to support the proper management of this entity based on updated and integrated knowledge of its etiopathogenesis, prevalence, diagnosis, and treatment.

Role of Exocrine and Endocrine Insufficiency in the Management of Patients with Chronic Pancreatitis.

BACKGROUND: Exocrine pancreatic insufficiency results from the destruction of the pancreatic parenchyma and is diagnosed by using direct or indirect tests, both of which have shortcomings. Chronic pancreatitis is the most frequent cause of this pathology in adults. METHODS: Patients meeting radiological or histological diagnostic criteria of chronic pancreatitis are enrolled and the stool elastase test is conducted, considering fecal elastase levels >200 µg/g to represent normal pancreatic function, and levels <200 µg/g to indicate the presence of exocrine pancreatic insufficiency. Additionally, we determine the body mass index of the patients and study their nutritional status and main biochemical and hematological variables, including their glucose and hemoglobin A1c (HbA1c) levels. RESULTS: Exocrine pancreatic insufficiency is detected in 60% of the patients. Among these, 83.3% are severe cases, and 72% of the latter also are diagnosed with endocrine pancreatic insufficiency (diabetes mellitus). During the nutritional status study, HbA1c levels are significantly higher, and magnesium and prealbumin levels are significantly lower in patients with exocrine pancreatic insufficiency than in those without this disease. CONCLUSIONS: Exocrine and endocrine pancreatic insufficiency are highly prevalent among patients with chronic pancreatitis and an early diagnosis of these diseases is vital to improve the clinical management of these patients and reduce their risk of mortality.

Discovery of Pancreatic Adenocarcinoma Biomarkers by Untargeted Metabolomics.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal cancers, with a 5-year survival rate of less than 5%. In fact, complete surgical resection remains the only curative treatment. However, fewer than 20% of patients are candidates for surgery at the time of presentation. Hence, there is a critical need to identify diagnostic biomarkers with potential clinical utility in this pathology. In this context, metabolomics could be a powerful tool to search for new robust biomarkers. Comparative metabolomic profiling was performed in serum samples from 59 unresectable PDAC patients and 60 healthy controls. Samples were analyzed by using an untargeted metabolomics workflow based on liquid chromatography, coupled to high-resolution mass spectrometry in positive and negative electrospray ionization modes. Univariate and multivariate analysis allowed the identification of potential candidates that were significantly altered in PDAC patients. A panel of nine candidates yielded excellent diagnostic capacities. Pathway analysis revealed four altered pathways in our patients. This study shows the potential of liquid chromatography coupled to high-resolution mass spectrometry as a diagnostic tool for PDAC. Furthermore, it identified novel robust biomarkers with excellent diagnostic capacities.

Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets.

Many clinical studies have revealed the high biological similarities existing among different skin pathological states. These similarities create difficulties in the efficient diagnosis of skin cancer, and encourage to study and design new intelligent clinical decision support systems. In this sense, gene expression analysis can help find differentially expressed genes (DEGs) simultaneously discerning multiple skin pathological states in a single test. The integration of multiple heterogeneous transcriptomic datasets requires different pipeline stages to be properly designed: from suitable batch merging and efficient biomarker selection to automated classification assessment. This article presents a novel approach addressing all these technical issues, with the intention of providing new sights about skin cancer diagnosis. Although new future efforts will have to be made in the search for better biomarkers recognizing specific skin pathological states, our study found a panel of 8 highly relevant multiclass DEGs for discerning up to 10 skin pathological states: 2 healthy skin conditions a priori, 2 cataloged precancerous skin diseases and 6 cancerous skin states. Their power of diagnosis over new samples was widely tested by previously well-trained classification models. Robust performance metrics such as overall and mean multiclass F1-score outperformed recognition rates of 94% and 80%, respectively. Clinicians should give special attention to highlighted multiclass DEGs that have high gene expression changes present among them, and understand their biological relationship to different skin pathological states.

Untargeted LC-HRMS-based metabolomics to identify novel biomarkers of metastatic colorectal cancer.

Colorectal cancer is one of the main causes of cancer death worldwide, and novel biomarkers are urgently needed for its early diagnosis and treatment. The utilization of metabolomics to identify and quantify metabolites in body fluids may allow the detection of changes in their concentrations that could serve as diagnostic markers for colorectal cancer and may also represent new therapeutic targets. Metabolomics generates a pathophysiological 'fingerprint' that is unique to each individual. The purpose of our study was to identify a differential metabolomic signature for metastatic colorectal cancer. Serum samples from 60 healthy controls and 65 patients with metastatic colorectal cancer were studied by liquid chromatography coupled to high-resolution mass spectrometry in an untargeted metabolomic approach. Multivariate analysis revealed a separation between patients with metastatic colorectal cancer and healthy controls, who significantly differed in serum concentrations of one endocannabinoid, two glycerophospholipids, and two sphingolipids. These findings demonstrate that metabolomics using liquid-chromatography coupled to high-resolution mass spectrometry offers a potent diagnostic tool for metastatic colorectal cancer.

