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1.
Sci Immunol ; 9(95): eadn0126, 2024 May 10.
Article in English | MEDLINE | ID: mdl-38728413

ABSTRACT

MR1T cells are a recently found class of T cells that recognize antigens presented by the major histocompatibility complex-I-related molecule MR1 in the absence of microbial infection. The nature of the self-antigens that stimulate MR1T cells remains unclear, hampering our understanding of their physiological role and therapeutic potential. By combining genetic, pharmacological, and biochemical approaches, we found that carbonyl stress and changes in nucleobase metabolism in target cells promote MR1T cell activation. Stimulatory compounds formed by carbonyl adducts of nucleobases were detected within MR1 molecules produced by tumor cells, and their abundance and antigenicity were enhanced by drugs that induce carbonyl accumulation. Our data reveal carbonyl-nucleobase adducts as MR1T cell antigens. Recognizing cells under carbonyl stress allows MR1T cells to monitor cellular metabolic changes with physiological and therapeutic implications.


Subject(s)
Histocompatibility Antigens Class I , Histocompatibility Antigens Class I/immunology , Histocompatibility Antigens Class I/metabolism , Humans , Minor Histocompatibility Antigens/metabolism , Minor Histocompatibility Antigens/immunology , Animals , Lymphocyte Activation/immunology , Mice , T-Lymphocytes/immunology
2.
Cancer Immunol Immunother ; 73(4): 63, 2024 Mar 02.
Article in English | MEDLINE | ID: mdl-38430255

ABSTRACT

Tumor-associated macrophages (TAMs) are key components of the tumor microenvironment (TME). In colorectal liver metastasis (CLM), TAM morphology correlates with prognosis, with smaller TAMs (S-TAMs) conferring a more favorable prognosis than larger TAMs (L-TAMs). However, the metabolic profile of in vivo human TAM populations remains unknown. Multiparametric flow cytometry was used to freshly isolate S- and L-TAMs from surgically resected CLM patients (n = 14S-, 14L-TAMs). Mass spectrometry-based metabolomics analyses were implemented for the metabolic characterization of TAM populations. Gene expression analysis and protein activity were used to support the biochemical effects of the enzyme-substrate link between riboflavin and (lysine-specific demethylase 1A, LSD1) with TAM morphologies. L-TAMs were characterized by a positive correlation and a strong association between riboflavin and TAM morphologies. Riboflavin in both L-TAMs and in-vitro M2 polarized macrophages modulates LSD1 protein expression and activity. The inflammatory stimuli promoted by TNFα induced the increased expression of riboflavin transporter SLC52A3 and LSD1 in M2 macrophages. The modulation of the riboflavin-LSD1 axis represents a potential target for reprogramming TAM subtypes, paving the way for promising anti-tumor therapeutic strategies.


Subject(s)
Colorectal Neoplasms , Liver Neoplasms , Humans , Tumor-Associated Macrophages/metabolism , Macrophages/metabolism , Liver Neoplasms/pathology , Prognosis , Colorectal Neoplasms/pathology , Tumor Microenvironment , Membrane Transport Proteins/metabolism
3.
Front Immunol ; 14: 1193235, 2023.
Article in English | MEDLINE | ID: mdl-37503340

ABSTRACT

Tumor-associated macrophages (TAMs) represent one of the main tumor-infiltrating immune cell types and are generally categorized into either of two functionally contrasting subtypes, namely classical activated M1 macrophages and alternatively activated M2 macrophages. TAMs showed different activation states that can be represent by the two extremes of the complex profile of macrophages biology, the M1-like phenotype (pro-inflammatory activity) and the M2-like phenotype (anti-inflammatory activity). Based on the tumor type, and grades, TAMs can acquire different functions and properties; usually, the M1-like phenotype is typical of early tumor stages and is associated to an anti-tumor activity, while M2-like phenotype has a pro-inflammatory activity and is related to a poor patients' prognosis. The classification of macrophages into M1/M2 groups based on well-defined stimuli does not model the infinitely more complex tissue milieu where macrophages (potentially of different origin) would be exposed to multiple signals in different sequential order. This review aims to summarize the recent mass spectrometry-based (MS-based) metabolomics findings about the modifications of metabolism in TAMs polarization in different tumors. The published data shows that MS-based metabolomics is a promising tool to help better understanding TAMs metabolic phenotypes, although it is still poorly applied for TAMs metabolism. The knowledge of key metabolic alterations in TAMs is an essential step for discovering TAMs polarization novel biomarkers and developing novel therapeutic approaches targeting TAM metabolism to repolarize TAMs towards their anti-tumor phenotype.


