Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach.

Despite the recent and increasing knowledge surrounding COVID-19 infection, the underlying mechanisms of the persistence of symptoms for a long time after the acute infection are still not completely understood. Here, a multiplatform mass spectrometry-based approach was used for metabolomic and lipidomic profiling of human plasma samples from Long COVID patients (n = 40) to reveal mitochondrial dysfunction when compared with individuals fully recovered from acute mild COVID-19 (n = 40). Untargeted metabolomic analysis using CE-ESI(+/-)-TOF-MS and GC-Q-MS was performed. Additionally, a lipidomic analysis using LC-ESI(+/-)-QTOF-MS based on an in-house library revealed 447 lipid species identified with a high confidence annotation level. The integration of complementary analytical platforms has allowed a comprehensive metabolic and lipidomic characterization of plasma alterations in Long COVID disease that found 46 relevant metabolites which allowed to discriminate between Long COVID and fully recovered patients. We report specific metabolites altered in Long COVID, mainly related to a decrease in the amino acid metabolism and ceramide plasma levels and an increase in the tricarboxylic acid (TCA) cycle, reinforcing the evidence of an impaired mitochondrial function. The most relevant alterations shown in this study will help to better understand the insights of Long COVID syndrome by providing a deeper knowledge of the metabolomic basis of the pathology.

Metabolic changes contribute to maladaptive right ventricular hypertrophy in pulmonary hypertension beyond pressure overload: an integrative imaging and omics investigation.

Right ventricular (RV) failure remains the strongest determinant of survival in pulmonary hypertension (PH). We aimed to identify relevant mechanisms, beyond pressure overload, associated with maladaptive RV hypertrophy in PH. To separate the effect of pressure overload from other potential mechanisms, we developed in pigs two experimental models of PH (M1, by pulmonary vein banding and M2, by aorto-pulmonary shunting) and compared them with a model of pure pressure overload (M3, pulmonary artery banding) and a sham-operated group. Animals were assessed at 1 and 8 months by right heart catheterization, cardiac magnetic resonance and blood sampling, and myocardial tissue was analyzed. Plasma unbiased proteomic and metabolomic data were compared among groups and integrated by an interaction network analysis. A total of 33 pigs completed follow-up (M1, n = 8; M2, n = 6; M3, n = 10; and M0, n = 9). M1 and M2 animals developed PH and reduced RV systolic function, whereas animals in M3 showed increased RV systolic pressure but maintained normal function. Significant plasma arginine and histidine deficiency and complement system activation were observed in both PH models (M1&M2), with additional alterations to taurine and purine pathways in M2. Changes in lipid metabolism were very remarkable, particularly the elevation of free fatty acids in M2. In the integrative analysis, arginine-histidine-purines deficiency, complement activation, and fatty acid accumulation were significantly associated with maladaptive RV hypertrophy. Our study integrating imaging and omics in large-animal experimental models demonstrates that, beyond pressure overload, metabolic alterations play a relevant role in RV dysfunction in PH.

The impact of high-IgE levels on metabolome and microbiome in experimental allergic enteritis.

BACKGROUND: The pathological mechanism of the gastrointestinal forms of food allergies is less understood in comparison to other clinical phenotypes, such as asthma and anaphylaxis Importantly, high-IgE levels are a poor prognostic factor in gastrointestinal allergies. METHODS: This study investigated how high-IgE levels influence the development of intestinal inflammation and the metabolome in allergic enteritis (AE), using IgE knock-in (IgEki) mice expressing high levels of IgE. In addition, correlation of the altered metabolome with gut microbiome was analysed. RESULTS: Ovalbumin-sensitized and egg-white diet-fed (OVA/EW) BALB/c WT mice developed moderate AE, whereas OVA/EW IgEki mice induced more aggravated intestinal inflammation with enhanced eosinophil accumulation. Untargeted metabolomics detected the increased levels of N-tau-methylhistamine and 2,3-butanediol, and reduced levels of butyric acid in faeces and/or sera of OVA/EW IgEki mice, which was accompanied with reduced Clostridium and increased Lactobacillus at the genus level. Non-sensitized and egg-white diet-fed (NC/EW) WT mice did not exhibit any signs of AE, whereas NC/EW IgEki mice developed marginal degrees of AE. Compared to NC/EW WT mice, enhanced levels of lysophospholipids, sphinganine and sphingosine were detected in serum and faecal samples of NC/EW IgEki mice. In addition, several associations of altered metabolome with gut microbiome-for example Akkermansia with lysophosphatidylserine-were detected. CONCLUSIONS: Our results suggest that high-IgE levels alter intestinal and systemic levels of endogenous and microbiota-associated metabolites in experimental AE. This study contributes to deepening the knowledge of molecular mechanisms for the development of AE and provides clues to advance diagnostic and therapeutic strategies of allergic diseases.