Leukemia multiclass assessment and classification from Microarray and RNA-seq technologies integration at gene expression level.

In more recent years, a significant increase in the number of available biological experiments has taken place due to the widespread use of massive sequencing data. Furthermore, the continuous developments in the machine learning and in the high performance computing areas, are allowing a faster and more efficient analysis and processing of this type of data. However, biological information about a certain disease is normally widespread due to the use of different sequencing technologies and different manufacturers, in different experiments along the years around the world. Thus, nowadays it is of paramount importance to attain a correct integration of biologically-related data in order to achieve genuine benefits from them. For this purpose, this work presents an integration of multiple Microarray and RNA-seq platforms, which has led to the design of a multiclass study by collecting samples from the main four types of leukemia, quantified at gene expression. Subsequently, in order to find a set of differentially expressed genes with the highest discernment capability among different types of leukemia, an innovative parameter referred to as coverage is presented here. This parameter allows assessing the number of different pathologies that a certain gen is able to discern. It has been evaluated together with other widely known parameters under assessment of an ANOVA statistical test which corroborated its filtering power when the identified genes are subjected to a machine learning process at multiclass level. The optimal tuning of gene extraction evaluated parameters by means of this statistical test led to the selection of 42 highly relevant expressed genes. By the use of minimum-Redundancy Maximum-Relevance (mRMR) feature selection algorithm, these genes were reordered and assessed under the operation of four different classification techniques. Outstanding results were achieved by taking exclusively the first ten genes of the ranking into consideration. Finally, specific literature was consulted on this last subset of genes, revealing the occurrence of practically all of them with biological processes related to leukemia. At sight of these results, this study underlines the relevance of considering a new parameter which facilitates the identification of highly valid expressed genes for simultaneously discerning multiple types of leukemia.

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Proteomic biomarkers in body fluids associated with pancreatic cancer.

Pancreatic cancer (PC) is a highly malignant disease that represents the fourth leading cancer-related death worldwide. There has been very little improvement in survival rates over recent years, and surgical resection remains the only reliable curative approach. Factors that contribute to this dismal prognosis for PC include its rapid progression and invasion, the absence of specific symptoms, and the little impact of available chemotherapy. Importantly, the management of this malignancy is also limited by the lack of highly specific and sensitive biomarkers for its diagnosis and follow-up, and their identification is therefore considered a promising strategy to improve outcomes in these patients. Numerous translational studies have explored the usefulness of body fluids as a non-invasive source of PC-specific biomarkers, and innovations in proteomic methods and technologies have provided a myriad of protein biomarkers for different cancers. The adoption of a proteomic approach has improved understanding of the biology of PC and contributed to the potential identification of protein biomarkers for this disease. This review considers the most recent research efforts to develop novel proteomic biomarkers in body fluids for PC.

Untargeted LC-HRMS-Based Metabolomics for Searching New Biomarkers of Pancreatic Ductal Adenocarcinoma: A Pilot Study.

Pancreatic ductal adenocarcinoma is one of the most lethal tumors since it is usually detected at an advanced stage in which surgery and/or current chemotherapy have limited efficacy. The lack of sensitive and specific markers for diagnosis leads to a dismal prognosis. The purpose of this study is to identify metabolites in serum of pancreatic ductal adenocarcinoma patients that could be used as diagnostic biomarkers of this pathology. We used liquid chromatography-high-resolution mass spectrometry for a nontargeted metabolomics approach with serum samples from 28 individuals, including 16 patients with pancreatic ductal adenocarcinoma and 12 healthy controls. Multivariate statistical analysis, which included principal component analysis and partial least squares, revealed clear separation between the patient and control groups analyzed by liquid chromatography-high-resolution mass spectrometry using a nontargeted metabolomics approach. The metabolic analysis showed significantly lower levels of phospholipids in the serum from patients with pancreatic ductal adenocarcinoma compared with serum from controls. Our results suggest that the liquid chromatography-high-resolution mass spectrometry-based metabolomics approach provides a potent and promising tool for the diagnosis of pancreatic ductal adenocarcinoma patients using the specific metabolites identified as novel biomarkers that could be used for an earlier detection and treatment of these patients.