Subject(s)
Neoplasms , Tumor-Associated Macrophages , Humans , Macrophages , Biomarkers/metabolism , Phenotype
4.
Eur Radiol ; 33(8): 5368-5377, 2023 Aug.
Article in English | MEDLINE | ID: mdl-36562783

ABSTRACT

OBJECTIVES: To investigate the normal-appearing white matter (NAWM) susceptibility in a cohort of newly diagnosed multiple sclerosis (MS) patients and to evaluate possible correlations between NAWM susceptibility and disability progression. METHODS: Fifty-nine patients with a diagnosis of MS (n = 53) or clinically isolated syndrome (CIS) (n = 6) were recruited and followed up. All participants underwent neurological examination, blood sampling for serum neurofilament light chain (sNfL) level assessment, lumbar puncture for the quantification of cerebrospinal fluid (CSF) ß-amyloid1-42 (Aß) levels, and brain MRI. T2-weighted scans were used to quantify white matter (WM) lesion loads. For each scan, we derived the NAWM volume fraction and the WM lesion volume fraction. Quantitative susceptibility mapping (QSM) of the NAWM was calculated using the susceptibility tensor imaging (STI) suite. Susceptibility maps were computed with the STAR algorithm. RESULTS: Primary progressive patients (n = 9) showed a higher mean susceptibility value in the NAWM than relapsing-remitting (n = 44) and CIS (n = 6) (p = 0.01 and p = 0.02). Patients with a higher susceptibility in the NAWM showed increased sNfL concentration (ρ = 0.38, p = 0.004) and lower CSF Aß levels (ρ = -0.34, p = 0.009). Mean NAWM susceptibility turned out to be a predictor of the expanded disability status scale (EDSS) worsening at follow-up (ß = 0.41, t = 2.66, p = 0.01) and of the MS severity scale (MSSS) (ß = 0.38, t = 2.43, p = 0.019). CONCLUSIONS: QSM in the NAWM seems to predict the EDSS increment over time. This finding might provide evidence on the role of QSM in identifying patients with an increased risk of early disability progression. KEY POINTS: • NAWM-QSM is higher in PPMS patients than in RRMS. • NAWM-QSM seems to be a predictor of EDSS worsening over time. • Patients with higher NAWM-QSM show increased sNfL concentration and lower CSF Aß levels.


Subject(s)
Demyelinating Diseases , Multiple Sclerosis, Relapsing-Remitting , Multiple Sclerosis , White Matter , Humans , Multiple Sclerosis/diagnostic imaging , Multiple Sclerosis/pathology , White Matter/diagnostic imaging , White Matter/pathology , Magnetic Resonance Imaging/methods , Neuroimaging , Brain/diagnostic imaging , Brain/pathology , Multiple Sclerosis, Relapsing-Remitting/pathology
5.
Metabolites ; 13(1)2022 Dec 21.
Article in English | MEDLINE | ID: mdl-36676938

ABSTRACT

Flow injection analysis coupled with high-resolution mass spectrometry (FIA-HRMS) is a fair trade-off between resolution and speed. However, free software available for data pre-processing is few, web-based, and often requires advanced user specialization. These tools rarely embedded blank and noise evaluation strategies, and direct feature annotation. We developed EASY-FIA, a free standalone application that can be employed for FIA-HRMS metabolomic data pre-processing by users with no bioinformatics/programming skills. We validated the tool's performance and applicability in two clinical metabolomics case studies. The main functions of our application are blank subtraction, alignment of the metabolites, and direct feature annotation by means of the Human Metabolome Database (HMDB) using a minimum number of mass spectrometry parameters. In a scenario where FIA-HRMS is increasingly recognized as a reliable strategy for fast metabolomics analysis, EASY-FIA could become a standardized and feasible tool easily usable by all scientists dealing with MS-based metabolomics. EASY-FIA was implemented in MATLAB with the App Designer tool and it is freely available for download.

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