Plasma Metabolome Profiling Identifies Metabolic Subtypes of Pancreatic Ductal Adenocarcinoma

Intestinal mycobiota dysbiosis associated inflammation activation in chronic schizophrenia

The microbiome-gut-brain axis is related to schizophrenia (SCZ). The role of intestinal mycobiota in SCZ has been under investigated. We present a half-year follow-up study involving 109 chronic SCZ patients and 77 healthy controls. Intestinal mycobiota was tested by internal transcribed spacer (ITS). Untargeted liquid chromatography-mass spectrometry (LC-MS) was used to measure fecal metabolites. Symptom severity was assessed using the Positive and Negative Syndrome Scale. Enterotype analysis showed that Candida-type patients exhibited severer positive symptoms and depression factors than Saccharomyces-type patients. Candida and its top species and operational taxonomic units (OTUs) were positively correlated with depression factors (all p=0.001). Fecal metabolites analysis showed that upregulated metabolites were associated with chronic inflammation (NF-κB pathway and T helper cell differentiation), downregulated metabolites were associated with glutamate metabolism, serotonergic and dopaminergic synapse. Procrustes analysis revealed significant correlation between intestinal mycobiota and fecal metabolites (M2=0.937, p<0.001). Metabolic module analysis showed that the top module, MEturquoise (associated with Th1 and Th2 cell differentiation), was negatively correlated with SCZ (r=-0.783, p<0.0001), positively correlated with Candida, Aspergillus, Trichosporon and Talaromyces (decreased in SCZ) and negatively correlated with Saccharomyces (increased in SCZ). We also found impairments of intestinal barrier in SCZ, characterized by increased in blood D-lactate (mucosa impairment marker) and decreased in blood mucin 2 (mucosal barrier protective protein). Serum levels of TNF-α was increased and showed stable high levels during treatment. This study suggests that mycobiota dysbiosis-related chronic inflammation and an impaired intestinal mucosal barrier are associated with chronic SCZ.

Understanding the Conundrum of Pancreatic Cancer in the Omics Sciences Era

Pancreatic cancer (PC) is an increasing cause of cancer-related death, with a dismal prognosis caused by its aggressive biology, the lack of clinical symptoms in the early phases of the disease, and the inefficacy of treatments. PC is characterized by a complex tumor microenvironment. The interaction of its cellular components plays a crucial role in tumor development and progression, contributing to the alteration of metabolism and cellular hyperproliferation, as well as to metastatic evolution and abnormal tumor-associated immunity. Furthermore, in response to intrinsic oncogenic alterations and the influence of the tumor microenvironment, cancer cells undergo a complex oncogene-directed metabolic reprogramming that includes changes in glucose utilization, lipid and amino acid metabolism, redox balance, and activation of recycling and scavenging pathways. The advent of omics sciences is revolutionizing the comprehension of the pathogenetic conundrum of pancreatic carcinogenesis. In particular, metabolomics and genomics has led to a more precise classification of PC into subtypes that show different biological behaviors and responses to treatments. The identification of molecular targets through the pharmacogenomic approach may help to personalize treatments. Novel specific biomarkers have been discovered using proteomics and metabolomics analyses. Radiomics allows for an earlier diagnosis through the computational analysis of imaging. However, the complexity, high expertise required, and costs of the omics approach are the main limitations for its use in clinical practice at present. In addition, the studies of extracellular vesicles (EVs), the use of organoids, the understanding of host-microbiota interactions, and more recently the advent of artificial intelligence are helping to make further steps towards precision and personalized medicine. This present review summarizes the main evidence for the application of omics sciences to the study of PC and the identification of future perspectives.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Evaluating Metabolite-Based Biomarkers for Early Diagnosis of Pancreatic Cancer: A Systematic Review

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.

Plasma Metabolomics Predicts Chemotherapy Response in Advanced Pancreatic Cancer

Pancreatic cancer (PC) is one of the deadliest cancers. Developing biomarkers for chemotherapeutic response prediction is crucial for improving the dismal prognosis of advanced-PC patients (pts). To evaluate the potential of plasma metabolites as predictors of the response to chemotherapy for PC patients, we analyzed plasma metabolites using high-performance liquid chromatography-mass spectrometry from 31 cachectic, advanced-PC subjects enrolled into the PANCAX-1 (NCT02400398) prospective trial to receive a jejunal tube peptide-based diet for 12 weeks and who were planned for palliative chemotherapy. Overall, there were statistically significant differences in the levels of intermediates of multiple metabolic pathways in pts with a partial response (PR)/stable disease (SD) vs. progressive disease (PD) to chemotherapy. When stratified by the chemotherapy regimen, PD after 5-fluorouracil-based chemotherapy (e.g., FOLFIRINOX) was associated with decreased levels of amino acids (AAs). For gemcitabine-based chemotherapy (e.g., gemcitabine/nab-paclitaxel), PD was associated with increased levels of intermediates of glycolysis, the TCA cycle, nucleoside synthesis, and bile acid metabolism. These results demonstrate the feasibility of plasma metabolomics in a prospective cohort of advanced-PC patients for assessing the effect of enteral feeding as their primary source of nutrition. Metabolic signatures unique to FOLFIRINOX or gemcitabine/nab-paclitaxel may be predictive of a patient's response and warrant further study.