Allergic inflammation triggers dyslipidemia via IgG signalling.

BACKGROUND: Allergic diseases begin early in life and are often chronic, thus creating an inflammatory environment that may precede or exacerbate other pathologies. In this regard, allergy has been associated to metabolic disorders and with a higher risk of cardiovascular disease, but the underlying mechanisms remain incompletely understood. METHODS: We used a murine model of allergy and atherosclerosis, different diets and sensitization methods, and cell-depleting strategies to ascertain the contribution of acute and late phase inflammation to dyslipidemia. Untargeted lipidomic analyses were applied to define the lipid fingerprint of allergic inflammation at different phases of allergic pathology. Expression of genes related to lipid metabolism was assessed in liver and adipose tissue at different times post-allergen challenge. Also, changes in serum triglycerides (TGs) were evaluated in a group of 59 patients ≥14 days after the onset of an allergic reaction. RESULTS: We found that allergic inflammation induces a unique lipid signature that is characterized by increased serum TGs and changes in the expression of genes related to lipid metabolism in liver and adipose tissue. Alterations in blood TGs following an allergic reaction are independent of T-cell-driven late phase inflammation. On the contrary, the IgG-mediated alternative pathway of anaphylaxis is sufficient to induce a TG increase and a unique lipid profile. Lastly, we demonstrated an increase in serum TGs in 59 patients after undergoing an allergic reaction. CONCLUSION: Overall, this study reveals that IgG-mediated allergic inflammation regulates lipid metabolism.

Addressing the untargeted lipidomics challenge in urine samples: Comparative study of extraction methods by UHPLC-ESI-QTOF-MS.

Urine analysis has remained a fundamental and widely used method in clinical diagnostics for over a century. With its minimal invasive nature and comprehensive range of analytes, urine has established itself as a clinical diagnostic tool for various disorders, including renal, urological, metabolic, and endocrine diseases. Furthermore, urine's unique attributes make it an attractive matrix for biomarker discovery, as well as in assessing the metabolic and physiological states of patients and healthy individuals alike. However, limitations in our knowledge of average values and sources of urinary lipids decrease the wider clinical application of urinary lipidomics. In this context, untargeted lipidomics analysis relies heavily on the extraction and analysis of lipids in biological samples. Nevertheless, this type of analysis presents challenges in lipid identification due to the diverse nature of lipids. Therefore, proper sample treatment before analysis is crucial to obtain robust and reproducible lipidomic profiles. To address this gap, we conducted a comparative study of a urine pool sample collected from twenty healthy volunteers using four different lipid extraction methods: one biphasic and three monophasic protocols. The extracted lipids were then analyzed using UHPLC-MS and MS/MS, and the semi-quantification of all the accurately annotated lipid species was performed for each extraction method.

Metabolomics for searching validated biomarkers in cancer studies: a decade in review.

INTRODUCTION: In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways. AREAS COVERED: This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types. EXPERT OPINION: Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

Exploring sample treatment strategies for untargeted metabolomics: A comparative study of solid phase microextraction (SPME) and homogenization with solid-liquid extraction (SLE) in renal tissue.

