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Pancreatic ductal adenocarcinoma (PDAC) has one of the highest mortality rates among all cancer types. Its delayed diagnosis precludes curative resection, thus most of the current therapies against PDAC are based on chemo- and radiotherapy. Unfortunately, these strategies are insufficient to improve its poor prognosis. Despite the advances made in chemotherapy (e.g. nab-paclitaxel and gemcitabine), many patients with PDAC are unable to benefit from them due to the rapid development of drug resistance. Currently, more than 165 genes have been found to be implicated in drug resistance of pancreatic tumors, including different integrins, mucins, NF-κB, RAS and CXCR4. Moreover, drug resistance in PDAC is thought to be mediated by the modulation of miRNAs (e.g. miRNA-21, miRNA-145 and miRNA-155), which regulate genes that participate in cell proliferation, invasion and metastasis. Finally, cancer stem cells are intimately related to drug resistance in PDAC due to their ability to overexpress ABC genes -involved in drug transport-, and enzymes such as aldehyde dehydrogenases -implicated in cellular drug metabolism- and poly (ADP-ribose) polymerases -involved in drug-induced DNA damage repair. Understanding the mechanisms involved in drug resistance will contribute to the development of efficient therapeutic strategies and to improve the prognosis of patients with PDAC.

Aims: To analyze the clinical relevance of O6-methylguanine-DNA methyltransferase in rectal adenocarcinoma treated with chemoradiotherapy followed by surgery. Methods: Tissue samples from 29 rectal adenocarcinoma patients were obtained after chemoradiotherapy. O6-methylguanine-DNA methyltransferase promoter methylation status was established by methylation-specific polymerase chain reaction. O6-methylguanine-DNA methyltransferase protein levels were determined by immunohistochemistry. Clinicopathologic variables, including treatment regression grade, recurrence, lymph node invasion, and stage and differentiation grade of the tumor, were determined. Results: The O6-methylguanine-DNA methyltransferase gene promoter was methylated in 81.5% of samples. Most patients (88.9%) showed low O6-methylguanine-DNA methyltransferase protein expression. O6-methylguanine-DNA methyltransferase methylation status was not correlated with any of the clinicopathological variables determined in rectal adenocarcinomas selected for chemoradiotherapy. Conclusion: O6-methylguanine-DNA methyltransferase methylation status is not correlated with clinicopathologic variables examined in rectal adenocarcinoma selected for chemoradiotherapy, although its role as a biomarker awaits further investigation.

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.

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.

Abstract The COVID-19 pandemic remains a significant global health threat, with uncertainties persisting regarding the factors determining whether individuals experience mild symptoms, severe conditions, or succumb to the disease. This study presents an NMR metabolomics-based approach, analysing 80 serum and urine samples from COVID-19 patients (34 intensive care patients and 46 hospitalized patients) and 32 from healthy controls. Our research identifies discriminant metabolites and clinical variables relevant to COVID-19 diagnosis and severity. These discriminant metabolites play a role in specific pathways, mainly “Phenylalanine, tyrosine and tryptophan biosynthesis”, “Phenylalanine metabolism”, “Glycerolipid metabolism” and “Arginine and proline metabolism”. We propose a three-metabolite diagnostic panel—comprising isoleucine, TMAO, and glucose—that effectively discriminates COVID-19 patients from healthy individuals, achieving high efficiency. Furthermore, we found an optimal biomarker panel capable of efficiently classify disease severity considering both clinical characteristics (obesity/overweight, dyslipidemia, and lymphocyte count) together with metabolites content (ethanol, TMAO, tyrosine and betaine).

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with five-year survival rates around 10%. The only curative option remains complete surgical resection, but due to the delay in diagnosis, less than 20% of patients are eligible for surgery. Therefore, discovering diagnostic biomarkers for early detection is crucial for improving clinical outcomes. Metabolomics has become a powerful technology for biomarker discovery, and several metabolomic-based panels have been proposed for PDAC diagnosis, but these advances have not yet been translated into the clinic. Therefore, this review focused on summarizing metabolites identified for the early diagnosis of PDAC in the last five years. Bibliographic searches were performed in the PubMed, Scopus and WOS databases, using the terms “Biomarkers, Tumor”, “Pancreatic Neoplasms”, “Early Diagnosis”, “Metabolomics” and “Lipidome” (January 2018–March 2023), and resulted in the selection of fourteen original studies that compared PDAC patients with subjects with other pancreatic diseases. These investigations showed amino acid and lipid metabolic pathways as the most commonly altered, reflecting their potential for biomarker research. Furthermore, other relevant metabolites such as glucose and lactate were detected in the pancreas tissue and body fluids from PDAC patients. Our results suggest that the use of metabolomics remains a robust approach to improve the early diagnosis of PDAC. However, these studies showed heterogeneity with respect to the metabolomics techniques used and further studies will be needed to validate the clinical utility of these biomarkers.

Human adipose-derived mesenchymal stem cells (hASCs) may be used in some nervous system pathologies, although obtaining an adequate degree of neuronal differentiation is an important barrier to their applicability. This requires a deep understanding of the expression and epigenetic changes of the most important genes involved in their differentiation. We used hASCs from human lipoaspirates to induce neuronal-like cells through three protocols (Neu1, 2, and 3), determined the degree of neuronal differentiation using specific biomarkers in culture cells and neurospheres, and analyzed epigenetic changes of genes involved in this differentiation. Furthermore, we selected the Hoxa-5 gene to determine its potential to improve neuronal differentiation. Our results showed that an excellent hASC neuronal differentiation process using Neu1 which efficiently modulated NES, CHAT, SNAP25, or SCN9A neuronal marker expression. In addition, epigenetic studies showed relevant changes in Hoxa-5, GRM4, FGFR1, RTEL1, METRN, and PAX9 genes. Functional studies of the Hoxa-5 gene using CRISPR/dCas9 and lentiviral systems showed that its overexpression induced hASCs neuronal differentiation that was accelerated with the exposure to Neu1. These results suggest that Hoxa-5 is an essential gene in hASCs neuronal differentiation and therefore, a potential candidate for the development of cell therapy strategies in neurological disorders.

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.

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.