Comprehensive characterization of complex glycosphingolipids in human pancreatic cancer tissues

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common causes of cancer-related deaths worldwide, accounting for 90% of primary pancreatic tumors with an average 5-year survival rate of less than 10%. PDAC exhibits aggressive biology, which, together with late detection, results in most PDAC patients presenting with unresectable, locally advanced, or metastatic disease. In-depth lipid profiling and screening of potential biomarkers currently appear to be a promising approach for early detection of PDAC or other cancers. Here, we isolated and characterized complex glycosphingolipids (GSL) from normal and tumor pancreatic tissues of patients with PDAC using a combination of TLC, chemical staining, carbohydrate-recognized ligand-binding assay, and LC/ESI-MS². The major neutral GSL identified were GSL with the terminal blood groups A, B, H, Le^a, Le^b, Le^x, Le^y, P1, and PX2 determinants together with globo- (Gb₃ and Gb₄) and neolacto-series GSL (nLc₄ and nLc₆). We also revealed that the neutral GSL profiles and their relative amounts differ between normal and tumor tissues. Additionally, the normal and tumor pancreatic tissues differ in type 1/2 core chains. Sulfatides and GM₃ gangliosides were the predominant acidic GSL along with the minor sialyl-nLc₄/nLc₆ and sialyl-Le^a/Le^x. The comprehensive analysis of GSL in human PDAC tissues extends the GSL coverage and provides an important platform for further studies of GSL alterations; therefore, it could contribute to the development of new biomarkers and therapeutic approaches.

Metabolomic analyses redefine the biological classification of pancreatic cancer and correlate with clinical outcomes

Pancreatic ductal adenocarcinoma (PDAC) is characterized by high heterogeneity, and the postoperative prognosis of different patients often varies greatly. Therefore, the classification of pancreatic cancer patients and precise treatment becomes particularly important. In our study, 1 H NMR spectroscopy was used to analyze the 76 PDAC serum samples and identify the potential metabolic subtypes. The metabolic characteristics of each metabolic subtype were screened out and the relationship between metabolic subtype and the long-term prognosis was further identified. The clinical stages of PDAC did not show the metabolic differences at the serum metabolomic level. And three metabolic subtypes, basic, choline-like and amino acid-enriched types, were defined by the hierarchical cluster analysis of the serum metabolites and the disturbed metabolic pathways. The characteristic metabolites of each PDAC subtype were identified, and the metabolite model was established to distinguish the PDAC patients in the different subtypes. Among the three metabolic subtypes, choline-like type displayed better long-term prognosis compared to the other two types of patients. Metabolic subtypes are of clinical importance and are closer to expressing the heterogeneity in the actual life activities of pancreatic cancer than molecular typing. The excavation of metabolic subtypes based on this will be more in line with clinical reality and more promising to guide clinical precision individualization treatment.

High-fat diet aggravates prenatal low-dose DEHP exposure induced spermatogenesis disorder: Characterization of testicular metabolic patterns in mouse offspring

Di-(2-ethylhexyl) phthalate (DEHP) is a widely used plasticizer and has been identified as a male prenatal reproductive toxicant. A high fat diet (HFD) has also been suggested as another potential disruptor of male reproductive function. Despite this potential synergism between DEHP exposure and HFD, little is known about the concomitant effects of prenatal DEHP and a subsequent HFD exposure on male offspring reproductive injury. Here we established a mouse model of prenatal exposure to DEHP (0.2 mg/kg/day) to assess the testicular development and spermatogenesis in offspring subjected to obesogenic diet during the pubertal period. Gross phenotype, hormone profiles and the testicular metabolome were analyzed to determine the underlying mechanism. We found that prenatal exposure to low-dose DEHP resulted in decreased sperm density, decreased testosterone (T) levels, increased luteinizing hormone (LH) levels and testicular germ cell apoptosis. Furthermore, these injury phenotypes were aggravated by pubertal HFD treatment. Testicular riboflavin and biotin metabolites were enriched implying their roles in contributing HFD to exacerbate offspring spermatogenesis disorders due to prenatal low-dose DEHP exposure. Our findings suggest that pubertal HFD exacerbates reproductive dysfunction associated with prenatal exposure to low-dose DEHP in male adult offspring.

Deconstructing Pancreatic Cancer Using Next Generation-Omic Technologies-From Discovery to Knowledge-Guided Platforms for Better Patient Management

Comprehensive molecular landscaping studies reveal a potentially brighter future for pancreatic ductal adenocarcinoma (PDAC) patients. Blood-borne biomarkers obtained from minimally invasive "liquid biopsies" are now being trialled for early disease detection and to track responses to therapy. Integrated genomic and transcriptomic studies using resectable tumour material have defined intrinsic patient subtypes and actionable genomic segments that promise a shift towards genome-guided patient management. Multimodal mapping of PDAC using spatially resolved single cell transcriptomics and imaging techniques has identified new potentially therapeutically actionable cellular targets and is providing new insights into PDAC tumour heterogeneity. Despite these rapid advances, defining biomarkers for patient selection remain limited. This review examines the current PDAC cancer biomarker ecosystem (identified in tumour and blood) and explores how advances in single cell sequencing and spatially resolved imaging modalities are being used to uncover new targets for therapeutic intervention and are transforming our understanding of this difficult to treat disease.

Defining Blood Plasma and Serum Metabolome by GC-MS

Metabolomics uses advanced analytical chemistry methods to analyze metabolites in biological samples. The most intensively studied samples are blood and its liquid components: plasma and serum. Armed with advanced equipment and progressive software solutions, the scientific community has shown that small molecules’ roles in living systems are not limited to traditional “building blocks” or “just fuel” for cellular energy. As a result, the conclusions based on studying the metabolome are finding practical reflection in molecular medicine and a better understanding of fundamental biochemical processes in living systems. This review is not a detailed protocol of metabolomic analysis. However, it should support the reader with information about the achievements in the whole process of metabolic exploration of human plasma and serum using mass spectrometry combined with gas chromatography.