BACKGROUND: The selection of the sample treatment strategy is a crucial step in the metabolomics workflow. Solid phase microextraction (SPME) is a sample processing methodology with great potential for use in untargeted metabolomics of tissue samples. However, its utilization is not as widespread as other standard protocols involving steps of tissue collection, metabolism quenching, homogenization, and extraction of metabolites by solvents. Since SPME allows us to perform all these steps in one action in tissue samples, in addition to other advantages, it is necessary to know whether this methodology produces similar or comparable metabolome and lipidome coverage and performance to classical methods. RESULTS: SPME and homogenization with solid-liquid extraction (Homo-SLE) sample treatment methods were applied to healthy murine kidney tissue, followed by comprehensive metabolomics and lipidomics analyses. In addition, it has been tested whether freezing and storage of the tissue causes alterations in the renal metabolome and lipidome, so the analyses were performed on fresh and frozen tissue samples Lipidomics analysis revealed the exclusive presence of different structural membrane and intracellular lipids in the Homo-SLE group. Conversely, all annotated metabolites were detected in both groups. Notably, the freezing of the sample mainly causes a decrease in the levels of most lipid species and an increase in metabolites such as amino acids, purines, and pyrimidines. These alterations are principally detected in a statistically significant way by SPME methodology. Finally, the samples of both methodologies show a positive correlation in all the analyses. SIGNIFICANCE: These results demonstrate that in SPME processing, as long as the fundamentals of non-exhaustive extraction in a pre-equilibrium kinetic regime, extraction in a tissue localized area, the chemistry of the fiber coating and non-homogenization of the tissue are taken into account, is an excellent method to use in kidney tissue metabolomics; since this methodology presents an easy-to-use, efficient, and less invasive approach that simplifies the different sample processing steps.

Abaloparatide is more potent than teriparatide in restoring bone mass and strength in type 1 diabetic male mice.

This study investigated the efficacy of the two FDA-approved bone anabolic ligands of the parathyroid hormone receptor 1 (PTH1R), teriparatide or human parathyroid hormone 1-34 (PTH) and abaloparatide (ABL), to restoring skeletal health using a preclinical murine model of streptozotocin-induced T1-DM. Intermittent daily subcutaneous injections of equal molar doses (12 pmoles/g/day) of PTH (50 ng/g/day), ABL (47.5 ng/g/day), or vehicle, were administered for 28 days to 5-month-old C57Bl/6 J male mice with established T1-DM or control (C) mice. ABL was superior to PTH in increasing or restoring bone mass in control or T1-MD mice, respectively, which was associated with superior stimulation of trabecular and periosteal bone formation, upregulation of osteoclastic/osteoblastic gene expression, and increased circulating bone remodeling markers. Only ABL corrected the reduction in ultimate load, which is a measure of bone strength, induced by T1-DM, and it also increased energy to ultimate load. In addition, bones from T1-DM mice treated with PTH or ABL exhibited increased ultimate stress, a material index, compared to T1-DM mice administered with vehicle. And both PTH and ABL prevented the increased expression of the Wnt antagonist Sost/sclerostin displayed by T1-DM mice. Further, PTH and ABL increased to a similar extent the circulating bone resorption marker CTX and the bone formation marker P1NP in T1-DM after 2 weeks of treatment; however, only ABL sustained these increases after 4 weeks of treatment. We conclude that at equal molar doses, ABL is more effective than PTH in increasing bone mass and restoring the cortical and trabecular bone lost with T1-DM, due to higher and longer-lasting increases in bone remodeling.

Untargeted metabolomics analysis of serum and urine unveils the protective effect of cilastatin on altered metabolic pathways during cisplatin-induced acute kidney injury.

Acute kidney injury (AKI) is one of the most serious complications of cisplatin anticancer therapies. Cilastatin is a highly promising nephroprotective agent to eventually enter clinical use, but its biochemical mechanism is still not fully understood. We have employed an untargeted metabolomics approach based on capillary electrophoresis mass spectrometry (CE-MS) analysis of serum and urine from an in vivo rat model, to explore the metabolic pathways involved in cisplatin-induced AKI and cilastatin nephroprotection. A total of 155 and 76 identified metabolites were found to be significantly altered during cisplatin treatment in urine and serum, respectively. Most of these altered metabolites were either partially or totally recovered by cilastatin and cisplatin co-treatment. The main metabolic pathways disturbed by cisplatin during AKI involved diverse amino acids metabolism and biosynthesis, tricarboxylic acids (TCA) cycle, nicotinate and nicotinamide metabolism, among others. Cilastatin was proved to protect diverse cisplatin-altered pathways involving metabolites related to immunomodulation, inflammation, oxidative stress and amino acid metabolism in proximal tubules. However, cisplatin-altered mitochondrial metabolism (especially, the energy-producing TCA cycle) remained largely unprotected by cilastatin, suggesting an unresolved mitochondrial direct damage. Multivariate analysis allowed effective discrimination of cisplatin-induced AKI and cilastatin renoprotection based on metabolic features. A number of potential serum and urine biomarkers could also be foreseen for cisplatin-induced AKI detection and cilastatin nephroprotection.

LiLA: lipid lung-based ATLAS built through a comprehensive workflow designed for an accurate lipid annotation.

Accurate lipid annotation is crucial for understanding the role of lipids in health and disease and identifying therapeutic targets. However, annotating the wide variety of lipid species in biological samples remains challenging in untargeted lipidomic studies. In this work, we present a lipid annotation workflow based on LC-MS and MS/MS strategies, the combination of four bioinformatic tools, and a decision tree to support the accurate annotation and semi-quantification of the lipid species present in lung tissue from control mice. The proposed workflow allowed us to generate a lipid lung-based ATLAS (LiLA), which was then employed to unveil the lipidomic signatures of the Mycobacterium tuberculosis infection at two different time points for a deeper understanding of the disease progression. This workflow, combined with manual inspection strategies of MS/MS data, can enhance the annotation process for lipidomic studies and guide the generation of sample-specific lipidome maps. LiLA serves as a freely available data resource that can be employed in future studies to address lipidomic alterations in mice lung tissue.

Plasma metabolomic profile is near-normal in people with HIV on long-term suppressive antiretroviral therapy.

Background: Combination antiretroviral therapy (ART) has transformed human immunodeficiency virus (HIV) infection in people with HIV (PWH). However, a chronic state of immune activation and inflammation is maintained despite achieving HIV suppression and satisfactory immunological recovery. We aimed to determine whether the plasma metabolomic profile of PWH on long-term suppressive ART and immunologically recovered approximates the normality by comparison with healthy controls with similar age and gender. Methods: We carried out a cross-sectional study in 17 PWH on long-term ART (HIV-RNA <50 copies/mL, CD4+ ≥500 cells/mm3, and CD4+/CD8+ ≥1) and 19 healthy controls with similar age and gender. Metabolomics analysis was performed by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). The statistical association analysis was performed by principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and Generalized Linear Models (GLM) with a gamma distribution (log-link). Significance levels (p-value) were corrected for multiple testing (q-value). Results: PCA and PLS-DA analyses found no relevant differences between groups. Adjusted GLM showed 14 significant features (q-value<0.20), of which only three could be identified: lysophosphatidylcholine (LysoPC) (22:6) (q-value=0.148), lysophosphatidylethanolamine (LysoPE) (22:6) (q-value=0.050) and hydroperoxy-octadecatrienoic acid (HpOTrE)/dihydroperoxy-octadecatrienoic acid (DiHOTrE)/epoxy-octadecadienoic acid (EpODE) (q-value=0.136). These significant identified metabolites were directly correlated to plasma inflammatory biomarkers in PWH and negatively correlated in healthy controls. Conclusion: PWH on long-term ART have a metabolomic profile that is almost normal compared to healthy controls. Nevertheless, residual metabolic alterations linked to inflammatory biomarkers persist, which could favor the development of age-related comorbidities among this population.

Metabolomic insights in advanced cardiomyopathy of chronic chagasic and idiopathic patients that underwent heart transplant.

Heart failure (HF) studies typically focus on ischemic and idiopathic heart diseases. Chronic chagasic cardiomyopathy (CCC) is a progressive degenerative inflammatory condition highly prevalent in Latin America that leads to a disturbance of cardiac conduction system. Despite its clinical and epidemiological importance, CCC molecular pathogenesis is poorly understood. Here we characterize and discriminate the plasma metabolomic profile of 15 patients with advanced HF referred for heart transplantation - 8 patients with CCC and 7 with idiopathic dilated cardiomyopathy (IDC) - using gas chromatography/quadrupole time-of-flight mass spectrometry. Compared to the 12 heart donor individuals, also included to represent the control (CTRL) scenario, patients with advanced HF exhibited a metabolic imbalance with 21 discriminating metabolites, mostly indicative of accumulation of fatty acids, amino acids and important components of the tricarboxylic acid (TCA) cycle. CCC vs. IDC analyses revealed a metabolic disparity between conditions, with 12 CCC distinctive metabolites vs. 11 IDC representative metabolites. Disturbances were mainly related to amino acid metabolism profile. Although mitochondrial dysfunction and loss of metabolic flexibility may be a central mechanistic event in advanced HF, metabolic imbalance differs between CCC and IDC populations, possibly explaining the dissimilar clinical course of Chagas' patients.

Effects of pectin methyl-esterification on intestinal microbiota and its immunomodulatory properties in naive mice.

Pectins are dietary fibers that are attributed with several beneficial immunomodulatory effects. Depending on the degree of esterification (DE), pectins can be classified as high methoxyl pectin (HMP) or low methoxyl pectin (LMP). The aim of this study was to investigate the effects of pectin methyl-esterification on intestinal microbiota and its immunomodulatory properties in naive mice. Supplementation of the diet with LMP or HMP induced changes in the composition of the intestinal microbiota in mice toward Bacteroides, which was mainly promoted by HMP. Metabolome analysis of stool samples from pectin-fed mice showed a different effect of the two types of pectin on the levels of short-chain fatty acids and bile acids, which was consistent with highly efficient in vivo fermentation of LMP. Analysis of serum antibody levels showed a significant increase in IgG and IgA levels by both pectins, while FACS analysis revealed a decrease of infiltrating inflammatory cells in the intestinal lamina propria by HMP. Our study revealed that the structural properties of the investigated pectins determine fermentability, effects on microbial composition, metabolite production, and modulation of immune responses. Consumption of HMP preferentially altered the gut microbiota and suppressed pro-inflammatory immune responses, suggesting a beneficial role in inflammatory diseases.

Comparative characterization of the infant gut microbiome and their maternal lineage by a multi-omics approach.

The human gut microbiome establishes and matures during infancy, and dysregulation at this stage may lead to pathologies later in life. We conducted a multi-omics study comprising three generations of family members to investigate the early development of the gut microbiota. Fecal samples from 200 individuals, including infants (0-12 months old; 55% females, 45% males) and their respective mothers and grandmothers, were analyzed using two independent metabolomics platforms and metagenomics. For metabolomics, gas chromatography and capillary electrophoresis coupled to mass spectrometry were applied. For metagenomics, both 16S rRNA gene and shotgun sequencing were performed. Here we show that infants greatly vary from their elders in fecal microbiota populations, function, and metabolome. Infants have a less diverse microbiota than adults and present differences in several metabolite classes, such as short- and branched-chain fatty acids, which are associated with shifts in bacterial populations. These findings provide innovative biochemical insights into the shaping of the gut microbiome within the same generational line that could be beneficial in improving childhood health outcomes.

GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review.

Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.

Identifying subgroups of childhood obesity by using multiplatform metabotyping.

Introduction: Obesity results from an interplay between genetic predisposition and environmental factors such as diet, physical activity, culture, and socioeconomic status. Personalized treatments for obesity would be optimal, thus necessitating the identification of individual characteristics to improve the effectiveness of therapies. For example, genetic impairment of the leptin-melanocortin pathway can result in rare cases of severe early-onset obesity. Metabolomics has the potential to distinguish between a healthy and obese status; however, differentiating subsets of individuals within the obesity spectrum remains challenging. Factor analysis can integrate patient features from diverse sources, allowing an accurate subclassification of individuals. Methods: This study presents a workflow to identify metabotypes, particularly when routine clinical studies fail in patient categorization. 110 children with obesity (BMI > +2 SDS) genotyped for nine genes involved in the leptin-melanocortin pathway (CPE, MC3R, MC4R, MRAP2, NCOA1, PCSK1, POMC, SH2B1, and SIM1) and two glutamate receptor genes (GRM7 and GRIK1) were studied; 55 harboring heterozygous rare sequence variants and 55 with no variants. Anthropometric and routine clinical laboratory data were collected, and serum samples processed for untargeted metabolomic analysis using GC-q-MS and CE-TOF-MS and reversed-phase U(H)PLC-QTOF-MS/MS in positive and negative ionization modes. Following signal processing and multialignment, multivariate and univariate statistical analyses were applied to evaluate the genetic trait association with metabolomics data and clinical and routine laboratory features. Results and Discussion: Neither the presence of a heterozygous rare sequence variant nor clinical/routine laboratory features determined subgroups in the metabolomics data. To identify metabolomic subtypes, we applied Factor Analysis, by constructing a composite matrix from the five analytical platforms. Six factors were discovered and three different metabotypes. Subtle but neat differences in the circulating lipids, as well as in insulin sensitivity could be established, which opens the possibility to personalize the treatment according to the patients categorization into such obesity subtypes. Metabotyping in clinical contexts poses challenges due to the influence of various uncontrolled variables on metabolic phenotypes. However, this strategy reveals the potential to identify subsets of patients with similar clinical diagnoses but different metabolic conditions. This approach underscores the broader applicability of Factor Analysis in metabotyping across diverse clinical scenarios.

Exploration of oxidized phosphocholine profile in non-small-cell lung cancer.

Introduction: Lung cancer is one of the most frequently studied types of cancer and represents the most common and lethal neoplasm. Our previous research on non-small cell lung cancer (NSCLC) has revealed deep lipid profile reprogramming and redox status disruption in cancer patients. Lung cell membranes are rich in phospholipids that are susceptible to oxidation, leading to the formation of bioactive oxidized phosphatidylcholines (oxPCs). Persistent and elevated levels of oxPCs have been shown to induce chronic inflammation, leading to detrimental effects. However, recent reports suggest that certain oxPCs possess anti-inflammatory, pro-survival, and endothelial barrier-protective properties. Thus, we aimed to measure the levels of oxPCs in NSCLC patients and investigate their potential role in lung cancer. Methods: To explore the oxPCs profiles in lung cancer, we performed in-depth, multi-level metabolomic analyses of nearly 350 plasma and lung tissue samples from 200 patients with NSCLC, including adenocarcinoma (ADC) and squamous cell carcinoma (SCC), the two most prevalent NSCLC subtypes and COPD patients as a control group. First, we performed oxPC profiling of plasma samples. Second, we analyzed tumor and non-cancerous lung tissues collected during the surgical removal of NSCLC tumors. Because of tumor tissue heterogeneity, subsequent analyses covered the surrounding healthy tissue and peripheral and central tumors. To assess whether the observed phenotypic changes in the patients were associated with measured oxPC levels, metabolomics data were augmented with data from medical records. Results: We observed a predominance of long-chain oxPCs in plasma samples and of short-chain oxPCs in tissue samples from patients with NSCLC. The highest concentration of oxPCs was observed in the central tumor region. ADC patients showed higher levels of oxPCs compared to the control group, than patients with SCC. Conclusion: The detrimental effects associated with the accumulation of short-chain oxPCs suggest that these molecules may have greater therapeutic utility than diagnostic value, especially given that elevated oxPC levels are a hallmark of multiple types of cancer.